Statistics of opinion domains of the majority-vote model on a square lattice

The existence of juxtaposed regions of distinct cultures in spite of the fact that people's beliefs have a tendency to become more similar to each other's as the individuals interact repeatedly is a puzzling phenomenon in the social sciences. Here we study an extreme version of the frequency-dependent bias model of social influence in which an individual adopts the opinion shared by the majority of the members of its extended neighborhood, which includes the individual itself. This is a variant of the majority-vote model in which the individual retains its opinion in case there is a tie among the neighbors' opinions. We assume that the individuals are fixed in the sites of a square lattice of linear size L and that they interact with their nearest neighbors only. Within a mean-field framework, we derive the equations of motion for the density of individuals adopting a particular opinion in the single-site and pair approximations. Although the single-site approximation predicts a single opinion domain that takes over the entire lattice, the pair approximation yields a qualitatively correct picture with the coexistence of different opinion domains and a strong dependence on the initial conditions. Extensive Monte Carlo simulations indicate the existence of a rich distribution of opinion domains or clusters, the number of which grows with L(2) whereas the size of the largest cluster grows with ln L(2). The analysis of the sizes of the opinion domains shows that they obey a power-law distribution for not too large sizes but that they are exponentially distributed in the limit of very large clusters. In addition, similarly to other well-known social influence model-Axelrod's model-we found that these opinion domains are unstable to the effect of a thermal-like noise.

On the k-restricted structure ratio in planar and outerplanar graphs

A planar k-restricted structure is a simple graph whose blocks are planar and each has at most k vertices. Planar k-restricted structures are used by approximation algorithms for Maximum Weight Planar Subgraph, which motivates this work. The planar k-restricted ratio is the infimum, over simple planar graphs H, of the ratio of the number of edges in a maximum k-restricted structure subgraph of H to the number edges of H. We prove that, as k tends to infinity, the planar k-restricted ratio tends to 1/2. The same result holds for the weighted version. Our results are based on analyzing the analogous ratios for outerplanar and weighted outerplanar graphs. Here both ratios tend to 1 as k goes to infinity, and we provide good estimates of the rates of convergence, showing that they differ in the weighted from the unweighted case.

Context tree selection: A unifying view

Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

Neutron Activation Analysis: A Primary (Ratio) Method to Determine SI-Traceable Values of Element Content in Complex Samples

The metrological principles of neutron activation analysis are discussed. It has been demonstrated that this method can provide elemental amount of substance with values fully traceable to the SI. The method has been used by several laboratories worldwide in a number of CCQM key comparisons - interlaboratory comparison tests at the highest metrological level - supplying results equivalent to values from other methods for elemental or isotopic analysis in complex samples without the need to perform chemical destruction and dissolution of these samples. The CCOM accepted therefore in April 2007 the claim that neutron activation analysis should have the similar status as the methods originally listed by the CCOM as `primary methods of measurement`. Analytical characteristics and scope of application are given.

Exercise training changes IL-10/TNF-alpha ratio in the skeletal muscle of post-MI rats

Heart failure (HF) is associated with changes in the skeletal muscle (SM) which might be a consequence of the unbalanced local expression of pro- (TNF-alpha) and anti- (IL-10) inflammatory cytokines, leading to inflammation-induced myopathy, and SM wasting. This local effect of HF on SM may, on the other hand, contribute to systemic inflammation, as this tissue actively secretes cytokines. Since increasing evidence points out to an anti-inflammatory effect of exercise training, the goal of the present study was to investigate its effect in rats with HF after post-myocardial infarction (MI), with special regard to the expression of TNF-alpha and IL-10 in the soleus and extensor digitorum longus (EDL), muscles with different fiber composition. Wistar rats underwent left thoracotomy with ligation of the left coronary artery, and were randomly assigned to either a sedentary (Sham-operated and MI sedentary) or trained (Sham-operated and MI trained) group. Animals in the trained groups ran on a treadmill (0% grade at 13-20 m/min) for 60 min/day, 5 days/week, for 8-10 weeks. The training protocol was able to reverse the changes induced by MI, decreasing TNF-alpha protein (26%, P < 0.05) and mRNA (58%, P < 0.05) levels in the soleus, when compared with the sedentary MI group. Training also increased soleus IL-10 expression (2.6-fold, P < 0.001) in post-MI HF rats. As a consequence, the IL-10/TNF-alpha ratio was increased. This ""anti-inflammatory effect"" was more pronounced in the soleus than in the EDL, suggesting a fiber composition dependent response. (C) 2009 Elsevier Ltd. All rights reserved.

Influence of aggregates grading and water/cement ratio in workability and hardened properties of mortars

Mortar is the material responsible for the distribution of stresses in masonry structures. The knowledge about the fresh and hardened properties of mortar is fundamental to ensure a good performance of masonry walls. Water/cement ratio and aggregates grading are among several variables that influence physical and mechanical behaviour of mortars. An experimental program is presented in order to evaluate the influence of aggregates grading and water/cement ratio in workability and hardened properties of mortars. Eighteen compositions of mortar are prepared using three relations cement:lime:sand, two types of sand and three water/cement ratios. Specimens are analyzed through flow table test, compressive and flexural strength tests. Results indicate that the increase of water/cement ratio reduces the values of hardened properties and increases the workability. Besides, sands grading has no influence in compressive strength. On the other hand, significant differences in deformation capacity of mortars were verified with the variation of the type of sand. Finally, some correlations are presented among hardened properties and the compressive strength. (C) 2010 Elsevier Ltd. All rights reserved.

