The Building Partnerships Program: An Approach to Community-based Learning for Medical Students in Australia

The Building Partnerships Program at the University of Queensland, Australia seeks to address the dual challenge of preparing doctors who are responsive to the community while providing a meaningful context for social sciences learning. Through partnerships with a diverse range of community agencies, the program offers students opportunities to gain non-clinical perspectives on health and illness through structured learning activities including: family visits; community agency visits and attachments; and interview training. Students learn first-hand about psychosocial influences on health and how people manage health problems on a day-to-day basis. They also gain insights into the work of community agencies and how they as future doctors might work in partnership with them to enhance patient care. We outline the main components of the program, identify challenges and successes from student and community agency perspectives, and consider areas that invite further development.

Application of a simplified method based on regular regime approach to determine the effective moisture diffusivity of mixture of low molecular weight sugars and maltodextrin during desorption

The binary diffusivities of water in low molecular weight sugars; fructose, sucrose and a high molecular weight carbohydrate; maltodextrin (DE 11) and the effective diffusivities of water in mixtures of these sugars (sucrose, glucose, fructose) and maltodextrin (DE 11) were determined using a simplified procedure based on the Regular Regime Approach. The effective diffusivity of these mixtures exhibited both the concentration and molecular weight dependence. Surface stickiness was observed in all samples during desorption, with fructose exhibiting the highest and maltodextrin the lowest. (C) 2002 Elsevier Science Ltd. All rights reserved.

UML approach to the generation of test sequences for Java-based concurrent systems

Starting with a UML specification that captures the underlying functionality of some given Java-based concurrent system, we describe a systematic way to construct, from this specification, test sequences for validating an implementation of the system. The approach is to first extend the specification to create UML state machines that directly address those aspects of the system we wish to test. To be specific, the extended UML state machines can capture state information about the number of waiting threads or the number of threads blocked on a given object. Using the SAL model checker we can generate from the extended UML state machines sequences that cover all the various possibilities of events and states. These sequences can then be directly transformed into test sequences suitable for input into a testing tool such as ConAn. As an illustration, the methodology is applied to generate sequences for testing a Java implementation of the producer-consumer system. © 2005 IEEE

Learning to play Pac-Man: An evolutionary, rule-based approach

Pac-Man is a well-known, real-time computer game that provides an interesting platform for research. We describe an initial approach to developing an artificial agent that replaces the human to play a simplified version of Pac-Man. The agent is specified as a simple finite state machine and ruleset. with parameters that control the probability of movement by the agent given the constraints of the maze at some instant of time. In contrast to previous approaches, the agent represents a dynamic strategy for playing Pac-Man, rather than a pre-programmed maze-solving method. The agent adaptively "learns" through the application of population-based incremental learning (PBIL) to adjust the agents' parameters. Experimental results are presented that give insight into some of the complexities of the game, as well as highlighting the limitations and difficulties of the representation of the agent.

Approach to designing rotating drum bioreactors for solid-state fermentation on the basis of dimensionless design factors

The development of large-scale solid-stale fermentation (SSF) processes is hampered by the lack of simple tools for the design of SSF bioreactors. The use of semifundamental mathematical models to design and operate SSF bioreactors can be complex. In this work, dimensionless design factors are used to predict the effects of scale and of operational variables on the performance of rotating drum bioreactors. The dimensionless design factor (DDF) is a ratio of the rate of heat generation to the rate of heat removal at the time of peak heat production. It can be used to predict maximum temperatures reached within the substrate bed for given operational variables. Alternatively, given the maximum temperature that can be tolerated during the fermentation, it can be used to explore the combinations of operating variables that prevent that temperature from being exceeded. Comparison of the predictions of the DDF approach with literature data for operation of rotating drums suggests that the DDF is a useful tool. The DDF approach was used to explore the consequences of three scale-up strategies on the required air flow rates and maximum temperatures achieved in the substrate bed as the bioreactor size was increased on the basis of geometric similarity. The first of these strategies was to maintain the superficial flow rate of the process air through the drum constant. The second was to maintain the ratio of volumes of air per volume of bioreactor constant. The third strategy was to adjust the air flow rate with increase in scale in such a manner as to maintain constant the maximum temperature attained in the substrate bed during the fermentation. (C) 2000 John Wiley & Sons, Inc.

