Evolution of a rift basin dominated by subaerial deposits: The Guaritas Rift, Early Cambrian, Southern Brazil

Most existing models for the evolution of rift basins predict the development of deep-water depositional systems during the stage of greatest tectonic subsidence, when accommodation generation potentially outpaces sedimentation. Despite this, some rift basins do not present deep-water systems, instead being dominated by subaerial deposits. This paper focuses on one of these particular rift basins, the Cambrian Guaritas Rift, Southern Brazil, characterized by more than 1500 m of alluvial and aeolian strata deposited in a 50-km-wide basin. The deposits of the Guaritas Rift can be ascribed to four depositional systems: basin-border alluvial fans, bedload-dominated ephemeral rivers, mixed-load ephemeral rivers and aeolian dune fields. These four systems are in part coeval and in part succeed each other, forming three stages of basin evolution: (i) Rift Initiation to Early Rift Climax stage, (ii) Mid to Late Rift Climax stage, and (iii) Early Post-Rift stage. The first stage comprises most of the Guaritas Group and is characterized by homogeneous bed-load-dominated river deposits, which do not clearly record the evolution of subsidence rates. The onset of sedimentation of finer-grained deposits occurred as a consequence of a reactivation event that changed the outline of the basin and the distribution of the nearby highlands. This strongly suggests that the capture of the main river system to another depression decreased the sediment supply to the basin. The study of the Guaritas Rift indicates that rift basins in which the sediment supply exceeds the accommodation generation occur as a consequence of moderate subsidence combined with the capture of a major river system to the basin during the initial stages of basin evolution. In these basins, changes in the average discharge of the river system or tectonic modification of the drainage network may be the major control on the stratigraphic architecture. (c) 2009 Published by Elsevier B.V.

Well-preserved Late Paleoproterozoic volcanic centers in the Sao Felix do Xingu region, Amazonian Craton, Brazil

The Amazonian craton in the Sao Felix do Xingu city, southeast region of the Para state, north of Brazil, hosts exceptionally well-preserved Paleoproterozoic bimodal magmatic units grouped in the Sobreiro and Santa Rosa formations. These formations are correlated to the Uatuma magmatic event, which is largely distributed in the Amazonian craton occupying more than 1,500,000 km(2). Geological mapping and petrographical observations reveal distinct spectra of volcanic facies in both formations. The basal calc-alkaline Sobreiro Formation is composed mainly of andesitic and dacitic lava flows and associated volcaniclastic facies of autoclastic origin, with subordinate pyroclastic flow deposits. This formation shows inferred eruption style that is similar to those in Flood Basalt Provinces, with rare scutulum-type lava shields. The upper A-type Santa Rosa Formation was generated by multicyclic explosive and effusive episodes predominantly associated with large fissures and is materialized by voluminous ignimbrites with subordinated ash-fall tuff, crystal tuff, lapilli-tuff, co-ignimbritic breccias, rhyolitic dikes and domes, and associated granitic porphyries and equigranular granitic intrusions. Ignimbrite and rhyolite dikes reveal conspicuous vertical flow pattern pointing to a fissure-controlled eruption, similar to Sierra Madre Occidental ignimbrite province. The proposed evolutionary model for the Sao Felix do Xingu units differs from those of other occurrences related to the Uatuma magmatic event in the Amazonian craton, characterized by predominance of A-type volcanism and contemporaneous granites. (C) 2010 Elsevier B.V. All rights reserved.

Weak hypergraph regularity and linear hypergraphs

We consider conditions which allow the embedding of linear hypergraphs of fixed size. In particular, we prove that any k-uniform hypergraph H of positive uniform density contains all linear k-uniform hypergraphs of a given size. More precisely, we show that for all integers l >= k >= 2 and every d > 0 there exists Q > 0 for which the following holds: if His a sufficiently large k-uniform hypergraph with the property that the density of H induced on every vertex subset of size on is at least d, then H contains every linear k-uniform hypergraph F with l vertices. The main ingredient in the proof of this result is a counting lemma for linear hypergraphs, which establishes that the straightforward extension of graph epsilon-regularity to hypergraphs suffices for counting linear hypergraphs. We also consider some related problems. (C) 2009 Elsevier Inc. All rights reserved.

