'Explain in plain English' questions revisited : data structures problems

Recent studies have linked the ability of novice (CS1) programmers to read and explain code with their ability to write code. This study extends earlier work by asking CS2 students to explain object-oriented data structures problems that involve recursion. Results show a strong correlation between ability to explain code at an abstract level and performance on code writing and code reading test problems for these object-oriented data structures problems. The authors postulate that there is a common set of skills concerned with reasoning about programs that explains the correlation between writing code and explaining code. The authors suggest that an overly exclusive emphasis on code writing may be detrimental to learning to program. Non-code writing learning activities (e.g., reading and explaining code) are likely to improve student ability to reason about code and, by extension, improve student ability to write code. A judicious mix of code-writing and code-reading activities is recommended.

Nutrition screening and assessment in Parkinson's disease : a comparison of methods

Background & Aims Nutrition screening and assessment enable early identification of malnourished people and those at risk of malnutrition. Appropriate assessment tools assist with informing and monitoring nutrition interventions. Tool choice needs to be appropriate to the population and setting. Methods Community-dwelling people with Parkinson’s disease (>18 years) were recruited. Body mass index (BMI) was calculated from weight and height. Participants were classified as underweight according to World Health Organisation (WHO) (≤18.5kg/m2) and age specific (<65 years,≤18.5kg/m2; ≥65 years,≤23.5kg/m2) cut-offs. The Mini-Nutritional Assessment (MNA) screening (MNA-SF) and total assessment scores were calculated. The Patient-Generated Subjective Global Assessment (PG-SGA), including the Subjective Global Assessment (SGA), was performed. Sensitivity, specificity, positive predictive value, negative predictive value and weighted kappa statistic of each of the above compared to SGA were determined. Results Median age of the 125 participants was 70.0(35-92) years. Age-specific BMI (Sn 68.4%, Sp 84.0%) performed better than WHO (Sn 15.8%, Sp 99.1%) categories. MNA-SF performed better (Sn 94.7%, Sp 78.3%) than both BMI categorisations for screening purposes. MNA had higher specificity but lower sensitivity than PG-SGA (MNA Sn 84.2%, Sp 87.7%; PG-SGA Sn 100.0%, Sp 69.8%). Conclusions BMI lacks sensitivity to identify malnourished people with Parkinson’s disease and should be used with caution. The MNA-SF may be a better screening tool in people with Parkinson’s disease. The PG-SGA performed well and may assist with informing and monitoring nutrition interventions. Further research should be conducted to validate screening and assessment tools in Parkinson’s disease.  

Species-specific homing mechanisms of human prostate cancer metastasis in tissue engineered bone

The development of effective therapeutic strategies against prostate cancer bone metastases has been impeded by the lack of adequate animal models that are able to recapitulate the biology of the disease in humans. Bioengineered approaches allow researchers to create sophisticated experimentally and physiologically relevant in vivo models to study interactions between cancer cells and their microenvironment under reproducible conditions. The aim of this study was to engineer a morphologically and functionally intact humanized organ bone which can serve as a homing site for human prostate cancer cells. Transplantation of biodegradable tubular composite scaffolds seeded with human mesenchymal progenitor cells and loaded with rhBMP-7 resulted in the development of a chimeric bone construct including a large number of human mesenchymal cells which were shown to be metabolically active and capable of producing extracellular matrix components. Micro-CT analysis demonstrated that the newly formed ossicle recapitulated the morphological features of a physiological organ bone with a trabecular network surrounded by a cortex-like outer structure. This microenvironment was supportive of the lodgement and maintenance of murine haematopoietic cell clusters, thus mimicking a functional organ bone. Bioluminescence imaging demonstrated that luciferase-transduced human PC3 cells reproducibly homed to the humanized tissue engineered bone constructs, proliferated, and developed macro-metastases. This model allows the analysis of interactions between human prostate cancer cells and a functional humanized bone organ within an immuno-incompetent murine host. The system can serve as a reproducible platform to study effects of therapeutics against prostate cancer bone metastases within a humanized microenvironment.

Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.

Mining specific features for acquiring user information needs

Term-based approaches can extract many features in text documents, but most include noise. Many popular text-mining strategies have been adapted to reduce noisy information from extracted features; however, text-mining techniques suffer from low frequency. The key issue is how to discover relevance features in text documents to fulfil user information needs. To address this issue, we propose a new method to extract specific features from user relevance feedback. The proposed approach includes two stages. The first stage extracts topics (or patterns) from text documents to focus on interesting topics. In the second stage, topics are deployed to lower level terms to address the low-frequency problem and find specific terms. The specific terms are determined based on their appearances in relevance feedback and their distribution in topics or high-level patterns. We test our proposed method with extensive experiments in the Reuters Corpus Volume 1 dataset and TREC topics. Results show that our proposed approach significantly outperforms the state-of-the-art models.

