Estudo clássico completo do formalismo de Hamilton-Jacobi

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise genética de resistência ao Rhipicephalus (Boophilus) microplus em bovinos cruzados Hereford x Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

O princípio de ação quântica de Schwinger: aspectos do tratamento de sistemas dependentes do tempo e interagentes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Process for genetically engineering acidophilic bacteria and constructing a transformation vector

The present invention describes a method for transforming chemolithotrophic acidophilic bacteria using electroporation technology. The proposed method allows transforming a bacterial line using a transformation vector, the pAF vector, which contains an origin of vegetative replication that allows the vector to replicate inside the bacteria without altering the natural physiological functions of the latter. Also disclosed is the use of the bacteria modified according to the invention in bioleaching processes of sulphated copper, gold, uranium, nickel, zinc and cobalt ore, inter alia.

Photochemical transformation of antibiotics by excitation of Fe(III)-complexes in aqueous medium

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Salivary carriage of periodontal pathogens in generalized aggressive periodontitis families

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Leukotoxicity of Aggregatibacter actinomycetemcomitans in generalized aggressive periodontitis in Brazilians and their family members

Objective: The purpose of this study was to examine the leukotoxin promoter types of Aggregatibacter actinomycetemcomitans clones in subjects with generalized aggressive periodontitis (GAgP) and in their family members (FM). Material and Methods: Thirty-five patients with GAgP (33.9+/-7.1 years), 33 of their FM (22.8+/-11.4 years), and 41 patients with chronic periodontitis (CP) (44.1+/-9.4 years) were clinically analyzed using the plaque index, gingival index, probing depth (PD), and clinical attachment level (CAL). Subgingival biofilm samples were collected from four interproximal periodontal sites (>PD and >CAL) of each patient. The presence of A. actinomycetemcomitans and its leukotoxic clone was confirmed by polymerase chain reaction (PCR). Results: A. actinomycetemcomitans was observed in 23 (51.1%) GAgP patients and 16 (30.1%) CP patients. Thirty-seven (94.8%) patients showed minimally leukotoxic strains and 2 (5.1%) showed highly leukotoxic strains. In the FM group, 10 (30.3%) had aggressive periodontitis (AgP), 12 (36.3%) had CP, 11 (33.3%) were periodontally healthy or had gingivitis, and 12.2% were A. actinomycetemcomitans positive. Greater full mouth PD and CAL were observed in GAgP patients positive for the bacteria than those negative for it (p<0.05), and the presence of A. actinomycetemcomitans positively correlated with GAgP (Odds ratio, 3.1; confidence interval, 1.4-7.0; p=0.009). Conclusions: The presence of A. actinomycetemcomitans was associated with the clinical condition of GAgP, with most patients exhibiting a generalized form of the disease and minimally leukotoxic clones. Most of the relatives of GAgP patients presented either CP or AgP.

Computer intensive methods for controlling bias in a generalized species diversity index

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The bias in reversing the Box-Cox transformation in time series forecasting: An empirical study based on neural networks

The Box-Cox transformation is a technique mostly utilized to turn the probabilistic distribution of a time series data into approximately normal. And this helps statistical and neural models to perform more accurate forecastings. However, it introduces a bias when the reversion of the transformation is conducted with the predicted data. The statistical methods to perform a bias-free reversion require, necessarily, the assumption of Gaussianity of the transformed data distribution, which is a rare event in real-world time series. So, the aim of this study was to provide an effective method of removing the bias when the reversion of the Box-Cox transformation is executed. Thus, the developed method is based on a focused time lagged feedforward neural network, which does not require any assumption about the transformed data distribution. Therefore, to evaluate the performance of the proposed method, numerical simulations were conducted and the Mean Absolute Percentage Error, the Theil Inequality Index and the Signal-to-Noise ratio of 20-step-ahead forecasts of 40 time series were compared, and the results obtained indicate that the proposed reversion method is valid and justifies new studies. (C) 2014 Elsevier B.V. All rights reserved.