Estudo da topologia de redes de conexão funcional no córtex sensorial primário e hipocampo durante o sono de ondas lentas

Complex network analysis is a powerful tool into research of complex systems like brain networks. This work aims to describe the topological changes in neural functional connectivity networks of neocortex and hippocampus during slow-wave sleep (SWS) in animals submited to a novel experience exposure. Slow-wave sleep is an important sleep stage where occurs reverberations of electrical activities patterns of wakeness, playing a fundamental role in memory consolidation. Although its importance there s a lack of studies that characterize the topological dynamical of functional connectivity networks during that sleep stage. There s no studies that describe the topological modifications that novel exposure leads to this networks. We have observed that several topological properties have been modified after novel exposure and this modification remains for a long time. Major part of this changes in topological properties by novel exposure are related to fault tolerance

Estudo Comparativo de Métricas de Pontuação para Aprendizagem Estrutural de Redes Bayesianas

Bayesian networks are powerful tools as they represent probability distributions as graphs. They work with uncertainties of real systems. Since last decade there is a special interest in learning network structures from data. However learning the best network structure is a NP-Hard problem, so many heuristics algorithms to generate network structures from data were created. Many of these algorithms use score metrics to generate the network model. This thesis compare three of most used score metrics. The K-2 algorithm and two pattern benchmarks, ASIA and ALARM, were used to carry out the comparison. Results show that score metrics with hyperparameters that strength the tendency to select simpler network structures are better than score metrics with weaker tendency to select simpler network structures for both metrics (Heckerman-Geiger and modified MDL). Heckerman-Geiger Bayesian score metric works better than MDL with large datasets and MDL works better than Heckerman-Geiger with small datasets. The modified MDL gives similar results to Heckerman-Geiger for large datasets and close results to MDL for small datasets with stronger tendency to select simpler network structures

Modelagem de Superfícies Seletivas de Freqüência e Antenas de Microfita utilizando Redes Neurais Artificiais

This work has as main objective the application of Artificial Neural Networks, ANN, in the resolution of problems of RF /microwaves devices, as for example the prediction of the frequency response of some structures in an interest region. Artificial Neural Networks, are presently a alternative to the current methods of analysis of microwaves structures. Therefore they are capable to learn, and the more important to generalize the acquired knowledge, from any type of available data, keeping the precision of the original technique and adding the low computational cost of the neural models. For this reason, artificial neural networks are being increasily used for modeling microwaves devices. Multilayer Perceptron and Radial Base Functions models are used in this work. The advantages/disadvantages of these models and the referring algorithms of training of each one are described. Microwave planar devices, as Frequency Selective Surfaces and microstrip antennas, are in evidence due the increasing necessities of filtering and separation of eletromagnetic waves and the miniaturization of RF devices. Therefore, it is of fundamental importance the study of the structural parameters of these devices in a fast and accurate way. The presented results, show to the capacities of the neural techniques for modeling both Frequency Selective Surfaces and antennas

Previsão do módulo de elasticidade transversal de compósitos unidirecionais através de redes neurais mistas

The aim of this study is to create an artificial neural network (ANN) capable of modeling the transverse elasticity modulus (E2) of unidirectional composites. To that end, we used a dataset divided into two parts, one for training and the other for ANN testing. Three types of architectures from different networks were developed, one with only two inputs, one with three inputs and the third with mixed architecture combining an ANN with a model developed by Halpin-Tsai. After algorithm training, the results demonstrate that the use of ANNs is quite promising, given that when they were compared with those of the Halpín-Tsai mathematical model, higher correlation coefficient values and lower root mean square values were observed

Controle inteligente de sistemas eletroidráulicos utilizando redes neurais artificiais

This work describes the development of a nonlinear control strategy for an electro-hydraulic actuated system. The system to be controlled is represented by a third order ordinary differential equation subject to a dead-zone input. The control strategy is based on a nonlinear control scheme, combined with an artificial intelligence algorithm, namely, the method of feedback linearization and an artificial neural network. It is shown that, when such a hard nonlinearity and modeling inaccuracies are considered, the nonlinear technique alone is not enough to ensure a good performance of the controller. Therefore, a compensation strategy based on artificial neural networks, which have been notoriously used in systems that require the simulation of the process of human inference, is used. The multilayer perceptron network and the radial basis functions network as well are adopted and mathematically implemented within the control law. On this basis, the compensation ability considering both networks is compared. Furthermore, the application of new intelligent control strategies for nonlinear and uncertain mechanical systems are proposed, showing that the combination of a nonlinear control methodology and artificial neural networks improves the overall control system performance. Numerical results are presented to demonstrate the efficacy of the proposed control system

