996 resultados para Fluid models


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Epstein–Barr virus (EBV) encephalitis has been reported rarely in the context of solid-organ and bone-marrow transplantation [1]. We report a case of a renal transplant recipient who developed EBV encephalitis following OKT3 therapy for acute allograft rejection. The diagnosis was expedited by the detection of EBV DNA in the cerebrospinal fluid (CSF) by nested polymerase chain reaction (PCR). Moreover, clinical recovery and clearance of CSF EBV DNA appeared to follow the institution of parenteral ganciclovir treatment.

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Background Icodextrin is a high molecular weight, starch-derived glucose polymer, which is capable of inducing sustained ultrafiltration over prolonged (12–16 hour) peritoneal dialysis (PD) dwells. The aim of this study was to evaluate the ability of icodextrin to alleviate refractory, symptomatic fluid overload and prolong technique survival in PD patients. Methods A prospective, open-label, pre-test/post-test study was conducted in 17 PD patients (8 females/9 males, mean age 56.8 ± 2.9 years) who were on the verge of being transferred to haemodialysis because of symptomatic fluid retention that was refractory to fluid restriction, loop diuretic therapy, hypertonic glucose exchanges and dwell time optimisation. One icodextrin exchange (2.5 L 7.5%, 12-hour dwell) was substituted for a long-dwell glucose exchange each day. Results Icodextrin significantly increased peritoneal ultrafiltration (885 ± 210 ml to 1454 ± 215 ml, p < 0.05) and reduced mean arterial pressure (106 ± 4 to 96 ± 4 mmHg, p < 0.05), but did not affect weight, plasma albumin concentration, haemoglobin levels or dialysate:plasma creatinine ratio. Diabetic patients (n = 12) also experienced improved glycaemic control (haemoglobin Alc decreased from 8.9 ± 0.7% to 7.9 ± 0.7%, p < 0.05). Overall PD technique survival was prolonged by a mean of 11.6 months (95% CI 6.0–17.3 months). On multivariate Cox proportional hazards analysis, extension of technique survival by icodextrin was only significantly predicted by baseline net daily peritoneal ultrafiltration (adjusted HR 2.52, 95% CI 1.13–5.62, p < 0.05). Conclusions Icodextrin significantly improved peritoneal ultrafiltration and extended technique survival in PD patients with symptomatic fluid overload, especially those who had substantially impaired peritoneal ultrafiltration.

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In this paper, we look at three models (mixture, competing risk and multiplicative) involving two inverse Weibull distributions. We study the shapes of the density and failure-rate functions and discuss graphical methods to determine if a given data set can be modelled by one of these models. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Purpose: This study was designed to investigate the immediate effect of exercise intensity and duration on body fluid volumes in rats throughout a 3-wk exercise program. Methods: Changes in the extracellular water (ECW) and total body water (TBW) volumes of rats were measured preexercise and postexercise using multiple frequency bioelectrical impedance analysis. Groups of rats were exercised at two intensities (6 m.min(-1) and 12 m.min(-1)) for two exercise times (60 min and 90 min) 5 d.wk(-1) during a 3-wk period. Changes in plasma electrolytes, glucose, and lactate resulting from the exercise were also measured on 3 d of each week. Results: Each group of animals showed significant losses in ECW and TBW as a direct result of daily exercise. The magnitude of fluid loss was directly related to the intensity of the exercise, bur not to exercise duration; although the magnitude of daily fluid loss at the higher intensity exercise (12 m.min(-1)) decreased as the study progressed, possibly indicating a training effect. Conclusion: At low-intensity exercise, there is a small bur significant loss in both TBW and ECW fluids, and the magnitude of these losses does not change throughout a 3-wk exercise program. At moderate levels of exercise intensity, there is a greater loss of both TBW and ECW fluids. However, the magnitudes of these losses decrease significantly during the 3-wk exercise program, thus demonstrating a training effect.

