Search results for "PREDICTION"

showing 10 items of 511 documents

Molecular basis of filamin a-filGAP interaction and its impairment in congenital disorders associated with filamin a mutations

2008

Background Mutations in filamin A (FLNa), an essential cytoskeletal protein with multiple binding partners, cause developmental anomalies in humans. Methodology/Principal Findings We determined the structure of the 23rd Ig repeat of FLNa (IgFLNa23) that interacts with FilGAP, a Rac-specific GTPase-activating protein and regulator of cell polarity and movement, and the effect of the three disease-related mutations on this interaction. A combination of NMR structural analysis and in silico modeling revealed the structural interface details between the C and D β-strands of the IgFLNa23 and the C-terminal 32 residues of FilGAP. Mutagenesis of the predicted key interface residues confirmed the b…

ImmunoprecipitationFilaminsMolecular Sequence Dataeducationlcsh:MedicineComputational Biology/Protein Structure PredictionBiologyFilaminCell Biology/Cell SignalingCongenital AbnormalitiesBiochemistry/Protein Folding03 medical and health sciences0302 clinical medicineProtein structureContractile ProteinsCell Biology/CytoskeletonFLNAHumansFLNBFLNCAmino Acid Sequencelcsh:Science030304 developmental biologyGenetics0303 health sciencesMultidisciplinaryBinding SitesMolecular StructureSequence Homology Amino AcidPoint mutationlcsh:RGTPase-Activating ProteinsMicrofilament Proteins3. Good healthBiochemistry/BioinformaticsMutationProtein foldinglcsh:Q118 Biological sciences030217 neurology & neurosurgeryResearch Article
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In silico methods for metabolomic and toxicity prediction of zearalenone, α-zearalenone and β-zearalenone.

2020

Zearalenone (ZEA), α-zearalenol (α-ZEL) and β-zearalenol (β-ZEL) (ZEA's metabolites) are co/present in cereals, fruits or their products. All three with other compounds, constitute a cocktail-mixture that consumers (and also animals) are exposed and never entirely evaluated, nor in vitro nor in vivo. Effect of ZEA has been correlated to endocrine disruptor alterations as well as its metabolites (α-ZEL and β-ZEL); however, toxic effects associated to metabolites generated once ingested are unknown and difficult to study. The present study defines the metabolomics profile of all three mycotoxins (ZEA, α-ZEL and β-ZEL) and explores the prediction of their toxic effects proposing an in silico w…

In silicoMetaboliteToxicologyArticleAmes test03 medical and health scienceschemistry.chemical_compound0404 agricultural biotechnologyMetabolomicsGlucuronidesCytochrome P-450 Enzyme SystemIn vivoAnimalsMetabolomicsComputer SimulationMycotoxinZearalenoneZebrafish030304 developmental biology0303 health sciencesChemistryIn silicofood and beverages04 agricultural and veterinary sciencesGeneral Medicine040401 food sciencePASS onlineEndocrine disruptorBiochemistryBlood-Brain BarrierMetaToxZearalenoneSwissADMEReactive Oxygen SpeciesPredictionFood ScienceFood and chemical toxicology : an international journal published for the British Industrial Biological Research Association
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Performance and energy optimisation in CPUs through fuzzy knowledge representation

2019

Abstract This paper presents an automatic design space exploration using processor design knowledge for the multi-objective optimisation of a superscalar microarchitecture enhanced with selective load value prediction (SLVP). We introduced new important SLVP parameters and determined their influence regarding performance, energy consumption, and thermal dissipation. We significantly enlarged initial processor design knowledge expressed through fuzzy rules and we analysed its role in the process of automatic design space exploration. The proposed fuzzy rules improve the diversity and quality of solutions, and the convergence speed of the design space exploration process. Experiments show tha…

Information Systems and ManagementComputer scienceDesign space exploration02 engineering and technologyFuzzy logicMulti-objective optimizationTheoretical Computer ScienceProcessor design knowledgeArtificial IntelligenceEnergy savingSuperscalar0202 electrical engineering electronic engineering information engineeringAutomatic design space exploration Processor design knowledge Superscalar microarchitecture Dynamic value prediction Energy savingProcessor design05 social sciencesProcess (computing)050301 educationEnergy consumptionComputer Science ApplicationsMicroarchitectureComputer engineeringControl and Systems EngineeringDynamic value prediction020201 artificial intelligence & image processingAutomatic design space exploration; Processor design knowledge; Superscalar microarchitecture; Dynamic value prediction; Energy savingSuperscalar microarchitecture0503 educationAutomatic design space explorationSoftwareEnergy (signal processing)Information Sciences
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Privacy and temporal aware allocation of data in decentralized online social networks

