Improving wheat simulation capabilities in Australia from a cropping systems perspective: water and nitrogen effects on spring wheat in a semi-arid environment

Systems approaches can help to evaluate and improve the agronomic and economic viability of nitrogen application in the frequently water-limited environments. This requires a sound understanding of crop physiological processes and well tested simulation models. Thus, this experiment on spring wheat aimed to better quantify water x nitrogen effects on wheat by deriving some key crop physiological parameters that have proven useful in simulating crop growth. For spring wheat grown in Northern Australia under four levels of nitrogen (0 to 360 kg N ha(-1)) and either entirely on stored soil moisture or under full irrigation, kernel yields ranged from 343 to 719 g m(-2). Yield increases were strongly associated with increases in kernel number (9150-19950 kernels m(-2)), indicating the sensitivity of this parameter to water and N availability. Total water extraction under a rain shelter was 240 mm with a maximum extraction depth of 1.5 m. A substantial amount of mineral nitrogen available deep in the profile (below 0.9 m) was taken up by the crop. This was the source of nitrogen uptake observed after anthesis. Under dry conditions this late uptake accounted for approximately 50% of total nitrogen uptake and resulted in high (>2%) kernel nitrogen percentages even when no nitrogen was applied,Anthesis LAI values under sub-optimal water supply were reduced by 63% and under sub-optimal nitrogen supply by 50%. Radiation use efficiency (RUE) based on total incident short-wave radiation was 1.34 g MJ(-1) and did not differ among treatments. The conservative nature of RUE was the result of the crop reducing leaf area rather than leaf nitrogen content (which would have affected photosynthetic activity) under these moderate levels of nitrogen limitation. The transpiration efficiency coefficient was also conservative and averaged 4.7 Pa in the dry treatments. Kernel nitrogen percentage varied from 2.08 to 2.42%. The study provides a data set and a basis to consider ways to improve simulation capabilities of water and nitrogen effects on spring wheat. (C) 1997 Elsevier Science B.V.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.

A semi-analytical solution for vibration of rectangular plates with abrupt thickness variation

A semi-analytical analysis of free vibration of plates with cross-sectional discontinuities due to abrupt changes in thickness is presented. A basic square element divided into suitable subdomains dependent upon the positions of these abrupt changes is used as the basic building element, Admissible functions that satisfy the essential or geometric boundary conditions are used to define the transverse deflection of each subdomain. Continuities in the displacement, slope, moment and higher derivatives between adjacent subdomains are enforced at the interconnecting edges. The resulting global energy functional from the proper assembly of the coupled strain and kinetic energy contributions of each subdomain is then minimized via the Ritz procedure to extract the frequencies and mode shapes. Contour plots of a range of new mode shapes are presented for the enhancement of understanding the dynamic behavior of this class of plates, (C) 2001 Elsevier Science Ltd, All rights reserved.

A mixture model-based approach to the clustering of microarray expression data

Motivation: This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. Results: The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets.

Engineering closure of an open pit gold operation in a semi-arid climate

Along with material characteristics and geometry, the climate in which a mine is located can have a dramatic effect on the appropriate options for rehabilitation. The paper outlines the setting, mining, milling and waste disposal at Kidston Gold Mine's open pit operations in the semi-arid climate of North Queensland, Australia, before focusing on the engineering aspects of the rehabilitation of Kidston. The mine took a holistic and proactive approach to rehabilitation, and was prepared to demonstrate a number of innovative approaches, which are described in the paper. Engineering issues that had to be addressed included the geotechnical stability and deformation of waste rock dumps, including a 240 m high in-pit dump: the construction and performance monitoring of a “store and release” cover over potentially acid forming mineralised waste rock; erosion from the side slopes of the waste rock dumps; the in-pit co-disposal of waste rock and thickened tailings; the geotechnical stability of the tailings dam wall; the potential for erosion of bare tailings; the water balance of the tailings dam; direct revegetation of the tailings; and the pit hydrology. The rehabilitation of the mine represents an important benchmark in mine site rehabilitation best practice, from which lessons applicable worldwide can be shared.

Ontogenetic changes of swimming kinematics in a semi-aquatic reptile (Crocodylus porosus)

Semi-aquatic animals represent a transitional locomotor condition characterised by the possession of morphological features that allow locomotion both in water and on land. Most ecologically important behaviours of crocodilians occur in the water, raising the question of whether their 'terrestrial construction' constrains aquatic locomotion. Moreover, the demands for aquatic locomotion change with life-history stage. It was the aim of this research to determine the kinematic characteristics and efficiency of aquatic locomotion in different-sized crocodiles (Crocodylus porosus). Aquatic propulsion was achieved primarily by tail undulations, and the use of limbs during swimming was observed only in very small animals or at low swimming velocities in larger animals. Over the range of swimming speeds we examined, tail beat amplitude did not change with increasing velocity, but amplitude increased significantly with body length. However, amplitude expressed relative to body length decreased with increasing body length. Tail beat frequency increased with swimming velocity but there were no differences in frequency between different-sized animals. Mechanical power generated during swimming and thrust increased non-linearly with swimming velocity, but disproportionally so that kinematic efficiency decreased with increasing swimming velocity. The importance of unsteady forces, expressed as the reduced frequency, increased with increasing swimming velocity. Amplitude is the main determinant of body-size-related increases in swimming velocity but, compared with aquatic mammals and fish, crocodiles are slow swimmers probably because of constraints imposed by muscle performance and unsteady forces opposing forward movement. Nonetheless, the kinematic efficiency of aquatic locomotion in crocodiles is comparable to that of fully aquatic mammals, and it is considerably greater than that of semi-aquatic mammals.

An EM-based Semi-Parametric Mixture Model Approach to the Regression Analysis of Competing-Risks Data

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright (C) 2003 John Wiley Sons, Ltd.