Phase composition of the rapidly quenched melt of YBa2Cu3O7-y+20 mol% Y2BaCuO5

Samples of YBa2Cu3O7-y+20 mol% Y2BaCuO5, with thicknesses ranging between 50-250 μm, have been melt processed and rapidly quenched from temperatures between 985 and 1100°C by immersing them in liquid nitrogen. The phase composition and microstructures of these samples have been characterised using a combination of X-ray diffractometry, optical microscopy and scanning electron microscopy with energy dispersive X-ray spectroscopy. The quenched melt of samples quenched from temperatures greater than 985°C appears relatively homogeneous but consists of Ba2Cu3Ox (BC1.5) and BaCu2O2 (BC2) regions. At about 985°C, BaCuO2 (BC1) crystallises from the melt and most of the BC1.5 decomposes into BC1 and CuO or into BC1 and BC2. The crystallisation of BC1 induces segregation of elements in the melt and this is very significant for the melt texturing of YBCO.

'Sarcobesity' : a metabolic conundrum

Two independent but inter-related conditions that have a growing impact on healthy life expectancy and health care costs in developed nations are an age-related loss of muscle mass (i.e., sarcopenia) and obesity. Sarcopenia is commonly exacerbated in overweight and obese individuals. Progression towards obesity promotes an increase in fat mass and a concomitant decrease in muscle mass, producing an unfavourable ratio of fat to muscle. The coexistence of diminished muscle mass and increased fat mass (so-called 'sarcobesity') is ultimately manifested by impaired mobility and/or development of life-style-related diseases. Accordingly, the critical health issue for a large proportion of adults in developed nations is how to lose fat mass while preserving muscle mass. Lifestyle interventions to prevent or treat sarcobesity include energy-restricted diets and exercise. The optimal energy deficit to reduce body mass is controversial. While energy restriction in isolation is an effective short-term strategy for rapid and substantial weight loss, it results in a reduction of both fat and muscle mass and therefore ultimately predisposes one to an unfavourable body composition. Aerobic exercise promotes beneficial changes in whole-body metabolism and reduces fat mass, while resistance exercise preserves lean (muscle) mass. Current evidence strongly supports the inclusion of resistance and aerobic exercise to complement mild energy-restricted high-protein diets for healthy weight loss as a primary intervention for sarcobesity.

A novel iterative method for simulating patient-specific optimal deformation and fit of fracture fixation plates

This paper proposes a new iterative method to achieve an optimally fitting plate for preoperative planning purposes. The proposed method involves integration of four commercially available software tools, Matlab, Rapidform2006, SolidWorks and ANSYS, each performing specific tasks to obtain a plate shape that fits optimally for an individual tibia and is mechanically safe. A typical challenge when crossing multiple platforms is to ensure correct data transfer. We present an example of the implementation of the proposed method to demonstrate successful data transfer between the four platforms and the feasibility of the method.

A proposed approach to monitor private-sector policies and practices related to food environments, obesity and non-communicable disease prevention

Private-sector organizations play a critical role in shaping the food environments of individuals and populations. However, there is currently very limited independent monitoring of private-sector actions related to food environments. This paper reviews previous efforts to monitor the private sector in this area, and outlines a proposed approach to monitor private-sector policies and practices related to food environments, and their influence on obesity and non-communicable disease (NCD) prevention. A step-wise approach to data collection is recommended, in which the first (‘minimal’) step is the collation of publicly available food and nutrition-related policies of selected private-sector organizations. The second (‘expanded’) step assesses the nutritional composition of each organization's products, their promotions to children, their labelling practices, and the accessibility, availability and affordability of their products. The third (‘optimal’) step includes data on other commercial activities that may influence food environments, such as political lobbying and corporate philanthropy. The proposed approach will be further developed and piloted in countries of varying size and income levels. There is potential for this approach to enable national and international benchmarking of private-sector policies and practices, and to inform efforts to hold the private sector to account for their role in obesity and NCD prevention.

