Expert system for the assessment of power transformer insulation condition based on type-2 fuzzy logic systems

An efficient expert system for the power transformer condition assessment is presented in this paper. Through the application of Duval`s triangle and the method of the gas ratios a first assessment of the transformer condition is obtained in the form of a dissolved gas analysis (DGA) diagnosis according IEC 60599. As a second step, a knowledge mining procedure is performed, by conducting surveys whose results are fed into a first Type-2 Fuzzy Logic System (T2-FLS), in order to initially evaluate the condition of the equipment taking only the results of dissolved gas analysis into account. The output of this first T2-FLS is used as the input of a second T2-FLS, which additionally weighs up the condition of the paper-oil system. The output of this last T2-FLS is given in terms of words easily understandable by the maintenance personnel. The proposed assessing methodology has been validated for several cases of transformers in service. (C) 2010 Elsevier Ltd. All rights reserved.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

A ductile damage criterion at various stress triaxialities

The paper discusses the effect of stress triaxiality on the onset and evolution of damage in ductile metals. A series of tests including shear tests and experiments oil smooth and pre-notched tension specimens wits carried Out for it wide range of stress triaxialities. The underlying continuum damage model is based oil kinematic definition of damage tensors. The modular structure of the approach is accomplished by the decomposition of strain rates into elastic, plastic and damage parts. Free energy functions with respect to fictitious undamaged configurations as well as damaged ones are introduced separately leading to elastic material laws which are affected by increasing damage. In addition, a macroscopic yield condition and a flow rule are used to adequately describe the plastic behavior. Numerical simulations of the experiments are performed and good correlation of tests and numerical results is achieved. Based oil experimental and numerical data the damage criterion formulated in stress space is quantified. Different branches of this function are taken into account corresponding to different damage modes depending oil stress triaxiality and Lode parameter. In addition, identification of material parameters is discussed ill detail. (C) 2007 Elsevier Ltd. All rights reserved.

Robust model predictive controller with output feedback and target tracking

A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.

Identification of protein coding regions using the modified Gabor-wavelet transform

An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods based on the occurrence of specific patterns of nucleotides at coding regions have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically predefined window length required for a local analysis of a DNA region. We introduce a method based on a modified Gabor-wavelet transform (MGWT) for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods by using eukaryote data sets. The results show that MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors but also makes a tool available for detailed exploration of the nucleotide occurrence.

Molecular dynamics, density functional, ADMET predictions, virtual screening, and molecular interaction field studies for identification and evaluation of novel potential CDK2 inhibitors in cancer therapy

In this work, we have used molecular dynamics, density functional theory, virtual screening, ADMET predictions, and molecular interaction field studies to design and propose eight novel potential inhibitors of CDK2. The eight molecules proposed showed interesting structural characteristics that are required for inhibiting the CDK2 activity and show potential as drug candidates for the treatment of cancer. The parameters related to the Rule of Five were calculated, and only one of the molecules violated more than one parameter. One of the proposals and one of the drug-like compounds selected by virtual screening indicated to be promising candidates for CDK2-based cancer therapy.

Classification model based on Raman spectra of selected morphological and biochemical tissue constituents for identification of atherosclerosis in human coronary arteries

This study presents the results of Raman spectroscopy applied to the classification of arterial tissue based on a simplified model using basal morphological and biochemical information extracted from the Raman spectra of arteries. The Raman spectrograph uses an 830-nm diode laser, imaging spectrograph, and a CCD camera. A total of 111 Raman spectra from arterial fragments were used to develop the model, and those spectra were compared to the spectra of collagen, fat cells, smooth muscle cells, calcification, and cholesterol in a linear fit model. Non-atherosclerotic (NA), fatty and fibrous-fatty atherosclerotic plaques (A) and calcified (C) arteries exhibited different spectral signatures related to different morphological structures presented in each tissue type. Discriminant analysis based on Mahalanobis distance was employed to classify the tissue type with respect to the relative intensity of each compound. This model was subsequently tested prospectively in a set of 55 spectra. The simplified diagnostic model showed that cholesterol, collagen, and adipocytes were the tissue constituents that gave the best classification capability and that those changes were correlated to histopathology. The simplified model, using spectra obtained from a few tissue morphological and biochemical constituents, showed feasibility by using a small amount of variables, easily extracted from gross samples.

