Residence time distribution in holding tubes using generalized convection model and numerical convolution for non-ideal tracer detection

A procedure is proposed for the determination of the residence time distribution (RTD) of curved tubes taking into account the non-ideal detection of the tracer. The procedure was applied to two holding tubes used for milk pasteurization in laboratory scale. Experimental data was obtained using an ionic tracer. The signal distortion caused by the detection system was considerable because of the short residence time. Four RTD models, namely axial dispersion, extended tanks in series, generalized convection and PER + CSTR association, were adjusted after convolution with the E-curve of the detection system. The generalized convection model provided the best fit because it could better represent the tail on the tracer concentration curve that is Caused by the laminar velocity profile and the recirculation regions. Adjusted model parameters were well cot-related with the now rate. (C) 2010 Elsevier Ltd. All rights reserved.

Generalized Coupled Algebraic Riccati Equations for Discrete-time Markov Jump with Multiplicative Noise Systems

In this paper we consider the existence of the maximal and mean square stabilizing solutions for a set of generalized coupled algebraic Riccati equations (GCARE for short) associated to the infinite-horizon stochastic optimal control problem of discrete-time Markov jump with multiplicative noise linear systems. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. We present a sufficient condition, based only on some positive semi-definite and kernel restrictions on some matrices, under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution fir the GCARE. We also present a solution for the discounted and long run average cost problems when the performance criterion is assumed be composed by a linear combination of an indefinite quadratic part and a linear part in the state and control variables. The paper is concluded with a numerical example for pension fund with regime switching.

A generalized multi-period mean-variance portfolio optimization with Markov switching parameters

In this paper, we deal with a generalized multi-period mean-variance portfolio selection problem with market parameters Subject to Markov random regime switchings. Problems of this kind have been recently considered in the literature for control over bankruptcy, for cases in which there are no jumps in market parameters (see [Zhu, S. S., Li, D., & Wang, S. Y. (2004). Risk control over bankruptcy in dynamic portfolio selection: A generalized mean variance formulation. IEEE Transactions on Automatic Control, 49, 447-457]). We present necessary and Sufficient conditions for obtaining an optimal control policy for this Markovian generalized multi-period meal-variance problem, based on a set of interconnected Riccati difference equations, and oil a set of other recursive equations. Some closed formulas are also derived for two special cases, extending some previous results in the literature. We apply the results to a numerical example with real data for Fisk control over bankruptcy Ill a dynamic portfolio selection problem with Markov jumps selection problem. (C) 2008 Elsevier Ltd. All rights reserved.

The generalized inverse Weibull distribution

The inverse Weibull distribution has the ability to model failure rates which are quite common in reliability and biological studies. A three-parameter generalized inverse Weibull distribution with decreasing and unimodal failure rate is introduced and studied. We provide a comprehensive treatment of the mathematical properties of the new distribution including expressions for the moment generating function and the rth generalized moment. The mixture model of two generalized inverse Weibull distributions is investigated. The identifiability property of the mixture model is demonstrated. For the first time, we propose a location-scale regression model based on the log-generalized inverse Weibull distribution for modeling lifetime data. In addition, we develop some diagnostic tools for sensitivity analysis. Two applications of real data are given to illustrate the potentiality of the proposed regression model.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

A generalized modified Weibull distribution for lifetime modeling

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution. (C) 2008 Elsevier B.V. All rights reserved.

The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Book illustration, as (intersemiotic) translation: Pictures translating words

This article examines book illustrations through the prism of Translation Studies. It mainly suggests that the pictures in illustrated books are (intersemiotic) translations of the text and that, as such, they can be analyzed making use of the same tools applied to verbal interlingual translation. The first section deals with the theoretical bases upon which illustrations can be regarded as translations, concentrating on theories of re-creation, as illustration is viewed essentially as the re-creation of the text in visual form. One of the claims in this section is that, because illustration is carried out in very similar ways as interlingual translation itself, the term ""intersemiotic"" relates more to the (obvious) difference of medium. For this reason the word is most often referred to in parentheses. The second section discusses three particular ways through which illustrations can translate the text, namely, by reproducing the textual elements literally in the picture, by emphasizing a specific narrative element, and by adapting the pictures to a certain ideology or artistic trend. The example illustrations are extracted from different. kinds of publication and media, ranging from Virgil`s Aeneid, Lewis Carroll`s Alice in Wonderland and Mark Twain`s Adventures of Huckleberry Finn to an online comic version of Shakespeare`s Hamlet.

