Search results for "model [interaction]"

showing 10 items of 1495 documents

Cobalt Clusters with Cubane-Type Topologies Based on Trivacant Polyoxometalate Ligands.

2016

Four novel cobalt-substituted polyoxometalates having cobalt cores exhibiting cubane or dicubane topologies have been synthesized and characterized by IR, elemental analysis, electrochemistry, UV-vis spectroscopy, X-ray single-crystal analysis, and magnetic studies. The tetracobalt(II)-substituted polyoxometalate [Co4(OH)3(H2O)6(PW9O34)](4-) (1) consists of a trilacunary [B-α-PW9O34](9-) unit which accommodates a cubane-like {Co(II)4O4} core. In the heptacobalt(II,III)-containing polyoxometalates [Co7(OH)6(H2O)6(PW9O34)2](9-) (2), [Co7(OH)6(H2O)4(PW9O34)2]n(9n-) (3), and [Co7(OH)6(H2O)6(P2W15O56)2](15-) (4), dicubane-like {Co(II)6Co(III)O8} cores are encapsulated between two heptadentate [B…

010405 organic chemistrychemistry.chemical_elementNanotechnologyType (model theory)010402 general chemistryElectrochemistry01 natural sciences0104 chemical sciencesInorganic Chemistrychemistry.chemical_compoundCrystallographychemistryCubanePolyoxometalatePhysical and Theoretical ChemistrySpectroscopyCobaltExchange modelInorganic chemistry
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Joint interpretation of seismic refraction tomography and electrical resistivity tomography by cluster analysis to detect buried cavities

2020

Abstract In the last few years, the geophysical methods of seismic refraction tomography (SRT) and electrical resistivity tomography (ERT) are among the most used geophysical techniques for the reconstruction of subsoil geometries, for the investigation of underground cavities and also for the archaeological prospecting. However, the main disadvantage of each geophysical method is the difficulty of final interpretation of the data. In order to eliminate artifacts and generally improve the reliability and accuracy of geophysical interpretation, it is useful to perform a joint approach of different geophysical methods, also introducing the a priori information. In this work, it is shown the i…

010504 meteorology & atmospheric sciences010502 geochemistry & geophysics01 natural sciencesSRT ERT Joint interpretation K-means cluster analysis Modeling CavityInterpretation (model theory)GeophysicsElectrical resistivity and conductivitySettore GEO/11 - Geofisica ApplicataCluster (physics)A priori and a posterioriTomographySeismic refractionElectrical resistivity tomographyJoint (geology)GeologySeismology0105 earth and related environmental sciences
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Photometric variability of the Be star CoRoT-ID 102761769

2010

Classical Be stars are rapid rotators of spectral type late O to early A and luminosity class V-III, wich exhibit Balmer emission lines and often a near infrared excess originating in an equatorially concentrated circumstellar envelope, both produced by sporadic mass ejection episodes. The causes of the abnormal mass loss (the so-called Be phenomenon) are as yet unknown. For the first time, we can now study in detail Be stars outside the Earth's atmosphere with sufficient temporal resolution. We investigate the variability of the Be Star CoRoT-ID 102761769 observed with the CoRoT satellite in the exoplanet field during the initial run. One low-resolution spectrum of the star was obtained wi…

010504 meteorology & atmospheric sciencesBe starFOS: Physical sciencesAstrophysicsAstrophysics::Cosmology and Extragalactic AstrophysicsType (model theory)01 natural sciencesPartícules (Física nuclear)Luminositysymbols.namesake0103 physical sciencesAstrophysics::Solar and Stellar Astrophysics010303 astronomy & astrophysicsSolar and Stellar Astrophysics (astro-ph.SR)Astrophysics::Galaxy Astrophysics0105 earth and related environmental sciencesPhysicsStellar rotationBalmer seriesAstronomy and AstrophysicsCircumstellar envelopeLight curveStarsAstrophysics - Solar and Stellar Astrophysics13. Climate actionSpace and Planetary ScienceEsteroidessymbolsAstrophysics::Earth and Planetary Astrophysics[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]
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Optimal modalities for radiative transfer-neural network estimation of canopy biophysical characteristics: Evaluation over an agricultural area with …

2011

International audience; Neural networks trained over radiative transfer simulations constitute the basis of several operational algorithms to estimate canopy biophysical variables from satellite reflectance measurements. However, only little attention was paid to the training process which has a major impact on retrieval performances. This study focused on the several modalities of the training process within neural network estimation of LAI, FCOVER and FAPAR biophysical variables. Performances were evaluated over both actual experimental observations and model simulations. The SAIL and PROSPECT radiative transfer models were used here to simulate the training and the synthetic test dataset…

