Travelling-wave model of semiconductor optical amplifier based non-linear loop mirror

A travelling-wave model of a semiconductor optical amplifier based non-linear loop mirror is developed to investigate the importance of travelling-wave effects and gain/phase dynamics in predicting device behaviour. A constant effective carrier recovery lifetime approximation is found to be reasonably accurate (±10%) within a wide range of control pulse energies. Based on this approximation, a heuristic model is developed for maximum computational efficiency. The models are applied to a particular configuration involving feedback.

Concentration polarization model of spiral-wound membrane modules with application to batch-mode RO desalination of brackish water

Batch-mode reverse osmosis (batch-RO) operation is considered a promising desalination method due to its low energy requirement compared to other RO system arrangements. To improve and predict batch-RO performance, studies on concentration polarization (CP) are carried out. The Kimura-Sourirajan mass-transfer model is applied and validated by experimentation with two different spiral-wound RO elements. Explicit analytical Sherwood correlations are derived based on experimental results. For batch-RO operation, a new genetic algorithm method is developed to estimate the Sherwood correlation parameters, taking into account the effects of variation in operating parameters. Analytical procedures are presented, then the mass transfer coefficient models are developed for different operation processes, i.e., batch-RO and continuous RO. The CP related energy loss in batch-RO operation is quantified based on the resulting relationship between feed flow rates and mass transfer coefficients. It is found that CP increases energy consumption in batch-RO by about 25% compared to the ideal case in which CP is absent. For continuous RO process, the derived Sherwood correlation predicted CP accurately. In addition, we determined the optimum feed flow rate of our batch-RO system.

A geometrical model for surface roughness prediction when face milling Al 7075-T7351 with square insert tools

Surface quality is important in engineering and a vital aspect of it is surface roughness, since it plays an important role in wear resistance, ductility, tensile, and fatigue strength for machined parts. This paper reports on a research study on the development of a geometrical model for surface roughness prediction when face milling with square inserts. The model is based on a geometrical analysis of the recreation of the tool trail left on the machined surface. The model has been validated with experimental data obtained for high speed milling of aluminum alloy (Al 7075-T7351) when using a wide range of cutting speed, feed per tooth, axial depth of cut and different values of tool nose radius (0.8. mm and 2.5. mm), using the Taguchi method as the design of experiments. The experimental roughness was obtained by measuring the surface roughness of the milled surfaces with a non-contact profilometer. The developed model can be used for any combination of material workpiece and tool, when tool flank wear is not considered and is suitable for using any tool diameter with any number of teeth and tool nose radius. The results show that the developed model achieved an excellent performance with almost 98% accuracy in terms of predicting the surface roughness when compared to the experimental data. © 2014 The Society of Manufacturing Engineers.

Placebo expectancy effect of consuming psychoactive beverages on cognition and mood

