The coexistence of terms to describe the presence of multiple concurrent diseases

Background: Consensus on terminology for multiple diseases is lacking. Because of the clinical relevance and social impact of multiple concurrent diseases, it is important that concepts are clear. Objective: To highlight the diversity of terms in the literature referring to the presence of multiple concurrent diseases/conditions and make recommendations. Design: A bibliometric analysis of English-language publications indexed in the MEDLINE database from 1970 to 2012 for the terms comorbidity, multimorbidity, polymorbidity, polypathology, pluripathology, multipathology, and multicondition, and a review of definitions of multimorbidity found in English-language publications indexed from 1970 to 2012 in the MEDLINE and SCOPUS databases. Results: Comorbidity was used in 67,557 publications, multimorbidity in 434, and the other terms in three to 31 publications. At least 144 publications used the term comorbidity without referring to an index disease. Thirteen general definitions of multimorbidity were identified, but only two were frequently used (91% of publications). The most frequently used definition (48% of publications) was “more than one or multiple chronic or long-term diseases/conditions”. Multimorbidity was not defined in 51% of the publications using the term. Conclusions: Comorbidity was overwhelmingly used to describe any clinical entity coexisting with an index disease under study. Multimorbidity was the term most frequently used when no index disease was designated. Several definitions of multimorbidity were found. However, most authors using the term did not define it. The use of clearly defined terms in the literature is recommended until a general consensus on the terminology of multiple coexistent diseases is reached.Journal of Comorbidity 2013;3(1):4–9 

Practice-oriented controversies and borrowed epistemic credibility in current evolutionary biology: phylogeography as a case study

Although there is increasing recognition that theory and practice in science are intimately intertwined, philosophy of science perspectives on scientific controversies have been historically focused on theory rather than practice. As a step in the construction of frameworks for understanding controversies linked to scientific practices, here we introduce the notion of borrowed epistemic credibility (BEC), to describe the situation in which scientists, in order to garner support for their own stances, exploit similarities between tenets in their own field and accepted statements or positions properly developed within other areas of expertise. We illustrate the scope of application of our proposal with the analysis of a heavily methods-grounded, recent controversy in phylogeography, a biological subdiscipline concerned with the study of the historical causes of biogeographical variation through population genetics- and phylogenetics-based computer analyses of diversity in DNA sequences, both within species and between closely related taxa. Toward this end, we briefly summarize the arguments proposed by selected authors representing each side of the controversy: the ‘nested clade analysis’ school versus the ‘statistical phylogeography’ orientation. We claim that whereas both phylogeographic ‘research styles’ borrow epistemic credibility from sources such as formal logic, the familiarity of results from other scientific areas, the authority of prominent scientists, or the presumed superiority of quantitative vs. verbal reasoning, ‘theory’ plays essentially no role as a foundation of the controversy. Besides underscoring the importance of strictly methodological and other non-theoretical aspects of controversies in current evolutionary biology, our analysis suggests a perspective with potential usefulness for the re-examination of more general philosophy of biology issues, such as the nature of historical inference, rationality, justification, and objectivity

Citation Analyses in Information Systems

Few scientists that specialize in information systems would recognize the name one of the field’s most cited authors, Ike Antkare. It is not that Antkare is from an obscure discipline. This aberration is the result of a vulnerability of citation analyses. A vulnerability proven with a computer program. Today, funding, promotion and tenure extension depend on the results of these analyses. This paper explores the nature of citation analyses in the information systems (IS) field and classifies them based on an adapted framework of Zupic and Cater (2015). The results illustrate two types of citation analyses. The first type contains ranking studies using measures of the h-family index calculated on citation networks. The second type involves co-citation analysis applying cluster or factor analysis to determine the intellectual structure, trajectory or maturity

Global Evolution of Research on Silvopastoral Systems through Bibliometric Analysis: Insights from Ecuador

Scientific studies on silvopastoral systems have led to permanent changes oriented toward better silvopasture practices, as well as to policy strategies to respond effectively to the global objectives of restoration and sustainable development. In this work, we performed a bibliometric analysis with the purpose of identifying changes associated with different silvopastoral systems. We applied Bibliometrix in R to analyze 5708 documents published between 1983 and 2022 by including the terms “silvopastoral” and “silvopasture”, among others. The results showed a longitudinal and exponential increase in silvopasture studies over the last 20 years. We adjusted the growth to an S-Curve function with an R2 of 96.06%. The interest of researchers regarding knowledge about silvopasture has evolved; initially, it focused on the characterization of silvopasture, whereas recently, it has focused on the search for strategies to improve the sustainable use of silvopasture, including ecosystem restoration and the implementation of better practices. The following countries stand out as those with the largest scientific production of studies on silvopasture: The United States, Brazil, Mexico, Colombia, and Argentina in the Americas; China and India in Asia; and Spain; and Germany, and the United Kingdom in Europe. In the case of Ecuador, cited leaders in silvopasture facilitated the construction of a group of experts who contribute to the development of public policies. The most cited publications appeared in journals published by the Springer group, Elsevier, and MDPI Journals, mostly in open-access systems. In the future, the disruptive contribution of open-access systems in the global dissemination of knowledge, breaking through the economic constraints of countries, universities, and researchers, should be evaluated

