Automatic construction of explicit R matrices for the one-parameter families of irreducible typical highest weight (0(m)vertical bar alpha(n)) representations of U-q[gl(m vertical bar n)]

We detail the automatic construction of R matrices corresponding to (the tensor products of) the (O-m\alpha(n)) families of highest-weight representations of the quantum superalgebras Uq[gl(m\n)]. These representations are irreducible, contain a free complex parameter a, and are 2(mn)-dimensional. Our R matrices are actually (sparse) rank 4 tensors, containing a total of 2(4mn) components, each of which is in general an algebraic expression in the two complex variables q and a. Although the constructions are straightforward, we describe them in full here, to fill a perceived gap in the literature. As the algorithms are generally impracticable for manual calculation, we have implemented the entire process in MATHEMATICA; illustrating our results with U-q [gl(3\1)]. (C) 2002 Published by Elsevier Science B.V.

Effect of Co addition on the lattice parameter, electrical conductivity and sintering of gadolinia-doped ceria

Co-sintering aid has been added to Ce1.9Gd0.1O1.95 (CGO) by treating a commercial powder with Co(NO3)(2) (COCGO), X-ray diffraction (XRD) measurements of lattice parameter indicated that the Co was located on the CGO particle surface after calcination at 650 degreesC. After heat treatment at temperatures above 650 degreesC, the room temperature lattice parameter of CGO was found to increase, indicating redistribution of the Gd. Compared to CGO, the lattice parameter of CGO + 2 cation% Co (2CoCGO) was lower for a given temperature (650-1100 degreesC), A.C. impedance revealed that the lattice conductivity of 2CoCGO was enhanced when densified at lower temperatures, Transmission electron microscopy (TEM) showed that, even after sintering for 4 h at 980 degreesC, most of the Co was located at grain boundaries. (C) 2002 Published by Elsevier Science B.V.

Fast, scalable master equation solution algorithms. IV. Lanczos iteration with diffusion approximation preconditioned iterative inversion

In this paper we propose a second linearly scalable method for solving large master equations arising in the context of gas-phase reactive systems. The new method is based on the well-known shift-invert Lanczos iteration using the GMRES iteration preconditioned using the diffusion approximation to the master equation to provide the inverse of the master equation matrix. In this way we avoid the cubic scaling of traditional master equation solution methods while maintaining the speed of a partial spectral decomposition. The method is tested using a master equation modeling the formation of propargyl from the reaction of singlet methylene with acetylene, proceeding through long-lived isomerizing intermediates. (C) 2003 American Institute of Physics.

Link invariants associated with gauge equivalent solutions of the Yang-Baxter equation: The one-parameter family of minimal typical representations of Uq[gl(2|1)]

In this paper we investigate the construction of state models for link invariants using representations of the braid group obtained from various gauge choices for a solution of the trigonometric Yang-Baxter equation. Our results show that it is possible to obtain invariants of regular isotopy (as defined by Kauffman) which may not be ambient isotopic. We illustrate our results with explicit computations using solutions of the trigonometric Yang-Baxter equation associated with the one-parameter family of minimal typical representations of the quantum superalgebra U-q,[gl(2/1)]. We have implemented MATHEMATICA code to evaluate the invariants for all prime knots up to 10 crossings.

Quantitative justification for target concentration intervention - parameter variability and predictive performance using population pharmacokinetic models for aminoglycosides

