Search results for "Recurrent"

showing 10 items of 256 documents

Lack of association between celiac disease and dental enamel hypoplasia in a case-control study from an Italian central region

2007

Abstract Background A close correlation between celiac disease (CD) and oral lesions has been reported. The aim of this case-control study was to assess prevalence of enamel hypoplasia, recurrent aphthous stomatitis (RAS), dermatitis herpetiformis and atrophic glossitis in an Italian cohort of patients with CD. Methods Fifty patients with CD and fifty healthy subjects (age range: 3–25 years), matched for age, gender and geographical area, were evaluated by a single trained examiner. Diagnosis of oral diseases was based on typical medical history and clinical features. Histopathological analysis was performed when needed. Adequate univariate statistical analysis was performed. Results Enamel…

Dental Enamel Hypoplasiamedicine.medical_specialtyPathologylcsh:Specialties of internal medicineCase StudyGlossitisDentistry(all)business.industryClinical NeurologyCase-control studyEnamel hypoplasiamedicine.diseaseRecurrent aphthous stomatitisDermatologyOtorhinolaryngologylcsh:RC581-951Dermatitis herpetiformisceliac disease dental enamel hypoplasiaCohortmedicineOral and maxillofacial surgeryNeurology (clinical)businessGeneral DentistryHead & Face Medicine
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Potential implementation of reservoir computing models based on magnetic skyrmions

2018

Reservoir Computing is a type of recursive neural network commonly used for recognizing and predicting spatio-temporal events relying on a complex hierarchy of nested feedback loops to generate a memory functionality. The Reservoir Computing paradigm does not require any knowledge of the reservoir topology or node weights for training purposes and can therefore utilize naturally existing networks formed by a wide variety of physical processes. Most efforts prior to this have focused on utilizing memristor techniques to implement recursive neural networks. This paper examines the potential of skyrmion fabrics formed in magnets with broken inversion symmetry that may provide an attractive phy…

Distributed computingMathematicsofComputing_NUMERICALANALYSISFOS: Physical sciencesGeneral Physics and Astronomy02 engineering and technologyMemristor01 natural scienceslaw.inventionlawMesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciences010306 general physicsTopology (chemistry)PhysicsCondensed Matter - Mesoscale and Nanoscale PhysicsArtificial neural networkHierarchy (mathematics)SkyrmionReservoir computingPhysik (inkl. Astronomie)021001 nanoscience & nanotechnologylcsh:QC1-999Recurrent neural networkNode (circuits)0210 nano-technologylcsh:PhysicsAIP Advances
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Dolor abdominal crónico en la edad pediátrica: implicación de factores clínicos, ambientales y psicosociales. Desarrollo de un programa informático e…

2015

El dolor abdominal crónico (orgánico o funcional) es una causa frecuente de dolor en la infancia, suponiendo hasta el 25% de las derivaciones desde atención primaria a gastroenterología. Es un fenómeno complejo en el que intervienen factores biológicos, psicológicos y sociales en su cronificación. Por ello, el objetivo de este trabajo fue analizar los principales factores clínicos, ambientales y psicosociales relacionados con el DAC (dolor abdominal crónico) en escolares y adolescentes, en la consulta de gastroenterología infantil del Hospital Clínico Universitario de Valencia, así como, desarrollar un programa informático específico útil para el manejo de estos pacientes. Se diseñó un estu…

Dolor abdominal crónico infantilDolor abdominal recurrentetrastornos funcionales gastrointestinales infantilesUNESCO::CIENCIAS MÉDICAS:CIENCIAS MÉDICAS [UNESCO]Dolor abdominalDolor abdominal funcional
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Autoencoders and Recurrent Neural Networks Based Algorithm for Prognosis of Bearing Life

2018

Bearings are one of the most critical components in electric motors, gearboxes and wind turbines. Therefore, bearing fault detection and prognosis of remaining useful life are important to prevent productivity losses. In this study, a novel method is proposed for prognosis of bearing life using an autoencoder and recurrent neural networks-based prediction algorithm. Promising results have been obtained from the experimental data. A monotonic upward trend of the produced health indicator is obtained for all test cases, being one of critical indicators of a proper prognosis. The remaining useful life estimation is moderately accurate under a limited data.

