71 resultados para Vibration signal analysis


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This work presents the application of reduced rank regression to the field of systems biology. A computational approach is used to investigate the mechanisms of the janus-associated kinases/signal transducers and transcription factors (JAK/STAT) and mitogen activated protein kinases (MAPK) signal transduction pathways in hepatic cells stimulated by interleukin-6. The results obtained identify the contribution of individual reactions to the dynamics of the model. These findings are compared to previously available results from sensitivity analysis of the model which focused on the parameters involved and their effect. This application of reduced rank regression allows for an understanding of the individual reaction terms involved in the modelled signal transduction pathways and has the benefit of being computationally inexpensive. The obtained results complement existing findings and also confirm the importance of several protein complexes in the MAPK pathway which hints at benefits that can be achieved by further refining the model.

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During extreme sea states so called impact events can be observed on the wave energy converter Oyster. In small scale experimental tests these impact events cause high frequency signals in the measured load which decrease confidence in the data obtained. These loads depend on the structural dynamics of the model. Amplification of the loads can occur and is transferred through the structure from the point of impact to the load cell located in the foundation. Since the determination of design data and load cases for Wave Energy Converters originate from scale experiments, this lack of confidence has a direct effect on the development.

Numerical vibration analysis is a valuable tool in the research of the structural load response of Oyster to impact events, but must take into account the effect of the surrounding water. This can be done efficiently by adding an added mass distribution, computed with a linearised potential boundary element method. This paper presents the development and validation of a numerical procedure, which couples the OpenSource boundary element code NEMOH with the Finite Element Analysis tool CodeAster. Numerical results of the natural frequencies and mode shapes of the structure under the influence of added mass due to specific structural modes are compared with experimental results.

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Fully quantitative analyses of DRIFTS data are required when the surface concentrations and the specific rate constants of reaction (or desorption) of adsorbates are needed to validate microkinetic models. The relationship between the surface coverage of adsorbates and various functions derived from the signal collected by DRIFTS is discussed here. The Kubelka-Munk and pseudoabsorbance (noted here as absorbance, for the sake of brevity) transformations were considered, since those are the most commonly used functions when data collected by DRIFTS are reported. Theoretical calculations and experimental evidence based on the study of CO adsorption on Pt/SiO2 and formate species adsorbed on Pt/CeO2 showed that the absorbance (i.e., ) log 1/R������¢, with R������¢ ) relative reflectance) is the most appropriate, yet imperfect, function to give a linear representation of the adsorbate surface concentration in the examples treated here, for which the relative reflectance R������¢ is typically > 60%. When the adsorbates lead to a strong signal absorption (e.g., R������¢ < 60%), the Kubelka-Munk function is actually more appropriate. The absorbance allows a simple correction of baseline drifts, which often occur during time-resolved data collection over catalytic materials. Baseline corrections are markedly more complex in the case of the other mathematical transforms, including the function proposed by Matyshak and Krylov (Catal. Today 1995, 25, 1-87), which has been proposed as an appropriate representation of surface concentrations in DRIFTS spectroscopy.

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The reactivity of the species formed at the surface of a Au/Ce(La)O2 catalyst during the water������¢���¯���¿���½���¯���¿���½gas shift (WGS) reaction were investigated by operando diffuse reflectance Fourier transform spectroscopy (DRIFTS) at the chemical steady state during isotopic transient kinetic analyses (SSITKA). The exchanges of the reaction product CO2 and of formate and carbonate surface species were followed during an isotopic exchange of the reactant CO using a DRIFTS cell as a single reactor. The DRIFTS cell was a modified commercial cell that yielded identical reaction rates to that measured over a quartz plug-flow reactor. The DRIFTS signal was used to quantify the relative oncentrations of the surface species and CO2. The analysis of the formate exchange curves between 428 and 493 K showed that at least two levels of reactivity were present. ������¢���¯���¿���½���¯���¿���½Slow formates������¢���¯���¿���½���¯���¿���½ displayed an exchange rate constant 10- to 20-fold slower than that of the reaction product CO2. ������¢���¯���¿���½���¯���¿���½Fast formates������¢���¯���¿���½���¯���¿���½ were exchanged on a time scale similar to that of CO2. Multiple nonreactive readsorption of CO2 took place, accounting for the kinetics of the exchange of CO2(g) and making it impossible to determine the number of active sites through the SSITKA technique. The concentration (in mol g������¢���¯���¿���½���¯���¿���½1) of formates on the catalyst was determined through a calibration curve and allowed calculation of the specific rate of formate decomposition. The rate of CO2 formation was more than an order of magnitude higher than the rate of decomposition of formates (slow + fast species), indicating that all of the formates detected by DRIFTS could not be the main reaction intermediates in the production of CO2. This work stresses the importance of full quantitative analyses (measuring both rate constants and adsorbate concentrations) when investigating the role of adsorbates as potential reaction intermediates, and illustrates how even reactive species seen by DRIFTS may be unimportant in the overall reaction scheme.

