34 resultados para alternative modeling approaches

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Catalytic systems for the direct production of hydrogen peroxide from hydrogen and oxygen are investigated, and the factors which make a successful process identified. The use of low metal loadings, an organic co-solvent (such as ethanol) and reduced palladium as the catalytic metal all lead to good activity and selectivity. (C) 2002 Elsevier Science B.V. All rights reserved.

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Despite tremendous successes of GPCR crystallography, the receptors with available structures represent only a small fraction of human GPCRs. An important role of the modeling community is to maximize structural insights for the remaining receptors and complexes. The community-wide GPCR Dock assessment was established to stimulate and monitor the progress in molecular modeling and ligand docking for GPCRs. The four targets in the present third assessment round presented new and diverse challenges for modelers, including prediction of allosteric ligand interaction and activation states in 5-hydroxytryptamine receptors 1B and 2B, and modeling by extremely distant homology for smoothened receptor. Forty-four modeling groups participated in the assessment. State-of-the-art modeling approaches achieved close-to-experimental accuracy for small rigid orthosteric ligands and models built by close homology, and they correctly predicted protein fold for distant homology targets. Predictions of long loops and GPCR activation states remain unsolved problems.

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With field, laboratory, and modeling approaches, we examined the interplay among habitat structure, intraguild predation (IGP), and parasitism in an ongoing species invasion. Native Gammarus duebeni celticus (Crustacea: Amphipoda) are often, but not always, replaced by the invader Gammarus pulex through differential IGP. The muscle-wasting microsporidian parasite Pleistophora mulleri infects the native but not the invader. We found a highly variable prevalence of P. mulleri in uninvaded rivers, with 0–91% of hosts parasitized per sample. In addition, unparasitized natives dominated fast-flowing riffle patches of river, whereas parasitized individuals dominated slower- flowing, pooled patches. We examined the survivorship of invader and native in single and mixed-species microcosms with high, intermediate, and zero parasite prevalence. G. pulex survivorship was high in all treatments, whereas G. duebeni subsp. celticus survivorship was significantly lower in the presence of the invader. Further, parasitized G. duebeni subsp. celticus experienced near-total elimination. Models of the species replacement process implied that parasite-enhanced IGP would make invasion by G. pulex more likely, regardless of habitat and parasite spatial structure. However, where heterogeneity in parasite prevalence creates a landscape of patches with different susceptibilities to invasion, G. pulex may succeed in cases where invasion would not be possible if patches were equivalent. The different responses of parasitized and unparasitized G. duebeni subsp. celticus to environmental heterogeneity potentially link landscape patterns to the success or failure of the invasion process.

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Recent thinking on open innovation and the knowledge-based economy have stressed the importance of external knowledge sources in stimulating innovation. Policy-makers have recognised this, establishing publicly funded Centres of R&D Excellence with the objective of stimulating industry–science links and localised innovation spillovers. Here, we examine the contrasting IP management practices of a group of 18 university- and company-based R&D centres supported by the same regional programme. Our analysis covers all but one of the Centres supported by the programme and suggests marked contrasts between the IP strategies of the university-based and company-based centres. This suggests the potential for very different types of knowledge spillovers from publicly funded R&D centres based in different types of organisations, and a range of alternative policy approaches to the future funding of R&D centres depending on policy-makers’ objectives.

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In collaboration with Airbus-UK, the dimensional growth of aircraft panels while being riveted with stiffeners is investigated. Small panels are used in this investigation. The stiffeners have been fastened to the panels with rivets and it has been observed that during this operation the panels expand in the longitudinal and transverse directions. It has been observed that the growth is variable and the challenge is to control the riveting process to minimize this variability. In this investigation, the assembly of the small panels and longitudinal stiffeners has been simulated using static stress and nonlinear explicit finite element models. The models have been validated against a limited set of experimental measurements; it was found that more accurate predictions of the riveting process are achieved using explicit finite element models. Yet, the static stress finite element model is more time efficient, and more practical to simulate hundreds of rivets and the stochastic nature of the process. Furthermore, through a series of numerical simulations and probabilistic analyses, the manufacturing process control parameters that influence panel growth have been identified. Alternative fastening approaches were examined and it was found that dimensional growth can be controlled by changing the design of the dies used for forming the rivets.

