935 resultados para Steady state.


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Objective To explore a possible correlation between endothelin 1 (ET-1), the most potent endothelium-derived contracting factor that modulates vascular smooth muscle tone, and arterial disease in patients with the antiphospholipid syndrome (APS). Methods Plasma levels of ET-1 were measured in APS patients with (n = 16) and without (n = 11) arterial thrombosis and in non-APS patients with arterial thrombosis (n = 9). In addition, steady-state prepro-ET-1 messenger RNA (mRNA) levels were determined in endothelial cells treated with a range of human monoclonal anticardiolipin antibodies (aCL) (as anti-β2-glycoprotein I antibodies) by semiquantitative 32P-dCTP-labeled reverse transcription-polymerase chain reaction. Results Compared with healthy controls, markedly increased plasma levels of ET-1 were found in APS patients with arterial thrombosis (2.00 ± 0.87 versus 0.96 ± 0.37 pg/ml; P = 0.0001) but not in other groups. Three human monoclonal aCL induced prepro-ET-1 mRNA levels significantly more than did control monoclonal antibody lacking aCL activity. Conclusion Plasma ET-1 levels correlated significantly with a history of arterial thrombosis in patients with APS. Prepro-ET-1 mRNA was induced by human monoclonal aCL in the in vitro experimental system. The induction of ET-1 by antiphospholipid antibodies might contribute to increased arterial tone, leading to vasospasm and, ultimately, to arterial occlusion.

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We previously showed that growth of the nontumorigenic, immortal murine melanocyte line Mel-ab correlates with the depletion of protein kinase C (PKC), whereas quiescence is associated with elevated levels of this enzyme (Brooks G, et al., Cancer Res 51: 3281–3288, 1991). Here we report responses that occur in these cells downstream of PKC activation or downregulation. We examined induction of 12-O-tetradecanoylphorbol-13-acetate (TPA)-inducible sequence (TIS) gene expression in Mel-ab melanocytes and in their transformed counterparts, B16 melanoma cells. Exposure of quiescent Mel-ab cells to the PKC-activating phorbol esters TPA or sapintoxin A at 81 nM for 2 h increased levels of mRNA for six of seven TIS genes examined (twofold to 80-fold increase in steady-state RNA levels for TIS 1, 7, 8, 11, 21, and 28 (c-fos); TIS 10 expression was not affected). No induction of 115 gene expression was observed either in growing Mel-ab cells maintained in 324 nM phorbol 12,13-dibutyrate or in B16 cells previously unexposed to phorbol esters, in which normal PKC levels were endogenously depressed. The cAMP-elevating agents choleratoxin (10 nM) and dibutyryl cyclic AMP (2.5 mM) increased levels of TIS mRNA (with the exception of TIS 10) in both proliferating Mel-ab and B16 cells, suggesting that downregulation of the PKC pathway is specific and not a consequence of a general inhibition of all signalling pathways.

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The Stokes drift induced by surface waves distorts turbulence in the wind-driven mixed layer of the ocean, leading to the development of streamwise vortices, or Langmuir circulations, on a wide range of scales. We investigate the structure of the resulting Langmuir turbulence, and contrast it with the structure of shear turbulence, using rapid distortion theory (RDT) and kinematic simulation of turbulence. Firstly, these linear models show clearly why elongated streamwise vortices are produced in Langmuir turbulence, when Stokes drift tilts and stretches vertical vorticity into horizontal vorticity, whereas elongated streaky structures in streamwise velocity fluctuations (u) are produced in shear turbulence, because there is a cancellation in the streamwise vorticity equation and instead it is vertical vorticity that is amplified. Secondly, we develop scaling arguments, illustrated by analysing data from LES, that indicate that Langmuir turbulence is generated when the deformation of the turbulence by mean shear is much weaker than the deformation by the Stokes drift. These scalings motivate a quantitative RDT model of Langmuir turbulence that accounts for deformation of turbulence by Stokes drift and blocking by the air–sea interface that is shown to yield profiles of the velocity variances in good agreement with LES. The physical picture that emerges, at least in the LES, is as follows. Early in the life cycle of a Langmuir eddy initial turbulent disturbances of vertical vorticity are amplified algebraically by the Stokes drift into elongated streamwise vortices, the Langmuir eddies. The turbulence is thus in a near two-component state, with suppressed and . Near the surface, over a depth of order the integral length scale of the turbulence, the vertical velocity (w) is brought to zero by blocking of the air–sea interface. Since the turbulence is nearly two-component, this vertical energy is transferred into the spanwise fluctuations, considerably enhancing at the interface. After a time of order half the eddy decorrelation time the nonlinear processes, such as distortion by the strain field of the surrounding eddies, arrest the deformation and the Langmuir eddy decays. Presumably, Langmuir turbulence then consists of a statistically steady state of such Langmuir eddies. The analysis then provides a dynamical connection between the flow structures in LES of Langmuir turbulence and the dominant balance between Stokes production and dissipation in the turbulent kinetic energy budget, found by previous authors.

