64 resultados para Hazard-Based Models


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This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters' responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers' behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture. (C) 2002 Elsevier Science Ltd. All rights reserved.

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Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.

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Antigen recognition by cytotoxic CD8 T cells is dependent upon a number of critical steps in MHC class I antigen processing including proteosomal cleavage, TAP transport into the endoplasmic reticulum, and MHC class 1 binding. Based on extensive experimental data relating to each of these steps there is now the capacity to model individual antigen processing steps with a high degree of accuracy. This paper demonstrates the potential to bring together models of individual antigen processing steps, for example proteosome cleavage, TAP transport, and MHC binding, to build highly informative models of functional pathways. In particular, we demonstrate how an artificial neural network model of TAP transport was used to mine a HLA-binding database so as to identify H LA-binding peptides transported by TAP. This integrated model of antigen processing provided the unique insight that HLA class I alleles apparently constitute two separate classes: those that are TAP-efficient for peptide loading (HLA-B27, -A3, and -A24) and those that are TAP-inefficient (HLA-A2, -B7, and -B8). Hence, using this integrated model we were able to generate novel hypotheses regarding antigen processing, and these hypotheses are now capable of being tested experimentally. This model confirms the feasibility of constructing a virtual immune system, whereby each additional step in antigen processing is incorporated into a single modular model. Accurate models of antigen processing have implications for the study of basic immunology as well as for the design of peptide-based vaccines and other immunotherapies. (C) 2004 Elsevier Inc. All rights reserved.

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This study evaluated whether projects conducted through the Access to Allied Health Services component of the Australian Better Outcomes in Mental Health Care initiative are improving access to evidence-based, non-pharmacological therapies for people with depression and anxiety. Synthesising data from the first 29 projects funded through the initiative, the study found that the models utilised in the projects have evolved over time. The projects have achieved a high level uptake; at a conservative estimate, 710 GPs and 160 allied health professionals (AHPs) have provided care to 3,476 consumers. The majority of these consumers have depression (77%) and/or anxiety disorders (55%); many are low income earners (57%); and a number have not previously accessed mental health care (40%). The projects have delivered 8,678 sessions of high quality care to these consumers, most commonly providing CBT-based cognitive and behavioural interventions (55% and 41%, respectively). In general, GPs, AHPs and consumers are sanguine about the projects, and have reported positive consumer outcomes. However, as with any new initiative, there are some practical and professional issues that need to be addressed. The projects are improving access to evidence-based, non-pharmacological therapies. The continuation and expansion of the initiative should be a priority.

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Few prospective data from the Asia Pacific region are available relating body mass index to the risk of diabetes. Our objective was to provide reliable age, sex and region specific estimates of the associations between body mass index and diabetes. Twenty-seven cohort studies from Asia, New Zealand and Australia, including 154,989 participants, contributed 1,244,793 person-years of follow-up. Outcome data included a combination of incidence of diabetes (based on blood glucose measurements) and fatal diabetes events. Hazard ratios were calculated from Cox models, stratified by sex and cohort, and adjusted for age at risk and smoking. During follow-up (mean = 8 years), 75 fatal diabetes events and 242 new cases of diabetes were documented. There were continuous positive associations between baseline body mass index and risk of diabetes with each 2 kg/m(2) lower body mass index associated with a 27% (23-30%) lower risk of diabetes. The associations were stronger in younger age groups, and regional comparisons demonstrated slightly stronger associations in Asian than in Australasian cohorts (P = 0.04). This overview provides evidence of a strong continuous association between body mass index and diabetes in the Asia Pacific region. The results indicate considerable potential for reduction in incidence of diabetes with population-wide lowering of body mass index in this region.

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An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

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The dynamic response of dry masonry columns can be approximated with finite-difference equations. Continuum models follow by replacing the difference quotients of the discrete model by corresponding differential expressions. The mathematically simplest of these models is a one-dimensional Cosserat theory. Within the presented homogenization context, the Cosserat theory is obtained by making ad hoc assumptions regarding the relative importance of certain terms in the differential expansions. The quality of approximation of the various theories is tested by comparison of the dispersion relations for bending waves with the dispersion relation of the discrete theory. All theories coincide with differences of less than 1% for wave-length-block-height (L/h) ratios bigger than 2 pi. The theory based on systematic differential approximation remains accurate up to L/h = 3 and then diverges rapidly. The Cosserat model becomes increasingly inaccurate for L/h < 2 pi. However, in contrast to the systematic approximation, the wave speed remains finite. In conclusion, considering its relative simplicity, the Cosserat model appears to be the natural starting point for the development of continuum models for blocky structures.

