Existence of solutions for second order partial neutral functional differential equations

We establish existence of mild solutions for a class of abstract second-order partial neutral functional differential equations with unbounded delay in a Banach space.

Almost automorphic mild solutions to some partial neutral functional-differential equations and applications

The paper considers the existence and uniqueness of almost automorphic mild solutions to some classes of first-order partial neutral functional-differential equations. Sufficient conditions for the existence and uniqueness of almost automorphic mild solutions to the above-mentioned equations are obtained. As an application, a first-order boundary value problem arising in control systems is considered. (C) 2007 Elsevier Ltd. All fights reserved.

The influence of oscillations on global existence for a class of semi-linear wave equations

The goal of this paper is to study the global existence of small data solutions to the Cauchy problem for the nonlinear wave equation u(tt) - a(t)(2) Delta u = u(t)(2) - a(t)(2)vertical bar del u vertical bar(2). In particular we are interested in statements for the 1D case. We will explain how the interplay between the increasing and oscillating behavior of the coefficient will influence global existence of small data solutions. Copyright c 2011 John Wiley & Sons, Ltd.

On a class of abstract neutral functional differential equations

By using the theory of semigroups of growth a, we discuss the existence of mild solutions for a class of abstract neutral functional differential equations. A concrete application to partial neutral functional differential equations is considered. (C) 2011 Elsevier Ltd. All rights reserved.

Existence of solutions for a class of abstract differential equations with nonlocal conditions

We discuss the existence of mild, classical and strict solutions for a class of abstract differential equations with nonlocal conditions. Our technical approach allows the study of partial differential equations with nonlocal conditions involving partial derivatives or nonlinear expressions of the solution. Some concrete applications to partial differential equations are considered. (C) 2010 Elsevier Ltd. All rights reserved.

High-breakdown linear discriminant analysis

The classification rules of linear discriminant analysis are defined by the true mean vectors and the common covariance matrix of the populations from which the data come. Because these true parameters are generally unknown, they are commonly estimated by the sample mean vector and covariance matrix of the data in a training sample randomly drawn from each population. However, these sample statistics are notoriously susceptible to contamination by outliers, a problem compounded by the fact that the outliers may be invisible to conventional diagnostics. High-breakdown estimation is a procedure designed to remove this cause for concern by producing estimates that are immune to serious distortion by a minority of outliers, regardless of their severity. In this article we motivate and develop a high-breakdown criterion for linear discriminant analysis and give an algorithm for its implementation. The procedure is intended to supplement rather than replace the usual sample-moment methodology of discriminant analysis either by providing indications that the dataset is not seriously affected by outliers (supporting the usual analysis) or by identifying apparently aberrant points and giving resistant estimators that are not affected by them.

Robust algorithms for solving stochastic partial differential equations

A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differential equations (PDEs) is described. This can be used for calculating correlation functions of systems of interacting stochastic fields. Such field equations can arise in the description of Hamiltonian and open systems in the physics of nonlinear processes, and may include multiplicative noise sources. The algorithm can be used for studying the properties of nonlinear quantum or classical field theories. The general approach is outlined and applied to a specific example, namely the quantum statistical fluctuations of ultra-short optical pulses in chi((2)) parametric waveguides. This example uses a non-diagonal coherent state representation, and correctly predicts the sub-shot noise level spectral fluctuations observed in homodyne detection measurements. It is expected that the methods used wilt be applicable for higher-order correlation functions and other physical problems as well. A stochastic differencing technique for reducing sampling errors is also introduced. This involves solving nonlinear stochastic parabolic PDEs in combination with a reference process, which uses the Wigner representation in the example presented here. A computer implementation on MIMD parallel architectures is discussed. (C) 1997 Academic Press.

Differential disease reactions on lucerne genotypes inoculated with Phytophthora medicaginis isolates from lucerne and chickpea

Stem inoculation of clonally propagated lucerne genotypes was used to assess levels of host species and genotype specialisation in Phytophthora medicaginis. A quantitative assessment of pathogenic aggressiveness of 29 P. medicaginis isolates (from lucerne and chickpea) on 9 different clonally propagated lucerne genotypes revealed no significant difference in aggressiveness between isolates from lucerne and those from chickpea on all of the lucerne genotypes. This supported previous studies which showed that P. medicaginis isolates from lucerne and chickpea were indistinguishable using random amplified polymorphic DNA (RAPD) analysis. Analysis of pathogenic aggressiveness towards individual lucerne genotypes revealed, for the first time, specificity of individual P. medicaginis isolates. This has implications for breeding for resistance to P. medicaginis in lucerne, where screening should be done using the widest range of pathogen specificity obtainable.

Applying linear time-varying constraints to econometric models: With an application to demand systems

When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.

