Search results for "Gaussian network model"

showing 10 items of 13 documents

Prediction of peak shape in hydro-organic and micellar-organic liquid chromatography as a function of mobile phase composition

2007

A simple model is proposed that relates the parameters describing the peak width with the retention time, which can be easily predicted as a function of mobile phase composition. This allows the further prediction of peak shape with global errors below 5%, using a modified Gaussian model with a parabolic variance. The model is useful in the optimisation of chromatographic resolution to assess an eventual overlapping of close peaks. The dependence of peak shape with mobile phase composition was studied for mobile phases containing acetonitrile in the presence and absence of micellised surfactant (micellar-organic and hydro-organic reversed-phase liquid chromatography, RPLC). In micellar RPLC…

AcetonitrilesChromatographyResolution (mass spectrometry)ChemistryOrganic ChemistryAnalytical chemistrySodium Dodecyl SulfateGeneral MedicineFunction (mathematics)Reversed-phase chromatographyModels TheoreticalBiochemistryHigh-performance liquid chromatographyAnalytical Chemistrysymbols.namesakechemistry.chemical_compoundPulmonary surfactantPhase (matter)symbolsAcetonitrileGaussian network modelAlgorithmsChromatography High Pressure LiquidJournal of Chromatography A
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Approaches to estimate the time and height at the peak maximum in liquid chromatography based on a modified Gaussian model

2011

The time and height at the peak maximum are key parameters to describe a chromatographic peak with prediction or optimization purposes, or in the qualitative/quantitative analysis of samples. Three different approaches to estimate these parameters, using the experimental points in the peak maximum region, are here described and compared. The approaches are based on the reliable description of the peak profile using a modified Gaussian model with a parabolic variance (PVMG). In the first approach, non-linear fitting of the chromatographic data to the PVMG model is carried out to obtain the time and height at the peak maximum (Approach I). In the other two approaches, the PVMG model is linear…

Chromatography Reverse-PhaseSulfonamidesChromatographyLinear fittingChemistryElutionOrganic ChemistryNormal DistributionGeneral MedicineBiochemistryNoise (electronics)Analytical Chemistrysymbols.namesakeModels ChemicalRobustness (computer science)symbolsAlprenololGaussian network modelAlgorithmsJournal of Chromatography A
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Characterization of chromatographic peaks using the linearly modified Gaussian model. Comparison with the bi-Gaussian and the Foley and Dorsey approa…

2017

To characterize column performance in liquid chromatography, several parameters must be obtained from experimental data. These parameters can be computed through the numerical integration of the net signal to calculate the moments after subtraction of the baseline. This requires the establishment of the peak integration limits. The whole process introduces significant uncertainty. For this reason, several alternative procedures have been proposed to measure the area, mean time and variance, based on the assumption that the chromatographic peak can be described with a mathematical function. This allows the calculation of the peak position and variance making use of the values of the experime…

ChromatographyChemistryGaussianmedia_common.quotation_subject010401 analytical chemistryOrganic ChemistryGeneral MedicineVariance (accounting)010402 general chemistry01 natural sciencesBiochemistryMeasure (mathematics)Asymmetry0104 chemical sciencesAnalytical ChemistryNumerical integrationsymbols.namesakePosition (vector)Linear ModelssymbolsRange (statistics)Gaussian network modelChromatography Liquidmedia_commonJournal of Chromatography A
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Parabolic-Lorentzian modified Gaussian model for describing and deconvolving chromatographic peaks.

2002

Abstract A new mathematical model for characterising skewed chromatographic peaks, which improves the previously reported polynomially modified Gaussian (PMG) model, is proposed. The model is a Gaussian based equation whose variance is a combined parabolic-Lorentzian function. The parabola accounts for the non-Gaussian shaped peak, whereas the Lorentzian function cancels the variance growth out of the elution region, which gives rise to a problematic baseline increase in the PMG model. The proposed parabolic-Lorentzian modified Gaussian (PLMG) model makes a correct description of peaks showing a wide range of asymmetry with positive and/or negative skewness. The new model is shown to give b…

ChromatographyChromatographyModels StatisticalChemistryGaussianOrganic ChemistryCauchy distributionGeneral MedicineFunction (mathematics)BiochemistryAnalytical Chemistrysymbols.namesakeSkewnesssymbolsKurtosisDeconvolutionGaussian network modelAntibacterial agentJournal of chromatography. A
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Modelling the presence of disease under spatial misalignment using Bayesian latent Gaussian models.

2015

Modelling patterns of the spatial incidence of diseases using local environmental factors has been a growing problem in the last few years. Geostatistical models have become popular lately because they allow estimating and predicting the underlying disease risk and relating it with possible risk factors. Our approach to these models is based on the fact that the presence/absence of a disease can be expressed with a hierarchical Bayesian spatial model that incorporates the information provided by the geographical and environmental characteristics of the region of interest. Nevertheless, our main interest here is to tackle the misalignment problem arising when information about possible covar…

Health (social science)Computer scienceEpidemiologyGaussian030231 tropical medicineGeography Planning and DevelopmentBayesian probabilityNormal Distributionlcsh:G1-922Medicine (miscellaneous)Bayesian inference01 natural sciencesNormal distribution010104 statistics & probability03 medical and health sciencessymbols.namesakeBayes' theorem0302 clinical medicineCovariateStatisticsINLAHierarchical Bayesian modellingEconometricsHumansGeostatistics0101 mathematicsSpatial AnalysisStochastic ProcessesModels StatisticalHealth PolicyBayes TheoremFasciola hepaticaLaplace's methodsymbolsGaussian network modelBayesian Kriginglcsh:Geography (General)Geospatial health
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Study of elution behaviour with gradient voltage in CEC using methacrylate monolithic columns.

