Areas of endemism in the Antarctic - a case study of the benthic hydrozoan genus Oswaldella (Cnidaria, Kirchenpaueriidae)

Aim The aim of this study is to investigate areas of endemism within the distribution of Oswaldella species in the Southern Ocean, thereby testing previous hypotheses and proposing alternative scenarios for Antarctic evolution. Location Southern Ocean, Antarctic and sub-Antarctic waters of southern South America. Methods We prepared a database for the 31 currently known species of the Antarctic genus Oswaldella, which includes geographical locations gathered from published taxonomic studies as well as materials from museums and expeditions. A parsimony analysis of endemicity (PAE) was used to test hypotheses of distribution patterns. Results Four areas of endemism are hypothesized: southern South America, two high Antarctic areas (eastern and western) and a larger area, mainly in western Antarctica at lower latitudes and including insular areas (but not the Balleny Islands). Main conclusions The results support, in part, previous hypotheses for the Southern Ocean region, while providing more detailed resolution. The areas of endemism may reflect both historical and ecological processes that influenced the Antarctic biota. The Magellanic area reflects the well-known affinities of the Antarctic biota with that of South America and may be a consequence of dispersal through deeper (and colder) waters, followed by speciation. The second area, the largest one, encompasses most of the insular faunas and may also be associated with deeper waters formed since 43 Ma. The third area may be explained by the development of seaways in the circum-Antarctic region beginning 50 Ma. Finally, the fourth zone, with a very poor fauna, coincides with the opening of the Tasman Strait and the formation of the Australo-Antarctic Gulf, associated with a minor wind-driven current.

Hypotheses testing for structural calibration model

The main objective of this paper is to discuss maximum likelihood inference for the comparative structural calibration model (Barnett, in Biometrics 25:129-142, 1969), which is frequently used in the problem of assessing the relative calibrations and relative accuracies of a set of p instruments, each designed to measure the same characteristic on a common group of n experimental units. We consider asymptotic tests to answer the outlined questions. The methodology is applied to a real data set and a small simulation study is presented.

The comparative field body temperature among Liolaemus lizards: Testing the static and the labile hypotheses

Two competing hypotheses have been suggested to explain thermal sensitivity of lizards to environmental conditions. These are the static and the labile hypotheses. The static hypothesis posits that thermal physiology is evolutionary conservative and consequently relatively insensitive to directional selection. Contrarily, the labile hypothesis states that thermal physiology does respond readily to directional selection in some lizard taxa. In this paper, we tested both hypotheses among species of Liolaemus lizards. The genus Liolaemus is diverse with about 200 species, being broadly distributed from central Peru to Tierra del Fuego at the southern end of South America. Data of field body temperature (T(b)) from Liolaemus species were collected from the literature. Based on the distributional range of the species we also collected data of mean annual ambient temperatures. We observed that both the traditional analysis and the phylogenetic approach indicate that in the genus Liolaemus T(b) of species varies in a manner that is consistent with ecological gradient of ambient temperature. The data suggest that the thermal physiology of Liolaemus lizards is evolutionarily flexible, and that this plasticity has been partially responsible for the colonization of a wide array of thermal environments. (C) 2009 Elsevier Ltd. All rights reserved.

Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model

Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.

Testing hypotheses in the Birnbaum-Saunders distribution under type-II censored samples

The two-parameter Birnbaum-Saunders distribution has been used successfully to model fatigue failure times. Although censoring is typical in reliability and survival studies, little work has been published on the analysis of censored data for this distribution. In this paper, we address the issue of performing testing inference on the two parameters of the Birnbaum-Saunders distribution under type-II right censored samples. The likelihood ratio statistic and a recently proposed statistic, the gradient statistic, provide a convenient framework for statistical inference in such a case, since they do not require to obtain, estimate or invert an information matrix, which is an advantage in problems involving censored data. An extensive Monte Carlo simulation study is carried out in order to investigate and compare the finite sample performance of the likelihood ratio and the gradient tests. Our numerical results show evidence that the gradient test should be preferred. Further, we also consider the generalized Birnbaum-Saunders distribution under type-II right censored samples and present some Monte Carlo simulations for testing the parameters in this class of models using the likelihood ratio and gradient tests. Three empirical applications are presented. (C) 2011 Elsevier B.V. All rights reserved.

Accelerated testing of mold growth on traditional and recycled book paper

The growth of molds on paper containing cellulose is a frequent occurrence when the level of relative air humidity is high or when books become wet due to water leaks in libraries. The aim of this study is to differentiate the bioreceptivity of different types of book paper for different fungi. Laboratory tests were performed with strains of Aspergillus niger, Cladosporium sp., Chaetomium globosum and Trichoderma harzianum isolated from books. Four paper types were evaluated: couche Men (offset), recycled and a reference paper containing only cellulose. The tests were carried out in chambers with relative air humidity of 95% and 100%. Mold growth was greatest in the tests at 100% relative humidity. Results of stereoscopic microscopy observation showed that Cladosporium sp. grew in 74% of these samples, A. niger in 75%, T. harzianum in 72% and C. globosum in 60%. In the chambers with 95% air humidity Cladosporium sp. grew in only 9% of the samples, A. niger in 1%, T harzianum in 3% and C globosum did not grow in any sample. The most bioreceptive paper was couche and the least receptive was recycled paper. The composition of the recycled paper, however, varies depending on the types of waste materials used to make it. (C) 2011 Elsevier Ltd. All rights reserved.