Desenvolvimento de perfis aerodinâmicos a partir de suas características utilizando redes neurais artificiais

One of the current major concerns in engineering is the development of aircrafts that have low power consumption and high performance. So, airfoils that have a high value of Lift Coefficient and a low value for the Drag Coefficient, generating a High-Efficiency airfoil are studied and designed. When the value of the Efficiency increases, the aircraft s fuel consumption decreases, thus improving its performance. Therefore, this work aims to develop a tool for designing of airfoils from desired characteristics, as Lift and Drag coefficients and the maximum Efficiency, using an algorithm based on an Artificial Neural Network (ANN). For this, it was initially collected an aerodynamic characteristics database, with a total of 300 airfoils, from the software XFoil. Then, through the software MATLAB, several network architectures were trained, between modular and hierarchical, using the Back-propagation algorithm and the Momentum rule. For data analysis, was used the technique of cross- validation, evaluating the network that has the lowest value of Root Mean Square (RMS). In this case, the best result was obtained for a hierarchical architecture with two modules and one layer of hidden neurons. The airfoils developed for that network, in the regions of lower RMS, were compared with the same airfoils imported into the software XFoil

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

O Modelo de Ising inomogêneo: uma interrupção contínua entre as redes quadrada e triangular.

The ferromagnetic and antiferromagnetic Ising model on a two dimensional inhomogeneous lattice characterized by two exchange constants (J1 and J2) is investigated. The lattice allows, in a continuous manner, the interpolation between the uniforme square (J2 = 0) and triangular (J2 = J1) lattices. By performing Monte Carlo simulation using the sequential Metropolis algorithm, we calculate the magnetization and the magnetic susceptibility on lattices of differents sizes. Applying the finite size scaling method through a data colappse, we obtained the critical temperatures as well as the critical exponents of the model for several values of the parameter α = J2 J1 in the [0, 1] range. The ferromagnetic case shows a linear increasing behavior of the critical temperature Tc for increasing values of α. Inwhich concerns the antiferromagnetic system, we observe a linear (decreasing) behavior of Tc, only for small values of α; in the range [0.6, 1], where frustrations effects are more pronunciated, the critical temperature Tc decays more quickly, possibly in a non-linear way, to the limiting value Tc = 0, cor-responding to the homogeneous fully frustrated antiferromagnetic triangular case.

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

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Propagação de danos no modelo de ising em redes de bravais e em fractais

In this work we have studied, by Monte Carlo computer simulation, several properties that characterize the damage spreading in the Ising model, defined in Bravais lattices (the square and the triangular lattices) and in the Sierpinski Gasket. First, we investigated the antiferromagnetic model in the triangular lattice with uniform magnetic field, by Glauber dynamics; The chaotic-frozen critical frontier that we obtained coincides , within error bars, with the paramegnetic-ferromagnetic frontier of the static transition. Using heat-bath dynamics, we have studied the ferromagnetic model in the Sierpinski Gasket: We have shown that there are two times that characterize the relaxation of the damage: One of them satisfy the generalized scaling theory proposed by Henley (critical exponent z~A/T for low temperatures). On the other hand, the other time does not obey any of the known scaling theories. Finally, we have used methods of time series analysis to study in Glauber dynamics, the damage in the ferromagnetic Ising model on a square lattice. We have obtained a Hurst exponent with value 0.5 in high temperatures and that grows to 1, close to the temperature TD, that separates the chaotic and the frozen phases

