Master of Science / Department of Animal Sciences and Industry / J. Scott Smith / Emulsifiers have been and remain highly functional ingredients in the food industry. Emulsifiers contain both hydrophilic and lipophilic parts, resulting in their ability to be useful in foods at very low levels. However, knowledge of why emulsifiers work and how to use them most effectively is reserved for the few scientists who specialize in the discipline. Therefore, a comparison of current emulsifier theory with known emulsifier usage in the industry is beneficial to all who use these ingredients. Current emulsifier theory effectively describes how emulsifiers behave in food systems. Emulsion theory details how emulsifiers facilitate the formation and stability of emulsions through study of the kinetics of food systems. Emulsion theory further relates the ability of emulsifiers to interact with other substances in a food system. The main interactions concerning emulsifiers are their ability to form mesophases with water, to strengthen or weaken protein interactions, to form complexes with starches, and to promote or subdue fat crystallization. However, industrial applications of emulsifiers indicate areas where exceptions to theory exist. While emulsion theory has been found to effectively describe the individual interactions and functions in food, the simplicity of the models indicates that complex food system models are still needed to truly understand how to maximize the functionality of emulsifiers.

Master of Science / Food Science Institute - Animal Science & Industry / Kelly J. K. Getty / Fats and oils are an important topic in the margarine and spreads industry. The selection of these ingredients can be based on many factors including flavor, functionality, cost, and health aspects. In general, fat is an important component of a healthy diet. Fat or oil provides nine calories per gram of energy, transports essential vitamins, and is necessary in cellular structure. Major shifts in consumption of fats and oils through history have been driven by consumer demand. An example is the decline in animal fat consumption due to consumers’ concern over saturated fats. Also, consumers’ concern over the obesity epidemic and coronary heart disease has driven demand for new, lower calorie, nutrient-rich spreads products. Fats and oils can be separated into many different subgroups. “Fats” generally refer to lipids that are solid at room temperature while “oils” refer to those that are liquid. Fatty acids can be either saturated or unsaturated. If they are unsaturated, they can be either mono-, di-, or poly-unsaturated. Also, unsaturated bonds can be in the cis or trans conformation. A triglyceride, which is three fatty acids esterified to a glycerol backbone, can have any combination of saturated and unsaturated fatty acids. Triglycerides are the primary components of animal and vegetable fats and oils. The ratio of saturated to unsaturated fatty acids in these fats and oils has a great impact on their functionality. Common fats and oils include butterfat, beef tallow, fish oils, soybean oil, rapeseed (canola) oil, corn oil, cottonseed oil, olive oil, sunflower oil, palm oil, palm kernel oil, coconut oil, linseed (flax) oil, and safflower oil. Typical fat and oil modification techniques include hydrogenation, interesterification, alternative hydrogenation, fractionation, blending, farm/field practices and genetic modification, and the use of fat replacers. There are many processing techniques that can be utilized in margarine and spreads production. The process can be optimized for each margarine or spreads product. There are many fats and oils in margarine and spreads formulations. Familiarity with commonly used fats and oils in regards to availability, cost, nutrition, chemistry, and functionality are important when creating a cost-effective, functional margarine or spreads product.

This project explores the dynamics of medical innovation using the development of deep brain stimulation therapy in paediatric neurology as a case study. Ethnographic research was conducted with a multidisciplinary clinical team developing a novel clinical service that uses deep brain stimulation (DBS) to treat children and young people with movement disorders. Interviews and observations were carried out to identify key challenges encountered by team members, and to explore the way in which team members attempt to manage these challenges in day-to-day clinical practice. Four key challenges were identified: coordinating multidisciplinary teamwork, identifying suitable candidates for deep brain stimulation; managing the expectations of patients and families; and measuring clinical outcomes. By exploring the strategies used by team members to overcome these challenges, this thesis develops the Complex Model of Medical Innovation which challenges prevalent, linear ‘bench-to-bedside’ understandings of innovation. While scientific ‘discovery’ is one source of medical innovation, new therapies in medicine also emerge from technology transfer (the transfer of technology from one sector into another) and clinicians’ learning-in-practice (the ability of clinician to learn ‘on the spot’). Importantly, this thesis demonstrates that technology transfer, learning-in-practice, and medical innovation in general are shaped by various socio-political trends. The activities of the multidisciplinary team and their novel DBS service, for example, have been shaped by the evidence based medicine movement, commercial interests, and a movement that promotes multidisciplinary approaches to paediatric service provision. A consequence of these influences is that the team subjects their patients to a broad clinical gaze. Adopting the Complex Model of Medical Innovation has important consequences: First, it draws attention to the innovative activities of clinicians, activities that may be worth disseminating in other contexts. Second, it highlights the role of existing social and material factors in shaping the development of new clinical services. The social impact of new technologies will be influenced by these contextual factors and cannot be attributed to the technology alone.

