An EM-based Semi-Parametric Mixture Model Approach to the Regression Analysis of Competing-Risks Data

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright (C) 2003 John Wiley Sons, Ltd.

Síntese e caracterização de NiO-CGO para anodo e eletrólitos sólidos e base de Céria para SOFC

The direct use of natural gas makes the Solid Oxide Fuel Cell (SOFC) potentially more competitive with the current energy conversions technologies. The Intermediate Temperature SOFC (IT-SOFC) offer several advantages over the High Temperature SOFC (HT-SOFC), which includes better thermal compatibility among components, fast start with lower energy consumption, manufacture and operation cost reduction. The CeO2 based materials are alternatives to the Yttria Stabilized Zirconia (YSZ) to application in SOFC, as they have higher ionic conductivity and less ohmic losses comparing to YSZ, and they can operate at lower temperatures (500-800°C). Ceria has been doped with a variety of cations, although, the Gd3+ has the ionic radius closest to the ideal one to form solid solution. These electrolytes based in ceria require special electrodes with a higher performance and chemical and termomechanical compatibility. In this work compounds of gadolinia-doped ceria, Ce1-xGdxO2-δ (x = 0,1; 0,2 and 0,3), used as electrolytes, were synthesized by polymeric precursors method, Pechini, as well as the composite material NiO - Ce0,9Gd0,1O1,95, used as anode, also attained by oxide mixture method, mixturing the powders of the both phases calcinated already. The materials were characterized by X ray diffraction, dilatometry and scanning electronic microscopy. The refinement of the diffraction data indicated that all the Ce1-xGdxO2-δ powders were crystallized in a unique cubic phase with fluorite structure, and the composite synthesized by Pechini method produced smaller crystallite size in comparison with the same material attained by oxide mixture method. All the produced powders had nanometric characteristics. The composite produced by Pechini method has microstructural characteristics that can increase the triple phase boundaries (TPB) in the anode, improving the cell efficiency, as well as reducing the mass transport mechanism effect that provokes anode degradation

SnO 2 ceramics with low electrical resistivity obtained by microwave sintering

The main aim of this study was to develop dense and conducting SnO 2 ceramics without precipitated phases on the grain boundaries, which was verified using field emission scanning microscopy (FE-SEM) coupled with an energy-dispersive X-ray spectroscopy (FE-SEM/EDS). Two sample groups were investigated, where the first sample group was doped with zinc while the second one was doped with cobalt. The ceramics were prepared using the oxides mixture method and the sintering was carried out in a conventional muffle oven as well as in microwave oven. The results obtained were found to be similar regarding the relative density for the two sintering methods while time and temperature gains were observed for the microwave sintering method. The relative densities obtained were nearly 95%, for the two sintering methods. Concerning the electrical characterization measurements-electric field x current density as well as the environment temperature, the ceramics obtained through the conventional sintering method presented non-ohmic behavior. For the microwave sintered ceramics, we observed an ohmic behavior with electrical resistivity of 1.3 Ωcm for the samples doped with ZnO/Nb 2O 5 and 2.5 Ωcm for that of the samples doped with CoO/Nb 2O 5. The FE-SEM/EDS results for the microwave sintered ceramics indicated a structure with a reduced number of pores and other phases segregated at the grain boundaries, which leads to a better conductive ceramic than the conventional oven sintered samples. The dilatometry analysis determined the muffle sintering temperature and the difference between the densification of cobalt and zinc oxides. The addition of niobium oxide resulted in the decrease in resistivity, which thus led us to conclude that it is possible to obtain dense ceramics with low electrical resistivity based on SnO 2 using commercial oxides by the oxides mixture technique and the microwave oven sintering method. Copyright © 2011 American Scientific Publishers All rights reserved.

The evaluation of the spatial and temporal stability of sugarcane farm performance based on yield and commercial cane sugar

In broader catchment scale investigations, there is a need to understand and ultimately exploit the spatial variation of agricultural crops for an improved economic return. In many instances, this spatial variation is temporally unstable and may be different for various crop attributes and crop species. In the Australian sugar industry, the opportunity arose to evaluate the performance of 231 farms in the Tully Mill area in far north Queensland using production information on cane yield (t/ha) and CCS ( a fresh weight measure of sucrose content in the cane) accumulated over a 12-year period. Such an arrangement of data can be expressed as a 3-way array where a farm x attribute x year matrix can be evaluated and interactions considered. Two multivariate techniques, the 3-way mixture method of clustering and the 3-mode principal component analysis, were employed to identify meaningful relationships between farms that performed similarly for both cane yield and CCS. In this context, farm has a spatial component and the aim of this analysis was to determine if systematic patterns in farm performance expressed by cane yield and CCS persisted over time. There was no spatial relationship between cane yield and CCS. However, the analysis revealed that the relationship between farms was remarkably stable from one year to the next for both attributes and there was some spatial aggregation of farm performance in parts of the mill area. This finding is important, since temporally consistent spatial variation may be exploited to improve regional production. Alternatively, the putative causes of the spatial variation may be explored to enhance the understanding of sugarcane production in the wet tropics of Australia.

