Influence diagnostics in nonlinear mixed-effects elliptical models

In this work we propose and analyze nonlinear elliptical models for longitudinal data, which represent an alternative to gaussian models in the cases of heavy tails, for instance. The elliptical distributions may help to control the influence of the observations in the parameter estimates by naturally attributing different weights for each case. We consider random effects to introduce the within-group correlation and work with the marginal model without requiring numerical integration. An iterative algorithm to obtain maximum likelihood estimates for the parameters is presented, as well as diagnostic results based on residual distances and local influence [Cook, D., 1986. Assessment of local influence. journal of the Royal Statistical Society - Series B 48 (2), 133-169; Cook D., 1987. Influence assessment. journal of Applied Statistics 14 (2),117-131; Escobar, L.A., Meeker, W.Q., 1992, Assessing influence in regression analysis with censored data, Biometrics 48, 507-528]. As numerical illustration, we apply the obtained results to a kinetics longitudinal data set presented in [Vonesh, E.F., Carter, R.L., 1992. Mixed-effects nonlinear regression for unbalanced repeated measures. Biometrics 48, 1-17], which was analyzed under the assumption of normality. (C) 2009 Elsevier B.V. All rights reserved.

Inference From Aging Information

For many learning tasks the duration of the data collection can be greater than the time scale for changes of the underlying data distribution. The question we ask is how to include the information that data are aging. Ad hoc methods to achieve this include the use of validity windows that prevent the learning machine from making inferences based on old data. This introduces the problem of how to define the size of validity windows. In this brief, a new adaptive Bayesian inspired algorithm is presented for learning drifting concepts. It uses the analogy of validity windows in an adaptive Bayesian way to incorporate changes in the data distribution over time. We apply a theoretical approach based on information geometry to the classification problem and measure its performance in simulations. The uncertainty about the appropriate size of the memory windows is dealt with in a Bayesian manner by integrating over the distribution of the adaptive window size. Thus, the posterior distribution of the weights may develop algebraic tails. The learning algorithm results from tracking the mean and variance of the posterior distribution of the weights. It was found that the algebraic tails of this posterior distribution give the learning algorithm the ability to cope with an evolving environment by permitting the escape from local traps.

Investigation by Combined Solid-State NMR and SAXS Methods of the Morphology and Domain Size in Polystyrene-b-Polyethylene Oxide-b-Polystyrene Triblock Copolymers

The microphase structure of a series of polystyrene-b-polyethylene oxide-b-polystyrene (SEOS) triblock copolymers with different compositions and molecular weights has been studied by solid-state NMR, DSC, wide and small angle X-ray scattering (WAXS and SAXS). WAXS and DSC measurements were used to detect the presence of crystalline domains of polyethyleneoxide (PEO) blocks at room temperature as a function of the copolymer chemical composition. Furthermore, DSC experiments allowed the determination of the melting temperatures of the crystalline part of the PEO blocks. SAXS measurements, performed above and below the melting temperature of the PEO blocks, revealed the formation of periodic structures, but the absence or the weakness of high order reflections peaks did not allow a clear assessment of the morphological structure of the copolymers. This information was inferred by combining the results obtained by SAXS and (1)H NMR spin diffusion experiments, which also provided an estimation of the size of the dispersed phases of the nanostructured copolymers. (C) 2009 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 48:55-64,2010

Groundwater favorability map using GIS multicriteria data analysis on crystalline terrain, Sao Paulo State, Brazil

This paper presents the groundwater favorability mapping on a fractured terrain in the eastern portion of Sao Paulo State, Brazil. Remote sensing, airborne geophysical data, photogeologic interpretation, geologic and geomorphologic maps and geographic information system (GIS) techniques have been used. The results of cross-tabulation between these maps and well yield data allowed groundwater prospective parameters in a fractured-bedrock aquifer. These prospective parameters are the base for the favorability analysis whose principle is based on the knowledge-driven method. The mutticriteria analysis (weighted linear combination) was carried out to give a groundwater favorabitity map, because the prospective parameters have different weights of importance and different classes of each parameter. The groundwater favorability map was tested by cross-tabulation with new well yield data and spring occurrence. The wells with the highest values of productivity, as well as all the springs occurrence are situated in the excellent and good favorabitity mapped areas. It shows good coherence between the prospective parameters and the well yield and the importance of GIS techniques for definition of target areas for detail study and wells location. (c) 2008 Elsevier B.V. All rights reserved.

