1,721,103 research outputs found

    Deep Learning in Multiomics Sciences: Where We are, Emerging Topics, and Future Challenges

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    Multiomics is an emerging biological analysis approach in which the datasets come from multiple “omics”, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics. Nowadays, the convergence of Deep Learning and multiomics sciences presents an unprecedented opportunity to dissect the intricate interplay of biological processes. Specifically, multiomics data integration, propelled by Deep Learning methodologies, has revolutionised biological research, enabling a more holistic understanding of complex biological systems and disease mechanisms. This paper explores the current landscape of Deep Learning applications in multiomics, highlighting state-of-the-art techniques, emerging research areas, and the challenges that lie ahead. In particular, we delve into the application areas and computational methods that have been considered so far, offering guidance to researchers navigating this intricate field

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Electronic transitions in low dimensional semiconductor structures measured by surface photovoltage spectroscopy

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    Aim of the present contribution is to review several results obtained by the application of surface photovoltage spectroscopy method to low dimensional semiconductors. Photo-induced electronic transitions have been detected in: heterostructures based on III-nitrides, Si-based nanostructures (nanowires and nanocrystals) and nanoporous Ge layers. The effect of two-dimensional electron gas and of quantum confinement on the energy of band-to-band transitions in these structures has been studied. The results show that Surface Potovoltage Spectroscopy is a flexible and non-destructive method capable to reveal phase changes, Burstein Moss effects, doping-related features, light trapping and quantum confinement effects in low dimensional structures that can be useful for several optoelectronic applications

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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