Search results for " Mixed"

GC-MS as a tool to study the aromatic profiles of Candida zemplinina/ Saccharomyces cerevisiae mixed fermentation wines

2013

MAST-RT0 solution of the incompressible Navier–Stokes equations in 3D complex domains

2020

A new numerical methodology to solve the 3D Navier-Stokes equations for incompressible fluids within complex boundaries and unstructured body-fitted tetrahedral mesh is presented and validated with three literature and one real-case tests. We apply a fractional time step procedure where a predictor and a corrector problem are sequentially solved. The predictor step is solved applying the MAST (Marching in Space and Time) procedure, which explicitly handles the non-linear terms in the momentum equations, allowing numerical stability for Courant number greater than one. Correction steps are solved by a Mixed Hybrid Finite Elements discretization that assumes positive distances among tetrahedr…

Infinitely many solutions for a mixed boundary value problem

2010

The existence of infinitely many solutions for a mixed boundary value problem is established. The approach is based on variational methods.

Nonlinear elliptic equations involving the p-Laplacian with mixed Dirichlet-Neumann boundary conditions

2019

In this paper, a nonlinear differential problem involving the \(p\)-Laplacian operator with mixed boundary conditions is investigated. In particular, the existence of three non-zero solutions is established by requiring suitable behavior on the nonlinearity. Concrete examples illustrate the abstract results.

A Widrow–Hoff Learning Rule for a Generalization of the Linear Auto-associator

1996

Abstract A generalization of the linear auto-associator that allows for differential importance and nonindependence of both the stimuli and the units has been described previously by Abdi (1988). This model was shown to implement the general linear model of multivariate statistics. In this note, a proof is given that the Widrow–Hoff learning rule can be similarly generalized and that the weight matrix will converge to a generalized pseudo-inverse when the learning parameter is properly chosen. The value of the learning parameter is shown to be dependent only upon the (generalized) eigenvalues of the weight matrix and not upon the eigenvectors themselves. This proof provides a unified framew…

Dealing with the Pseudo-Replication Problem in Longitudinal Data from Posidonia Oceanica Surveys: Modeling Dependence vs. Subsampling

2012

Posidonia oceanica represents the key species of the most important ecosystem in subtidal habitats of the Mediterranean Sea. Being sensitive to changes in the environment, it is considered a crucial indicator of the quality of coastal marine waters. A peculiarity of P. oceanica is the presence of reiterative modules characterizing its growth, which lend themselves to back-dating techniques, allowing for the reconstruction of past history of growth variables (annual rhizome elongation and diameter, primary production, etc.). Such back-dating techniques provide, for each sampled shoot, a longitudinal series of multivariate data; this is an instance of what Hurlbert (1984) in a seminal paper d…

Model averaging estimation of generalized linear models with imputed covariates

2015

a b s t r a c t We address the problem of estimating generalized linear models when some covariate values are missing but imputations are available to fill-in the missing values. This situation generates a bias-precision trade- off in the estimation of the model parameters. Extending the generalized missing-indicator method proposed by Dardanoni et al. (2011) for linear regression, we handle this trade-off as a problem of model uncertainty using Bayesian averaging of classical maximum likelihood estimators (BAML). We also propose a block model averaging strategy that incorporates information on the missing-data patterns and is computationally simple. An empirical application illustrates our…

Using the dglars Package to Estimate a Sparse Generalized Linear Model

2015

dglars is a publicly available R package that implements the method proposed in Augugliaro et al. (J. R. Statist. Soc. B 75(3), 471-498, 2013) developed to study the sparse structure of a generalized linear model (GLM). This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method. The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve. dglars is a publicly available R package that implements the method proposed in Augugliaro et al. (J. R. Statist. Soc. B 75(3), 471-498, 2013) developed to study the sparse structure of a generalized linear model (GLM). This method, call…

Lack of linkage between gene(s) controlling the synthesis of the seventh component of complement and the HLA region on chromosome No. 6 in man.

1976

The family of an individual was studied who lacks the seventh component of complement in his serum (C7 homozygous deficiency). Both parents are C7 heterozygousdeficient. In this investigation, the following parameters were determined: complement components in functional and immunochemical tests; HLA-A,B antigens, HLA-D (MLC) determinants; the Bf system; glyoxalase I and B cell antigens. No evidence for linkage between the immunogenetic linkage group on chromosome 6 and gene(s) controlling the synthesis of the seventh component of complement was obtained. This is in accordance with the assumption that only genes controlling components of the initiating rather than the membrane attack unit of…

A coordinated preventive care approach for healthy ageing in five European cities: A mixed methods study of process evaluation components

2019

To evaluate specific process components of the Urban Health Centres Europe (UHCE) approach; a coordinated preventive care approach aimed at healthy ageing by decreasing falls, polypharmacy, loneliness and frailty among older persons in community settings of five cities in the United Kingdom, Greece, Croatia, the Netherlands and Spain.Mixed methods evaluation of specific process components of the UHCE approach: reach of the target population, dose of the intervention actually delivered and received by participants and satisfaction and experience of main stakeholders involved in the approach.The UHCE approach intervention consisted of a preventive assessment, shared decision-making on a care …