Augmented Lagrangian methods under the constant positive linear dependence constraint qualification

Two Augmented Lagrangian algorithms for solving KKT systems are introduced. The algorithms differ in the way in which penalty parameters are updated. Possibly infeasible accumulation points are characterized. It is proved that feasible limit points that satisfy the Constant Positive Linear Dependence constraint qualification are KKT solutions. Boundedness of the penalty parameters is proved under suitable assumptions. Numerical experiments are presented.

Improved score tests in symmetric linear regression models

The class of symmetric linear regression models has the normal linear regression model as a special case and includes several models that assume that the errors follow a symmetric distribution with longer-than-normal tails. An important member of this class is the t linear regression model, which is commonly used as an alternative to the usual normal regression model when the data contain extreme or outlying observations. In this article, we develop second-order asymptotic theory for score tests in this class of models. We obtain Bartlett-corrected score statistics for testing hypotheses on the regression and the dispersion parameters. The corrected statistics have chi-squared distributions with errors of order O(n(-3/2)), n being the sample size. The corrections represent an improvement over the corresponding original Rao`s score statistics, which are chi-squared distributed up to errors of order O(n(-1)). Simulation results show that the corrected score tests perform much better than their uncorrected counterparts in samples of small or moderate size.

Local influence for Student-t partially linear models

In this paper we extend partial linear models with normal errors to Student-t errors Penalized likelihood equations are applied to derive the maximum likelihood estimates which appear to be robust against outlying observations in the sense of the Mahalanobis distance In order to study the sensitivity of the penalized estimates under some usual perturbation schemes in the model or data the local influence curvatures are derived and some diagnostic graphics are proposed A motivating example preliminary analyzed under normal errors is reanalyzed under Student-t errors The local influence approach is used to compare the sensitivity of the model estimates (C) 2010 Elsevier B V All rights reserved

Leverage analysis for linear mixed models

We consider a generalized leverage matrix useful for the identification of influential units and observations in linear mixed models and show how a decomposition of this matrix may be employed to identify high leverage points for both the marginal fitted values and the random effect component of the conditional fitted values. We illustrate the different uses of the two components of the decomposition with a simulated example as well as with a real data set.

Improved testing inference in mixed linear models

Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Often, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test, and also to a test obtained from a modified profile likelihood function. Our results generalize those in [Zucker, D.M., Lieberman, O., Manor, O., 2000. Improved small sample inference in the mixed linear model: Bartlett correction and adjusted likelihood. Journal of the Royal Statistical Society B, 62,827-838] by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report simulation results which show that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presented and discussed. (C) 2008 Elsevier B.V. All rights reserved.

Likelihood ratio tests for variance components in linear mixed models

Although the asymptotic distributions of the likelihood ratio for testing hypotheses of null variance components in linear mixed models derived by Stram and Lee [1994. Variance components testing in longitudinal mixed effects model. Biometrics 50, 1171-1177] are valid, their proof is based on the work of Self and Liang [1987. Asymptotic properties of maximum likelihood estimators and likelihood tests under nonstandard conditions. J. Amer. Statist. Assoc. 82, 605-610] which requires identically distributed random variables, an assumption not always valid in longitudinal data problems. We use the less restrictive results of Vu and Zhou [1997. Generalization of likelihood ratio tests under nonstandard conditions. Ann. Statist. 25, 897-916] to prove that the proposed mixture of chi-squared distributions is the actual asymptotic distribution of such likelihood ratios used as test statistics for null variance components in models with one or two random effects. We also consider a limited simulation study to evaluate the appropriateness of the asymptotic distribution of such likelihood ratios in moderately sized samples. (C) 2008 Elsevier B.V. All rights reserved.

Influence diagnostics for linear models with first-order autoregressive elliptical errors

We introduce in this paper the class of linear models with first-order autoregressive elliptical errors. The score functions and the Fisher information matrices are derived for the parameters of interest and an iterative process is proposed for the parameter estimation. Some robustness aspects of the maximum likelihood estimates are discussed. The normal curvatures of local influence are also derived for some usual perturbation schemes whereas diagnostic graphics to assess the sensitivity of the maximum likelihood estimates are proposed. The methodology is applied to analyse the daily log excess return on the Microsoft whose empirical distributions appear to have AR(1) and heavy-tailed errors. (C) 2008 Elsevier B.V. All rights reserved.

