Search results for "density [energy]"

showing 10 items of 138 documents

A semiparametric approach to estimate reference curves for biophysical properties of the skin

2006

Reference curves which take one covariable into account such as the age, are often required in medicine, but simple systematic and efficient statistical methods for constructing them are lacking. Classical methods are based on parametric fitting (polynomial curves). In this chapter, we describe a new methodology for the estimation of reference curves for data sets, based on nonparametric estimation of conditional quantiles. The derived method should be applicable to all clinical or more generally biological variables that are measured on a continuous quantitative scale. To avoid the curse of dimensionality when the covariate is multidimensional, a new semiparametric approach is proposed. Th…

Statistics::TheoryKernel density estimationcomputer.software_genre01 natural sciences010104 statistics & probability0502 economics and businessCovariateSliced inverse regressionApplied mathematicsStatistics::MethodologySemiparametric regression0101 mathematics[SHS.ECO] Humanities and Social Sciences/Economics and Finance050205 econometrics MathematicsParametric statisticsDimensionality reduction05 social sciencesNonparametric statistics[ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie[SHS.ECO]Humanities and Social Sciences/Economics and Finance3. Good health[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologieC140;C630Data miningcomputerQuantile
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The purification and properties of nucleoside phosphotransferase from mucosa of chicken intestine

1984

Abstract (1) Nucleoside phosphotransferase (nucleotide:3′-deoxynucleoside 5′-phosphotransferase, EC 2.7.1.77) has been purified from chicken intestine mucosa to apparent homogeneity. The enzyme is represented by a multisubunit protein at different degrees of association. It can dissociate into a compoenent with a marked fall in catalytic activity. (2) The associated forms are similar to the enzyme previously purified from chick embryo as regards: substrate specificity both with respect to nucleoside monophosphate donors and to deoxyribonucleoside acceptors; sigmoidicity in the rate curve with a variable phosphate donor; instability to heat, dilution and lowering of pH; the activating and pr…

StereochemistryCations DivalentProtein subunitBiophysicsBiologyBiochemistrychemistry.chemical_compoundStructural BiologySettore BIO/10 - BiochimicaNucleoside phosphotransferaseCentrifugation Density GradientAnimalsUreaNucleotideEnzyme kineticsIntestinal MucosaMolecular Biologychemistry.chemical_classificationNucleotidesPhosphotransferasesPhosphatenucleoside phosphotransferaseDeoxyuridineDeoxyribonucleosideMolecular WeightKineticsEnzymechemistryBiochemistryAlcoholsChromatography GelElectrophoresis Polyacrylamide GelChickens
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Studies on sea urchin oocytes. II. Synthesis of RNA during oogenesis.

1972

Abstract Isolated oocytes of the sea urchin Paracentrotus lividus actively incorporate 3H-uridine into RNA. Labeled RNA was analysed by sucrose gradient and acrylamide gel electrophoresis following cell fractionation. Much of the radioactivity is incorporated at the nucleolar level in the form of rRNA precursors. The kinetics of maturation of these latter suggests that this occurs at a slower rate than during embryogenesis. Other non-nucleolar RNA classes are also actively labelled and retained in the nucleus for many hours. These results are confirmed by an autoradiographic investigation.

SucroseTime FactorsBiologyCell FractionationTritiumOogenesisParacentrotus lividusbiology.animalBotanyCentrifugation Density GradientAnimalsPolyacrylamide gel electrophoresisSea urchinUridineOvumCell NucleusHistocytochemistryEmbryogenesisRNACell BiologyRibosomal RNAbiology.organism_classificationElectrophoresis DiscMolecular WeightBiochemistryRNA RibosomalSea UrchinsAutoradiographyRNAFemaleCell fractionationCell NucleolusExperimental cell research
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Echovirus 1 Endocytosis into Caveosomes Requires Lipid Rafts, Dynamin II, and Signaling EventsV⃞