Electric motor021103 operations researchBearing (mechanical)Computer science020208 electrical & electronic engineeringFeature extraction0211 other engineering and technologies02 engineering and technologyBearing fault detectionAutoencoderlaw.inventionRecurrent neural networkTest caselaw0202 electrical engineering electronic engineering information engineeringPrognosticsAlgorithm2018 21st International Conference on Electrical Machines and Systems (ICEMS)
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Transcriptional changes through menstrual cycle reveal a global transcriptional derepression underlying the molecular mechanism involved in the windo…

2021

The human endometrium is a dynamic tissue that only is receptive to host the embryo during a brief time in the middle secretory phase, called the window of implantation (WOI). Despite its importance, regulation of the menstrual cycle remains incompletely understood. The aim of this study was to characterize the gene cooperation and regulation of menstrual cycle progression, to dissect the molecular complexity underlying acquisition of endometrial receptivity for a successful pregnancy, and to provide the scientific community with detailed gene co-expression information throughout the menstrual cycle on a user-friendly web-tool database. A retrospective gene co-expression analysis was perfor…

Embryologysystems biology of the menstrual cycleTranscription Geneticendometrial receptivitymedia_common.quotation_subjectweighted gene correlation network analysis (WGCNA)BiologyCohort StudiesEndometriumgenetic regulation of menstrual cyclePregnancymicroRNAGeneticsHumansEmbryo ImplantationMolecular BiologyGeneTranscription factorgene co-expressionDerepressionMenstrual cycleMenstrual Cycletranscription factormedia_commonrecurrent implantation failuremicroRNAObstetrics and GynecologyGene Expression Regulation DevelopmentalEmbryoCell BiologyGene signatureCell biologyendometrial transcriptomicsnuclear hormone receptorReproductive MedicineNuclear receptorEmbryo LossFemaleTranscriptomeDevelopmental Biology
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Extensive molecular analysis of patients bearing CFTR-related disorders.

2012

Cystic fibrosis transmembrane conductance regulator (CFTR)–related disorders (CFTR-RDs) may present with pancreatic sufficiency, normal sweat test results, and better outcome. The detection rate of mutations is lower in CFTR-RD than in classic CF: mutations may be located in genes encoding proteins that interact with CFTR or support channel activity. We tested the whole CFTR coding regions in 99 CFTR-RD patients, looking for gene mutations in solute carrier (SLC) 26A and in epithelial Na channel (ENaC) in 33 patients who had unidentified mutations. CFTR analysis revealed 28 mutations, some of which are rare. Of these mutations, RT-PCR demonstrated that the novel 1525-1delG impairs exon 10 s…

Epithelial sodium channelcongenital hereditary and neonatal diseases and abnormalitiesCystic fibrosis CFTR SLC26A SCNNCystic FibrosisAnion Transport ProteinsDNA Mutational Analysismolecular analysiCystic Fibrosis Transmembrane Conductance RegulatorGene mutationPathology and Forensic Medicinecongenital bilateral absence of vasa deferentesExonGene Frequencydisseminated bronchiectasiscongenital bilateral absence of vasa deferenteHumansTrypsinmolecular analysisEpithelial Sodium ChannelsGeneCells CulturedGenetic Association StudiesGeneticsbiologydisseminated bronchiectasiEpithelial Cellsrespiratory systemrecurrent pancreatitidigestive system diseasesCystic fibrosis transmembrane conductance regulatorrespiratory tract diseasesSolute carrier familyCFTR related disordersTrypsin Inhibitor Kazal PancreaticCase-Control StudiesRNA splicingMutationbiology.proteinMolecular MedicineCFTR related disorderSLC26 familyCarrier ProteinsNa channel ENaCMinigenerecurrent pancreatitis
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A Deep Network Approach to Multitemporal Cloud Detection

2018

We present a deep learning model with temporal memory to detect clouds in image time series acquired by the Seviri imager mounted on the Meteosat Second Generation (MSG) satellite. The model provides pixel-level cloud maps with related confidence and propagates information in time via a recurrent neural network structure. With a single model, we are able to outline clouds along all year and during day and night with high accuracy.

