Search results for "e learning"

showing 10 items of 2703 documents

Optogenetically enhanced pituitary corticotroph cell activity post-stress onset causes rapid organizing effects on behaviour

2016

The anterior pituitary is the major link between nervous and hormonal systems, which allow the brain to generate adequate and flexible behaviour. Here, we address its role in mediating behavioural adjustments that aid in coping with acutely threatening environments. For this we combine optogenetic manipulation of pituitary corticotroph cells in larval zebrafish with newly developed assays for measuring goal-directed actions in very short timescales. Our results reveal modulatory actions of corticotroph cell activity on locomotion, avoidance behaviours and stimulus responsiveness directly after the onset of stress. Altogether, the findings uncover the significance of endocrine pituitary cell…

0301 basic medicinemedicine.medical_specialtyScienceGeneral Physics and AstronomyBiologyStimulus (physiology)OptogeneticsGeneral Biochemistry Genetics and Molecular BiologyArticleAnimals Genetically Modified03 medical and health sciencesAnterior pituitaryInternal medicinemedicineZebrafish larvaeAvoidance LearningEndocrine systemAnimalsCorticotrophsZebrafishQLMultidisciplinaryQGeneral ChemistryCorticotroph CellOptogenetics030104 developmental biologyEndocrinologymedicine.anatomical_structureCorticotropic cellNeuroscienceLocomotionStress PsychologicalHormone
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Automatic detection and measurement of nuchal translucency.

2017

In this paper we propose a new methodology to support the physician both to identify automatically the nuchal region and to obtain a correct thickness measurement of the nuchal translucency. The thickness of the nuchal translucency is one of the main markers for screening of chromosomal defects such as trisomy 13, 18 and 21. Its measurement is performed during ultrasound scanning in the first trimester of pregnancy. The proposed methodology is mainly based on wavelet and multi resolution analysis. The performance of our method was analysed on 382 random frames, representing mid-sagittal sections, uniformly extracted from real clinical ultrasound videos of 12 patients. According to the groun…

0301 basic medicinemedicine.medical_specialtyWavelet AnalysisFirst trimester of pregnancyHealth InformaticsSensitivity and SpecificityWavelet analysi030218 nuclear medicine & medical imagingPattern Recognition AutomatedMachine Learning03 medical and health sciencesPrenatal ultrasound0302 clinical medicineNuchal regionNuchal translucencyUltrasound fetal examinationMedian sagittal sectionNuchal Translucency MeasurementImage Interpretation Computer-AssistedMedicineHumansPixelbusiness.industryMulti resolution analysisUltrasoundReproducibility of ResultsPattern recognitionComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science ApplicationsSurgeryClinical ultrasound030104 developmental biologyNuchal translucencyArtificial intelligenceDown SyndromebusinessNuchal Translucency MeasurementAlgorithmsComputers in biology and medicine
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Statistical Explorations and Univariate Timeseries Analysis on COVID-19 Datasets to Understand the Trend of Disease Spreading and Death

2020

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0301 basic medicinetransmission ratepopulationSevere Acute Respiratory Syndromemedicine.disease_causelcsh:Chemical technologyBiochemistryRNNDisease OutbreaksAnalytical Chemistry0302 clinical medicinePandemiclcsh:TP1-1185030212 general & internal medicineInstrumentationVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Coronaviruskeraseducation.field_of_studypublic healthartificial intelligenceAtomic and Molecular Physics and OpticsRegressionmachine learningGeographySevere acute respiratory syndrome-related coronavirusstatisticsMiddle East Respiratory Syndrome Coronaviruscommunity diseaseregressionCoronavirus InfectionsLSTMPneumonia ViralPopulationWorld Health OrganizationArticleBetacoronavirusspread factor03 medical and health sciencesCode (cryptography)medicineAnimalsHumansElectrical and Electronic EngineeringeducationPandemicsmeasurable sensor dataalgorithmSARS-CoV-2ICDUnivariatedeep learningOutbreakCOVID-19medicine.diseasehypothesis testpython030104 developmental biologycorrelationCatsMiddle East respiratory syndromeCattleDemographySensors
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Towards identifying drug side effects from social media using active learning and crowd sourcing.

2019

Motivation Social media is a largely untapped source of information on side effects of drugs. Twitter in particular is widely used to report on everyday events and personal ailments. However, labeling this noisy data is a difficult problem because labeled training data is sparse and automatic labeling is error-prone. Crowd sourcing can help in such a scenario to obtain more reliable labels, but is expensive in comparison because workers have to be paid. To remedy this, semi-supervised active learning may reduce the number of labeled data needed and focus the manual labeling process on important information. Results We extracted data from Twitter using the public API. We subsequently use Ama…

0303 health sciencesFocus (computing)Information retrievalDrug-Related Side Effects and Adverse ReactionsProcess (engineering)business.industryActive learning (machine learning)Computer scienceComputational BiologyCrowdsourcing03 medical and health sciences0302 clinical medicineProblem-based learningCode (cryptography)CrowdsourcingHumansSocial media030212 general & internal medicinebusinessBaseline (configuration management)Social Media030304 developmental biologyPacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
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Boosting Signal-to-Noise in Complex Biology: Prior Knowledge Is Power

2011

A major difficulty in the analysis of complex biological systems is dealing with the low signal-to-noise inherent to nearly all large biological datasets. We discuss powerful bioinformatic concepts for boosting signal-to-noise through external knowledge incorporated in processing units we call filters and integrators. These concepts are illustrated in four landmark studies that have provided model implementations of filters, integrators, or both.

