Semiochemicals in merino ewes : field effects and chemical identification

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Testing and modelling to obtain material behaviour for crash simulations

The thesis focusses on improving the material behaviour models used in vehicle crash simulations by identifying the mechanical properties most important to crash events, reformulating the material models used in crash simulations, and developing new tests to obtain crash-relevant material.

Cross-field effects and temporary social fields : a case study of the mediatization of recent Australian knowledge economy policies

This paper utilizes Bourdieu's conceptual frame to examine the mediatized effects of policy processes concerned with the growth and support of knowledge industries in Australia. These policies span education, science, research and other knowledge industries (such as venture capital firms and intellectual property law). The paper argues that some policy processes are best represented as temporary social fields. The nature of these fields can be described by the kinds of cross-field effects that they produce, A case study of an Australian knowledge economy policy, The chance to change, and associated policy processes demonstrates the broad analytic capacities of Bourdieu 's conceptual frame for policy analysis, when combined with the concepts of cross-field effects and temporary social field developed here.

Recognising and monitoring high-level behaviours in complex spatial environments

The recognition of activities from sensory data is important in advanced surveillance systems to enable prediction of high-level goals and intentions of the target under surveillance. The problem is complicated by sensory noise and complex activity spanning large spatial and temporal extents. This paper presents a system for recognising high-level human activities from multi-camera video data in complex spatial environments. The Abstract Hidden Markov mEmory Model (AHMEM) is used to deal with noise and scalability The AHMEM is an extension of the Abstract Hidden Markov Model (AHMM) that allows us to represent a richer class of both state-dependent and context-free behaviours. The model also supports integration with low-level sensory models and efficient probabilistic inference. We present experimental results showing the ability of the system to perform real-time monitoring and recognition of complex behaviours of people from observing their trajectories within a real, complex indoor environment.

Developing a simple, rapid method for identifying and monitoring jellyfish aggregations from the air

Within the marine environment, aerial surveys have historically centred on apex predators, such as pinnipeds, cetaceans and sea birds. However, it is becoming increasingly apparent that the utility of this technique may also extend to subsurface species such as pre-spawning fish stocks and aggregations of jellyfish that occur close to the surface. In light of this, we tested the utility of aerial surveys to provide baseline data for 3 poorly understood scyphozoan jellyfish found throughout British and Irish waters: Rhizostoma octopus, Cyanea capillata and Chrysaora hysoscella. Our principal objectives were to develop a simple sampling protocol to identify and quantify surface aggregations, assess their consistency in space and time, and consider the overall applicability of this technique to the study of gelatinous zooplankton. This approach provided a general understanding of range and relative abundance for each target species, with greatest suitability to the study of R. octopus. For this species it was possible to identify and monitor extensive, temporally consistent and previously undocumented aggregations throughout the Irish Sea, an area spanning thousands of square kilometres. This finding has pronounced implications for ecologists and fisheries managers alike and, moreover, draws attention to the broad utility of aerial surveys for the study of gelatinous aggregations beyond the range of conventional ship-based techniques.

Influence of field position and phase of play on the physical demands of match-play in professional rugby league forwards

This article describes the utilisation of an unsupervised machine learning technique and statistical approaches (e.g., the Kolmogorov-Smirnov test) that assist cycling experts in the crucial decision-making processes for athlete selection, training, and strategic planning in the track cycling Omnium. The Omnium is a multi-event competition that will be included in the summer Olympic Games for the first time in 2012. Presently, selectors and cycling coaches make decisions based on experience and intuition. They rarely have access to objective data. We analysed both the old five-event (first raced internationally in 2007) and new six-event (first raced internationally in 2011) Omniums and found that the addition of the elimination race component to the Omnium has, contrary to expectations, not favoured track endurance riders. We analysed the Omnium data and also determined the inter-relationships between different individual events as well as between those events and the final standings of riders. In further analysis, we found that there is no maximum ranking (poorest performance) in each individual event that riders can afford whilst still winning a medal. We also found the required times for riders to finish the timed components that are necessary for medal winning. The results of this study consider the scoring system of the Omnium and inform decision-making toward successful participation in future major Omnium competitions.

Zebrafish as a genetic model in pre-clinical drug testing and screening

The traditional drug discovery pipeline for the identification and development of compounds that selectively target specific molecules to ameliorate disease remains a major focus for medical research. However, the zebrafish is increasingly providing alternative strategies for various components of this pipeline. Zebrafish and their embryos are small, easily accessible and relatively low cost, making them applicable to high-throughput, small molecule screening. Zebrafish can also be manipulated by a range of forward and reverse genetics techniques to facilitate gene discovery and functional studies. Moreover, their physiological and developmental complexity provides accurate models of human disease to underpin mechanism of action and in vivo validation studies. Finally, several of these biological characteristics make zebrafish eminently suitable for toxicity testing, including eco-toxicology. Here we review the application of zebrafish to preclinical drug development and toxicity testing, including recent advances in mutant generation, drug screening and toxicology that serve to further enhance the capabilities of this valuable model organism in drug discovery.