A new class of survival regression models with heavy-tailed errors: robustness and diagnostics

Birnbaum-Saunders models have largely been applied in material fatigue studies and reliability analyses to relate the total time until failure with some type of cumulative damage. In many problems related to the medical field, such as chronic cardiac diseases and different types of cancer, a cumulative damage caused by several risk factors might cause some degradation that leads to a fatigue process. In these cases, BS models can be suitable for describing the propagation lifetime. However, since the cumulative damage is assumed to be normally distributed in the BS distribution, the parameter estimates from this model can be sensitive to outlying observations. In order to attenuate this influence, we present in this paper BS models, in which a Student-t distribution is assumed to explain the cumulative damage. In particular, we show that the maximum likelihood estimates of the Student-t log-BS models attribute smaller weights to outlying observations, which produce robust parameter estimates. Also, some inferential results are presented. In addition, based on local influence and deviance component and martingale-type residuals, a diagnostics analysis is derived. Finally, a motivating example from the medical field is analyzed using log-BS regression models. Since the parameter estimates appear to be very sensitive to outlying and influential observations, the Student-t log-BS regression model should attenuate such influences. The model checking methodologies developed in this paper are used to compare the fitted models.

Isosorbide Polyesters from Enzymatic Catalysis

The synthesis of isosorbide aliphatic polyesters is demonstrated by the use of Novozym 435, a catalyst consisting of Candida antarctica lipase B immobilized on a macroporous support Several experimental procedures were tested and azeotropic distillation was most effective in removing low mass byproduct Furthermore, the use of diethyl ester derivatives of diacid comonomers gave isosorbide copolyesters with highest Isolated yield and molecular weights The length of the diacid aliphatic chain was less restrictive, but with a clear preference for longer aliphatic chains The molecular mass values of the obtained products were equivalent or higher than those obtained by nonenzymatic polymerizations, a clear illustration of the potential of enzymatic over conventional catalysis The ability of Novozym 435 to catalyze the synthesis of isosorbide polyester with weight-average molecular weights in excess of 40000 Da was unexpected given that isosorbide has two chemically distinct secondary hydroxyl groups This is the first example in which isosorbide polyesters were synthesized by enzyme catalysis, opening a large array of possibilities for this important class of biomass-derived building blocks Because these polymers are potential biomaterials the total absence of conventional Lewis acid catalyst residues represents a major Improvement in the toxicity of the material

Influence of package, type of apple juice and temperature on the production of patulin by Byssochlamys nivea and Byssochlamys fulva

Although the production of patulin in apple fruits is mainly by Penicillium expansum, there is no information on the ability of heat resistant moulds that may survive pasteurization to produce this mycotoxin in juice packages during storage and distribution. In this study, the production of patulin by Byssochlamys spp (Byssochlamys nivea FRR 4421, B. nivea ATCC 24008 and Byssochlamys fulva IOC 4518) in cloudy and clarified apple juices packaged in laminated paperboard packages or in polyethylene terephthalate bottles (PET) and stored at both 21 degrees C and 30 degrees C, was investigated. The three Byssochlamys strains were able to produce patulin in both cloudy and clarified apple juices. Overall, the lower the storage temperature, the lower the patulin levels and mycelium dry weight in the apple juices (p<0.05). The greatest variations in pH and degrees Brix were observed in the juices from which the greatest mycelium dry weights were recovered. The maximum levels of patulin recovered from the juices were ca. 150 mu g/kg at 21 degrees C and 220 mu g/kg at 30 degrees C. HPLC-UV, HPCL-DAD and mass spectrometry analyses confirmed the ability of B. fulva IOC 4518 to produce patulin. Due to the heat resistance of B. nivea and B. fulva and their ability to produce patulin either in PET bottles or in laminated paperboard packages, the control of contamination and the incidence of these fungi should be a matter of concern for food safety. Control measures taken by juice industries must also focus on controlling the ascospores of heat resistant moulds. (C) 2010 Elsevier B.V. All rights reserved.