2017

Distributed Online Social Networks (DOSNs) have recently been proposed to grant users more control over the data they share with the other users. Indeed, in contrast to centralized Online Social Networks (such as Facebook), DOSNs are not based on centralized storage services, because the contents shared by the users are stored on the devices of the users themselves. One of the main challenges in a DOSN comes from guaranteeing availability of the users' contents when the data owner disconnects from the network. In this paper, we focus our attention on data availability by proposing a distributed allocation strategy which takes into account both the privacy policies defined on the contents an…

Information privacyComputer sciencePrivacy policyControl (management)02 engineering and technologyInterval (mathematics)Computer securitycomputer.software_genreAvailability predictionTheoretical Computer ScienceSet (abstract data type)0202 electrical engineering electronic engineering information engineeringFocus (computing)Social networkSettore INF/01 - Informaticabusiness.industry020206 networking & telecommunicationsData availabilityOrder (business)Computer ScienceDecentralized online social networkDecentralized online social networks020201 artificial intelligence & image processingbusinesscomputerData privacyComputer network
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Isolated childhood growth hormone deficiency: a 30-year experience on final height and a new prediction model

2022

Purpose We aimed to evaluate the near-final height (nFHt) in a large cohort of pediatricpatients with growth hormone deficiency (GHD) and to elaborate a new predictive method of nFHt. Methods We recruited GHD patients diagnosed between 1987 and 2014 and followed-up until nFHt. To predict the values of nFHt, each predictor was run in a univariable spline. Results We enrolled 1051 patients. Pre-treatment height was -2.43 SDS, lower than parental height (THt) (-1.09 SDS, p < 0.001). The dose of recombinant human GH (rhGH) was 0.21mg/kg/week at start of treatment. nFHt was -1.08 SDS (height gain 1.27 SDS), higher than pre-treatment height (p < 0.001) and comparable to THt. 1.6% of the pat…

Insulin-like growth factor 1Human Growth HormoneEndocrinology Diabetes and MetabolismPubertyFinal height; Growth; Growth hormone deficiency; Growth hormone retesting; Insulin-like growth factor 1; LMG method; PredictionDwarfismGrowthBody HeightCohort StudiesEndocrinologySettore MED/38 - Pediatria Generale E SpecialisticaGrowth hormone retestingPituitaryFinal heightGrowth HormoneFinal height; Growth; Growth hormone deficiency; Growth hormone retesting; Insulin-like growth factor 1; LMG method; Prediction; Body Height; Child; Cohort Studies; Growth Hormone; Humans; Puberty; Dwarfism Pituitary; Human Growth HormoneHumansGrowth hormone deficiencyLMG methodDwarfism PituitaryPredictionChildFinal height Growth Growth hormone deficiency Growth hormone retesting Insulin-like growth factor 1 LMG method Prediction
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An Efficient Hardware Architecture for the HEVC Intra Prediction

2014

International audience; A novel intra prediction hardware architecture forthe High Efficiency Video Coding (HEVC) is presented in thispaper in order to reduce the computation complexity within thisstandard and to accelerate the concerned calculations, and thusto process more and more of video frames at high resolutions. Wepropose a new pipelined structure that we called ProcessingElement (PE) to calculate the angular prediction modes, and werepeat it in three paths that our design composed of. And wepresent, in this paper, a dynamic structure to carry out thePlanar mode. This architecture supports all intra predictionmodes for 8x8 and 4x4 prediction unit sizes. The synthesis resultsshow tha…

Intra prediction[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingHEVC standardFPGA
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Predicting lorawan behavior. How machine learning can help

2020

Large scale deployments of Internet of Things (IoT) networks are becoming reality. From a technology perspective, a lot of information related to device parameters, channel states, network and application data are stored in databases and can be used for an extensive analysis to improve the functionality of IoT systems in terms of network performance and user services. LoRaWAN (Long Range Wide Area Network) is one of the emerging IoT technologies, with a simple protocol based on LoRa modulation. In this work, we discuss how machine learning approaches can be used to improve network performance (and if and how they can help). To this aim, we describe a methodology to process LoRaWAN packets a…

