Information theoretic interpretation of frequency domain connectivity measures

In order to provide adequate multivariate measures of information flow between neural structures, modified expressions of partial directed coherence (PDC) and directed transfer function (DTF), two popular multivariate connectivity measures employed in neuroscience, are introduced and their formal relationship to mutual information rates are proved.

Pitfalls driven by the sole use of local updates in dynamical

The recent claim that the exit probability (EP) of a slightly modified version of the Sznadj model is a continuous function of the initial magnetization is questioned. This result has been obtained analytically and confirmed by Monte Carlo simulations, simultaneously and independently by two different groups (EPL, 82 (2008) 18006; 18007). It stands at odds with an earlier result which yielded a step function for the EP (Europhys. Lett., 70 (2005) 705). The dispute is investigated by proving that the continuous shape of the EP is a direct outcome of a mean-field treatment for the analytical result. As such, it is most likely to be caused by finite-size effects in the simulations. The improbable alternative would be a signature of the irrelevance of fluctuations in this system. Indeed, evidence is provided in support of the stepwise shape as going beyond the mean-field level. These findings yield new insight in the physics of one-dimensional systems with respect to the validity of a true equilibrium state when using solely local update rules. The suitability and the significance to perform numerical simulations in those cases is discussed. To conclude, a great deal of caution is required when applying updates rules to describe any system especially social systems. Copyright (C) EPLA, 2011

Electrochemical and spectroscopic characterization of screen-printed gold-based electrodes modified with self-assembled monolayers and Tc85 protein

This work investigates the formation of self-assembled monolayers (SAMs) of cystamine and cystamine-glutaraldehyde on a screen-printed electrode, and the immobilization of the Tc85 protein (from Trypanosoma cruzi) on these monolayers. The methods used included infrared techniques, cyclic voltammetry, and electrochemical impedance spectroscopy. The electrochemical studies were performed at pH 6.9 in 0.1 mol L(-1) phosphate buffer solution containing Fe(CN)(6)(-3/-4) redox species. The surface coverage (0) of the electrode was 0.10 (cystamine), 0.35 (cystamine-glutaraldehyde) and 0.84 (Tc85). Interpretation of electrochemical impedance spectroscopy results was based on a charge-transfer reaction involving Fe(CN)(6)(-3/-4) species at high frequencies, followed by a diffusion through the monolayers at lower frequencies. Estimates of the electrode surface coverage, active site radius, and distance between two adjacent sites assumed that charge transfer occurred at the active sites, and that there was a planar diffusion of redox species to these sites. (C) 2009 Elsevier B.V. All rights reserved.

A modified epidemiological model for computer viruses

Since the computer viruses pose a serious problem to individual and corporative computer systems, a lot of effort has been dedicated to study how to avoid their deleterious actions, trying to create anti-virus programs acting as vaccines in personal computers or in strategic network nodes. Another way to combat viruses propagation is to establish preventive policies based on the whole operation of a system that can be modeled with population models, similar to those that are used in epidemiological studies. Here, a modified version of the SIR (Susceptible-Infected-Removed) model is presented and how its parameters are related to network characteristics is explained. Then, disease-free and endemic equilibrium points are calculated, stability and bifurcation conditions are derived and some numerical simulations are shown. The relations among the model parameters in the several bifurcation conditions allow a network design minimizing viruses risks. (C) 2009 Elsevier Inc. All rights reserved.

Biogenic modified silica as a sorbent of cadmium ions: Preparation and characterization

This work describes the preparation and characterization of biogenic modified silica from rice hull ash and its use as a sorbent of cadmium ions. Thus, an agro-industrial residue has been used to produce a new adsorbent product which is able to remove toxic elements. Mesoporous biogenic silica was obtained by alkaline extraction of sodium silicate by hydrolysis with the sol-gel process, and it was modified with salen using 1,2-dichloroethane as a spacer. The surface area of the silica was measured by nitrogen adsorption/desorption analysis. Surface modification was measured by Fourier transform infrared spectroscopy. The degree of functionalization was obtained by elemental analysis. This work showed that biogenic modified silica can be produced in aqueous media from rice hull ash using a simple method, providing an alternative method for adsorbent preparation. Thermogravimetric analysis showed that the salen-modified silica is stable up to 209 C. The modified silica displays appropriate structural characteristics for an adsorbent. The cylindrical pores, open at both ends, allow free diffusion of cadmium ions to the adsorption sites on the silica surface. The surface modification increases cadmium adsorption on the silica surface 100-fold. The salen-modified silica showed specific adsorption for Cd2+ of 44.52 mg/g SiO2 at cadmium concentration of 100 mg/l.

