Haplotype analysis of two recurrent CDKN2A mutations in 10 melanoma families : evidence for common founders and independent mutations

Germ-line mutations in CDKN2A have been shown to predispose to cutaneous malignant melanoma. We have identified 2 new melanoma kindreds which carry a duplication of a 24bp repeat present in the 5' region of CDKN2A previously identified in melanoma families from Australia and the United States. This mutation has now been reported in 5 melanoma families from 3 continents: Europe, North America, and Australasia. The M53I mutation in exon 2 of CDKN2A has also been documented in 5 melanoma families from Australia and North America. The aim of this study was to determine whether the occurrence of the mutations in these families from geographically diverse populations represented mutation hotspots within CDKN2A or were due to common ancestors. Haplotypes of 11 microsatellite markers flanking CDKN2A were constructed in 5 families carrying the M53I mutation and 5 families carrying the 24bp duplication. There were some differences in the segregating haplotypes due primarily to recombinations and mutations within the short tandem-repeat markers; however, the data provide evidence to indicate that there were at least 3 independent 24bp duplication events and possibly only 1 original M53I mutation. This is the first study to date which indicates common founders in melanoma families from different continents.

Pedagogy of introductory computer programming : a people-first approach

Students struggle with learning to program. In recent years, not only has there been a dramatic drop in the number of students enrolling in IT and Computer Science courses, but attrition from these courses continues to be significant. Introductory programming subjects traditionally have high failure rates and as they tend to be core to IT and Computer Science courses can be a road block for many students to their university studies. Is programming really that difficult — or are there other barriers to learning that have a serious and detrimental effect on student progression? In-class experiments were conducted in introductory programming units to confirm our hypothesis that that pair-programming would benefit students' learning to program. We investigated the social and cultural barriers to learning programming by questioning students' perceptions of confidence, difficulty and enjoyment of programming. The results of paired and non-paired students were compared to determine the effect of pair-programming on learning outcomes. Both the empirical and anecdotal results of our experiments strongly supported our hypothesis.

The future of the internet economy : addressing challenges facing the implementation of the Australian national broadband network

Innovation is vital for the future of Australia.s internet economy. Innovations rely on businesses. ability to innovate. Businesses. ability to innovate relies on their employees. The more these individual end users engage in the internet economy, the better businesses. engagement will be. The less these individual end users engage, the less likely a business is to engage and innovate. This means, for the internet economy to function at its fullest potential, it is essential that individual Australians have the capacity to engage with it and participate in it. The Australian federal government is working to facilitate the internet economy through policies, legislation and practices that implement high-speed broadband. The National Broadband Network will be a vital tool for Australia.s internet economy. Its .chief importance¡® is that it will provide faster internet access speeds that will facilitate access to internet services and content. However, an appropriate infrastructure and internet speed is only part of the picture. As the Organisation for Economic Co-operation and Development identified, appropriate government policies are also needed to ensure that vital services are more accessible by consumers. The thesis identifies essential theories and principles underpinning the internet economy and from which the concept of connectedness is developed. Connectedness is defined as the ability of end users to connect with internet content and services, other individuals and organisations, and government. That is, their ability to operate in the internet economy. The NBN will be vital in ensuring connectedness into the future. What is not currently addressed by existing access regimes is how to facilitate end user access capacity and participation. The thesis concludes by making recommendations to the federal government as to what the governing principles of the Australian internet economy should include in order to enable individual end user access capacity.

