Probabilistic modelling of CO2 corrosion laboratory data using neural networks

The present paper addresses two major concerns that were identified when developing neural network based prediction models and which can limit their wider applicability in the industry. The first problem is that it appears neural network models are not readily available to a corrosion engineer. Therefore the first part of this paper describes a neural network model of CO2 corrosion which was created using a standard commercial software package and simple modelling strategies. It was found that such a model was able to capture practically all of the trends noticed in the experimental data with acceptable accuracy. This exercise has proven that a corrosion engineer could readily develop a neural network model such as the one described below for any problem at hand, given that sufficient experimental data exist. This applies even in the cases when the understanding of the underlying processes is poor. The second problem arises from cases when all the required inputs for a model are not known or can be estimated with a limited degree of accuracy. It seems advantageous to have models that can take as input a range rather than a single value. One such model, based on the so-called Monte Carlo approach, is presented. A number of comparisons are shown which have illustrated how a corrosion engineer might use this approach to rapidly test the sensitivity of a model to the uncertainities associated with the input parameters. (C) 2001 Elsevier Science Ltd. All rights reserved.

Optimal input states and feedback for interferometric phase estimation

We derive optimal N-photon two-mode input states for interferometric phase measurements. Under canonical measurements the phase variance scales as N-2 for these states, as compared to N-1 or N-1/2 for states considered bq previous authors. We prove, that it is not possible to realize the canonical measurement by counting photons in the outputs of the interferometer, even if an adjustable auxiliary phase shift is allowed in the interferometer. However. we introduce a feedback algorithm based on Bayesian inference to control this auxiliary phase shift. This makes the measurement close to a canonical one, with a phase variance scaling slightly above N-2. With no feedback, the best result (given that the phase to be measured is completely unknown) is a scaling of N-1. For optimal input states having up to four photons, our feedback scheme is the best possible one, but for higher photon numbers more complicated schemes perform marginally better.

Breeding for low input conditions and consequences for participatory plant breeding: Examples from tropical maize and wheat

Participatory plant breeding (PPB) has been suggested as an effective alternative to formal plant breeding (FPB) as a breeding strategy for achieving productivity gains under low input conditions. With genetic progress through PPB and FPB being determined by the same genetic variables, the likelihood of success of PPB approaches applied in low input target conditions was analyzed using two case studies from FPB that have resulted in significant productivity gains under low input conditions: (1) breeding tropical maize for low input conditions by CIMMYT, and (2) breeding of spring wheat for the highly variable low input rainfed farming systems in Australia. In both cases, genetic improvement was an outcome of long-term investment in a sustained research effort aimed at understanding the detail of the important environmental constraints to productivity and the plant requirements for improved adaptation to the identified constraints, followed up by the design and continued evaluation of efficient breeding strategies. The breeding strategies used differed between the two case studies but were consistent in their attention to the key determinants of response to selection: (1) ensuring adequate sources of genetic variation and high selection pressures for the important traits at all stages of the breeding program, (2) use of experimental procedures to achieve high levels of heritability in the breeding trials, and (3) testing strategies that achieved a high genetic correlation between performance of germplasm in the breeding trials and under on-farm conditions. The implications of the outcomes from these FPB case studies for realizing the positive motivations for adopting PPB strategies are discussed with particular reference for low input target environment conditions.

Tracks of Change - the changing value commitments of non-profit organisations

If nonprofit organisations are moving towards more market oriented ways of operating, is this changing the traditional meanings and value of commitments associated with their activities? This article discusses the findings of a research project conducted by the University of Queensland into the impact that changes in government policies are having on the community services sector, in particular disability services. The values and belief systems traditionally associated with the sector were found to be fundamentally unaltered.

Estimating economic relationships subject to firm- and time-varying equality and inequality constraints

Applied econometricians often fail to impose economic regularity constraints in the exact form economic theory prescribes. We show how the Singular Value Decomposition (SVD) Theorem and Markov Chain Monte Carlo (MCMC) methods can be used to rigorously impose time- and firm-varying equality and inequality constraints. To illustrate the technique we estimate a system of translog input demand functions subject to all the constraints implied by economic theory, including observation-varying symmetry and concavity constraints. Results are presented in the form of characteristics of the estimated posterior distributions of functions of the parameters. Copyright (C) 2001 John Wiley Sons, Ltd.

Relationships between crude protein and mineral concentrations in alfalfa and value of alfalfa silage as a mineral source for periparturient cows

One hundred and eight samples from three cultivars of alfalfa were obtained from three cuttings in 1996-1998 to evaluate the relationship between crude protein (CP) and mineral concentrations of alfalfa with cutting and maturation. The CP content drastically decreased from 27.9 to 11.4% on DM with maturity. Highly positive correlations were observed between CP and K in the first and the second cutting of alfalfa. The Ca content remained almost constant throughout the growth period. Four multiparous Holstein cows were assigned an alfalfa silage diet or an orchardgrass silage diet from 3 weeks prepartum to 1 week postpartum to examine the effect on the mineral balance. In the prepartum and postpartum diet, the roughage to concentrate ratio was 70:30 and 50:50, with alfalfa being 50 and 100% of the roughage, respectively. The alfalfa contained 1.93% of K. No metabolic disorders occurred, but the body weight decreased drastically from 1 to 6 days postpartum with each diet because of the high milk production immediately after the parturition. Positive retention of N, Ca, P, Mg, and K was observed prepartum, whereas the cows had negative N and mineral retention from 2 to 4 days postpartum. The Ca and P absorption, and Mg retention of cows with the alfalfa diet were higher than with the grass diet. The plasma Ca and inorganic P were not affected by diet, but the plasma PTH at parturition and plasma hydroxyproline from 1 week prepartum to 1 week postpartum were higher with the alfalfa diet. These results suggest that the low K alfalfa is suitable not only to prevent the incidence of milk fever but also to increase Ca, P and Mg utilization of periparturient cows, but the mineral supplementation is needed for the postpartum cows immediately after the parturition. (C) 2001 Elsevier Science B.V. All rights reserved.

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

The nutritive value of Rhodes grass (Chloris gayana) when treated with CaO, NaOH or a microbial inoculant and offered to dairy heifers as big-bale silage

A series of laboratory and animal studies examined the use of chemical and biological agents to enhance the digestibility of Rhodes grass (grass) cut at 60 (young) and 100 (mature) days of regrowth and ensiled as big round bales. The treatments included an untreated control (C), a microbial inoculant (I), NaOH, CaO and NaOH plus inoculant (NaOH + I). Inoculant was grown anaerobically, using a starter culture of rumen fluid from cattle given Rhodes grass. Treatments C, 1, NaOH, NaOH + I, were offered separately to twelve dairy heifers, in a 3 X 4 randomized complete block design, repeated twice for each grass silage. C and I had substantial mould growth, compared with no visible mould in NaOH or NaOH + 1. CaO treatment was effective in preventing mould growth, but had little effect on the chemical composition and in sacco digestibility of mature grass silage. NaOH reduced NDF content and increased in sacco digestibility (P < 0.05) but not the in vivo digestibility (P > 0.05) of both mature- and young-grass silage. The effects of other treatments on nutritive value were non-significant at both stages of maturity. NaOH increased the intake of mature-grass silage by 24-26% (P < 0.05), but had little effect on the intake of young-grass silage (P > 0.05). Treatment I consistently reduced grass silage intake (P < 005) for young-grass silage. The findings of these studies show that treating mature Rhodes grass with NaOH will improve its nutritive value and reduce mould growth in conserved herbage. However none of the treatments in this study had any consistently positive effects on the in vivo nutritive value or storage quality of young-grass silage.