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Brand competition is modelled using an agent based approach in order to examine the long run dynamics of market structure and brand characteristics. A repeated game is designed where myopic firms choose strategies based on beliefs about their rivals and consumers. Consumers are heterogeneous and can observe neighbour behaviour through social networks. Although firms do not observe them, the social networks have a significant impact on the emerging market structure. Presence of networks tends to polarize market share and leads to higher volatility in brands. Yet convergence in brand characteristics usually happens whenever the market reaches a steady state. Scale-free networks accentuate the polarization and volatility more than small world or random networks. Unilateral innovations are less frequent under social networks.

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Orlistat is an anti-obesity treatment with which several gastrointestinal (GI) side-effects are commonly associated in the initial stages of therapy. There is no physiological explanation as to why two-thirds of those who take the drug experience one or more side-effects. It has been hypothesized that the GI microbiota may protect from or contribute to these GI disturbances. Using in vitro batch culture and human gut model systems, studies were conducted to determine whether increased availability of dietary lipids and/or orlistat affect the composition and/or activity of the faecal microbiota. Results from 24-h batch culture fermentation experiments demonstrated no effect of orlistat in the presence or absence of a dietary lipid (olive oil) on the composition of bacterial communities [as determined by fluorescence in situ hybridization (FISH) and denaturing gradient gel electrophoresis (DGGE) analyses], but did show there was great variability in the lipolytic activities of the microbiotas of individuals, as determined by gas chromatography analysis of long-chain fatty acids in samples. Subsequent studies focused on the effect of orlistat in the presence and absence of lipid in in vitro human gut model systems. Systems were run for 14 days with gut model medium (GMM) only (to steady state, SS), then fed at 12-h intervals with 50 mg orlistat, 2 g olive oil or a mixture of both for 14 days. FISH and DGGE were used to monitor changes in bacterial populations. Bacteria were cultivated from the GMM only (control) systems at SS. All strains isolated were screened for lipolytic activity using tributyrin agar. FISH and DGGE demonstrated that none of the compounds (singly or in combination) added to the systems had any notable effect on microbial population dynamics for any of the donors, although Subdoligranulum populations appeared to be inhibited by orlistat in the presence or absence of lipid. Orlistat had little or no effect on the metabolism of indigenous and added lipids in the fermentation systems, but there was great variability in the way the faecal microbiotas of the donors were able to degrade added lipids. Variability in lipid degradation could be correlated with the number and activity of isolated lipolytic bacteria. The mechanism by which orlistat and the GI microbiota cause side-effects in individuals is unknown, but several hypotheses have been proposed to account for their manifestation. The demonstration of great variability in the lipolytic activity of microbiotas to degrade lipids led to a large-scale cultivation-based study of lipolytic/lipase-positive bacteria present in the human faecal microbiota. Of 4,000 colonies isolated from 15 donors using five different agars, 378 strains were identified that had lipase activity. Molecular identification of strains isolated from five donors demonstrated that lipase activity is more prevalent in the human GI microbiota than previously thought, with members of the phyla Firmicutes, Bacteroidetes and Actinobacteria identified. Molecular identification and characterization of the substrate specificities of the strains will be carried out as part of ongoing work.

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Atmosphere–ocean general circulation models (AOGCMs) predict a weakening of the Atlantic meridional overturning circulation (AMOC) in response to anthropogenic forcing of climate, but there is a large model uncertainty in the magnitude of the predicted change. The weakening of the AMOC is generally understood to be the result of increased buoyancy input to the north Atlantic in a warmer climate, leading to reduced convection and deep water formation. Consistent with this idea, model analyses have shown empirical relationships between the AMOC and the meridional density gradient, but this link is not direct because the large-scale ocean circulation is essentially geostrophic, making currents and pressure gradients orthogonal. Analysis of the budget of kinetic energy (KE) instead of momentum has the advantage of excluding the dominant geostrophic balance. Diagnosis of the KE balance of the HadCM3 AOGCM and its low-resolution version FAMOUS shows that KE is supplied to the ocean by the wind and dissipated by viscous forces in the global mean of the steady-state control climate, and the circulation does work against the pressure-gradient force, mainly in the Southern Ocean. In the Atlantic Ocean, however, the pressure-gradient force does work on the circulation, especially in the high-latitude regions of deep water formation. During CO2-forced climate change, we demonstrate a very good temporal correlation between the AMOC strength and the rate of KE generation by the pressure-gradient force in 50–70°N of the Atlantic Ocean in each of nine contemporary AOGCMs, supporting a buoyancy-driven interpretation of AMOC changes. To account for this, we describe a conceptual model, which offers an explanation of why AOGCMs with stronger overturning in the control climate tend to have a larger weakening under CO2 increase.

