The potential of combining phenomenography, variation theory and threshold concepts to inform curriculum design in higher education

This chapter describes an innovative method of curriculum design that is based on combining phenomenographic research, and the associated variation theory of learning, with the notion of disciplinary threshold concepts to focus specialised design attention on the most significant and difficult parts of the curriculum. The method involves three primary stages: (i) identification of disciplinary concepts worthy of intensive curriculum design attention, using the criteria for threshold concepts; (ii) action research into variation in students’ understandings/misunderstandings of those concepts, using phenomenography as the research approach; (iii) design of learning activities to address the poorer understandings identified in the second stage, using variation theory as a guiding framework. The curriculum design method is inherently theory and evidence based. It was developed and trialed during a two-year project funded by the Australian Learning and Teaching Council, using physics and law disciplines as case studies. Disciplinary teachers’ perceptions of the impact of the method on their teaching and understanding of student learning were profound. Attempts to measure the impact on student learning were less conclusive; teachers often unintentionally deviated from the design when putting it into practice for the first time. Suggestions for improved implementation of the method are discussed.

Inferring diffusion in single live cells at the single-molecule level

The movement of molecules inside living cells is a fundamental feature of biological processes. The ability to both observe and analyse the details of molecular diffusion in vivo at the single-molecule and single-cell level can add significant insight into understanding molecular architectures of diffus- ing molecules and the nanoscale environment in which the molecules diffuse. The tool of choice for monitoring dynamic molecular localization in live cells is fluorescence microscopy, especially so combining total internal reflection fluorescence with the use of fluorescent protein (FP) reporters in offering exceptional imaging contrast for dynamic processes in the cell mem- brane under relatively physiological conditions compared with competing single-molecule techniques. There exist several different complex modes of diffusion, and discriminating these from each other is challenging at the mol- ecular level owing to underlying stochastic behaviour. Analysis is traditionally performed using mean square displacements of tracked particles; however, this generally requires more data points than is typical for single FP tracks owing to photophysical instability. Presented here is a novel approach allowing robust Bayesian ranking of diffusion processes to dis-criminate multiple complex modes probabilistically. It is a computational approach that biologists can use to understand single-molecule features in live cells.

Small RNA sequencing of potato leafroll virus-infected plants reveals an additional subgenomic RNA encoding a sequence-specific RNA-binding protein

Potato leafroll virus (PLRV) is a positive-strand RNA virus that generates subgenomic RNAs (sgRNA) for expression of 3' proximal genes. Small RNA (sRNA) sequencing and mapping of the PLRV-derived sRNAs revealed coverage of the entire viral genome with the exception of four distinctive gaps. Remarkably, these gaps mapped to areas of PLRV genome with extensive secondary structures, such as the internal ribosome entry site and 5' transcriptional start site of sgRNA1 and sgRNA2. The last gap mapped to ~500. nt from the 3' terminus of PLRV genome and suggested the possible presence of an additional sgRNA for PLRV. Quantitative real-time PCR and northern blot analysis confirmed the expression of sgRNA3 and subsequent analyses placed its 5' transcriptional start site at position 5347 of PLRV genome. A regulatory role is proposed for the PLRV sgRNA3 as it encodes for an RNA-binding protein with specificity to the 5' of PLRV genomic RNA. © 2013.

Expression patterns of vascular-specific promoters RolC and Sh in transgenic potatoes and their use in engineering PLRV-resistant plants

The expression patterns of GUS fusion constructs driven by the Agrobacterium rhizogenes RolC and the maize Sh (Shrunken: sucrose synthase-1) promoters were examined in transgenic potatoes (cv. Atlantic). RolC drove high-level gene expression in phloem tissue, bundle sheath cells and vascular parenchyma, but not in xylem or non-vascular tissues. Sh expression was exclusively confined to phloem tissue. Potato leafroll luteovirus (PLRV) replicates only in phloem tissues, and we show that when RolC is used to drive expression of the PLRV coat protein gene, virus-resistant lines can be obtained. In contrast, no significant resistance was observed when the Sh promoter was used.

