Predicting the columnar-to-equiaxed transition for a distribution of nucleation undercoolings

A deterministic mathematical model for steady-state unidirectional solidification is proposed to predict the columnar-to-equiaxed transition. In the model, which is an extension to the classic model proposed by Hunt [Hunt JD. Mater Sci Eng 1984;65:75], equiaxed grains nucleate according to either a normal or a log-normal distribution of nucleation undercoolings. Growth maps are constructed, indicating either columnar or equiaxed solidification as a function of the velocity of isotherms and temperature gradient. The fields A columnar and equiaxed growth change significantly with the spread of the nucleation undercooling distribution. Increasing the spread Favors columnar solidification if the dimensionless velocity of the isotherms is larger than 1. For a velocity less than 1, however, equiaxed solidification is initially favored, but columnar solidification is enhanced for a larger increase in the spread. This behavior was confirmed by a stochastic model, which showed that an increase in the distribution spread Could change the grain structure from completely columnar to 50% columnar grains. (c) 2008 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Temporal and spatial distribution of anurans in the Pampa Region (Santa Maria, RS).

The present study aimed to determine the richness, occurrence constancy, reproductive modes. standard of abundance distribution, season of vocalization and to test correlation among climatic variables and activity of vocalization of anurans in a region of the Pampa Biome, Santa Maria, Rio Grande do Sul State. During the period of Novernber/2001 to October/2002 monthly collections were carried out utilizing the `survey at breeding site` method and examination of specimens kept in the Colecao Herpetologica do Setor de Zoologia da Universidade Federal de Santa Maria (ZUFSM). Tire Occurrence of 25 species of anurans was recorded. The anurofauna recorded represents 30% of the species known to Occur in Rio Grande do Sul, and comprises species generally associated with grasslands in this state and neighboring countries. Four reproductive modes were recorded: mode 1 (14 species: 58.3%) mode 11 and 30 (9 species` 37.5%) and mode 24 (1 species; 4.2%). The low diversification of reproductive modes is likely related to the homogeneity of the grassland habitat. Most species were constant or accessory in the Study area and the species abundance distribution patterns fit in the Broken Stick and Log-normal models. characterized by homogeneity of species abundance distribution. Most species showed great plasticity in habitat. but few were plastic in vocalization sites use. There was a weak positive correlation between species richness and precipitation. There was also a weak positive correlation between the abundance of species calling activity and maximum average temperatures. These correlations indicated that, in the study area. the abundance of calling males is more affected by the temperature, and species richness is more affected by precipitation, despite the fact that significantly higher species richness occurs during the hottest period of the year. These results showed that the climatological variables examined were not enough to explain the seasonal occurrence of species, thus the influence of other environmental variables merit to be tested in future studies.

Hedging in a discontinuous market: the barrier option

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Calidad microbiológica de las aguas de baño del embalse Conde del Guadalhorce, de Málaga (España), 2000-2005.

Background. Determine the presence and evolution of indicators microorganisms of water pollution in “Conde del Guadalhorce” reservoir, Málaga city, Spain. A second objective was to analyze pollution degree and evaluate the sanitary quality of bathing water and compliance with European Directive 76/160/CE. Method. A total of 120 water samples were collected in two bathing freshwater sites during May to September sampling period between 2000 to 2005, and the numbers of total coliforms (CT), faecal coliforms (CF) and faecal streptococci (EF) were enumerated using the membrane filtration method. We used the log-normal distribution method and calculate the logarithmic means, percentile points, ratios CF:EF, ANOVA and Pearson correlations. Results. Only two samples overcome CF limit values at Camping sampling station during 2000 year. Ratios CF:EF values were higher (> 4) during 2000 to 2002, and lower (< 0,7) during 2003 to 2005. Significant differences (ANOVA F = 3,41, ∝ < 0,01) was only observed with EF during evaluated period. There was no significant difference between concentration means at bathing water sites (ANOVA, F = 3,395, ∝ < 0,01). The counts of CT and CF were significantly correlated in Kiosko water samples, while in Camping water, significant correlation (t = 0,632, p < 0,05) was only observed with EF at the Camping station during 2000, 2003 and 2005 years. Conclusions. “Conde del Guadalhorce” reservoir showed hygienic conditions for safety bathing. Globally, water bathing quality is good. CT, CF y EF indicators were agreed with UE Directive during 2000- 2005, with exception CF at Camping station in 2000 year. CT y CF concentrations at Camping were frecuently higher than Kiosko, it could be caused to swimmers abundance and recreational activities. There was a trend towards rising EF, it could be caused to faecal pollution source of animal origin, needed to research it.

Determining the best population-level alcohol consumption model and its impact on estimates of alcohol-attributable harms.