Ondas de spin em super-redes ferromagnéticas com campo de anisotropia

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

A relação de amizade nas redes sociais de estudantes universitários de Natal/RN

The basis of sociability in humans is based on cooperation. The relationship of friendship is vital to the social, emotional and cognitive development of an individual and can be understood as a consequence of selection for reciprocal altruism in humans. The period of adulthood is considered very suitable and appropriate for the investigation of the relations of friendship, but the Brazilian literature on friendship in adults is still nascent. Therefore, the objective was to characterize the relationship of friendship among college students. The study gathered 500 students from higher education institutions in the city of Natal-RN, Brazil, and 250 women (average age 24.1 ± 7.66 years) and 250 men (mean age 26.77 ± 9.64 years). Two questionnaires anonymously and individual were applied: a sociodemographic questionnaire and the other with the desired characteristics in idealized friends. Study 1 assessed the degree of importance of characteristics in the process of choosing a friend of the same sex and opposite sex of the participant. Study 2 investigated the relationship between patterns of idealization of friends and self-assessment of participants. Overall, were the preferred characteristics "Companionship" and "Sincerity" to idealized friends. We also found the influence of sex on the characteristics attributed to an female ideal friend, with emphasis on men for "Beauty/Good looks" and "Intelligence" and women to "Companionship" and "Sincerity". Finally, we observed a positive correlation between participants' self-assessment and preferences for the characteristics of the friends devised. This study revealed important elements for understanding the relationship of friendship, specifically the process of choosing friends. The results reinforce the importance of studying the relationship of friendship to a better understanding of human social behavior.

A dimensão sociocultural da reforma psiquiátrica: articulando redes para a consolidação da estratégia de atenção psicossocial

This thesis aims to discuss on articulations that have been produced on the socio-cultural field in the Psychiatric Reform process and its pertinence to the streghtening of Psychosocial Care Strategy (EAPS) in Fortaleza/CE. Such interest has been justified by the need to promote not only the production of these networks, but also interfaces to enable strategies of support and sociability from the perspective of deinstitutionalization of madness. We were inspired by the cartography perspective of Deleuze e Guattari, and determined as objectives: 1) to discuss the complexity of Psychiatric Reform process and analyze the EAPS as a model for the current Mental Health policy in the country; 2) to map socio-cultural strategies connected to the CAPS network in the city, investigating experiences that already exist or may be constituted as everyday social support networks; 3) from that mapping to start, define and discuss some aspects that converge to the accomplishment for this new mental health paradigm, drawing a cartography of the issues and movements in progress. The mapping was carried out in 2009 and consisted of semi-structured interviews with the coordinators of the 14 existent CAPS and with some people connected to the Coordination of Mental Health. Besides, during the whole development of the study, we have taken part in public events that brought us clues on the connection between mental health and culture. From the survey produced, we defined three vectors for discussion (Art, Labour and Partnership with Social Movements) which have been highlighted as effective possibilities of intervention in the socio-cultural field of Psychiatric Reform in Fortaleza and reveal important paths on the fulfillment process of a new pattern of care. For each of these axes, we chose a field of empirical research (Projeto Arte e Saúde, COOPCAPS e MSMCBJ) in which we could better understand their strengths and difficulties, starting from open interviews with some of their actors and the production of a diary of sensations in 2010. We have seen that they are articulated with the proposal of EAPS, being part of the concerns to the National Mental Health Policy and also the municipal administration. However, we have noticed to be necessary to promote those dimensions further, focusing on its complexity at the macro and micro policies, with the purpose of leading the Psychiatric Reform process

Síntese e caracterização de redes metalorgânicas baseadas em zinco e ácidos benzenodicarboxílicos

Metal Organic Frameworks (MOFs) are supramolecular structures consisted of ions or metal clusters coordinated to organic ligands which are repeated in two or three dimensions. These structures have atracted much attention due to their properties such as low density, high specific surface area and large volume of pores. In this work, MOFs consisted of zinc clusters connected by ditopic ligands, terephthalic acid (1,4- H2BDC) or isophthalic acid (1,3-H2BDC) were synthesized. To obtain the proposed materials, different routes and synthetic parameters were tested, such as the molar ratio of the precursors, the addition of template molecules, the type of solvente, the addition of organic base or the type of a counter-ion of Zn salt. It was found that the variation of these parameters led to the formation of different metalorganic structures. The solids obtained were characterized by XRD, SEM and IR. For the samples identified as MOF- 5, it was verified that the structure was composed of both interpenetrated and non interpenetrated structures. These samples showed a low stability, becoming totally transformed into another structure within less than 72 hours. The addition of the nickel and/or cobalt was found to be a promissing method for increasing the stability of MOF- 5, which in this case, still remained unconverted to another structure even after 15 days of exposure to air. The samples prepared from 1,3-H2BDC were probably new, still unknown Metal Organic Frameworks