Pooled biological specimens for human biomonitoring of environmental chemicals : opportunities and limitations

Biomonitoring has become the ‘gold standard’ in assessing chemical exposures, and plays an important role in risk assessment. The pooling of biological specimens – combining multiple individual specimens into a single sample – can be used in biomonitoring studies to monitor levels of exposure and identify exposure trends, or to identify susceptible populations in a cost-effective manner. Pooled samples provide an estimate of central tendency, and may also reveal information about variation within the population. The development of a pooling strategy requires careful consideration of the type and number of samples collected, the number of pools required, and the number of specimens to combine per pool in order to maximize the type and robustness of the data. Creative pooling strategies can be used to explore exposure-outcome associations, and extrapolation from other larger studies can be useful in identifying elevated exposures in specific individuals. The use of pooled specimens is advantageous as it saves significantly on analytical costs, may reduce the time and resources required for recruitment, and in certain circumstances, allows quantification of samples approaching the limit of detection. In addition, use of pooled samples can provide population estimates while avoiding ethical difficulties that may be associated with reporting individual results.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Reconsidering the agency of a privately appointed receiver and manager in three specific circumstances

Where a secured lender elects to appoint a receiver and manager, the appointment document standardly provides for the receiver and manager to act as the agent of the debtor. This article considers the significance of this agency in the context of three specific issues that have the potential to arise in the receivership of a corporate borrower across all Australian jurisdictions.

Separating shadows

This practice-led research is in the field of dance creation and performance. The dancer, unlike many artists from different fields, has to contend with the added complexity of being a creative tool. Grove states, ‘..they are the phenomenon of self-creation twice over, being both the artist and the work of art’ (2005, 44). A dancer’s success relies on the quality of their instrument and their ability to reliably employ it in the creative act (Jowitt 2001a). The traditional rehearsal studio is the creative meeting place for dance artists. A liminal space with specific spatial, temporal and personal considerations: a space fraught with uncertainty and vulnerability, ripe with potential. If harnessed, the creative potential inherent in vulnerability, experienced as increased sensitivity and openness (Press 2002), can facilitate new ways of investigating and doing. This research investigated ways in which dancers prepare themselves during the act of creation and rehearsal within the studio, for the public presentation of a site-specific dance work. Navigating the complexities inherent in performing site-specific dance work is best achieved through the development of a connection with the site during the creation of the work. This is achieved through the provision of rehearsals within the site and ensures seamless replication of rehearsal qualities from studio to non-traditional site. This research received funding and support from the Australia Council for the Arts, Arts Queensland, Brisbane Festival, Kelvin Grove Urban Village, Besen Family Foundation, Korean Culture Arts Foundation and the Australia Korea Foundation. It was presented in the Brisbane Festival, 2006. http://www.accentedbody.com/projects/accented-body

Slicing big data - Twitter, gambling and time sensitive information

Big Data presents many challenges related to volume, whether one is interested in studying past datasets or, even more problematically, attempting to work with live streams of data. The most obvious challenge, in a ‘noisy’ environment such as contemporary social media, is to collect the pertinent information; be that information for a specific study, tweets which can inform emergency services or other responders to an ongoing crisis, or give an advantage to those involved in prediction markets. Often, such a process is iterative, with keywords and hashtags changing with the passage of time, and both collection and analytic methodologies need to be continually adapted to respond to this changing information. While many of the data sets collected and analyzed are preformed, that is they are built around a particular keyword, hashtag, or set of authors, they still contain a large volume of information, much of which is unnecessary for the current purpose and/or potentially useful for future projects. Accordingly, this panel considers methods for separating and combining data to optimize big data research and report findings to stakeholders. The first paper considers possible coding mechanisms for incoming tweets during a crisis, taking a large stream of incoming tweets and selecting which of those need to be immediately placed in front of responders, for manual filtering and possible action. The paper suggests two solutions for this, content analysis and user profiling. In the former case, aspects of the tweet are assigned a score to assess its likely relationship to the topic at hand, and the urgency of the information, whilst the latter attempts to identify those users who are either serving as amplifiers of information or are known as an authoritative source. Through these techniques, the information contained in a large dataset could be filtered down to match the expected capacity of emergency responders, and knowledge as to the core keywords or hashtags relating to the current event is constantly refined for future data collection. The second paper is also concerned with identifying significant tweets, but in this case tweets relevant to particular prediction market; tennis betting. As increasing numbers of professional sports men and women create Twitter accounts to communicate with their fans, information is being shared regarding injuries, form and emotions which have the potential to impact on future results. As has already been demonstrated with leading US sports, such information is extremely valuable. Tennis, as with American Football (NFL) and Baseball (MLB) has paid subscription services which manually filter incoming news sources, including tweets, for information valuable to gamblers, gambling operators, and fantasy sports players. However, whilst such services are still niche operations, much of the value of information is lost by the time it reaches one of these services. The paper thus considers how information could be filtered from twitter user lists and hash tag or keyword monitoring, assessing the value of the source, information, and the prediction markets to which it may relate. The third paper examines methods for collecting Twitter data and following changes in an ongoing, dynamic social movement, such as the Occupy Wall Street movement. It involves the development of technical infrastructure to collect and make the tweets available for exploration and analysis. A strategy to respond to changes in the social movement is also required or the resulting tweets will only reflect the discussions and strategies the movement used at the time the keyword list is created — in a way, keyword creation is part strategy and part art. In this paper we describe strategies for the creation of a social media archive, specifically tweets related to the Occupy Wall Street movement, and methods for continuing to adapt data collection strategies as the movement’s presence in Twitter changes over time. We also discuss the opportunities and methods to extract data smaller slices of data from an archive of social media data to support a multitude of research projects in multiple fields of study. The common theme amongst these papers is that of constructing a data set, filtering it for a specific purpose, and then using the resulting information to aid in future data collection. The intention is that through the papers presented, and subsequent discussion, the panel will inform the wider research community not only on the objectives and limitations of data collection, live analytics, and filtering, but also on current and in-development methodologies that could be adopted by those working with such datasets, and how such approaches could be customized depending on the project stakeholders.

