Personal Injury Liability in Sport: Emerging Trends

Violent play during the course of a game or sport is not a new phenomenon; accompanying legal proceedings are. This article considers personal injury liability for injuries inflicted by a participant upon an opponent during a sporting pursuit. The jurisdictional focus is on England and Wales. The sporting emphasis of the article is on competitive, body contact games. The legal emphasis is on the tort of negligence. Analogous to the law of criminal assault, breach of "implied sporting consent" or the volenti of the claimant will be seen as central in application, as assessed through a number of objective criteria, including the skill level of the injuring party and whether that defendant was acting in "reckless disregard" of the claimant's safety. These criteria or evidential guidelines, which emerge from a careful doctrinal analysis of the relevant case law, are seen as crucial to the examination of the appropriate degree of care in negligence within the prevailing circumstances of sport. The article also searches for some theoretical coherency within the case law, premising it on Fletcher's idea of reciprocal risk-taking. In addition, the underlying policy-related issue of sport's social utility is discussed, as are practical matters relating to vicarious liability, insurance and the measure of damages for "lost sporting opportunity". Moreover, it will be shown that personal injury claims relating to sports participant liability now extend to a consideration of the duties of coaches, referees, sports governing bodies and schools. Finally, this article is set against the backdrop of an apparently spiralling "compensation culture" and the concomitant threat that that "blame culture" poses for the future promotion, operation and administration of sport.

Estimation of ternary liquid-liquid equilibria for arene/alkane/ionic liquid mixtures using neural networks

Neural network models have been explored for the prediction of the liquid-liquid equilibrium data and aromatic/aliphatic selectivity values. Four ternary systems composed of toluene, heptane, and the ionic liquids 1-ethyl-3-methylimidazolium ethylsulfate, or 1,3-dimethylimidazolium methylsulfate were investigated at 313.2 and 348.2 K.

Robust face recognition using posterior union model based neural networks

Face recognition with unknown, partial distortion and occlusion is a practical problem, and has a wide range of applications, including security and multimedia information retrieval. The authors present a new approach to face recognition subject to unknown, partial distortion and occlusion. The new approach is based on a probabilistic decision-based neural network, enhanced by a statistical method called the posterior union model (PUM). PUM is an approach for ignoring severely mismatched local features and focusing the recognition mainly on the reliable local features. It thereby improves the robustness while assuming no prior information about the corruption. We call the new approach the posterior union decision-based neural network (PUDBNN). The new PUDBNN model has been evaluated on three face image databases (XM2VTS, AT&T and AR) using testing images subjected to various types of simulated and realistic partial distortion and occlusion. The new system has been compared to other approaches and has demonstrated improved performance.

Integrated structure selection and parameter optimisation for eng-genes neural models

The eng-genes concept involves the use of fundamental known system functions as activation functions in a neural model to create a 'grey-box' neural network. One of the main issues in eng-genes modelling is to produce a parsimonious model given a model construction criterion. The challenges are that (1) the eng-genes model in most cases is a heterogenous network consisting of more than one type of nonlinear basis functions, and each basis function may have different set of parameters to be optimised; (2) the number of hidden nodes has to be chosen based on a model selection criterion. This is a mixed integer hard problem and this paper investigates the use of a forward selection algorithm to optimise both the network structure and the parameters of the system-derived activation functions. Results are included from case studies performed on a simulated continuously stirred tank reactor process, and using actual data from a pH neutralisation plant. The resulting eng-genes networks demonstrate superior simulation performance and transparency over a range of network sizes when compared to conventional neural models. (c) 2007 Elsevier B.V. All rights reserved.