Linear IgA dermatosis induced by pregnancy

Linear IgA disease is a rare autoimmune subepidermal bullous disorder characterized by linear IgA deposits at the epidermal basement membrane zone. According to the literature, in patients who have linear IgA disease and become pregnant, the disease tends to improve. We report a case of linear IgA disease induced by pregnancy, successfully treated with dapsone and prednisone with no adverse effects observed in the patient and her newborns.

Differential expression of mitochondrial NADH dehydrogenase in ethanol-treated rat brain: Revealed by differential display

The technique of polymerase chain reaction (PCR) differential display was used to detect alterations in gene expression after chronic alcohol administration. Male Wistar rats were treated with ethanol vapor for 14 days. The cDNA generated from mRNA isolated from the hippocampi of ethanol-treated and control animals was compared by PCR differential display. A differentially expressed cDNA fragment was used to screen mRNA samples by Northern analysis. The level of a mRNA was significantly elevated (x 2.5) in the hippocampus, but not the cortex of alcohol-treated rats up to 48 hr after withdrawal. Sequence analysis of the cDNA fragment revealed an almost perfect homology to rat mitochondrial NADH dehydrogenase subunit 4 mRNA. The selective induction of this mRNA in alcohol-treated rat brain areas suggests altered metabolic processes and possible dysfunction of the mitochondria. The technique of PCR differential display may prove useful in further analysis of gene expression during alcohol dependence and withdrawal.

Leptospirosis pulmonary haemorrhage syndrome is associated with linear deposition of immunoglobulin and complement on the alveolar surface

Leptospirosis is a zoonotic infection associated with severe diseases such as leptospirosis pulmonary haemorrhage syndrome (LPHS). The cause of pulmonary haemorrhage is unclear. Understanding which mechanisms and processes are involved in LPHS will be important in treatment regimens under development for this life-threatening syndrome. In the present study, we evaluated 30 lung specimens from LPHS patients and seven controls using histology and immunohistochemistry (detection of IgM, IgG, IgA and C3) in order to describe the pathological features associated with this syndrome. Immunoglobulin deposits were detected on the alveolar surface in 18/30 LPHS patients. Three staining patterns were observed for the immunoglobulins and C3 in the lung tissues of LPHS patients: AS, delicate linear staining adjacent to the alveolar surface, which was indicative of a membrane covering the luminal surface of type I and II pneumocyte cells; S, heterogeneous staining which was sporadically distributed along the alveolar septum; and IA, weak, focal intra-alveolar granular staining. Human LPHS is associated with individual and unique histological patterns that differ from those of other causes of pulmonary haemorrhage. In the present study, it was found that the linear deposition of immunoglobulins (IgA, IgG and IgM) and complement on the alveolar surface may play a role in the pathogenesis of pulmonary haemorrhage in human leptospirosis.

Differential expression of Egr-1-like DNA-binding activities in the naive rat brain and after excitatory stimulation

Egr-1 and related proteins are inducible transcription factors within the brain recognizing the same consensus DNA sequence. Three Egr DNA-binding activities were observed in regions of the naive rat brain. Egr-1 was present in all brain regions examined. Bands composed, at least in part, of Egr-2 and Egr-3 were present in different relative amounts in the cerebral cortex, striatum, hippocampus, thalamus, and midbrain. All had similar affinity and specificity for the Egr consensus DNA recognition sequence. Administration of the convulsants NMDA, kainate, and pentylenetetrazole differentially induced Egr-1 and Egr-2/3 DNA-binding activities in the cerebral cortex, hippocampus, and cerebellum. All convulsants induced Egr-1 and Egr-2 immunoreactivity in the cerebral cortex and hippocampus. These data indicate that the members of the Egr family are regulated at different levels and may interact at promoters containing the Egr consensus sequence to fine tune a program of gene expression resulting from excitatory stimuli.

Model for Differential Nursing Diagnosis of Alterations in Urinary Elimination Based on Fuzzy Logic

Nursing diagnoses associated with alterations of urinary elimination require different interventions, Nurses, who are not specialists, require support to diagnose and manage patients with disturbances of urine elimination. The aim of this study was to present a model based on fuzzy logic for differential diagnosis of alterations in urinary elimination, considering nursing diagnosis approved by the North American Nursing Diagnosis Association, 2001-2002. Fuzzy relations and the maximum-minimum composition approach were used to develop the system. The model performance was evaluated with 195 cases from the database of a previous study, resulting in 79.0% of total concordance and 19.5% of partial concordance, when compared with the panel of experts. Total discordance was observed in only three cases (1.5%). The agreement between model and experts was excellent (kappa = 0.98, P < .0001) or substantial (kappa = 0.69, P < .0001) when considering the overestimative accordance (accordance was considered when at least one diagnosis was equal) and the underestimative discordance (discordance was considered when at least one diagnosis was different), respectively. The model herein presented showed good performance and a simple theoretical structure, therefore demanding few computational resources.