Analytical solution for tidal propagation in a coupled semi-confined/phreatic coastal aquifer

An analytical solution is derived for tidal fluctuations in a coupled coastal aquifer system consisting of a semi-confined aquifer, a thin semi-permeable layer and a phreatic aquifer. Based on the solution, we study the interactions (via leakage) between the confined and unconfined aquifers in response to tides. The results show that, under certain conditions, leakage from the confined aquifer can affect considerably the tidal water table fluctuation in the phreatic aquifer and vice versa. Ignoring these effects could lead to errors in estimating aquifer properties based on tidal signals. (C) 2002 Elsevier Science Ltd. All rights reserved.

Finite element modelling of reactive fluids mixing and mineralization in pore-fluid saturated hydrothermal/sedimentary basins

We present the finite element simulations of reactive mineral carrying fluids mixing and mineralization in pore-fluid saturated hydrothermal/sedimentary basins. In particular we explore the mixing of reactive sulfide and sulfate fluids and the relevant patterns of mineralization for Load, zinc and iron minerals in the regime of temperature-gradient-driven convective flow. Since the mineralization and ore body formation may last quite a long period of time in a hydrothermal basin, it is commonly assumed that, in the geochemistry, the solutions of minerals are in an equilibrium state or near an equilibrium state. Therefore, the mineralization rate of a particular kind of mineral can be expressed as the product of the pore-fluid velocity and the equilibrium concentration of this particular kind of mineral Using the present mineralization rate of a mineral, the potential of the modern mineralization theory is illustrated by means of finite element studies related to reactive mineral-carrying fluids mixing problems in materially homogeneous and inhomogeneous porous rock basins.

Spatial data mining for enhanced soil map modelling

The principle of using induction rules based on spatial environmental data to model a soil map has previously been demonstrated Whilst the general pattern of classes of large spatial extent and those with close association with geology were delineated small classes and the detailed spatial pattern of the map were less well rendered Here we examine several strategies to improve the quality of the soil map models generated by rule induction Terrain attributes that are better suited to landscape description at a resolution of 250 m are introduced as predictors of soil type A map sampling strategy is developed Classification error is reduced by using boosting rather than cross validation to improve the model Further the benefit of incorporating the local spatial context for each environmental variable into the rule induction is examined The best model was achieved by sampling in proportion to the spatial extent of the mapped classes boosting the decision trees and using spatial contextual information extracted from the environmental variables.

Epidemiological modelling (including economic modelling) and its role in preventive drug therapy

In contrast to curative therapies, preventive therapies are administered to largely healthy individuals over long periods. The risk-benefit and cost-benefit ratios are more likely to be unfavourable, making treatment decisions difficult. Drug trials provide insufficient information for treatment decisions, as they are conducted on highly selected populations over short durations, estimate only relative benefits of treatment and offer little information on risks and costs. Epidemiological modelling is a method of combining evidence from observational epidemiology and clinical trials to assist in clinical and health policy decision-making. It can estimate absolute benefits, risks and costs of long-term preventive strategies, and thus allow their precise targeting to individuals for whom they are safest and most cost-effective. Epidemiological modelling also allows explicit information about risks and benefits of therapy to be presented to patients, facilitating informed decision-making.

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

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.

Late Quaternary Milankovitch-scale climatic change and variability and its impact on monsoonal Australasia

Four pollen and charcoal records derived from marine cores around the northern perimeter of Australia are examined to provide a regional picture of patterns, causes and impacts of climate change over the last 100-300 ka. The availability of radiocarbon dates and oxygen isotope records for the cores provides primary chronological control. Spectral analysis of components of these records demonstrates an overall importance of Milankovitch frequencies with clear glacial-interglacial cyclicity dominated by variation in precipitation. In addition, a number of pollen taxa, as well as charcoal particles, exhibit a 30 ka frequency that is considered, from its relationship with biomass burning and with results of past modelling, to reflect changes in the intensity of El Nino-Southern Oscillation (ENSO) variability. Pollen components of all records show a decline, frequently stepwise, in more fire-sensitive vegetation and its replacement with more fire-tolerant vegetation. There is some evidence that this trend is linked to an onset or general increase in ENSO activity and perhaps also to variation in monsoon activity dating from about 300 ka BP that was caused by changes to oceanic circulation within the Indonesian region. The trend may have accelerated within the last 45 ka due to burning by indigenous people. (C) 2003 Elsevier B.V. All rights reserved.

Event-related FMRI analysis with maximum correlation modelling

Functional magnetic resonance imaging (FMRI) analysis methods can be quite generally divided into hypothesis-driven and data-driven approaches. The former are utilised in the majority of FMRI studies, where a specific haemodynamic response is modelled utilising knowledge of event timing during the scan, and is tested against the data using a t test or a correlation analysis. These approaches often lack the flexibility to account for variability in haemodynamic response across subjects and brain regions which is of specific interest in high-temporal resolution event-related studies. Current data-driven approaches attempt to identify components of interest in the data, but currently do not utilise any physiological information for the discrimination of these components. Here we present a hypothesis-driven approach that is an extension of Friman's maximum correlation modelling method (Neurolmage 16, 454-464, 2002) specifically focused on discriminating the temporal characteristics of event-related haemodynamic activity. Test analyses, on both simulated and real event-related FMRI data, will be presented.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

Expectation Propagation with Factorizing Distributions: A Gaussian Approximation and Performance Results for Simple Models

We discuss the expectation propagation (EP) algorithm for approximate Bayesian inference using a factorizing posterior approximation. For neural network models, we use a central limit theorem argument to make EP tractable when the number of parameters is large. For two types of models, we show that EP can achieve optimal generalization performance when data are drawn from a simple distribution.