Scientific output trends in oral health in Brazil

Objective. To describe dental research trends in Brazil (especially population-based oral health) in the early Twenty-first Century. Methods. The abstracts of studies presented at meetings of the Brazilian Society for Dental Medicine Research (Sociedade Brasileira de Pesquisa Odontologica) from 2001-2006 were assessed in terms of methodological design (aggregate or population-based and individual-based studies, observational and intervention studies, cross-sectional and longitudinal studies); general type (literature review, studies with human subjects, and laboratory studies); and classification into one of the 19 specialty categories recognized by the Brazilian Federal Dentistry Council. Of the 10 406 abstracts presented in this period, 5 203 (50%) were reviewed. Results. Concerning methodological design, 87.5% of the abstracts referred to individual-based studies, whereas 12.5% were of aggregate studies. Concerning the general category, 41.7% referred to studies with human subjects. The remaining abstracts (58.3%) described in vitro (31.1%) or in vivo (23.6%) laboratory research and literature reviews (3.6%). Concerning the Council`s specialty categories, only five had a frequency higher than 10.0%: esthetic dentistry, periodontics, endodontics, pediatric dentistry, and population-based oral health. Conclusions. Brazil`s scientific output in the field of oral health for the period 2001-2006 was balanced, with increasing interest in the area of population-based oral health.

Identification of Hammondia heydorni oocysts by a heminested-PCR (hnPCR-AP10) based on the H-heydorni RAPD fragment AP10

Toxoplasma gondii, Hammondia hammondi, Neospora caninum, Neospora hughesi and Hammondia heydorni are members of the Toxoplasmatinae sub-family. They are closely related coccidians with similarly sized oocysts. Molecular diagnostic techniques, especially those based on polymerase chain reaction (PCR), can be successfully applied for the differentiation of Hammondia-like oocysts. In this paper, we describe a rapid and simple method for the identification of H. heydorni oocysts among other members of the Toxoplasmatinae sub-family, using a heminested-PCR (hnPCR-AP10) based on a H. heydorni RAPD fragment available in molecular database. DNA of oocysts of H. heydorni yielded a specific fragment of 289-290 bp in the heminested-PCR assay. No product was yielded when the primers were used for the amplification of DNA extracted from T. gondii, N. caninum, N. hughesi and H. hammondi, thus allowing the differentiation of H. heydorni among other members of the Toxoplasmatinae sub-family. The hnPCR-AP10 was capable of detecting H. heydorni genetic sequences from suspensions with at least 10 oocysts. In conclusion, the hnPCR-AP10 proved to be a reliable method to be used in the identification of H. heydorni oocysts from feces of dogs. (C) 2010 Elsevier B.V. All rights reserved.

Clinical evaluation and COL2A1 gene analysis in 21 Brazilian families with Stickler syndrome: Identification of novel mutations, further genotype/phenotype correlation, and its implications for the diagnosis

We present clinical and molecular evaluation from a large cohort of patients with Stickler syndrome: 78 individuals from 21 unrelated Brazilian families. The patients were selected in a Hospital with a craniofacial dysmorphology assistance service and clinical diagnosis was based on the presence of cleft palate associated to facial and ocular anomalies of Stickler syndrome. Analysis of COL2A1 gene revealed 9 novel and 4 previously described pathogenic mutations. Except for the mutation c.556G>T (p.Gly186X), all the others were located in the triple helical domain. We did not find genotype/phenotype correlation in relation to type and position of the mutation in the triple helical domain. However, a significantly higher proportion of myopia in patients with mutations located in this domain was observed in relation to those with the mutation in the non-tripe helical domain (c.556G>T; P < 0.04). A trend towards a higher prevalence of glaucoma, although not statistically significant, was observed in the presence of the mutation c.556G>T. It is possible. that this mutation alters the splicing of the mRNA instead of only creating a premature stop codon and therefore it can lead to protein products of different ocular effects. One novel DNA variation (c.1266+7G>C) occurs near a splice site and it was observed to co-segregate with the phenotype in one of the two families with this DNA variation. As in silico analysis predicted that the c.1266+7G>C DNA variation can affect the efficiency of the splicing, we still cannot rule it out as non-pathogenic. Our study also showed that ascertainment through cleft palate associated to other craniofacial signs can be very efficient for identification of Stickler syndrome patients. Still, high frequency of familial cases and high frequency of underdevelopment of distal lateral tibial epiphyses observed in our patients suggested that the inclusion of this information can improve the clinical diagnosis of Stickler syndrome. (C) 2008 Elsevier Masson SAS. All rights reserved.

