99 resultados para iterative methods


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This article describes a new test method for the assessment of the severity of environmental stress cracking of biomedical polyurethanes in a manner that minimizes the degree of subjectivity involved. The effect of applied strain and acetone pre-treatment on degradation of Pellethane 2363 80A and Pellethane 2363 55D polyurethanes under in vitro and in vivo conditions is studied. The results are presented using a magnification-weighted image rating system that allows the semi-quantitative rating of degradation based on distribution and severity of surface damage. Devices for applying controlled strain to both flat sheet and tubing samples are described. The new rating system consistently discriminated between. the effects of acetone pre-treatments, strain and exposure times in both in vitro and in vivo experiments. As expected, P80A underwent considerable stress cracking compared with P55D. P80A produced similar stress crack ratings in both in vivo and in vitro experiments, however P55D performed worse under in vitro conditions compared with in vivo. This result indicated that care must be taken when interpreting in vitro results in the absence of in vivo data. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Sympatric individuals of Rattus fuscipes and Rattus leucopus, two Australian native rats from the tropical wet forests of north Queensland, are difficult to distinguish morphologically and are often confused in the field. When we started a study on fine-scale movements of these species, using microsatellite markers, we found that the species as identified in the field did not form coherent genetic groups. In this study, we examined the potential of an iterative process of genetic assignment to separate specimens from distinct (e.g. species, populations) natural groups. Five loci with extensive overlap in allele distributions between species were used for the iterative process. Samples were randomly distributed into two starting groups of equal size and then subjected to the test. At each iteration, misassigned samples switched groups, and the output groups from a given round of assignment formed the input groups for the next round. All samples were assigned correctly on the 10th iteration, in which two genetic groups were clearly separated. Mitochondrial DNA sequences were obtained from samples from each genetic group identified by assignment, together with those of museum voucher specimens, to assess which species corresponded to which genetic group. The iterative procedure was also used to resolve groups within species, adequately separating the genetically identified R. leucopus from our two sampling sites. These results show that the iterative assignment process can correctly differentiate samples into their appropriate natural groups when diagnostic genetic markers are not available, which allowed us to resolve accurately the two R. leucopus and R. fuscipes species. Our approach provides an analytical tool that may be applicable to a broad variety of situations where genetic groups need to be resolved.

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Qualitative data analysis (QDA) is often a time-consuming and laborious process usually involving the management of large quantities of textual data. Recently developed computer programs offer great advances in the efficiency of the processes of QDA. In this paper we report on an innovative use of a combination of extant computer software technologies to further enhance and simplify QDA. Used in appropriate circumstances, we believe that this innovation greatly enhances the speed with which theoretical and descriptive ideas can be abstracted from rich, complex, and chaotic qualitative data. © 2001 Human Sciences Press, Inc.

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Low-micromolar concentrations of sulfite, thiosulfate and sulfide, present in synthetic wastewater or anaerobic digester effluent, were quantified by means of derivatization with monobromobimane, followed by HPLC separation with fluorescence detection. The concentration of elemental sulfur was determined, after its extraction with chloroform from the derivatized sample, by HPLC with UV detection. Recoveries of sulfide (both matrices), and of thiosulfate and sulfite (synthetic wastewater) were between 98 and 103%. The in-run RSDs on separate derivatizations were 13 and 19% for sulfite (two tests), between 1.5 and 6.6% for thiosulfate (two tests) and between 4.1 and 7.7% for sulfide (three tests). Response factors for derivatives of sulfide and thiosulfate, but not sulfite, were steady over a 13-month period during which 730 samples were analysed. Dithionate and tetrathionate did not seem to be detectable with this method. The distinctness of the elemental sulfur and the derivatizing-agent peaks was improved considerably by detecting elution at 297 instead of 263 nm. (C) 2002 Elsevier Science B.V. All rights reserved.

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Application of novel analytical and investigative methods such as fluorescence in situ hybridization, confocal laser scanning microscopy (CLSM), microelectrodes and advanced numerical simulation has led to new insights into micro-and macroscopic processes in bioreactors. However, the question is still open whether or not these new findings and the subsequent gain of knowledge are of significant practical relevance and if so, where and how. To find suitable answers it is necessary for engineers to know what can be expected by applying these modern analytical tools. Similarly, scientists could benefit significantly from an intensive dialogue with engineers in order to find out about practical problems and conditions existing in wastewater treatment systems. In this paper, an attempt is made to help bridge the gap between science and engineering in biological wastewater treatment. We provide an overview of recently developed methods in microbiology and in mathematical modeling and numerical simulation. A questionnaire is presented which may help generate a platform from which further technical and scientific developments can be accomplished. Both the paper and the questionnaire are aimed at encouraging scientists and engineers to enter into an intensive, mutually beneficial dialogue. (C) 2002 Elsevier Science Ltd. All rights reserved.