Psychoses of epilepsy: A study comparing the clinical features of patients with focal versus generalized epilepsies

In the literature, psychosis of epilepsy (POE) has been described as one of the most frequent psychiatric comorbidities of epilepsy, occurring particularly in association with temporal lobe epilepsy. However, the presence of such psychiatric disorders among patients with idiopathic generalized epilepsies has also been mentioned. In this study, we evaluated the clinical features of psychotic disorders in a series of patients with temporal lobe epilepsy related to mesial temporal sclerosis (TLE-MTS) and juvenile myoclonic epilepsy with the aim of describing and comparing the clinical patterns of the psychotic symptoms in such frequent and important epilepsy syndromes. POE occurred most frequently in patients with TLE-MTS (P=0.01), but no differences were observed between the groups with respect to the subtypes and core symptoms of psychoses. The clinical implications of POE in both epilepsy syndromes are discussed. (C) 2011 Elsevier Inc. All rights reserved.

Novel mutations of the BSCL2 and AGPAT2 genes in 10 families with Berardinelli-Seip congenital generalized lipodystrophy syndrome

P>Context Congenital generalized lipodystrophy, or Berardinelli-Seip syndrome, is a rare autosomal recessive disease caused by mutations in either the BSCL2 or AGPAT2 genes. This syndrome is characterized by an almost complete loss of adipose tissue usually diagnosed at birth or early infancy resulting in apparent muscle hypertrophy. Common clinical features are acanthosis nigricans, hepatomegaly with or without splenomegaly and high stature. Acromegaloid features, cardiomyopathy and mental retardation can also be present. Design We investigated 11 kindreds from different geographical areas of Brazil (northeast and southeast). All coding regions as well as flanking intronic regions of both genes were examined. Polymerase chain reaction (PCR) amplifications were performed using primers described previously and PCR products were sequenced directly. Results Four AGPAT2 and two BSCL2 families harboured the same set of mutations. BSCL2 gene mutations were found in the homozygous form in four kindreds (c.412C > T c.464T > C, c.518-519insA, IVS5-2A > G), and in two kindreds compound mutations were found (c.1363C > T, c.424A > G). In the other four families, one mutation of the AGPAT2 gene was found (IVS3-1G > C and c.299G > A). Conclusions We have demonstrated four novel mutations of the BSCL2 and AGPAT2 genes responsible for Berardinelli-Seip syndrome and Brunzell syndrome (AGPAT2-related syndrome).

Translation to Portuguese and Validation of the Douleur Neuropathique 4 Questionnaire

The Douleur Neuropathique 4 (DN4) questionnaire was developed by the French Neuropathic Pain Group and is a simple and objective tool, with the ability to distinguish nociceptive from neuropathic pain. The purpose of this work was to validate the DN4 questionnaire in the Portuguese language in order to allow its use in clinical and research settings. A double-blind, accuracy study was conducted, consisting of translation, back-translation, literal evaluation, semantic equivalence, and communication with the target population. The Portuguese version of the questionnaire was applied in a sample of 101 patients with neuropathic (N = 42) or nociceptive pain (N = 59), ranked according to medical diagnosis. The reproducibility, reliability and validity of the instrument were analyzed, and showed a high diagnostic power for this version of the DN4 questionnaire. The Portuguese version of the DN4 questionnaire presented good validity and reliability, allowing it to identify neuropathic pain and neuropathic characteristics of mixed pain syndromes. Perspective: This article presents the first validated neuropathic pain questionnaire in the Portuguese language and represents a useful tool in the assessment of neuropathic pain both in the clinical setting and in population-based studies. The sensible and quick format of this instrument are key factors that will contribute to its widespread use, permitting a true recognition of patients with neuropathic pain. (C) 2010 by the American Pain Society

Neural basis of anxiolytic effects of cannabidiol (CBD) in generalized social anxiety disorder: a preliminary report

Animal and human studies indicate that cannabidiol (CBD), a major constituent of cannabis, has anxiolytic properties. However, no study to date has investigated the effects of this compound on human pathological anxiety and its underlying brain mechanisms. The aim of the present study was to investigate this in patients with generalized social anxiety disorder (SAD) using functional neuroimaging. Regional cerebral blood flow (rCBF) at rest was measured twice using (99m)Tc-ECD SPECT in 10 treatment-naive patients with SAD. In the first session, subjects were given an oral dose of CBD (400 mg) or placebo, in a double-blind procedure. In the second session, the same procedure was performed using the drug that had not been administered in the previous session. Within-subject between-condition rCBF comparisons were performed using statistical parametric mapping. Relative to placebo, CBD was associated with significantly decreased subjective anxiety (p < 0.001), reduced ECD uptake in the left parahippocampal gyrus, hippocampus, and inferior temporal gyrus (p < 0.001, uncorrected), and increased ECD uptake in the right posterior cingulate gyrus (p < 0.001, uncorrected). These results suggest that CBD reduces anxiety in SAD and that this is related to its effects on activity in limbic and paralimbic brain areas.