68 resultados para Tanks-in-series Model

em University of Queensland eSpace - Australia


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Predicted area under curve (AUC), mean transit time (MTT) and normalized variance (CV2) data have been compared for parent compound and generated metabolite following an impulse input into the liver, Models studied were the well-stirred (tank) model, tube model, a distributed tube model, dispersion model (Danckwerts and mixed boundary conditions) and tanks-in-series model. It is well known that discrimination between models for a parent solute is greatest when the parent solute is highly extracted by the liver. With the metabolite, greatest model differences for MTT and CV2 occur when parent solute is poorly extracted. In all cases the predictions of the distributed tube, dispersion, and tasks-in-series models are between the predictions of the rank and tube models. The dispersion model with mixed boundary conditions yields identical predictions to those for the distributed tube model (assuming an inverse gaussian distribution of tube transit times). The dispersion model with Danckwerts boundary conditions and the tanks-in series models give similar predictions to the dispersion (mixed boundary conditions) and the distributed tube. The normalized variance for parent compound is dependent upon hepatocyte permeability only within a distinct range of permeability values. This range is similar for each model but the order of magnitude predicted for normalized variance is model dependent. Only for a one-compartment system is the MIT for generated metabolite equal to the sum of MTTs for the parent compound and preformed metabolite administered as parent.

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In this paper, we report our modelling evaluation on the effect of tracer density on axial dispersion in a batch oscillatory baffled column (OBC). Tracer solution of potassium nitrite, its specific density ranged from 1.0 to 1.5, was used in the study, and was injected to the vertical column from either the top or bottom. Local concentration profiles are measured using conductivity probes at two locations along the height of the column. Using the experimental measured concentration profiles together with both 'Tank-in-Series' and 'Plug Flow with Axial Dispersion' models, axial dispersion coefficients were determined and used to describe the effect of specific tracer density on mixing in the OBC. The results showed that the axial dispersion coefficients evaluated by the two models are very similar in both magnitudes and trends, and the range of variations in such coefficients is generally larger for the bottom injection than for the top one. Empirical correlations linking the mechanical energy for mixing, the specific density of tracer and axial dispersion coefficient were established. Using these correlations, we identified the enhancements of up to 269% on axial dispersion for various specific tracer densities. (C) 2002 Elsevier Science B.V. All rights reserved.

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The Gauss-Marquardt-Levenberg (GML) method of computer-based parameter estimation, in common with other gradient-based approaches, suffers from the drawback that it may become trapped in local objective function minima, and thus report optimized parameter values that are not, in fact, optimized at all. This can seriously degrade its utility in the calibration of watershed models where local optima abound. Nevertheless, the method also has advantages, chief among these being its model-run efficiency, and its ability to report useful information on parameter sensitivities and covariances as a by-product of its use. It is also easily adapted to maintain this efficiency in the face of potential numerical problems (that adversely affect all parameter estimation methodologies) caused by parameter insensitivity and/or parameter correlation. The present paper presents two algorithmic enhancements to the GML method that retain its strengths, but which overcome its weaknesses in the face of local optima. Using the first of these methods an intelligent search for better parameter sets is conducted in parameter subspaces of decreasing dimensionality when progress of the parameter estimation process is slowed either by numerical instability incurred through problem ill-posedness, or when a local objective function minimum is encountered. The second methodology minimizes the chance of successive GML parameter estimation runs finding the same objective function minimum by starting successive runs at points that are maximally removed from previous parameter trajectories. As well as enhancing the ability of a GML-based method to find the global objective function minimum, the latter technique can also be used to find the locations of many non-global optima (should they exist) in parameter space. This can provide a useful means of inquiring into the well-posedness of a parameter estimation problem, and for detecting the presence of bimodal parameter and predictive probability distributions. The new methodologies are demonstrated by calibrating a Hydrological Simulation Program-FORTRAN (HSPF) model against a time series of daily flows. Comparison with the SCE-UA method in this calibration context demonstrates a high level of comparative model run efficiency for the new method. (c) 2006 Elsevier B.V. All rights reserved.

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Form factors are derived for a model describing the coherent Josephson tunneling between two coupled Bose-Einstein condensates. This is achieved by studying the exact solution of the model within the framework of the algebraic Bethe ansatz. In this approach the form factors are expressed through determinant representations which are functions of the roots of the Bethe ansatz equations.

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We extend a recent construction for an integrable model describing Josephson tunneling between identical BCS systems to the case where the BCS systems have different single particle energy levels. The exact solution of this generalized model is obtained through the Bethe ansatz.

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A substantial number of GH regulated genes have been reported in mature hepatocytes. but genes involved in GH-initiated cell differentiation have not yet been identified. Here we have studied a, ell-characterised model of GH-dependent differentiation, adipogenesis of 3T3-F442A preadipocytes, to identify genes rapidly induced by GH. Using the suppression subtractive hybridisation technique, we have identified eight genes induced within 60 min of GH treatment, and verified these by northern analysis. Six were identifiable as Stat 2. Stat 3, thrombospondin-1. oncostatin M receptor beta chain. a DEAD box RNA helicase. and muscleblind. a developmental transcription factor. Bioinformatic approaches assigned one of the two remaining unknown genes as a novel 436 residue serine,threonine kinase. As each of the identified genes hake important developmental roles. they may be important in initiating GH-induced adipogenesis. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

