Preparação e carcterização de complexos multicomponentes contendo ciclodextrinas e benznidazol

The benznidazole (BNZ) is the only alternative for Chagas disease treatment in Brazil. This drug has low solubility, which restricts its dissolution rate. Thus, the present work aimed to study the BNZ interactions in binary systems with beta cyclodextrin (β-CD) and hydroxypropyl-beta cyclodextrin (HP-β-CD), in order to increase the apparent aqueous solubility of drug. The influence of seven hydrophilic polymers, triethanolamine (TEA) and 1-methyl-2- pyrrolidone (NMP) in benznidazole apparent aqueous solubility, as well as the formation of inclusion complexes was also investigated. The interactions in solution were predicted and investigated using phase solubility diagram methodology, nuclear magnetic resonance of protons (RMN) and molecular modeling. Complexes were obtained in solid phase by spray drying and physicochemical characterization included the UV-Vis spectrophotometric spectroscopy in the infrared region, scanning electron microscopy, X-ray diffraction and dissolution drug test from the different systems. The increment on apparent aqueous solubility of drug was achieved with a linear type (AL) in presence of both cyclodextrins at different pH values. The hydrophilic polymers and 1-methyl-2-pyrrolidone contributes to the formation of inclusion complexes, while the triethanolamine decreased the complex stability constant (Kc). The log-linear model applied for solubility diagrams revealed that both triethanolamine and 1-methyl-2-pyrrolidone showed an action cosolvent (both solvents) and complexing (1-methyl-2-pyrrolidone). The best results were obtained with complexes involving 1-methyl-2-pyrrolidone and hydroxypropylbeta- cyclodextrin, with an increased of benznidazole solubility in 27.9 and 9.4 times, respectively. The complexes effectiveness was proven by dissolution tests, in which the ternary complexes and physical mixtures involving 1-methyl- 2-pyrrolidone and both cyclodextrins investigated showed better results, showing the potential use as novel pharmaceutical ingredient, that leads to increased benznidazole bioavailability

Estrutura ANFIS modificada para identificação e controle de plantas com ampla faixa de operação e não linearidade acentuada

In this work a modification on ANFIS (Adaptive Network Based Fuzzy Inference System) structure is proposed to find a systematic method for nonlinear plants, with large operational range, identification and control, using linear local systems: models and controllers. This method is based on multiple model approach. This way, linear local models are obtained and then those models are combined by the proposed neurofuzzy structure. A metric that allows a satisfactory combination of those models is obtained after the structure training. It results on plant s global identification. A controller is projected for each local model. The global control is obtained by mixing local controllers signals. This is done by the modified ANFIS. The modification on ANFIS architecture allows the two neurofuzzy structures knowledge sharing. So the same metric obtained to combine models can be used to combine controllers. Two cases study are used to validate the new ANFIS structure. The knowledge sharing is evaluated in the second case study. It shows that just one modified ANFIS structure is necessary to combine linear models to identify, a nonlinear plant, and combine linear controllers to control this plant. The proposed method allows the usage of any identification and control techniques for local models and local controllers obtaining. It also reduces the complexity of ANFIS usage for identification and control. This work has prioritized simpler techniques for the identification and control systems to simplify the use of the method

Aids em idosos no Brasil no período de 2000 a 2012: uma análise de série temporal e dos fatores contextuais associados

The characteristics profile of individuals who develop AIDS in Brazil has changed over time. Among these modifications, a worrying finding is the increased incidence of AIDS in the elderly across the country. But, however, is not yet clear whether the increase in AIDS cases is sufficient to produce a change in the trend of measures in recent years in the Brazilian states, and this increase has an effect from the socioeconomic and demographic indicators. In this sense, the objective of this study is to analyze the AIDS incidence rates among the elderly in Brazil and its effect on socioeconomic and demographic inequalities in the period 2000 to 2012. This is an ecological time-series study to meet behavior of the time series of the incidence rates of AIDS in the elderly from 2000 to 2012. the rates were calculated using the secondary data from Diseases Information System Notification and the Brazilian Institute of Geography and Statistics. Data were analyzed statistically to know the trends in incidence rates, by polynomial regression model and joinpoint log-linear regression model, but also the simple linear regression analysis to find the relationship of trends with variables socioeconomic and demographic. SPSS 20.0® and Joinpoint 4.1.1 programs were used. All tests were carried out considering a significance of 5%. After the analysis, in Brazil were reported 62,052 new cases of AIDS in the elderly from 2000 to 2012. During this period, a significant increase was found for males, both aged 50-59 years (APPC: 3.46 %, p <0.001), such as above 59 years (AAPC: 4.38%; p <0.001). For females, the increase was significant and has the largest increments in the time series, when compared to males in both age groups (AAPC: 4.62%, p <0.001 and AAPC: 6.53%; p <0.001) respectively. The largest increases are observed in women and in the states of North and Northeast. In the Southeast Region is observed stabilization of rates throughout the series. The reason of trends between the sexes had a significant reduction, but also an approach in both age groups of the study, reaching a ratio of 1.7 males for every female in the youngest age group. The trends were related to illiteracy rates, with increasing social inequality and the lowest human development in the Brazilian states. We conclude that in Brazil the incidence of AIDS in the elderly follows an increasing trend in individuals over 50 years. Noteworthy are the highest rates of study in women and in the states of North and Northeast. In this sense, the country needs to enhance policies towards older people with STD / AIDS, training health professionals and developing effective measures for the prevention and early diagnosis of infected people, especially in places with limited resources and high social inequality. In the long term, it is developing new studies to understand whether the measures taken were effective in reducing the trends identified in this study.