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A simple parameter adaptive controller design methodology is introduced in which steady-state servo tracking properties provide the major control objective. This is achieved without cancellation of process zeros and hence the underlying design can be applied to non-minimum phase systems. As with other self-tuning algorithms, the design (user specified) polynomials of the proposed algorithm define the performance capabilities of the resulting controller. However, with the appropriate definition of these polynomials, the synthesis technique can be shown to admit different adaptive control strategies, e.g. self-tuning PID and self-tuning pole-placement controllers. The algorithm can therefore be thought of as an embodiment of other self-tuning design techniques. The performances of some of the resulting controllers are illustrated using simulation examples and the on-line application to an experimental apparatus.

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We present a novel kinetic multi-layer model that explicitly resolves mass transport and chemical reaction at the surface and in the bulk of aerosol particles (KM-SUB). The model is based on the PRA framework of gas-particle interactions (Poschl-Rudich-Ammann, 2007), and it includes reversible adsorption, surface reactions and surface-bulk exchange as well as bulk diffusion and reaction. Unlike earlier models, KM-SUB does not require simplifying assumptions about steady-state conditions and radial mixing. The temporal evolution and concentration profiles of volatile and non-volatile species at the gas-particle interface and in the particle bulk can be modeled along with surface concentrations and gas uptake coefficients. In this study we explore and exemplify the effects of bulk diffusion on the rate of reactive gas uptake for a simple reference system, the ozonolysis of oleic acid particles, in comparison to experimental data and earlier model studies. We demonstrate how KM-SUB can be used to interpret and analyze experimental data from laboratory studies, and how the results can be extrapolated to atmospheric conditions. In particular, we show how interfacial and bulk transport, i.e., surface accommodation, bulk accommodation and bulk diffusion, influence the kinetics of the chemical reaction. Sensitivity studies suggest that in fine air particulate matter oleic acid and compounds with similar reactivity against ozone (carbon-carbon double bonds) can reach chemical lifetimes of many hours only if they are embedded in a (semi-)solid matrix with very low diffusion coefficients (< 10(-10) cm(2) s(-1)). Depending on the complexity of the investigated system, unlimited numbers of volatile and non-volatile species and chemical reactions can be flexibly added and treated with KM-SUB. We propose and intend to pursue the application of KM-SUB as a basis for the development of a detailed master mechanism of aerosol chemistry as well as for the derivation of simplified but realistic parameterizations for large-scale atmospheric and climate models.

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We present a novel kinetic multi-layer model that explicitly resolves mass transport and chemical reaction at the surface and in the bulk of aerosol particles (KM-SUB). The model is based on the PRA framework of gas–particle interactions (P¨oschl et al., 5 2007), and it includes reversible adsorption, surface reactions and surface-bulk exchange as well as bulk diffusion and reaction. Unlike earlier models, KM-SUB does not require simplifying assumptions about steady-state conditions and radial mixing. The temporal evolution and concentration profiles of volatile and non-volatile species at the gas-particle interface and in the particle bulk can be modeled along with surface 10 concentrations and gas uptake coefficients. In this study we explore and exemplify the effects of bulk diffusion on the rate of reactive gas uptake for a simple reference system, the ozonolysis of oleic acid particles, in comparison to experimental data and earlier model studies. We demonstrate how KM-SUB can be used to interpret and analyze experimental data from laboratory stud15 ies, and how the results can be extrapolated to atmospheric conditions. In particular, we show how interfacial transport and bulk transport, i.e., surface accommodation, bulk accommodation and bulk diffusion, influence the kinetics of the chemical reaction. Sensitivity studies suggest that in fine air particulate matter oleic acid and compounds with similar reactivity against ozone (C=C double bonds) can reach chemical lifetimes of 20 multiple hours only if they are embedded in a (semi-)solid matrix with very low diffusion coefficients (10−10 cm2 s−1). Depending on the complexity of the investigated system, unlimited numbers of volatile and non-volatile species and chemical reactions can be flexibly added and treated with KM-SUB. We propose and intend to pursue the application of KM-SUB 25 as a basis for the development of a detailed master mechanism of aerosol chemistry as well as for the derivation of simplified but realistic parameterizations for large-scale atmospheric and climate models.

