Conceptions of school-based youth health nursing

The aim of this research is to explore the meaning of the experience of school-based youth health nursing in Queensland, Australia. The research follows a qualitative approach and is based on indepth interviews. The dominant experience is negative because participants feel they have to battle to gain respect and survive in the school environment. The small, positive experience of school-based youth health nursing is related to student consultations. Student consultations are a ‘golden egg’ because participants gain a sense of reward from making a difference to student wellbeing. This paper proposes operational recommendations including those related to health promotion and professional development and strategic recommendations regarding this model of school nursing. The authors conclude, first, that this ‘golden egg’ should be promoted to ensure all school nurses reap the rewards, second, that this model of school nursing is not the most effective model.

A genome-based strategy uncovers frequent BRAF mutations in melanoma

Using a genome-scanning approach to search for oncogenes, a recent report identifies somatic mutations in the signaling gene BRAF that are particularly prevalent in melanoma.

Chain scission resists for extreme ultraviolet lithography based on high performance polysulfone-containing polymers

A series of polymers with a comb architecture were prepared where the poly(olefin sulfone) backbone was designed to be highly sensitive to extreme ultraviolet (EUV) radiation, while the well-defined poly(methyl methacrylate) (PMMA) arms were incorporated with the aim of increasing structural stability. It is hypothesized that upon EUV radiation rapid degradation of the polysulfone backbone will occur leaving behind the well-defined PMMA arms. The synthesized polymers were characterised and have had their performance as chain-scission EUV photoresists evaluated. It was found that all materials possess high sensitivity towards degradation by EUV radiation (E0 in the range 4–6 mJ cm−2). Selective degradation of the poly(1-pentene sulfone) backbone relative to the PMMA arms was demonstrated by mass spectrometry headspace analysis during EUV irradiation and by grazing-angle ATR-FTIR. EUV interference patterning has shown that materials are capable of resolving 30 nm 1:1 line:space features. The incorporation of PMMA was found to increase the structural integrity of the patterned features. Thus, it has been shown that terpolymer materials possessing a highly sensitive poly(olefin sulfone) backbone and PMMA arms are able to provide a tuneable materials platform for chain scission EUV resists. These materials have the potential to benefit applications that require nanopattering, such as computer chip manufacture and nano-MEMS.

Patterning of tailored polycarbonate based non-chemically amplified resists using extreme ultraviolet lithography

A series of high-performance polycarbonates have been prepared with glass-transition temperatures and decomposition temperatures that are tunable by varying the repeat-unit chemical structure. Patterning of the polymers with extreme UV lithography has been achieved by taking advantage of direct photoinduced chain scission of the polymer chains, which results in a molecular-weight based solubility switch. After selective development of the irradiated regions of the polymers, feature sizes as small as 28.6 nm have been printed and the importance of resist-developer interactions for maximizing image quality has been demonstrated.

Polycarbonate based nonchemically amplified photoresists for extreme ultraviolet lithography

Some initial EUVL patterning results for polycarbonate based non-chemically amplified resists are presented. Without full optimization the developer a resolution of 60 nm line spaces could be obtained. With slight overexposure (1.4 × E0) 43.5 nm lines at a half pitch of 50 nm could be printed. At 2x E0 a 28.6 nm lines at a half pitch of 50 nm could be obtained with a LER that was just above expected for mask roughness. Upon being irradiated with EUV photons, these polymers undergo chain scission with the loss of carbon dioxide and carbon monoxide. The remaining photoproducts appear to be non-volatile under standard EUV irradiation conditions, but do exhibit increased solubility in developer compared to the unirradiated polymer. The sensitivity of the polymers to EUV light is related to their oxygen content and ways to increase the sensitivity of the polymers to 10 mJ cm-2 is discussed.

Look before you leap : a confidence-based method for selecting species criticality while avoiding negative populations in τ-leaping

The stochastic simulation algorithm was introduced by Gillespie and in a different form by Kurtz. There have been many attempts at accelerating the algorithm without deviating from the behavior of the simulated system. The crux of the explicit τ-leaping procedure is the use of Poisson random variables to approximate the number of occurrences of each type of reaction event during a carefully selected time period, τ. This method is acceptable providing the leap condition, that no propensity function changes “significantly” during any time-step, is met. Using this method there is a possibility that species numbers can, artificially, become negative. Several recent papers have demonstrated methods that avoid this situation. One such method classifies, as critical, those reactions in danger of sending species populations negative. At most, one of these critical reactions is allowed to occur in the next time-step. We argue that the criticality of a reactant species and its dependent reaction channels should be related to the probability of the species number becoming negative. This way only reactions that, if fired, produce a high probability of driving a reactant population negative are labeled critical. The number of firings of more reaction channels can be approximated using Poisson random variables thus speeding up the simulation while maintaining the accuracy. In implementing this revised method of criticality selection we make use of the probability distribution from which the random variable describing the change in species number is drawn. We give several numerical examples to demonstrate the effectiveness of our new method.

