Using clusters of computers for large QU-GENE simulation experiments

The QU-GENE Computing Cluster (QCC) is a hardware and software solution to the automation and speedup of large QU-GENE (QUantitative GENEtics) simulation experiments that are designed to examine the properties of genetic models, particularly those that involve factorial combinations of treatment levels. QCC automates the management of the distribution of components of the simulation experiments among the networked single-processor computers to achieve the speedup.

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.

Development of educational policy and early intervention for learning difficulties in Australia: In the case of Queensland

This paper aims to describe the historical outline and current development of the educational policy for students with learning difficulties in Australia, focusing especially on the state of Queensland. In order to develop educational policy of learning difficulities at the state level, the concept of learning difficulities had been discussed until the middle of the 1970's. Receiving the submissions which argued strongly against a diagnostically-oriented definition of learning disabilities, the Select Comittee concluded that there was much conceptual confusion regarding the definition and cause of learining difficulties that might take many years to resolve. Despite that it was recongnised that action was needed to assist children by looking at their "total learning environmerit", and recommended the development of an educational policy for students with learning difficulties. During 1980's, support teachers for students with learning difficulties were employed in many schools. Scince the early 1980's support teachers have been making their efforts in regular classrooms rather than in the resource rooms. Their roles have been to help students with learning difficulties using effective and specific skills, and to consult with the regular classroom teacher in solving the problems related to learning difficulties in regular classes. Currently, the support system for students with learning difficulties has been employed to organize a more systematic and broader approach in Queensland based on the accountability of schools. In the context of enphasizing literacy and numeracy, a systematic whole school approach and particular programs, such as the Year 2 Diagnostic Net and Reading Recovery, have been introduced into the educational system for early identification and early intervention.

Improving pain management by nurses: A pilot peer intervention program

Significant pain continues to be reported by many hospitalized patients despite the numerous and varied educational programs developed and implemented to improve pain management. A theoretically based Peer Intervention Program was designed from a predictive model to address nurses' beliefs, attitudes, subjective norms, self-efficacy, perceived control and intentions in the management of pain with p.r.n. (as required) narcotic analgesia. The pilot study of this program utilized a quasi-experimental pre-post test design with a patient intervention, nurse and patient intervention and control conditions consisting of 24, 18 and 19 nurses, respectively. One week after the intervention, significant differences were found between the nurse and patient condition and the two other conditions in beliefs, self-efficacy, perceived control, positive trend in attitudes, subjective norms and intentions. The most positive aspects of the program were supportive interactive discussions with peers and an awareness and understanding of beliefs and attitudes and their roles in behavior.

Brief opportunistic intervention: The role of psychologists in initiating self-change amongst problem drinkers

Excessive consumption of alcohol is a serious public health problem. While intensive treatments are suitable for those who are physically dependent on alcohol, they are not cost-effective options for the vast majority of problem drinkers who are not dependent. There is good evidence that brief interventions are effective in reducing overall alcohol consumption, alcohol-related problems, and health-care utilisation among nondependent problem drinkers. Psychologists are in an ideal position to opportunistically detect people who drink excessively and to offer them brief advice to reduce their drinking. In this paper we outline the process involved in providing brief opportunistic screening and intervention for problem drinkers. We also discuss methods that psychologists can employ if a client is not ready to reduce drinking, or is ambivalent about change. Depending on the client's level of motivation to change, psychologists can engage in either an education-clarification approach, a commitment-enhancement approach, or a skills-training approach. Routine engagement in opportunistic intervention is an important public-health approach to reducing alcohol-related harm in the community.

Evolutionary experiments on mate recognition in the Drosophila serrata species complex

It is becoming increasingly apparent that at least some aspects of the evolution of mate recognition may be amenable to manipulation in evolutionary experiments. Quantitative genetic analyses that focus on the genetic consequences of evolutionary processes that result in mate recognition evolution may eventually provide an understanding of the genetic basis of the process of speciation. We review a series of experiments that have attempted to determine the genetic basis of the response to natural and sexual selection on mate recognition in the Drosophila serrata species complex. The genetic basis of mate recognition has been investigated at three levels: (1) between the species of D. serrata and D. birchii using interspecific hybrids, (2) between populations of D. serrata that are sympatric and allopatric with respect to D. birchii, and (3) within populations of D. serrata. These experiments suggest that it may be possible to use evolutionary experiments to observe important events such as the reinforcement of mate recognition, or the generation of the genetic associations that are central to many sexual selection models.

On the importance function in splitting simulation

The splitting method is a simulation technique for the estimation of very small probabilities. In this technique, the sample paths are split into multiple copies, at various stages in the simulation. Of vital importance to the efficiency of the method is the Importance Function (IF). This function governs the placement of the thresholds or surfaces at which the paths are split. We derive a characterisation of the optimal IF and show that for multi-dimensional models the natural choice for the IF is usually not optimal. We also show how nearly optimal splitting surfaces can be derived or simulated using reverse time analysis. Our numerical experiments illustrate that by using the optimal IF, one can obtain a significant improvement in simulation efficiency.