The use of semantic priming as a paradigm for the detection of faking on self-report psychological tests

It is recognised that individuals do not always respond honestly when completing psychological tests. One of the foremost issues for research in this area is the inability to detect individuals attempting to fake. While a number of strategies have been identified in faking, a commonality of these strategies is the latent role of long term memory. Seven studies were conducted in order to examine whether it is possible to detect the activation of faking related cognitions using a lexical decision task. Study 1 found that engagement with experiential processing styles predicted the ability to fake successfully, confirming the role of associative processing styles in faking. After identifying appropriate stimuli for the lexical decision task (Studies 2A and 2B), Studies 3 to 5 examined whether a cognitive state of faking could be primed and subsequently identified, using a lexical decision task. Throughout the course of these studies, the experimental methodology was increasingly refined in an attempt to successfully identify the relevant priming mechanisms. The results were consistent and robust throughout the three priming studies: faking good on a personality test primed positive faking related words in the lexical decision tasks. Faking bad, however, did not result in reliable priming of negative faking related cognitions. To more completely address potential issues with the stimuli and the possible role of affective priming, two additional studies were conducted. Studies 6A and 6B revealed that negative faking related words were more arousing than positive faking related words, and that positive faking related words were more abstract than negative faking related words and neutral words. Study 7 examined whether the priming effects evident in the lexical decision tasks occurred as a result of an unintentional mood induction while faking the psychological tests. Results were equivocal in this regard. This program of research aligned the fields of psychological assessment and cognition to inform the preliminary development and validation of a new tool to detect faking. Consequently, an implicit technique to identify attempts to fake good on a psychological test has been identified, using long established and robust cognitive theories in a novel and innovative way. This approach represents a new paradigm for the detection of individuals responding strategically to psychological testing. With continuing development and validation, this technique may have immense utility in the field of psychological assessment.

The teacher as reflexive professional : making visible the excluded discourse in teacher standards

In the current climate of accountability, political manoeuvring, changing curriculum, increasingly diverse student cohorts and community expectations, teachers, more than ever, need to develop the skills and abilities to be reflective and reflexive practitioners. This study examines national teacher professional standards from Australia and the UK to identify the extent to which reflexivity is embedded in key policy documents that are intended to guide the work of teachers in those countries. Using Margaret Archer's theories of reflexivity and morphogenesis, and methods of critical discourse analysis, we argue that these blueprints for teachers’ work exclude reflexivity as an essential and overarching discourse of teacher professionalism.

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

Toward a shared understanding of competency in programming : an invitation to the BABELnot Project

The ICT degrees in most Australian universities have a sequence of up to three programming subjects, or units. BABELnot is an ALTC-funded project that will document the academic standards associated with those three subjects in the six participating universities and, if possible, at other universities. This will necessitate the development of a rich framework for describing the learning goals associated with programming. It will also be necessary to benchmark exam questions that are mapped onto this framework. As part of the project, workshops are planned for ACE 2012, ICER 2012 and ACE 2013, to elicit feedback from the broader Australasian computing education community, and to disseminate the project’s findings. The purpose of this paper is to introduce the project to that broader Australasian computing education community and to invite their active participation.

Livable housing design: Is it likely to work?

The need for accessible housing in Australia is acute. Both government and the community service sector recognise the importance of well designed accessible housing to optimise the integration of older people and people with disability, to encourage a prudent use of scarce health and community services and to enhance the liveability of our cities. In 2010, the housing industry, negotiated with the Australian Government and community representatives to adopt a nationally consistent voluntary code (Livable Housing Design) and a strategy to provide minimal level of accessibility in all new housing by 2020. Evidence from the implementation of such programs in the United Kingdom and USA, however, serves to question whether this aspirational goal can be achieved through voluntary codes. Minimal demand at the point of new sale, and problems in the production of housing to the required standards have raised questions regarding the application of program principles in the context of a voluntary code. In addressing the latter issue, this paper presents early findings from the analysis of qualitative interviews conducted with developers, builders and designers in various housing contexts. It identifies their “logics in use” in the production of housing in response to Livable Housing Design’s voluntary code and indicates factors that are likely to assist and impede the attainment of the 2020 aspirational goal.