Sex-specific compromised bone healing in female rats might be associated with a decrease in mesenchymal stem cell quantity

Introduction The clinically known importance of patient sex as a major risk factor for compromised bone healing is poorly reflected in animal models. Consequently, the underlying cellular mechanisms remain elusive. Because mesenchymal stem cells (MSCs) are postulated to regulate tissue regeneration and give rise to essential differentiated cell types, they may contribute to sex-specific differences in bone healing outcomes. Methods We investigated sex-specific variations in bone healing and associated differences in MSC populations. A 1.5 mm osteotomy gap in the femora of 8 male and 8 female 12-month-old Sprague-Dawley rats was stabilized by an external fixator. Healing was analyzed in terms of biomechanical testing, bridging and callus size over time (radiography at 2, 4, and 6 weeks after surgery), and callus volume and geometry by μCT at final follow-up. MSCs were obtained from bone marrow samples of an age-matched group of 12 animals (6 per gender) and analyzed for numbers of colony-forming units (CFUs) and their capacity to differentiate and proliferate. The proportion of senescent cells was determined by β-galactosidase staining. Results Sex-specific differences were indicated by a compromised mechanical competence of the callus in females compared with males (maximum torque at failure, p = 0.028). Throughout the follow-up, the cross-sectional area of callus relative to bone was reduced in females (p ≤ 0.01), and the bridging of callus was delayed (p 2weeks = 0.041). μCT revealed a reduced callus size (p = 0.003), mineralization (p = 0.003) and polar moment of inertia (p = 0.003) in female animals. The female bone marrow contained significantly fewer MSCs, represented by low CFU numbers in both femora and tibiae (p femur = 0.017, p tibia = 0.010). Functional characteristics of male and female MSCs were similar. Conclusion Biomechanically compromised and radiographically delayed bone formation were distinctive in female rats. These differences were concomitant with a reduced number of MSCs, which may be causative for the suboptimal bone healing.

Second harmonic generation and multiphoton microscopic detection of collagen without the need for species specific antibodies

High-resolution, high-contrast, three-dimensional images of live cell and tissue architecture can be obtained using second harmonic generation (SHG), which comprises non-absorptive frequency changes in an excitation laser line. SHG does not require any exogenous antibody or fluorophore labeling, and can generate images from unstained sections of several key endogenous biomolecules, in a wide variety of species and from different types of processed tissue. Here, we examined normal control human skin sections and human burn scar tissues using SHG on a multi-photon microscope (MPM). Examination and comparison of normal human skin and burn scar tissue demonstrated a clear arrangement of fibers in the dermis, similar to dermal collagen fiber signals. Fluorescence-staining confirmed the MPM-SHG collagen colocalization with antibody staining for dermal collagen type-I but not fibronectin or elastin. Furthermore, we were able to detect collagen MPM-SHG signal in human frozen sections as well as in unstained paraffin embedded tissue sections that were then compared with hematoxylin and eosin staining in the identical sections. This same approach was also successful in localizing collagen in porcine and ovine skin samples, and may be particularly important when species-specific antibodies may not be available. Collectively, our results demonstrate that MPM SHG-detection is a useful tool for high resolution examination of collagen architecture in both normal and wounded human, porcine and ovine dermal tissue.