The direct determination of rare earth elements in basaltic and related rocks using ICP-MS: Testing the efficiency of microwave oven sample decomposition procedures

Tests are described showing the results obtained for the determination of REE and the trace elements Rb, Y, Zr, Nb, Cs, Ba, Hf, Ta, Pb, Th and U with ICP-MS methodology for nine basaltic reference materials, and thirteen basalts and amphibolites from the mafic-ultramafic Niquelandia Complex, central Brazil. Sample decomposition for the reference materials was performed by microwave oven digestion (HF and HNO(3), 100 mg of sample), and that for the Niquelandia samples also by Parr bomb treatment (5 days at 200 degrees C, 40 mg of sample). Results for the reference materials were similar to published values, thus showing that the microwave technique can be used with confidence for basaltic rocks. No fluoride precipitates were observed in the microwave-digested solutions. Total recovery of elements, including Zr and Hf, was obtained for the Niquelandia samples, with the exception of an amphibolite. For this latter sample, the Parr method achieved a total digestion, but not so the microwave decomposition; losses, however, were observed only for Zr and Hf, indicating difficulty in dissolving Zr-bearing minerals by microwave acid attack.

Improving data perturbation testing techniques for Web services

The widespread use of service-oriented architectures (SOAs) and Web services in commercial software requires the adoption of development techniques to ensure the quality of Web services. Testing techniques and tools concern quality and play a critical role in accomplishing quality of SOA based systems. Existing techniques and tools for traditional systems are not appropriate to these new systems, making the development of Web services testing techniques and tools required. This article presents new testing techniques to automatically generate a set of test cases and data for Web services. The techniques presented here explore data perturbation of Web services messages upon data types, integrity and consistency. To support these techniques, a tool (GenAutoWS) was developed and applied to real problems. (C) 2010 Elsevier Inc. All rights reserved.

Testing permutation properties through subpermutations

There has been great interest in deciding whether a combinatorial structure satisfies some property, or in estimating the value of some numerical function associated with this combinatorial structure, by considering only a randomly chosen substructure of sufficiently large, but constant size. These problems are called property testing and parameter testing, where a property or parameter is said to be testable if it can be estimated accurately in this way. The algorithmic appeal is evident, as, conditional on sampling, this leads to reliable constant-time randomized estimators. Our paper addresses property testing and parameter testing for permutations in a subpermutation perspective; more precisely, we investigate permutation properties and parameters that can be well approximated based on a randomly chosen subpermutation of much smaller size. In this context, we use a theory of convergence of permutation sequences developed by the present authors [C. Hoppen, Y. Kohayakawa, C.G. Moreira, R.M. Sampaio, Limits of permutation sequences through permutation regularity, Manuscript, 2010, 34pp.] to characterize testable permutation parameters along the lines of the work of Borgs et al. [C. Borgs, J. Chayes, L Lovasz, V.T. Sos, B. Szegedy, K. Vesztergombi, Graph limits and parameter testing, in: STOC`06: Proceedings of the 38th Annual ACM Symposium on Theory of Computing, ACM, New York, 2006, pp. 261-270.] in the case of graphs. Moreover, we obtain a permutation result in the direction of a famous result of Alon and Shapira [N. Alon, A. Shapira, A characterization of the (natural) graph properties testable with one-sided error, SIAM J. Comput. 37 (6) (2008) 1703-1727.] stating that every hereditary graph property is testable. (C) 2011 Elsevier B.V. All rights reserved.

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.

Methods for Equivalence and Noninferiority Testing

Classical hypothesis testing focuses on testing whether treatments have differential effects on outcome. However, sometimes clinicians may be more interested in determining whether treatments are equivalent or whether one has noninferior outcomes. We review the hypotheses for these noninferiority and equivalence research questions, consider power and sample size issues, and discuss how to perform such a test for both binary and survival outcomes. The methods are illustrated on 2 recent studies in hematopoietic cell transplantation.

Hypothesis testing in an errors-in-variables model with heteroscedastic measurement errors

In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone observations and variances of the measurement errors changing across observations. We suppose that the observations follow a bivariate normal distribution and the measurement errors are normally distributed. Aggregate data allow the estimation of the error variances. Maximum likelihood estimates are computed numerically via the EM algorithm. Consistent estimation of the asymptotic variance of the maximum likelihood estimators is also discussed. Test statistics are proposed for testing hypotheses of interest. Further, we implement a simple graphical device that enables an assessment of the model`s goodness of fit. Results of simulations concerning the properties of the test statistics are reported. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease. Copyright (C) 2008 John Wiley & Sons, Ltd.