Search results for "curs"

showing 10 items of 1595 documents

The silicatein propeptide acts as inhibitor/modulator of self-organization during spicule axial filament formation.

2013

Silicateins are crucial enzymes that are involved in formation of the inorganic biosilica scaffold of the spicular skeleton of siliceous sponges. We show that silicatein acquires its structure-guiding and enzymatically active state by processing of silicatein from pro-silicatein to the mature enzyme. A recombinant propeptide (PROP) of silicatein from the siliceous demosponge Suberites domuncula was prepared, and antibodies were raised against the peptide. In sponge tissue, these antibodies reacted with both surface structures and the central region of the spicules. Using phage display expression, spicule-binding 12-mer peptides were identified that are rich in histidine residues. In the pre…

SpiculeProtein ConformationMolecular Sequence Data02 engineering and technologyArginineBiochemistry03 medical and health sciencesProtein structurePeptide LibraryAnimalsUreaHistidineAmino Acid SequenceProtein PrecursorsProtein precursorMolecular BiologyPeptide sequenceHistidine030304 developmental biology0303 health sciencesbiologyLysineCell Biology021001 nanoscience & nanotechnologybiology.organism_classificationCathepsinsProtein tertiary structureRecombinant ProteinsSuberites domunculaBiochemistry0210 nano-technologyPeptidesSuberitesSuberitesThe FEBS journal
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Los profesionales de la organización y gestión de actividad física y deporte en las instalaciones deportivas y entidades : características socio-demo…

2007

Este artículo pertenece al estudio realizado en la Comunidad Valenciana sobre la situación profesional de las personas que trabajan en funciones de actividad física y deporte. Primeramente se contextualiza las tareas de organización y gestión de la actividad física y deporte en el mercado laboral de la actividad física y el deporte y después se detalla aspectos específicos profesionales y técnicos de esta función laboral. Posteriormente se describe, reflexiona y concluye diversos aspectos sobre las características sociodemográficas de las personas que realizan las tareas de organización y gestión de la actividad física y deporte así como sus características formativas y las necesidad de que…

Sports facilitiesQualificationsTitulacionProfesionalesGestion ; Recursos humanos ; Profesionales ; Deporte ; Instalaciones deportivas ; TitulacionInstalaciones deportivasDeporteManagement ; Human professional resources ; Sport ; Sports facilities ; QualificationsHuman professional resources:CIENCIAS DE LA VIDA [UNESCO]ManagementGestionRecursos humanosUNESCO::CIENCIAS DE LA VIDASport
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Time delay induced effects on control of linear systems under random excitation

2001

Recursive formulas in terms of statistics of the response of linear systems with time delay under normal white noise input are developed. Two alternative methods are presented, in order to capture the time delay effects. The first is given in an approximate solution obtained by expanding the control force in a Taylor series. The second, available for the stationary solution (if it exists) gets the variance of the controlled system, with time delay in an analytical form. The efficacy loss in terms of statistics of the response is discussed in detail.

State variableMechanical EngineeringLinear systemApproximation theoryRecursive functionAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsWhite noiseVariance (accounting)White noiseCondensed Matter Physicssymbols.namesakeNuclear Energy and EngineeringControl theoryControl systemTaylor seriessymbolsDelay circuitExcitationCivil and Structural EngineeringMathematicsGroup delay and phase delayElectric excitation
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A fast and recursive algorithm for clustering large datasets with k-medians

2012

Clustering with fast algorithms large samples of high dimensional data is an important challenge in computational statistics. Borrowing ideas from MacQueen (1967) who introduced a sequential version of the $k$-means algorithm, a new class of recursive stochastic gradient algorithms designed for the $k$-medians loss criterion is proposed. By their recursive nature, these algorithms are very fast and are well adapted to deal with large samples of data that are allowed to arrive sequentially. It is proved that the stochastic gradient algorithm converges almost surely to the set of stationary points of the underlying loss criterion. A particular attention is paid to the averaged versions, which…

Statistics and ProbabilityClustering high-dimensional dataFOS: Computer and information sciencesMathematical optimizationhigh dimensional dataMachine Learning (stat.ML)02 engineering and technologyStochastic approximation01 natural sciencesStatistics - Computation010104 statistics & probabilityk-medoidsStatistics - Machine Learning[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]stochastic approximation0202 electrical engineering electronic engineering information engineeringComputational statisticsrecursive estimatorsAlmost surely[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematicsCluster analysisComputation (stat.CO)Mathematicsaveragingk-medoidsRobbins MonroApplied MathematicsEstimator[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]stochastic gradient[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]MedoidComputational MathematicsComputational Theory and Mathematicsonline clustering020201 artificial intelligence & image processingpartitioning around medoidsAlgorithm
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Fast Estimation of the Median Covariation Matrix with Application to Online Robust Principal Components Analysis

2017

International audience; The geometric median covariation matrix is a robust multivariate indicator of dispersion which can be extended without any difficulty to functional data. We define estimators, based on recursive algorithms, that can be simply updated at each new observation and are able to deal rapidly with large samples of high dimensional data without being obliged to store all the data in memory. Asymptotic convergence properties of the recursive algorithms are studied under weak conditions. The computation of the principal components can also be performed online and this approach can be useful for online outlier detection. A simulation study clearly shows that this robust indicat…

Statistics and ProbabilityComputer scienceMathematics - Statistics TheoryStatistics Theory (math.ST)01 natural sciences010104 statistics & probabilityMatrix (mathematics)Dimension (vector space)Geometric medianStochastic gradientFOS: Mathematics0101 mathematicsL1-median010102 general mathematicsEstimator[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Geometric medianCovariance[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]Functional dataMSC: 62G05 62L20Principal component analysisProjection pursuitAnomaly detectionRecursive robust estimationStatistics Probability and UncertaintyAlgorithm
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Large deviations results for subexponential tails, with applications to insurance risk