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We solve the Sp(N) Heisenberg and SU(N) Hubbard-Heisenberg models on the anisotropic triangular lattice in the large-N limit. These two models may describe respectively the magnetic and electronic properties of the family of layered organic materials K-(BEDT-TTF)(2)X, The Heisenberg model is also relevant to the frustrated antiferromagnet, Cs2CuCl4. We find rich phase diagrams for each model. The Sp(N) :antiferromagnet is shown to have five different phases as a function of the size of the spin and the degree of anisotropy of the triangular lattice. The effects of fluctuations at finite N are also discussed. For parameters relevant to Cs2CuCl4 the ground state either exhibits incommensurate spin order, or is in a quantum disordered phase with deconfined spin-1/2 excitations and topological order. The SU(N) Hubbard-Heisenberg model exhibits an insulating dimer phase, an insulating box phase, a semi-metallic staggered flux phase (SFP), and a metallic uniform phase. The uniform and SFP phases exhibit a pseudogap, A metal-insulator transition occurs at intermediate values of the interaction strength.

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Activated sludge models are used extensively in the study of wastewater treatment processes. While various commercial implementations of these models are available, there are many people who need to code models themselves using the simulation packages available to them, Quality assurance of such models is difficult. While benchmarking problems have been developed and are available, the comparison of simulation data with that of commercial models leads only to the detection, not the isolation of errors. To identify the errors in the code is time-consuming. In this paper, we address the problem by developing a systematic and largely automated approach to the isolation of coding errors. There are three steps: firstly, possible errors are classified according to their place in the model structure and a feature matrix is established for each class of errors. Secondly, an observer is designed to generate residuals, such that each class of errors imposes a subspace, spanned by its feature matrix, on the residuals. Finally. localising the residuals in a subspace isolates coding errors. The algorithm proved capable of rapidly and reliably isolating a variety of single and simultaneous errors in a case study using the ASM 1 activated sludge model. In this paper a newly coded model was verified against a known implementation. The method is also applicable to simultaneous verification of any two independent implementations, hence is useful in commercial model development.

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Despite their limitations, linear filter models continue to be used to simulate the receptive field properties of cortical simple cells. For theoreticians interested in large scale models of visual cortex, a family of self-similar filters represents a convenient way in which to characterise simple cells in one basic model. This paper reviews research on the suitability of such models, and goes on to advance biologically motivated reasons for adopting a particular group of models in preference to all others. In particular, the paper describes why the Gabor model, so often used in network simulations, should be dropped in favour of a Cauchy model, both on the grounds of frequency response and mutual filter orthogonality.

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This article modifies the usual form of the Dubinin-Radushkevich pore-filling model for application to liquid-phase adsorption data, where large molecules are often involved. In such cases it is necessary to include the repulsive part of the energy in the micropores, which is accomplished here by relating the pore potential to the fluid-solid interaction potential. The model also considers the nonideality of the bulk liquid phase through the UNIFAC activity coefficient model, as well as structural heterogeneity of the carbon. For the latter the generalized adsorption integral is used while incorporating the pore-size distribution obtained by density functional theory analysis of argon adsorption data. The model is applied here to the interpretation of aqueous phase adsorption isotherms of three different esters on three commercial activated carbons. Excellent agreement between the model and experimental data is observed, and the fitted Lennard-Jones size parameter for the adsorbate-adsorbate interactions compares well with that estimated from known critical properties, supporting the modified approach. On the other hand, the model without consideration of bulk nonideality, or when using classical models of the characteristic energy, gives much poorer bts of the data and unrealistic parameter values.

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Five kinetic models for adsorption of hydrocarbons on activated carbon are compared and investigated in this study. These models assume different mass transfer mechanisms within the porous carbon particle. They are: (a) dual pore and surface diffusion (MSD), (b) macropore, surface, and micropore diffusion (MSMD), (c) macropore, surface and finite mass exchange (FK), (d) finite mass exchange (LK), and (e) macropore, micropore diffusion (BM) models. These models are discriminated using the single component kinetic data of ethane and propane as well as the multicomponent kinetics data of their binary mixtures measured on two commercial activated carbon samples (Ajax and Norit) under various conditions. The adsorption energetic heterogeneity is considered for all models to account for the system. It is found that, in general, the models assuming diffusion flux of adsorbed phase along the particle scale give better description of the kinetic data.

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Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.