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Transformative consumer researchers seek to enhance consumer well-being by tackling some of the more difficult and intractable social problems and getting the results into the hands of stakeholders who can apply the research findings. Although traditional research approaches offer a viable path for doing research seeking positive social change, alternative research approaches exist that are uniquely suited to the challenges of Transformative Consumer Research. This article examines the standard research process from the perspective of a transformative research agenda to highlight steps in the process that can be better adapted and suggests innovations inspired from other translational research programs.

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This paper addresses the problem of optimally locating intermodal freight terminals in Serbia. To solve this problem and determine the effects of the resulting scenarios, two modeling approaches were combined. The first approach is based on multiple-assignment hub-network design, and the second is based on simulation. The multiple-assignment p-hub network location model was used to determine the optimal location of intermodal terminals. Simulation was used as a tool to estimate intermodal transport flow volumes, due to the unreliability and unavailability of specific statistical data, and as a method for quantitatively analyzing the economic, time, and environmental effects of different scenarios of intermodal terminal development. The results presented here represent a summary, with some extension, of the research realized in the IMOD-X project (Intermodal Solutions for Competitive Transport in Serbia).

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From a review of technical literature, it was not apparent if the Lagrangian or the Eulerian dispersed phase modeling approach was more valid to simulate dilute erosive slurry flow. In this study, both modeling approaches were employed and a comparative analysis of performances and accuracy between the two models was carried out. Due to an impossibility to define, for the Eulerian model already implemented in FLUENT, a set of boundary conditions consistent with the Lagrangian impulsive equations, an Eulerian dispersed phase model was integrated in the FLUENT code using subroutines and user-defined scalar equations. Numerical predictions obtained from the two different approaches for two-phase flow in a sudden expansion were compared with the measured data. Excellent agreement was attained between the predicted and observed fluid and particle velocity in the axial direction and for the kinetic energy. Erosion profiles in a sudden expansion computed using the Lagrangian scheme yielded good qualitative agreement with measured data and predicted a maximum impact angle of 29 deg at the fluid reattachment point. The Eulerian model was adversely affected by the reattachment of the fluid phase to the wall and the simulated erosion profiles were not in agreement with the Lagrangian or measured data. Furthermore, the Eulerian model under-predicted the Lagrangian impact angle at all locations except the reattachment point. © 2010 American Society of Mechanical Engineers.

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In recent years, the issue of life expectancy has become of upmost importance to pension providers, insurance companies and the government bodies in the developed world. Significant and consistent improvements in mortality rates and, hence, life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data in order to anticipate future life expectancy and, hence, quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age and cohort, and forecast these trends into the future using standard statistical methods. The modeling approaches used failed to capture the effects of any structural change in the trend and, thus, potentially produced incorrect forecasts of future mortality rates. In this paper, we look at a range of leading stochastic models of mortality and test for structural breaks in the trend time series.

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In collaboration with Airbus-UK, the dimensional growth of small panels while being riveted with stiffeners is investigated. The stiffeners have been fastened to the panels with rivets and it has been observed that during this operation the panels expand in the longitudinal and transverse directions. It has been observed that the growth is variable and the challenge is to control the riveting process to minimize this variability. In this investigation, the assembly of the small panels and longitudinal stiffeners has been simulated using low and high fidelity nonlinear finite element models. The models have been validated against a limited set of experimental measurements; it was found that more accurate predictions of the riveting process are achieved using high fidelity explicit finite element models. Furthermore, through a series of numerical simulations and probabilistic analyses, the manufacturing process control parameters that influence panel growth have been identified. Alternative fastening approaches were examined and it was found that dimensional growth can be controlled by changing the design of the dies used for forming the rivets.