Local Influence Analysis for Skew-Normal Linear Mixed Models

In this article, we consider local influence analysis for the skew-normal linear mixed model (SN-LMM). As the observed data log-likelihood associated with the SN-LMM is intractable, Cook`s well-known approach cannot be applied to obtain measures of local influence. Instead, we develop local influence measures following the approach of Zhu and Lee (2001). This approach is based on the use of an EM-type algorithm and is measurement invariant under reparametrizations. Four specific perturbation schemes are discussed. Results obtained for a simulated data set and a real data set are reported, illustrating the usefulness of the proposed methodology.

Skew-normal linear calibration: a Bayesian perspective

In this paper, we present a Bayesian approach for estimation in the skew-normal calibration model, as well as the conditional posterior distributions which are useful for implementing the Gibbs sampler. Data transformation is thus avoided by using the methodology proposed. Model fitting is implemented by proposing the asymmetric deviance information criterion, ADIC, a modification of the ordinary DIC. We also report an application of the model studied by using a real data set, related to the relationship between the resistance and the elasticity of a sample of concrete beams. Copyright (C) 2008 John Wiley & Sons, Ltd.

In vitro basal cytotoxicity assay applied to estimate acute oral systemic toxicity of grandisin and its major metabolite

Preclinical investigations can start with preliminary in vitro studies before using animal models. Following this approach, the number of animals used in preclinical acute toxicity testing can be reduced. In this study, we employed an in-house validated in vitro cytotoxicity test based on the Spielmann approach for toxicity evaluation of the lignan grandisin, a candidate anticancer agent, and its major metabolite. the 4-O-demethylgrandisin, by neutral red uptake (NRU) assay, on mouse fibroblasts Balb/c 3T3 cell line. Using different concentrations of grandisin and its major metabolite (2.31; 1.16; 0.58; 0.29; 0.14; 0.07; 0.04; 0.002 mu M) in Balb/c 3T3-A31 NRU cytotoxicity assay, after incubation for 48 h, we obtained IC(50) values for grandisin and its metabolite of 0.078 and 0.043 mu M, respectively. The computed LD(50) of grandisin and 4-O-demethylgrandisin were 617.72 and 429.95 mg/kg, respectively. Both were classified under the Globally Harmonized System as category 4. Since pharmacological and toxicological data are crucial in the developmental stages of drug discovery, using an in vitro assay we demonstrated that grandisin and its metabolite exhibit distinct toxicity profiles. Furthermore, results presented in this work can contribute to reduce the number of animals required in subsequent pharmacological/toxicological studies. (C) 2010 Elsevier GmbH. All rights reserved.

Formation of Dextran Deposits in Brazilian Sugar Cane Spirits

The formation of dextran deposits in sugared Brazilian cachaca was studied as a function of the time considering the effects of temperature, molecular weight (M(w)), visible light, pH, and the presence of Ca, Mg, Cu, and Fe ions in the concentrations at which they are usually present in this beverage. At 25 degrees C and pH 4.4, the experimental half-lives (t(1/2)) for precipitation are 73 and 124 days for dextrans with M(w) 5.9 x 10(6) and 2.1 x 10(6) Da, respectively. For dextrans with M(w) 5.0 x 10(5) and 4.0 x 10(4) Da, the experimental t(1/2) values are >180 days. For a dextran with M(w) 2.1 x 10(6) Da a change in pH from 4.4 to 5.5 at 25 degrees C resulted in a t(1/2) decrease from 124 to 25 days. At pH 4.4 the visible light and the presence of metal ions in average concentrations usually found in cachacas do not exhibit noticeable influence on the rate of dextran precipitation.

Molecular mass distribution of dextran in Brazilian sugar and insoluble deposits of cachaca

The dextran molecular mass distribution profile in 77 sugar samples from Brazil and twelve insoluble deposits (alcoholic flocks) samples from sugared cachacas (Brazilian sugar cane spirit) is described in terms of number-average molecular mass M,,, weight-average molecular mass M(w), Z-average molecular mass M,, and polydispersity. The analyses were performed by size-exclusion chromatography, using a refractive index detector. In most of the sugar samples, it was possible to identify two major groups of dextrans with Mw averages of 5 x 10(6) and 5 x 10(4) Da. Based on the evaluated parameters, the dextran distribution profile is about the same in samples analyzed over five seasons, and, therefore, it is likely that the Brazilian product pattern will not change very much over the years. In insoluble deposits from sugared cachacas, dextrans with Mw values in the order of the 10(5) Da were the most frequent ones, being present in 58% of the samples. (c) 2008 Elsevier Ltd. All rights reserved.