2004

Binding of echovirus 1 (EV1, a nonenveloped RNA virus) to the α2β1 integrin on the cell surface is followed by endocytic internalization of the virus together with the receptor. Here, video-enhanced live microscopy revealed the rapid uptake of fluorescently labeled EV1 into mobile, intracellular structures, positive for green fluorescent protein-tagged caveolin-1. Partial colocalization of EV1 with SV40 (SV40) and cholera toxin, known to traffic via caveosomes, demonstrated that the vesicles were caveosomes. The initiation of EV1 infection was dependent on dynamin II, cholesterol, and protein phosphorylation events. Brefeldin A, a drug that prevents SV40 transport, blocked the EV1 infection…

SucroseTime FactorsvirusesEndocytic cycleDynamin IIchemistry.chemical_compoundDynamin IIPhosphorylationInternalizationCytoskeletonIn Situ HybridizationIn Situ Hybridization Fluorescencemedia_commonGenes Dominant0303 health sciencesMicroscopy Videobiology030302 biochemistry & molecular biologyArticlesBrefeldin AEndocytosisCell biologyEnterovirus B HumanCholesterolRNA ViralElectrophoresis Polyacrylamide GelProtein BindingSignal TransductionCholera Toxinmedia_common.quotation_subjectIntegrinGreen Fluorescent ProteinsImmunoblottingEndocytosisTransfectionCell Line03 medical and health sciencesCapsidMembrane MicrodomainsViral entryCentrifugation Density GradientAnimalsMolecular Biology030304 developmental biologyBinding SitesBrefeldin ACell MembraneCell BiologyKineticschemistryViral replicationMicroscopy Fluorescencebiology.protein
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Chromospheric evaporation and phase mixing of Alfvén waves in coronal loops

2020

Phase mixing of Alfv\'en waves has been studied extensively as a possible coronal heating mechanism but without the full thermodynamic consequences considered self-consistently. It has been argued that in some cases, the thermodynamic feedback of the heating could substantially affect the transverse density gradient and even inhibit the phase mixing process. In this paper, we use MHD simulations with the appropriate thermodynamical terms included to quantify the evaporation following heating by phase mixing of Alfv\'en waves in a coronal loop and the effect of this evaporation on the transverse density profile. The numerical simulations were performed using the Lare2D code. We set up a 2D l…

Sun: generalatmosphere [Sun]Magnetohydrodynamics (MHD)corona [Sun]010504 meteorology & atmospheric sciencesDensity gradientThermodynamic equilibriumT-NDASEvaporationAstrophysics01 natural sciencesAlfvén wave0103 physical sciencesgeneral [Sun]QB AstronomyAstrophysics::Solar and Stellar AstrophysicsSun: oscillations010303 astronomy & astrophysicsQCQB0105 earth and related environmental sciencesPhysicsSun: coronaoscillations [Sun]Astronomy and AstrophysicsMechanicsCoronal loopDissipationTransverse planeQC PhysicsAstrophysics - Solar and Stellar AstrophysicsSpace and Planetary SciencePhysics::Space PhysicsWavesMagnetohydrodynamicsBDCSun: atmosphere
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Applications of Kernel Methods

2009

In this chapter, we give a survey of applications of the kernel methods introduced in the previous chapter. We focus on different application domains that are particularly active in both direct application of well-known kernel methods, and in new algorithmic developments suited to a particular problem. In particular, we consider the following application fields: biomedical engineering (comprising both biological signal processing and bioinformatics), communications, signal, speech and image processing.

Support vector machineKernel methodbusiness.industryComputer scienceVariable kernel density estimationPolynomial kernelRadial basis function kernelPattern recognitionArtificial intelligenceGeometric modeling kernelTree kernelbusinessKernel principal component analysis
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Thirty years of synaptosome research.

