BeachWin: modelling groundwater effects on swash sediment transport and beach profile changes

Field and laboratory observations have shown that a relatively low beach groundwater table enhances beach accretion. These observations have led to the beach dewatering technique (artificially lowering the beach water table) for combating beach erosion. Here we present a process-based numerical model that simulates the interacting wave motion on the beach. coastal groundwater flow, swash sediment transport and beach profile changes. Results of model simulations demonstrate that the model replicates accretionary effects of a low beach water table on beach profile changes and has the potential to become a tool for assessing the effectiveness of beach dewatering systems. (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.

Inter-subband redundancy prediction using neural network for video coding

High performance video codec is mandatory for multimedia applications such as video-on-demand and video conferencing. Recent research has proposed numerous video coding techniques to meet the requirement in bandwidth, delay, loss and Quality-of-Service (QoS). In this paper, we present our investigations on inter-subband self-similarity within the wavelet-decomposed video frames using neural networks, and study the performance of applying the spatial network model to all video frames over time. The goal of our proposed method is to restore the highest perceptual quality for video transmitted over a highly congested network. Our contributions in this paper are: (1) A new coding model with neural network based, inter-subband redundancy (ISR) prediction for video coding using wavelet (2) The performance of 1D and 2D ISR prediction, including multiple levels of wavelet decompositions. Our result shows a short-term quality enhancement may be obtained using both 1D and 2D ISR prediction.

Causes and consequences of long-term climatic variability on the Australian continent

1. Ice-volume forced glacial-interglacial cyclicity is the major cause of global climate variation within the late Quaternary period. Within the Australian region, this variation is expressed predominantly as oscillations in moisture availability. Glacial periods were substantially drier than today with restricted distribution of mesic plant communities, shallow or ephemeral water bodies and extensive aeolian dune activity. 2. Superimposed on this cyclicity in Australia is a trend towards drier and/or more variable climates within the last 350 000 years. This trend may have been initiated by changes in atmospheric and ocean circulation resulting from Australia's continued movement into the Southeast Asian region and involving the onset or intensification of the El Nino-Southern Oscillation system and a reduction in summer monsoon activity. 3. Increased biomass burning, stemming originally from increased climatic variability and later enhanced by activities of indigenous people, resulted in a more open and sclerophyllous vegetation, increased salinity and a further reduction in water availability. 4. Past records combined with recent observations suggest that the degree of environmental variability will increase and the drying trend will be enhanced in the foreseeable future, regardless of the extent or nature of human intervention.

Variation in the dispersal potential of non-feeding invertebrate larvae: the desperate larva hypothesis and larval size

For many species of marine invertebrates, variability in larval settlement behaviour appears to be the rule rather than the exception. This variability has the potential to affect larval dispersal, because settlement behaviour will influence the length of time larvae are in the plankton. Despite the ubiquity and importance of this variability, relatively few sources of variation in larval settlement behaviour have been identified. One important factor that can affect larval settlement behaviour is the nutritional state of larvae. Non-feeding larvae often become less discriminating in their 'choice' of settlement substrate, i.e. more desperate to settle, when energetic reserves run low. We tested whether variation in larval size (and presumably in nutritional reserves) also affects the settlement behaviour of 3 species of colonial marine invertebrate larvae, the bryozoans Bugula neritina and Watersipora subtorquata and the ascidian Diplosoma listerianum. For all 3 species, larger larvae delayed settlement for longer in the absence of settlement cues, and settlement of Bugula neritina larvae was accelerated by the presence of settlement cues, independently of larval size. In the field, larger W subtorquata larvae also took longer to settle than smaller larvae and were more discriminating towards settlement surfaces. These differences in settlement time are likely to result in differences in the distance that larvae disperse in the field. We suggest that species that produce non-feeding larvae can affect the dispersal potential of their offspring by manipulating larval size and thus larval desperation.

Assessing the ex ante economic impacts of transportation infrastructure policies in Brazil