Mortalidade da população em idade ativa (PIA) por doença cardiovascular e câncer nas capitais e nas regiões metropolitanas brasileiras: associação com indicadores socioeconômicos

Universidade Estadual do Rio Grande do Norte

Análise e desenvolvimento de controladores preditivos multivariáveis baseados em multi-modelos bilineares

This work addresses issues related to analysis and development of multivariable predictive controllers based on bilinear multi-models. Linear Generalized Predictive Control (GPC) monovariable and multivariable is shown, and highlighted its properties, key features and applications in industry. Bilinear GPC, the basis for the development of this thesis, is presented by the time-step quasilinearization approach. Some results are presented using this controller in order to show its best performance when compared to linear GPC, since the bilinear models represent better the dynamics of certain processes. Time-step quasilinearization, due to the fact that it is an approximation, causes a prediction error, which limits the performance of this controller when prediction horizon increases. Due to its prediction error, Bilinear GPC with iterative compensation is shown in order to minimize this error, seeking a better performance than the classic Bilinear GPC. Results of iterative compensation algorithm are shown. The use of multi-model is discussed in this thesis, in order to correct the deficiency of controllers based on single model, when they are applied in cases with large operation ranges. Methods of measuring the distance between models, also called metrics, are the main contribution of this thesis. Several application results in simulated distillation columns, which are close enough to actual behaviour of them, are made, and the results have shown satisfactory

Controle preditivo não linear baseado no modelo de Hammerstein com prova de estabilidade

The Predictive Controller has been receiving plenty attention in the last decades, because the need to understand, to analyze, to predict and to control real systems has been quickly growing with the technological and industrial progress. The objective of this thesis is to present a contribution for the development and implementation of Nonlinear Predictive Controllers based on Hammerstein model, as well as to its make properties evaluation. In this case, in the Nonlinear Predictive Controller development the time-step linearization method is used and a compensation term is introduced in order to improve the controller performance. The main motivation of this thesis is the study and stability guarantee for the Nonlinear Predictive Controller based on Hammerstein model. In this case, was used the concepts of sections and Popov Theorem. Simulation results with literature models shows that the proposed approaches are able to control with good performance and to guarantee the systems stability

Identificação não linear usando uma rede fuzzy wavelet neural network modificada

In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed

Desenvolvimento e avaliação de controladores preditivos baseados em modelos biliares

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Modelos de dispositivos de microondas e ópticos através de redes neurais artificiais de alimentação direta

This dissertation contributes for the development of methodologies through feed forward artificial neural networks for microwave and optical devices modeling. A bibliographical revision on the applications of neuro-computational techniques in the areas of microwave/optical engineering was carried through. Characteristics of networks MLP, RBF and SFNN, as well as the strategies of supervised learning had been presented. Adjustment expressions of the networks free parameters above cited had been deduced from the gradient method. Conventional method EM-ANN was applied in the modeling of microwave passive devices and optical amplifiers. For this, they had been proposals modular configurations based in networks SFNN and RBF/MLP objectifying a bigger capacity of models generalization. As for the training of the used networks, the Rprop algorithm was applied. All the algorithms used in the attainment of the models of this dissertation had been implemented in Matlab

Influência dos modelos digitais de terreno na modelagem de circulação hidrodinâmica 2DH: um estudo de caso

Digital Elevation Models (DEM) are numerical representations of a portion of the earth surface. Among several factors which affect the quality of a DEM, it should be emphasized the attention on the input data and the choice of the interpolating algorithm. On the other hand, several numerical models are used nowadays to characterize nearshore hydrodynamics and morphological changes in coastal areas, whose validation is based on field data collection. Independent on the complexity of the physical processes which are modeled, little attention has been given to the intrinsic bathymetric interpolation built within the numerical models of the specific application. Therefore, this study aims to investigate and to quantify the influence of the bathymetry, as obtained by a DEM, on the hydrodynamic circulation model at a coastal stretch, off the coast of the State of Rio Grande do Norte, Northeast Brazil. This coastal region is characterized by strong hydrodynamic and littoral processes, resulting in a very dynamic morphology with shallow coastal bathymetry. Important economic activities, such as oil exploitation and production, fisheries, salt ponds, shrimp farms and tourism, also bring impacts upon the local ecosystems and influence themselves the local hydrodynamics. This fact makes the region one of the most important for the development of the State, but also enhances the possibility of serious environmental accidents. As a hydrodynamic model, SisBaHiA® - Environmental Hydrodynamics System ( Sistema Básico de Hidrodinâmica Ambiental ) was chosen, for it has been successfully employed at several locations along the Brazilian coast. This model was developed at the Coastal and Oceanographical Engineering Group of the Ocean Engineering Program at the Federal University of Rio de Janeiro. Several interpolating methods were tested for the construction of the DEM, namely Natural Neighbor, Kriging, Triangulation with Linear Interpolation, Inverse Distance to a Power, Nearest Neighbor, and Minimum Curvature, all implemented within the software Surfer®. The bathymetry which was used as reference for the DEM was obtained from nautical charts provided by the Brazilian Hydrographic Service of the Brazilian Navy and from a field survey conducted in 2005. Changes in flow velocity and free surface elevation were evaluated under three aspects: a spatial vision along three profiles perpendicular to the coast and one profile longitudinal to the coast as shown; a temporal vision from three central nodes of the grid during 30 days; a hodograph analysis of components of speed in U and V, by different tidal cycles. Small, but negligible, variations in sea surface elevation were identified. However, the differences in flow and direction of velocities were significant, depending on the DEM

