933 resultados para System identification
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Background: Leptospirosis is a multisystem disease caused by pathogenic strains of the genus Leptospira. We have reported that Leptospira are able to bind plasminogen (PLG), to generate active plasmin in the presence of activator, and to degrade purified extracellular matrix fibronectin. Methodology/Principal Findings: We have now cloned, expressed and purified 14 leptospiral recombinant proteins. The proteins were confirmed to be surface exposed by immunofluorescence microscopy and were evaluated for their ability to bind plasminogen (PLG). We identified eight as PLG-binding proteins, including the major outer membrane protein LipL32, the previously published rLIC12730, rLIC10494, Lp29, Lp49, LipL40 and MPL36, and one novel leptospiral protein, rLIC12238. Bound PLG could be converted to plasmin by the addition of urokinase-type PLG activator (uPA), showing specific proteolytic activity, as assessed by its reaction with the chromogenic plasmin substrate, D-Val-Leu-Lys 4-nitroanilide dihydrochloride. The addition of the lysine analog 6-aminocaproic acid (ACA) inhibited the protein-PLG interaction, thus strongly suggesting the involvement of lysine residues in plasminogen binding. The binding of leptospiral surface proteins to PLG was specific, dose-dependent and saturable. PLG and collagen type IV competed with LipL32 protein for the same binding site, whereas separate binding sites were observed for plasma fibronectin. Conclusions/Significance: PLG-binding/activation through the proteins/receptors on the surface of Leptospira could help the bacteria to specifically overcome tissue barriers, facilitating its spread throughout the host.
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Context. Close binary supersoft X-ray sources (CBSS) are binary systems that contain a white dwarf with stable nuclear burning on its surface. These sources, first discovered in the Magellanic Clouds, have high accretion rates and near-Eddington luminosities (10(37)-10(38) erg s(-1)) with high temperatures (T = 2-7 x 10(5) K). Aims. The total number of known objects in the MC is still small and, in our galaxy, even smaller. We observed the field of the unidentified transient supersoft X-ray source RX J0527.8-6954 in order to identify its optical counterpart. Methods. The observation was made with the IFU-GMOS on the Gemini South telescope with the purpose of identifying stars with possible He II or Balmer emission or else of observing nebular extended jets or ionization cones, features that may be expected in CBSS. Results. The X-ray source is identified with a B5e V star that is associated with subarcsecond extended H alpha emission, possibly bipolar. Conclusions. If the primary star is a white dwarf, as suggested by the supersoft X-ray spectrum, the expected orbital period exceeds 21 h; therefore, we believe that the 9.4 h period found so far is not associated to this system.
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Repeated exposure of rabbits and other animals to ticks results in acquired resistance or immunity to subsequent tick bites and is partially elicited by antibodies directed against tick antigens. In this study we demonstrate the utility of a yeast surface display approach to identify tick salivary antigens that react with tick-immune serum. We constructed an Ixodes scapularis nymphal salivary gland yeast surface display library and screened the library with nymph-immune rabbit sera and identified five salivary antigens. Four of these proteins, designated P8, P19, P23 and P32, had a predicted signal sequence. We generated recombinant (r) P8, P19 and P23 in a Drosophila expression system for functional and immunization studies. rP8 showed anti-complement activity and rP23 demonstrated anti-coagulant activity. Ixodes scapularis feeding was significantly impaired when nymphs were fed on rabbits immunized with a cocktail of rP8, rP19 and rP23, a hall mark of tick-immunity. These studies also suggest that these antigens may serve as potential vaccine candidates to thwart tick feeding.
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Diffuse infiltrating gliomas are the most common tumors of the central nervous system. Gliomas are classified by the WHO according to their histopathological and clinical characteristics into four classes: grade I (pilocytic astrocytoma), grade II (diffuse astrocytoma), grade III (anaplastic astrocytoma), and grade IV (glioblastoma multiforme). Several genes have already been correlated with astrocytomas, but many others are yet to be uncovered. By analyzing the public SAGE data from 21 patients, comprising low malignant grade astrocytomas and glioblastomas, we found COL6A1 to be differentially expressed, confirming this finding by real time RT-PCR in 66 surgical samples. To the best of our knowledge, COL6A1 has never been described in gliomas. The expression of this gene has significantly different means when normal glia is compared with low-grade astrocytomas (grades I and II) and high-grade astrocytomas (grades III and IV), with a tendency to be greater in higher grade samples, thus rendering it a powerful tumor marker.
