Estimation of cosmological parameters from neutral hydrogen observations of the post-reionization epoch

The emission from neutral hydrogen (HI) clouds in the post-reionization era (z <= 6), too faint to be individually detected, is present as a diffuse background in all low frequency radio observations below 1420MHz. The angular and frequency fluctuations of this radiation (similar to 1 mK) are an important future probe of the large-scale structures in the Universe. We show that such observations are a very effective probe of the background cosmological model and the perturbed Universe. In our study we focus on the possibility of determining the redshift-space distortion parameter beta, coordinate distance r(nu), and its derivative with redshift r(nu)('). Using reasonable estimates for the observational uncertainties and configurations representative of the ongoing and upcoming radio interferometers, we predict parameter estimation at a precision comparable with supernova Ia observations and galaxy redshift surveys, across a wide range in redshift that is only partially accessed by other probes. Future HI observations of the post-reionization era present a new technique, complementing several existing ones, to probe the expansion history and to elucidate the nature of the dark energy.

Improved Approach for Analyzing Bromophenols in Seafood Using Stable Isotope Dilution Analysis in Combination with SPME

An analytical method for the measurement of five naturally occurring bromophenols of sensory relevance in seafood (barramundi and prawns) is presented. The method combines simultaneous distillation−extraction followed by alkaline back extraction of a hexane extract and subsequent acetylation of the bromophenols. Analysis of the bromophenol acetates was accomplished by headspace solid phase microextraction and gas chromatography−mass spectrometry using selected ion monitoring. The addition of 13C6 bromophenol stable isotope internal standards for each of the five congeners studied permitted the accurate quantitation of 2-bromophenol, 4-bromophenol, 2,6-dibromophenol, 2,4-dibromophenol, and 2,4,6-tribromophenol down to a limit of quantification of 0.05 ng/g of fish flesh. The method indicated acceptable precision and repeatability and excellent linearity over the typical concentration range of these compounds in seafood (0.5−50 ng/g). The analytical method was applied to determine the concentration of bromophenols in a range of farmed and wild barramundi and prawns and was also used to monitor bromophenol uptake in a pilot feeding trial.

Rice molecular breeding laboratories in the genomics era: Current status and future considerations

Using DNA markers in plant breeding with marker-assisted selection (MAS) could greatly improve the precision and efficiency of selection, leading to the accelerated development of new crop varieties. The numerous examples of MAS in rice have prompted many breeding institutes to establish molecular breeding labs. The last decade has produced an enormous amount of genomics research in rice, including the identification of thousands of QTLs for agronomically important traits, the generation of large amounts of gene expression data, and cloning and characterization of new genes, including the detection of single nucleotide polymorphisms. The pinnacle of genomics research has been the completion and annotation of genome sequences for indica and japonica rice. This information-coupled with the development of new genotyping methodologies and platforms, and the development of bioinformatics databases and software tools-provides even more exciting opportunities for rice molecular breeding in the 21st century. However, the great challenge for molecular breeders is to apply genomics data in actual breeding programs. Here, we review the current status of MAS in rice, current genomics projects and promising new genotyping methodologies, and evaluate the probable impact of genomics research. We also identify critical research areas to "bridge the application gap" between QTL identification and applied breeding that need to be addressed to realize the full potential of MAS, and propose ideas and guidelines for establishing rice molecular breeding labs in the postgenome sequence era to integrate molecular breeding within the context of overall rice breeding and research programs.

Flow of metal in constrained plane-strain extrusion forging- Part II

With many innovations in process technology, forging is establishing itself as a precision manufacturing process: as forging is used to produce complex shapes in difficult materials, it requires dies of complex configuration of high strength and of wear-resistant materials. Extensive research and development work is being undertaken, internationally, to analyse the stresses in forging dies and the flow of material in forged components. Identification of the location, size and shape of dead-metal zones is required for component design. Further, knowledge of the strain distribution in the flowing metal indicates the degree to which the component is being work hardened. Such information is helpful in the selection of process parameters such as dimensional allowances and interface lubrication, as well as in the determination of post-forging operations such as heat treatment and machining. In the presently reported work the effect of aperture width and initial specimen height on the strain distribution in the plane-strain extrusion forging of machined lead billets is observed: the distortion of grids inscribed on the face of the specimen gives the strain distribution. The stress-equilibrium approach is used to optimise a model of flow in extrusion forging, which model is found to be effective in estimating the size of the dead-metal zone. The work carried out so far indicates that the methodology of using the stress-equilibrium approach to develop models of flow in closed-die forging can be a useful tool in component, process and die design.