Criação da matéria em cosmologias com velocidade da luz variável e eletrônico não-linear

In this work we obtain the cosmological solutions and investigate the thermodynamics of matter creation in two diferent contexts. In the first we propose a cosmological model with a time varying speed of light c. We consider two diferent time dependence of c for a at Friedmann-Robertson- Walker (FRW) universe. We write the energy conservation law arising from Einstein equations and study how particles are created as c decreases with cosmic epoch. The variation of c is coupled to a cosmological Λ term and both singular and non-singular solutions are possible. We calculate the "adiabatic" particle creation rate and the total number of particles as a function of time and find the constrains imposed by the second law of thermodynamics upon the models. In the second scenario, we study the nonlinearity of the electrodynamics as a source of matter creation in the cosmological models with at FRW geometry. We write the energy conservation law arising from Einstein field equations with cosmological term Λ, solve the field equations and study how particles are created as the magnetic field B changes with cosmic epoch. We obtain solutions for the adiabatic particle creation rate, the total number of particles and the scale factor as a function of time in three cases: Λ = 0, Λ = constant and Λ α H2 (cosmological term proportional to the Hubble parameter). In all cases, the second law of thermodynamics demands that the universe is not contracting (H ≥ 0). The first two solutions are non-singular and exhibit in ationary periods. The third case studied allows an always in ationary universe for a suficiently large cosmological term

Estudos de modelos Estocásticos: processo de contato, séries aleatórias e processos difusivos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Identificação e comparação entre controle preditivo com modelo não linear e PI sintonizados com PSO em sistema de separação gravitacional de águia-óleo

The separation methods are reduced applications as a result of the operational costs, the low output and the long time to separate the uids. But, these treatment methods are important because of the need for extraction of unwanted contaminants in the oil production. The water and the concentration of oil in water should be minimal (around 40 to 20 ppm) in order to take it to the sea. Because of the need of primary treatment, the objective of this project is to study and implement algorithms for identification of polynomial NARX (Nonlinear Auto-Regressive with Exogenous Input) models in closed loop, implement a structural identification, and compare strategies using PI control and updated on-line NARX predictive models on a combination of three-phase separator in series with three hydro cyclones batteries. The main goal of this project is to: obtain an optimized process of phase separation that will regulate the system, even in the presence of oil gushes; Show that it is possible to get optimized tunings for controllers analyzing the mesh as a whole, and evaluate and compare the strategies of PI and predictive control applied to the process. To accomplish these goals a simulator was used to represent the three phase separator and hydro cyclones. Algorithms were developed for system identification (NARX) using RLS(Recursive Least Square), along with methods for structure models detection. Predictive Control Algorithms were also implemented with NARX model updated on-line, and optimization algorithms using PSO (Particle Swarm Optimization). This project ends with a comparison of results obtained from the use of PI and predictive controllers (both with optimal state through the algorithm of cloud particles) in the simulated system. Thus, concluding that the performed optimizations make the system less sensitive to external perturbations and when optimized, the two controllers show similar results with the assessment of predictive control somewhat less sensitive to disturbances

Predição em modelos de tempo de falha acelerado com efeito aleatório para avaliação de riscos de falha em poços petrolíferos

We considered prediction techniques based on models of accelerated failure time with random e ects for correlated survival data. Besides the bayesian approach through empirical Bayes estimator, we also discussed about the use of a classical predictor, the Empirical Best Linear Unbiased Predictor (EBLUP). In order to illustrate the use of these predictors, we considered applications on a real data set coming from the oil industry. More speci - cally, the data set involves the mean time between failure of petroleum-well equipments of the Bacia Potiguar. The goal of this study is to predict the risk/probability of failure in order to help a preventive maintenance program. The results show that both methods are suitable to predict future failures, providing good decisions in relation to employment and economy of resources for preventive maintenance.

A distribuição F generalizada para selecionar modelos de sobrevivência com fração de cura

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior