Home range and habitat use by the roadside hawk, Rupornis magnirostris (Gmelin, 1788) (Aves: Falcaniformes) in southeastern Brazil

Although most raptor species are found mainly in the tropics, information on their home range and spatial requirements in the Neotropics is still scarce. In this study, we used radio telemetry to evaluate the home range and the habitat use and selection of five Roadside hawks, Rupornis magnirostris (Gmelin, 1788) in a heterogeneous landscape in southeastern Brazil. The average home range size calculated using the adaptive kernel method (95% isopleth) was 126.1ha (47.4-266.7ha), but using the minimum convex polygon method (95% isopleth) it was 143.54ha (32.6-382.3ha). The roadside hawk explored a wide variety of habitats, most of them opportunistically, as suggested in the literature. Despite this, habitat quality could influence home range size and promote habitat selection. The observation of habitat use as expected, as well as the relatively small home range size, could be related to the generalist/opportunistic behaviour of the roadside hawk.

Fungi, mycotoxins and phytoalexin in peanut varieties, during plant growth in the field

The aim of the present study was to analyze the mycobiota, occurrence of mycotoxins (aflatoxins and cyclopiazonic acid), and production of phytoalexin (trans-resveratrol) in two peanut varieties (Runner IAC 886 and Caiapo) during plant growth in the field. Climatic factors (rainfall, relative humidity and temperature) and water activity were also evaluated. The results showed a predominance of Fusarium spp. in kernels and pods, followed by Penicillium spp. and Aspergillus flavus. Aflatoxins were detected in 20% and 10% of samples of the IAC 886 and Caiapo varieties, respectively. Analysis showed that 65% of kernel samples of the IAC 886 variety and 25% of the Caiapo variety were contaminated with cyclopiazonic acid. trans-Resveratrol was detected in 6.7% of kernel samples of the IAC 886 variety and in 20% of the Caiapo variety. However, trans-resveratrol was found in 73.3% of leaf samples in the two varieties studied. (C) 2011 Published by Elsevier Ltd.

Relative populations and toxin production by Aspergillus flavus and Fusarium verticillioides in artificially inoculated corn at various stages of development under field conditions

The presence, development and production of mycotoxins by Aspergillus flavus and Fusarium verticillioides were studied in corn ears under field conditions after artificial contamination of corn silks. The planted area was divided into five treatments: T1, inoculated with A.flavus solution containing 1 x 10(8) spores, ears covered; T2, inoculated with F. verticillioides solution containing 1 X 10(8) spores, ears covered; T3, inoculated with E verticillioides plus A. flavus solution containing 1 x 10(8) spores of each, ears covered; T4, sprayed with sterile phosphate-buffered saline, ears covered; TS, non-sprayed silks, uncovered ears. Soil and air samples were also collected and analysed for the occurrence of fungi. Water activity, relative air humidity, rainfall and temperature were determined to assess the correlation between abiotic factors and the presence of fungi in the samples. Contamination with the inoculated fungus predominated in T1 and T2. In the other treatments, F. verticillioides was the most frequently isolated contaminant irrespective of treatment. Considering the production of mycotoxins, a positive relation between the production of fumonisins B-1 and B-2 and the frequency of F. verticillioides was statistically verified in all treatments. (C) 2007 Society of Chemical Industry.

Exact Search Directions for Optimization of Linear and Nonlinear Models Based on Generalized Orthonormal Functions

A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

Nonexistence of global solutions for a class of complex vector fields on two-torus

The goal of this paper is study the global solvability of a class of complex vector fields of the special form L = partial derivative/partial derivative t + (a + ib)(x)partial derivative/partial derivative x, a, b epsilon C(infinity) (S(1) ; R), defined on two-torus T(2) congruent to R(2)/2 pi Z(2). The kernel of transpose operator L is described and the solvability near the characteristic set is also studied. (c) 2008 Elsevier Inc. All rights reserved.