010504 meteorology & atmospheric sciencesComputer scienceGaussian0211 other engineering and technologiesSoil ScienceCANOPY BIOPHYSICAL CHARACTERISTICS02 engineering and technologyNEURAL NETWORK01 natural sciencesTransfer functionsymbols.namesakeAtmospheric radiative transfer codesRadiative transferRange (statistics)Sensitivity (control systems)Computers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingArtificial neural networkGeologySigmoid functionRELATION SOL-PLANTE-ATMOSPHEREMODEL INVERSION[SDE]Environmental SciencessymbolsINDICE FOLIAIRE
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Anticipating the impact of pitfalls in kinetic biodegradation parameter estimation from substrate depletion curves of organic pollutants

2019

[EN] Accurate and reliable estimation of kinetic parameters of pollutant biodegradation processes is essential for environmental and health risk assessment. Common biodegradation models proposed in the literature, such as the nonlinear Monod equation and its simplified versions (e.g. Michaelis-Menten-like and first-order equations), are problematic in terms of accuracy of kinetic parameters due to the parameter correlation. However, a comparison between these models in terms of accuracy and reliability, related to data imprecision, has not been performed in the literature. This task is necessary, mainly because the model selection cannot be straightforward, as shown in this work. To facilit…

010504 meteorology & atmospheric sciencesComputer scienceHealth Toxicology and Mutagenesis010501 environmental sciencesToxicology01 natural sciencesRisk AssessmentModelling depletion curveMonod equationLimit (mathematics)Reliability (statistics)0105 earth and related environmental sciencesPollutantObservational errorEstimation theoryModel selectionReproducibility of ResultsModel comparisonGeneral MedicineModels TheoreticalPollutionNonlinear systemKineticsBiodegradation EnvironmentalParameter estimationsBiodegradationEnvironmental PollutantsBiochemical engineeringPitfallsAlgorithms
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Projecting Exposure to Extreme Climate Impact Events Across Six Event Categories and Three Spatial Scales

2020

Summarization: The extent and impact of climate‐related extreme events depend on the underlying meteorological, hydrological, or climatological drivers as well as on human factors such as land use or population density. Here we quantify the pure effect of historical and future climate change on the exposure of land and population to extreme climate impact events using an unprecedentedly large ensemble of harmonized climate impact simulations from the Inter‐Sectoral Impact Model Intercomparison Project phase 2b. Our results indicate that global warming has already more than doubled both the global land area and the global population annually exposed to all six categories of extreme events co…

010504 meteorology & atmospheric sciencesHYDROLOGICAL MODELSPopulation0207 environmental engineeringFLOOD RISKEnvironmental Sciences & Ecology02 engineering and technologySubtropics[SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology01 natural sciencesPopulation densityLatitudeClimate-related extreme events/dk/atira/pure/sustainabledevelopmentgoals/climate_actionEarth and Planetary Sciences (miscellaneous)SDG 13 - Climate ActionMeteorology & Atmospheric SciencesBURNED AREAGLOBAL CROP PRODUCTIONGeosciences Multidisciplinary020701 environmental engineeringeducation0105 earth and related environmental sciencesGeneral Environmental ScienceEvent (probability theory)education.field_of_studyScience & TechnologyLand useGlobal warmingGlobal warmingVEGETATION MODEL ORCHIDEEGeology15. Life on landTERRESTRIAL CARBON BALANCE13. Climate actionClimatologyPhysical SciencesTROPICAL CYCLONE ACTIVITYHURRICANE INTENSITYEnvironmental scienceTropical cycloneINTERANNUAL VARIABILITYLife Sciences & BiomedicineEnvironmental SciencesINCORPORATING SPITFIRE
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Empirical and physical estimation of Canopy Water Content from CHRIS/PROBA data

2013

20 páginas, 4 tablas, 7 figuras.

010504 meteorology & atmospheric sciencesMean squared errorScience0211 other engineering and technologies02 engineering and technologyCHRIS/PROBA01 natural sciencescanopy water content;model inversion;neural networks;look up tables;empirical up-scalingmodel inversionEmpirical up-scalingAtmospheric radiative transfer codeslook up tablesRadiative transferModel inversion021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote sensingArtificial neural networkCanopy water contentQHyperspectral imagingInversion (meteorology)Sigmoid functionSpectral bandsempirical up-scaling15. Life on landneural networks[SDE]Environmental SciencesGeneral Earth and Planetary SciencesLook up tablescanopy water contentNeural networkscanopy water content; model inversion; neural networks; look up tables; empirical up-scaling; CHRIS/PROBA
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The Synergistic Impacts of Anthropogenic Stressors and COVID-19 on Aquaculture: A Current Global Perspective

2021

13 pages, 6 figures, 2 tables.-- This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License

