As relações entre tectonismo e seqüências deposiconais no rifte potiguar - porção SW do Graben de Umbuzeiro, bacia potiguar emersa

Through an integrated approach, using litho, chrono and biostratigraphic data, the relative importance of climate variations and tectonics were recognized in rift sediments of the onshore Potiguar Basin, Northeast Brazil. Concepts of sequence stratigraphy were applied as a template to integrate sedimentological and geochemical data (oxygen isotopes), as well as quantitative palynologic methods to address and recognize the main depositional patterns produced in a rift basin. The main objective was to address the relative importance of climate changes and tectonics to the resultant stratigraphic architecture. The results of computer simulations of sedimentary basin fills of rift basins were quite useful to test working hypothesis and mimic the process of filling a half graben during a rift event. The studied section includes a neovalanginian-eobarremian (Lower Cretaceous) rift interval from the Pendência Formation, located in the southwestern portion of Umbuzeiro Graben, in the offshore Potiguar Basin. The depositional setting is interpreted as progradational deltaic system entering a lake from its flexural margin. Sismoestratigraphyc and well logs analyses allowed to interpret two regressive intervals (Green and Yellow Sequences), separated by a broad transgressive interval (Orange Sequence), known as the Livramento Shale. The depositional history encompass three stages: two tectonically active phases, during the deposition of the Green and Yellow Sequences, and a tectonically quiescent phase, during the deposition of the Orange Sequence. Paleoclimatic interpretation, based on quantitative palynology and geochemical data (��18O), suggests a tendency to arid conditions during the tectonically active phases and wet conditions during the tectonically quiescent phase. Stratigraphic modeling and backstripping techniques, supported by paleoclimatic/paleoecologic interpretations provide a powerful methodology to evaluate the tectonic and climatic controls on tectonic lakes

Imageamento digital de paleocavernas colapsadas com georadar

In this study, the methodological procedures involved in digital imaging of collapsed paleocaves in tufa using GPR are presented. These carbonate deposits occur in the Quixeré region, Ceará State (NE Brazil), on the western border of the Potiguar Basin. Collapsed paleocaves are exposed along a state road, which were selected to this study. We chose a portion of the called Quixeré outcrop for making a photomosaic and caring out a GPR test section to compare and parameterize the karst geometries on the geophysical line. The results were satisfactory and led to the adoption of criteria for the interpretation of others GPR sections acquired in the region of the Quixeré outcrop. Two grids of GPR lines were acquired; the first one was wider and more spaced and guided the location of the second grid, denser and located in the southern part of the outcrop. The radargrams of the second grid reveal satisfactorily the collapsed paleocaves geometries. For each grid has been developed a digital solid model of the Quixeré outcrop. The first model allows the recognition of the general distribution and location of collapsed paleocaves in tufa deposits, while the second more detailed digital model provides not only the 3D individualization of the major paleocaves, but also the estimation of their respective volumes. The digital solid models are presented here as a new frontier in the study of analog outcrops to reservoirs (for groundwater and hydrocarbon), in which the volumetric parameterization and characterization of geological bodies become essential for composing the databases, which together with petrophysical properties information, are used in more realistic computer simulations for sedimentary reservoirs.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

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

Método da histerese por auto-ajuste para minimização de esforço de controle no separador submarino VASPS

Neste trabalho apresenta-se o estudo do desenvolvimento de um controlador não-tradicional baseado em um mecanismo de histerese com auto-ajuste para o controle de nível de líquido de um sistema de separação e bombeio submarino conhecido como VASPS. O controlador desenvolvido gera sinais enviados para a bomba centrífuga submersa para controlar o nível de líquido no tanque do separador, evitando que ele atinja valores muito baixos que poderiam danificar a bomba ou valores muito altos que reduziriam a eficiência da separação líquido/gás. Os sinais de controle gerados pelo controlador visam solicitar a bomba o mínimo possível de modo a evitar o seu desgaste e falhas prematuras. Nas simulações, o controlador desenvolvido foi testado sob grandes variações nas condições de operação, tais como golfadas, produzindo resultados bastante satisfatórios e promissores.

Neutron Diffraction Study of Liquid N-Methylformamide Using EPSR Simulation

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

Time evolution of the structure function and dynamical scaling in porous SnO2 dry gels

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Another prefiltering algorithm for adaptive IIR filtering

An algorithm for adaptive IIR filtering that uses prefiltering structure in direct form is presented. This structure has an estimation error that is a linear function of the coefficients. This property greatly simplifies the derivation of gradient-based algorithms. Computer simulations show that the proposed structure improves convergence speed.

Diversity of fragments in the collapse of brittle solids

An experimental study of fragmentation of brittle solids under the application of repeated impulsive force is made, emphasizing the behavior of the diversity of fragments. Several scaling relations involving diversity and number of fragments are obtained from experiments and the results are compared with computer simulations. © 1998 Elsevier Science B.V. All rights reserved.