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Research over the past two decades on the Holocene sediments from the tide dominated west side of the lower Ganges delta has focussed on constraining the sedimentary environment through grain size distributions (GSD). GSD has traditionally been assessed through the use of probability density function (PDF) methods (e.g. log-normal, log skew-Laplace functions), but these approaches do not acknowledge the compositional nature of the data, which may compromise outcomes in lithofacies interpretations. The use of PDF approaches in GSD analysis poses a series of challenges for the development of lithofacies models, such as equifinal distribution coefficients and obscuring the empirical data variability. In this study a methodological framework for characterising GSD is presented through compositional data analysis (CODA) plus a multivariate statistical framework. This provides a statistically robust analysis of the fine tidal estuary sediments from the West Bengal Sundarbans, relative to alternative PDF approaches.

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Bovine Respiratory Disease (BRD) is considered to be one of the most significant causes of economic loss in cattle worldwide. The disease has multifactorial aetiology, where viral induced respiratory damage can predispose animals to developing secondary bacterial infections. Accurate identification of viral infected animals prior to the onset of bacterial infection is necessary to reduce the overuse of antimicrobial treatments and minimize further economic losses from reduced production capacity and death. This research focuses on Bovine Parainfluenza Virus Type 3 (BPIV-3), one of the viruses involved in generating BRD. Vaccination measures for BPIV-3 can induce a level of immunity preventing disease progression, however, not all animals respond equally and immunization can complicate disease diagnosis. Alternative diagnostic approaches are required to identify animals which fail to respond to vaccination during infection outbreaks and are therefore likely to be more susceptible to secondary bacterial infections. Mass spectrometry based metabolomics was employed to identify plasma markers capable of differentiating between vaccinated and non-vaccinated calves after challenge with BPIV-3. Differentiation of vaccinated and non-vaccinated study groups (n=6) was possible as early as day 2 post-BPIV-3 challenge up until day 20 using a panel of potential metabolite markers. This study illustrates the potential for metabolomics to provide more detailed information on animal vaccination status that could be used to develop tools for improved herd health management, reduce economic loss through rapid identification and isolation of animals without immune protection (improving herd level immunity) and help reduce the usage of antimicrobial therapeutic treatments in animals.

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Microbial communities are enigmatically diverse. We propose a novel view of processes likely affecting microbial assemblages, which could be viewed as the Great American Interchange en miniature: the wholesale exchange among microbial communities resulting from moving pieces of the environment containing entire assemblages. Incidental evidence for such ‘community coalescence’ is accumulating, but such processes are rarely studied, likely because of the absence of suitable terminology or a conceptual framework. We provide the nucleus for such a conceptual foundation for the study of community coalescence, examining factors shaping these events, links to bodies of ecological theory, and we suggest modeling approaches for understanding coalescent communities. We argue for the systematic study of community coalescence because of important functional and applied consequences.

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Aggression occurs when individuals compete over limiting resources. While theoretical studies have long placed a strong emphasis on context-specificity of aggression, there is increasing recognition that consistent behavioural differences exist among individuals, and that aggressiveness may be an important component of individual personality. Though empirical studies tend to focus on one aspect or the other, we suggest there is merit in modelling both within- and among-individual variation in agonistic behaviour simultaneously. Here, we demonstrate how this can be achieved using multivariate linear mixed effect models. Using data from repeated mirror trials and dyadic interactions of male green swordtails, Xiphophorus helleri, we show repeatable components of (co)variation in a suite of agonistic behaviour that is broadly consistent with a major axis of variation in aggressiveness. We also show that observed focal behaviour is dependent on opponent effects, which can themselves be repeatable but were more generally found to be context specific. In particular, our models show that within-individual variation in agonistic behaviour is explained, at least in part, by the relative size of a live opponent as predicted by contest theory. Finally, we suggest several additional applications of the multivariate models demonstrated here. These include testing the recently queried functional equivalence of alternative experimental approaches, (e.g., mirror trials, dyadic interaction tests) for assaying individual aggressiveness. © 2011 Wilson et al.