Accelerating Pseudo-Marginal MCMC using Gaussian Processes

Pseudo-marginal methods such as the grouped independence Metropolis-Hastings (GIMH) and Markov chain within Metropolis (MCWM) algorithms have been introduced in the literature as an approach to perform Bayesian inference in latent variable models. These methods replace intractable likelihood calculations with unbiased estimates within Markov chain Monte Carlo algorithms. The GIMH method has the posterior of interest as its limiting distribution, but suffers from poor mixing if it is too computationally intensive to obtain high-precision likelihood estimates. The MCWM algorithm has better mixing properties, but less theoretical support. In this paper we propose to use Gaussian processes (GP) to accelerate the GIMH method, whilst using a short pilot run of MCWM to train the GP. Our new method, GP-GIMH, is illustrated on simulated data from a stochastic volatility and a gene network model.

Grower group case study on new farming practices in the Herbert region, Australia

Growers working together have proven to be a successful method for improving the utilization of farm resources and accelerating the adoption of the Sugar Yield Decline Joint Venture principles (SYDJV). The Pinnacle Precision Farming Group was formed in 2004 with the aim to bring together the ideas, knowledge and resources of growers in the Herbert region. Along with their common interest in controlled traffic, minimal tillage and crop rotations, the grower group utilize a farm machinery contractor to provide some of their major farming operations. This paper provides an insight into the changes made by the Pinnacle Precision Farming Group and their journey to adopt the new farming system practices. This paper also details the changes made by the group machinery contractor and a comparison of the old and new farming systems used by a group member. A focus point of the document is the impact of the new farming system on the economic, social and environmental components of the farming business. Analysis of the new farming system with a legume crop rotation revealed an increase in the farm gross margin by AU$22 024 and, in addition, a reduction in tractor operation time by 38% across the whole farm. This represents a return on marginal capital of 14.68 times the original capital outlay required by the group member. Using the new farming system without a legume crop will still improve the group members whole of farm gross margin by AU$6 839 and reduce tractor operation time by 43% across the whole farm. The Pinnacle Precision Farming group recognize the need to continually improve their farming businesses and believe that the new farming system principles are critical for the long term viability of the industry. [U$1 = AU$1.19].

A fuzzy logic based dynamic wave model inversion algorithm for canal regulation

A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint-Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Timing of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms.

Nutritional management for reproductive efficiency

Nutrition influences reproductive efficiency and the survival of lambs and weaners but the costs of supplementary feeding or maintaining low stocking rates are not justified by the resulting income from higher lamb weaning rates and reduced weaner mortality. The current practice of segmenting the ewe flock using ultrasound scanning to determine the number of foetuses still results in groups of ewes with a wide range of condition scores and with widely differing nutritional requirements. This report describes an approach to precision management of pregnant ewes and weaners that is based on the e-sheep platform of technologies and uses computer-directed drafting for nutritional management of individual animals and walk-through weighing to monitor changing nutritional status. It is estimated that the cost of feeding a thousand-ewe flock can be reduced from $14,000 for feeding all animals to $3300 for targeted feeding of 25% of ewes requiring additional nutrition and 20% of weaners at risk of dying. The cost of the targeted feeding strategy is more than justified by the value of additional 12-month-old animals, which is $9000. The e-sheep precision nutrition system is not attractive to industry at this stage because of the cost of the e-sheep infrastructure, the perceived complexity of the technology and the requirement for further research, but it is expected to be a commercial option within three years.

