Optimising profitability and environmental trade-offs in managing cropping systems using differential evolution

Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.

Differential evolution based total transfer capability assessment with optimal dispatch

In this paper, a new differential evolution (DE) based power system optimal available transfer capability (ATC) assessment is presented. Power system total transfer capability (TTC) is traditionally solved by the repeated power flow (RPF) method and the continuation power flow (CPF) method. These methods are based on the assumption that the productions of the source area generators are increased in identical proportion to balance the load increment in the sink area. A new approach based on DE algorithm to generate optimal dispatch both in source area generators and sink area loads is proposed in this paper. This new method can compute ATC between two areas with significant improvement in accuracy compared with the traditional RPF and CPF based methods. A case study using a 30 bus system is given to verify the efficiency and effectiveness of this new DE based ATC optimization approach.

Modelling of microstructure formation and evolution during solidification

A comprehensive probabilistic model for simulating microstructure formation and evolution during solidification has been developed, based on coupling a Finite Differential Method (FDM) for macroscopic modelling of heat diffusion to a modified Cellular Automaton (mCA) for microscopic modelling of nucleation, growth of microstructures and solute diffusion. The mCA model is similar to Nastac's model for handling solute redistribution in the liquid and solid phases, curvature and growth anisotropy, but differs in the treatment of nucleation and growth. The aim is to improve understanding of the relationship between the solidification conditions and microstructure formation and evolution. A numerical algorithm used for FDM and mCA was developed. At each coarse scale, temperatures at FDM nodes were calculated while nucleation-growth simulation was done at a finer scale, with the temperature at the cell locations being interpolated from those at the coarser volumes. This model takes account of thermal, curvature and solute diffusion effects. Therefore, it can not only simulate microstructures of alloys both on the scale of grain size (macroscopic level) and the dendrite tip length (mesoscopic level), but also investigate nucleation mechanisms and growth kinetics of alloys solidified with various solute concentrations and solidification morphologies. The calculated results are compared with values of grain sizes and solidification morphologies of microstructures obtained from a set of casting experiments of Al-Si alloys in graphite crucibles.

A genetic estimation algorithm for parameters of stochastic ordinary differential equations

A generic method for the estimation of parameters for Stochastic Ordinary Differential Equations (SODEs) is introduced and developed. This algorithm, called the GePERs method, utilises a genetic optimisation algorithm to minimise a stochastic objective function based on the Kolmogorov-Smirnov statistic. Numerical simulations are utilised to form the KS statistic. Further, the examination of some of the factors that improve the precision of the estimates is conducted. This method is used to estimate parameters of diffusion equations and jump-diffusion equations. It is also applied to the problem of model selection for the Queensland electricity market. (C) 2003 Elsevier B.V. All rights reserved.

Geochronology of weathering and landscape evolution, Dugald River valley, NW Queensland, Australia

40Ar/39Ar laser incremental heating analyses of individual grains of supergene jarosite, alunite, and cryptomelane from weathering profiles in the Dugald River area, Queensland, Australia, show a strong positive correlation between a sample’s age and its elevation. We analyzed 125 grains extracted from 35 hand specimens collected from weathering profiles at 11 sites located at 3 distinct elevations. The highest elevation profile hosts the oldest supergene minerals, whereas progressively younger samples occur at lower positions in the landscape. The highest elevation sampling sites (three sites), located on top of an elongated mesa (255 to 275 m elevation), yield ages in the 16 to 12 Ma range. Samples from an intermediate elevation site (225 to 230 m elevation) yield ages in the 6 to 4 Ma range. Samples collected at the lowest elevation sites (200 to 220 m elevation) yield ages in the 2.2 to 0.8 Ma interval. Grains of supergene alunite, jarosite, and cryptomelane analyzed from individual single hand specimens yield reproducible results, confirming the suitability of these minerals to 40Ar/39Ar geochronology. Multiple samples collected from the same site also yield reproducible results, indicating that the ages measured are true precipitation ages for the samples analyzed. Different sites, up to 3 km apart, sampled from weathering profiles at the same elevation again yield reproducible results. The consistency of results confirms that 40Ar/39Ar geochronology of supergene jarosite, alunite, and cryptomelane yields ages of formation of weathering profiles, providing a reliable numerical basis for differentiating and correlating these profiles. The age versus elevation relationship obtained suggest that the stepped landscapes in the Dugald River area record a progressive downward migration of a relatively flat weathering front. The steps in the landscape result from differential erosion of previously weathered bedrock displaying different susceptibility to weathering and contrasting resistance to erosion. Combined, the age versus elevation relationships measured yield a weathering rate of 3.8 m. Myr−1 (for the past 15 Ma) if a descending subhorizontal weathering front is assumed. The results also permit the calculation of the erosion rate of the more easily weathered and eroded lithologies, assuming an initially flat landscape as proposed in models of episodic landscape development. The average erosion rate for the past 15 Ma is 3.3 m. Myr−1, consistent with erosion rates obtained by cosmogenic isotope studies in the region.