This paper uses a fully operational inter-regional computable general equilibrium (CGE) model implemented for the Brazilian economy, based on previous work by Haddad and Hewings, in order to assess the likely economic effects of road transportation policy changes in Brazil. Among the features embedded in this framework, modelling of external scale economies and transportation costs provides an innovative way of dealing explicitly with theoretical issues related to integrated regional systems. The model is calibrated for 109 regions. The explicit modelling of transportation costs built into the inter-regional CGE model, based on origin-destination flows, which takes into account the spatial structure of the Brazilian economy, creates the capability of integrating the inter-regional CGE model with a geo-coded transportation network model enhancing the potential of the framework in understanding the role of infrastructure on regional development. The transportation model used is the so-called Highway Development and Management, developed by the World Bank, implemented using the software TransCAD. Further extensions of the current model specification for integrating other features of transport planning in a continental industrialising country like Brazil are discussed, with the goal of building a bridge between conventional transport planning practices and the innovative use of CGE models. In order to illustrate the analytical power of the integrated system, the authors present a set of simulations, which evaluate the ex ante economic impacts of physical/qualitative changes in the Brazilian road network (for example, a highway improvement), in accordance with recent policy developments in Brazil. Rather than providing a critical evaluation of this debate, they intend to emphasise the likely structural impacts of such policies. They expect that the results will reinforce the need to better specifying spatial interactions in inter-regional CGE models.

Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison

This paper develops a multi-regional general equilibrium model for climate policy analysis based on the latest version of the MIT Emissions Prediction and Policy Analysis (EPPA) model. We develop two versions so that we can solve the model either as a fully inter-temporal optimization problem (forward-looking, perfect foresight) or recursively. The standard EPPA model on which these models are based is solved recursively, and it is necessary to simplify some aspects of it to make inter-temporal solution possible. The forward-looking capability allows one to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. To evaluate the solution approaches, we benchmark each version to the same macroeconomic path, and then compare the behavior of the two versions under a climate policy that restricts greenhouse gas emissions. We find that the energy sector and CO(2) price behavior are similar in both versions (in the recursive version of the model we force the inter-temporal theoretical efficiency result that abatement through time should be allocated such that the CO(2) price rises at the interest rate.) The main difference that arises is that the macroeconomic costs are substantially lower in the forward-looking version of the model, since it allows consumption shifting as an additional avenue of adjustment to the policy. On the other hand, the simplifications required for solving the model as an optimization problem, such as dropping the full vintaging of the capital stock and fewer explicit technological options, likely have effects on the results. Moreover, inter-temporal optimization with perfect foresight poorly represents the real economy where agents face high levels of uncertainty that likely lead to higher costs than if they knew the future with certainty. We conclude that while the forward-looking model has value for some problems, the recursive model produces similar behavior in the energy sector and provides greater flexibility in the details of the system that can be represented. (C) 2009 Elsevier B.V. All rights reserved.

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.

Revision of the larval morphology (Zoea I) of the family Hippolytidae (Decapoda, Caridea), with a description of the first stage of the shrimp Hippolyte obliquimanus Dana, 1852

The aim of this study was to summarize the available data on larval morphology of the first zoea of the family Hippolytidae and describe the first zoeal stage of H. obliquimanus from two geographically distinct populations, Brazilian and Caribbean in order to discuss inter- and intraspecific variability. Ovigerous females of Hippolyte obliquimanus were collected at Cahuita (Limon, Costa Rica) and at Ubatuba (Sao Paulo, Brazil). We compiled the published descriptions of all available hippolytid Zoea I (66 spp., 21%), and all zoeae share several characteristics. However, such morphological features cannot be used to distinguish the first zoeae of Hippolytidae from other caridean larvae. Historically, the presence of an exopodal seta at the maxillule and the absence of the anal spine/papilla have been considered as characteristic for the Zoea I of the genus Hippolyte. The results of our revision, however, did not support these conclusions: although H. obliquimanus showed an exopodal seta at the maxillule, four congeners did not bear such structure; moreover, H. obliquimanus as well as one other congener have an anal spine/papilla. All morphological characters observed in the first zoeal stage of H. obliquimanus are shared with others species of the family Hippolytidae. Intraspecific variability in Hippolyte obliquimanus was detected in one morphological aspect: the first zoea had four denticles on the ventral margin of the carapace in the Brazilian population, while specimens from the Costa Rican population had three.

Low Satellite DNA Variability in Natural Populations of Drosophila antonietae Involved in Different Evolutionary Events

Drosophila antonietae is a cactophilic species that is found in the mesophilic forest of the Parana`-Paraguay river basin and in the dunes of the South Atlantic coast of Brazil. Although the genetic structure of the Parana`-Paraguay river basin populations has already been established, the relationship between these populations and those on the Atlantic coast is controversial. In this study, we compared 33 repetitive units of pBuM-2 satellite DNA isolated from individuals from 8 populations of D. antonietae in these geographic regions, including some populations found within a contact zone with the closely related D. serido. The pBuM-2 sequences showed low interpopulational variability. This result was interpreted as a consequence of both gene flow among the populations and unequal crossing over promoting homogenization of the tandem arrays. The results presented here, together with those of previous studies, highlight the use of pBuM-2 for solving taxonomic conflicts within the D. buzzatii species cluster.

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.