7,536 research outputs found

    gOntt: a Tool for Scheduling Ontology Development Projects

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    The Ontology Engineering field lacks tools that guide ontology developers to plan and schedule their ontology development projects. gOntt helps ontology developers in two ways: (a) to schedule ontology projects; and (b) to execute such projects based on the schedule and using the NeOn Methodology

    The Ca II infrared triplet's performance as an activity indicator compared to Ca II H and K

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    Aims. A large number of Calcium Infrared Triplet (IRT) spectra are expected from the GAIA- and CARMENES missions. Conversion of these spectra into known activity indicators will allow analysis of their temporal evolution to a better degree. We set out to find such a conversion formula and to determine its robustness. Methods. We have compared 2274 Ca II IRT spectra of active main-sequence F to K stars taken by the TIGRE telescope with those of inactive stars of the same spectral type. After normalizing and applying rotational broadening, we subtracted the comparison spectra to find the chromospheric excess flux caused by activity. We obtained the total excess flux, and compared it to established activity indices derived from the Ca II H & K lines, the spectra of which were obtained simultaneously to the infrared spectra. Results. The excess flux in the Ca II IRT is found to correlate well with RHKR_\mathrm{HK}' and RHK+R_\mathrm{HK}^{+}, as well as SMWOS_\mathrm{MWO}, if the BVB-V-dependency is taken into account. We find an empirical conversion formula to calculate the corresponding value of one activity indicator from the measurement of another, by comparing groups of datapoints of stars with similar B-V.Comment: 16 pages, 15 figures. Accepted for publication in Astronomy & Astrophysic

    The biomedical abbreviation recognition and resolution (BARR) track: Benchmarking, evaluation and importance of abbreviation recognition systems applied to Spanish biomedical abstracts

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    Healthcare professionals are generating a substantial volume of clinical data in narrative form. As healthcare providers are confronted with serious time constraints, they frequently use telegraphic phrases, domain-specific abbreviations and shorthand notes. Efficient clinical text processing tools need to cope with the recognition and resolution of abbreviations, a task that has been extensively studied for English documents. Despite the outstanding number of clinical documents written worldwide in Spanish, only a marginal amount of studies has been published on this subject. In clinical texts, as opposed to the medical literature, abbreviations are generally used without their definitions or expanded forms. The aim of the first Biomedical Abbreviation Recognition and Resolution (BARR) track, posed at the IberEval 2017 evaluation campaign, was to assess and promote the development of systems for generating a sense inventory of medical abbreviations. The BARR track required the detection of mentions of abbreviations or short forms and their corresponding long forms or definitions from Spanish medical abstracts. For this track, the organizers provided the BARR medical document collection, the BARR corpus of manually annotated abstracts labelled by domain experts and the BARR-Markyt evaluation platform. A total of 7 teams submitted 25 runs for the two BARR subtasks: (a) the identification of mentions of abbreviations and their definitions and (b) the correct detection of short form-long form pairs. Here we describe the BARR track setting, the obtained results and the methodologies used by participating systems. The BARR task summary, corpus, resources and evaluation tool for testing systems beyond this campaign are available at: http://temu.inab.org .We acknowledge the Encomienda MINETAD-CNIO/OTG Sanidad Plan TL and Open-Minted (654021) H2020 project for funding.Postprint (published version

    Comparison of Machine Learning Methods Using Spectralis OCT for Diagnosis and Disability Progression Prognosis in Multiple Sclerosis

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    Machine learning approaches in diagnosis and prognosis of multiple sclerosis (MS) were analysed using retinal nerve fiber layer (RNFL) thickness, measured by optical coherence tomography (OCT). A cross-sectional study (72 MS patients and 30 healthy controls) was used for diagnosis. These 72 MS patients were involved in a 10-year longitudinal follow-up study for prognostic purposes. Structural measurements of RNFL thickness were performed using different Spectralis OCT protocols: fast macular thickness protocol to measure macular RNFL, and fast RNFL thickness protocol and fast RNFL-N thickness protocol to measure peripapillary RNFL. Binary classifiers such as multiple linear regression (MLR), support vector machines (SVM), decision tree (DT), k-nearest neighbours (k-NN), Naïve Bayes (NB), ensemble classifier (EC) and long short-term memory (LSTM) recurrent neural network were tested. For MS diagnosis, the best acquisition protocol was fast macular thickness protocol using k-NN (accuracy: 95.8%; sensitivity: 94.4%; specificity: 97.2%; precision: 97.1%; AUC: 0.958). For MS prognosis, our model with a 3-year follow up to predict disability progression 8 years later was the best predictive model. DT performed best for fast macular thickness protocol (accuracy: 91.3%; sensitivity: 90.0%; specificity: 92.5%; precision: 92.3%; AUC: 0.913) and SVM for fast RNFL-N thickness protocol (accuracy: 91.3%; sensitivity: 87.5%; specificity: 95.0%; precision: 94.6%; AUC: 0.913). This work concludes that measurements of RNFL thickness obtained with Spectralis OCT have a good ability to diagnose MS and to predict disability progression in MS patients. This machine learning approach would help clinicians to have valuable information. © 2022, The Author(s)

    Controlling anomalous stresses in soft field-responsive systems

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    We report a new phenomenon occurring in field-responsive suspensions: shear-induced anomalous stresses. Competition between a rotating field and a shear flow originates a multiplicity of anomalous stress behaviors in suspensions of bounded dimers constituted by induced dipoles. The great variety of stress regimes includes non-monotonous behaviors, multi-resonances, negative viscosity effect and blockades. The reversibility of the transitions between the different regimes and the self-similarity of the stresses make this phenomenon controllable and therefore applicable to modify macroscopic properties of soft condensed matter phasesComment: 5 pages, 6 figures, submitted to PR
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