23 resultados para ISA implementation


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In population pharmacokinetic studies, the precision of parameter estimates is dependent on the population design. Methods based on the Fisher information matrix have been developed and extended to population studies to evaluate and optimize designs. In this paper we propose simple programming tools to evaluate population pharmacokinetic designs. This involved the development of an expression for the Fisher information matrix for nonlinear mixed-effects models, including estimation of the variance of the residual error. We implemented this expression as a generic function for two software applications: S-PLUS and MATLAB. The evaluation of population designs based on two pharmacokinetic examples from the literature is shown to illustrate the efficiency and the simplicity of this theoretic approach. Although no optimization method of the design is provided, these functions can be used to select and compare population designs among a large set of possible designs, avoiding a lot of simulations.

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Telemedicine is often proposed as a solution to certain health-care problems in the developing world. There seems to be little published experience on which to make judgements. A literature search revealed 39 articles, of which only two related to any kind of direct clinical work; most of them were review articles or editorials. The majority of the work reported was educational in nature, and there has been little clinical experience. It seems probable that telemedicine can help with the education of health-care workers and patients; it seems likely that it could bring major benefits to the organization of health-care. Without proper trials, it will be impossible to determine the place of health-care in the developing world. Trials are the only way in which rational decisions can ultimately be reached regarding whether scarce resources should be devoted to telemedicine in developing countries, or whether they should be employed in more conventional health-care measures whose outcomes are known to be cost-effective.

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The ventilation and cooling of deep, hot mines present particular problems in Australia as a consequence of the surface climate, the size of the underground voids, the degree of mechanization and the cost of power in remote areas. A preliminary investigation of the effects of controlled partial recirculation of air was conducted in Mount Isa Mines' Deep Copper section. Gas and dust concentrations were measured in the exhaust air of the major working section to assess the potential for recirculating exhaust air to the intake airways to reduce the cost of providing an acceptable working environment in the deep parts of the mine. Studies were undertaken of airborne dust deposition in vertical airways and the efficiency of usage of the ventilation air in diluting contaminants. It was established that 45% of the respirable dust was deposited in a 130-m vertical raise and 60% of the air supplied to the section could be reused or recirculated. The first major field trial of a controlled partial recirculation system in Australia was undertaken in the light of these results and demonstrated excellent potential for significant reduction in ventilation costs. Gas and dust contaminant levels were well below the threshold limit values during the trial. It is concluded that controlled partial recirculation can be a practical, effective and safe aid to normal ventilation practice in Australian deep, hot mines.

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We present an efficient and robust method for calculating state-to-state reaction probabilities utilising the Lanczos algorithm for a real symmetric Hamiltonian. The method recasts the time-independent Artificial Boundary Inhomogeneity technique recently introduced by Jang and Light (J. Chem. Phys. 102 (1995) 3262) into a tridiagonal (Lanczos) representation. The calculation proceeds at the cost of a single Lanczos propagation for each boundary inhomogeneity function and yields all state-to-state probabilities (elastic, inelastic and reactive) over an arbitrary energy range. The method is applied to the collinear H + H-2 reaction and the results demonstrate it is accurate and efficient in comparison with previous calculations. (C) 2002 Elsevier Science B.V. All rights reserved.

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Stochastic differential equations (SDEs) arise from physical systems where the parameters describing the system can only be estimated or are subject to noise. Much work has been done recently on developing higher order Runge-Kutta methods for solving SDEs numerically. Fixed stepsize implementations of numerical methods have limitations when, for example, the SDE being solved is stiff as this forces the stepsize to be very small. This paper presents a completely general variable stepsize implementation of an embedded Runge Kutta pair for solving SDEs numerically; in this implementation, there is no restriction on the value used for the stepsize, and it is demonstrated that the integration remains on the correct Brownian path.