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Thymic CD4(+)CD25(+) cells play an important role in immune regulation and are continuously developed in the thymus as an independent lineage. How these cells are generated, what are their multiple pathways of suppressive activity and which are their specific markers are questions that remain unanswered. To identify molecules involved in the function and development of human CD4(+)CD25(+) T regulatory cells we targeted thymic CD4(+)CD25(+) cells by peptide phage display. A phage library containing random peptides was screened ex vivo for binding to human thymic CD4(+)CD25(+) T cells. After four rounds of selection on CD4(+)CD25(+) enriched populations of thymocytes, we sequenced several phage displayed peptides and selected one with identity to the Vitamin D Receptor (VDR). We confirmed the binding of the VDR phage to active Vitamin D in vitro, as well as the higher expression of VDR in CD4(+)CD25(+) cells. We suggest that differential expression of VDR on natural Tregs may be related to the relevance of Vitamin D in function and ontogeny of these cells.
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This paper presents a compact embedded fuzzy system for three-phase induction-motor scalar speed control. The control strategy consists in keeping constant the voltage-frequency ratio of the induction-motor supply source. A fuzzy-control system is built on a digital signal processor, which uses speed error and speed-error variation to change both the fundamental voltage amplitude and frequency of a sinusoidal pulsewidth modulation inverter. An alternative optimized method for embedded fuzzy-system design is also proposed. The controller performance, in relation to reference and load-torque variations, is evaluated by experimental results. A comparative analysis with conventional proportional-integral controller is also achieved.
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In this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. (C) 2010 Elsevier B. V. All rights reserved.
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This work proposes a method based on both preprocessing and data mining with the objective of identify harmonic current sources in residential consumers. In addition, this methodology can also be applied to identify linear and nonlinear loads. It should be emphasized that the entire database was obtained through laboratory essays, i.e., real data were acquired from residential loads. Thus, the residential system created in laboratory was fed by a configurable power source and in its output were placed the loads and the power quality analyzers (all measurements were stored in a microcomputer). So, the data were submitted to pre-processing, which was based on attribute selection techniques in order to minimize the complexity in identifying the loads. A newer database was generated maintaining only the attributes selected, thus, Artificial Neural Networks were trained to realized the identification of loads. In order to validate the methodology proposed, the loads were fed both under ideal conditions (without harmonics), but also by harmonic voltages within limits pre-established. These limits are in accordance with IEEE Std. 519-1992 and PRODIST (procedures to delivery energy employed by Brazilian`s utilities). The results obtained seek to validate the methodology proposed and furnish a method that can serve as alternative to conventional methods.
A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification
Resumo:
This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSO(b)). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results. (C) 2009 Elsevier Ltd. All rights reserved
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One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.
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This paper presents both the theoretical and the experimental approaches of the development of a mathematical model to be used in multi-variable control system designs of an active suspension for a sport utility vehicle (SUV), in this case a light pickup truck. A complete seven-degree-of-freedom model is successfully quickly identified, with very satisfactory results in simulations and in real experiments conducted with the pickup truth. The novelty of the proposed methodology is the use of commercial software in the early stages of the identification to speed up the process and to minimize the need for a large number of costly experiments. The paper also presents major contributions to the identification of uncertainties in vehicle suspension models and in the development of identification methods using the sequential quadratic programming, where an innovation regarding the calculation of the objective function is proposed and implemented. Results from simulations of and practical experiments with the real SUV are presented, analysed, and compared, showing the potential of the method.