Exact Search Directions for Optimization of Linear and Nonlinear Models Based on Generalized Orthonormal Functions

A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

PLANT LEAF IDENTIFICATION BASED ON VOLUMETRIC FRACTAL DIMENSION

Texture is an important visual attribute used to describe the pixel organization in an image. As well as it being easily identified by humans, its analysis process demands a high level of sophistication and computer complexity. This paper presents a novel approach for texture analysis, based on analyzing the complexity of the surface generated from a texture, in order to describe and characterize it. The proposed method produces a texture signature which is able to efficiently characterize different texture classes. The paper also illustrates a novel method performance on an experiment using texture images of leaves. Leaf identification is a difficult and complex task due to the nature of plants, which presents a huge pattern variation. The high classification rate yielded shows the potential of the method, improving on traditional texture techniques, such as Gabor filters and Fourier analysis.

Phase transitions in biodegradable films based on blends of gelatin and poly (vinyl alcohol)

The aim of this work was to study the effect of the hydrolysis degree (HD) and the concentration (C PVA) of two types of poly (vinyl alcohol) (PVA) and the effect of the type and the concentration of plasticizers on the phase properties of biodegradable films based on blends of gelatin and PVA, using a response-surface methodology. The films were made by casting and the studied properties were their glass (Tg) and melting (Tm) transition temperatures, which were determined by diferential scanning calorimetry (DSC). For the data obtained on the first scan, the fitting of the linear model was statistically significant and predictive only for the second melting temperature. In this case, the most important effect on the second Tm of the first scan was due to the HD of the PVA. In relation to the second scan, the linear model could be fit to Tg data with only two statistically significant parameters. Both the PVA and plasticizer concentrations had an important effect on Tg. Concerning the second Tm of the second scan, the linear model was fit to data with two statistically significant parameters, namely the HD and the plasticizer concentration. But, the most important effect was provoked by the HD of the PVA.

Phylogenetic analyses of Cladophora vagabunda (L.) C. Hoek (Cladophorales, Chlorophyta) from Brazil based on SSU rDNA sequences

The complete SSU rDNA was sequenced for 10 individuals of Cladophora vagabunda collected along the coast of Brazil. For C. rupestris (L.) Kütz. a partial SSU rDNA sequence (1634 bp) was obtained. Phylogenetic trees indicate that Cladophora is paraphyletic, but the section Glomeratae sensu lato including C. vagabunda from Brazil, Japan and France, C. albida (Nees) Kütz., C. sericea (Hudson) Kütz., and C. glomerata (L.) Kütz. is monophyletic. Within this group C. vagabunda is paraphyletic. The sequence identity for the SSU rDNA varied from 98.9% to 100% for the Brazilian C. vagabunda, and from 98.3% to 99.7% comparing the Brazilian individuals to the ones from France and Japan. Sequence identity of the Brazilian C. vagabunda to C. albida and C. sericea vary from 98.0% to 98.6%. The SSU rDNA phylogeny support partially the morphological characteristics presented by Brazilian populations of C. vagabunda. On the other hand, C. rupestris from Brazil does not group with C. rupestris from France, both sequences presenting only 96.9% of identity. The inclusion of sequences of individuals from Brazil reinforces the need of taxonomical revision for the genus Cladophora and for the complex C. vagabunda.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.