Close-range hyperspectral image analysis for the early detection of stress responses in individual plants in a high-throughput phenotyping platform

The potential of close-range hyperspectral imaging (HSI) as a tool for detecting early drought stress responses in plants grown in a high-throughput plant phenotyping platform (HTPPP) was explored. Reflectance spectra from leaves in close-range imaging are highly influenced by plant geometry and its specific alignment towards the imaging system. This induces high uninformative variability in the recorded signals, whereas the spectral signature informing on plant biological traits remains undisclosed. A linear reflectance model that describes the effect of the distance and orientation of each pixel of a plant with respect to the imaging system was applied. By solving this model for the linear coefficients, the spectra were corrected for the uninformative illumination effects. This approach, however, was constrained by the requirement of a reference spectrum, which was difficult to obtain. As an alternative, the standard normal variate (SNV) normalisation method was applied to reduce this uninformative variability. Once the envisioned illumination effects were eliminated, the remaining differences in plant spectra were assumed to be related to changes in plant traits. To distinguish the stress-related phenomena from regular growth dynamics, a spectral analysis procedure was developed based on clustering, a supervised band selection, and a direct calculation of a spectral similarity measure against a reference. To test the significance of the discrimination between healthy and stressed plants, a statistical test was conducted using a one-way analysis of variance (ANOVA) technique. The proposed analysis techniques was validated with HSI data of maize plants (Zea mays L.) acquired in a HTPPP for early detection of drought stress in maize plant. Results showed that the pre-processing of reflectance spectra with the SNV effectively reduces the variability due to the expected illumination effects. The proposed spectral analysis method on the normalized spectra successfully detected drought stress from the third day of drought induction, confirming the potential of HSI for drought stress detection studies and further supporting its adoption in HTPPP

An axiomatic approach to bibliometric rankings and indices

This paper analyzes several well-known bibliometric indices using an axiomatic approach. We concentrate on indices aiming at capturing the global impact of a scientific output and do not investigate indices aiming at capturing an average impact. Hence, the indices that we study are designed to evaluate authors or groups of authors but not journals. The bibliometric indices that are studied include classic ones such as the number of highly cited papers as well as more recent ones such as the h-index and the g-index. We give conditions that characterize these indices, up to the multiplication by a positive constant. We also study the bibliometric rankings that are induced by these indices. Hence, we provide a general framework for the comparison of bibliometric rankings and indices

The Impacts of Bibliometrics Measurement in the Scientific Community A Statistical Analysis of Multiple Case Studies

In recent years, statistical methods such as bibliometrics have increasingly intensified to analyse books, articles, and other publications. Bibliometric methods, as techniques to measure the information distribution models, are frequently used in the field of information science and social research. The main purpose of this article is to offer scholars a general framework for the comparison between positive and negative aspects of bibliometrics, on the methods and tools used. Therefore, both the strengths and the critical points will be highlighted, to obtain a complete and detailed overview of the entire argument. In the methodological part, a bibliometric analysis will be applied to various case studies, such as with the Generalized Error Distribution, analysing and commenting on the data, and using the Bibliometrix software. The results suggest that in the future there will be greater consolidation of bibliometrics, as the introduction of increasingly advanced technologies will create new tools and methods characterized by a high degree of automation and speed

Development of a Data-Driven Scientific Methodology : From Articles to Chemometric Data Products

Acknowledgements This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.Peer reviewedPostprin

ASA 2021 Statistics and Information Systems for Policy Evaluation

This book includes 25 peer-reviewed short papers submitted to the Scientific Opening Conference titled “Statistics and Information Systems for Policy Evaluation”, aimed at promoting new statistical methods and applications for the evaluation of policies and organized by the Association for Applied Statistics (ASA) and the Department of Statistics, Computer Science, Applications DiSIA “G. Parenti” of the University of Florence, jointly with the partners AICQ (Italian Association for Quality Culture), AICQ-CN (Italian Association for Quality Culture North and Centre of Italy), AISS (Italian Academy for Six Sigma), ASSIRM (Italian Association for Marketing, Social and Opinion Research), Comune di Firenze, the SIS – Italian Statistical Society, Regione Toscana and Valmon – Evaluation & Monitoring