Innovation through action research in environmental education : from project to praxis

This thesis is a work-in-progress that articulates my research journey based on the development of a curriculum innovation in environmental education. This journey had two distinct, but intertwined phases: action research based fieldwork, conducted collaboratively, to create a whole school approach to environmental education curriculum planning; and a phase of analysis and reflection based on the emerging findings, as I sought to create personal "living educational theory" about change and innovation. A key stimulus for the study was the perceived theory-practice gap in environmental education, which is often presented in the literature as a criticism of teachers for failing to achieve the values and action objectives of critical environmental education. Hence, many programs and projects are considered to be superficial and inconsequential in terms of their ability to seriously address environmental issues. The intention of this study was to work with teachers in a project that would be an exemplar of critical environmental education. This would be in the form of a whole school "learnscaping" curriculum in a primary school whereby the schoolgrounds would be utilised for interdisciplinary critical environment education. Parallel with the three cycles of action research in this project, my research objectives were to identify and comment upon the factors that influence the generation of successful educational innovation. It was anticipated that the project would be a collaboration involving me, as researcher-facilitator, and many of the teachers in the school as active participants. As the project proceeded through its action cycles, however, it became obvious that the goal of developing a critical environmental education curriculum, and the use of highly participatory processes, were unrealistic. Institutional and organisational rigidities in education generally, teachers' day-to-day work demands, and the constant juggle of work, family and other responsibilities for all participants acted as significant constraints. Consequently, it became apparent that the learnscaping curriculum would not be the hoped-for exemplar. Progress was slow and, at times, the project was in danger of stalling permanently. While the curriculum had some elements of critical environmental education, these were minor and not well spread throughout the school. Overall, the outcome seemed best described as a "small win"; perhaps just another example of the theory-practice gap that I had hoped this project would bridge. Towards the project's end, however, my continuing reflection led to an exploration of chaos/complexity theory which gave new meaning to the concept of a "small win". According to this theory, change is not the product of linear processes applied methodically in purposeful and diligent ways, but emerges from serendipitous events that cannot be planned for, or forecast in advance. When this perspective of change is applied to human organisations - in this study, a busy school - the context for change is recognised not as a stable, predictable environment, but as a highly complex system where change happens all the time, cannot be controlled, and no one can be really sure where the impacts might lead. This so-called "butterfly effect" is a central idea of this theory where small changes or modifications are created - the effects of which are difficult to know, let alone determine - and which can have large-scale impacts. Allied with this effect is the belief that long term developments in an organisation that takes complexity into account, emerge by spontaneous self-organising evolution, requiring political interaction and learning in groups, rather than systematic progress towards predetermined goals or "visions". Hence, because change itself and the contexts of change are recognised as complex, chaos/complexity theory suggests that change is more likely to be slow and evolutionary - cultural change - rather than fast and revolutionary where the old is quickly ushered out by radical reforms and replaced by new structures and processes. Slow, small-scale changes are "normal", from a complexity viewpoint, while rapid, wholesale change is both unlikely and unrealistic. Therefore, the frustratingly slow, small-scale, imperfect educational changes that teachers create - including environmental education initiatives - should be seen for what they really are. They should be recognised as successful changes, the impacts of which cannot be known, but which have the potential to magnify into large-scale changes into the future. Rather than being regarded as failures for not meeting critical education criteria, "small wins" should be cause for celebration and support. The intertwined phases of collaborative action research and individual researcher reflection are mirrored in the thesis structure. The first three chapters, respectively, provide the thesis overview, the literature underpinning the study's central concern, and the research methodology. Chapters 4, 5, and 6 report on each of the three action research cycles of the study, namely Laying the Groundwork, Down to Work!, and The Never-ending Story. Each of these chapters presents a narrative of events, a literature review specific to developments in the cycle, and analysis and critique of the events, processes and outcomes of each cycle. Chapter 7 provides a synthesis of the whole of the study, outlining my interim propositions about facilitating curriculum change in schools through action research, and the implications of these for environmental education.

