Single case experimental design : an overview

Background: In health related research, it is critical not only to demonstrate the efficacy of intervention, but to show that this is not due to chance or confounding variables. Content: Single case experimental design is a useful quasi-experimental design and method used to achieve these goals when there are limited participants and funds for research. This type of design has various advantages compared to group experimental designs. One such advantage is the capacity to focus on individual performance outcomes compared to group performance outcomes. Conclusions: This comprehensive review demonstrates the benefits and limitations of using single case experimental design, its various design methods, and data collection and analysis for research purposes.

Physical inactivity, appetite regulation and obesity

In a consumerist society obsessed with body image and thinness, obesity levels have reached an all-time high. This multi-faceted book written by a range of experts, explores the social, cultural, clinical and psychological factors that lie behind the Obesity Epidemic . It is required reading for the many healthcare professionals dealing with the effects of obesity and for anyone who wants to know more about the causes of weight gain and the best ways of dealing with it. Fat Matters covers a range of issues from sociology through medicine to technology. This is not a book for the highly specialised expert. Rather it is a book that shows the diversity of approaches to the phenomenon of obesity, tailored to the reader who wants to be up-to-date and well-informed on a subject that is possibly as frequently discussed and as misunderstood as the weather.

The effect of rhBMP-2 on canine osteoblasts seeded onto 3D bioactive polycaprolactone scaffolds

Our strategy entails investigating the influence of varied concentrations (0, 10, 100 and 1000 ng/ml) of human recombinant bone morphogenetic protein-2 (rhBMP-2) on the osteogenic expression of canine osteoblasts, seeded onto poly-caprolactone 20% tricalcium phosphate (PCL-TCP) scaffolds in vitro. Biochemical assay revealed that groups with rhBMP-2 displayed an initial burst in cell growth that was not dose-dependent. However, after 13 days, cell growth declined to a value similar to control. Significantly less cell growth was observed for construct with 1000 ng/ml of rhBMP-2 from 20 days onwards. Confocal microscopy confirmed viability of osteoblasts and at day 20, groups seeded with rhBMP-2 displayed heightened cell death as compared to control. Phase contrast and scanning electron microscopy revealed that osteoblasts heavily colonized surfaces, rods and pores of the PCL-TCP scaffolds. This was consistent for all groups. Finally, Von Kossa and osteocalcin assays demonstrated that cells from all groups maintained their osteogenic phenotype throughout the experiment. Calcification was observed as early as four days after stimulation for groups seeded with rhBMP-2. In conclusion, rhBMP-2 seems to enhance the differentiated function of canine osteoblasts in a non-dose dependent manner. This resulted in accelerated mineralization, followed by death of osteoblasts as they underwent terminal differentiation. Notably, PCL-TCP scaffolds seeded only with canine osteoblasts could sustain excellent osteogenic expression in vitro. Hence, the synergy of PCL with bioactive TCP and rhBMP-2 in a novel composite scaffold, could offer an exciting approach for bone regeneration.

Aligning project stakeholder motivation through incentivisation : a client-driven approach

The use of appropriate financial incentives within construction projects can contribute to strong alignment of project stakeholder motivation with project goals. However, effective incentive system design can be a challenging task and takes skillful planning by client managers in the early stages of a project. In response to a lack of information currently available to construction clients in this area, this paper explores the features of a successful incentive system and identifies key learnings for client managers to consider when designing incentives. Our findings, based on data from a large Australian case study, suggest that key stakeholders place greater emphasis on the project management processes that support incentives than on the incentive itself. Further, contractors need adequate time and information to accurately estimate construction costs prior to their tender price submission to ensure cost-focused incentive goals remain achievable. Thus, client managers should be designing incentives as part of a supportive procurement strategy to maximize project stakeholder motivation and prevent goal misalignment.

Momentum and seasonality in Chinese stock markets

In this paper, we follow Jegadeesh and Titman's (1993, Journal of Finance) approach to examine 25 momentum/contrarian trading strategies using monthly stock returns in China for the period from 1994 to 2007. Our results suggest that there is no momentum profitability in any of the 25 strategies. In contrast, there is some evidence of reversal effects where the past winners become losers and past losers become winners afterward. The contrarian profit is statistically significant for the strategies using short formation and holding periods, especially for the formation periods of 1 to 3 months and the holding periods of 1 to 3 months. The contrarian strategies can generate about 12% per annum on average. Moreover, we follow Heston and Sadka (2008, Journal of Financial Economics) to investigate where there is any seasonal pattern in the cross-sectional variation of average stock returns in our momentum/contrarian strategies. There is no evidence of any seasonal pattern, and the results are robust to different formation and holding periods.