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The work presented here is aimed at determining the potential and limitations of Raman spectroscopy for fat analysis by carrying out a systematic investigation of C-4-C-24 FAME. These provide a simple, well-characterized set of compounds in which the effect of making incremental changes can be studied over a wide range of chain lengths and degrees of unsaturation. The effect of temperature on the spectra was investigated over much larger ranges than would normally be encountered in real analytical measurements. It was found that for liquid FAME the best internal standard band was the carbonyl stretching vibration nu(C = O), whose position is affected by changes in sample chain length and physical state; in the samples studied here, it was found to lie between 1729 and 1748 cm(-1). Further, molar unsaturation could be correlated with the ratio of the nu(C = O) to either nu(C = C) or delta(H-C = ) with R-2 > 0.995. Chain length was correlated with the delta(CH2)(tw)/nu(C = O) ratio, (where "tw" indicates twisting) but separate plots for odd- and even-numbered carbon chains were necessary to obtain R-2 > 0.99 for liquid samples. Combining the odd- ani even-numbered carbon chain data in a single plot reduced the correlation to R-2 = 0.94-0.96, depending on the band ratios used. For molal unsaturation the band ratio that correlated linearly with unsaturation (R-2 > 0.99) was nu(C = C)/delta(CH2)(SC) (where "sc" indicates scissoring). Other band ratios show much more complex behavior with changes in chemical and physical structure. This complex behavior results from the fact that the bands do not arise from simple vibrations of small, discrete regions of the molecules but are due to complex motions of large sections of the FAME so that making incremental changes in structure does not necessarily lead to simple incremental changes in spectra.

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A preliminary differential non-LTE model atmosphere analysis of moderate resolution (R ~ 5 000) and signal-to-noise ratio spectra of 48 Small Magellanic Cloud B-type supergiants is presented. Standard techniques are adopted, viz. plane-parallel geometry and radiative and hydrostatic equilibrium. Spectroscopic atmospheric parameters (T_eff, log g and v_turb), luminosities and chemical abundances (He, C, N, O, Mg and Si) are estimated. These are compared with those deduced for a comparable sample of Galactic supergiants. The SMC targets appear to have similar atmospheric parameters, luminosities and helium abundances to the Galactic sample. Their magnesium and silicon underabundances are compatible with those found for main sequence SMC objects and there is no evidence for any large variation in their oxygen abundances. By contrast both their carbon and nitrogen lines strengths are inconsistent with single abundances, while their nitrogen to carbon abundance ratios appear to vary by at least as much and probably more than that found in the Galactic sample.

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This paper considers invariant texture analysis. Texture analysis approaches whose performances are not affected by translation, rotation, affine, and perspective transform are addressed. Existing invariant texture analysis algorithms are carefully studied and classified into three categories: statistical methods, model based methods, and structural methods. The importance of invariant texture analysis is presented first. Each approach is reviewed according to its classification, and its merits and drawbacks are outlined. The focus of possible future work is also suggested.