FOS: Computer and information sciencesComputer Science - Machine Learning010504 meteorology & atmospheric sciencesComputer scienceFeature extraction0211 other engineering and technologiesCloud detectionFOS: Physical sciencesCloud computing02 engineering and technologyCloud detection01 natural sciencesMachine Learning (cs.LG)Laboratory of Geo-information Science and Remote SensingLaboratorium voor Geo-informatiekunde en Remote Sensing021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingbusiness.industrySeviriDeep learningDeep learningPE&RCPhysics - Atmospheric and Oceanic PhysicsRecurrent neural networkRecurrent neural networksAtmospheric and Oceanic Physics (physics.ao-ph)Convolutional neural networksSatelliteArtificial intelligencebusinessNetwork approachIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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Deep Learning for Classifying Physical Activities from Accelerometer Data

2021

Physical inactivity increases the risk of many adverse health conditions, including the world’s major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening life expectancy. There are minimal medical care and personal trainers’ methods to monitor a patient’s actual physical activity types. To improve activity monitoring, we propose an artificial-intelligence-based approach to classify the physical movement activity patterns. In more detail, we employ two deep learning (DL) methods, namely a deep feed-forward neural network (DNN) and a deep recurrent neural network (RNN) for this purpose. We evaluate the proposed models on two phy…

Fysisk aktivitetComputer scienceVDP::Informasjons- og kommunikasjonsteknologi: 550physical activityAccelerometercomputer.software_genresensorsBiochemistryMedical careRNNAnalytical Chemistry:Information and communication technology: 550 [VDP]Accelerometer dataAccelerometryartificial_intelligence_roboticsInstrumentationArtificial neural networkhealthAtomic and Molecular Physics and Opticsmachine learningclassificationHealthFeedforward neural network:Informasjons- og kommunikasjonsteknologi: 550 [VDP]Physical activityTP1-1185Movement activityMachine learningHelseFeed-forward neural networksVDP::Information and communication technology: 550ArticleFysisk aktiviteterMachine learningHumansAccelerometer dataElectrical and Electronic EngineeringExercisebusiness.industryPhysical activitySensorsDeep learningChemical technologydeep learningDeep learningfeed-forward neural networkRecurrent neural networkPhysical activitiesDiabetes Mellitus Type 2Recurrent neural networksaccelerometer dataUCIrecurrent neural networkNeural Networks ComputerArtificial intelligenceClassificationsbusinesscomputerDNN
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IL-10 and TGF-β1 gene polymorphisms in Greek patients with recurrent aphthous stomatitis.

2022

Recurrent aphthous stomatitis (RAS) is one of the most frequent inflammatory disorders of the oral mucosa. Cytokines, which play an important role in RAS pathogenesis, participate directly or indirectly in normal, immunological and inflammatory processes and are secreted from cells belonging to innate and adaptive immunity as a consequence of microbial and antigenic stimuli. Gene polymorphisms in specific cytokines may predispose to RAS development. The aim of this study was the investigation and association of IL-10 and TGF-β1 gene polymorphisms with RAS.Study's cohort consisted of 60 Greek patients diagnosed with RAS, including 40 patients with minor, 10 patients with major and 10 with he…

GenotypeGreecePolymorphism Single NucleotideInterleukin-10Transforming Growth Factor beta1OtorhinolaryngologyCase-Control StudiesHumansSurgeryGenetic Predisposition to DiseaseStomatitis Aphthousrecurrent aphthous stomatitis aphthae IL-10 TGF-β gene polymorphisms oral mucosaCodonGeneral DentistryUNESCO:CIENCIAS MÉDICASMedicina oral, patologia oral y cirugia bucal
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Embryo Aneuploidy Screening for Unexplained Recurrent Miscarriage: A Minireview

2005

Problem:  The aim of this study was to investigate the incidence of chromosomal abnormalities in unexplained recurrent miscarriage (RM) patients and assess the role of pre-implantation genetic diagnosis (PGD) in preventing subsequent pregnancy loss and improving pregnancy outcome. Method of Study:  Pre-implantation genetic diagnosis was performed in 241 RM cycles and in 35 cycles in patients undergoing PGD for sex-linked diseases (control group). Chromosomes 13, 16, 18, 21, 22, X and Y were analysed by fluorescence in situ hybridization. Results:  The implantation and pregnancy rates in RM patients were 26.4 and 36.5% versus 20.6 and 29.0% in the control group, respectively. The percentage …

Gynecologymedicine.medical_specialtyPregnancyIn vitro fertilisationmedicine.diagnostic_testObstetricsmedicine.medical_treatmentIncidence (epidemiology)ImmunologyObstetrics and GynecologyAneuploidyBiologyAbortionmedicine.diseasemedicine.anatomical_structureReproductive MedicineRecurrent miscarriagemedicineImmunology and AllergyBlastocystFluorescence in situ hybridizationAmerican Journal of Reproductive Immunology
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