Neo-planning: Location-based social media to engage Australia’s new digital locals

Community engagement with time poor and seemingly apathetic citizens continues to challenge local governments. Capturing the attention of a digitally literate community who are technology and socially savvy adds a new quality to this challenge. Community engagement is resource and time intensive, yet local governments have to manage on continually tightened budgets. The benefits of assisting citizens in taking ownership in making their community and city a better place to live in collaboration with planners and local governments are well established. This study investigates a new collaborative form of civic participation and engagement for urban planning that employs in-place digital augmentation. It enhances people’s experience of physical spaces with digital technologies that are directly accessible within that space, in particular through interaction with mobile phones and public displays. The study developed and deployed a system called Discussions in Space (DIS) in conjunction with a major urban planning project in Brisbane. Planners used the system to ask local residents planning-related questions via a public screen, and passers-by sent responses via SMS or Twitter onto the screen for others to read and reflect, hence encouraging in-situ, real-time, civic discourse. The low barrier of entry proved to be successful in engaging a wide range of residents who are generally not heard due to their lack of time or interest. The system also reflected positively on the local government for reaching out in this way. Challenges and implications of the short-texted and ephemeral nature of this medium were evaluated in two focus groups with urban planners. The paper concludes with an analysis of the planners’ feedback evaluating the merits of the data generated by the system to better engage with Australia’s new digital locals.

Hybrid light-emitting diodes based on flexible sheets of mass-produced ZnO nanowires

We report the production of free-standing thin sheets made up of mass-produced ZnO nanowires and the application of these nanowire sheets for the fabrication of ZnO/organic hybrid light-emitting diodes in the manner of assembly. Different p-type organic semiconductors are used to form heterojunctions with the ZnO nanowire film. Electroluminescence measurements of the devices show UV and visible emissions. Identical strong red emission is observed independent of the organic semiconductor materials used in this work. The visible emissions corresponding to the electron transition between defect levels within the energy bandgap of ZnO are discussed.

Order of instruction effects - do they make a difference when teaching senior chemistry with computer based visualizations?

This study investigated whether conceptual development is greater if students learning senior chemistry hear teacher explanations and other traditional teaching approaches first then see computer based visualizations or vice versa. Five Canadian chemistry classes, taught by three different teachers, studied the topics of Le Chatelier’s Principle and dynamic chemical equilibria using scientific visualizations with the explanation and visualizations in different orders. Conceptual development was measured using a 12 item test based on the Chemistry Concepts Inventory. Data was obtained about the students’ abilities, learning styles (auditory, visual or kinesthetic) and sex, and the relationships between these factors and conceptual development due to the teaching sequences were investigated. It was found that teaching sequence is not important in terms of students’ conceptual learning gains, across the whole cohort or for any of the three subgroups.

Novel corrosion sensor based on carbon nanotube composites for structural health monitoring

Bridges are important infrastructures of all nations and are required for transportation of goods as well as human. A catastrophic failure can result in loss of lives and enormous financial hardship to the nation. Hence, there is an urgent need to monitor our infrastructures to prolong their life span, at the same time catering for heavier and faster moving traffics. Although various kinds of sensors are now available to monitor the health of the structures due to corrosion, they do not provide permanent and long term measurements. This paper investigates the fabrication of Carbon Nanotube (CNT) based composite sensors for structural health monitoring. The CNTs, a key material in nanotechnology has aroused great interest in the research community due to their remarkable mechanical, electrochemical, piezoresistive and other physical properties. Multi-wall CNT (MWCNT)/Nafion composite sensors were fabricated to evaluate their electrical properties when subjected to chemical solutions, to simulate a chemical reaction due to corrosion and real life corrosion experimental tests. The electrical resistance of the sensor electrode was dramatically changed due to corrosion. The novel sensor is expected to effectively detect corrosion in structures based on the measurement of electrical impedances of the CNT composite.

Interactive peer-based learning in a comparative case study : what do students gain?

