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.

Identification of protein coding regions using the modified Gabor-wavelet transform

An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods based on the occurrence of specific patterns of nucleotides at coding regions have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically predefined window length required for a local analysis of a DNA region. We introduce a method based on a modified Gabor-wavelet transform (MGWT) for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods by using eukaryote data sets. The results show that MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors but also makes a tool available for detailed exploration of the nucleotide occurrence.

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.

New Analytic Solution of Boltzmann Transform for Horizontal Water Infiltration into Sand

The use of the Boltzmann transform function, lambda(theta), to solve the Richards equation when the diffusivity, D, is a function of only soil water content,., is now commonplace in the literature. Nevertheless, a new analytic solution of the Boltzmann transform lambda(h) as a function of matric potential for horizontal water infiltration into a sand was derived without invoking the concept or use of D(theta). The derivation assumes that a similarity exists between the soil water retention function and the Boltzmann transform lambda(theta). The solution successfully described soil water content profiles experimentally measured for different infiltration times into a homogeneous sand and agrees with those presented by Philip in 1955 and 1957. The applicability of this solution for all soils remains open, but it is anticipated to hold for soils whose air-filled pore-size distribution before wetting is sufficiently narrow to yield a sharp increase of water content at the wetting front during infiltration. It also improves and provides a versatile alternative to the well-known analysis pioneered by Green and Ampt in 1911.

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.

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).

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.

Generalized Pustular Psoriasis in Childhood

Generalized pustular psoriasis is a rare form of psoriasis consisting of a generalized eruption of sudden onset with erythema and sterile pustules. In children, generalized pustular psoriasis is even more uncommon and may present as a severe and potentially life-threatening disorder. In this study, we present demographics, clinical aspects, treatment response, and follow-up of seven children with generalized pustular psoriasis. Retrospective study reviewing the records of seven children with generalized pustular psoriasis including age, gender, age of onset, presence of scalp and nail involvement, family history, concomitant diseases, precipitating factors, treatment modalities, and outcome. Age of first symptoms ranged from 1 month to 11 years. All patients received systemic retinoids at one time of the follow-up period. Other treatment modalities included immunosuppressive drugs, biologics, phototherapy, and sulfasalazine. Two patients presented with severe constitutional illness, secondary infection and septic shock, including one fatal outcome. All further cases have remained free of recurrences for a mean period of up to 3 years. In our study, generalized pustular psoriasis presented a wide clinical spectrum in children ranging from mild, asymptomatic outbreaks to more severe, life-threatening episodes. One fatality was observed. Children generally responded well to systemic retinoids. Further studies and long-term follow-up periods are needed to define potential trigger factors, efficacy and safety of different treatment modalities in children with generalized pustular psoriasis.

Some results on holomorphic generalized functions

In this note, we present three independent results within generalized complex analysis (in the Colombeau sense). The first of them deals with non-removable singularities; we construct a generalized function u on an open subset Omega of C(n), which is not a holomorphic generalized function on Omega but it is a holomorphic generalized function on Omega\S, where S is a hypersurface contained in Omega. The second result shows the existence of a holomorphic generalized function with prescribed values in the zero-set of a classical holomorphic function. The last result states the existence of a compactly supported solution to the (partial derivative) over bar operator.

Involvement of median raphe nucleus 5-HT1A receptors in the regulation of generalized anxiety-related defensive behaviours in rats

Changes in 5-HT1A receptor-mediated neurotransmission at the level of the median raphe nucleus (MRN) are reported to affect the expression of defensive responses that are associated with generalized anxiety disorder (e.g. inhibitory avoidance) but not with panic (e.g. escape). The objective of this study was to further explore the involvement of MRN 5-HT1A receptors in the regulation of generalized anxiety-related behaviours. Results of experiment 1 showed that intra-MRN injection of the 5-HT1A/7 receptor agonist 8-OH-DPAT (0.6 nmol) in male Wistar rats impaired the acquisition of inhibitory avoidance, without interfering with the performance of escape in the elevated T-maze test of anxiety. Pre-treatment with the 5-HT1A receptor antagonist WAY-100635 (0.18 nmol) fully blocked this anxiolytic-like effect. As revealed by experiment 2, intra-MRN injection of 8-OH-DPAT (0.6, 3 or 15 nmol) also caused anxiolytic effect in rats submitted to the light-dark transition test, another animal model that has been associated with generalized anxiety. In the same test, intra-MRN injection of WAY-100635 (0.18, 0.37 or 0.74 nmol) caused the opposite effect. Overall, the current findings support the view that MRN 5-HT neurons, through the regulation of 5-HT1A somatodendritic autoreceptors, are implicated in the regulation of generalized anxiety-associated behaviours. (C) 2008 Elsevier Ireland Ltd. All rights reserved.