Differential patterns of Male and Female mtDNA exchange across the Atlantic Ocean in the blue mussel, Mytilus edulis

Comparisons among loci with differing modes of inheritance can reveal unexpected aspects of population history. We employ a multilocus approach to ask whether two types of independently assorting mitochondrial DNAs (maternally and paternally inherited: F- and M-mtDNA) and a nuclear locus (ITS) yield concordant estimates of gene flow and population divergence. The blue mussel, Mytilus edulis, is distributed on both North American and European coastlines and these populations are separated by the waters of the Atlantic Ocean. Gene flow across the Atlantic Ocean differs among loci, with F-mtDNA and ITS showing an imprint of some genetic interchange and M-mtDNA showing no evidence for gene flow. Gene flow of F-mtDNA and ITS causes trans-Atlantic population divergence times to be greatly underestimated for these loci, although a single trans-Atlantic population divergence time (1.2 MYA) can be accommodated by considering all three loci in combination in a coalescent framework. The apparent lack of gene flow for M-mtDNA is not readily explained by different dispersal capacities of male and female mussels. A genetic barrier to M-mtDNA exchange between North American and European mussel populations is likely to explain the observed pattern, perhaps associated with the double uniparental system of mitochondrial DNA inheritance.

Evolution of three-dimensional folds for a non-Newtonian plate in a viscous medium

We derive analytical solutions for the three-dimensional time-dependent buckling of a non-Newtonian viscous plate in a less viscous medium. For the plate we assume a power-law rheology. The principal, axes of the stretching D-ij in the homogeneously deformed ground state are parallel and orthogonal to the bounding surfaces of the plate in the flat state. In the model formulation the action of the less viscous medium is replaced by equivalent reaction forces. The reaction forces are assumed to be parallel to the normal vector of the deformed plate surfaces. As a consequence, the buckling process is driven by the differences between the in-plane stresses and out of plane stress, and not by the in-plane stresses alone as assumed in previous models. The governing differential equation is essentially an orthotropic plate equation for rate dependent material, under biaxial pre-stress, supported by a viscous medium. The differential problem is solved by means of Fourier transformation and largest growth coefficients and corresponding wavenumbers are evaluated. We discuss in detail fold evolutions for isotropic in-plane stretching (D-11 = D-22), uniaxial plane straining (D-22 = 0) and in-plane flattening (D-11 = -2D(22)). Three-dimensional plots illustrate the stages of fold evolution for random initial perturbations or initial embryonic folds with axes non-parallel to the maximum compression axis. For all situations, one dominant set of folds develops normal to D-11, although the dominant wavelength differs from the Biot dominant wavelength except when the plate has a purely Newtonian viscosity. However, in the direction parallel to D-22, there exist infinitely many modes in the vicinity of the dominant wavelength which grow only marginally slower than the one corresponding to the dominant wavelength. This means that, except for very special initial conditions, the appearance of a three-dimensional fold will always be governed by at least two wavelengths. The wavelength in the direction parallel to D-11 is the dominant wavelength, and the wavelength(s) in the direction parallel to D-22 is determined essentially by the statistics of the initial state. A comparable sensitivity to the initial geometry does not exist in the classic two-dimensional folding models. In conformity with tradition we have applied Kirchhoff's hypothesis to constrain the cross-sectional rotations of the plate. We investigate the validity of this hypothesis within the framework of Reissner's plate theory. We also include a discussion of the effects of adding elasticity into the constitutive relations and show that there exist critical ratios of the relaxation times of the plate and the embedding medium for which two dominant wavelengths develop, one at ca. 2.5 of the classical Biot dominant wavelength and the other at ca. 0.45 of this wavelength. We propose that herein lies the origin of parasitic folds well known in natural examples.