Swarm intelligence-based solver for parameter estimation of laboratory through-diffusion transport of contaminants

Theoretical approaches are of fundamental importance to predict the potential impact of waste disposal facilities on ground water contamination. Appropriate design parameters are generally estimated be fitting theoretical models to data gathered from field monitoring or laboratory experiments. Transient through-diffusion tests are generally conducted in the laboratory to estimate the mass transport parameters of the proposed barrier material. Thes parameters are usually estimated either by approximate eye-fitting calibration or by combining the solution of the direct problem with any available gradient-based techniques. In this work, an automated, gradient-free solver is developed to estimate the mass transport parameters of a transient through-diffusion model. The proposed inverse model uses a particle swarm optimization (PSO) algorithm that is based on the social behavior of animals searching for food sources. The finite difference numerical solution of the forward model is integrated with the PSO algorithm to solve the inverse problem of parameter estimation. The working principle of the new solver is demonstrated and mass transport parameters are estimated from laboratory through-diffusion experimental data. An inverse model based on the standard gradient-based technique is formulated to compare with the proposed solver. A detailed comparative study is carried out between conventional methods and the proposed solver. The present automated technique is found to be very efficient and robust. The mass transport parameters are obtained with great precision.

Weed management in wide-row cropping systems: a review of current practices and risks for Australian farming systems.

Growing agricultural crops in wide row spacings has been widely adopted to conserve water, to control pests and diseases, and to minimise problems associated with sowing into stubble. The development of herbicide resistance combined with the advent of precision agriculture has resulted in a further reason for wide row spacings to be adopted: weed control. Increased row spacing enables two different methods of weed control to be implemented with non-selective chemical and physical control methods utilised in the wide inter-row zone, with or without selective chemicals used on the on-row only. However, continual application of herbicides and tillage on the inter-row zone brings risks of herbicide resistance, species shifts and/or changes in species dominance, crop damage, increased costs, yield losses, and more expensive weed management technology.

Automatic ICD-10 classification of cancers from free-text death certificates

Objective Death certificates provide an invaluable source for cancer mortality statistics; however, this value can only be realised if accurate, quantitative data can be extracted from certificates – an aim hampered by both the volume and variable nature of certificates written in natural language. This paper proposes an automatic classification system for identifying cancer related causes of death from death certificates. Methods Detailed features, including terms, n-grams and SNOMED CT concepts were extracted from a collection of 447,336 death certificates. These features were used to train Support Vector Machine classifiers (one classifier for each cancer type). The classifiers were deployed in a cascaded architecture: the first level identified the presence of cancer (i.e., binary cancer/nocancer) and the second level identified the type of cancer (according to the ICD-10 classification system). A held-out test set was used to evaluate the effectiveness of the classifiers according to precision, recall and F-measure. In addition, detailed feature analysis was performed to reveal the characteristics of a successful cancer classification model. Results The system was highly effective at identifying cancer as the underlying cause of death (F-measure 0.94). The system was also effective at determining the type of cancer for common cancers (F-measure 0.7). Rare cancers, for which there was little training data, were difficult to classify accurately (F-measure 0.12). Factors influencing performance were the amount of training data and certain ambiguous cancers (e.g., those in the stomach region). The feature analysis revealed a combination of features were important for cancer type classification, with SNOMED CT concept and oncology specific morphology features proving the most valuable. Conclusion The system proposed in this study provides automatic identification and characterisation of cancers from large collections of free-text death certificates. This allows organisations such as Cancer Registries to monitor and report on cancer mortality in a timely and accurate manner. In addition, the methods and findings are generally applicable beyond cancer classification and to other sources of medical text besides death certificates.

