Search results for "Matrix"
showing 10 items of 3205 documents
Digital simulation of multivariate earthquake ground motions
2000
In this paper a new generation procedure of multivariate earthquake ground motion is presented. The technique takes full advantage of the decomposition of the power spectral density matrix by means of its eigenvectors. The application of the method to multivariate ground accelerations shows some very interesting physical properties which allows one to obtain significant reduction of the computational effort in the generation of sample functions relative to multivariate earthquake ground motion processes. Copyright © 2000 John Wiley & Sons, Ltd.
Multivariate stochastic wave generation
1996
Abstract In this paper, for the case of the fluid particle velocity, a procedure that substantially reduces the computational effort to generate a multivariate stochastic process is proposed. It is shown that, for a fully coherent wave field, it is possible to decompose the Power Spectral Density (PSD) matrix into the eigenvectors of the matrix itself. This leads to generate each field's process as independent, and the time generation increases linearly with the processes' number in the field. A numerical example to evaluate the statistical properties, in terms of correlation and cross-correlation functions, of the processes is also presented.
Information decomposition in the frequency domain: a new framework to study cardiovascular and cardiorespiratory oscillations
2021
While cross-spectral and information-theoretic approaches are widely used for the multivariate analysis of physiological time series, their combined utilization is far less developed in the literature. This study introduces a framework for the spectral decomposition of multivariate information measures, which provides frequency-specific quantifications of the information shared between a target and two source time series and of its expansion into amounts related to how the sources contribute to the target dynamics with unique, redundant and synergistic information. The framework is illustrated in simulations of linearly interacting stochastic processes, showing how it allows us to retrieve …
On Mardia’s Tests of Multinormality
2004
Classical multivariate analysis is based on the assumption that the data come from a multivariate normal distribution. The tests of multinormality have therefore received very much attention. Several tests for assessing multinormality, among them Mardia’s popular multivariate skewness and kurtosis statistics, are based on standardized third and fourth moments. In Mardia’s construction of the affine invariant test statistics, the data vectors are first standardized using the sample mean vector and the sample covariance matrix. In this paper we investigate whether, in the test construction, it is advantageous to replace the regular sample mean vector and sample covariance matrix by their affi…
Locally optimal invariant detector for testing equality of two power spectral densities
2018
This work addresses the problem of determining whether two multivariate random time series have the same power spectral density (PSD), which has applications, for instance, in physical-layer security and cognitive radio. Remarkably, existing detectors for this problem do not usually provide any kind of optimality. Thus, we study here the existence under the Gaussian assumption of optimal invariant detectors for this problem, proving that the uniformly most powerful invariant test (UMPIT) does not exist. Thus, focusing on close hypotheses, we show that the locally most powerful invariant test (LMPIT) only exists for univariate time series. In the multivariate case, we prove that the LMPIT do…
Adaptive independent vector analysis for multi-subject complex-valued fMRI data.
2017
Abstract Background Complex-valued fMRI data can provide additional insights beyond magnitude-only data. However, independent vector analysis (IVA), which has exhibited great potential for group analysis of magnitude-only fMRI data, has rarely been applied to complex-valued fMRI data. The main challenges in this application include the extremely noisy nature and large variability of the source component vector (SCV) distribution. New method To address these challenges, we propose an adaptive fixed-point IVA algorithm for analyzing multiple-subject complex-valued fMRI data. We exploited a multivariate generalized Gaussian distribution (MGGD)- based nonlinear function to match varying SCV dis…
Two Antigenic Peptides from Genes m123 and m164 of Murine Cytomegalovirus Quantitatively Dominate CD8 T-Cell Memory in the H-2 d Haplotype
2001
ABSTRACT The importance of CD8 T cells for the control of cytomegalovirus (CMV) infection has raised interest in the identification of immunogenic viral proteins as candidates for vaccination and cytoimmunotherapy. The final aim is to determine the viral “immunome” for any major histocompatibility complex class I molecule by antigenicity screening of proteome-derived peptides. For human CMV, there is a limitation to this approach: the T cells used as responder cells for peptide screening are usually memory cells that have undergone in vivo selection. On this basis, pUL83 (pp65) and pUL123 (IE1 or pp68 to -72) were classified as immunodominant proteins. It is an open question whether this li…
Identification of a Kd-restricted antigenic peptide encoded by murine cytomegalovirus early gene M84
2000
The two sister cytomegaloviruses (CMVs), human and murine CMV, have both evolved immune evasion functions that interfere with the major histocompatibility complex class I (MHC-I) pathway of antigen processing and presentation and are effectual in the early (E) phase of virus gene expression. However, studies on murine CMV have shown that E-phase immune evasion is leaky. An E-phase protein involved in immune evasion, namely m04-gp34, was found to simultaneously account for an antigenic peptide presented by the MHC-I molecule Dd. Recent work has demonstrated the induction of protective immunity specific for the E-phase protein M84-p65, one of two murine CMV homologues of the human CMV matrix …
Defective stromal remodeling and neutrophil extracellular traps in lymphoid tissues favor the transition from autoimmunity to lymphoma
2013
Abstract Altered expression of matricellular proteins can become pathogenic in the presence of persistent perturbations in tissue homeostasis. Here, we show that autoimmunity associated with Fas mutation was exacerbated and transitioned to lymphomagenesis in the absence of SPARC (secreted protein acidic rich in cysteine). The absence of SPARC resulted in defective collagen assembly, with uneven compartmentalization of lymphoid and myeloid populations within secondary lymphoid organs (SLO), and faulty delivery of inhibitory signals from the extracellular matrix. These conditions promoted aberrant interactions between neutrophil extracellular traps and CD5+ B cells, which underwent malignant …
G.P.199
2014
Our group has recently derived skeletal muscle from dermis-derived cells, by using an extracellular matrix that recreates the myogenic niche. After one week of differentiation, we observed isolated, twitching myotubes followed by spontaneous contractions of the entire tissue-engineered muscle construct. In vitro engineered myofibers expressed canonical markers, ultrastructure and electrophysiological characteristics of skeletal muscle. Interestingly, after one-month engineered muscle constructs showed progressive degradation of the myofibers concomitant with fatty infiltration, paralleling the natural course of muscular degeneration. However, we do not yet know how dermis-resident precursor…