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The problem of designing spatially cohesive nature reserve systems that meet biodiversity objectives is formulated as a nonlinear integer programming problem. The multiobjective function minimises a combination of boundary length, area and failed representation of the biological attributes we are trying to conserve. The task is to reserve a subset of sites that best meet this objective. We use data on the distribution of habitats in the Northern Territory, Australia, to show how simulated annealing and a greedy heuristic algorithm can be used to generate good solutions to such large reserve design problems, and to compare the effectiveness of these methods.

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Control of chaotic instability in a rotating multibody system in the form of a dual-spin spacecraft with an axial nutational damper is achieved using an algorithm derived using energy methods. The control method is implemented on two realistic spacecraft parameter configurations which have been found to exhibit chaotic instability when a sinusoidally varying torque is applied to the spacecraft for a range of forcing amplitudes and frequencies. Such a torque, in practice, may arise under malfunction of the control system or from an unbalanced rotor. Chaotic instabilities arising from these torques could introduce uncertainties and irregularities into a spacecraft's attitude and consequently impair pointing accuracy. The control method is formulated from nutational stability results derived using an energy sink approximation for a dual-spin spacecraft with an asymmetric platform and axisymmetric rotor. The effectiveness of the control method is shown numerically and the results are studied by means of time history, phase space, Poincare map, Lyapunov characteristic exponents and Bifurcation diagrams.

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Improvements to peroxide oxidation methods for analysing acid sulfate soils (ASS) are introduced. The soil solution ratio has been increased to 1 : 40, titrations are performed in suspension, and the duration of the peroxide digest stage is substantially shortened. For 9 acid sulfate soils, the peroxide oxidisable sulfur value obtained using the improved method was compared with the reduced inorganic sulfur result obtained using the chromium reducible sulfur method. Their regression was highly significant, the slope of the regression line was not significantly different (P = 0.05) from unity, and the intercept not significantly different from zero. A complete sulfur budget for the improved method showed there was no loss of sulfur as has been reported for earlier peroxide oxidation techniques. When soils were very finely ground, efficient oxidation of sulfides was achieved, despite the milder digestion conditions. Highly sulfidic and organic soils were shown to be the most difficult to analyse using either the improved method or the chromium method. No single analytical method can be universally applied to all ASS, rather a suite of methods is necessary for a thorough understanding of many ASS. The improved peroxide method, in combination with the chromium method and the 4 M HCl extraction, form a sound platform for informed decision making on the management of acid sulfate soils.

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In this paper we construct predictor-corrector (PC) methods based on the trivial predictor and stochastic implicit Runge-Kutta (RK) correctors for solving stochastic differential equations. Using the colored rooted tree theory and stochastic B-series, the order condition theorem is derived for constructing stochastic RK methods based on PC implementations. We also present detailed order conditions of the PC methods using stochastic implicit RK correctors with strong global order 1.0 and 1.5. A two-stage implicit RK method with strong global order 1.0 and a four-stage implicit RK method with strong global order 1.5 used as the correctors are constructed in this paper. The mean-square stability properties and numerical results of the PC methods based on these two implicit RK correctors are reported.

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This paper presents results on the simulation of the solid state sintering of copper wires using Monte Carlo techniques based on elements of lattice theory and cellular automata. The initial structure is superimposed onto a triangular, two-dimensional lattice, where each lattice site corresponds to either an atom or vacancy. The number of vacancies varies with the simulation temperature, while a cluster of vacancies is a pore. To simulate sintering, lattice sites are picked at random and reoriented in terms of an atomistic model governing mass transport. The probability that an atom has sufficient energy to jump to a vacant lattice site is related to the jump frequency, and hence the diffusion coefficient, while the probability that an atomic jump will be accepted is related to the change in energy of the system as a result of the jump, as determined by the change in the number of nearest neighbours. The jump frequency is also used to relate model time, measured in Monte Carlo Steps, to the actual sintering time. The model incorporates bulk, grain boundary and surface diffusion terms and includes vacancy annihilation on the grain boundaries. The predictions of the model were found to be consistent with experimental data, both in terms of the microstructural evolution and in terms of the sintering time. (C) 2002 Elsevier Science B.V. All rights reserved.