1993

Detached synapses (synaptosomes), first isolated by the author in 1958 and identified as such in 1960, are sealed presynaptic nerve terminals often with a portion of the target cell--sometimes amounting to a complete dendritic spine--adhering to their external surface. They can be prepared in high yield from brain tissue and also in decreasing yield from spinal cord, retina, sympathetic ganglia, myenteric plexus and electric organs. They are sealed structures which, under metabolizing conditions, respire, take up oxygen and glucose, extrude Na+, accumulate K+, maintain a normal membrane potential and, on depolarization, release transmitter in a Ca(2+)-dependent manner. They thus provide an …

SynaptosomeNervous systemMembrane potentialNeurotransmitter AgentsHistologyDendritic spineGeneral NeuroscienceResearchModels NeurologicalDepolarizationCell BiologyBiologySynaptic vesicleSynapsemedicine.anatomical_structureSynapsesmedicineBiophysicsCentrifugation Density GradientAnimalsAnatomyNeuroscienceMyenteric plexusSynaptosomesJournal of neurocytology
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Learning non-linear time-scales with kernel -filters

2009

A family of kernel methods, based on the @c-filter structure, is presented for non-linear system identification and time series prediction. The kernel trick allows us to develop the natural non-linear extension of the (linear) support vector machine (SVM) @c-filter [G. Camps-Valls, M. Martinez-Ramon, J.L. Rojo-Alvarez, E. Soria-Olivas, Robust @c-filter using support vector machines, Neurocomput. J. 62(12) (2004) 493-499.], but this approach yields a rigid system model without non-linear cross relation between time-scales. Several functional analysis properties allow us to develop a full, principled family of kernel @c-filters. The improved performance in several application examples suggest…

TelecomunicacionesSupport vector machinesbusiness.industryCognitive NeuroscienceNonlinear System IdentificationPattern recognitionKernel principal component analysisComputer Science ApplicationsKernel methodMercer's KernelArtificial IntelligenceVariable kernel density estimationString kernelKernel embedding of distributionsPolynomial kernelRadial basis function kernelGamma-FiltersArtificial intelligenceTree kernelbusinessMathematicsNeurocomputing
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Event generation and statistical sampling for physics with deep generative models and a density information buffer

2021

Simulating nature and in particular processes in particle physics require expensive computations and sometimes would take much longer than scientists can afford. Here, we explore ways to a solution for this problem by investigating recent advances in generative modeling and present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but to also ensure that these events occur with the correct frequencies. We investigate the feasibility of learning the event generation and the frequency of occurrence with several generative machine learning models to produce events l…

Test data generationScienceMonte Carlo methodGeneral Physics and AstronomyFOS: Physical sciences01 natural sciencesCharacterization and analytical techniquesGeneral Biochemistry Genetics and Molecular BiologyArticleHigh Energy Physics - ExperimentHigh Energy Physics - Experiment (hep-ex)High Energy Physics - Phenomenology (hep-ph)0103 physical sciencesInformation theory and computationHigh Energy Physics010306 general physicsMultidisciplinary010308 nuclear & particles physicsEvent (computing)QStatisticsData ScienceSampling (statistics)General ChemistryDensity estimationAutoencoderHigh Energy Physics - PhenomenologyPhysics - Data Analysis Statistics and ProbabilityExperimental High Energy PhysicsAnomaly detectionAlgorithmImportance samplingData Analysis Statistics and Probability (physics.data-an)
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Proportional Small Sample Bias in Pricing Kernel Estimations

2014

Numerous empirical studies find pricing kernels that are not-monotonically decreasing; the findings are at odds with the pricing kernel being marginal utility of a risk-averse, so-called representative agent. We study in detail the common procedure which estimates the pricing kernel as the ratio of two separate density estimations. In a first step, we analyze theoretically the functional dependence for the ratio of a density to its estimated density; this cautions the reader of potential computational issues coupled with statistical techniques. In a second step, we study this quantitatively; we show that small sample biases shape the estimated pricing kernel, and that estimated pricing kern…

TheoryofComputation_MISCELLANEOUSComputer Science::Computer Science and Game TheoryVariable kernel density estimationStochastic discount factorKernel (statistics)StatisticsKernel density estimationEconomicsEconometricsKernel smootherRepresentative agentImplied volatilityOddsSSRN Electronic Journal
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