Application of neural networks to identify features of dynamical grounding systems

The accurate identification of features of dynamical grounding systems are extremely important to define the operational safety and proper functioning of electric power systems. Several experimental tests and theoretical investigations have been carried out to obtain characteristics and parameters associated with the technique of grounding. The grounding system involves a lot of non-linear parameters. This paper describes a novel approach for mapping characteristics of dynamical grounding systems using artificial neural networks. The network acts as identifier of structural features of the grounding processes. So that output parameters can be estimated and generalized from an input parameter set. The results obtained by the network are compared with other approaches also used to model grounding systems.

Study of the timber constructive systems that are more commercialized in Brazil

The Brazilian houses in wood are executed with several techniques and species, in function of the areas they are located, therefore, it is treated of regional traditional houses, built practically without modem technological resources. These houses are the ones of the tropical areas, where there is abundance of this material, or the ones of the south region, prevailing the European immigrant's constructive techniques. Nowadays, in the urbanized centers of the country it is observed that this type of house can be found sheltering the most lacking populations, in the slums; or in highly sophisticated residential units which are conceived and executed by specialist professionals for a social class of high purchasing power; or still, those that are marketed by companies of small load, that offer standardized residences, usually acquired by the middle class as second residence, in the field or in the coast. The work has for objective to study the houses of these companies that are consolidated at the market, identifying the constructive system, the product; as well as, its production process, trying to verify which technologies are incorporated to these processes. The analysis that was made allows a larger understanding of the product, wood house, that exists in the market and identification of the technological degree in the productive process of those constructive systems.

Adaptive filter feature identification for structural health monitoring in an aeronautical panel

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Identification of Staphylococcus saprophyticus isolated from patients with urinary tract infection using a simple set of biochemical tests correlating with 16S-23S interspace region molecular weight patterns

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level data

Background: The genome-wide identification of both morbid genes, i.e., those genes whose mutations cause hereditary human diseases, and druggable genes, i.e., genes coding for proteins whose modulation by small molecules elicits phenotypic effects, requires experimental approaches that are time-consuming and laborious. Thus, a computational approach which could accurately predict such genes on a genome-wide scale would be invaluable for accelerating the pace of discovery of causal relationships between genes and diseases as well as the determination of druggability of gene products.Results: In this paper we propose a machine learning-based computational approach to predict morbid and druggable genes on a genome-wide scale. For this purpose, we constructed a decision tree-based meta-classifier and trained it on datasets containing, for each morbid and druggable gene, network topological features, tissue expression profile and subcellular localization data as learning attributes. This meta-classifier correctly recovered 65% of known morbid genes with a precision of 66% and correctly recovered 78% of known druggable genes with a precision of 75%. It was than used to assign morbidity and druggability scores to genes not known to be morbid and druggable and we showed a good match between these scores and literature data. Finally, we generated decision trees by training the J48 algorithm on the morbidity and druggability datasets to discover cellular rules for morbidity and druggability and, among the rules, we found that the number of regulating transcription factors and plasma membrane localization are the most important factors to morbidity and druggability, respectively.Conclusions: We were able to demonstrate that network topological features along with tissue expression profile and subcellular localization can reliably predict human morbid and druggable genes on a genome-wide scale. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing morbidity and druggability.

Boron transport in Eucalyptus. 2. Identification in silico of a putative boron transporter for xylem loading in eucalypt

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Identification and description of distinct B chromosomes in Cyphocharax modestus (Characiformes, Curimatidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multiscale Fractal Descriptors and Polynomial Classifier for Partial Pixels Identification in Regions of Interest of Mammographic Images

Computer systems are used to support breast cancer diagnosis, with decisions taken from measurements carried out in regions of interest (ROIs). We show that support decisions obtained from square or rectangular ROIs can to include background regions with different behavior of healthy or diseased tissues. In this study, the background regions were identified as Partial Pixels (PP), obtained with a multilevel method of segmentation based on maximum entropy. The behaviors of healthy, diseased and partial tissues were quantified by fractal dimension and multiscale lacunarity, calculated through signatures of textures. The separability of groups was achieved using a polynomial classifier. The polynomials have powerful approximation properties as classifiers to treat characteristics linearly separable or not. This proposed method allowed quantifying the ROIs investigated and demonstrated that different behaviors are obtained, with distinctions of 90% for images obtained in the Cranio-caudal (CC) and Mediolateral Oblique (MLO) views.

Comparison of methods for the identification of coagulase-negative staphylococci

Coagulase-negative staphylococci (CNS) species identification is still difficult for most clinical laboratories. The scheme proposed by Kloos and Schleifer and modified by Bannerman is the reference method used for the identification of staphylococcal species and subspecies; however, this method is relatively laborious for routine use since it requires the utilization of a large number of biochemical tests. The objective of the present study was to compare four methods, i.e., the reference method, the API Staph system (bioMérieux) and two methods modified from the reference method in our laboratory (simplified method and disk method), in the identification of 100 CNS strains. Compared to the reference method, the simplified method and disk method correctly identified 100 and 99% of the CNS species, respectively, while this rate was 84% for the API Staph system. Inaccurate identification by the API Staph method was observed for Staphylococcus epidermidis (2.2%), S. hominis (25%), S. haemolyticus (37.5%), and S. warneri (47.1%). The simplified method using the simple identification scheme proposed in the present study was found to be efficient for all strains tested, with 100% sensitivity and specificity and proved to be available alternative for the identification of staphylococci, offering, higher reliability and lower cost than the currently available commercial systems. This method would be very useful in clinical microbiology laboratory, especially in places with limited resources.