IoTComputer Networks and CommunicationsComputer scienceDecision treeChannel occupancy; cluster analysis; IoT; LoRa; LoRaWAN; machine learning; network optimization; prediction analysisMachine learningcomputer.software_genreChannel occupancyLoRalcsh:QA75.5-76.95network optimizationNetwork performanceProtocol (object-oriented programming)Profiling (computer programming)Artificial neural networkNetwork packetbusiness.industrySettore ING-INF/03 - TelecomunicazioniPipeline (software)LoRaWANHuman-Computer Interactionmachine learningprediction analysisArtificial intelligencelcsh:Electronic computers. Computer sciencebusinesscomputerCommunication channelcluster analysis
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Predicción de la reincidencia con delincuentes juveniles: adaptación del IGI-J

2017

[EN] The aim of this study is to determine the usefulness of the Management and Intervention Inventory for Young (IGI-J) in predicting the past recidivism in young offenders, and the implementation of appropriate intervention programs for that population. A retrospective study with a sample of 258 juvenile offenders who were serving a penal measure was performed. The instrument that evaluated the prediction of recidivism is the Youth Level of Service/Case Management Inventory (Hoge and Andrews, 2002). Its adaptation to spanish is the IGI-J (Garrido, Lopez and Silva, 2004). The results indicate that the IGI-J correctly identified 66.7% of offenders and 68.8% of non-recidivists, with an alpha…

Juvenile offenders05 social sciencesOrganic ChemistryIntervention programsIGI-JBiochemistryJuicio clínico estructuradoStructured clinical judgmentProgramas de intervenciónRecidivism prediction050501 criminologyDelincuentes juvenilesPredicción de la reincidencia0505 law
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Large eddy simulation of inertial particles dispersion in a turbulent gas-particle channel flow bounded by rough walls

2020

The purpose of this paper is to understand the capability and consistency of large eddy simulation (LES) in Eulerian–Lagrangian studies aimed at predicting inertial particle dispersion in turbulent wall-bounded flows, in the absence of ad hoc closure models in the Lagrangian equations of particle motion. The degree of improvement granted by LES models is object of debate, in terms of both accurate prediction of particle accumulation and local particle segregation; therefore, we assessed the accuracy in the prediction of the particle velocity statistics by comparison against direct numerical simulation (DNS) of a finer computational mesh, under both one-way and two-way coupling regimes. We p…

Lagrange multipliersLagrangian equationsParticle statisticsParticle statisticsVelocity controlComputational MechanicsDirect numerical simulationWall flow Accurate prediction02 engineering and technology01 natural sciencesReynolds numberSettore ICAR/01 - Idraulica010305 fluids & plasmasPhysics::Fluid Dynamicssymbols.namesake0203 mechanical engineeringEquations of motion0103 physical sciencesParticle velocityDispersionsPhysicsTurbulence modificationTurbulenceMechanical EngineeringLarge eddy simulationTwo phase flowReynolds numberMechanicsTurbulent wall-bounded flows Segregation (metallography)Open-channel flow020303 mechanical engineering & transportsParticle accumulationQuay wallssymbolsParticle segregationParticleForecastingParticle velocitiesLarge eddy simulationActa Mechanica
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Simulation of surface energy fluxes and meteorological variables using the Regional Atmospheric Modeling System (RAMS): Evaluating the impact of land…

2018

Atmospheric mesoscale numerical models are commonly used not only for research and air quality studies, but also for other related applications, such as short-term weather forecasting for atmospheric, hydrological, agricultural and ecological modelling. A key element to produce faithful simulations is the proper representation of the soil parameters used in the initialization of the corresponding mesoscale numerical model. The Regional Atmospheric Modeling System (RAMS) is used in the current study. The model code has been updated in order to permit the model to be initialized using a heterogeneous soil moisture and temperature distribution derived from land surface models. Particularly, RA…

Land coverAtmospheric ScienceNumerical weather prediction/forecasting010504 meteorology & atmospheric sciencesMeteorology0208 environmental biotechnologyWeather forecastingMesoscale meteorologyInitialization02 engineering and technologyLand covercomputer.software_genre01 natural sciencesMesoscale modellingWeather stationData assimilationFluxNetMeteorologiaLand surface modelsSurface energy fluxes0105 earth and related environmental sciencesGlobal and Planetary ChangeSoil initializationFísica de la TierraForestry020801 environmental engineeringRegional Atmospheric Modeling SystemEnvironmental scienceAgronomy and Crop Sciencecomputer
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