Aims [1] To quantify the random and predictable components of variability for aminoglycoside clearance and volume of distribution [2] To investigate models for predicting aminoglycoside clearance in patients with low serum creatinine concentrations [3] To evaluate the predictive performance of initial dosing strategies for achieving an aminoglycoside target concentration. Methods Aminoglycoside demographic, dosing and concentration data were collected from 697 adult patients (>=20 years old) as part of standard clinical care using a target concentration intervention approach for dose individualization. It was assumed that aminoglycoside clearance had a renal and a nonrenal component, with the renal component being linearly related to predicted creatinine clearance. Results A two compartment pharmacokinetic model best described the aminoglycoside data. The addition of weight, age, sex and serum creatinine as covariates reduced the random component of between subject variability (BSVR) in clearance (CL) from 94% to 36% of population parameter variability (PPV). The final pharmacokinetic parameter estimates for the model with the best predictive performance were: CL, 4.7 l h(-1) 70 kg(-1); intercompartmental clearance (CLic), 1 l h(-1) 70 kg(-1); volume of central compartment (V-1), 19.5 l 70 kg(-1); volume of peripheral compartment (V-2) 11.2 l 70 kg(-1). Conclusions Using a fixed dose of aminoglycoside will achieve 35% of typical patients within 80-125% of a required dose. Covariate guided predictions increase this up to 61%. However, because we have shown that random within subject variability (WSVR) in clearance is less than safe and effective variability (SEV), target concentration intervention can potentially achieve safe and effective doses in 90% of patients.

The HIPASS catalogue - II. Completeness reliability and parameter accuracy

The H I Parkes All Sky Survey (HIPASS) is a blind extragalactic H I 21-cm emission-line survey covering the whole southern sky from declination -90degrees to +25degrees. The HIPASS catalogue (HICAT), containing 4315 H I-selected galaxies from the region south of declination +2degrees, is presented in Meyer et al. (Paper I). This paper describes in detail the completeness and reliability of HICAT, which are calculated from the recovery rate of synthetic sources and follow-up observations, respectively. HICAT is found to be 99 per cent complete at a peak flux of 84 mJy and an integrated flux of 9.4 Jy km. s(-1). The overall reliability is 95 per cent, but rises to 99 per cent for sources with peak fluxes >58 mJy or integrated flux >8.2 Jy km s(-1). Expressions are derived for the uncertainties on the most important HICAT parameters: peak flux, integrated flux, velocity width and recessional velocity. The errors on HICAT parameters are dominated by the noise in the HIPASS data, rather than by the parametrization procedure.

Comparison of the R-70 self-heating rate of New Zealand and Australian coals to Suggate rank parameter

Samples from New Zealand and Australia have been tested in an adiabatic oven to assess the effect of rank on the R-70 selfheating rate of coal. A non-linear relationship can be defined for coals from both countries using the revised Suggate rank (S-r) parameter. Subbituminous coals have the highest R-70 self-heating rate values, which are 20 times that of high volatile A bituminous coals on a dry mineral matter free basis (similar to 1 cf. 20 degrees C h(-1)). However, the moderating effects of moisture and mineral matter can reduce this difference to only 2-3 times for coal in-situ. (c) 2005 Elsevier B.V All rights reserved.

Population inversion of a driven two-level system in a structureless bath

We derive a master equation for a driven double quantum dot damped by an unstructured phonon bath, and calculate the spectral density. We find that bath-mediated photon absorption is important at relatively strong driving, and may even dominate the dynamics, inducing population inversion of the double-dot system. This phenomenon is consistent with recent experimental observations.

Unidirectional inversion of ibuprofen in Caco-2 cells: Developing a suitable model for presystemic chiral inversion study

Intestinal chiral inversion of ibuprofen is still lacking direct evidence. In a preliminary experiment, ibuprofen was found to undergo inversion in Caco-2 cells. This investigation was thus conducted to determine the characteristics and influence of some biochemical factors on the chiral inversion of ibuprofen in Caco-2 cells. The effects of substrate concentration (2.5-40 mu g/ml), cell density (0.5-2 x 10(6) cells/ well), content of serum (0-20%), coexistence of S ibuprofen (corresponding doses), sodium azide (10mm), exogenous Coenzyme A (CoA) (0.1 - 0.4 mm),. and palmitic acid (5-25 mu m) on inversion were examined. A stereoselective HPLC method based on the Chromasil-CHI-TBB column was developed for quantitative analysis of the drug in cell culture medium. The inversion ratio (F-i) and elimination rate constant were calculated as the indexes of inversion extent. Inversion of ibuprofen in Caeo-2 cells was found to be both dose and cell density dependent, indicating saturable characteristics. Addition of serum significantly inhibited the inversion, to an extent of 2.7 fold decrease at 20% content. Preexistence of S enantiomer exerted a significant inhibitory effect (p < 0.01 for all tests). Sodium azide decreased the inversion ratio from 0.43 to 0.32 (p < 0.01). Exogenous CoA and palmitic acid significantly promoted the inversion at all tested doses (p < 0.01 for all tests). This research provided strong evidence to the capacity and capability of intestinal chiral inversion. Although long incubation times up to 120 h were required, Caco-2 cells should be a suitable model for chiral inversion research of 2-APAs considering the human-resourced and well-defined characteristics from the present study.