Things just got really serious : coping in crisis

You have chosen to enter a profession that can afford you a wonderfully rich career. It is a role that has many areas of speciality and many opportunities and challenges in communicating with a vast array of people including patients, families, peers, and management. Inherent in the role are all sorts of potential stressors such as not having the equipment you need at a time you think you crucially need it, working with people you find difficult, shift work, lack of staffing, overcrowding, and the list is sometimes seemingly endless. But there are also obvious advantages to your role such as meeting a large variety of people, helping people to recover, to feel comfortable in your care and supporting families, patients and colleagues. This brings me to the two primary points to this chapter. The first point of this chapter is to understand that sometimes the challenges you may face in the health arena overwhelm your initial understanding of your capacity to cope. That is to say, there will likely be times when you feel overwhelmed or even distraught in the face of a particular situation. The second point is that these same overwhelming experiences can provide a catalyst for you to grow as a human being; to develop beyond the person you perceived yourself to be beforehand. According to Aaron Antonovsky (1985), stress is inherent in the human condition, but further to that, in your role, there is a very high possibility of traumatic experiences as well.

Rethinking comprehension and strategy use in second language listening instruction

In second language classrooms, listening is gaining recognition as an active element in the processes of learning and using a second language. Currently, however, much of the teaching of listening prioritises comprehension without sufficient emphasis on the skills and strategies that enhance learners’ understanding of spoken language. This paper presents an argument for rethinking the emphasis on comprehension and advocates augmenting current teaching with an explicit focus on strategies. Drawing on the literature, the paper provides three models of strategy instruction for the teaching and development of listening skills. The models include steps for implementation that accord with their respective approaches to explicit instruction. The final section of the paper synthesises key points from the models as a guide for application in the second language classroom. The premise underpinning the paper is that the teaching of strategies can provide learners with active and explicit measures for managing and expanding their listening capacities, both in the learning and ‘real world’ use of a second language.

A prospective surveillance model for rehabilitation for women with breast cancer

Background: The current model of care for breast cancer is focused on disease treatment followed by ongoing recurrence surveillance. This approach lacks attention to the patients’ physical and functional well-being. Breast cancer treatment sequelae can lead to physical impairments and functional limitations. Common impairments include pain, fatigue, upper extremity dysfunction, lymphedema, weakness, joint arthralgia, neuropathy, weight gain, cardiovascular effects, and osteoporosis. Evidence supports prospective surveillance for early identification and treatment as a means to prevent or mitigate many of these concerns. Purpose: This paper proposes a prospective surveillance model for physical rehabilitation and exercise that can be integrated with disease treatment to create a more comprehensive approach to survivorship health care. The goals of the model are to promote surveillance for common physical impairments and functional limitations associated with breast cancer treatment, to provide education to facilitate early identification of impairments, to introduce rehabilitation and exercise intervention when physical impairments are identified and to promote and support physical activity and exercise behaviors through the trajectory of disease treatment and survivorship. Methods: The model is the result of a multi-disciplinary meeting of research and clinical experts in breast cancer survivorship and representatives of relevant professional and advocacy organizations. Outcomes: The proposed model identifies time points during breast cancer care for assessment of and education about physical impairments. Ultimately, implementation of the model may influence incidence and severity of breast cancer treatment related physical impairments. As such, the model seeks to optimize function during and following treatment and positively influence a growing survivorship community.

Comparison of three-dimensional profiles over time

In this paper, we describe an analysis for data collected on a three-dimensional spatial lattice with treatments applied at the horizontal lattice points. Spatial correlation is accounted for using a conditional autoregressive model. Observations are defined as neighbours only if they are at the same depth. This allows the corresponding variance components to vary by depth. We use the Markov chain Monte Carlo method with block updating, together with Krylov subspace methods, for efficient estimation of the model. The method is applicable to both regular and irregular horizontal lattices and hence to data collected at any set of horizontal sites for a set of depths or heights, for example, water column or soil profile data. The model for the three-dimensional data is applied to agricultural trial data for five separate days taken roughly six months apart in order to determine possible relationships over time. The purpose of the trial is to determine a form of cropping that leads to less moist soils in the root zone and beyond.We estimate moisture for each date, depth and treatment accounting for spatial correlation and determine relationships of these and other parameters over time.

A Bayesian analysis of an agricultural field trial with three spatial dimensions

Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.