As English increasingly becomes one of the most commonly spoken languages in the world today for a variety of economic, social and cultural reasons, education is impacted by globalisation, the internationalisation of universities and the diversity of learners in classrooms. The challenge for educators is to find more effective ways of teaching English language so that students are better able to create meaning and communicate in the target language as well as to transform knowledge and understanding into relevant skills for a rapidly changing world. This research focuses broadly on English language education underpinned by social constructivist principles informing communicative language teaching and in particular, interactive peer learning approaches. An intervention of interactive peer-based learning in two case study contexts of English as Foreign Language (EFL) undergraduates in a Turkish university and English as Second Language (ESL) undergraduates in an Australian university investigates what students gain from the intervention. Methodology utilising qualitative data gathered from student reflective logs, focus group interviews and researcher field notes emphasises student voice. The cross case comparative study indicates that interactive peer-based learning enhances a range of learning outcomes for both cohorts including engagement, communicative competence, diagnostic feedback as well as assisting development of inclusive social relationships, civic skills, confidence and self efficacy. The learning outcomes facilitate better adaptation to a new learning environment and culture. An iterative instructional matrix tool is a useful product of the research for first year university experiences, teacher training, raising awareness of diversity, building learning communities, and differentiating the curriculum. The study demonstrates that English language learners can experience positive impact through peer-based learning and thus holds an influential key for Australian universities and higher education.

A Krylov-based finite state projection algorithm for solving the chemical master equation arising in the discrete modelling of biological systems

Biochemical reactions underlying genetic regulation are often modelled as a continuous-time, discrete-state, Markov process, and the evolution of the associated probability density is described by the so-called chemical master equation (CME). However the CME is typically difficult to solve, since the state-space involved can be very large or even countably infinite. Recently a finite state projection method (FSP) that truncates the state-space was suggested and shown to be effective in an example of a model of the Pap-pili epigenetic switch. However in this example, both the model and the final time at which the solution was computed, were relatively small. Presented here is a Krylov FSP algorithm based on a combination of state-space truncation and inexact matrix-vector product routines. This allows larger-scale models to be studied and solutions for larger final times to be computed in a realistic execution time. Additionally the new method computes the solution at intermediate times at virtually no extra cost, since it is derived from Krylov-type methods for computing matrix exponentials. For the purpose of comparison the new algorithm is applied to the model of the Pap-pili epigenetic switch, where the original FSP was first demonstrated. Also the method is applied to a more sophisticated model of regulated transcription. Numerical results indicate that the new approach is significantly faster and extendable to larger biological models.

Non-redundant sequential association rule mining based on closed sequential patterns

In many applications, e.g., bioinformatics, web access traces, system utilisation logs, etc., the data is naturally in the form of sequences. People have taken great interest in analysing the sequential data and finding the inherent characteristics or relationships within the data. Sequential association rule mining is one of the possible methods used to analyse this data. As conventional sequential association rule mining very often generates a huge number of association rules, of which many are redundant, it is desirable to find a solution to get rid of those unnecessary association rules. Because of the complexity and temporal ordered characteristics of sequential data, current research on sequential association rule mining is limited. Although several sequential association rule prediction models using either sequence constraints or temporal constraints have been proposed, none of them considered the redundancy problem in rule mining. The main contribution of this research is to propose a non-redundant association rule mining method based on closed frequent sequences and minimal sequential generators. We also give a definition for the non-redundant sequential rules, which are sequential rules with minimal antecedents but maximal consequents. A new algorithm called CSGM (closed sequential and generator mining) for generating closed sequences and minimal sequential generators is also introduced. A further experiment has been done to compare the performance of generating non-redundant sequential rules and full sequential rules, meanwhile, performance evaluation of our CSGM and other closed sequential pattern mining or generator mining algorithms has also been conducted. We also use generated non-redundant sequential rules for query expansion in order to improve recommendations for infrequently purchased products.

Cross likelihood ratio based speaker clustering using eigenvoice models

This paper proposes the use of eigenvoice modeling techniques with the Cross Likelihood Ratio (CLR) as a criterion for speaker clustering within a speaker diarization system. The CLR has previously been shown to be a robust decision criterion for speaker clustering using Gaussian Mixture Models. Recently, eigenvoice modeling techniques have become increasingly popular, due to its ability to adequately represent a speaker based on sparse training data, as well as an improved capture of differences in speaker characteristics. This paper hence proposes that it would be beneficial to capitalize on the advantages of eigenvoice modeling in a CLR framework. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 35.1% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.