Optimal design for model discrimination and parameter estimation for itraconazole population pharmacokinetics in cystic fibrosis patients

Optimal sampling times are found for a study in which one of the primary purposes is to develop a model of the pharmacokinetics of itraconazole in patients with cystic fibrosis for both capsule and solution doses. The optimal design is expected to produce reliable estimates of population parameters for two different structural PK models. Data collected at these sampling times are also expected to provide the researchers with sufficient information to reasonably discriminate between the two competing structural models.

Advances in distributed parameter approach to the dynamics and control of activated sludge processes for wastewater treatment

This paper presents a review of modelling and control of biological nutrient removal (BNR)-activated sludge processes for wastewater treatment using distributed parameter models described by partial differential equations (PDE). Numerical methods for solution to the BNR-activated sludge process dynamics are reviewed and these include method of lines, global orthogonal collocation and orthogonal collocation on finite elements. Fundamental techniques and conceptual advances of the distributed parameter approach to the dynamics and control of activated sludge processes are briefly described. A critical analysis on the advantages of the distributed parameter approach over the conventional modelling strategy in this paper shows that the activated sludge process is more adequately described by the former and the method is recommended for application to the wastewater industry (c) 2006 Elsevier Ltd. All rights reserved.

An advanced regularization methodology for use in watershed model calibration

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.

The cost of uniqueness in groundwater model calibration

Calibration of a groundwater model requires that hydraulic properties be estimated throughout a model domain. This generally constitutes an underdetermined inverse problem, for which a Solution can only be found when some kind of regularization device is included in the inversion process. Inclusion of regularization in the calibration process can be implicit, for example through the use of zones of constant parameter value, or explicit, for example through solution of a constrained minimization problem in which parameters are made to respect preferred values, or preferred relationships, to the degree necessary for a unique solution to be obtained. The cost of uniqueness is this: no matter which regularization methodology is employed, the inevitable consequence of its use is a loss of detail in the calibrated field. This, ill turn, can lead to erroneous predictions made by a model that is ostensibly well calibrated. Information made available as a by-product of the regularized inversion process allows the reasons for this loss of detail to be better understood. In particular, it is easily demonstrated that the estimated value for an hydraulic property at any point within a model domain is, in fact, a weighted average of the true hydraulic property over a much larger area. This averaging process causes loss of resolution in the estimated field. Where hydraulic conductivity is the hydraulic property being estimated, high averaging weights exist in areas that are strategically disposed with respect to measurement wells, while other areas may contribute very little to the estimated hydraulic conductivity at any point within the model domain, this possibly making the detection of hydraulic conductivity anomalies in these latter areas almost impossible. A study of the post-calibration parameter field covariance matrix allows further insights into the loss of system detail incurred through the calibration process to be gained. A comparison of pre- and post-calibration parameter covariance matrices shows that the latter often possess a much smaller spectral bandwidth than the former. It is also demonstrated that, as all inevitable consequence of the fact that a calibrated model cannot replicate every detail of the true system, model-to-measurement residuals can show a high degree of spatial correlation, a fact which must be taken into account when assessing these residuals either qualitatively, or quantitatively in the exploration of model predictive uncertainty. These principles are demonstrated using a synthetic case in which spatial parameter definition is based oil pilot points, and calibration is Implemented using both zones of piecewise constancy and constrained minimization regularization. (C) 2005 Elsevier Ltd. All rights reserved.