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Recent advances in computer technology have made it possible to create virtual plants by simulating the details of structural development of individual plants. Software has been developed that processes plant models expressed in a special purpose mini-language based on the Lindenmayer system formalism. These models can be extended from their architectural basis to capture plant physiology by integrating them with crop models, which estimate biomass production as a consequence of environmental inputs. Through this process, virtual plants will gain the ability to react to broad environmental conditions, while crop models will gain a visualisation component. This integration requires the resolution of the fundamentally different time scales underlying the approaches. Architectural models are usually based on physiological time; each time step encompasses the same amount of development in the plant, without regard to the passage of real time. In contrast, physiological models are based in real time; the amount of development in a time step is dependent on environmental conditions during the period. This paper provides a background on the plant modelling language, then describes how widely-used concepts of thermal time can be implemented to resolve these time scale differences. The process is illustrated using a case study. (C) 1997 Elsevier Science Ltd.

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Impulsivity based on Gray's [Gray, J. A. (1982) The neuropsychology of anxiety: an enquiry into the function of the septo-hippocampal system. New York: Oxford University Press: (1991). The neurophysiology of temperament. In J. Strelau & A. Angleitner. Explorations in temperament: international perspectives on theory and measurement. London. Plenum Press]. physiological model of personality was hypothesised to be more predictive of goal oriented criteria within the workplace than scales derived From Eysenck's [Eysenck. H.J. (1967). The biological basis of personality. Springfield, IL: Charles C. Thompson.] physiological model of personality. Results confirmed the hypothesis and also showed that Gray's scale of Impulsivity was generally a better predictor than attributional style and interest in money. Results were interpreted as providing support for Gray's Behavioural Activation System which moderates response to reward. (C) 2001 Elsevier Science Ltd. All rights reserved.

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In a previous study eight MHC class I-matched sheep were vaccinated with a minimal cytotoxic T lymphocyte (CTL) peptide epitope vaccine and were challenged with the retrovirus, bovine leukemia virus (BLV). Half the vaccinated animals remained PCR negative after challenge, whereas the remaining half and the placebo group became PCR positive within 4 weeks postchallenge (Hislop AD, Good MF, Mateo L, Gardner J, Gatei MH, Daniel RCW, Meyers BV, Lavin MF, and Suhrbier A: Nat Med 1998; 4: 1193). Here we show that neither epitope mutations nor processing differences explained why half the peptide-vaccinated animals failed to resist the BLV challenge. However, in these animals the development of BLV-induced lymphosarcomas was significantly delayed compared with the placebo group, suggesting a role for CTLs in preventing retrovirus-induced cancers. Importantly, two of the initially protected animals become PCR positive after similar to1.5 years, indicating extended suppression but not elimination of challenge virus by vaccine-induced CTLs. The late emergence of virus could not be explained by epitope escape mutations or the loss of memory CTL responses. We speculate that high levels of effector CTL may be needed to protect animals from a postchallenge viremia and maintenance of such effector CTLs, rather than memory CTLs, may be required to prevent subsequent emergence of virus from latent pools.

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Observations of accelerating seismic activity prior to large earthquakes in natural fault systems have raised hopes for intermediate-term eartquake forecasting. If this phenomena does exist, then what causes it to occur? Recent theoretical work suggests that the accelerating seismic release sequence is a symptom of increasing long-wavelength stress correlation in the fault region. A more traditional explanation, based on Reid's elastic rebound theory, argues that an accelerating sequence of seismic energy release could be a consequence of increasing stress in a fault system whose stress moment release is dominated by large events. Both of these theories are examined using two discrete models of seismicity: a Burridge-Knopoff block-slider model and an elastic continuum based model. Both models display an accelerating release of seismic energy prior to large simulated earthquakes. In both models there is a correlation between the rate of seismic energy release with the total root-mean-squared stress and the level of long-wavelength stress correlation. Furthermore, both models exhibit a systematic increase in the number of large events at high stress and high long-wavelength stress correlation levels. These results suggest that either explanation is plausible for the accelerating moment release in the models examined. A statistical model based on the Burridge-Knopoff block-slider is constructed which indicates that stress alone is sufficient to produce accelerating release of seismic energy with time prior to a large earthquake.