Síntese e caracterização de NiO-CGO para anodo e eletrólitos sólidos e base de Céria para SOFC

The direct use of natural gas makes the Solid Oxide Fuel Cell (SOFC) potentially more competitive with the current energy conversions technologies. The Intermediate Temperature SOFC (IT-SOFC) offer several advantages over the High Temperature SOFC (HT-SOFC), which includes better thermal compatibility among components, fast start with lower energy consumption, manufacture and operation cost reduction. The CeO2 based materials are alternatives to the Yttria Stabilized Zirconia (YSZ) to application in SOFC, as they have higher ionic conductivity and less ohmic losses comparing to YSZ, and they can operate at lower temperatures (500-800°C). Ceria has been doped with a variety of cations, although, the Gd3+ has the ionic radius closest to the ideal one to form solid solution. These electrolytes based in ceria require special electrodes with a higher performance and chemical and termomechanical compatibility. In this work compounds of gadolinia-doped ceria, Ce1-xGdxO2-δ (x = 0,1; 0,2 and 0,3), used as electrolytes, were synthesized by polymeric precursors method, Pechini, as well as the composite material NiO - Ce0,9Gd0,1O1,95, used as anode, also attained by oxide mixture method, mixturing the powders of the both phases calcinated already. The materials were characterized by X ray diffraction, dilatometry and scanning electronic microscopy. The refinement of the diffraction data indicated that all the Ce1-xGdxO2-δ powders were crystallized in a unique cubic phase with fluorite structure, and the composite synthesized by Pechini method produced smaller crystallite size in comparison with the same material attained by oxide mixture method. All the produced powders had nanometric characteristics. The composite produced by Pechini method has microstructural characteristics that can increase the triple phase boundaries (TPB) in the anode, improving the cell efficiency, as well as reducing the mass transport mechanism effect that provokes anode degradation

Application of a simplified method based on regular regime approach to determine the effective moisture diffusivity of mixture of low molecular weight sugars and maltodextrin during desorption

The binary diffusivities of water in low molecular weight sugars; fructose, sucrose and a high molecular weight carbohydrate; maltodextrin (DE 11) and the effective diffusivities of water in mixtures of these sugars (sucrose, glucose, fructose) and maltodextrin (DE 11) were determined using a simplified procedure based on the Regular Regime Approach. The effective diffusivity of these mixtures exhibited both the concentration and molecular weight dependence. Surface stickiness was observed in all samples during desorption, with fructose exhibiting the highest and maltodextrin the lowest. (C) 2002 Elsevier Science Ltd. All rights reserved.

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

Optimization of solvent mixtures for extraction from bark of Schinus terebinthifolius by a statistical mixture-design technique and development of a UV-Vis spectrophotometric method for analysis of total polyphenols in the extract

A statistical mixture-design technique was used to study the effects of different solvents and their mixtures on the yield, total polyphenol content, and antioxidant capacity of the crude extracts from the bark of Schinus terebinthifolius Raddi (Anacardiaceae). The experimental results and their response-surface models showed that ternary mixtures with equal portions of all the three solvents (water, ethanol and acetone) were better than the binary mixtures in generating crude extracts with the highest yield (22.04 ± 0.48%), total polyphenol content (29.39 ± 0.39%), and antioxidant capacity (6.38 ± 0.21). An analytical method was developed and validated for the determination of total polyphenols in the extracts. Optimal conditions for the various parameters in this analytical method, namely, the time for the chromophoric reaction to stabilize, wavelength of the absorption maxima to be monitored, the reference standard and the concentration of sodium carbonate were determined to be 5 min, 780 nm, pyrogallol, and 14.06% w v-1, respectively. UV-Vis spectrophotometric monitoring of the reaction under these conditions proved the method to be linear, specific, precise, accurate, reproducible, robust, and easy to perform.

A mixture theory based method for three-dimensional modeling of reinforce concrete members with embedded crack finite elements

The paper presents a methodology to model three-dimensional reinforced concrete members by means of embedded discontinuity elements based on the Continuum Strong Discontinuous Approach (CSDA). Mixture theory concepts are used to model reinforced concrete as a 31) composite material constituted of concrete with long fibers (rebars) bundles oriented in different directions embedded in it. The effects of the rebars are modeled by phenomenological constitutive models devised to reproduce the axial non-linear behavior, as well as the bond-slip and dowel action. The paper presents the constitutive models assumed for the components and the compatibility conditions chosen to constitute the composite. Numerical analyses of existing experimental reinforced concrete members are presented, illustrating the applicability of the proposed methodology.