Application of auto-associative neural networks to transient fault detection in an IC engine

The tailpipe emissions from automotive engines have been subject to steadily reducing legislative limits. This reduction has been achieved through the addition of sub-systems to the basic four-stroke engine which thereby increases its complexity. To ensure the entire system functions correctly, each system and / or sub-systems needs to be continuously monitored for the presence of any faults or malfunctions. This is a requirement detailed within the On-Board Diagnostic (OBD) legislation. To date, a physical model approach has been adopted by me automotive industry for the monitoring requirement of OBD legislation. However, this approach has restrictions from the available knowledge base and computational load required. A neural network technique incorporating Multivariant Statistical Process Control (MSPC) has been proposed as an alternative method of building interrelationships between the measured variables and monitoring the correct operation of the engine. Building upon earlier work for steady state fault detection, this paper details the use of non-linear models based on an Auto-associate Neural Network (ANN) for fault detection under transient engine operation. The theory and use of the technique is shown in this paper with the application to the detection of air leaks within the inlet manifold system of a modern gasoline engine whilst operated on a pseudo-drive cycle. Copyright © 2007 by ASME.

Neural network based control for synchronous generators

In this paper, a Radial Basis Function neural network based AVR is proposed. A control strategy which generates local linear models from a global neural model on-line is used to derive controller feedback gains based on the Generalised Minimum Variance technique. Testing is carried out on a micromachine system which enables evaluation of practical implementation of the scheme. Constraints imposed by gathering training data, computational load, and memory requirements for the training algorithm are addressed.

A fast method for fuzzy neural modeling and refinement

In the identification of complex dynamic systems using fuzzy neural networks, one of the main issues is the curse of dimensionality, which makes it difficult to retain a large number of system inputs or to consider a large number of fuzzy sets. Moreover, due to the correlations, not all possible network inputs or regression vectors in the network are necessary and adding them simply increases the model complexity and deteriorates the network generalisation performance. In this paper, the problem is solved by first proposing a fast algorithm for selection of network terms, and then introducing a refinement procedure to tackle the correlation issue. Simulation results show the efficacy of the method.

The Effects of Cilostazol on Exercise-induced Ischaemia-reperfusion Injury in Patients with Peripheral Arterial Disease

Objectives: Cilostazol improves walking distance in peripheral arterial disease (PAD) patients. The study objectives were to assess the effects of cilostazol on walking distance, followed by the additional assessment of cilostazol on exercise-induced ischaemiaereperfusion injury in such patients.

Methods: PAD patients were prospectively recruited to a double-blinded, placebo-controlled trial. Patients were randomised to receive either cilostazol 100 mg or placebo twice a day. The primary end-point was an improvement in walking distance. Secondary end-points included the assessment of oxygen-derived free-radical generation, antioxidant consumption and other markers of the in?ammatory cascade. Initial and absolute claudication distances (ICDs and ACDs, respectively) were measured on a treadmill. In?ammatory response was assessed before and 30 min post-exercise by measuring lipid hydroperoxide, ascorbate, atocopherol, b-carotene, P-selectin, intracellular and vascular cell-adhesion molecules (I-CAM and V-CAM), thromboxane B2 (TXB2), interleukin-6, interleukin-10, high-sensitive C-reactive protein (hsCRP), albuminecreatinine ratio (ACR) and urinary levels of p75TNF receptor. All tests were performed at baseline and 6 and 24 weeks.

Results: One hundred and six PAD patients (of whom 73 were males) were recruited and successfully randomised from December 2004 to January 2006. Patients who received cilostazol demonstrated a more signi?cant improvement in the mean percentage change from baseline in ACD (77.2% vs. 26.6% at 6 weeks, pZ0.026 and 161.7% vs. 79.0% at 24 weeks, pZ0.048) as compared to the placebo. Cilostazol reduced lipid hydroperoxide levels compared to a placebo-related increase before and after exercise (6 weeks: pre-exercise: 11.8% vs.

Interviewing children with acquired brain injury (ABI).

Research into the lives of children with acquired brain injury (ABI) often neglects to incorporate children as participants, preferring to obtain the opinions of the adult carer (e.g. McKinlay et al., 2002). There has been a concerted attempt to move away from this position by those working in children’s research with current etiquette highlighting the inclusion of children and the use of a child-friendly methodology (Chappell, 2000). Children with disabilities can represent a challenge to the qualitative researcher due to the combination of maintaining the child’s attention and the demands placed on them by their disability. The focus of this article is to discuss possible impediments to interviewing children with acquired brain injury (ABI) and provide an insight into how the qualitative researcher may address these.