An investigation into the expert performance approach using tests of visual and motion perception

The Expert-Performance Approach suggests that in order to gain the most accurate reflection of human behaviour, scientific experiments must employ designs that represent the natural environment as closely as possible. By adopting this approach, the ability to identify expert-novice differences in measures (such as visual ability) is enhanced. Too often in the sporting literature this has been neglected, and may explain why the research on visual differences between athletes and non-athletes is so ambiguous. The present study aims to address this. 60 athletes performed a series of visual and motion tests on a computer. For each test, between 6-9 versions were run, with the response stimulus being modified in each version so that it reflected either the sport of the athlete (associate), an opposing sport (dissociate), or unbiased source (neutral). The results indicate the selective attention, motion perception, and the ability to discriminate direction of motion were all greater in the associate tests than in the dissociate tests. There was no difference in divided attention. These results lend support for the adoption of the Expert-Performance Approach in sports testing. Athletes show superior visual and perceptual functioning for stimuli which reflect their natural environment best

Vision testing and visual training in sport

This thesis examines vision testing and visual training in sport. Through four related studies, the predictive ability of visual and perceptual tests was examined in a range of activities including driving and one-handed ball catching. The potential benefits of visual training methods were investigated (with particular emphasis on stroboscopic training), as well as the mechanisms that may underpin any changes. A key theme throughout the thesis was that of task representativeness; a concept by which it is believed the more a study design reflects the environment it is meant to predict, the more valid and reliable the results obtained are. Chapter one is a review of the literature highlighting the key areas which the thesis as a whole addresses. Chapter’s two to five include the studies undertaken in this thesis and follow the same format each time; an introduction to the relevant research, a methods section detailing the experimental procedure, a results section which statistically analysed the measures employed, and a discussion of the findings with reference to the existing literature. Finally, in chapter six the strengths and limitations of the thesis are considered, before suggestions are made for future studies, and concluding remarks made

Observation of large-scale multi-agent based simulations

The computational cost of large-scale multi-agent based simulations (MABS) can be extremely important, especially if simulations have to be monitored for validation purposes. In this paper, two methods, based on self-observation and statistical survey theory, are introduced in order to optimize the computation of observations in MABS. An empirical comparison of the computational cost of these methods is performed on a toy problem

Exploring the relationship between mindset and psychological factors linked to doping

Mindset refers to the way in which one attributes his or her abilities and traits as either ‘fixed’ (e.g., immutable), ‘growth’ (e.g., highly malleable), or somewhere in between. It is possible that mindset may be related to psychological factors linked to doping – such as doping moral disengagement (MD) and doping self-regulatory efficacy (SRE) – though no research as yet has confirmed this. In the present study, 322 student-athletes completed a questionnaire pack measuring mindset and various psychological factors linked to doping. Structural equation modeling provided strong support for all study hypotheses. Specifically, we established: (a) mindset positively predicted doping SRE, (b) mindset negatively predicted doping MD, (c) doping MD positively predicted susceptibility to intentional and inadvertent doping, (d) doping MD negatively predicted anticipated guilt, (e) anticipated guilt negatively predicted susceptibility to intentional and inadvertent doping. In addition, significant negative correlations were found between MSA and doping moral disengagement (r = -.19, p < .01), MSA and susceptibility to inadvertent doping (r = -.11, p < .01), MMC and moral disengagement (r = -.12, p < .05), and MMC and susceptibility to inadvertent doping (r = -.13, p < .05). A significant positive correlation was found between MSA and doping SRE (r = .23, p < .01). Implications of the findings include the potential for early identification of athletes at risk of doping based on their mindset. Future research should look to explore the effectiveness of mindset interventions on reducing transgressive doping attitudes and behaviours

Simulating the Multi-Epoch Direct Detection Technique to Isolate the Thermal Emission of the Non-Transiting Hot Jupiter HD187123B