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The thiol tripeptides, glutathione (GSH) and homoglutathione (hGSH), perform multiple roles in legumes, including protection against toxicity of free radicals and heavy metals. The three genes involved in the synthesis of GSH and hGSH in the model legume, Lotus japonicus, have been fully characterized and appear to be present as single copies in the genome. The gamma-glutamylcysteine synthetase (gammaecs) gene was mapped on the long arm of chromosome 4 (70.0 centimorgans [cM]) and consists of 15 exons, whereas the glutathione synthetase (gshs) and homoglutathione synthetase (hgshs) genes were mapped on the long arm of chromosome 1 (81.3 cM) and found to be arranged in tandem, with a separation of approximately 8 kb. Both genes consist of 12 exons of exactly the same size (except exon 1, which is similar). Two types of transcripts were detected for the gshs gene, which putatively encode proteins localized in the plastids and cytosol. Promoter regions contain cis-acting regulatory elements that may be involved in the plant's response to light, hormones, and stress. Determination of transcript levels, enzyme activities, and thiol contents in nodules, roots, and leaves revealed that gammaecs and hgshs are expressed in all three plant organs, whereas gshs is significantly functional only in nodules. This strongly suggests an important role of GSH in the rhizobia-legume symbiosis.

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and human capital externalities. Because of such externalities, education investment is too low and fertility is too high. While education subsidies are the conventional means to deal with these problems, we show that the optimal policy also comprises debt even when distortionary taxes are used. The reason is that debt tips the usual trade-off between children's quantity and quality in favor of the latter by increasing the bequest cost of children. The optimal debt-output ratio exceeds 10% for plausible parameterization. (C) 2002 Elsevier B.V. All rights reserved.

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Background and Aims: We have optimized the isolated perfused mouse kidney (IPMK) model for studying renal vascular and tubular function in vitro using 24-28 g C57BL6J mice; the wild type controls for many transgenic mice. Methods and Results: Buffer composition was optimized for bovine serum albumin concentration (BSA). The effect of adding erythrocytes on renal function and morphology was assessed. Autoregulation was investigated during stepped increases in perfusion pressure. Perfusion for 60 min at 90-110 mmHg with Krebs bicarbonate buffer containing 5.5% BSA, and amino acids produced functional parameters within the in vivo range. Erythrocytes increased renal vascular resistance (3.8 +/- 0.2 vs 2.4 +/- 0.1 mL/min.mmHg, P < 0.05), enhanced sodium reabsorption (FENa = 0.3 +/- 0.08 vs 1.5 +/- 0.7%, P < 0.05), produced equivalent glomerular filtration rates (GFR; 364 +/- 38 vs 400 +/- 9 muL/min per gkw) and reduced distal tubular cell injury in the inner stripe (5.8 +/- 1.7 vs 23.7 +/- 3.1%, P < 0.001) compared to cell free perfusion. The IPMK was responsive to vasoconstrictor (angiotensin II, EC50 100 pM) and vasodilator (methacholine, EC50 75 nM) mediators and showed partial autoregulation of perfusate flow under control conditions over 65-85 mmHg; autoregulatory index (ARI) of 0.66 +/- 0.11. Angiotensin II (100 pM) extended this range (to 65-120 mmHg) and enhanced efficiency (ARI 0.21 +/- 0.02, P < 0.05). Angiotensin II facilitation was antagonized by methacholine (ARI 0.76 +/- 0.08) and papaverine (ARI 0.91 +/- 0.13). Conclusion: The IPMK model is useful for studying renal physiology and pathophysiology without systemic neurohormonal influences.

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In this work we investigate the energy gap between the ground state and the first excited state in a model of two single-mode Bose-Einstein condensates coupled via Josephson tunnelling. The ene:rgy gap is never zero when the tunnelling interaction is non-zero. The gap exhibits no local minimum below a threshold coupling which separates a delocalized phase from a self-trapping phase that occurs in the absence of the external potential. Above this threshold point one minimum occurs close to the Josephson regime, and a set of minima and maxima appear in the Fock regime. Expressions for the position of these minima and maxima are obtained. The connection between these minima and maxima and the dynamics for the expectation value of the relative number of particles is analysed in detail. We find that the dynamics of the system changes as the coupling crosses these points.

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A calibration methodology based on an efficient and stable mathematical regularization scheme is described. This scheme is a variant of so-called Tikhonov regularization in which the parameter estimation process is formulated as a constrained minimization problem. Use of the methodology eliminates the need for a modeler to formulate a parsimonious inverse problem in which a handful of parameters are designated for estimation prior to initiating the calibration process. Instead, the level of parameter parsimony required to achieve a stable solution to the inverse problem is determined by the inversion algorithm itself. Where parameters, or combinations of parameters, cannot be uniquely estimated, they are provided with values, or assigned relationships with other parameters, that are decreed to be realistic by the modeler. Conversely, where the information content of a calibration dataset is sufficient to allow estimates to be made of the values of many parameters, the making of such estimates is not precluded by preemptive parsimonizing ahead of the calibration process. White Tikhonov schemes are very attractive and hence widely used, problems with numerical stability can sometimes arise because the strength with which regularization constraints are applied throughout the regularized inversion process cannot be guaranteed to exactly complement inadequacies in the information content of a given calibration dataset. A new technique overcomes this problem by allowing relative regularization weights to be estimated as parameters through the calibration process itself. The technique is applied to the simultaneous calibration of five subwatershed models, and it is demonstrated that the new scheme results in a more efficient inversion, and better enforcement of regularization constraints than traditional Tikhonov regularization methodologies. Moreover, it is argued that a joint calibration exercise of this type results in a more meaningful set of parameters than can be achieved by individual subwatershed model calibration. (c) 2005 Elsevier B.V. All rights reserved.