010504 meteorology & atmospheric sciencesNatural resource economicsSocio-ecological systemsvulnerabilityVulnerabilitySARS (Disease)01 natural sciencesFood security -- Case studiesStakeholder perceptionsCOVID-19 (Disease)Aquaculturefood insecurityStakeholderPerceptionsClimate changeZoologíastakeholders perceptions2. Zero hunger04 agricultural and veterinary sciencesSARS-COV2-pandemicmultiple stressorsFood insecurityclimate change2019-20 coronavirus outbreakCoronavirus disease 2019 (COVID-19)VulnerabilityClimate changesocio-ecological systemManagement Monitoring Policy and LawAquatic Science14. Life underwaterSARS-CoV-2 pandemic ; supply chain ; food insecurity ; climate change ; multiple stressors ; vulnerability ; stakeholder perceptions ; socioecological systemsMultiple stressorssupply chainEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesFood insecuritybusiness.industryPerspective (graphical)Stressorclimate change food insecurity multiple stressors SARS-CoV-2 pandemic socio-ecological systems stakeholder perceptions supply chain vulnerabilitySocioecological systemsVulnerability model of recoveryClimatic changesSupply chain13. Climate action040102 fisheriesBusiness logistics -- Case studies0401 agriculture forestry and fisheriesEnvironmental scienceSARS-CoV-2 pandemicbusiness
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Molecular signatures of silencing suppression degeneracy from a complex RNA virus

2021

As genomic architectures become more complex, they begin to accumulate degenerate and redundant elements. However, analyses of the molecular mechanisms underlying these genetic architecture features remain scarce, especially in compact but sufficiently complex genomes. In the present study, we followed a proteomic approach together with a computational network analysis to reveal molecular signatures of protein function degeneracy from a plant virus (as virus-host protein-protein interactions). We employed affinity purification coupled to mass spectrometry to detect several host factors interacting with two proteins of Citrus tristeza virus (p20 and p25) that are known to function as RNA sil…

0106 biological sciences0301 basic medicineProteomicsCitrusInteraction NetworksPathogenesisPlant Sciencemedicine.disease_causePathology and Laboratory Medicine01 natural sciencesInteractomeBiochemistryBimolecular fluorescence complementationRNA interferenceRNA silencing supressorsCitrus tristeza virusMedicine and Health SciencesDegeneracy (biology)Protein Interaction MapsBiology (General)H20 Plant diseasesPlant ProteinsEcologybiologyPlant virusesEukaryotaArgonautePlantsSmall interfering RNANucleic acidsRNA silencingComputational Theory and MathematicsGenetic interferenceExperimental Organism SystemsModeling and SimulationProteomeArgonaute ProteinsHost-Pathogen InteractionsRNA ViralEpigeneticsResearch ArticleClosterovirusRNA virusViral proteinQH301-705.5Arabidopsis ThalianaPlant PathogensComputational biologyGenome ViralBrassicaResearch and Analysis MethodsModels BiologicalPlant Viral Pathogens03 medical and health sciencesCellular and Molecular NeuroscienceViral ProteinsModel OrganismsPlant and Algal ModelsTobaccomedicineGeneticsGenomesNon-coding RNAProtein InteractionsMolecular signaturesMolecular BiologyEcology Evolution Behavior and SystematicsPlant DiseasesHost Microbial InteractionsBiology and life sciencesMass spectrometryOrganismsComputational BiologyProteinsRNA virusPlant Pathologybiology.organism_classificationGene regulationRepressor Proteins030104 developmental biologyU30 Research methodsAnimal StudiesRNAGene expression010606 plant biology & botanyF30 Plant genetics and breeding
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Environment-sensitivity functions for gross primary productivity in light use efficiency models

2022

International audience; The sensitivity of photosynthesis to environmental changes is essential for understanding carbon cycle responses to global climate change and for the development of modeling approaches that explains its spatial and temporal variability. We collected a large variety of published sensitivity functions of gross primary productivity (GPP) to different forcing variables to assess the response of GPP to environmental factors. These include the responses of GPP to temperature; vapor pressure deficit, some of which include the response to atmospheric CO2 concentrations; soil water availability (W); light intensity; and cloudiness. These functions were combined in a full fact…

0106 biological sciencesAtmospheric Science010504 meteorology & atmospheric sciencesVapour Pressure DeficitBiomeRandomly sampled sitesPlant Ecology and Nature ConservationForcing (mathematics)04 Earth Sciences 06 Biological Sciences 07 Agricultural and Veterinary SciencesAtmospheric sciences01 natural sciences[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsFluxNetLaboratory of Geo-information Science and Remote SensingEvapotranspirationMeteorology & Atmospheric SciencesEcosystemLaboratorium voor Geo-informatiekunde en Remote SensingRadiation use efficiencySensitivity formulations0105 earth and related environmental sciencesGlobal and Planetary ChangeDiffuse fractionGlobal warmingModel equifinalityForestryModel comparison15. Life on landPE&RCLight intensity13. Climate actionEnvironmental sciencePlantenecologie en NatuurbeheerCarbon assimilationTemporal scalesAgronomy and Crop Science010606 plant biology & botany
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