Influence of carbon sources and C/N ratio on EPS production in anaerobic sequencing batch biofilm reactors for wastewater treatment

The objective of this work was to evaluate the influence of different carbon sources and the carbon/nitrogen ratio (C/N) on the production and main composition of insoluble extracellular polymers (EPS) produced in an anaerobic sequencing batch biofilm reactor (ASBBR) with immobilized biomass in polyurethane foam. The yield of EPS was 23.6 mg/g carbon, 13.3 mg/g carbon, 9.0 mg/g carbon and 1.4 mg/g carbon when the reactor was fed with glucose, soybean oil. fat acids, and meat extract, respectively. The yield of EPS decreased from 23.6 to 2.6 mg/g carbon as the C/N ratio was decreased from 13.6 to 3.4 gC/gN, using glucose as carbon source. EPS production was not observed under strict anaerobic conditions. The results suggest that the carbon source, microaerophilic conditions and high C/N ratio favor EPS production in the ASBBR used for wastewater treatment. Cellulose was the main exopolysaccharide observed in all experimental conditions. (C) 2009 Elsevier Ltd. All rights reserved.

Slip ratio in dispersed viscous oil-water pipe flow

In this article, dispersed flow of viscous oil and water is investigated. The experimental work was performed in a 26.2-mm-i.d. 12-m-long horizontal glass pipe using water and oil (viscosity of 100 mPa s and density of 860 kg/m(3)) as test fluids. High-speed video recording and a new wire-mesh sensor based on capacitance (permittivity) measurements were used to characterize the flow. Furthermore, holdup data were obtained using quick-closing-valves technique (QCV). An interesting finding was the oil-water slip ratio greater than one for dispersed flow at high Reynolds number. Chordal phase fraction distribution diagrams and images of the holdup distribution over the pipe cross-section obtained via wire-mesh sensor indicated a significant amount of water near to the pipe wall for the three different dispersed flow patterns identified in this study: oil-in-water homogeneous dispersion (o/w H), oil-in-water non-homogeneous dispersion (o/w NH) and Dual continuous (Do/w & Dw/o). The phase slip might be explained by the existence of a water film surrounding the homogeneous mixture of oil-in-water in a hidrofilic-oilfobic pipe. (C) 2010 Elsevier Inc. All rights reserved.

Adaptive Carrier Tracking for Mars to Earth Communications During Entry, Descent, and Landing

We propose a robust and low complexity scheme to estimate and track carrier frequency from signals traveling under low signal-to-noise ratio (SNR) conditions in highly nonstationary channels. These scenarios arise in planetary exploration missions subject to high dynamics, such as the Mars exploration rover missions. The method comprises a bank of adaptive linear predictors (ALP) supervised by a convex combiner that dynamically aggregates the individual predictors. The adaptive combination is able to outperform the best individual estimator in the set, which leads to a universal scheme for frequency estimation and tracking. A simple technique for bias compensation considerably improves the ALP performance. It is also shown that retrieval of frequency content by a fast Fourier transform (FFT)-search method, instead of only inspecting the angle of a particular root of the error predictor filter, enhances performance, particularly at very low SNR levels. Simple techniques that enforce frequency continuity improve further the overall performance. In summary we illustrate by extensive simulations that adaptive linear prediction methods render a robust and competitive frequency tracking technique.

The Poisson-exponential lifetime distribution

In this paper we proposed a new two-parameters lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk problem base. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulae for its reliability and failure rate functions, quantiles and moments, including the mean and variance. A simple EM-type algorithm for iteratively computing maximum likelihood estimates is presented. The Fisher information matrix is derived analytically in order to obtaining the asymptotic covariance matrix. The methodology is illustrated on a real data set. (C) 2010 Elsevier B.V. All rights reserved.

Variability on red blood cell transfusion practices among Brazilian neonatal intensive care units

BACKGROUND: Guidelines for red blood cell (RBC) transfusions exist; however, transfusion practices vary among centers. This study aimed to analyze transfusion practices and the impact of patients and institutional characteristics on the indications of RBC transfusions in preterm infants. STUDY DESIGN AND METHODS: RBC transfusion practices were investigated in a multicenter prospective cohort of preterm infants with a birth weight of less than 1500 g born at eight public university neonatal intensive care units of the Brazilian Network on Neonatal Research. Variables associated with any RBC transfusions were analyzed by logistic regression analysis. RESULTS: Of 952 very-low-birth-weight infants, 532 (55.9%) received at least one RBC transfusion. The percentages of transfused neonates were 48.9, 54.5, 56.0, 61.2, 56.3, 47.8, 75.4, and 44.7%, respectively, for Centers 1 through 8. The number of transfusions during the first 28 days of life was higher in Center 4 and 7 than in other centers. After 28 days, the number of transfusions decreased, except for Center 7. Multivariate logistic regression analysis showed higher likelihood of transfusion in infants with late onset sepsis (odds ratio [OR], 2.8; 95% confidence interval [CI], 1.8-4.4), intraventricular hemorrhage (OR, 9.4; 95% CI, 3.3-26.8), intubation at birth (OR, 1.7; 95% CI, 1.0-2.8), need for umbilical catheter (OR, 2.4; 95% CI, 1.3-4.4), days on mechanical ventilation (OR, 1.1; 95% CI, 1.0-1.2), oxygen therapy (OR, 1.1; 95% CI, 1.0-1.1), parenteral nutrition (OR, 1.1; 95% CI, 1.0-1.1), and birth center (p < 0.001). CONCLUSIONS: The need of RBC transfusions in very-low-birth-weight preterm infants was associated with clinical conditions and birth center. The distribution of the number of transfusions during hospital stay may be used as a measure of neonatal care quality.

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.

A frailty modeling approach for parental effects in animal breeding

Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.

The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

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.