Comprehensive Path-sensitive Data-flow Analysis

Data-flow analysis is an integral part of any aggressive optimizing compiler. We propose a framework for improving the precision of data-flow analysis in the presence of complex control-flow. W initially perform data-flow analysis to determine those control-flow merges which cause the loss in data-flow analysis precision. The control-flow graph of the program is then restructured such that performing data-flow analysis on the resulting restructured graph gives more precise results. The proposed framework is both simple, involving the familiar notion of product automata, and also general, since it is applicable to any forward data-flow analysis. Apart from proving that our restructuring process is correct, we also show that restructuring is effective in that it necessarily leads to more optimization opportunities. Furthermore, the framework handles the trade-off between the increase in data-flow precision and the code size increase inherent in the restructuring. We show that determining an optimal restructuring is NP-hard, and propose and evaluate a greedy strategy. The framework has been implemented in the Scale research compiler, and instantiated for the specific problem of Constant Propagation. On the SPECINT 2000 benchmark suite we observe an average speedup of 4% in the running times over Wegman-Zadeck conditional constant propagation algorithm and 2% over a purely path profile guided approach.

Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index—The canopy chlorophyll content index (CCCI).

Varying the spatial distribution of applied nitrogen (N) fertilizer to match demand in crops has been shown to increase profits in Australia. Better matching the timing of N inputs to plant requirements has been shown to improve nitrogen use efficiency and crop yields and could reduce nitrous oxide emissions from broad acre grains. Farmers in the wheat production area of south eastern Australia are increasingly splitting N application with the second timing applied at stem elongation (Zadoks 30). Spectral indices have shown the ability to detect crop canopy N status but a robust method using a consistent calibration that functions across seasons has been lacking. One spectral index, the canopy chlorophyll content index (CCCI) designed to detect canopy N using three wavebands along the "red edge" of the spectrum was combined with the canopy nitrogen index (CNI), which was developed to normalize for crop biomass and correct for the N dilution effect of crop canopies. The CCCI-CNI index approach was applied to a 3-year study to develop a single calibration derived from a wheat crop sown in research plots near Horsham, Victoria, Australia. The index was able to predict canopy N (g m-2) from Zadoks 14-37 with an r2 of 0.97 and RMSE of 0.65 g N m-2 when dry weight biomass by area was also considered. We suggest that measures of N estimated from remote methods use N per unit area as the metric and that reference directly to canopy %N is not an appropriate method for estimating plant concentration without first accounting for the N dilution effect. This approach provides a link to crop development rather than creating a purely numerical relationship. The sole biophysical input, biomass, is challenging to quantify robustly via spectral methods. Combining remote sensing with crop modelling could provide a robust method for estimating biomass and therefore a method to estimate canopy N remotely. Future research will explore this and the use of active and passive sensor technologies for use in precision farming for targeted N management.

Using harvest statistics to monitor temporal variation in kangaroo density and harvest rate

Management of the commercial harvest of kangaroos relies on quotas set annually as a proportion of regular estimates of population size. Surveys to generate these estimates are expensive and, in the larger states, logistically difficult; a cheaper alternative is desirable. Rainfall is a disappointingly poor predictor of kangaroo rate of increase in many areas, but harvest statistics (sex ratio, carcass weight, skin size and animals shot per unit time) potentially offer cost-effective indirect monitoring of population abundance (and therefore trend) and status (i.e. under-or overharvest). Furthermore, because harvest data are collected continuously and throughout the harvested areas, they offer the promise of more intensive and more representative coverage of harvest areas than aerial surveys do. To be useful, harvest statistics would need to have a close and known relationship with either population size or harvest rate. We assessed this using longterm (11-22 years) data for three kangaroo species (Macropus rufus, M. giganteus and M. fuliginosus) and common wallaroos (M. robustus) across South Australia, New South Wales and Queensland. Regional variation in kangaroo body size, population composition, shooter efficiency and selectivity required separate analyses in different regions. Two approaches were taken. First, monthly harvest statistics were modelled as a function of a number of explanatory variables, including kangaroo density, harvest rate and rainfall. Second, density and harvest rate were modelled as a function of harvest statistics. Both approaches incorporated a correlated error structure. Many but not all regions had relationships with sufficient precision to be useful for indirect monitoring. However, there was no single relationship that could be applied across an entire state or across species. Combined with rainfall-driven population models and applied at a regional level, these relationships could be used to reduce the frequency of aerial surveys without compromising decisions about harvest management.