Patterns, heuristics for architectural design support: making use of evolutionary modelling in design

Software used by architectural and industrial designers – has moved from becoming a tool for drafting, towards use in verification, simulation, project management and project sharing remotely. In more advanced models, parameters for the designed object can be adjusted so a family of variations can be produced rapidly. With advances in computer aided design technology, numerous design options can now be generated and analyzed in real time. However the use of digital tools to support design as an activity is still at an early stage and has largely been limited in functionality with regard to the design process. To date, major CAD vendors have not developed an integrated tool that is able to both leverage specialized design knowledge from various discipline domains (known as expert knowledge systems) and support the creation of design alternatives that satisfy different forms of constraints. We propose that evolutionary computing and machine learning be linked with parametric design techniques to record and respond to a designer’s own way of working and design history. It is expected that this will lead to results that impact on future work on design support systems-(ergonomics and interface) as well as implicit constraint and problem definition for problems that are difficult to quantify.

Theoretical analysis of serrated chip formation based on ideal models in high speed cutting

In this paper, two ideal formation models of serrated chips, the symmetric formation model and the unilateral right-angle formation model, have been established for the first time. Based on the ideal models and related adiabatic shear theory of serrated chip formation, the theoretical relationship among average tooth pitch, average tooth height and chip thickness are obtained. Further, the theoretical relation of the passivation coefficient of chip's sawtooth and the chip thickness compression ratio is deduced as well. The comparison between these theoretical prediction curves and experimental data shows good agreement, which well validates the robustness of the ideal chip formation models and the correctness of the theoretical deducing analysis. The proposed ideal models may have provided a simple but effective theoretical basis for succeeding research on serrated chip morphology. Finally, the influences of most principal cutting factors on serrated chip formation are discussed on the basis of a series of finite element simulation results for practical advices of controlling serrated chips in engineering application.

Getting research data ‘out there’ : collaborative solutions to identifying, describing and making research data more visible

At QUT research data refers to information that is generated or collected to be used as primary sources in the production of original research results, and which would be required to validate or replicate research findings (Callan, De Vine, & Baker, 2010). Making publicly funded research data discoverable by the broader research community and the public is a key aim of the Australian National Data Service (ANDS). Queensland University of Technology (QUT) has been innovating in this space by undertaking mutually dependant technical and content (metadata) focused projects funded by ANDS. Research Data Librarians identified and described datasets generated from Category 1 funded research at QUT, by interviewing researchers, collecting metadata and fashioning metadata records for upload to the Australian Research Data commons (ARDC) and exposure through the Research Data Australia interface. In parallel to this project, a Research Data Management Service and Metadata hub project were being undertaken by QUT High Performance Computing & Research Support specialists. These projects will collectively store and aggregate QUT’s metadata and research data from multiple repositories and administration systems and contribute metadata directly by OAI-PMH compliant feed to RDA. The pioneering nature of the work has resulted in a collaborative project dynamic where good data management practices and the discoverability and sharing of research data were the shared drivers for all activity. Each project’s development and progress was dependent on feedback from the other. The metadata structure evolved in tandem with the development of the repository and the development of the repository interface responded to meet the needs of the data interview process. The project environment was one of bottom-up collaborative approaches to process and system development which matched top-down strategic alliances crossing organisational boundaries in order to provide the deliverables required by ANDS. This paper showcases the work undertaken at QUT, focusing on the Seeding the Commons project as a case study, and illustrates how the data management projects are interconnected. It describes the processes and systems being established to make QUT research data more visible and the nature of the collaborations between organisational areas required to achieve this. The paper concludes with the Seeding the Commons project outcomes and the contribution this project made to getting more research data ‘out there’.

Cooperative multi-AUV tracking of phytoplankton blooms based on ocean model predictions

In recent years, ocean scientists have started to employ many new forms of technology as integral pieces in oceanographic data collection for the study and prediction of complex and dynamic ocean phenomena. One area of technological advancement in ocean sampling if the use of Autonomous Underwater Vehicles (AUVs) as mobile sensor plat- forms. Currently, most AUV deployments execute a lawnmower- type pattern or repeated transects for surveys and sampling missions. An advantage of these missions is that the regularity of the trajectory design generally makes it easier to extract the exact path of the vehicle via post-processing. However, if the deployment region for the pattern is poorly selected, the AUV can entirely miss collecting data during an event of specific interest. Here, we consider an innovative technology toolchain to assist in determining the deployment location and executed paths for AUVs to maximize scientific information gain about dynamically evolving ocean phenomena. In particular, we provide an assessment of computed paths based on ocean model predictions designed to put AUVs in the right place at the right time to gather data related to the understanding of algal and phytoplankton blooms.