What the evolution of the amyloid protein precursor supergene family tells us about its function

The Alzheimer's disease amyloid protein precursor (APP) gene is part of a multi-gene super-family from which sixteen homologous amyloid precursor-like proteins (APLP) and APP species homologues have been isolated and characterised. Comparison of exon structure (including the uncharacterised APL-1 gene), construction of phylogenetic trees, and analysis of the protein sequence alignment of known homologues of the APP super-family were performed to reconstruct the evolution of the family and to assess the functional significance of conserved protein sequences between homologues. This analysis supports an adhesion function for all members of the APP super family, with specificity determined by those sequences which are not conserved between APLP lineages, and provides evidence for an increasingly complex APP superfamily during evolution. The analysis also suggests that Drosophila APPL and Caenorhabdotids elegans APL-1 may be a fourth APLP lineage indicating that these proteins, while not functional homologues of human APP, are similarly likely to regulate cell adhesion. Furthermore, the beta A4 sequence is highly conserved only in APP orthologues, strongly suggesting this sequence is of significant functional importance in this lineage. (C) 2000 Elsevier Science Ltd. All rights reserved.

Robust algorithms for solving stochastic partial differential equations

A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differential equations (PDEs) is described. This can be used for calculating correlation functions of systems of interacting stochastic fields. Such field equations can arise in the description of Hamiltonian and open systems in the physics of nonlinear processes, and may include multiplicative noise sources. The algorithm can be used for studying the properties of nonlinear quantum or classical field theories. The general approach is outlined and applied to a specific example, namely the quantum statistical fluctuations of ultra-short optical pulses in chi((2)) parametric waveguides. This example uses a non-diagonal coherent state representation, and correctly predicts the sub-shot noise level spectral fluctuations observed in homodyne detection measurements. It is expected that the methods used wilt be applicable for higher-order correlation functions and other physical problems as well. A stochastic differencing technique for reducing sampling errors is also introduced. This involves solving nonlinear stochastic parabolic PDEs in combination with a reference process, which uses the Wigner representation in the example presented here. A computer implementation on MIMD parallel architectures is discussed. (C) 1997 Academic Press.

Subspace wavepacket evolution with Newton polynomials

Time-dependent wavepacket evolution techniques demand the action of the propagator, exp(-iHt/(h)over-bar), on a suitable initial wavepacket. When a complex absorbing potential is added to the Hamiltonian for combating unwanted reflection effects, polynomial expansions of the propagator are selected on their ability to cope with non-Hermiticity. An efficient subspace implementation of the Newton polynomial expansion scheme that requires fewer dense matrix-vector multiplications than its grid-based counterpart has been devised. Performance improvements are illustrated with some benchmark one and two-dimensional examples. (C) 2001 Elsevier Science B.V. All rights reserved.

MRI based diffusion and perfusion predictive model to estimate stroke evolution

In this study we present a novel automated strategy for predicting infarct evolution, based on MR diffusion and perfusion images acquired in the acute stage of stroke. The validity of this methodology was tested on novel patient data including data acquired from an independent stroke clinic. Regions-of-interest (ROIs) defining the initial diffusion lesion and tissue with abnormal hemodynamic function as defined by the mean transit time (MTT) abnormality were automatically extracted from DWI/PI maps. Quantitative measures of cerebral blood flow (CBF) and volume (CBV) along with ratio measures defined relative to the contralateral hemisphere (r(a)CBF and r(a)CBV) were calculated for the MTT ROIs. A parametric normal classifier algorithm incorporating these measures was used to predict infarct growth. The mean r(a)CBF and r(a)CBV values for eventually infarcted MTT tissue were 0.70 +/-0.19 and 1.20 +/-0.36. For recovered tissue the mean values were 0.99 +/-0.25 and 1.87 +/-0.71, respectively. There was a significant difference between these two regions for both measures (P

The tree cut and merge algorithm for estimation of network reliability

This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.

An approach to verifying and debugging simulation models governed by ordinary differential equations: Part 2. Residuals analysis and a case study

In Part 1 of this paper a methodology for back-to-back testing of simulation software was described. Residuals with error-dependent geometric properties were generated. A set of potential coding errors was enumerated, along with a corresponding set of feature matrices, which describe the geometric properties imposed on the residuals by each of the errors. In this part of the paper, an algorithm is developed to isolate the coding errors present by analysing the residuals. A set of errors is isolated when the subspace spanned by their combined feature matrices corresponds to that of the residuals. Individual feature matrices are compared to the residuals and classified as 'definite', 'possible' or 'impossible'. The status of 'possible' errors is resolved using a dynamic subset testing algorithm. To demonstrate and validate the testing methodology presented in Part 1 and the isolation algorithm presented in Part 2, a case study is presented using a model for biological wastewater treatment. Both single and simultaneous errors that are deliberately introduced into the simulation code are correctly detected and isolated. Copyright (C) 2003 John Wiley Sons, Ltd.