Evidence-based perspective on CP rehabilitation : Reviews on physiotherapy, physiotherapy-related motor-based interventions and orthotic devices

This thesis utilises an evidence-based approach to critically evaluate and summarize effectiveness research on physiotherapy, physiotherapy-related motor-based interventions and orthotic devices in children and adolescents with cerebral palsy (CP). It aims to assess the methodological challenges of the systematic reviews and trials, to evaluate the effectiveness of interventions in current use, and to make suggestions for future trials Methods: Systematic reviews were searched from computerized bibliographic databases up to August 2007 for physiotherapy and physiotherapy-related interventions, and up to May 2003 for orthotic devices. Two reviewers independently identified, selected, and assessed the quality of the reviews using the Overview Quality Assessment Questionnaire complemented with decision rules. From a sample of 14 randomized controlled trials (RCT) published between January 1990 and June 2003 we analysed the methods of sampling, recruitment, and comparability of groups; defined the components of a complex intervention; identified outcome measures based on the International Classification of Functioning, Disability and Health (ICF); analysed the clinical interpretation of score changes; and analysed trial reporting using a modified 33-item CONSORT (Consolidated Standards of Reporting Trials) checklist. The effectiveness of physiotherapy and physiotherapy-related interventions in children with diagnosed CP was evaluated in a systematic review of randomised controlled trials that were searched from computerized databases from January 1990 up to February 2007. Two reviewers independently assessed the methodological quality, extracted the data, classified the outcomes using the ICF, and considered the level of evidence according to van Tulder et al. (2003). Results: We identified 21 reviews on physiotherapy and physiotherapy-related interventions and five on orthotic devices. These reviews summarized 23 or 5 randomised controlled trials and 104 or 27 observational studies, respectively. Only six reviews were of high quality. These found some evidence supporting strength training, constraint-induced movement therapy or hippotherapy, and insufficient evidence on comprehensive interventions. Based on the original studies included in the reviews on orthotic devices we found some short-term effects of lower limb casting on passive range of movement, and of ankle-foot orthoses on equinus walk. Long term effects of lower limb orthoses have not been studied. Evidence of upper limb casting or orthoses is conflicting. In the sample of 14 RCTs, most trials used simple randomisation, complemented with matching or stratification, but only three specified the concealed allocation. Numerous studies provided sufficient details on the components of a complex intervention, but the overlap of outcome measures across studies was poor and the clinical interpretation of observed score changes was mostly missing. Almost half (48%) of the applicable CONSORT-based items (range 28 32) were reported adequately. Most reporting inadequacies were in outcome measures, sample size determination, details of the sequence generation, allocation concealment and implementation of the randomization, success of assessor blinding, recruitment and follow-up dates, intention-to-treat analysis, precision of the effect size, co-interventions, and adverse events. The systematic review identified 22 trials on eight intervention categories. Four trials were of high quality. Moderate evidence of effectiveness was established for upper extremity treatments on attained goals, active supination and developmental status, and of constraint-induced therapy on the amount and quality of hand use and new emerging behaviours. Moderate evidence of ineffectiveness was found for strength training's effect on walking speed and stride length. Conflicting evidence was found for strength training's effect on gross motor function. For the other intervention categories the evidence was limited due to the low methodological quality and the statistically insignificant results of the studies. Conclusions: The high-quality reviews provide both supportive and insufficient evidence on some physiotherapy interventions. The poor quality of most reviews calls for caution, although most reviews drew no conclusions on effectiveness due to the poor quality of the primary studies. A considerable number of RCTs of good to fair methodological and reporting quality indicate that informative and well-reported RCTs on complex interventions in children and adolescents with CP are feasible. Nevertheless, methodological improvement is needed in certain areas of the trial design and performance, and the trial authors are encouraged to follow the CONSORT criteria. Based on RCTs we established moderate evidence for some effectiveness of upper extremity training. Due to limitations in methodological quality and variations in population, interventions and outcomes, mostly limited evidence on the effectiveness of most physiotherapy interventions is available to guide clinical practice. Well-designed trials are needed, especially for focused physiotherapy interventions.