Robust inference in an heteroscedastic measurement error model

In this paper we deal with robust inference in heteroscedastic measurement error models Rather than the normal distribution we postulate a Student t distribution for the observed variables Maximum likelihood estimates are computed numerically Consistent estimation of the asymptotic covariance matrices of the maximum likelihood and generalized least squares estimators is also discussed Three test statistics are proposed for testing hypotheses of interest with the asymptotic chi-square distribution which guarantees correct asymptotic significance levels Results of simulations and an application to a real data set are also reported (C) 2009 The Korean Statistical Society Published by Elsevier B V All rights reserved

Shared information in stationary states at criticality

We consider bipartitions of one-dimensional extended systems whose probability distribution functions describe stationary states of stochastic models. We define estimators of the information shared between the two subsystems. If the correlation length is finite, the estimators stay finite for large system sizes. If the correlation length diverges, so do the estimators. The definition of the estimators is inspired by information theory. We look at several models and compare the behaviors of the estimators in the finite-size scaling limit. Analytical and numerical methods as well as Monte Carlo simulations are used. We show how the finite-size scaling functions change for various phase transitions, including the case where one has conformal invariance.

New insights on the Lewis acidity of diorganolead(IV) compounds: Diphenyllead(IV) complexes with N,O,S-chelating ligands

The reactions of PbPh2(OAC)(2) with alkylglyoxylate thiosemicarbazones (HRGTSC, R = Et, Bu) afforded complexes of the type [PbPh2(GTSC)] center dot H2O, [PbPh2(RGTSC)(2)] and [PbPh2Cl(BUGTSC)]. The structures of HRGTSC (R = Me, Et, Bu), [PbPh2(OAc)(RGTSC)](R = Me, Et, Bu), [PbPh2Cl(BuGTSC)] and [PbPh2(GTSC)] center dot H2O have been studied by X-ray diffraction. [PbPh2(OAc)(RGTSC)] and [PbPh2(GTSC)] center dot H2O have [PbC2NO3S] kernels and the coordination sphere of the metal is pentagonal bipyramidal. [PbPh2Cl(BuGTSC)] has a [PbC2NOSCI] kernel and the coordination geometry around lead is pentagonal bipyramidal with one vacant site. Analysis of the bond distances in [PbPh2(GTSC)] center dot H2O suggests a significant affinity between diphenyllead(IV) and carboxylate donor groups, supporting a borderline acidic character for this organometallic cation. H-1 and C-13 NMR spectra in DMSO-d(6) suggest the partial dissociation of the acetate in [PbPh2(OAc)(RGTSC)] solutions and indicate some differences in the coordination mode of the two RGTSC(-) ligands in [PbPh2(RGTSC)(2)] complexes. (C) 2007 Elsevier Ltd. All rights reserved.

Xyloglucan nano-aggregates: Physico-chemical characterisation in buffer solution and potential application as a carrier for camptothecin, an anti-cancer drug

In this work, native xyloglucan was extracted from Tamarindus indica seeds (XGT), and its properties in phosphate buffer solution (PBS) were evaluated in comparison with a commercial tamarind kernel powder (TKP). The physico-chemical characteristics of the polysaccharides such as molar mass, critical concentration and intrinsic viscosity were determined. Furthermore, using spectroscopic and microscopy techniques, it was observed that the XGs tested can be considered macromolecules able to aggregate as nano-entities of 60-140 nm. The XGT tended to an ordered and compact spherical conformation determined by the Huggins constant, circular dichroism, atomic force microscopy and transmission electron microscopy. After the determination of the properties in PBS the XGs, at concentrations of 25% above their critical aggregation concentration, were used to encapsulate camptothecin, an anti-cancer drug. The XGT sample showed an encapsulation efficiency of 42% and first-order drug delivery kinetics. These results demonstrated the importance of knowledge of the physico-chemical properties of polysaccharides, for example, to better conduct their biotechnological applications as drug carriers. (C) 2010 Elsevier Ltd. 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.

