Otimização de forma aplicando B-splines sob critério integral de tensões

This work proposes a computational methodology to solve problems of optimization in structural design. The application develops, implements and integrates methods for structural analysis, geometric modeling, design sensitivity analysis and optimization. So, the optimum design problem is particularized for plane stress case, with the objective to minimize the structural mass subject to a stress criterion. Notice that, these constraints must be evaluated at a series of discrete points, whose distribution should be dense enough in order to minimize the chance of any significant constraint violation between specified points. Therefore, the local stress constraints are transformed into a global stress measure reducing the computational cost in deriving the optimal shape design. The problem is approximated by Finite Element Method using Lagrangian triangular elements with six nodes, and use a automatic mesh generation with a mesh quality criterion of geometric element. The geometric modeling, i.e., the contour is defined by parametric curves of type B-splines, these curves hold suitable characteristics to implement the Shape Optimization Method, that uses the key points like design variables to determine the solution of minimum problem. A reliable tool for design sensitivity analysis is a prerequisite for performing interactive structural design, synthesis and optimization. General expressions for design sensitivity analysis are derived with respect to key points of B-splines. The method of design sensitivity analysis used is the adjoin approach and the analytical method. The formulation of the optimization problem applies the Augmented Lagrangian Method, which convert an optimization problem constrained problem in an unconstrained. The solution of the Augmented Lagrangian function is achieved by determining the analysis of sensitivity. Therefore, the optimization problem reduces to the solution of a sequence of problems with lateral limits constraints, which is solved by the Memoryless Quasi-Newton Method It is demonstrated by several examples that this new approach of analytical design sensitivity analysis of integrated shape design optimization with a global stress criterion purpose is computationally efficient

Indicadores de cálcio e de voltagem codificados geneticamente na detecção de potenciais de ação e inputs sinápticos em cultura de neurônios hipocampais

Recently, genetically encoded optical indicators have emerged as noninvasive tools of high spatial and temporal resolution utilized to monitor the activity of individual neurons and specific neuronal populations. The increasing number of new optogenetic indicators, together with the absence of comparisons under identical conditions, has generated difficulty in choosing the most appropriate protein, depending on the experimental design. Therefore, the purpose of our study was to compare three recently developed reporter proteins: the calcium indicators GCaMP3 and R-GECO1, and the voltage indicator VSFP butterfly1.2. These probes were expressed in hippocampal neurons in culture, which were subjected to patchclamp recordings and optical imaging. The three groups (each one expressing a protein) exhibited similar values of membrane potential (in mV, GCaMP3: -56 ±8.0, R-GECO1: -57 ±2.5; VSFP: -60 ±3.9, p = 0.86); however, the group of neurons expressing VSFP showed a lower average of input resistance than the other groups (in Mohms, GCaMP3: 161 ±18.3; GECO1-R: 128 ±15.3; VSFP: 94 ±14.0, p = 0.02). Each neuron was submitted to current injections at different frequencies (10 Hz, 5 Hz, 3 Hz, 1.5 Hz, and 0.7 Hz) and their fluorescence responses were recorded in time. In our study, only 26.7% (4/15) of the neurons expressing VSFP showed detectable fluorescence signal in response to action potentials (APs). The average signal-to-noise ratio (SNR) obtained in response to five spikes (at 10 Hz) was small (1.3 ± 0.21), however the rapid kinetics of the VSFP allowed discrimination of APs as individual peaks, with detection of 53% of the evoked APs. Frequencies below 5 Hz and subthreshold signals were undetectable due to high noise. On the other hand, calcium indicators showed the greatest change in fluorescence following the same protocol (five APs at 10 Hz). Among the GCaMP3 expressing neurons, 80% (8/10) exhibited signal, with an average SNR value of 21 ±6.69 (soma), while for the R-GECO1 neurons, 50% (2/4) of the neurons had signal, with a mean SNR value of 52 ±19.7 (soma). For protocols at 10 Hz, 54% of the evoked APs were detected with GCaMP3 and 85% with R-GECO1. APs were detectable in all the analyzed frequencies and fluorescence signals were detected from subthreshold depolarizations as well. Because GCaMP3 is the most likely to yield fluorescence signal and with high SNR, some experiments were performed only with this probe. We demonstrate that GCaMP3 is effective in detecting synaptic inputs (involving Ca2+ influx), with high spatial and temporal resolution. Differences were also observed between the SNR values resulting from evoked APs, compared to spontaneous APs. In recordings of groups of cells, GCaMP3 showed clear discrimination between activated and silent cells, and reveals itself as a potential tool in studies of neuronal synchronization. Thus, our results indicate that the presently available calcium indicators allow detailed studies on neuronal communication, ranging from individual dendritic spines to the investigation of events of synchrony in neuronal networks genetically defined. In contrast, studies employing VSFPs represent a promising technology for monitoring neural activity and, although still to be improved, they may become more appropriate than calcium indicators, since neurons work on a time scale faster than events of calcium may foresee