Monitoring food and non-alcoholic beverage promotions to children

Food and non-alcoholic beverage marketing is recognized as an important factor influencing food choices related to non-communicable diseases. The monitoring of populations' exposure to food and non-alcoholic beverage promotions, and the content of these promotions, is necessary to generate evidence to understand the extent of the problem, and to determine appropriate and effective policy responses. A review of studies measuring the nature and extent of exposure to food promotions was conducted to identify approaches to monitoring food promotions via dominant media platforms. A step-wise approach, comprising ‘minimal’, ‘expanded’ and ‘optimal’ monitoring activities, was designed. This approach can be used to assess the frequency and level of exposure of population groups (especially children) to food promotions, the persuasive power of techniques used in promotional communications (power of promotions) and the nutritional composition of promoted food products. Detailed procedures for data sampling, data collection and data analysis for a range of media types are presented, as well as quantifiable measurement indicators for assessing exposure to and power of food and non-alcoholic beverage promotions. The proposed framework supports the development of a consistent system for monitoring food and non-alcoholic beverage promotions for comparison between countries and over time.

Carrot red leaf and carrot mottle viruses : observations on the composition of the particles in single and mixed infections

Particles of carrot red leaf virus (CRLV; luteovirus group) purified from chervil (Anthriscus cerefolium) contain a single ssRNA species of mol. wt. about 1.8 x 106 and a major protein of mol. wt. about 25000. CRLV acts as a helper for aphid transmission of carrot mottle virus (CMotV; ungrouped) from mixedly infected plants. Virus preparations purified from such plants possess the infectivity of both viruses but contain particles indistinguishable from those of CRLV; some of the particles are therefore thought to consist of CMotV RNA packaged in CRLV coat protein. When RNA from such preparations was electrophoresed in agarose/polyacrylamide gels, CMotV infectivity was associated with an RNA band that migrated ahead of the CRLV RNA band and had an estimated mol. wt. of about 1.5 x 106, similar to that previously found for the infective ssRNA extracted directly from Nicotiana clevelandii leaves infected with CMotV alone. Preparations of dsRNA from CMotV-infected N. clevelandii leaves contained two species: one of mol. wt. about 3.2 x 106, presumably the replicative form of the infective ssRNA, and the other, mol. wt. about 0.9 x 106, of unknown origin and function. The infective agent in buffer extracts of CMotV-infected N. clevelandii was resistant to RNase (although the enzyme acted as a reversible inhibitor of infection at high concentrations) and is therefore not unprotected RNA. It may be protected within the approximately 52 nm enveloped structures previously reported.

Optimal camera planning under versatile user constraints in multi-camera image processing systems

The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

Developing a dashboard for real-time data stream composition and visualization

Technological advances have led to an influx of affordable hardware that supports sensing, computation and communication. This hardware is increasingly deployed in public and private spaces, tracking and aggregating a wealth of real-time environmental data. Although these technologies are the focus of several research areas, there is a lack of research dealing with the problem of making these capabilities accessible to everyday users. This thesis represents a first step towards developing systems that will allow users to leverage the available infrastructure and create custom tailored solutions. It explores how this notion can be utilized in the context of energy monitoring to improve conventional approaches. The project adopted a user-centered design process to inform the development of a flexible system for real-time data stream composition and visualization. This system features an extensible architecture and defines a unified API for heterogeneous data streams. Rather than displaying the data in a predetermined fashion, it makes this information available as building blocks that can be combined and shared. It is based on the insight that individual users have diverse information needs and presentation preferences. Therefore, it allows users to compose rich information displays, incorporating personally relevant data from an extensive information ecosystem. The prototype was evaluated in an exploratory study to observe its natural use in a real-world setting, gathering empirical usage statistics and conducting semi-structured interviews. The results show that a high degree of customization does not warrant sustained usage. Other factors were identified, yielding recommendations for increasing the impact on energy consumption.