The full Bayesian significance test for mixture models: results in gene expression clustering

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

Thermally activated peroxydisulfate in the presence of additives: A clean method for the degradation of pollutants

The kinetics and mechanism of the thermal activation of peroxydisulfate, in the temperature range from 60 to 80 degrees C, was investigated in the presence and absence of sodium formate as an additive to turn the oxidizing capacity of the reaction mixture into a reductive one. Trichloroacetic acid, TCA, whose degradation by a reductive mechanism is well reported in the literature, was used as a probe. The chemistry of thermally activated peroxydisulfate is described by a reaction scheme involving free radical generation. The proposed mechanism is evaluated by a computer simulation of the concentration profiles obtained under different experimental conditions. In the presence of formate, SO(4)(center dot-) radicals yield CO(2)(center dot-), which are the main species available for degrading TCA. Under the latter conditions, TCA is more efficiently depleted than in the absence of formate, but otherwise identical conditions of temperature and [S(2)O(8)(2-)]. We therefore conclude that activated peroxydisulfate in the presence of formate as an additive is a convenient method for the mineralization of substrates that are refractory to oxidation. such as perchlorinated hydrocarbons and TCA. This method has the advantage that leaves no toxic residues. (C) 2009 Elsevier Ltd. All rights reserved.

Biomonitoring method for the simultaneous determination of cadmium and lead in whole blood by electrothermal atomic absorption spectrometry for assessment of environmental exposure

The aim of this work is to propose a biomonitoring method for the simultaneous determination of Cd and Pb in whole blood by simultaneous electrothermal atomic absorption spectrometry for assessment of environmental levels. A volume of 200 mu L of whole blood was diluted in 500 mu L of 0.2% (w v(-1)) Triton(R) X-100 + 2.0% (v v(-1)) HNO3. Trichloroacetic acid was added for protein precipitation and the supernatant analyzed. A mixture of 250 mu g W + 200 mu g Rh as permanent and 2.0% (w v(-1)) NH4H2PO4 as co-injected modifiers were used. Characteristic masses and limits of detections (n = 20, 3s) for Cd and Pb were 1.26 and 33 pg and 0.026 mu g L-1 and 0.65 mu g L-1, respectively. Repeatability ranged from 1.8 to 6.8% for Cd and 1.2 to 1.7% for Pb. The trueness of method was checked by the analysis of three Reference Materials: Lyphocheck(R) Whole Blood Metals Control level 1 and Seronorm(TM) Trace Elements in Whole Blood levels 1 and 2. The found concentrations presented no statistical differences at the 95% confidence level. Blood samples from 40 volunteers without occupational exposure were analyzed and the concentrations ranged from 0.13 to 0.71 mu g L-1 (0.32 +/- 0.19 mu g L-1) for Cd and 9.3 to 56.7 mu g L-1 (25.1 +/- 10.8 mu g L-1) for Pb. (C) 2007 Elsevier B.V. All rights reserved.

The Equilibrium Flux Method for the calculation of flows with non-equilbrium chemical reactions

The Equilibrium Flux Method [1] is a kinetic theory based finite volume method for calculating the flow of a compressible ideal gas. It is shown here that, in effect, the method solves the Euler equations with added pseudo-dissipative terms and that it is a natural upwinding scheme. The method can be easily modified so that the flow of a chemically reacting gas mixture can be calculated. Results from the method for a one-dimensional non-equilibrium reacting flow are shown to agree well with a conventional continuum solution. Results are also presented for the calculation of a plane two-dimensional flow, at hypersonic speed, of a dissociating gas around a blunt-nosed body.

A segmentation-based and partial-volume-compensated method for an accurate measurement of lateral ventricular volumes on T-1-weighted magnetic resonance images

Lateral ventricular volumes based on segmented brain MR images can be significantly underestimated if partial volume effects are not considered. This is because a group of voxels in the neighborhood of lateral ventricles is often mis-classified as gray matter voxels due to partial volume effects. This group of voxels is actually a mixture of ventricular cerebro-spinal fluid and the white matter and therefore, a portion of it should be included as part of the lateral ventricular structure. In this note, we describe an automated method for the measurement of lateral ventricular volumes on segmented brain MR images. Image segmentation was carried in combination of intensity correction and thresholding. The method is featured with a procedure for addressing mis-classified voxels in the surrounding of lateral ventricles. A detailed analysis showed that lateral ventricular volumes could be underestimated by 10 to 30% depending upon the size of the lateral ventricular structure, if mis-classified voxels were not included. Validation of the method was done through comparison with the averaged manually traced volumes. Finally, the merit of the method is demonstrated in the evaluation of the rate of lateral ventricular enlargement. (C) 2001 Elsevier Science Inc. All rights reserved.