We report the 6.5$\sigma$ detection of water from the hot Jupiter HD187123b with a Keplerian orbital velocity $K_p$ of 53 $\pm$ 13 km/s. This high confidence detection is made using a multi-epoch, high resolution, cross correlation technique, and corresponds to a planetary mass of 1.4$^{+0.5}_{-0.3}$ $M_J$ and an orbital inclination of 21 $\pm$ 5$^{\circ}$. The technique works by treating the planet/star system as a spectroscopic binary and obtaining high signal-to-noise, high resolution observations at multiple points across the planet's orbit to constrain the system's binary dynamical motion. All together, seven epochs of Keck/NIRSPEC $L$-band observations were obtained, with five before the instrument upgrade and two after. Using high resolution SCARLET planetary and PHOENIX stellar spectral models, along with a line-by-line telluric absorption model, we were able to drastically increase the confidence of the detection by running simulations that could reproduce, and thus remove, the non-random structured noise in the final likelihood space well. The ability to predict multi-epoch results will be extremely useful for furthering the technique. Here, we use these simulations to compare three different approaches to combining the cross correlations of high resolution spectra and find that the Zucker 2003 log(L) approach is least affected by unwanted planet/star correlation for our HD187123 data set. Furthermore, we find that the same total S/N spread across an orbit in many, lower S/N epochs rather than fewer, higher S/N epochs could provide a more efficient detection. This work provides a necessary validation of multi-epoch simulations which can be used to guide future observations and will be key to studying the atmospheres of further separated, non-transiting exoplanets.Comment: Accepted to AJ, 14 pages, 10 figure

Deep learning cardiac motion analysis for human survival prediction

Motion analysis is used in computer vision to understand the behaviour of moving objects in sequences of images. Optimising the interpretation of dynamic biological systems requires accurate and precise motion tracking as well as efficient representations of high-dimensional motion trajectories so that these can be used for prediction tasks. Here we use image sequences of the heart, acquired using cardiac magnetic resonance imaging, to create time-resolved three-dimensional segmentations using a fully convolutional network trained on anatomical shape priors. This dense motion model formed the input to a supervised denoising autoencoder (4Dsurvival), which is a hybrid network consisting of an autoencoder that learns a task-specific latent code representation trained on observed outcome data, yielding a latent representation optimised for survival prediction. To handle right-censored survival outcomes, our network used a Cox partial likelihood loss function. In a study of 302 patients the predictive accuracy (quantified by Harrell's C-index) was significantly higher (p < .0001) for our model C=0.73 (95$\%$ CI: 0.68 - 0.78) than the human benchmark of C=0.59 (95$\%$ CI: 0.53 - 0.65). This work demonstrates how a complex computer vision task using high-dimensional medical image data can efficiently predict human survival

Comparing awareness of mental health issues and cognitive behavioural therapy in male and female UK Premier League academy soccer players and university students

The aim of this study was to obtain information regarding elite soccer academy players’ and university students’ awareness of common mental disorders and intervention options. A cross-sectional design compared perceptions of male and female Premier League soccer academy players with those of male and female university students using a custom-made questionnaire. The prevalence of experiences of anxiety and depression was high in all groups. Significantly less male soccer players had heard of cognitive behavioural therapy (CBT) or knew what CBT was compared with all other groups. Barriers to obtaining support for mental health concerns included not knowing how or when to seek help and what treatment entailed. Participants indicated that they would first turn to family and friends rather than coaches or professionals for help. A preference for CBT over counselling was indicated by the majority of the soccer players and students. The findings of this study can be applied during the development of suitable evidence-based interventions tailored for elite academy soccer players

A qualitative exploration of the positive and negative experiences of individuals who play fantasy football

Fantasy football (FF) has become an increasingly popular activity and recent quantitative research has explored the potential impact it can have on mental health. The aim of the present study was to take a qualitative approach to obtain a deeper understanding of the experiences of FF players. Thematic analysis of semi-structured interviews with 15 experienced FF players led to the identification of 4 meta themes: Potential Positives (of which there were 3 further themes and 15 further sub-themes), Potential Negatives (3 further themes; 12 further sub-themes), Mediating Factors (4 further themes; 4 further sub-themes), and Future Game Play (2 further themes; 6 further sub-themes). Based on these results, we have proposed: i) a model for initial and continued involvement in FF, and ii) a framework of hypothesised factors leading to predominantly positive or negative experiences in FF. We discuss how these findings can be used by players and game creators alike in order to optimise the experience of playing FF

Deprivation and prognosis in patients with Pulmonary Arterial Hypertension: missing the effect of deprivation on a rare disease?

In this journal, Pellino et al presented survival analysis to assess how deprivation affects prognosis in patients with pulmonary arterial hypertension (PAH)1. Their conclusions were that social deprivation is not a significant referral barrier or prognostic factor for idiopathic (I)PAH or heritable (H)PAH in Scotland. This may appear surprising given the wider context of literature describing outcomes stratified by social deprivation. The authors were thorough on using both the address at time of diagnosis and at time of censoring to assign deprivation scores and compare the two, finding no significant differences between the two approaches. They also compared deprivation assigned to PAH cases to expected deprivation based on Scottish citizenry as a whole and found that PAH patients are more socially deprived than expected. Finally, they used the same survival univariate analysis adjusting for age and sex to assess how several clinical variables are associated with prognosis