The optimal temperature of first aid treatment for partial thickness burn injuries

Using our porcine model of deep dermal partial thickness burn injury, various cooling techniques (15 degrees C running water, 2 degrees C running water, ice) of first aid were applied for 20 minutes compared with a control (ambient temperature). The subdermal temperatures were monitored during the treatment and wounds observed and photographed weekly for 6 weeks, observing reepithelialization, wound surface area and cosmetic appearance. Tissue histology and scar tensile strength were examined 6 weeks after burn. The 2 degrees C and ice treatments decreased the subdermal temperature the fastest and lowest, however, generally the 15 and 2 degrees C treated wounds had better outcomes in terms of reepithelialization, scar histology, and scar appearance. These findings provide evidence to support the current first aid guidelines of cold tap water (approximately 15 degrees C) for 20 minutes as being beneficial in helping to heal the burn wound. Colder water at 2 degrees C is also beneficial. Ice should not be used.

The optimal duration and delay of first aid treatment for deep partial thickness burn injuries

Using our porcine model of deep dermal partial thickness burn injury, various durations (10min, 20min, 30min or 1h) and delays (immediate, 10min, 1h, 3h) of 15 degrees C running water first aid were applied to burns and compared to untreated controls. The subdermal temperatures were monitored during the treatment and wounds observed weekly for 6 weeks, for re-epithelialisation, wound surface area and cosmetic appearance. At 6 weeks after the burn, tissue biopsies were taken of the scar for histological analysis. Results showed that immediate application of cold running water for 20min duration is associated with an improvement in re-epithelialisation over the first 2 weeks post-burn and decreased scar tissue at 6 weeks. First aid application of cold water for as little as 10min duration or up to 1h delay still provides benefit.

Variability of metal composition and concentrations in road dust in the urban environment

Urban road dust comprises of a range of potentially toxic metal elements and plays a critical role in degrading urban receiving water quality. Hence, assessing the metal composition and concentration in urban road dust is a high priority. This study investigated the variability of metal composition and concentrations in road dust in 4 different urban land uses in Gold Coast, Australia. Samples from 16 road sites were collected and tested for selected 12 metal species. The data set was analyzed using both univariate and multivariate techniques. Outcomes of the data analysis revealed that the metal concentrations in road dust differ considerably within and between different land uses. Iron, aluminum, magnesium and zinc are the most abundant in urban land uses. It was also noted that metal species such as titanium, nickel, copper and zinc have the highest concentrations in industrial land use. The study outcomes revealed that soil and traffic related sources as key sources of metals deposited on road surfaces.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Maximum loadability achievement in SWER networks using optimal sizing and locating of batteries

This paper presents an optimisation algorithm to maximize the loadability of single wire earth return (SWER) by minimizing the cost of batteries and regulators considering the voltage constraints and thermal limits. This algorithm, that finds the optimum location of batteries and regulators, uses hybrid discrete particle swarm optimization and mutation (DPSO + Mutation). The simulation results on realistic highly loaded SWER network show the effectiveness of using battery to improve the loadability of SWER network in a cost-effective way. In this case, while only 61% of peak load can be supplied without violating the constraints by existing network, the loadability of the network is increased to peak load by utilizing two battery sites which are located optimally. That is, in a SWER system like the studied one, each installed kVA of batteries, optimally located, supports a loadability increase as 2 kVA.

Go with the flow : optimal AUV path planning in coastal environments

This paper describes a novel optimum path planning strategy for long duration AUV operations in environments with time-varying ocean currents. These currents can exceed the maximum achievable speed of the AUV, as well as temporally expose obstacles. In contrast to most other path planning strategies, paths have to be defined in time as well as space. The solution described here exploits ocean currents to achieve mission goals with minimal energy expenditure, or a tradeoff between mission time and required energy. The proposed algorithm uses a parallel swarm search as a means to reduce the susceptibility to large local minima on the complex cost surface. The performance of the optimisation algorithms is evaluated in simulation and experimentally with the Starbug AUV using a validated ocean model of Brisbane’s Moreton Bay.