Incidental treatment effects of CBT on suicidal ideation and hopelessness

Background: Depression and alcohol misuse are among the most prevalent diagnoses in suicide fatalities. The risk posed by these disorders is exacerbated when they co-occur. Limited research has evaluated the effectiveness of common depression and alcohol treatments for the reduction of suicide vulnerability in individuals experiencing comorbidity. Methods: Participants with depressive symptoms and hazardous alcohol use were selected from two randomised controlled trials. They had received either a brief (1 session) intervention, or depression-focused cognitive behaviour therapy (CBT), alcohol-focused CBT, therapist-delivered integrated CBT, computer-delivered integrated CBT or person-centred therapy (PCT) over a 10-week period. Suicidal ideation, hopelessness, depression severity and alcohol consumption were assessed at baseline and 12-month follow-up. Results: Three hundred three participants were assessed at baseline and 12 months. Both suicidal ideation and hopelessness were associated with higher severity of depressive symptoms, but not with alcohol consumption. Suicidal ideation did not improve significantly at follow-up, with no differences between treatment conditions. Improvements in hopelessness differed between treatment conditions; hopelessness improved more in the CBT conditions compared to PCT and in single-focused CBT compared to integrated CBT. Limitations: Low retention rates may have impacted on the reliability of our findings. Combining data from two studies may have resulted in heterogeneity of samples between conditions. Conclusions: CBT appears to be associated with reductions in hopelessness in people with co-occurring depression and alcohol misuse, even when it is not the focus of treatment. Less consistent results were observed for suicidal ideation. Establishing specific procedures or therapeutic content for clinicians to monitor these outcomes may result in better management of individuals with higher vulnerability for suicide.

A comparative analysis of risk stratification tools for emergency department patients with chest pain

Background: Appropriate disposition of emergency department (ED) patients with chest pain is dependent on clinical evaluation of risk. A number of chest pain risk stratification tools have been proposed. The aim of this study was to compare the predictive performance for major adverse cardiac events (MACE) using risk assessment tools from the National Heart Foundation of Australia (HFA), the Goldman risk score and the Thrombolysis in Myocardial Infarction risk score (TIMI RS). Methods: This prospective observational study evaluated ED patients aged ≥30 years with non-traumatic chest pain for which no definitive non-ischemic cause was found. Data collected included demographic and clinical information, investigation findings and occurrence of MACE by 30 days. The outcome of interest was the comparative predictive performance of the risk tools for MACE at 30 days, as analyzed by receiver operator curves (ROC). Results: Two hundred eighty-one patients were studied; the rate of MACE was 14.1%. Area under the curve (AUC) of the HFA, TIMI RS and Goldman tools for the endpoint of MACE was 0.54, 0.71 and 0.67, respectively, with the difference between the tools in predictive ability for MACE being highly significant [chi2 (3) = 67.21, N = 276, p < 0.0001]. Conclusion: The TIMI RS and Goldman tools performed better than the HFA in this undifferentiated ED chest pain population, but selection of cutoffs balancing sensitivity and specificity was problematic. There is an urgent need for validated risk stratification tools specific for the ED chest pain population.

Resilient Navigation through Probabilistic Modality Reconfiguration

This paper proposes an approach to achieve resilient navigation for indoor mobile robots. Resilient navigation seeks to mitigate the impact of control, localisation, or map errors on the safety of the platform while enforcing the robot’s ability to achieve its goal. We show that resilience to unpredictable errors can be achieved by combining the benefits of independent and complementary algorithmic approaches to navigation, or modalities, each tuned to a particular type of environment or situation. In this paper, the modalities comprise a path planning method and a reactive motion strategy. While the robot navigates, a Hidden Markov Model continually estimates the most appropriate modality based on two types of information: context (information known a priori) and monitoring (evaluating unpredictable aspects of the current situation). The robot then uses the recommended modality, switching between one and another dynamically. Experimental validation with a SegwayRMP- based platform in an office environment shows that our approach enables failure mitigation while maintaining the safety of the platform. The robot is shown to reach its goal in the presence of: 1) unpredicted control errors, 2) unexpected map errors and 3) a large injected localisation fault.