In this thesis we formalise and study computational aspects of group decision making for rational, self-interested agents. Specifically, we are interested in systems where agents reach consensus according to endogenous thresholds. Natural groups have been shown to make collective decisions according to threshold-mediated behaviours. An individual will commit to some collective endeavour only if the number of others having already committed exceeds their threshold. Consensus is reached only where all individuals express commitment. We present a family of models that describe fundamental aspects of cooperative behaviour in multi-agent systems. These include: coalition formation, participation in joint actions and the achievement of individuals’ goals over time. We associate novel solution concepts with our models and present results concerning the computational complexity of several natural decision problems arising from these. We demonstrate potential applications of our work by modelling a group decision problem common to many cohesive groups: establishing the location of the group. Using model checking tools we compute the effects of agents’ thresholds upon outcomes. We consider our results within an appropriate research context.

Hyper-heuristics are a class of high-level search methodologies which operate over a search space of heuristics rather than a search space of solutions. Hyper-heuristic research has set out to develop methods which are more general than traditional search and optimisation techniques. In recent years, focus has shifted considerably towards cross-domain heuristic search. The intention is to develop methods which are able to deliver an acceptable level of performance over a variety of different problem domains, given a set of low-level heuristics to work with. This thesis presents a body of work investigating the use of selection hyper-heuristics in a number of different problem domains. Specifically the use of crossover operators, prevalent in many evolutionary algorithms, is explored within the context of single-point search hyper-heuristics. A number of traditional selection hyper-heuristics are applied to instances of a well-known NP-hard combinatorial optimisation problem, the multidimensional knapsack problem. This domain is chosen as a benchmark for the variety of existing problem instances and solution methods available. The results suggest that selection hyper-heuristics are a viable method to solve some instances of this problem domain. Following this, a framework is defined to describe the conceptual level at which crossover low-level heuristics are managed in single-point selection hyper-heuristics. HyFlex is an existing software framework which supports the design of heuristic search methods over multiple problem domains, i.e. cross-domain optimisation. A traditional heuristic selection mechanism is modified in order to improve results in the context of cross-domain optimisation. Finally the effect of crossover use in cross-domain optimisation is explored.

Touchscreen mobile devices often use cut-down versions of desktop user interfaces placing high demands on the visual sense that may prove awkward in mobile settings. The research in this thesis addresses the problems encountered by situationally impaired mobile users by using crossmodal interaction to exploit the abundant similarities between the audio and tactile modalities. By making information available to both senses, users can receive the information in the most suitable way, without having to abandon their primary task to look at the device. This thesis begins with a literature review of related work followed by a definition of crossmodal icons. Two icons may be considered to be crossmodal if and only if they provide a common representation of data, which is accessible interchangeably via different modalities. Two experiments investigated possible parameters for use in crossmodal icons with results showing that rhythm, texture and spatial location are effective. A third experiment focused on learning multi-dimensional crossmodal icons and the extent to which this learning transfers between modalities. The results showed identification rates of 92% for three-dimensional audio crossmodal icons when trained in the tactile equivalents, and identification rates of 89% for tactile crossmodal icons when trained in the audio equivalent. Crossmodal icons were then incorporated into a mobile touchscreen QWERTY keyboard. Experiments showed that keyboards with audio or tactile feedback produce fewer errors and greater speeds of text entry compared to standard touchscreen keyboards. The next study examined how environmental variables affect user performance with the same keyboard. The data showed that each modality performs differently with varying levels of background noise or vibration and the exact levels at which these performance decreases occur were established. The final study involved a longitudinal evaluation of a touchscreen application, CrossTrainer, focusing on longitudinal effects on performance with audio and tactile feedback, the impact of context on performance and personal modality preference. The results show that crossmodal audio and tactile icons are a valid method of presenting information to situationally impaired mobile touchscreen users with recognitions rates of 100% over time. This thesis concludes with a set of guidelines on the design and application of crossmodal audio and tactile feedback to enable application and interface designers to employ such feedback in all systems.

Inactivation of bacteriophages MS-2 and PRD1, and poliovirus type 1 were measured in Pima Clay Loam and Brazito Sandy Loam soils amended with anaerobically digested sewage sludge. Inactivation was determined at 15°C, 27°C, and 40°C with soils maintained at 30% moisture, and amended soils exposed to evaporation. No inactivation of PRD1 was observed within 30 days and 16 days at 15°C and 27°C respectively with little inactivation after 7 days at 40°C. Inactivation of MS-2 and poliovirus was approximately 2 fold greater at 27°C compared to 16°C. At 40°C neither virus was recovered 24 hours after sludge amendment. Evaporation to less than 5% soil moisture resulted in rapid loss of titer for all three viruses regardless of temperature. Survival of MS-2 and poliovirus 1 in sludge amended fields (15°C) was longer than comparable laboratory studies. None of the viruses were recovered in fields amended during the summer (33°C) after 7 days. A method was also developed to remove cell culture toxic components from these soils.

