62 resultados para Identification method


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The identification of nonlinear dynamic systems using linear-in-the-parameters models is studied. A fast recursive algorithm (FRA) is proposed to select both the model structure and to estimate the model parameters. Unlike orthogonal least squares (OLS) method, FRA solves the least-squares problem recursively over the model order without requiring matrix decomposition. The computational complexity of both algorithms is analyzed, along with their numerical stability. The new method is shown to require much less computational effort and is also numerically more stable than OLS.

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An experimental investigation is carried out to verify the feasibility of using an instrumented vehicle to detect and monitor bridge dynamic parameters. The low-cost method consists of the use of a moving vehicle fitted with accelerometers on its axles. In the laboratory experiment, the vehicle–bridge interaction model consists of a scaled two-axle vehicle model crossing a simply supported steel beam. The bridge model also includes a scaled road surface profile. The effects of varying the vehicle model configuration and speed are investigated. A finite element beam model is calibrated using the experimental results, and a novel algorithm for the identification of global bridge stiffness is validated. Using measured vehicle accelerations as input to the algorithm, the beam stiffness is identified with a reasonable degree of accuracy.

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The development of a quick PCR-based method to distinguish European cryptic Myotis spp., Myotis mystacinus, Myotis brandtii and Myotis alcathoe is described. Primers were designed around species-specific single nucleotide polymorphisms (SNP’s) in the ND1 mitochondrial gene, and a pair of control primers was designed in the 12S mitochondrial gene. A multiplex of seven primer combinations produces clear species-specific bands using gel electrophoresis. Robustness of the method was tested on 33 M. mystacinus, 16 M. brandtii and 15 M. alcathoe samples from across the European range of these species. The method worked well on faecal samples collected from maternity roosts of M. mystacinus. The test is intended to aid collection of data on these species through a rapid and easy identification method with the ability to use DNA obtained from a range of sources including faecal matter.

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The development of a quick PCR-based method to distinguish European cryptic Myotis spp., Myotis mystacinus, Myotis brandtii and Myotis alcathoe is described. Primers were designed around species-specific single nucleotide polymorphisms (SNP's) in the ND1 mitochondrial gene, and a pair of control primers was designed in the 12S mitochondrial gene. A multiplex of seven primer combinations produces clear species-specific bands using gel electrophoresis. Robustness of the method was tested on 33 M. mystacinus, 16 M. brandtii and 15 M. alcathoe samples from across the European range of these species. The method worked well on faecal samples collected from maternity roosts of M. mystacinus. The test is intended to aid collection of data on these species through a rapid and easy identification method with the ability to use DNA obtained from a range of sources including faecal matter.

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Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

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As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.

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Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

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The Stein Collection in the British Library contains the Diamond Sutra, the world's oldest, dated, printed document. The paper of the Diamond Sutra and other documents from the Stein collection is believed to be dyed yellow by a natural extract, called huangbo, from the bark of Phellodendron amurense, which contains three major yellow chromophores: berberine, palmatine, and jatrorrhizine, Conservation of these documents requires definite information on the chemical composition of the dyes but no suitable, completely noninvasive analytical method is known. Here we report resonance Raman studies of a series of prate dyes, of plant materials and extracts, and of dyed ancient and modern paper samples. Resonance Raman spectroscopy is used to enhance the spectra of the dyes over the signals from the paper matrixes in which they are held. The samples an give resonance Raman spectra which are dominated by intense fluorescence, but by using SSRS (subtracted shifted Raman spectroscopy) we have obtained reliable spectra of the pure dyes, native bark from the Phellodendron amurense, modern paper dyed with huangbo extracted from this bark, and ancient paper samples. For both ancient paper samples whose pigment bands were detected, the relative intensities of the bands due to berberine and palmatine suggest that the ancient paper is richer in berberine than its modern counterpart, This is the first nondestructive in situ method for detection of these pigments in manuscripts, and as such has considerable potential benefit for the treatment of irreplaceable documents that are believed to be dyed with huangbo but documents on which conservation work cannot proceed without definite identification of the chemical compounds that they contain.

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A novel technique is described for the identification and quantification of environmental pollutants based on toxicity fingerprinting with a metabolic lux-marked bacterial biosensor. This method involved characterizing the toxicity-based responses of the biosensor to seven calibration pollutants as acute temporal-dose response fingerprints. An algorithm is described to allow comparisons of responses of an unknown pollutant to be made against the calibration data. This is based on predicting pollutant concentration at each of six different time points over the course of a 5-min assay. If the prediction is consistent between the unknown pollutant and a calibration pollutant at the 95% test level, this is considered to be a positive identification. All seven calibration pollutants could be successfully distinguished from each other with this technique. Environmental samples, individually spiked with single concentrations of pollutants, were compared in this way against the calibration pollutants. An 83% identification success was achieved, with no false positives at the 95% test level. This is a simple and rapid technique that potentially can be applied to monitoring of industrial wastewater or as a screening tool for regulators.

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Mercury in plants or animal tissue is supposed to occur in the form of complexes formed with biologically relevant thiols (biothiols), rather than as free cation. We describe a technique for the separation and molecular identification of mercury and methylmercury complexes derived from their reactions with cysteine (Cys) and glutathione (GS): Hg(Cys)(2), Hg(GS)(2), MeHgCys, MeHgGS. Complexes were characterised by electrospray mass spectrometry (MS) equipped with an ion trap and the fragmentation pattern of MeHgCys was explained by using MP2 and B3LYP calculations, showing the importance of mercury-amine interactions in the gas phase. Chromatographic baseline separation was performed within 10 min with formic acid as the mobile phase on a reversed-phase column. Detection was done by online simultaneous coupling of ES-MS and inductively coupled plasma MS. When the mercury complexes were spiked in real samples (plant extracts), no perturbation of the separation and detection conditions was observed, suggesting that this method is capable of detecting mercury biothiol complexes in plants.

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Collagen is widely used as a biomedical material, and its importance is likely to grow as research and understanding progresses in this field. As a biomedical material, ensuring the sterility of collagen before use as, or incorporation into, a medical device is paramount. However, common sterilisation techniques can induce changes in the physical structure and protein chemistry of collagen, potentially affecting the performance. In this preliminary study, the influence of autoclaving, gamma irradiation and ethylene oxide gas sterilisation on the denaturation temperature and helical content of the collagen was evaluated using differential scanning calorimetry and Fourier transform infrared spectroscopy. Early results indicate that all sterilisation techniques affect collagen properties but suggest that the least damaging of the techniques investigated was y irradiation.

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Cladobotryutn dendroides, causal agent of cobweb disease of Agaricus bisporus, has become increasingly resistant to methylbenzimidazole carbamate (MBC) fungicides following the extensive use of MBC in cultivated mushroom production in Ireland. Of 38 isolates of C. dendroides obtained from Irish mushroom units, 34 were resistant to carbendazim. Primers based on conserved regions of the -tubulin gene were used to amplify and sequence a portion of the -tubulin gene in C. dendroides. A point mutation was detected at codon 50 in isolates resistant to benzimidazole fungicides, causing an amino acid substitution from tyrosine to cysteine. Species-specific PCR primers were designed to amplify the region of the -tubulin gene containing this substitution. The point mutation removed an Ace I restriction site in the -tubulin gene sequence of resistant isolates. Digestion of the PCR product with Ace I thus provides a rapid diagnostic test to differentiate sensitive and resistant isolates of this fungus. EMBL accession number: YI2256.