Energy drinks have become very popular over the past few years with over half the student population in colleges and universities consuming them at least once a month (Malinauskas et al., 2007). It has been reported that the most common reasons why students consume energy drinks are to maintain alertness, reduce symptoms of hangover, increase energy, to help with driving and to prevent sleepiness (Attila and Cakir, 2011; Malinauskas et al., 2007). Previous research has suggested that energy drinks enhance sensorimotor speed, behaviour, and reduce levels of fatigue (Alford et al., 2001; Horne and Reyner, 2001; Howard and Marczinski, 2010; Kennedy and Scholey, 2004; Smit et al., 2004). The two key ingredients found in energy drinks are caffeine and glucose which have been examined together and alone, which have indicated enhanced reaction times, improvement in both verbal memory and sustained attention and more recently there is evidence to show that expectancy may play a key role in predicting intentions of future consumption (Adan and serra-Grabulosa, 2010). According to Kirsch (1997) people have specific expectations when they consume psychoactive substances that trigger physiological and psychological reactions, which tend to be independent of the psychoactive substance ingested. The concept of expectancy effects can be unambiguous especially when the information provided to the participants prior to the experimental study is specific to a possible outcome response. This thesis investigated the extent of expectancy effect on cognition and mood when psychoactive drinks containing caffeine and glucose were consumed in comparison to non-psychoactive drinks. The investigation commenced with examining the independent effects of caffeine and glucose, followed by the combination of caffeine and glucose as an energy drink on mood and cognition. The investigation advanced by comparing drink presentation effects (i.e., consuming the experimental drink from a branded bottle versus from a glass) irrespective of drink content on mood and cognition. Finally, the investigation lead to exploring what factors may predict expectancy effects when participants’ consumed psychoactive drinks among healthy adults. This was done by applying the Theory of Planned Behaviour model (TPB) (Azjen, 1991) to explore the contribution of specific attitudes, subjective norms and perceived behavioural control to the extent of expectancy effects as well as to behavioural intention, with additional variables including; beliefs, habits, past-behaviour, selfidentity. Self-identity representing someone who drinks energy drinks regularly. The level of internal consistency for Cronbach’s alpha was conducted for each variable within the TPB model and for the additional variables included for test reliability. This thesis consisted of four studies, which found that consumption of caffeine and glucose independently and also in combination resulted in psychoactive effects on mood and cognition. Experiment 2 was the only study, which indicated an expectancy effect for immediate verbal recall task and the mood subscale tension. Conversely, for experiment 4 there was a reverse effect found for the immediate verbal recall task. However, there were significant expectancy and psychoactive effects found for mood subscales throughout the four studies. It was also found that the TPB model had two significant variables past-behaviour and self-identity predicted intentions suggesting that participants who regularly consume psychoactive beverages have salient beliefs about consuming psychoactive drinks and the TPB model can be utilised to predict their intentions. Furthermore, the Theory of planned behaviour model found that habit and self-identity significantly predicted participants’ expectancy effects on the vigour. Indicating consumers of energy drinks are familiar with expected outcome response. This model was unsuccessful in predicting expectancy response for cognitive performance. Thus, overall the findings from the four studies indicated that caffeine and glucose have cognitive enhancing properties, which also positively improve mood. However, expectancy effects have been identified for mood only, whereas the overall findings within this thesis were unable to identify significant predictors of expectancy effect and response.

Predicting answering behaviour in online question answering communities

The value of Question Answering (Q&A) communities is dependent on members of the community finding the questions they are most willing and able to answer. This can be difficult in communities with a high volume of questions. Much previous has work attempted to address this problem by recommending questions similar to those already answered. However, this approach disregards the question selection behaviour of the answers and how it is affected by factors such as question recency and reputation. In this paper, we identify the parameters that correlate with such a behaviour by analysing the users' answering patterns in a Q&A community. We then generate a model to predict which question a user is most likely to answer next. We train Learning to Rank (LTR) models to predict question selections using various user, question and thread feature sets. We show that answering behaviour can be predicted with a high level of success, and highlight the particular features that inuence users' question selections.

Investigating the role of parent and child characteristics in healthy eating intervention outcomes

While numerous studies have investigated the efficacy of interventions at increasing children's vegetable consumption, little research has examined the effect of individual characteristics on intervention outcomes. In previous research, interventions consisting of modelling and rewards have been shown to increase children's vegetable intake, but differences were identified in terms of how much children respond to such interventions. With this in mind, the current study investigated the role of parental feeding practices, child temperament, and child eating behaviours as predictors of intervention success. Parents (N = 90) of children aged 2-4 years were recruited from toddler groups across Leicestershire, UK. Parents completed measures of feeding practices, child eating behaviours and child temperament, before participating in one of four conditions of a home-based, parent led 14 day intervention aimed at increasing their child's consumption of a disliked vegetable. Correlations and logistic regressions were performed to investigate the role of these factors in predicting intervention success. Parental feeding practices were not significantly associated with intervention success. However, child sociability and food fussiness significantly predicted intervention success, producing a regression model which could predict intervention success in 61% of cases. These findings suggest that future interventions could benefit from being tailored according to child temperament. Furthermore, interventions for children high in food fussiness may be better targeted at reducing fussiness in addition to increasing vegetable consumption.