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Higher order cumulant analysis is applied to the blind equalization of linear time-invariant (LTI) nonminimum-phase channels. The channel model is moving-average based. To identify the moving average parameters of channels, a higher-order cumulant fitting approach is adopted in which a novel relay algorithm is proposed to obtain the global solution. In addition, the technique incorporates model order determination. The transmitted data are considered as independently identically distributed random variables over some discrete finite set (e.g., set {±1, ±3}). A transformation scheme is suggested so that third-order cumulant analysis can be applied to this type of data. Simulation examples verify the feasibility and potential of the algorithm. Performance is compared with that of the noncumulant-based Sato scheme in terms of the steady state MSE and convergence rate.

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Searching for the optimum tap-length that best balances the complexity and steady-state performance of an adaptive filter has attracted attention recently. Among existing algorithms that can be found in the literature, two of which, namely the segmented filter (SF) and gradient descent (GD) algorithms, are of particular interest as they can search for the optimum tap-length quickly. In this paper, at first, we carefully compare the SF and GD algorithms and show that the two algorithms are equivalent in performance under some constraints, but each has advantages/disadvantages relative to the other. Then, we propose an improved variable tap-length algorithm using the concept of the pseudo fractional tap-length (FT). Updating the tap-length with instantaneous errors in a style similar to that used in the stochastic gradient [or least mean squares (LMS)] algorithm, the proposed FT algorithm not only retains the advantages from both the SF and the GD algorithms but also has significantly less complexity than existing algorithms. Both performance analysis and numerical simulations are given to verify the new proposed algorithm.

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Obstacles considerably influence boundary layer processes. Their influences have been included in mesoscale models (MeM) for a long time. Methods used to parameterise obstacle effects in a MeM are summarised in this paper using results of the mesoscale model METRAS as examples. Besides the parameterisation of obstacle influences it is also possible to use a joint modelling approach to describe obstacle induced and mesoscale changes. Three different methods may be used for joint modelling approaches: The first method is a time-slice approach, where steady basic state profiles are used in an obstacle resolving microscale model (MiM, example model MITRAS) and diurnal cycles are derived by joining steady-state MITRAS results. The second joint modelling approach is one-way nesting, where the MeM results are used to initialise the MiM and to drive the boundary values of the MiM dependent on time. The third joint modelling approach is to apply multi-scale models or two-way nesting approaches, which include feedbacks from the MiM to the MeM. The advantages and disadvantages of the different approaches and remaining problems with joint Reynolds-averaged Navier–Stokes modelling approaches are summarised in the paper.

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In industrial practice, constrained steady state optimisation and predictive control are separate, albeit closely related functions within the control hierarchy. This paper presents a method which integrates predictive control with on-line optimisation with economic objectives. A receding horizon optimal control problem is formulated using linear state space models. This optimal control problem is very similar to the one presented in many predictive control formulations, but the main difference is that it includes in its formulation a general steady state objective depending on the magnitudes of manipulated and measured output variables. This steady state objective may include the standard quadratic regulatory objective, together with economic objectives which are often linear. Assuming that the system settles to a steady state operating point under receding horizon control, conditions are given for the satisfaction of the necessary optimality conditions of the steady-state optimisation problem. The method is based on adaptive linear state space models, which are obtained by using on-line identification techniques. The use of model adaptation is justified from a theoretical standpoint and its beneficial effects are shown in simulations. The method is tested with simulations of an industrial distillation column and a system of chemical reactors.

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Based on integrated system optimisation and parameter estimation a method is described for on-line steady state optimisation which compensates for model-plant mismatch and solves a non-linear optimisation problem by iterating on a linear - quadratic representation. The method requires real process derivatives which are estimated using a dynamic identification technique. The utility of the method is demonstrated using a simulation of the Tennessee Eastman benchmark chemical process.

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Adaptive least mean square (LMS) filters with or without training sequences, which are known as training-based and blind detectors respectively, have been formulated to counter interference in CDMA systems. The convergence characteristics of these two LMS detectors are analyzed and compared in this paper. We show that the blind detector is superior to the training-based detector with respect to convergence rate. On the other hand, the training-based detector performs better in the steady state, giving a lower excess mean-square error (MSE) for a given adaptation step size. A novel decision-directed LMS detector which achieves the low excess MSE of the training-based detector and the superior convergence performance of the blind detector is proposed.