0303 health sciencesLandmarkBoosting (machine learning)Biochemistry Genetics and Molecular Biology(all)business.industryBiologyMachine learningcomputer.software_genreBioinformaticsGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciences0302 clinical medicine030220 oncology & carcinogenesisIntegratorArtificial intelligencebusinesscomputerImplementation030304 developmental biologyCell
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Efficient Online Laplacian Eigenmap Computation for Dimensionality Reduction in Molecular Phylogeny via Optimisation on the Sphere

2019

Reconstructing the phylogeny of large groups of large divergent genomes remains a difficult problem to solve, whatever the methods considered. Methods based on distance matrices are blocked due to the calculation of these matrices that is impossible in practice, when Bayesian inference or maximum likelihood methods presuppose multiple alignment of the genomes, which is itself difficult to achieve if precision is required. In this paper, we propose to calculate new distances for randomly selected couples of species over iterations, and then to map the biological sequences in a space of small dimension based on the partial knowledge of this genome similarity matrix. This mapping is then used …

0303 health sciences[STAT.AP]Statistics [stat]/Applications [stat.AP]Computer scienceDimensionality reductionComputationDimension (graph theory)Complete graphMinimum spanning treeBayesian inferenceQuantitative Biology::Genomics03 medical and health sciencesComputingMethodologies_PATTERNRECOGNITION0302 clinical medicine[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]Algorithm030217 neurology & neurosurgeryEigenvalues and eigenvectorsDistance matrices in phylogenyComputingMilieux_MISCELLANEOUS030304 developmental biology
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Operative Anatomy of the Skull Base: 3D Exploration with a Highly Detailed Interactive Atlas.

2020

Abstract Objective We evaluated the usefulness of a three-dimensional (3D) interactive atlas to illustrate and teach surgical skull base anatomy in a clinical setting. Study Design A highly detailed atlas of the adult human skull base was created from multiple high-resolution magnetic resonance imaging (MRI) and computed tomography (CT) scans of a healthy Caucasian male. It includes the parcellated and labeled bony skull base, intra- and extracranial vasculature, cranial nerves, cerebrum, cerebellum, and brainstem. We are reporting retrospectively on our experiences with employing the atlas for the simulation and teaching of neurosurgical approaches and concepts in a clinical setting. Setti…

0303 health sciencesmedicine.diagnostic_testbusiness.industryeducationInteractive 3dMagnetic resonance imagingCollaborative learningAnatomyUniversity hospital03 medical and health sciencesHuman skullSkull0302 clinical medicinemedicine.anatomical_structure030301 anatomy & morphologySurgical anatomyAtlas (anatomy)medicineNeurology (clinical)business030217 neurology & neurosurgeryJournal of neurological surgery. Part B, Skull base
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Sensory methodologies and the taste of water

2009

/WOS: 000285178000010; International audience; Describing the taste of water is a challenge since drinking water is supposed to have almost no taste. In this study, different classical sensory methodologies have been applied in order to assess sensory characteristics of water and have been compared: sensory profiling, Temporal Dominance of Sensations and free sorting task. These methodologies present drawbacks: sensory profile and TDS do not provide an effective discrimination of the taste of water and the free sorting task is efficient but does not enable data aggregation. A new methodology based on comparison with a set of references and named “Polarized Sensory Positioning” (PSP) has bee…

030309 nutrition & dieteticsComputer science[ SDV.AEN ] Life Sciences [q-bio]/Food and NutritionSensory systemSensory profileMachine learningcomputer.software_genreSensory analysissensory analysis03 medical and health sciences0404 agricultural biotechnology[SDV.IDA]Life Sciences [q-bio]/Food engineeringProfiling (information science)0303 health sciencesCommunicationNutrition and Dieteticsbusiness.industrydrinking water[ SDV.IDA ] Life Sciences [q-bio]/Food engineering04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceData aggregatorArtificial intelligencebusinesscomputerpolarized sensory positioning[SDV.AEN]Life Sciences [q-bio]/Food and NutritionFood Science
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Sort and beer: Everything you wanted to know about the sorting task but did not dare to ask

2011

author cannot archive publisher's version/PDF; International audience; In industries, the sensory characteristics of products are key points to control. The method commonly used to characterize and describe products is the conventional profile. This very efficient method requires a lot of time to train assessors and to teach them how to quantify the sensory characteristics of interest. Over the last few years, other faster and less restricting methods have been developed, such as free choice profile, flash profile, projective mapping or sorting tasks. Among these methods, the sorting task has recently become quite popular in sensory evaluation because of its simplicity: it only requires ass…

030309 nutrition & dieteticsComputer sciencemedia_common.quotation_subjectControl (management)NovicesStability (learning theory)Sensory systemMachine learningcomputer.software_genreTask (project management)03 medical and health sciences0404 agricultural biotechnologysortSimplicitySorting taskmedia_common0303 health sciencesNutrition and Dieteticsbusiness.industrySortingBeer04 agricultural and veterinary sciences040401 food scienceKey (cryptography)Artificial intelligencebusinesscomputer[SDV.AEN]Life Sciences [q-bio]/Food and NutritionFood ScienceExperts
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A Model of Positive and Negative Learning

2017

This chapter proposes a model of positive and negative learning (PNL model). We use the term negative learning when stress among students occurs, and when knowledge and abilities are not properly developed. We use the term positive learning if motivation is high and active learning occurs. The PNL model proposes that (a) learning-related demands and resources contribute to learning engagement and burnout, (b) that learning engagement improves critical thinking, which (c) should enhance students’ abilities to detect fake news. Two studies demonstrate the validity of the learning engagement and burnout constructs, and learning-related demands and resources as possible antecedents. Also, criti…

05 social sciences050301 educationBurnoutTerm (time)Learning engagementCritical thinking0502 economics and businessStress (linguistics)Active learningFake newsPsychology0503 education050203 business & managementCognitive psychology
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