Diet, phylogeny, and basal metabolic rate in phyllostomid bats

Aside from the pervasive effects of body mass, much controversy exists as to what factors account for interspecific variation in basal metabolic rates (BMR) of mammals; however, both diet and phylogeny have been strongly implicated. We examined variation in BMR within the New World bat family Phyllostomidae, which shows the largest diversity of food habits among mammalian families, including frugivorous, nectarivorous, insectivorous, carnivorous and blood-eating species. For 27 species, diet was taken from the literature and BMR was either measured on animals captured in Brazil or extracted from the literature. Conventional (nonphylogenetic) analysis of covariance (ANCOVA), with body mass as the covariate, was first used to test the effects of diet on BMR. In this analysis, which assumes that all species evolved simultaneously from a single ancestor (i.e., a star phylogeny), diet exerted a strong effect on mass-in-dependent BMR: nectarivorous bats showed higher mass-independent BMR than other bats feeding on fruits, insects or blood. In phylogenetic ANCOVAs via Monte Carlo computer simulation, which assume that species are part of a branching hierarchical phylogeny, no statistically significant effect of diet on BMR was observed. Hence, results of the nonphylogenetic analysis were misleading because the critical values for testing the effect of diet were underestimated. However, in this sample of bats, diet is perfectly confounded with phylogeny, because the four dietary categories represent four separate subclades, which greatly reduces statistical power to detect a diet (= subclade) effect. But even if diet did appear to exert an influence on BMR in this sample of bats, it would not be logically possible to separate this effect from the possibility that the dietary categories differ for some other reason (i.e., another synapomorphy of one or more of the subclades). Examples such as this highlight the importance of considering phylogenetic relationships when designing new comparative studies, as well as when analyzing existing data sets. We also discuss some possible reasons why BMR may not coadapt with diet. © by Urban & Fischer Verlag.

Tuning of fuzzy inference systems through unconstrained optimization techniques

This paper presents a new methodology for the adjustment of fuzzy inference systems. A novel approach, which uses unconstrained optimization techniques, is developed in order to adjust the free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through an estimation of time series. More specifically, the Mackey-Glass chaotic time series estimation is used for the validation of the proposed methodology.

Information and mechanical models of intelligence: What can we learn from cognitive science?

The impact of new advanced technology on issues that concern meaningful information and its relation to studies of intelligence constitutes the main topic of the present paper. The advantages, disadvantages and implications of the synthetic methodology developed by cognitive scientists, according to which mechanical models of the mind, such as computer simulations or self-organizing robots, may provide good explanatory tools to investigate cognition, are discussed. A difficulty with this methodology is pointed out, namely the use of meaningless information to explain intelligent behavior that incorporates meaningful information. In this context, it is inquired what are the contributions of cognitive science to contemporary studies of intelligent behavior and how technology may play a role in the analysis of the relationships established by organisms in their natural and social environments. © John Benjamins Publishing Company.

Efficient parametric adjustment of fuzzy inference system using unconstrained optimization

This paper presents a new methodology for the adjustment of fuzzy inference systems, which uses technique based on error back-propagation method. The free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules, are automatically adjusted. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through estimation of time series and by a mathematical modeling problem. More specifically, the Mackey-Glass chaotic time series is used for the validation of the proposed methodology. © Springer-Verlag Berlin Heidelberg 2007.

Modeling for performance analysis of electromagnetic zero-sequence suppressor

The purpose of this work is to present a frequency domain model to demonstrate the operation of an electromagnetic arrangement for controlling the injection of zero-sequence currents in the electrical system. Considering the diversity of sequential distribution of harmonic components of a current, the device proposed can be used in the process of mitigation of zero-sequence components. This device, here called electromagnetic suppressor, consists of a blocker and filter both electromagnetic, whose joint operation can provide paths of high and low impedances that can be conveniently adjusted in order to search for a desired performance. This study presents physical considerations, mathematical modeling and computer simulations that clearly demonstrate the viability of this application as a more viable alternative in the conception of filtering systems. The performance analysis is based on the frequency response of harmonic transmittances. The efficacy of this technique in direct actions to maximize the harmonic mitigation process is demonstrated. ©2010 IEEE.

Optimal trajectory and solution of the inverse kinematics of a robotic manipulator by genetic algorithms

This paper presents the generation of optimal trajectories by genetic algorithms (GA) for a planar robotic manipulator. The implemented GA considers a multi-objective function that minimizes the end-effector positioning error together with the joints angular displacement and it solves the inverse kinematics problem for the trajectory. Computer simulations results are presented to illustrate this implementation and show the efficiency of the used methodology producing soft trajectories with low computing cost. © 2011 Springer-Verlag Berlin Heidelberg.

Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.