The antibacterial effect of electrolytically generated copper and silver separately and combined with free chlorine on Listeria monocytogenes was evaluated in filtered well water (FWW) and autoclaved dairy process water (ADPW). The inactivation rate (k = log10 reduction/minute) was determined. Slow bactericidal effects were observed in both FWW and ADPW after exposure to 400:40 or 800:80 mug/L copper and silver compared to 0.15 mg/L chlorine. At least five hours of exposure was required for a 6 log10 reduction in the bacterial numbers with copper and silver; however, with chlorine, the exposure time was reduced to less than one minute for the FWW. Addition of 0.15 mg/L chlorine to water containing copper and silver resulted in a significantly enhanced inactivation rate as compared to chlorine alone in both FWW and ADPW. In ADPW, chlorine with copper (400, 800 mug/L) resulted in an increased k value compared to chlorine alone and copper alone.

The nutritional and chemical properties of three Chinese pollens, sorghum (Sorghum sp.), rapeseed (Brassica napus) and sunflower (Helianthus annuus), were studied. All three pollens were highly preferred, with sunflower pollen the highest, by young honey bees (Apis mellifera). Rapeseed pollen increased honey bee's longevity the greatest; however, sorghum and sunflower pollens also increased the longevity relative to the no-pollen group. All three pollens had high energy (about 5 kcal/g) and carbohydrate quantities (58%). The protein, fat, and fiber levels were 27%, 7%, and 9% in rapeseed pollen, 26%, 5%, and 13% in sorghum pollen, and 15%, 5%, and 10% in sunflower pollen. alpha-Tocopherol was high in sunflower pollen (61 μg/g), lower in rapeseed (33 μg/g) and sorghum pollen (15 μg/g). K, Ca, Mg, Fe, Cu, and Mn were high in all three pollens. These data suggest that a pollen which is highly preferred by honey bees is not necessarily the most nutritious.

This thesis is concerned with the application of system identification techniques to the analysis of complex physiological systems. The techniques are applied to neuronal spike-train data obtained from elements of the neuromuscular system. A brief description of the neuromuscular system is given in chapter 1, along with a more detailed discussion of the muscle spindle, which is the component of the neuromuscular system which this study deals with. In addition, some possibilities for system identification studies of the muscle spindle are discussed. The identification procedure is based on statistical methods for the treatment of point-process data. The point-process representation of a spike-train is introduced in chapter 2 with definitions of time and frequency domain point-process parameters. Estimates for these parameters are given, along with expressions for their asymptotic distributions. The linear point-process system identification model is introduced and estimates are described for the model parameters in terms of the previously defined point-process parameters. These point-process and linear parameter estimates are applied to muscle spindle spike-train data. In the analysis of a single spike-train certain important features only show up in the frequency domain, and for input and output spike-trains a linear transfer function type description is constructed in the frequency domain. The mathematical model of this transfer function is used as the basis for an analogue computer simulation of a subsystem of the muscle spindle. This consists of a linear first order filter followed by an encoder which generates output spikes. Data logged from the simulation is processed in the same manner as experimental data, and the effect of varying the simulation parameters on the linear model estimates is looked at. It is shown that in general the linear model description reflects the properties of the linear filter in the simulation, and varying the simulation parameters can be used to accurately match results from simulated data with those obtained from real data. Chapter 3 compares the point-process approach with a more conventional filtering and sampled data approach to estimate power spectra. The filtering of spike-trains with broad band spectra is investigated, and this shows up a pitfall in the choice of filter cut-off frequency. It is concluded that the point-process approach is preferable due to shorter computational times, and the well documented statistical propeties of the point-process estimates. The application of the point-process techniques described in chapter 2 to the analysis of more general spike-train data is considered in chapter 4. Three techniques for measuring the degree of coupling between two spike-trains are compared, and the point-process frequency domain measure is found to be the most sensitive. This measure is also applied to a data set containing a strong single periodicity, and the ability to detect coupling at a single harmonic is demonstrated. The analysis of coupling between spike-trains in the frequency domain is extended to deal with multiple spike-trains, and the ability to distinguish genuine coupling from the effect of a common input is shown to be a powerful tool which can be used to investigate communications pathways in neural systems. Finally, one special feature of the muscle spindle response to a spike-train input is analysed using the simulation. It is demonstrated that the point-process approach can produce results about a particular phenomenon from a single experiment much more rapidly than using a repetitive trial and error approach. Chapter 5 considers the extension of the linear point-process identification model introduced in chapter 2. Higher order time and frequency domain point-process parameters are defined and estimates given. In the time domain, a new technique for rapidly generating higher order time domain parameters is developed. The quadratic point-process model is introduced and solutions for its parameters given. These estimates are applied to muscle