1996

AbstractConsider a random walk or Lévy process {St} and let τ(u) = inf {t⩾0 : St > u}, P(u)(·) = P(· | τ(u) < ∞). Assuming that the upwards jumps are heavy-tailed, say subexponential (e.g. Pareto, Weibull or lognormal), the asymptotic form of the P(u)-distribution of the process {St} up to time τ(u) is described as u → ∞. Essentially, the results confirm the folklore that level crossing occurs as result of one big jump. Particular sharp conclusions are obtained for downwards skip-free processes like the classical compound Poisson insurance risk process where the formulation is in terms of total variation convergence. The ideas of the proof involve excursions and path decompositions for Mark…

Statistics and ProbabilityExponential distributionRegular variationRuin probabilityExcursionRandom walkDownwards skip-free processLévy processConditioned limit theoremTotal variation convergenceCombinatoricsInsurance riskPath decompositionIntegrated tailProbability theoryModelling and SimulationExtreme value theoryMaximum domain of attractionMathematicsStochastic processApplied MathematicsExtreme value theoryRandom walkSubexponential distributionModeling and SimulationLog-normal distributionLarge deviations theory60K1060F10Stochastic Processes and their Applications
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Tridiagonality, supersymmetry and non self-adjoint Hamiltonians

2019

In this paper we consider some aspects of tridiagonal, non self-adjoint, Hamiltonians and of their supersymmetric counterparts. In particular, the problem of factorization is discussed, and it is shown how the analysis of the eigenstates of these Hamiltonians produce interesting recursion formulas giving rise to biorthogonal families of vectors. Some examples are proposed, and a connection with bi-squeezed states is analyzed.

Statistics and ProbabilityFOS: Physical sciencesGeneral Physics and Astronomy01 natural sciencesFactorization0103 physical sciences010306 general physicsSettore MAT/07 - Fisica MatematicaMathematical PhysicsEigenvalues and eigenvectorsMathematicsQuantum PhysicsTridiagonal matrix010308 nuclear & particles physicsRecursion (computer science)Statistical and Nonlinear Physicstridiagonal matriceMathematical Physics (math-ph)SupersymmetryConnection (mathematics)non self-adjoint HamiltonianAlgebrabiorthogonal basesModeling and SimulationBiorthogonal systemQuantum Physics (quant-ph)Self-adjoint operatorJournal of Physics A: Mathematical and Theoretical
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Large systems of path-repellent Brownian motions in a trap at positive temperature

2006

We study a model of $ N $ mutually repellent Brownian motions under confinement to stay in some bounded region of space. Our model is defined in terms of a transformed path measure under a trap Hamiltonian, which prevents the motions from escaping to infinity, and a pair-interaction Hamiltonian, which imposes a repellency of the $N$ paths. In fact, this interaction is an $N$-dependent regularisation of the Brownian intersection local times, an object which is of independent interest in the theory of stochastic processes. The time horizon (interpreted as the inverse temperature) is kept fixed. We analyse the model for diverging number of Brownian motions in terms of a large deviation princip…

Statistics and ProbabilityFOS: Physical scienceslarge deviationssymbols.namesakeQuantum systemFOS: MathematicsGross-Pitaevskii formula60J6560F10; 60J65; 82B10; 82B26Brownian motionMathematical PhysicsEnergy functionalMathematicsInteracting Brownian motionsStochastic process82B10Mathematical analysisProbability (math.PR)Brownian excursionMathematical Physics (math-ph)Brownian intersection local timessymbolsoccupation measure82B26Large deviations theoryStatistics Probability and UncertaintyHamiltonian (quantum mechanics)Rate functionMathematics - Probability60F10
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Fractional Brownian motion and Martingale-differences

2004

Abstract We generalize a result of Sottinen (Finance Stochastics 5 (2001) 343) by proving an approximation theorem for the fractional Brownian motion, with H> 1 2 , using martingale-differences.

Statistics and ProbabilityGeometric Brownian motionFractional Brownian motionMathematics::ProbabilityDiffusion processReflected Brownian motionMathematical analysisBrownian excursionStatistics Probability and UncertaintyHeavy traffic approximationMartingale (probability theory)Martingale representation theoremMathematicsStatistics &amp; Probability Letters
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Multivariate GARCH estimation via a Bregman-proximal trust-region method

2011

The estimation of multivariate GARCH time series models is a difficult task mainly due to the significant overparameterization exhibited by the problem and usually referred to as the "curse of dimensionality". For example, in the case of the VEC family, the number of parameters involved in the model grows as a polynomial of order four on the dimensionality of the problem. Moreover, these parameters are subjected to convoluted nonlinear constraints necessary to ensure, for instance, the existence of stationary solutions and the positive semidefinite character of the conditional covariance matrices used in the model design. So far, this problem has been addressed in the literature only in low…

Statistics and ProbabilityMathematical optimizationPolynomialComputer scienceDiagonalComputational Finance (q-fin.CP)[QFIN.CP]Quantitative Finance [q-fin]/Computational Finance [q-fin.CP]FOS: Economics and businessQuantitative Finance - Computational FinanceDimension (vector space)0502 economics and business91G70 65C60050207 economicsMathematics050205 econometrics Trust regionStatistical Finance (q-fin.ST)Series (mathematics)Applied Mathematics05 social sciencesConstrained optimizationQuantitative Finance - Statistical Finance[QFIN.ST]Quantitative Finance [q-fin]/Statistical Finance [q-fin.ST]Computational MathematicsNonlinear systemComputational Theory and MathematicsParametrizationCurse of dimensionality
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