Search results for " Modeling"

showing 10 items of 2411 documents

HR3DHG version 1: modeling the spatiotemporal dynamics of mercury in the Augusta Bay (southern Italy)

2020

The biogeochemical dynamics of Hg, and specifically of its three species Hg0, HgII, and MeHg (elemental, inorganic, and organic, respectively), in the marine coastal area of Augusta Bay (southern Italy) have been explored by the high-resolution 3D Hg (HR3DHG) model, namely an advection–diffusion–reaction model for dissolved mercury in the seawater compartment coupled with a diffusion–reaction model for dissolved mercury in the pore water of sediments in which the desorption process for the sediment total mercury is taken into account. The spatiotemporal variability of the mercury concentration in both seawater ([HgD]) and the first layers of bottom sediments ([HgDsed] and [HgTsed]), as well…

Biogeochemical cycleBiogeochemical Cycleslcsh:QE1-996.5Sedimentchemistry.chemical_element3d modelHgSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Mercury (element)lcsh:GeologyPore water pressurechemistryTotal hgEnvironmental chemistryspatiotemporal dynamics environmental modeling pollutantsEnvironmental scienceSeawaterNumerical ModelingBay
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Enchytraeid population dynamics: Resource limitation and size-dependent mortality

2009

Abstract Enchytraeids are regarded as keystone soil organisms in forest ecosystems. Their abundance and biomass fluctuate widely. Predicting the consequences of anthropogenic disturbances requires an understanding of the mechanisms underlying enchytraeid population dynamics. Here I develop a simple model, which predicts that the type of dynamics is controlled by resource input rate. If fungal resource input is a discrete event once a year, an exponential growth phase is followed by starvation and sharp decline of enchytraeid abundance. Model simulations with three different forcing functions were compared to field data. Initial parameter values were obtained from various independent sources…

Biomass (ecology)education.field_of_studyEcologyEcological ModelingPopulationSimulation modelingBiologyAtmospheric sciencesStability (probability)Residual sum of squaresExponential growthAbundance (ecology)Forest ecologyeducationEcological Modelling
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Bicausative matrices to measure structural change: Are they a good tool?

1999

The causative-matrix method to analyze temporal change assumes that a matrix transforms one Markovian transition matrix into another by a left multiplication of the first matrix; the method is demand-driven when applied to input-output economics. An extension is presented without assuming the demand-driven or supply-driven hypothesis. Starting from two flow matrices X and Y, two diagonal matrices are searched, one premultiplying and the second postmultiplying X, to obtain a result the closer as possible to Y by least squares. The paper proves that the method is deceptive because the diagonal matrices are unidentified and the interpretation of results is unclear. Keywords : Input-Output ; Ch…

BiproportionBicausativePure mathematicsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelsjel:C63jel:C67JEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisLeast squaresMeasure (mathematics)Interpretation (model theory)JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingSylvester's law of inertiaMatrix (mathematics)Diagonal matrixStatisticsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceGeneral Environmental ScienceMathematicsJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelseconomic theoryhumanities social sciencessciences humaines et socialesStochastic matrixStructural ChangeGeneral Social Scienceseconomics[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D57CausativeJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingChaosMultiplicationThe Annals of Regional Science
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Forecast Output Coincidence and Biproportion: Two Criteria to Determine the Orientation of an Economy. Comparison for France (1980-1997)

2002

International audience; The method of forecast output coincidence used to determine if sectors are demand-sided or supply-sided in an input-output framework mixes two effects, the structural effect (choosing between demand and supply side models) and the effect of an exogenous factor (final demand or added-value). The note recalls that another method is possible, the comparison of the stability of technical and allocation coefficients, generalized by the biproportional filter: if for a sector, after biproportional filtering, column coefficients are more stable than row coefficients, then this sector is declared as not supply-sided (but one cannot decide that it is demand-sided anyway), and …

BiproportionEconomics and EconometricsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsSupplyChangeJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisStability (probability)Column (database)CoincidenceSupply and demandMicroeconomicsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingEconometricsEconomicsDemandJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceInput/outputJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsOrientation (computer vision)Exogenous factorFilter (signal processing)[SHS.ECO]Humanities and Social Sciences/Economics and FinanceJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingInput-OutputRAS
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A biproportional filter to compare technical and allocation coefficient variations

1997

International audience; In input-output analysis there are two alternate possibilities between Leontief's mechanism (fixed technical coefficients) and Ghosh's mechanism (fixed allocation coefficients). Testing the long term consistency of these mechanisms entails comparing input-output matrices over time. This paper challenges the value of proportional filters (separate comparison of column and row coefficients) and introduces the biproportional filter which allows simultaneous comparison of column and rows. An application is proposed using French input-output tables for 1980 and 1993. The stability of column coefficients cannot be taken for granted and generally, for any sector, both rows …

BiproportionSupply-drivenJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsChangeJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisEnvironmental Science (miscellaneous)DevelopmentRow and column spacesStability (probability)Column (database)Consistency (statistics)Demand-drivenStatisticsComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONApplied mathematicsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceMathematicsInput/outputJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Models[SHS.ECO]Humanities and Social Sciences/Economics and FinanceTerm (time)Input-OutputFilter (video)RowRAS
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Remodelling of biological parameters during human ageing: evidence for complex regulation in longevity and in type 2 diabetes.