Técnicas neuronais de agrupamentos aplicadas à detecção de anomalias em mamogramas digitais

This work proposes the development of an intelligent system for analysis of digital mammograms, capable to detect and to classify masses and microcalcifications. The digital mammograms will be pre-processed through techniques of digital processing of images with the purpose of adapting the image to the detection system and automatic classification of the existent calcifications in the suckles. The model adopted for the detection and classification of the mammograms uses the neural network of Kohonen by the algorithm Self Organization Map - SOM. The algorithm of Vector quantization, Kmeans it is also used with the same purpose of the SOM. An analysis of the performance of the two algorithms in the automatic classification of digital mammograms is developed. The developed system will aid the radiologist in the diagnosis and accompaniment of the development of abnormalities

Sistema inteligente para detecção de vazamentos em dutos de petróleo usando transformada Wavelet e redes neurais

This work consists in the use of techniques of signals processing and artificial neural networks to identify leaks in pipes with multiphase flow. In the traditional methods of leak detection exists a great difficulty to mount a profile, that is adjusted to the found in real conditions of the oil transport. These difficult conditions go since the unevenly soil that cause columns or vacuum throughout pipelines until the presence of multiphases like water, gas and oil; plus other components as sand, which use to produce discontinuous flow off and diverse variations. To attenuate these difficulties, the transform wavelet was used to map the signal pressure in different resolution plan allowing the extraction of descriptors that identify leaks patterns and with then to provide training for the neural network to learning of how to classify this pattern and report whenever this characterize leaks. During the tests were used transient and regime signals and pipelines with punctures with size variations from ½' to 1' of diameter to simulate leaks and between Upanema and Estreito B, of the UN-RNCE of the Petrobras, where it was possible to detect leaks. The results show that the proposed descriptors considered, based in statistical methods applied in domain transform, are sufficient to identify leaks patterns and make it possible to train the neural classifier to indicate the occurrence of pipeline leaks

Recuperação e purificação de quitosanases usando adsorção em leito expandido com streamline DEAE com modelagem e simulação usando redes neurais