Seed dormancy and germination responses of nine Australian fire ephemerals

Fire ephemerals are short-lived plants with seeds that persist in the soil and germinate after a fire or physical soil disturbance. Ex situ germination of many Australian fire ephemerals has previously been difficult. Dormancy was present in most of the nine fire ephemerals examined. Alyogyne hakeifolia (Giord.) Alef. and Alyogyne huegelii (Endl.) Fryxell (Malvaceae) seeds had physical and possibly also physiological dormancy, Actinotus leucocephalus Benth. (Apiaceae) seeds had morphophysiological dormancy, Austrostipa compressa (R.Br.) S.W.L. Jacobs & J. Everett and Austrostipa macalpinei (Reader) S.W.L. Jacobs & J. Everett (Poaceae) seeds were either non-dormant or possessed physiological dormancy, and seeds of all remaining species possessed physiological dormancy. A proportion of the Alyogyne hakeifolia, Alyogyne huegelii, Austrostipa compressa and Austrostipa macalpinei seed populations were non-dormant because some seeds could germinate at the various incubation temperatures without further treatment. At 20 degrees C, artificial methods of inducing germination such as manual or acid scarification were among the optimal treatments for Austrostipa compressa, Austrostipa macalpinei, Alyogyne huegelii, Actinotus leucocephalus and Grevillea scapigera A.S. George (Proteaceae), and gibberellic acid induced maximum germination of Tersonia cyathiflora (Fenzl) J.W. Green (Gyrostemonaceae) seeds. Heat (70 degrees C for 1 h) and smoke water was one of the most effective treatments for germinating Actinotus leucocephalus and Codonocarpus cotinifolius (Desf.) F. Muell. (Gyrostemonaceae) seeds. Germination of Grevillea scapigera, Codonocarpus cotinifolius, Gyrostemon racemiger H. Walter (Gyrostemonaceae) and Tersonia cyathiflora did not exceed 40% and may require other treatments to overcome dormancy. Although the nine fire ephemerals examined require fire to germinate under natural conditions, a range of germination responses and dormancy types was observed.

Dormancy release in Australian fire ephemeral seeds during burial increases germination response to smoke water or heat

Fire ephemerals are short-lived plants that primarily germinate after fire. Fresh and laboratory-stored seeds are difficult to germinate ex situ, even in response to fire-related cues such as heat and smoke. Seeds of eight Australian fire ephemeral species were buried in unburnt and recently burnt sites of natural bushland during autumn. Seeds were exhumed after 6 and 12 months and incubated in water and smoke water, either with or without a heat treatment at 70 degrees C for 1 h. Generally, germination did not increase after 6 months of burial, but after 12 months of burial germination was enhanced in seven of the eight species. Actinotus leucocephalus produced higher germination following 12 months of burial without any further treatment, and smoke water and heat further improved germination. The four Gyrostemonaceae species, Codonocarpus cotinifolius, Gyrostemon racemiger, Gyrostemon ramulosus and Tersonia cyathiflora, only germinated in the presence of smoke water, and their germination was enhanced by burial. Burial improved germination in response to a heat treatment in Grevillea scapigera and Alyogyne huegelii seeds, but did not enhance Alyogyne hakeifolia germination. During concurrent dry laboratory storage of seeds at 15 degrees C, only Actinotus leucocephalus produced increased germination in response to smoke water and heat over time. In summary, soil burial can alter the dormancy status of a number of Australian fire ephemeral seeds, rendering them more responsive to germination cues such as smoke water and heat. The requirement for a period of burial before seeds become responsive to smoke and/or heat would ensure that seeds persist in the soil until a subsequent fire, when there is an increase in nutrients available for growth and reduced competition from other plants.

Experiments and modelling of phenanthrene biodegradation in the aqueous phase by a mixed culture

Pollution by polycyclic aromatic hydrocarbons(PAHs) is widespread due to unsuitable disposal of industrial waste. They are mostly defined as priority pollutants by environmental protection authorities worldwide. Phenanthrene, a typical PAH, was selected as the target in this paper. The PAH-degrading mixed culture, named ZM, was collected from a petroleum contaminated river bed. This culture was injected into phenanthrene solutions at different concentrations to quantify the biodegradation process. Results show near-complete removal of phenanthrene in three days of biodegradation if the initial phenanthrene concentration is low. When the initial concentration is high, the removal rate is increased but 20%-40% of the phenanthrene remains at the end of the experiment. The biomass shows a peak on the third day due to the combined effects of microbial growth and decay. Another peak is evident for cases with a high initial concentration, possibly due to production of an intermediate metabolite. The pH generally decreased during biodegradation because of the production of organic acid. Two phenomenological models were designed to simulate the phenanthrene biodegradation and biomass growth. A relatively simple model that does not consider the intermediate metabolite and its inhibition of phenanthrene biodegradation cannot fit the observed data. A modified Monod model that considered an intermediate metabolite (organic acid) and its inhibiting reversal effect reasonably depicts the experimental results.