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SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques - combines computer engineering concepts with areas like dermatology and oncology. Its objective is to discern images of skin cancer, specifically melanoma, from others that show only common spots or other types of skin diseases, using image recognition. This work makes use of the ABCDE visual rule, which is often used by dermatologists for melanoma identification, to define which characteristics are analyzed by the software. It then applies various algorithms and techniques, including an ellipse-fitting algorithm, to extract and measure these characteristics and decide whether the spot is a melanoma or not. The achieved results are presented with special focus on the adaptive decision-making and its effect on the diagnosis. Finally, other applications of the software and its algorithms are presented.
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Recently, the development of industrial processes brought on the outbreak of technologically complex systems. This development generated the necessity of research relative to the mathematical techniques that have the capacity to deal with project complexities and validation. Fuzzy models have been receiving particular attention in the area of nonlinear systems identification and analysis due to it is capacity to approximate nonlinear behavior and deal with uncertainty. A fuzzy rule-based model suitable for the approximation of many systems and functions is the Takagi-Sugeno (TS) fuzzy model. IS fuzzy models are nonlinear systems described by a set of if then rules which gives local linear representations of an underlying system. Such models can approximate a wide class of nonlinear systems. In this paper a performance analysis of a system based on IS fuzzy inference system for the calibration of electronic compass devices is considered. The contribution of the evaluated IS fuzzy inference system is to reduce the error obtained in data acquisition from a digital electronic compass. For the reliable operation of the TS fuzzy inference system, adequate error measurements must be taken. The error noise must be filtered before the application of the IS fuzzy inference system. The proposed method demonstrated an effectiveness of 57% at reducing the total error based on considered tests. (C) 2011 Elsevier Ltd. All rights reserved.
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A new assessment of the aluminum corner of the quaternary Al-Fe-Mn-Si system has been made that extends beyond the COST-507 database. This assessment makes use of a recent, improved description of the ternary Al-Fe-Si system. In the present work, modeling of the Al-rich corner of the quaternary Al-Fe-Mn-Si system has been carried out by introducing Fe solubility into the so-called alpha-AlMnSi and beta-AlMnSi phases of the Al-Mn-Si system. A critical review of the data available on the quaternary system is presented and used for the extension of the description of these ternary phases into the quaternary Al-Fe-Mn-Si.
Resumo:
A simplex-lattice statistical project was employed to study an optimization method for a preservative system in an ophthalmic suspension of dexametasone and polymyxin B. The assay matrix generated 17 formulas which were differentiated by the preservatives and EDTA (disodium ethylene diamine-tetraacetate), being the independent variable: X-1 = chlorhexidine digluconate (0.010 % w/v); X-2 = phenylethanol (0.500 % w/v); X-3 = EDTA (0.100 % w/v). The dependent variable was the Dvalue obtained from the microbial challenge of the formulas and calculated when the microbial killing process was modeled by an exponential function. The analysis of the dependent variable, performed using the software Design Expert/W, originated cubic equations with terms derived from stepwise adjustment method for the challenging microorganisms: Pseudomonas aeruginosa, Burkholderia cepacia, Staphylococcus aureus, Candida albicans and Aspergillus niger. Besides the mathematical expressions, the response surfaces and the contour graphics were obtained for each assay. The contour graphs obtained were overlaid in order to permit the identification of a region containing the most adequate formulas (graphic strategy), having as representatives: X-1 = 0.10 ( 0.001 % w/v); X-2 = 0.80 (0.400 % w/v); X-3 = 0.10 (0.010 % w/v). Additionally, in order to minimize responses (Dvalue), a numerical strategy corresponding to the use of the desirability function was used, which resulted in the following independent variables combinations: X-1 = 0.25 (0.0025 % w/v); X-2 = 0.75 (0.375 % w/v); X-3 = 0. These formulas, derived from the two strategies (graphic and numerical), were submitted to microbial challenge, and the experimental Dvalue obtained was compared to the theoretical Dvalue calculated from the cubic equation. Both Dvalues were similar to all the assays except that related to Staphylococcus aureus. This microorganism, as well as Pseudomonas aeruginosa, presented intense susceptibility to the formulas independently from the preservative and EDTA concentrations. Both formulas derived from graphic and numerical strategies attained the recommended criteria adopted by the official method. It was concluded that the model proposed allowed the optimization of the formulas in their preservation aspect.