1,721,099 research outputs found
Underwater Mediterranean image analysis based on the compute continuum paradigm
No full text14 pages, 11 figures, 6 tables.-- Data availability: Data will be made available on request: Francescangeli, Marco; Aguzzi, Jacopo; Marini, Simone; Martínez, Enoc; Nogueras, Marc; Toma, Daniel M.; Carandell, Matias; Masmitja, Ivan; Sarriá, David; García-Benadí, Albert; Cadena, Javier; Bghiel, Ikram; Artero Delgado, Carlota; Vidal, Neus; Gomáriz, Spartacus; Olivé Duran, Joaquim; Santamaria, Pep; Mànuel-Làzaro, Antoni; Río, Joaquín del; 2022; Underwater camera photos with manual tagging of fish species at OBSEA seafloor observatory from 2013 to 2014 [Dataset]; PANGAEA; https://doi.org/10.1594/PANGAEA.946149Human activity depends on the oceans for food, transportation, leisure, and many more purposes. Oceans cover 70% of the Earth’s surface, but most of them are unknown to humankind. This is the reason why underwater imaging is a valuable resource asset to Marine Science. Images are acquired with observing systems, e.g. autonomous underwater vehicles or underwater observatories, that presently transmit all the raw data to land stations. However, the transfer of such an amount of data could be challenging, considering the limited power supply and transmission bandwidth of these systems. In this paper, we discuss these aspects, and in particular how it is possible to couple Edge and Cloud computing for effective management of the full processing pipeline according to the Compute Continuum paradigmThis work was partially funded by the European Union - NextGenerationEU and by the Ministry of University and Research (MUR), National Recovery and Resilience Plan (PNNR), Mission 4, Component 2, Investment 1.5, project “RAISE - Robotics and AI for Socio-economic Empowerment” - (ECS00000035); The co-author Simone Marini is part of the critical mass of the RAISE Innovation Ecosystem.
It is also funded by the Project “National Biodiversity Future Center - NBFC” funded under the National Recovery and Resilience Plan (PNNR), Mission 4 Component 2 Investment 1.4 - Call for tender No. 3138 of 16 December 2021, rectified by Decree n.3175 of 18 December 2021 of Italian Ministry of University and Research funded by the European Union – NextGenerationEU; Project code CN_00000033, Concession Decree No. 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research, CUP D33C22000960007.
The research was also supported by the ICM-CSIC “Severo Ochoa Centre Excellence” (CEX2019-000928-S) and the Research Unit Tecnoterra (ICM-CSIC/UPC) . Funds were also from DIGI4ECO (grant number 101112883 - GAP-101112883)Peer reviewe
"Noisy beets": impact of phenotyping errors on genomic predictions for binary traits in Beta vulgaris
Full text linkBackground
Noise (errors) in scientific data is endemic and may have a detrimental effect on statistical analyses and experimental results. The effects of noisy data have been assessed in genome-wide association studies for case-control experiments in human medicine. Little is known, however, on the impact of noisy data on genomic predictions, a widely used statistical application in plant and animal breeding.
Results
In this study, the sensitivity to noise in the data of five classification methods (K-nearest neighbours—KNN, random forest—RF, ridge logistic regression—LR, and support vector machines with linear or radial basis function kernels) was investigated. A sugar beet population of 123 plants phenotyped for a binary trait and genotyped for 192 SNP (single nucleotide polymorphism) markers was used. Labels (0/1 phenotype) were randomly sampled to generate noise. From the base scenario without errors in the labels, increasing proportions of noisy labels—up to 50 %—were generated and introduced in the data.
Conclusions
Local classification methods—KNN and RF—showed higher tolerance to noisy labels compared to methods that leverage global data properties—LR and the two SVM models. In particular, KNN outperformed all other classifiers with AUC (area under the ROC curve) higher than 0.95 up to 20 % noisy labels. The runner-up method, RF, had an AUC of 0.941 with 20 % noise
A simple time-lapse apparatus for monitoring macrozoobenthos activity in Antarctica
No full textIn situ time-lapse studies in Polar Regions are uncommon because of the intrinsic limitations of scientific SCUBA diving at sub-zero temperatures and the logistical challenges linked to the deployment of underwater time-lapse systems, which are typically large and heavy. In Antarctica, a number of non-invasive approaches have been adopted to document the behaviour of benthic organisms. For example, in the McMurdo Sound, Ross Sea, Kim et al. (2007) employed time-lapse arrays to study the movement of sea-stars Odontaster validus Koehler in response to organic enrichment, and McClintock et al. (2010) recorded valve clap frequency in scallops Adamussium colbecki (E.A. Smith). At King George Island, Antarctic Peninsula,
Schories (unpublished, https://www.youtube.com/watch? v=rKV8s00SFL8) conducted a time-lapse analysis
(6 hours) of limpet Nacella concinna (Strebel) and sea urchin Sterechinus neumayeri (Meissner) movement. Here we present a simple and portable time-lapse apparatus, which was tested in TerraNova Bay, Ross Sea, at a depth of 20m below the pack ice
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
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
PaPI: pseudo amino acid composition to score human protein-coding variants
No full textBackground: High throughput sequencing technologies are able to identify the whole genomic variation of an individual. Gene-targeted and whole-exome experiments are mainly focused on coding sequence variants related to a single or multiple nucleotides. The analysis of the biological significance of this multitude of genomic variant is challenging and computational demanding.
Results: We present PaPI, a new machine-learning approach to classify and score human coding variants by estimating the probability to damage their protein-related function. The novelty of this approach consists in using pseudo amino acid composition through which wild and mutated protein sequences are represented in a discrete model. A machine learning classifier has been trained on a set of known deleterious and benign coding variants with the aim to score unobserved variants by taking into account hidden sequence patterns in human genome potentially leading to diseases. We show how the combination of amphiphilic pseudo amino acid composition, evolutionary conservation and homologous proteins based methods outperforms several prediction algorithms and it is also able to score complex variants such as deletions, insertions and indels.
Conclusions: This paper describes a machine-learning approach to predict the deleteriousness of human coding variants. A freely available web application (http://papi.unipv.it) has been developed with the presented method, able to score up to thousands variants in a single run
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
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