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Previous studies have shown a significant effect of insulin administration on serum dehydroepiandrosterone sulfate (DHEA-S) concentration and its metabolic rate, with evidence for the effect in men, but not in women. This could lead to differences in the sources of variation in serum DHEA-S between men and women and in its covariation with insulin concentration. This study aimed to test whether these hypotheses were supported in a sample of healthy adult twins. Serum DHEA-S (n=2287) and plasma insulin (n=2436) were measured in samples from adult male and female twins recruited through the Australian Twin Registry. Models of genetic and environmental sources of variation and covariation were tested against the data. DHEA-S showed substantial genetic effects in both men and women after adjustment for covariates, including sex, age, body mass index, and time since the last meal. There was no significant phenotypic or genetic correlation between DHEA-S and insulin in either men or women. Despite the experimental evidence for insulin infusion producing a reduction in serum DHEA-S and some effect of meals on the observed DHEA-S concentration, there were no associations between insulin and DHEA-S at the population level. Variations in DHEA-S are due to age, sex, obesity, and substantial polygenic genetic influences.

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Stress echocardiography has been shown to improve the diagnosis of coronary artery disease in the presence of hypertension, but its value in prognostic evaluation is unclear. We sought to determine whether stress echocardiography could be used to predict mortality in 2363 patients with hypertension, who were followed for up to 10 years (mean 4.0+/-1.8) for death and revascularization. Stress echocardiograms were normal in 1483 patients (63%), 16% had resting left ventricular (LV) dysfunction alone, and 21% had ischemia. Abnormalities were confined to one territory in 489 patients (21%) and to multiple territories in 365 patients (15%). Cardiac death was less frequent among the patients able to exercise than among those undergoing dobutamine echocardiography (4% versus 7%, P<0.001). The risk of death in patients with a negative stress echocardiogram was <1% per year. Ischemia identified by stress echocardiography was an independent predictor of mortality in those able to exercise (hazard ratio 2.21, 95% confidence intervals 1.10 to 4.43, P=0.0001) as well as those undergoing dobutamine echo (hazard ratio 2.39, 95% confidence intervals 1.53 to 3.75, P=0.0001); other predictors were age, heart failure, resting LV dysfunction, and the Duke treadmill score. In stepwise models replicating the sequence of clinical evaluation, the results of stress echocardiography added prognostic power to models based on clinical and stress-testing variables. Thus, the results of stress echocardiography are an independent predictor of cardiac death in hypertensive patients with known or suspected coronary artery disease, incremental to clinical risks and exercise results.

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Issues concerning the influence of attachment characteristics on own and partner's disclosure were addressed using a sample of 113 couples in medium-term dating relationships. Individual differences in attachment were assessed in terms of relationship anxiety and avoidance. Disposition to disclose was assessed using questionnaire measures of self-disclosure, relationship-focused disclosure, and the ability to elicit disclosure from the partner; in addition, structured diaries were used to assess aspects of disclosure (amount, intimacy, emotional tone, and satisfaction) in the context of couples' everyday interactions. Couple-level analyses showed that avoidance strongly predicted dispositional measures of disclosure, whereas anxiety (particularly partner's anxiety) was related to negative evaluations of everyday interactions. Interactive effects of attachment dimensions and gender were also obtained, highlighting the complexity of communication behavior. The results are discussed in terms of the goals and strategies associated with working models of attachment.

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The thin-layer drying behaviour of bananas in a beat pump dehumidifier dryer was examined. Four pre-treatments (blanching, chilling, freezing and combined blanching and freezing) were applied to the bananas, which were dried at 50 degreesC with an air velocity of 3.1 m s(-1) and with the relative humidity of the inlet air of 10-35%. Three drying models, the simple model, the two-term exponential model and the Page model were examined. All models were evaluated using three statistical measures, correlation coefficient, root means square error, and mean absolute percent error. Moisture diffusivity was calculated based on the diffusion equation for an infinite cylindrical shape using the slope method. The rate of drying was higher for the pre-treatments involving freezing. The sample which was blanched only did not show any improvement in drying rate. In fact, a longer drying time resulted due to water absorption during blanching. There was no change in the rate for the chilled sample compared with the control. While all models closely fitted the drying data, the simple model showed greatest deviation from the experimental results. The two-term exponential model was found to be the best model for describing the drying curves of bananas because its parameters represent better the physical characteristics of the drying process. Moisture diffusivities of bananas were in the range 4.3-13.2 x 10(-10) m(2)s(-1). (C) 2002 Published by Elsevier Science Ltd.