2010

A theoretical study on the retention behaviour and chromatographic performance of neutral solutes using a lauryl methacrylate-based monolithic column under voltage gradient mode in CEC was carried out. Through a flexible mathematical function based on a modified Gaussian model, the peak shape of compounds was firstly fitted under constant and gradient voltage. Using the peak shape parameters and retention time, the estimation of global chromatographic performance, efficiency and peak capacity under several voltage conditions was performed. The influence of voltage gradient on the separation efficiency is discussed and simple equations are presented to calculate retention and peak widths und…

Monolithic HPLC columnChemistryElutionClinical BiochemistryAnalytical chemistryTEST MixtureMethacrylateBiochemistryAnalytical Chemistrysymbols.namesakeCapillary ElectrochromatographysymbolsConstant voltageMethacrylatesConstant (mathematics)Gaussian network modelMathematicsVoltageElectrophoresis
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Evidence against a glass transition in the 10-state short range Potts glass

2002

We present the results of Monte Carlo simulations of two different 10-state Potts glasses with random nearest neighbor interactions on a simple cubic lattice. In the first model the interactions come from a \pm J distribution and in the second model from a Gaussian one, and in both cases the first two moments of the distribution are chosen to be equal to J_0=-1 and Delta J=1. At low temperatures the spin autocorrelation function for the \pm J model relaxes in several steps whereas the one for the Gaussian model shows only one. In both systems the relaxation time increases like an Arrhenius law. Unlike the infinite range model, there are only very weak finite size effects and there is no evi…

PhysicsArrhenius equationStatistical Mechanics (cond-mat.stat-mech)GaussianMonte Carlo methodAutocorrelationFOS: Physical sciencesGeneral Physics and AstronomyDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural Networksk-nearest neighbors algorithmsymbols.namesakesymbolsStatistical physicsGlass transitionGaussian network modelCondensed Matter - Statistical MechanicsSpin-½
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Drift-controlled anomalous diffusion: a solvable Gaussian model

2000

We introduce a Langevin equation characterized by a time dependent drift. By assuming a temporal power-law dependence of the drift we show that a great variety of behavior is observed in the dynamics of the variance of the process. In particular diffusive, subdiffusive, superdiffusive and stretched exponentially diffusive processes are described by this model for specific values of the two control parameters. The model is also investigated in the presence of an external harmonic potential. We prove that the relaxation to the stationary solution is power-law in time with an exponent controlled by one of model parameters.

PhysicsStatistical Mechanics (cond-mat.stat-mech)Stochastic processAnomalous diffusionFOS: Physical sciencesLangevin equationsymbols.namesakeExponential growthExponentsymbolsRelaxation (physics)Statistical physicsGaussian network modelBrownian motionCondensed Matter - Statistical MechanicsPhysical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
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On Inverse Distance Weighting in Pollution Models

2011

When evaluating the impact of pollution, measurements from remote stations are often weighted by the inverse of distance raised to some nonnegative power (IDW). This is derived from Shepard's method of spatial interpolation (1968). The paper discusses the arbitrary character of the exponent of distance and the problem of monitoring stations that are close to the reference point. From elementary laws of physics, it is determined which exponent of distance should be chosen (or its upper bound) depending on the form of pollution encountered, such as radiant pollution (including radioactivity and sound), air pollution (plumes, puffs, and motionless clouds by using the classical Gaussian model),…

PollutionMeteorologymedia_common.quotation_subjectAir pollutionmedicine.disease_causeUpper and lower boundsWeightingMultivariate interpolationsymbols.namesakeInverse distance weightingsymbolsExponentmedicineEnvironmental scienceGaussian network modelPhysics::Atmospheric and Oceanic Physicsmedia_commonSSRN Electronic Journal
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Pollution models and inverse distance weighting: some critical remarks

2013

International audience; When evaluating the impact of pollution, measurements from remote stations are often weighted by the inverse of distance raised to some nonnegative power (IDW). This is derived from Shepard's method of spatial interpolation (1968). The paper discusses the arbitrary character of the exponent of distance and the problem of monitoring stations that are close to the reference point. From elementary laws of physics, it is determined which exponent of distance should be chosen (or its upper bound) depending on the form of pollution encountered, such as radiant pollution (including radioactivity and sound), air pollution (plumes, puffs, and motionless clouds by using the cl…

PollutionMeteorologymedia_common.quotation_subjectAir pollutionmedicine.disease_causeWeightingdistance inverseUpper and lower boundsMultivariate interpolationsymbols.namesakeInverse distance weightingStatisticsmedicineIDW[ SHS.ECO ] Humanities and Social Sciences/Economies and financesComputers in Earth Sciences[SHS.ECO] Humanities and Social Sciences/Economics and FinancePhysics::Atmospheric and Oceanic Physicsmedia_commonMathematicsExponentexposant[SHS.ECO]Humanities and Social Sciences/Economics and Finance[SDE.ES]Environmental Sciences/Environmental and SocietyPollutionWeightingpondérationExponentsymbolsShepard[SDE.ES] Environmental Sciences/Environmental and SocietyGaussian network modelInverse distance[ SDE.ES ] Environmental Sciences/Environmental and SocietyInformation Systems
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