A novel process of group-oriented question reduction for rule-based recommendation websites

Several websites utilise a rule-base recommendation system, which generates choices based on a series of questionnaires, for recommending products to users. This approach has a high risk of customer attrition and the bottleneck is the questionnaire set. If the questioning process is too long, complex or tedious; users are most likely to quit the questionnaire before a product is recommended to them. If the questioning process is short; the user intensions cannot be gathered. The commonly used feature selection methods do not provide a satisfactory solution. We propose a novel process combining clustering, decisions tree and association rule mining for a group-oriented question reduction process. The question set is reduced according to common properties that are shared by a specific group of users. When applied on a real-world website, the proposed combined method outperforms the methods where the reduction of question is done only by using association rule mining or only by observing distribution within the group.

Overview of the ShARe/CLEF eHealth Evaluation Lab 2013

Discharge summaries and other free-text reports in healthcare transfer information between working shifts and geographic locations. Patients are likely to have difficulties in understanding their content, because of their medical jargon, non-standard abbreviations,and ward-specific idioms. This paper reports on an evaluation lab with an aim to support the continuum of care by developing methods and resources that make clinical reports in English easier to understand for patients, and which helps them in finding information related to their condition.

The Cultural Atlas of Australia

An online interactive map and associated database including textual extracts and audiovisual material of film/novel/play locations in Australia.

Use of hospital emergency departments by immigrants from non-English speaking backgrounds in Queensland

This study aimed to examine the use of hospital emergency departments and to investigate the level of satisfaction with the emergency department service among patients from a non-English-speaking background compared to those of patients from an English-speaking background in Queensland. The findings of this study might inform health professionals and policy planners to develop educational interventions and policies to ensure equitable use of emergency services among the populations.

The ‘Indigenous Australian’ theme in the Australian Curriculum English : necessary or not?

On Friday 10 January 2014 Education Minister Christopher Pyne formally announced a review of the inaugural Australian curriculum. In his three and half minute televised justification, Pyne (2014) identified a number of criticisms of the national curriculum document, including the ‘necessity to have themes’ of ‘Australia’s place in Asia, Indigenous Australia and sustainability’. It is the second of these themes that we consider as ALEA’s Hot Topic for March 2014. We respond to Pyne’s momentary musing of the necessity of the ‘Indigenous Australian’ theme in the Australian Curriculum with a particular focus on the discipline of English. In the nomenclature of the Australian Curriculum, Assessment and Reporting Authority’s Australian Curriculum (ACARA, 2013), we are of course referring to the ‘cross curriculum priority’ of ‘Aboriginal and Torres Strait Islander histories and cultures’.

Literacy in the Middle Years : Learning from Collaborative Classroom Research

Literacy in the Middle Years: Learning from Collaborative Classroom Research, showcases teachers' innovative literacy work across the curriculum. Classroom practice, teacher thinking and collaborative research are highlighted in ways of working with new curricula and rapidly changing literacy modes and platforms. Connections with place, critical engagement with digital literacies, using polymedia with EAL/D learners, and subject-specific literacies are detailed in teachers' stories of practice. Teacher wellbeing, for a sustainable workforce, underpins the case studies, aimed at equipping 'change ready' teachers with positive examples of literacy approaches and inquiry in practice.

Development of Mobile Web App "ESP" for DeepBlue to interrogate how an audience is thinking

DeepBlue is much more than just an orchestra. Their innovative approach to audience engagement led it to develop ESP, their Electronic Show Programme web app which allows for real-time (synchronous) and delayed (asynchronous) audience interaction, customer feedback and research. The show itself is driven invisibly by a music technology operating system (currently QUT's Yodel) that allows them to adapt to a wide range of performance venues and varied types of presentation. DeepBlue's community engagement program has enabled over 5,500 young musicians and community choristers to participate in professional productions, it is also a cornerstone of DeepBlue's successful business model. You can view the ESP mobile web app at m.deepblue.net.au if you view this and only the landing page is active, there is not a show taking place or imminent. ESP prototype has already been used for 18 months. Imagine knowing what your audience really thinks – in real time so you can track their feelings and thoughts through the show. This tool has been developed and used by the performing group DeepBlue since late 2012 in Australia and Asia (even translated into Vietnamese). It has mostly superseded DeepBlue's SMS realtime communication during a show. It enables an event presenter or performance group to take the pulse of an audience through a series of targeted questions that can be anonymous or attributed. This will help build better, long-lasting, and more meaningful relationships with groups and individuals in the community. This can take place on a tablet, mobile phone or future platforms. There are three organisations trialling it so far.