Sampling, WLS, and Mixed Models

Mixed models may be defined with or without reference to sampling, and can be used to predict realized random effects, as when estimating the latent values of study subjects measured with response error. When the model is specified without reference to sampling, a simple mixed model includes two random variables, one stemming from an exchangeable distribution of latent values of study subjects and the other, from the study subjects` response error distributions. Positive probabilities are assigned to both potentially realizable responses and artificial responses that are not potentially realizable, resulting in artificial latent values. In contrast, finite population mixed models represent the two-stage process of sampling subjects and measuring their responses, where positive probabilities are only assigned to potentially realizable responses. A comparison of the estimators over the same potentially realizable responses indicates that the optimal linear mixed model estimator (the usual best linear unbiased predictor, BLUP) is often (but not always) more accurate than the comparable finite population mixed model estimator (the FPMM BLUP). We examine a simple example and provide the basis for a broader discussion of the role of conditioning, sampling, and model assumptions in developing inference.

Performance of balanced two-stage empirical predictors of realized cluster latent values from finite populations: A simulation study

Predictors of random effects are usually based on the popular mixed effects (ME) model developed under the assumption that the sample is obtained from a conceptual infinite population; such predictors are employed even when the actual population is finite. Two alternatives that incorporate the finite nature of the population are obtained from the superpopulation model proposed by Scott and Smith (1969. Estimation in multi-stage surveys. J. Amer. Statist. Assoc. 64, 830-840) or from the finite population mixed model recently proposed by Stanek and Singer (2004. Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 1119-1130). Predictors derived under the latter model with the additional assumptions that all variance components are known and that within-cluster variances are equal have smaller mean squared error (MSE) than the competitors based on either the ME or Scott and Smith`s models. As population variances are rarely known, we propose method of moment estimators to obtain empirical predictors and conduct a simulation study to evaluate their performance. The results suggest that the finite population mixed model empirical predictor is more stable than its competitors since, in terms of MSE, it is either the best or the second best and when second best, its performance lies within acceptable limits. When both cluster and unit intra-class correlation coefficients are very high (e.g., 0.95 or more), the performance of the empirical predictors derived under the three models is similar. (c) 2007 Elsevier B.V. All rights reserved.

Improved likelihood inference for the shape parameter in Weibull regression

We obtain adjustments to the profile likelihood function in Weibull regression models with and without censoring. Specifically, we consider two different modified profile likelihoods: (i) the one proposed by Cox and Reid [Cox, D.R. and Reid, N., 1987, Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society B, 49, 1-39.], and (ii) an approximation to the one proposed by Barndorff-Nielsen [Barndorff-Nielsen, O.E., 1983, On a formula for the distribution of the maximum likelihood estimator. Biometrika, 70, 343-365.], the approximation having been obtained using the results by Fraser and Reid [Fraser, D.A.S. and Reid, N., 1995, Ancillaries and third-order significance. Utilitas Mathematica, 47, 33-53.] and by Fraser et al. [Fraser, D.A.S., Reid, N. and Wu, J., 1999, A simple formula for tail probabilities for frequentist and Bayesian inference. Biometrika, 86, 655-661.]. We focus on point estimation and likelihood ratio tests on the shape parameter in the class of Weibull regression models. We derive some distributional properties of the different maximum likelihood estimators and likelihood ratio tests. The numerical evidence presented in the paper favors the approximation to Barndorff-Nielsen`s adjustment.

Comparing time-varying autoregressive structures of locally stationary processes

In this paper, a novel statistical test is introduced to compare two locally stationary time series. The proposed approach is a Wald test considering time-varying autoregressive modeling and function projections in adequate spaces. The covariance structure of the innovations may be also time- varying. In order to obtain function estimators for the time- varying autoregressive parameters, we consider function expansions in splines and wavelet bases. Simulation studies provide evidence that the proposed test has a good performance. We also assess its usefulness when applied to a financial time series.

A multivariate ultrastructural errors-in-variables model with equation error

This paper deals with asymptotic results on a multivariate ultrastructural errors-in-variables regression model with equation errors Sufficient conditions for attaining consistent estimators for model parameters are presented Asymptotic distributions for the line regression estimators are derived Applications to the elliptical class of distributions with two error assumptions are presented The model generalizes previous results aimed at univariate scenarios (C) 2010 Elsevier Inc All rights reserved