Recent advances in cancer therapy targeting proteins involved in DNA double-strand break repair

Damage to genetic material represents a persistent and ubiquitous threat to genomic stability. Once DNA damage is detected, a multifaceted signaling network is activated that halts the cell cycle, initiates repair, and in some instances induces apoptotic cell death. In this article, we will review DNA damage surveillance networks, which maintain the stability of our genome, and discuss the efforts underway to identify chemotherapeutic compounds targeting the core components of DNA double-strand breaks (DSB) response pathway. The majority of tumor cells have defects in maintaining genomic stability owing to the loss of an appropriate response to DNA damage. New anticancer agents are exploiting this vulnerability of cancer cells to enhance therapeutic indexes, with limited normal tissue toxicity. Recently inhibitors of the checkpoint kinases Chk1 and Chk2 have been shown to sensitize tumor cells to DNA damaging agents. In addition, the treatment of BRCA1- or BRCA2-deficient tumor cells with poly(ADP-ribose) polymerase (PARP) inhibitors also leads to specific tumor killing. Due to the numerous roles of p53 in genomic stability and its defects in many human cancers, therapeutic agents that restore p53 activity in tumors are the subject of multiple clinical trials. In this article we highlight the proteins mentioned above and catalog several additional players in the DNA damage response pathway, including ATM, DNA-PK, and the MRN complex, which might be amenable to pharmacological interventions and lead to new approaches to sensitize cancer cells to radio- and chemotherapy. The challenge is how to identify those patients most receptive to these treatments.

Ways of telling : tacit knowledge transfer for fashion design research

The knowledge and skills of fashion and textiles design have traditionally been transferred through the indenture of an apprentice to a master. This relationship relied heavily on the transfer of explicit methods of design and making but also on the transfer of tacit knowledge, explained by Michael Polanyi as knowledge that cannot be explicitly known. By watching the master and emulating his efforts in the presence of his example, the apprentice unconsciously picks up the rules of the art, including those which are not explicitly known to the master himself (Polanyi, 1962 p.53). However, it has been almost half a century since Michael Polanyi defined the tacit dimension as a state in which “we can know more than we can tell” (Polanyi, 1967 p.4) at a time when the accepted means of ‘telling’ was through academic writing and publishing in hardcopy format. The idea that tacit knowledge transfer involves a one to one relationship between apprentice and master would appear to have dire consequences for a discipline, such as fashion design, where there is no such tradition of academic writing. This paper counters this point of view by providing examples of strategies currently being employed in online environments (principally through ‘craft’) and explains how these methods might prove useful to support tacit knowledge transfer in respect to academic research within the field of fashion design, and in the wider academic community involved in creative practice research. A summary of the implications of these new ideas for contemporary fashion research will conclude the paper.

Assembling dynamic repertoires of literate practices : teaching that makes a difference

This chapter considers how teachers can make a difference to the kinds of literacy young people take up. Increasingly, researchers and policy-makers see literacy as an ensemble of socio-cultural situated practices rather than as a unitary skill. Accordingly, the differences in what young people come to do with literacy, in and out of school, confront us more directly. If literacy development involves assembling dynamic repertoires of practices, it is crucial to consider what different groups of children growing up and going to school in different places have access to and make investments in over time; the kinds of literate communities from which some are excluded or included; and how educators make a difference to the kinds of literate trajectories and identities young people put together.

A crash avoidance framework for heavy equipment control systems using 3D imaging sensors

This paper presents a preliminary crash avoidance framework for heavy equipment control systems. Safe equipment operation is a major concern on construction sites since fatal on-site injuries are an industry-wide problem. The proposed framework has potential for effecting active safety for equipment operation. The framework contains algorithms for spatial modeling, object tracking, and path planning. Beyond generating spatial models in fractions of seconds, these algorithms can successfully track objects in an environment and produce a collision-free 3D motion trajectory for equipment.

Machine learning techniques to improve software quality

A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.

Working in online groups-the challenges of virtually integrated learning environments

Universities continue to struggle with the need to combine the pedagogical benefits of collaborative learning with large scale, interactive and technologically sophisticated learning and teaching arrproaches and support systems. This challenge requires imaginative approaches if the outcome is not to the 'worst of both worlds' that results in confusion and disillusionism amongst students. This paper presents three case studies that use online technologies to provide collaborative teaching solutions arguably much superior to that possible without an online intervention.