A fuzzy inference system for identification of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behavior. In this paper, a system based on fuzzy logic systems is developed to overcome the problems usually found in the conventional mathematical models. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the fuzzy approach. Simulation results are presented to justify the validity of the proposed approach.

Applying fuzzy logic systems in the estimation of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behavior. In this paper, a system based on fuzzy logic systems is developed to overcome the problems usually found in the conventional mathematical models. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the fuzzy approach. Simulation results are presented to justify the validity of the proposed approach.

Phenotypic methods and commercial systems for the discrimination between C-albicans and C-dubliniensis

Candida dubliniensis is a recently described Candida species associated with oral candidosis that exhibits a high degree of phenotypic similarity to Candida albicans. However, these species show differences in levels of resistance to antimycotic agents and ability to cause infections. Therefore, accurate clinical identification of C. dubliniensis and C. albicans species is important in order to treat oral candidal infections. Phenotypic identification methods are easy-to-use procedures for routine discrimination of oral isolates in the clinical microbiology laboratory. However, C. dubliniensis may be so far underreported in clinical samples because most currently used identification methods fail to recognize this yeast. Phenotypic methods depend on growth temperature, carbon source assimilation, chlamydospore and hyphal growth production, positive or negative growth on special media and intracellular enzyme production, among others. In this review, some phenotypic methods are presented with a special emphasis on the discrimination of C. dubliniensis and C. albicans.

Identification of psoralen loaded PLGA microspheres in rat skin by light microscopy

Drug delivery systems involving the use of polymers are widely studied and discovery of biocompatible polymers has become the focus of research in this area. Psoralen loaded poly(DL-lactide-co-glycolide) (PLGA) microspheres to be used in PUVA therapy (psoralen and UVA irradiation (ultraviolet A, 320-400 nm) of psoriasis were identified in paraffin sections by histological analysis. The psoralen loaded PLGA microspheres were prepared using the solvent evaporation technique. They were spherical and possessed an external smooth surface as observed by scanning electron microscopy (SEM) analysis. This study describes a modification in the routine preparation of microsphere samples for examination by light microscopy. The changes involved fixative agents and/or stains allowing the identification of microspheres containing a non-fluorescent material. The preservation and identification of microspheres in tissues for histological processing in paraffin was greatly improved by these modifications as proven by our results. (c) 2007 Elsevicr Ltd. All rights reserved.

Expressed sequence tags from Atta laevigata and identification of candidate genes for the control of pest leaf-cutting ants.

Leafcutters are the highest evolved within Neotropical ants in the tribe Attini and model systems for studying caste formation, labor division and symbiosis with microorganisms. Some species of leafcutters are agricultural pests controlled by chemicals which affect other animals and accumulate in the environment. Aiming to provide genetic basis for the study of leafcutters and for the development of more specific and environmentally friendly methods for the control of pest leafcutters, we generated expressed sequence tag data from Atta laevigata, one of the pest ants with broad geographic distribution in South America. Results: The analysis of the expressed sequence tags allowed us to characterize 2,006 unique sequences in Atta laevigata. Sixteen of these genes had a high number of transcripts and are likely positively selected for high level of gene expression, being responsible for three basic biological functions: energy conservation through redox reactions in mitochondria; cytoskeleton and muscle structuring; regulation of gene expression and metabolism. Based on leafcutters lifestyle and reports of genes involved in key processes of other social insects, we identified 146 sequences potential targets for controlling pest leafcutters. The targets are responsible for antixenobiosis, development and longevity, immunity, resistance to pathogens, pheromone function, cell signaling, behavior, polysaccharide metabolism and arginine kynase activity. Conclusion: The generation and analysis of expressed sequence tags from Atta laevigata have provided important genetic basis for future studies on the biology of leaf-cutting ants and may contribute to the development of a more specific and environmentally friendly method for the control of agricultural pest leafcutters.

Application of HPLC-NMR coupling using C30 phase in the separation and identification of flavonoids of taxonomic relevance

The on-line separation and identification of two important taxonomic markers for plant species of the Paepalanthus genus, the flavonoids 6-methoxykaempferol-3-O-β-D-glucopyranoside and 6-methoxykaempferol-3-O-β-D-6″(p-coumaroyl)glucopyranoside, has been performed with an HPLC-NMR coupling using C30 phase. 1D spectra have been recorded in the stopped-flow mode for the two predominant chromatographic peaks. This is the first application of HPLC-NMR coupling using C30 phase to a taxonomic problem. The technique drastically reduces the required amount of sampling for structure determination. © Springer-Verlag 2000.