DISTRIBUTION OF THE NUMBER OF EURYTREMA SP EGGS PER GRAM OF FECES IN NATURALLY INFECTED CATTLE

Eurytrema sp. egg counts (epg) in the feces of naturally infected cattle were performed and the technique employed showed 94.2% probability of detecting positive cases of the infection with a single examination independently of the host parasite burden. It was also demonstrated that the epg of Eurytrema sp. follows a negative binomial distribution model and is characterized by its small magnitude.

Density and spatial distribution of Atta sexdens rubropilosa and Atta laevigata colonies (Hym., Formicidae) in Eucalyptus spp. forests

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Multivariate models for correlated count data

In this study, we deal with the problem of overdispersion beyond extra zeros for a collection of counts that can be correlated. Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial distributions have been considered. First, we propose a multivariate count model in which all counts follow the same distribution and are correlated. Then we extend this model in a sense that correlated counts may follow different distributions. To accommodate correlation among counts, we have considered correlated random effects for each individual in the mean structure, thus inducing dependency among common observations to an individual. The method is applied to real data to investigate variation in food resources use in a species of marsupial in a locality of the Brazilian Cerrado biome. © 2013 Copyright Taylor and Francis Group, LLC.

Spatial Distribution of Euschistus heros (F.) (Hemiptera: Pentatomidae) in Soybean

Soybean bugs are major crop pests that cause significant reduction in harvest yield and influence grain quality. The aim of this study was to verify the spatial distribution of Euschistus heros (F.) (Hemiptera: Pentatomidae) in conventional and transgenic soybean cultivars. The experiment was conducted during the 2010-2011 crop season in UNESP/FCAV, Jaboticabal, SP, Brazil, in two fields of 10,000-m2 area that were subdivided into 100 plots (10 m × 10 m). The cultivars sown were M 7908 RR and its isoline M-SOY 8001. The number of the first to fifth instars and the number of adults were determined. To evaluate insect dispersion in the area, the following indices were used: variance/mean ratio, Morisita index, Green coefficient, and the k exponent of the negative binomial distribution. To study probabilistic models to describe the spatial distribution of the insects, the adjustments of the Poisson and negative binomial distributions were tested. The first to third instars showed aggregated spatial distribution, whereas the fourth and fifth instars, and adults, isolated or grouped, showed variation in the arrangement, ranging from moderately aggregated to randomly dispersed. During the adjustment of probability distributions, the negative binomial distribution model showed adjustment for the first to third instars, fourth and fifth instars, adults, and fourth and fifth instars plus adults. © 2013 Sociedade Entomológica do Brasil.

Distribuição espacial e plano de amostragem sequencial para Euschistus heros (Fabricius, 1794) (Heteroptera: Pentatomidae) na cultura da soja convencional e transgênica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Distribuição espacial e amostragem sequencial de Cosmopolites sordidus (Germar) na cultura da bananeira

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Distribuição espacial e plano de amostragem seqüencial de ácaros fitófagos na cultura da seringueira [Hevea brasiliensis (Wild. Ex Adr. de Juss.) Müell.Arg.]

Pós-graduação em Agronomia - FEIS

Distribuição espacial e amostragem sequencial de Diatraea saccharalis (Fabricius, 1794) (Lepidoptera: Crambidae), na cultura de cana-de-açúcar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Distribuição espacial e amostragem sequencial de Triozoida limbata (Hemiptera: Triozidae) em goiabeira

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Distribuição espacial e plano amostragem seqüencial para a lagarta do minador-dos-citros Phyllocnistis citrella Stainton, 1856 (Lepidoptera: Gracillariidae), em laranjeira 'Pêra-Rio' Citrus sinensis (L.) Osbeck

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Distribuição espacial e plano de amostragem sequencial para Piezodorus guildinii (Westwood, 1837) (Hemiptera: Pentatomidae) na cultura de soja transgênica RR®

Pós-graduação em Agronomia (Entomologia Agrícola) - FCAV

Distribuição espacial, amostragem sequencial e dinâmica populacional de Leptopharsa heveae (Hemiptera: Tingidae) na cultura da seringueira

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Liquid nitrogen for the treatment of actinic keratosis: A longitudinal assessment

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Knowledge and use of wild edible plants in rural communities along Paraguay River, Pantanal, Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Bivariate gamma-geometric law and its induced Levy process

In this article we introduce a three-parameter extension of the bivariate exponential-geometric (BEG) law (Kozubowski and Panorska, 2005) [4]. We refer to this new distribution as the bivariate gamma-geometric (BGG) law. A bivariate random vector (X, N) follows the BGG law if N has geometric distribution and X may be represented (in law) as a sum of N independent and identically distributed gamma variables, where these variables are independent of N. Statistical properties such as moment generation and characteristic functions, moments and a variance-covariance matrix are provided. The marginal and conditional laws are also studied. We show that BBG distribution is infinitely divisible, just as the BEG model is. Further, we provide alternative representations for the BGG distribution and show that it enjoys a geometric stability property. Maximum likelihood estimation and inference are discussed and a reparametrization is proposed in order to obtain orthogonality of the parameters. We present an application to a real data set where our model provides a better fit than the BEG model. Our bivariate distribution induces a bivariate Levy process with correlated gamma and negative binomial processes, which extends the bivariate Levy motion proposed by Kozubowski et al. (2008) [6]. The marginals of our Levy motion are a mixture of gamma and negative binomial processes and we named it BMixGNB motion. Basic properties such as stochastic self-similarity and the covariance matrix of the process are presented. The bivariate distribution at fixed time of our BMixGNB process is also studied and some results are derived, including a discussion about maximum likelihood estimation and inference. (C) 2012 Elsevier Inc. All rights reserved.