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Platyhelminthes occupy a unique position in nerve-muscle evolution, being the most primitive of metazoan phyla. Essentially, their nervous system consists of an archaic brain and associated pairs of longitudinal nerve cords cross-linked as an orthogon by transverse commissures. Confocal imaging reveals that these central nervous system elements are in continuity with an array of peripheral nerve plexuses which innervate a well-differentiated grid work of somatic muscle as well as a complexity of myofibres associated with organs of attachment, feeding, and reproduction. Electrophysiological studies of flatworm muscles have exposed a diversity of voltage-activated ion channels that influence muscle contractile events. Neuronal cell types are mainly multi- and bi-polar and highly secretory in nature, producing a heterogeneity of vesicular inclusions whose contents have been identified cytochemically to include all three major types of cholinergic, aminergic, and peptidergic messenger molecules. A landmark discovery in flatworm neurobiology was the biochemical isolation and amino acid sequencing of two groups of native neuropeptides: neuropeptide F and FMRFamide-related peptides (FaRPs). Both families of neuropeptide are abundant and broadly distributed in platyhelminths, occurring in neuronal vesicles in representatives of all major flatworm taxa. Dual localization studies have revealed that peptidergic and cholinergic substances occupy neuronal sets separate from those of serotoninergic components. The physiological actions of neuronal messengers in flatworms are beginning to be established, and where examined, FaRPs and 5-HT are myoexcitatory, while cholinomimetic substances are generally inhibitory. There is immunocytochemical evidence that FaRPs and 5-HT have a regulatory role in the mechanism of egg assembly. Use of muscle strips and (or) muscle fibres from free-living and parasitic flatworms has provided baseline information to indicate that muscle responses to FaRPs are mediated by a G-protein-coupled receptor, and that the signal transduction pathway for contraction involves the second messengers cAMP and protein kinase C.

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The least-mean-fourth (LMF) algorithm is known for its fast convergence and lower steady state error, especially in sub-Gaussian noise environments. Recent work on normalised versions of the LMF algorithm has further enhanced its stability and performance in both Gaussian and sub-Gaussian noise environments. For example, the recently developed normalised LMF (XE-NLMF) algorithm is normalised by the mixed signal and error powers, and weighted by a fixed mixed-power parameter. Unfortunately, this algorithm depends on the selection of this mixing parameter. In this work, a time-varying mixed-power parameter technique is introduced to overcome this dependency. A convergence analysis, transient analysis, and steady-state behaviour of the proposed algorithm are derived and verified through simulations. An enhancement in performance is obtained through the use of this technique in two different scenarios. Moreover, the tracking analysis of the proposed algorithm is carried out in the presence of two sources of nonstationarities: (1) carrier frequency offset between transmitter and receiver and (2) random variations in the environment. Close agreement between analysis and simulation results is obtained. The results show that, unlike in the stationary case, the steady-state excess mean-square error is not a monotonically increasing function of the step size. (c) 2007 Elsevier B.V. All rights reserved.

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Modeling of on-body propagation channels is of paramount importance to those wishing to evaluate radio channel performance for wearable devices in body area networks (BANs). Difficulties in modeling arise due to the highly variable channel conditions related to changes in the user's state and local environment. This study characterizes these influences by using time-series analysis to examine and model signal characteristics for on-body radio channels in user stationary and mobile scenarios in four different locations: anechoic chamber, open office area, hallway, and outdoor environment. Autocorrelation and cross-correlation functions are reported and shown to be dependent on body state and surroundings. Autoregressive (AR) transfer functions are used to perform time-series analysis and develop models for fading in various on-body links. Due to the non-Gaussian nature of the logarithmically transformed observed signal envelope in the majority of mobile user states, a simple method for reproducing the failing based on lognormal and Nakagami statistics is proposed. The validity of the AR models is evaluated using hypothesis testing, which is based on the Ljung-Box statistic, and the estimated distributional parameters of the simulator output compared with those from experimental results.

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This letter derives mathematical expressions for the received signal-to-interference-plus-noise ratio (SINR) of uplink Single Carrier (SC) Frequency Division Multiple Access (FDMA) multiuser MIMO systems. An improved frequency domain receiver algorithm is derived for the studied systems, and is shown to be significantly superior to the conventional linear MMSE based receiver in terms of SINR and bit error rate (BER) performance.