2013

Factor structure analyses have revealed the presence of specific biological system markers in healthy humans and diseases. However, this type of approach in very old persons and in type 2 diabetes (T2DM) is lacking. A total sample of 2,137 Italians consisted of two groups: 1,604 healthy and 533 with T2DM. Age (years) was categorized as adults (≤65), old (66-85), oldest old (>85-98) and centenarians (≥99). Specific biomarkers of routine haematological and biochemical testing were tested across each age group. Exploratory factorial analysis (EFA) by principal component method with Varimax rotation was used to identify factors including related variables. Structural equation modelling (SEM) wa…

Blood GlucoseMaleGerontologyAgingAgeing Diabetes longevityPhysiologyType 2 diabetescentenarianHemoglobinsLeukocyte CountAged 80 and overPrincipal Component AnalysisHematologic TestsbiologyGeneral MedicineMiddle AgedExplained variationExploratory factor analysisexploratory factor analysiC-Reactive ProteinCholesteroldiabetic patientsItalyFemaleAnalysis of varianceAdultSTRUCTURAL EQUATION MODELINGAdolescentVarimax rotationLongevityAGEINGArticlemedicineHumansTriglyceridesAgedSettore MED/04 - Patologia GeneraleAnalysis of VarianceChi-Square DistributionC-reactive proteinFibrinogenmedicine.diseaseDiabetes Mellitus Type 2Ageingbiology.proteinGeriatrics and GerontologyFactor Analysis StatisticalChi-squared distributionBiomarkers
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A model for low-cycle fatigue in micro-structured materials

2020

A microscale formulation for low-cycle fatigue degradation in heterogeneous materials is presented. The interface traction-separation law is modelled by a cohesive zone model for low-cycle fatigue analysis, which is developed in a consistent thermodynamic framework of elastic-plastic-damage mechanics with internal variables. A specific fatigue activation condition allows to model the material degradation related to the elastic-plastic cyclic loading conditions, with tractions levels lower than the static failure condition. A moving endurance surface, in the classic framework of kinematic hardening, enables a pure elastic behaviour without any fatigue degradation for low levels of cyclic tra…

Boundary Element MethodCohesive Zone ModelingMicromechanicsLow-cycle fatigueSettore ING-IND/04 - Costruzioni E Strutture Aerospaziali
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The attitude towards boycotts: determining factors

2019

According to the theories of reasoned action and planned behavior, the precedent to any human conduct is the intention to display such conduct. People’s attitudes are one of those precedents. Our work is framed within this line of research, as it seeks to analyze and explain the main determinants of attitudes towards boycotts. Thus, we understand that consumers’ attitudes towards boycott behavior depend on three fundamental beliefs: perceived legitimacy of the behavior, ethical idealism towards such behavior, and finally, ethical relativism towards boycott behavior. We emphasize legitimacy since the relevance of legitimacy processes in the businessclient relationship lies in the validation …

Boycottlcsh:Management. Industrial managementBoycottEthical idealismEthical relativismTheory of planned behaviorGeneral Medicinelcsh:BusinessEthical relativismStructural equation modelingIdealismAction (philosophy)lcsh:HD28-70Relevance (law)lcsh:HF5001-6182PsychologySocial psychologyLegitimacyLegitimacy
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Class discovery from semi-structured EEG data for affective computing and personalisation

2017

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Many approaches to recognising emotions from metrical data such as EEG signals rely on identifying a very small number of classes and to train a classifier. The interpretation of these classes varies from a single emotion such as stress [24] to features of emotional model such as valence-arousal [4]. There are two major issues here. First classification approach limits the analysis of the data within the selected classes and is also highly dependent on training data/cycles, all of which limits generalisation. Second issue is that it does not exp…

Brain modelingComputer scienceFeature extraction02 engineering and technologyElectroencephalographyMachine learningcomputer.software_genrePersonalizationCorrelationDEAP03 medical and health sciences0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineCluster analysisAffective computingmedicine.diagnostic_testbusiness.industryElectroencephalographySelf-organizing feature mapsFeature extraction020201 artificial intelligence & image processingArtificial intelligenceEmotion recognitionbusinessClassifier (UML)computer030217 neurology & neurosurgery
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Measuring High-Order Interactions in Rhythmic Processes Through Multivariate Spectral Information Decomposition

2021

Many complex systems in physics, biology and engineering are modeled as dynamical networks and described using multivariate time series analysis. Recent developments have shown that the emergent dynamics of a network system are significantly affected by interactions involving multiple network nodes which cannot be described using pairwise links. While these higher-order interactions can be probed using information-theoretic measures, a rigorous framework to describe them in the frequency domain is still lacking. This work presents an approach for the spectral decomposition of multivariate information measures, capable of identifying higher-order synergistic and redundant interactions betwee…

Brain modelingMultivariate statisticsTechnology and EngineeringGeneral Computer ScienceTime series analysiComplex systemTIME-SERIESHEART-RATETime series analysisEEG analysisInformation theoryMOTOR IMAGERYMatrix decompositionCouplingFrequency-domain analysiRedundancyelectronic oscillatorsRedundancy (engineering)General Materials ScienceNETWORKTime domainFrequency-domain analysissignal processingTEMPERATUREParametric statisticsinformation theoryPhysicsFEEDBACKGeneral Engineeringclimate dynamicsTime measurementspectral analysisTK1-9971Mathematics and Statisticshigh-order interactionsconnectivityFrequency domainCouplingsElectrical engineering. Electronics. Nuclear engineeringBiological systeminformation dynamicsCoherenceIEEE Access
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