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De Melo E.B.,West Parana State University
European Journal of Medicinal Chemistry | Year: 2010

Two multivariate studies, a PCA-SAR and a PLS-QSAR, of 3-aryl-4- hydroxyquinolin-2(1H)-one derivatives described as type I fatty acid synthase (FAS) inhibitors, are presented in this work. The variable selection was performed with the Fisher's weight and Ordered Predictors Selection (OPS) algorithm, respectively. In the PCA, a separation between active and inactive compounds was obtained by six descriptors (topological and geometrical). The PLS model presented five descriptors and two Latent Variables. Leave-N-out cross validation and y-randomization test showed that the model presented robustness and no chance correlation, respectively, and the descriptors indicated that the FAS inhibition depends on electronic distribution of the investigated compounds. The model obtained in this study may provide a guidance for proposition of new FAS inhibitors. © 2010 Elsevier Masson SAS. All rights reserved.


Da Silva S.,West Parana State University
Mechanical Systems and Signal Processing | Year: 2011

The main goal of this short communication is to use orthogonal Kautz filters with multiple poles for non-parametric identification of the impulse response functions (IRFs) of mechanical structures. The IRF is estimated by using the covariance method based on the sum of convolution of the input signal processed by Kautz filters. The inclusion of different poles in the Kautz filter allows the use of a wide range of frequency and can improve the non-parametric identification process in the time domain by reducing the number of necessary terms. Some examples are provided to illustrate the simplicity and efficiency of the proposed approach. © 2010 Elsevier Ltd.


Valle M.E.,University of Londrina | Vicente D.M.G.,West Parana State University
Journal of Mathematical Imaging and Vision | Year: 2012

Sparsely connected autoassociative lattice memories (SCALMs) are very general models defined on complete lattices, a mathematical structure which is obtained by imposing some ordering on a set. They are computationally cheaper and mathematically simpler than "traditional" models and other memories such as the original autoassociative morphological memories (AMMs) of Ritter and Sussner because they only compute maximums and minimums. This paper provides theoretical results on SCALMs defined on a general complete lattice as well as an application of these memories for the storage and recall of color images. Precisely, we characterize the recall phase of SCALMs in terms of their fixed points. Then, we show that any endomorphic lattice polynomial-a concept that generalizes the notion of lattice polynomial of Birkhoff-on the fundamental memory set represents a fixed point of the SCALMs. Also, we discuss the relationship between SCALMs and the original AMMs. Finally, we provide some experimental results on the performance of SCALMs, defined on different color lattices, for the reconstruction of color images corrupted by either Gaussian or impulsive noise. © Springer Science+Business Media, LLC 2011.


Da Silva S.,West Parana State University
International Journal of Non-Linear Mechanics | Year: 2011

The common metrics used in linear finite element (FE) model updating using vibration test data are generally functions of relationships based on unidimensional convolution, for example, distances involving natural frequencies, frequency response or impulse response functions, modal shapes, etc. When a structure has local elements or geometry, like joints, bolts, gaps, backlash, etc., these approaches can fail once it could to induce non-linear behavior. Thus, the methods for FE model updating, when considering the existence of localized non-linear parameters, have been receiving much attention in the last years. In this sense, the present paper proposes the use of a strategy through objective functions based on multiples convolutions described by the first order and second order discrete-time Volterra kernels. These kernels are effective metrics for a model updating into large FE model with local non-linearity. In order to improve the non-linear coefficient identification, an orthogonal basis involving Kautz filter is used to expand the kernels, called by Wiener kernel. To exemplify in full details the steps of the updating procedure, an FE model of a three-dimensional portal frame with commons non-linearities is simulated with different excitation forces and used to identify the non-linear parameters. These results allow us to characterize the practical applicability and the drawbacks of the proposed method with suggestions and remarks for further use in industrial structures. © 2010 Elsevier Ltd. All rights reserved.


Among the methods of variable selection for Quantitative Structure-Property Relationship (QSPR) studies, one of the currently available alternatives is the Ordered Predictors Selection (OPS). Using this algorithm and descriptors obtained using only Simplified Molecular Input Line Entry System (SMILES) strings in the free web server Parameter Client, a QSPR study with a data set of 28 alkyl (1-phenylsulfonyl) cycloalkane-carboxylates and six different endpoints of environmental importance were developed and compared with other works. The comparison with models previously published was performed only with the internal validation, and four of the six new models proved to be superior. However, the six new models also presented high quality for external predictions, were robust and showed no chance correlation. The predicted endpoints of the six models were within the applicability domain. Thus, it can be concluded that the OPS algorithm was able to generate QSA(P)R models with high statistical quality for predicting of physicochemical and toxicological endpoints, thus showing its potential for development of predictive models of environmental interest. © 2012 Elsevier B.V.

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