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Search Results: 1 - 10 of 9713 matches for " Wagner Hugo Bonat "
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Multivariate Covariance Generalized Linear Models
Wagner Hugo Bonat,Bent J?rgensen
Statistics , 2015,
Abstract: We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models (McGLMs), designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated measures and longitudinal structures, and the third involves a spatio-temporal analysis of rainfall data. The models take non-normality into account in the conventional way by means of a variance function, and the mean structure is modelled by means of a link function and a linear predictor. The models are fitted using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of different types of response variables and covariance structures, including multivariate extensions of repeated measures, time series, longitudinal, spatial and spatio-temporal structures.
Bayesian analysis for a class of beta mixed models
Wagner Hugo Bonat,Paulo Justiniano Ribeiro Jr,Silvia emiko Shimakura
Statistics , 2014,
Abstract: Generalized linear mixed models (GLMM) encompass large class of statistical models, with a vast range of applications areas. GLMM extends the linear mixed models allowing for different types of response variable. Three most common data types are continuous, counts and binary and standard distributions for these types of response variables are Gaussian, Poisson and Binomial, respectively. Despite that flexibility, there are situations where the response variable is continuous, but bounded, such as rates, percentages, indexes and proportions. In such situations the usual GLMM's are not adequate because bounds are ignored and the beta distribution can be used. Likelihood and Bayesian inference for beta mixed models are not straightforward demanding a computational overhead. Recently, a new algorithm for Bayesian inference called INLA (Integrated Nested Laplace Approximation) was proposed.INLA allows computation of many Bayesian GLMMs in a reasonable amount time allowing extensive comparison among models. We explore Bayesian inference for beta mixed models by INLA. We discuss the choice of prior distributions, sensitivity analysis and model selection measures through a real data set. The results obtained from INLA are compared with those obtained by an MCMC algorithm and likelihood analysis. We analyze data from an study on a life quality index of industry workers collected according to a hierarchical sampling scheme. Results show that the INLA approach is suitable and faster to fit the proposed beta mixed models producing results similar to alternative algorithms and with easier handling of modeling alternatives. Sensitivity analysis, measures of goodness of fit and model choice are discussed.
The Gamma-count distribution in the analysis of experimental underdispersed data
Walmes Marques Zeviani,Paulo Justiniano Ribeiro Jr.,Wagner Hugo Bonat,Silvia Emiko Shimakura,Joel Augusti Muniz
Statistics , 2013, DOI: 10.1080/02664763.2014.922168
Abstract: Event counts are response variables with non-negative integer values representing the number of times that an event occurs within a fixed domain such as a time interval, a geographical area or a cell of a contingency table. Analysis of counts by Gaussian regression models ignores the discreteness, asymmetry and heterocedasticity and is inefficient, providing unrealistic standard errors or possibily negative predictions of the expected number of events. The Poisson regression is the standard model for count data with underlying assumptions on the generating process which may be implausible in many applications. Statisticians have long recognized the limitation of imposing equidispersion under the Poisson regression model. A typical situation is when the conditional variance exceeds the conditional mean, in which case models allowing for overdispersion are routinely used. Less reported is the case of underdispersion with fewer modelling alternatives and assessments available in the literature. One of such alternatives, the Gamma-count model, is adopted here in the analysis of an agronomic experiment designed to investigate the effect of levels of defoliation on different phenological states upon the number of cotton bolls. Results show improvements over the Poisson model and the semiparametric quasi-Poisson model in capturing the observed variability in the data. Estimating rather than assuming the underlying variance process lead to important insights into the process.
Likelihood analysis for a class of beta mixed models
Wagner H. Bonat,Paulo J. Ribeiro Jr.,Walmes Marque Zeviani
Statistics , 2013, DOI: 10.1080/02664763.2014.947248
Abstract: Beta regression models are a suitable choice for continuous response variables on the unity interval. Random effects add further flexibility to the models and accommodate data structures such as hierarchical, repeated measures and longitudinal, which typically induce extra variability and/or dependence. Closed expressions cannot be obtained for parameter estimation and numerical methods are required and possibly combined with sampling algorithms. We focus on likelihood inference and related algorithms for the analysis of beta mixed models motivated by two real problems with grouped data structures. The first is a study on a life quality index of industry workers with data collected according to an hierarchical sampling scheme. The second is a study with a nested and longitudinal data structure assessing the impact of hydroelectric power plants upon measures of water quality indexes up, downstream and at the reservoirs of the dammed rivers. Relevant scientific hypothesis are investigated by comparing alternative models. The analysis uses different algorithms including data-cloning, an alternative to numerical approximations which also assess identifiability. Confidence intervals based on profiled likelihoods are compared to those obtained by asymptotic quadratic approximations, showing relevant differences for parameters related to the random effects.
Sustained Reduction of the Dengue Vector Population Resulting from an Integrated Control Strategy Applied in Two Brazilian Cities
Lêda N. Regis, Ridelane Veiga Acioli, José Constantino Silveira, Maria Alice Varjal Melo-Santos, Wayner Vieira Souza, Candida M. Nogueira. Ribeiro, Juliana C. Serafim. da Silva, Antonio Miguel Vieira Monteiro, Cláudia M. F. Oliveira, Rosangela M. R. Barbosa, Cynthia Braga, Marco Aurélio Benedetti Rodrigues, Marilú Gomes N. M. Silva, Paulo Justiniano Ribeiro Jr., Wagner Hugo Bonat, Liliam César de Castro Medeiros, Marilia Sa Carvalho, André Freire Furtado
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0067682
Abstract: Aedes aegypti has developed evolution-driven adaptations for surviving in the domestic human habitat. Several trap models have been designed considering these strategies and tested for monitoring this efficient vector of Dengue. Here, we report a real-scale evaluation of a system for monitoring and controlling mosquito populations based on egg sampling coupled with geographic information systems technology. The SMCP-Aedes, a system based on open technology and open data standards, was set up from March/2008 to October/2011 as a pilot trial in two sites of Pernambuco -Brazil: Ipojuca (10,000 residents) and Santa Cruz (83,000), in a joint effort of health authorities and staff, and a network of scientists providing scientific support. A widespread infestation by Aedes was found in both sites in 2008–2009, with 96.8%–100% trap positivity. Egg densities were markedly higher in SCC than in Ipojuca. A 90% decrease in egg density was recorded in SCC after two years of sustained control pressure imposed by suppression of >7,500,000 eggs and >3,200 adults, plus larval control by adding fishes to cisterns. In Ipojuca, 1.1 million mosquito eggs were suppressed and a 77% reduction in egg density was achieved. This study aimed at assessing the applicability of a system using GIS and spatial statistic analysis tools for quantitative assessment of mosquito populations. It also provided useful information on the requirements for reducing well-established mosquito populations. Results from two cities led us to conclude that the success in markedly reducing an Aedes population required the appropriate choice of control measures for sustained mass elimination guided by a user-friendly mosquito surveillance system. The system was able to support interventional decisions and to assess the program’s success. Additionally, it created a stimulating environment for health staff and residents, which had a positive impact on their commitment to the dengue control program.
Molecular Assessment of Non-Muscle Invasive and Muscle Invasive Bladder Tumors: Mapping of Putative Urothelial Stem Cells and Toll-Like Receptors (TLR) Signaling  [PDF]
Rafael Mamprin Stopiglia, Wagner Eduardo Matheus, Patrick Vianna Garcia, Athanase Billis, Mariana Anteghini Castilho, Vitor Hugo Figueiredo de Jesus, Ubirajara Ferreira, Wagner José Fávaro
Journal of Cancer Therapy (JCT) , 2015, DOI: 10.4236/jct.2015.62014

Purpose: The main objectives of this study were to characterize and compare the urothelial stem cells (healthy and cancer cells) and TLRs features in the urinary bladder of men without lesionsand with non-muscle-invasive and muscle invasive urothelial tumors. Materials and Methods: Thirty samples of the urinary bladder of 50 to 80-year-old men, with and without diagnosis of malignant urothelial lesions were used. The 30 samples were divided into 3 groups (n = 10 per group): Normal Group; Non-Muscle Invasive Bladder Cancer Group; Muscle Invasive Bladder Cancer Group. The samples were histopathologically and immunohistochemically analyzed. The study was conducted at teaching Hospital of the University of Campinas (UNICAMP). Results: The CD44 and CD133 immunoreactivities were significantly intense in the muscle-invasive cancer group when compared to the other groups. The ABCG2 biomarker demonstrated intense immunoreactivities in both non-muscle and muscle invasive groups, and absent immunoreactivity in the normal group. All groups showed weak CD117 immunoreactivity. Putative Healthy Stem Cells (CD44/CD133/ CD117+) occurred in all groups. Putative Cancer Stem Cells (CD44/CD133/ABCG2+) only occurred in the non-muscle and muscle invasive cancer groups. TLR2 immunoreactivity was significantly lower in the non-muscle invasive cancer group and absent in the muscle invasive cancer group. TLR4 immunoreactivity was significantly lower in both cancer groups. Conclusions: This study leads us to the conclusion that putative cancer stem cell occurrence was sensitive to the decreased in TLR2 and TLR4 immunoreactivities. Also, TLR2 and TLR4 demonstrated their involvement in the regulation of the different biomarkers for putative healthy and cancer urothelial stem cells, probably acting as negative regulators of urothelial carcinogenesis. Taken together data obtained suggest that use of TLRs agonists could be a promising alternative for the treatment of non-muscle and muscle invasive bladder tumors.

Effect of the use of curing salts and of a starter culture on the sensory and microbiological characteristics of homemade salamis
Spricigo, Cinthia Bittencourt;Pianovsky, Patrícia Bonat;
Brazilian Archives of Biology and Technology , 2005, DOI: 10.1590/S1516-89132005000400021
Abstract: homemade salamis may have their food safety guaranteed by means of the addition of curing salt and starter cultures, without loosing their traditional manufacturing recipes brought to brazil by the italian immigration in the early 20th century. in this work, the influence of curing salt and of a starter culture, composed of lactobacillus and staphylococcus, over the sensory and microbiological characteristics of italian type salamis, containing 3% lactose and 0.5% saccharose, was evaluated. the starter culture and the curing salt inhibited the development of staphylococcus aureus and of coliforms, and the salamis added with curing salt presented better color attributes.
Hybrid Decision Models in Non-Proportional Reinsurance  [PDF]
Maik Wagner
Technology and Investment (TI) , 2010, DOI: 10.4236/ti.2010.11008
Abstract: Over the past years, risk measurement and therewith risk measures became more and more important in economics. While in the past risk measures were already adopted at the deposit of credit and shareholders equity, the approach now generates two hybrid decision models and applies them to the reinsurance business. The two introduced models implement a convex combination of risk measures and with it provide the possibility of modelling risk attitudes. By doing that, for the two hybrid decision models on the one hand can be shown, which risk attitude leads to the acceptance of a reinsurance contract and on the other hand, a deductible of which height an insurer is willing to undertake. Hence the possibility exists to identify the risk attitude of an insurer. In return, due to the knowledge of risk attitudes, under similar conditions the possibility arises to establish recommendations about the extent of the deductible at reinsurance contracts.
A Generalization of Cramer’s Rule  [PDF]
Hugo Leiva
Advances in Linear Algebra & Matrix Theory (ALAMT) , 2015, DOI: 10.4236/alamt.2015.54016

In this paper, we find two formulas for the solutions of the following linear equation \"\"\"\", where \"\" is a \"\" real matrix. This system has been well studied since the 1970s. It is known and simple proven that there is a solution for all \"\" if, and only if, the rows of A are linearly independent, and the minimum norm solution is given by the Moore-Penrose inverse formula, which is often denoted by \"\" ; in this case, this solution is given by \"\". Using this formula, Cramer’s Rule and Burgstahler’s Theorem (Theorem 2), we prove the following representation for this solution


\"\", where \"\" are the row vectors of the matrix A. To the best of our knowledge and looking in to many Linear Algebra books, there is not formula for this solution depending on determinants. Of course, this formula coincides with the one given by Cramer’s Rule when \"\".

Co-transfection of plasmid DNA and laser-generated gold nanoparticles does not disturb the bioactivity of GFP-HMGB1 fusion protein
Svea Petersen, Jan T Soller, Siegfried Wagner, Andreas Richter, J?rn Bullerdiek, Ingo Nolte, Stephan Barcikowski, Hugo Escobar
Journal of Nanobiotechnology , 2009, DOI: 10.1186/1477-3155-7-6
Abstract: Gold nanoparticles (AuNPs) are used widely for various biomedical applications including cell imaging [1], diagnostics [2], targeted drug delivery [3], and sensing [4]. Various methods have been established for AuNP generation. Many of these rely on several chemical reactions or gas pyrolysis, showing the risk of impurities or agglomeration [5]. Laser ablation in liquids showed to be a powerful tool with many advantages, having almost no restriction in the choice of source material and the ability of yielding highly pure colloidal particles[6-11]. These pure AuNPs are characterised by their unique surface chemistry free of surfactants, a feature unattainable by other methods [12-14]. X-ray photoelectron spectroscopy of such AuNPs revealed the presence of the oxidation states Au+ and Au3+ at the AuNP surface [15]. In previous studies we demonstrated that unmodified DNA oligonucleotides adsorb easily onto these positively charged nanoparticles [16,17], probably via amino- and keto-groups, which interact with the electron accepting surface of the generated AuNPs. However, these findings raised the possibility that more complex biomolecules could also be attracted and bound to such nanoparticles' surfaces, if incubated intentionally or unintentionally with colloidal laser-generated gold nanoparticles, even if no additional conjugation is envisaged. Such binding could have a strong effect on the properties of biomolecules and should be characterised with a view of their potential toxicity [18].We therefore decided to analyse the possible effects of laser-generated AuNPs on DNA functionality. For this reason we incubated the charged particles with recombinant eGFP-C1-HMGB1 expression plasmids and subsequently transfected them into mammalian cells. As the HMGB1 protein is normally highly abundant in the cell nuclei, we were able to show that the treated expression plasmids are still functional and suitable for use as transcription matrix, because the transfected cells were
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