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 beta modified Weibull distribution

A five-parameter distribution so-called the beta modified Weibull distribution is defined and studied. The new distribution contains, as special submodels, several important distributions discussed in the literature, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among others. The new distribution can be used effectively in the analysis of survival data since it accommodates monotone, unimodal and bathtub-shaped hazard functions. We derive the moments and examine the order statistics and their moments. We propose the method of maximum likelihood for estimating the model parameters and obtain the observed information matrix. A real data set is used to illustrate the importance and flexibility of the new distribution.

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. (C) 2009 Elsevier B.V. All rights reserved.

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.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (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.

Genetic potential of a maize population from Southern Brazil for the modified convergent-divergent selection scheme

Maize (Zea mays L.) is a very important cereal to world-wide economy which is also true for Brazil, particularly in the South region. Grain yield and plant height have been chosen as important criteria by breeders and farmers from Santa Catarina State (SC), Brazil. The objective of this work was to estimate genetic-statistic parameters associated with genetic gain for grain yield and plant height, in the first cycle of convergent-divergent half-sib selection in a maize population (MPA1) cultivated by farmers within the municipality of Anchieta (SC). Three experiments were carried out in different small farms at Anchieta using low external agronomic inputs; each experiment represented independent samples of half-sib families, which were evaluated in randomized complete blocks with three replications per location. Significant differences among half-sib families were observed for both variables in all experiments. The expected responses to truncated selection of the 25% better families in each experiment were 5.1, 5.8 and 5.2% for reducing plant height and 3.9, 5.7 and 5.0% for increasing grain yield, respectively. The magnitudes of genetic-statistic parameters estimated evidenced that the composite population MPA1 exhibits enough genetic variability to be used in cyclical process of recurrent selection. There were evidences that the genetic structure of the base population MPA1, as indicated by its genetic variability, may lead to expressive changes in the traits under selection, even under low selection pressure.

Particle size and concentration of poly(epsilon-caprolactone) and adipate modified starch blend on mineralization in soils with differing textures

The objective of this study was to evaluate the effect of particle size and concentration of poly(F.-caprolactone) and adipate modified starch blend on mineralization in soils with differing textures, comparing it with polyethylene under the same experimental conditions. Two soil types were used: a Kandiudalfic Eutrudox with a clayey texture and an Arenic Hapludult with a sandy texture. The two different plastic specimens were incorporated in the form of plastic films with three increasing particle sizes and six doses, from 0 to 2.5 mg C g(-1) soil. Each plastic dose was incorporated into 200 g of soil placed in a hermetically closed jar at 28 degrees C, and incubated for a 120-day period to determine CO(2) evolution. Once again it was confirmed that polyethylene is almost non-biodegradable, in contrast to PCL/S, which can be defined as a biodegradable material. Soil texture affected the mineralization kinetics of the plastic specimens, with higher values for the clayey soil. No changes in soil microbial biomass-C or -N were observed by adding polyethylene and PCL/S to the soil. Also, no significant differences were observed on seed emergence and development of rice seedlings (Oryza sativa L.) in plastic modified soil. (C) 2009 Elsevier Ltd. All rights reserved.

Ovarian function in cows submitted to acute stress during proestrus

Studies in which ACTH was administrated in heifers after the occurrence of luteolysis showed a delay in the onset of estrus and the estrus duration was shortened. This study evaluated the effect of acute stress by road transportation on estrous behavior and ovulation, monitored by serum progesterone and cortisol concentrations in cows at the periovulatory period, using a crossover design. Eleven crossbred cows, divided into Control and Transport groups had their estrus cycle synchronized with GnRH, an intravaginal progesterone device, and cloprostenol. Thirty hours after withdrawal of the device, the animals of the Transport group were transported for 60 min by truck and those from the Control group remained at pasture. Ovarian ultrasound examination was performed every 12 h from device withdrawal until ovulation in every cow. From the day after removal of the device until ovulation estrous behavior was monitored 24 h a day. Blood samples for serum cortisol and progesterone concentrations were taken at -90, -60, 0, 30, 60 and 180 min in relation to the end of transportation. Transportation during the estrous period induced stress in cows as reflected by changes in serum concentrations of progesterone and cortisol. However, we did not detect impairment in estrus expression, estrus duration or ovulation (P>0.05). (C) 2010 Elsevier B.V. All rights reserved.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.