MK Dons FC and AFC Wimbledon: moving the goalposts and rising from the ashes

This case study provides an insight into a unique and unprecedented event in English professional football: the relocation of a major club to a completely different geographical area. The ruling, in 2002, was hugely controversial, and effectively spawned two entirely new entities: MK Dons FC, who took the place of Wimbledon FC in the Football League and based themselves in Milton Keynes, 60 miles away from the original club; and AFC Wimbledon, a fan- owned ‘phoenix’ club which started again at the bottom of the football pyramid and is located near to Wimbledon FC’s original home. Despite their creation resulting from the same event, the two newly created clubs are notable for their contrasting ownership models and the reaction they have received from both the media and the wider football community in Great Britain

MK Dons FC and AFC Wimbledon: moving the goalposts and rising from the ashes

The aim of this paper will be to compare a franchise and fan-ownership model within a European sports team context, and conclude what the key learnings are for sport managers. In particular, the paper will examine an unprecedented event in English football, the relocation of a major professional club to a completely different geographical area and the resulting creation of an additional fan-owned 'phoenix club'

Notes on noncommutative supersymmetric gauge theory on the fuzzy supersphere

In these notes we review Klimcik's construction of noncommutative gauge theory on the fuzzy supersphere. This theory has an exact SUSY gauge symmetry with a finite number of degrees of freedom and thus in principle it is amenable to the methods of matrix models and Monte Carlo numerical simulations. We also write down in this article a novel fuzzy supersymmetric scalar action on the fuzzy supersphere

Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models

Wind farm modelling has been an area of rapidly increasing interest with numerous analytical as well as computational-based approaches developed to extend the margins of wind farm efficiency and maximise power production. In this work, we present the novel ML framework WakeNet, which can reproduce generalised 2D turbine wake velocity fields at hub-height over a wide range of yaw angles, wind speeds and turbulence intensities (TIs), with a mean accuracy of 99.8% compared to the solution calculated using the state-of-the-art wind farm modelling software FLORIS. As the generation of sufficient high-fidelity data for network training purposes can be cost-prohibitive, the utility of multi-fidelity transfer learning has also been investigated. Specifically, a network pre-trained on the low-fidelity Gaussian wake model is fine-tuned in order to obtain accurate wake results for the mid-fidelity Curl wake model. The robustness and overall performance of WakeNet on various wake steering control and layout optimisation scenarios has been validated through power-gain heatmaps, obtaining at least 90% of the power gained through optimisation performed with FLORIS directly. We also demonstrate that when utilising the Curl model, WakeNet is able to provide similar power gains to FLORIS, two orders of magnitude faster (e.g. 10 minutes vs 36 hours per optimisation case). The wake evaluation time of wakeNet when trained on a high-fidelity CFD dataset is expected to be similar, thus further increasing computational time gains. These promising results show that generalised wake modelling with ML tools can be accurate enough to contribute towards active yaw and layout optimisation, while producing realistic optimised configurations at a fraction of the computational cost, hence making it feasible to perform real-time active yaw control as well as robust optimisation under uncertainty.Comment: 16 Pages, 18 Figures, 3 Table

Legacy in major sport events: empirical insights from the 2010 FIFA World Cup in South Africa

The awarding of the 2010 FIFA World Cup to South Africa was an historic moment for all of Africa as football’s biggest event travelled to the continent for the first time. This study, set five years on, seeks to identify the legacies left by the construction of two new stadiums in Durban and Cape Town. As part of the EU-funded CARNiVAL project, which seeks to investigate the legacies and impacts of hosting such events, interviews were conducted with key stakeholders involved in the planning of legacies in the two cities. Using Chappelet and Junod’s (2006) framework to analyse the legacies, this study found that Durban and Cape Town have used different strategies to leverage the legacies with differing results. Yet, both stadiums have suffered from the same issue; a seeming lack of need for two stadiums with capacities over 54,000, for domestic sport leagues which average fewer than 10,000 spectators

A new perspective on matter coupling in 2d quantum gravity

We provide compelling evidence that a previously introduced model of non-perturbative 2d Lorentzian quantum gravity exhibits (two-dimensional) flat-space behaviour when coupled to Ising spins. The evidence comes from both a high-temperature expansion and from Monte Carlo simulations of the combined gravity-matter system. This weak-coupling behaviour lends further support to the conclusion that the Lorentzian model is a genuine alternative to Liouville quantum gravity in two dimensions, with a different, and much `smoother' critical behaviour.Comment: 24 pages, 7 figures (postscript

Anomaly Detection in Small-Scale Industrial and Household Appliances

Anomaly detection is concerned with identifying rare events/ observations that differ substantially from the majority of the data. It is considered an important task in the energy sector to enable the identification of non-standard device conditions. The use of anomaly detection techniques in small-scale residential and industrial settings can provide useful insights about device health, maintenance requirements, and downtime, which in turn can lead to lower operating costs. There are numerous approaches for detecting anomalies in a range of application scenarios such as prescriptive appliance maintenance. This work reports on anomaly detection using a data set of fridge power consumption that operates on a near zero energy building scenario. We implement a variety of machine and deep learning algorithms and evaluate performances using multiple metrics. In the light of the present state of the art, the contribution of this work is the development of a inference pipeline that incorporates numerous methodologies and algorithms capable of producing high accuracy results for detecting appliance failures

Relativistic calculations of pionic and kaonic atoms hyperfine structure

We present the relativistic calculation of the hyperfine structure in pionic and kaonic atoms. A perturbation method has been applied to the Klein-Gordon equation to take into account the relativistic corrections. The perturbation operator has been obtained \textit{via} a multipole expansion of the nuclear electromagnetic potential. The hyperfine structure of pionic and kaonic atoms provide an additional term in the quantum electrodynamics calculation of the energy transition of these systems. Such a correction is required for a recent measurement of the pion mass