Stepwise engineering of a Pichia pastoris D-amino acid oxidase whole cell catalyst

Trigonopsis variabilis D-amino acid oxidase (TvDAO) is a well characterized enzyme used for cephalosporin C conversion on industrial scale. However, the demands on the enzyme with respect to activity, operational stability and costs also vary with the field of application. Processes that use the soluble enzyme suffer from fast inactivation of TvDAO while immobilized oxidase preparations raise issues related to expensive carriers and catalyst efficiency. Therefore, oxidase preparations that are more robust and active than those currently available would enable a much broader range of economically viable applications of this enzyme in fine chemical syntheses. A multi-step engineering approach was chosen here to develop a robust and highly active Pichia pastoris TvDAO whole-cell biocatalyst. As compared to the native T. variabilis host, a more than seven-fold enhancement of the intracellular level of oxidase activity was achieved in P. pastoris through expression optimization by codon redesign as well as efficient subcellular targeting of the enzyme to peroxisomes. Multi copy integration further doubled expression and the specific activity of the whole cell catalyst. From a multicopy production strain, about 1.3 x 103 U/g wet cell weight (wcw) were derived by standard induction conditions feeding pure methanol. A fed-batch cultivation protocol using a mixture of methanol and glycerol in the induction phase attenuated the apparent toxicity of the recombinant oxidase to yield final biomass concentrations in the bioreactor of >or= 200 g/L compared to only 117 g/L using the standard methanol feed. Permeabilization of P. pastoris using 10% isopropanol yielded a whole-cell enzyme preparation that showed 49% of the total available intracellular oxidase activity and was notably stabilized (by three times compared to a widely used TvDAO expressing Escherichia coli strain) under conditions of D-methionine conversion using vigorous aeration. Stepwise optimization using a multi-level engineering approach has delivered a new P. pastoris whole cell TvDAO biocatalyst showing substantially enhanced specific activity and stability under operational conditions as compared to previously reported preparations of the enzyme. The production of the oxidase through fed-batch bioreactor culture and subsequent cell permeabilization is high-yielding and efficient. Therefore this P. pastoris catalyst has been evaluated for industrial purposes.

Geometric sensitivity of patient-specific finite element models of the spine to variability in user-selected anatomical landmarks

Software to create individualised finite element (FE) models of the osseoligamentous spine using pre-operative computed tomography (CT) data-sets for spinal surgery patients has recently been developed. This study presents a geometric sensitivity analysis of this software to assess the effect of intra-observer variability in user-selected anatomical landmarks. User-selected landmarks on the osseous anatomy were defined from CT data-sets for three scoliosis patients and these landmarks were used to reconstruct patient-specific anatomy of the spine and ribcage using parametric descriptions. The intra-observer errors in landmark co-ordinates for these anatomical landmarks were calculated. FE models of the spine and ribcage were created using the reconstructed anatomy for each patient and these models were analysed for a loadcase simulating clinical flexibility assessment. The intra-observer error in the anatomical measurements was low in comparison to the initial dimensions, with the exception of the angular measurements for disc wedge and zygapophyseal joint (z-joint) orientation and disc height. This variability suggested that CT resolution may influence such angular measurements, particularly for small anatomical features, such as the z-joints, and may also affect disc height. The results of the FE analysis showed low variation in the model predictions for spinal curvature with the mean intra-observer variability substantially less than the accepted error in clinical measurement. These findings demonstrate that intra-observer variability in landmark point selection has minimal effect on the subsequent FE predictions for a clinical loadcase.

Selecting volatility forecasting models for portfolio allocation purposes

Techniques for evaluating and selecting multivariate volatility forecasts are not yet understood as well as their univariate counterparts. This paper considers the ability of different loss functions to discriminate between a set of competing forecasting models which are subsequently applied in a portfolio allocation context. It is found that a likelihood-based loss function outperforms its competitors, including those based on the given portfolio application. This result indicates that considering the particular application of forecasts is not necessarily the most effective basis on which to select models.