Expanded Bed Adsorption (EBA) is an integrative process that combines concepts of chromatography and fluidization of solids. The many parameters involved and their synergistic effects complicate the optimization of the process. Fortunately, some mathematical tools have been developed in order to guide the investigation of the EBA system. In this work the application of experimental design, phenomenological modeling and artificial neural networks (ANN) in understanding chitosanases adsorption on ion exchange resin Streamline® DEAE have been investigated. The strain Paenibacillus ehimensis NRRL B-23118 was used for chitosanase production. EBA experiments were carried out using a column of 2.6 cm inner diameter with 30.0 cm in height that was coupled to a peristaltic pump. At the bottom of the column there was a distributor of glass beads having a height of 3.0 cm. Assays for residence time distribution (RTD) revelead a high degree of mixing, however, the Richardson-Zaki coefficients showed that the column was on the threshold of stability. Isotherm models fitted the adsorption equilibrium data in the presence of lyotropic salts. The results of experiment design indicated that the ionic strength and superficial velocity are important to the recovery and purity of chitosanases. The molecular mass of the two chitosanases were approximately 23 kDa and 52 kDa as estimated by SDS-PAGE. The phenomenological modeling was aimed to describe the operations in batch and column chromatography. The simulations were performed in Microsoft Visual Studio. The kinetic rate constant model set to kinetic curves efficiently under conditions of initial enzyme activity 0.232, 0.142 e 0.079 UA/mL. The simulated breakthrough curves showed some differences with experimental data, especially regarding the slope. Sensitivity tests of the model on the surface velocity, axial dispersion and initial concentration showed agreement with the literature. The neural network was constructed in MATLAB and Neural Network Toolbox. The cross-validation was used to improve the ability of generalization. The parameters of ANN were improved to obtain the settings 6-6 (enzyme activity) and 9-6 (total protein), as well as tansig transfer function and Levenberg-Marquardt training algorithm. The neural Carlos Eduardo de Araújo Padilha dezembro/2013 9 networks simulations, including all the steps of cycle, showed good agreement with experimental data, with a correlation coefficient of approximately 0.974. The effects of input variables on profiles of the stages of loading, washing and elution were consistent with the literature

Conexão entre as redes complexas e estatística de Kaniadakis e busca eficiente das propriedades críticas do processo epidêmico difusivo 1D

In this work we study a connection between a non-Gaussian statistics, the Kaniadakis statistics, and Complex Networks. We show that the degree distribution P(k)of a scale free-network, can be calculated using a maximization of information entropy in the context of non-gaussian statistics. As an example, a numerical analysis based on the preferential attachment growth model is discussed, as well as a numerical behavior of the Kaniadakis and Tsallis degree distribution is compared. We also analyze the diffusive epidemic process (DEP) on a regular lattice one-dimensional. The model is composed of A (healthy) and B (sick) species that independently diffusive on lattice with diffusion rates DA and DB for which the probabilistic dynamical rule A + B → 2B and B → A. This model belongs to the category of non-equilibrium systems with an absorbing state and a phase transition between active an inactive states. We investigate the critical behavior of the DEP using an auto-adaptive algorithm to find critical points: the method of automatic searching for critical points (MASCP). We compare our results with the literature and we find that the MASCP successfully finds the critical exponents 1/ѵ and 1/zѵ in all the cases DA =DB, DA DB. The simulations show that the DEP has the same critical exponents as are expected from field-theoretical arguments. Moreover, we find that, contrary to a renormalization group prediction, the system does not show a discontinuous phase transition in the regime o DA >DB.

Espectro de polariton de plasmons e propriedades ópitcas de super-redes tipo cantor

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Polaritons de exciton em super-redes semicondutoras

In this work we study the spectrum (bulk and surface modes) of exciton-polaritons in infinite and semi-infinite binary superlattices (such as, ···ABABA···), where the semiconductor medium (A), whose dielectric function depends on the frequency and the wavevector, alternating with a standard dielectric medium B. Here the medium A will be modeled by a nitride III-V semiconductor whose main characteristic is a wide-direct energy gap Eg. In particular, we consider the numerical values of gallium nitride (GaN) with a crystal structure wurtzite type. The transfer-matrix formalism is used to find the exciton-polariton dispersion relation. The results are obtained for both s (TE mode: transverse electric) and p (TM mode: transverse magnetic) polarizations, using three diferent kind of additional boundary conditions (ABC1, 2 e 3) besides the standard Maxwell's boundary conditions. Moreover, we investigate the behavior of the exciton-polariton modes for diferent ratios of the thickness of the two alternating materials forming the superlattice. The spectrums shows a confinement of the exciton-polariton modes due to the geometry of the superlattice. The method of Attenuated Total Reflection (ATR) and Raman scattering are the most adequate for probing this excitations