1,720,962 research outputs found
Clinical features of COVID-19 and SARS epidemics. A literature review
Full text linkSARS-CoV-2, responsible for the current pandemic, is a novel strain of the Coronaviridae family, which has infected humans as a result of the leap to a new species. It causes an atypical pneumonia similar to that caused by SARS-CoV in 2003. SARS-CoV-2 has currently infected more than 9,200,000 people and caused almost 480,000 deaths worldwide. Although SARS-CoV-2 and SARS-CoV have similar phylogenetic and pathogenetic characteristics, they show important differences in clinical manifestations. We have reviewed the recent literature comparing the characteristics of the two epidemics and highlight their peculiar aspects. An analysis of all signs and symptoms of 3,365 SARS patients and 23,280 COVID-19 patients as well as of the comorbidities has been carried out. A total of 17 and 75 studies regarding patients with SARS and COVID-19, respectively, were included in the analysis. The analysis revealed an overlap of some symptoms between the two infections. Unlike SARS patients, COVID-19 patients have developed respiratory, neurological and gastrointestinal symptoms, and, in a limited number of subjects, symptoms involving organs such as skin and subcutaneous tissue, kidneys, cardiovascular system, liver and eyes. This analysis was conducted in order to direct towards an early identification of the infection, a suitable diagnostic procedure and the adoption of appropriate containment measures
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
DIAMANTE: A data-centric semantic segmentation approach to map tree dieback induced by bark beetle infestations via satellite images
No full textForest tree dieback inventory has a crucial role in improving forest management strategies. This inventory is traditionally performed by forests through laborious and time-consuming human assessment of individual trees. On the other hand, the large amount of Earth satellite data that are publicly available with the Copernicus program and can be processed through advanced deep learning techniques has recently been established as an alternative to field surveys for forest tree dieback tasks. However, to realize its full potential, deep learning requires a deep understanding of satellite data since the data collection and preparation steps are essential as the model development step. In this study, we explore the performance of a data-centric semantic segmentation approach to detect forest tree dieback events due to bark beetle infestation in satellite images. The proposed approach prepares a multisensor data set collected using both the SAR Sentinel-1 sensor and the optical Sentinel-2 sensor and uses this dataset to train a multisensor semantic segmentation model. The evaluation shows the effectiveness of the proposed approach in a real inventory case study that regards non-overlapping forest scenes from the Northeast of France acquired in October 2018. The selected scenes host bark beetle infestation hotspots of different sizes, which originate from the mass reproduction of the bark beetle in the 2018 infestation
Variations on the Author
Full text link“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
Full text linkWe 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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
GANDALF: A LLM-based approach to map bark beetle outbreaks in semantic stories of Sentinel-2 images
No full textHuge spruce forest areas have been damaged by massive bark beetle outbreaks across Europe during the past few years. Hence, forest health management requires large-scale inventory of bark beetle outbreaks to plan actions for promptly mitigating forest tree dieback. Deep learning techniques have recently achieved amazing results in imagery semantic segmentation tasks by dominating the recent research for mapping bark beetle outbreaks in Sentinel-2 images of forest areas. In addition, due to the impressive performance of Large Language Models (LLMs) in natural language understanding and generation tasks, LLMs have started attracting attention in multiple fields. In this paper, we describe GANDALF: an approach that leverages the potential of LLMs for mapping bark beetle outbreaks in Sentinel-2 images of forest areas. Specifically, we take advantage of the rich context of textual data to transform Sentinel-2 images in smart data ready for boosting accurate semantic segmentation modeling. We use a foundation LLM model to account for the text encoding of the spectral-spatial imagery context information. We fine-tune the LLM model to perform the semantic segmentation of forest images and use the Integrated Gradients (IG) algorithm to explain how each spectral-spatial information has an effect on the bark beetle outbreak detection. We assess the effectiveness of the proposed approach in a case study regarding bark beetle outbreaks in Sentinel-2 images of forest scenes in Czech Republic
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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