BACKGROUND: The goals of our study are to determine the most appropriate model for alcohol consumption as an exposure for burden of disease, to analyze the effect of the chosen alcohol consumption distribution on the estimation of the alcohol Population- Attributable Fractions (PAFs), and to characterize the chosen alcohol consumption distribution by exploring if there is a global relationship within the distribution. METHODS: To identify the best model, the Log-Normal, Gamma, and Weibull prevalence distributions were examined using data from 41 surveys from Gender, Alcohol and Culture: An International Study (GENACIS) and from the European Comparative Alcohol Study. To assess the effect of these distributions on the estimated alcohol PAFs, we calculated the alcohol PAF for diabetes, breast cancer, and pancreatitis using the three above-named distributions and using the more traditional approach based on categories. The relationship between the mean and the standard deviation from the Gamma distribution was estimated using data from 851 datasets for 66 countries from GENACIS and from the STEPwise approach to Surveillance from the World Health Organization. RESULTS: The Log-Normal distribution provided a poor fit for the survey data, with Gamma and Weibull distributions providing better fits. Additionally, our analyses showed that there were no marked differences for the alcohol PAF estimates based on the Gamma or Weibull distributions compared to PAFs based on categorical alcohol consumption estimates. The standard deviation of the alcohol distribution was highly dependent on the mean, with a unit increase in alcohol consumption associated with a unit increase in the mean of 1.258 (95% CI: 1.223 to 1.293) (R2 = 0.9207) for women and 1.171 (95% CI: 1.144 to 1.197) (R2 = 0. 9474) for men. CONCLUSIONS: Although the Gamma distribution and the Weibull distribution provided similar results, the Gamma distribution is recommended to model alcohol consumption from population surveys due to its fit, flexibility, and the ease with which it can be modified. The results showed that a large degree of variance of the standard deviation of the alcohol consumption Gamma distribution was explained by the mean alcohol consumption, allowing for alcohol consumption to be modeled through a Gamma distribution using only average consumption.

Isotype distribution of anticardiolipin antibodies in systemic lupus erythematosus prospective analysis of a series of 100 patients

A prospective study of IgG and IgM isotypes of anticardiolipin antibodies (aCL) in a series of 100 patients with systemic lupus erythematosus was carried out. To determine the normal range of both isotype titres a group of 100 normal control serum samples was studied and a log-normal distribution of IgG and IgM isotypes was found. The IgG anticardiolipin antibody serum was regarded as positive if a binding index greater than 2.85 (SD 3.77) was detected and a binding index greater than 4.07 (3.90) was defined as positive for IgM anticardiolipin antibody. Twenty four patients were positive for IgG aCL, 20 for IgM aCL, and 36 for IgG or IgM aCL, or both. IgG aCL were found to have a significant association with thrombosis and thrombocytopenia, and IgM aCL with haemolytic anaemia and neutropenia. Specificity and predictive value for these clinical manifestations increased at moderate and high anticardiolipin antibody titres. In addition, a significant association was found between aCL and the presence of lupus anticoagulant. Identification of these differences in the anticardiolipin antibody isotype associations may improve the clinical usefulness of these tests, and this study confirms the good specificity and predictive value of the anticardiolipin antibody titre for these clinical manifestations.

Generalized log-gamma regression models with cure fraction

In this paper, the generalized log-gamma regression model is modified to allow the possibility that long-term survivors may be present in the data. This modification leads to a generalized log-gamma regression model with a cure rate, encompassing, as special cases, the log-exponential, log-Weibull and log-normal regression models with a cure rate typically used to model such data. The models attempt to simultaneously estimate the effects of explanatory variables on the timing acceleration/deceleration of a given event and the surviving fraction, that is, the proportion of the population for which the event never occurs. The normal curvatures of local influence are derived under some usual perturbation schemes and two martingale-type residuals are proposed to assess departures from the generalized log-gamma error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed.

Log-Burr XII regression models with censored data

In survival analysis applications, the failure rate function may frequently present a unimodal shape. In such case, the log-normal or log-logistic distributions are used. In this paper, we shall be concerned only with parametric forms, so a location-scale regression model based on the Burr XII distribution is proposed for modeling data with a unimodal failure rate function as an alternative to the log-logistic regression model. Assuming censored data, we consider a classic analysis, a Bayesian analysis and a jackknife estimator for the parameters of the proposed model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the log-logistic and log-Burr XII regression models. Besides, we use sensitivity analysis to detect influential or outlying observations, and residual analysis is used to check the assumptions in the model. Finally, we analyze a real data set under log-Buff XII regression models. (C) 2008 Published by Elsevier B.V.

Multivariate measurement error models based on scale mixtures of the skew-normal distribution

Scale mixtures of the skew-normal (SMSN) distribution is a class of asymmetric thick-tailed distributions that includes the skew-normal (SN) distribution as a special case. The main advantage of these classes of distributions is that they are easy to simulate and have a nice hierarchical representation facilitating easy implementation of the expectation-maximization algorithm for the maximum-likelihood estimation. In this paper, we assume an SMSN distribution for the unobserved value of the covariates and a symmetric scale mixtures of the normal distribution for the error term of the model. This provides a robust alternative to parameter estimation in multivariate measurement error models. Specific distributions examined include univariate and multivariate versions of the SN, skew-t, skew-slash and skew-contaminated normal distributions. The results and methods are applied to a real data set.

Using complex networks to quantify consistency in the use of words

In this paper we have quantified the consistency of word usage in written texts represented by complex networks, where words were taken as nodes, by measuring the degree of preservation of the node neighborhood. Words were considered highly consistent if the authors used them with the same neighborhood. When ranked according to the consistency of use, the words obeyed a log-normal distribution, in contrast to Zipf's law that applies to the frequency of use. Consistency correlated positively with the familiarity and frequency of use, and negatively with ambiguity and age of acquisition. An inspection of some highly consistent words confirmed that they are used in very limited semantic contexts. A comparison of consistency indices for eight authors indicated that these indices may be employed for author recognition. Indeed, as expected, authors of novels could be distinguished from those who wrote scientific texts. Our analysis demonstrated the suitability of the consistency indices, which can now be applied in other tasks, such as emotion recognition.