Bifurcation analysis of a new Lorenz-like chaotic system

In this paper we study the local codimension one and two bifurcations which occur in a family of three-dimensional vector fields depending on three parameters. An equivalent family, depending on five parameters, was recently proposed as a new chaotic system with a Lorenz-like butterfly shaped attractor and was studied mainly from a numerical point of view, for particular values of the parameters, for which computational evidences of the chaotic attractor was shown. In order to contribute to the understand of this new system we present an analytical study and the bifurcation diagrams of an equivalent three parameter system, showing the qualitative changes in the dynamics of its solutions, for different values of the parameters. (C) 2007 Elsevier Ltd. All rights reserved.

Expression, purification, and circular dichroism analysis of human CDK9

The human cyclin-dependent kinase 9 (CDK9) protein was expressed in E coli BL21 using the pET23a vector at 30 degrees C. Several milligrams of protein were purified from soluble fraction using ionic exchange and ATP-affinity chromatography. The structural quality of recombinant CDK9 and the estimation of its secondary structure were obtained by circular dichroism. Structural models of CDK9 presented 26% of helices in agreement with the spectra by circular dichroism analysis. This is the first report on human CDK9 expression in Escherichia coli and structure analysis and provides the first step for the development of CDK9 inhibitors. (c) 2006 Elsevier B.V. All rights reserved.

An Intelligent System for Petroleum Well Drilling Cutting Analysis

Cutting analysis is a important and crucial task task to detect and prevent problems during the petroleum well drilling process. Several studies have been developed for drilling inspection, but none of them takes care about analysing the generated cutting at the vibrating shale shakers. Here we proposed a system to analyse the cutting's concentration at the vibrating shale shakers, which can indicate problems during the petroleum well drilling process, such that the collapse of the well borehole walls. Cutting's images are acquired and sent to the data analysis module, which has as the main goal to extract features and to classify frames according to one of three previously classes of cutting's volume. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and efficiency. We used the Optimum-Path Forest (OPF), Artificial Neural Network using Multi layer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC) for this task. The first one outperformed all the remaining classifiers. Recall that we are also the first to introduce the OPF classifier in this field of knowledge. Very good results show the robustness of the proposed system, which can be also integrated with other commonly system (Mud-Logging) in order to improve the last one's efficiency.

On 3-Parameter Families of Piecewise Smooth Vector Fields in the Plane

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

Neonatal BCG Immunization Followed by DNAhsp65 Boosters: Highly Immunogenic but not Protective Against Tuberculosis - a Paradoxical Effect of the Vector?

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

Population structure of the malaria vector Anopheles darlingi in Rondônia, Brazilian Amazon, based on mitochondrial DNA

Anopheles darlingi is the most important Brazilian malaria vector, with a widespread distribution in the Amazon forest. Effective strategies for vector control could be better developed through knowledge of its genetic structure and gene flow among populations, to assess the vector diversity and competence in transmitting Plasmodium. The aim of this study was to assess the genetic diversity of An. darlingi collected at four locations in Porto Velho, by sequencing a fragment of the ND4 mitochondrial gene. From 218 individual mosquitoes, we obtained 20 different haplotypes with a diversity index of 0.756, equivalent to that found in other neotropical anophelines. The analysis did not demonstrate significant population structure. However, haplotype diversity within some populations seems to be over-represented, suggesting the presence of sub-populations, but the presence of highly represented haplotypes complicates this analysis. There was no clear correlation among genetic and geographical distance and there were differences in relation to seasonality, which is important for malarial epidemiology.

A class of reversible quadratic polynomial vector fields on S-2

We study a class of quadratic reversible polynomial vector fields on S-2. We classify all the centers of this class of vector fields and we characterize its global phase portrait. (C) 2010 Elsevier B.V. All rights reserved.

On the reversible quadratic polynomial vector fields on S-2

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

STABLE PIECEWISE POLYNOMIAL VECTOR FIELDS

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

Petroleum well drilling monitoring through cutting image analysis and artificial intelligence techniques

Petroleum well drilling monitoring has become an important tool for detecting and preventing problems during the well drilling process. In this paper, we propose to assist the drilling process by analyzing the cutting images at the vibrating shake shaker, in which different concentrations of cuttings can indicate possible problems, such as the collapse of the well borehole walls. In such a way, we present here an innovative computer vision system composed by a real time cutting volume estimator addressed by support vector regression. As far we know, we are the first to propose the petroleum well drilling monitoring by cutting image analysis. We also applied a collection of supervised classifiers for cutting volume classification. (C) 2010 Elsevier Ltd. All rights reserved.

Spatial evaluation of larvae of Culicidae (Diptera) from different breeding sites: application of a geospatial method and implications for vector control

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Periodic orbits for a class of reversible quadratic vector field on R-3

For a class of reversible quadratic vector fields on R-3 we study the periodic orbits that bifurcate from a heteroclinic loop having two singular points at infinity connected by an invariant straight line in the finite part and another straight line at infinity in the local chart U-2. More specifically, we prove that for all n is an element of N, there exists epsilon(n) > 0 such that the reversible quadratic polynomial differential systemx = a(0) + a(1y) + a(3y)(2) + a(4Y)(2) + epsilon(a(2x)(2) + a(3xz)),y = b(1z) + b(3yz) + epsilon b(2xy),z = c(1y) +c(4az)(2) + epsilon c(2xz)in R-3, with a(0) < 0, b(1)c(1) < 0, a(2) < 0, b(2) < a(2), a(4) > 0, c(2) < a(2) and b(3) is not an element of (c(4), 4c(4)), for epsilon is an element of (0, epsilon(n)) has at least n periodic orbits near the heteroclinic loop. (c) 2007 Elsevier B.V. All rights reserved.

A singular approach to discontinuous vector fields on the plane

In this paper we deal with discontinuous vector fields on R-2 and we prove that the analysis of their local behavior around a typical singularity can be treated via singular perturbation. The regularization process developed by Sotomayor and Teixeira is crucial for the development of this work. (c) 2006 Elsevier B.V. All rights reserved.

Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.

Signal and backgrounds for the single production of scalar and vector leptoquarks at the CERN LHC

We perform a detailed analysis of the potentiality of the CERN Large Hadron Collider to study the single production of leptoquarks via pp→e±q→ leptoquark →e± q, with e± generated by the splitting of photons radiated by the protons. Working with the most general SU(2)L⊗U( 1 )Y invariant effective Lagrangian for scalar and vector leptoquarks, we analyze in detail the leptoquark signals and backgrounds that lead to a final state containing an e± and a hard jet with approximately balanced transverse momenta. Our results indicate that the LHC will be able to discover leptoquarks with masses up to 2-3 TeV, depending on their type, for Yukawa couplings of the order of the electromagnetic one.