An object-oriented neural network approach to short-term traffic forecasting

This paper discusses an object-oriented neural network model that was developed for predicting short-term traffic conditions on a section of the Pacific Highway between Brisbane and the Gold Coast in Queensland, Australia. The feasibility of this approach is demonstrated through a time-lag recurrent network (TLRN) which was developed for predicting speed data up to 15 minutes into the future. The results obtained indicate that the TLRN is capable of predicting speed up to 5 minutes into the future with a high degree of accuracy (90-94%). Similar models, which were developed for predicting freeway travel times on the same facility, were successful in predicting travel times up to 15 minutes into the future with a similar degree of accuracy (93-95%). These results represent substantial improvements on conventional model performance and clearly demonstrate the feasibility of using the object-oriented approach for short-term traffic prediction. (C) 2001 Elsevier Science B.V. All rights reserved.

Teen Triple P: A universal approach to reducing risk factors for behavioural and emotional problems in adolescents at the transition to high school

Teen Triple P is a multilevel system of intervention that is designed to provide parents with specific strategies to promote the positive development of their teenage children as they make the transition into high school and through puberty. The program is based on a combination of education about the developmental needs of adolescents, skills training to improve communication and problem-solving, plus specific modules to deal with common problems encountered by parents and adolescents that can escalate into major conflict and violence. It is designed to increase the engagement of parents of adolescent and pre-adolescent children by providing them with easy access to evidencebased parenting advice and support. This paper presents data collected as part of a survey of over 1400 students in first year high school at 9 Brisbane schools. The survey instrument was constructed to obtain students' reports about behaviour which is known to be associated with their health and wellbeing, and also on the extent to which their parents promoted or discouraged such behaviour at home, at school, and in their social and recreational activities in the wider community. Selected data from the survey were extracted and presented to parents at a series of parenting seminars held at the schools to promote appropriate parenting of teenagers. The objectives were to provide parents with accurate data about teenagers' behaviour, and about teenagers' reports of how they perceived their parents' behaviour. Normative data on parent and teenager behaviour will be presented from the survey as well as psychometric data relating to the reliability and validity of this new measure. Implications of this strategy for increasing parent engagement in parenting programs that aim to reduce behavioural and emotional problems in adolescents will be discussed.

Molecular epidemiology: A multidisciplinary approach to understanding parasitic zoonoses

Sound application of molecular epidemiological principles requires working knowledge of both molecular biological and epidemiological methods. Molecular tools have become an increasingly important part of studying the epidemiology of infectious agents. Molecular tools have allowed the aetiological agent within a population to be diagnosed with a greater degree of efficiency and accuracy than conventional diagnostic tools. They have increased the understanding of the pathogenicity, virulence, and host-parasite relationships of the aetiological agent, provided information on the genetic structure and taxonomy of the parasite and allowed the zoonotic potential of previously unidentified agents to be determined. This review describes the concept of epidemiology and proper study design, describes the array of currently available molecular biological tools and provides examples of studies that have integrated both disciplines to successfully unravel zoonotic relationships that would otherwise be impossible utilising conventional diagnostic tools. The current limitations of applying these tools, including cautions that need to be addressed during their application are also discussed.(c) 2005 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

A semi-empirical approach to optimise the quantity of drying aids required to spray dry sugar-rich foods

A semi-empirical linear equation has been developed to optimise the amount of maltodextrin additive (DE 6) required to successfully spray dry a sugar-rich product on the basis of its composition. Based on spray drying experiments, drying index values for individual sugars (sucrose, glucose, frutose) and citric acid were determined, and us;ng these index values an equation for model mixtures of these components was established. This equation has been tested with two sugar-rich natural products, pineapple juice and honey. The relationship was found to be valid for these products.