Is bodybuilding a sport?

Since its beginnings, modern bodybuilding has been accompanied by the background issue of whether it should be considered a sport. The problem, culminating in its provisional acceptance as a sport by the International Olympic Committee, was later retracted. The uncertainty of whether bodybuilding is a sport or not seems to linger. Addressing this issue, Aranyosi (2018) provided an account to determine the status of bodybuilding as a sport that arrives at the negative answer: bodybuilding is not a sport but rather a form of artistic presentation. In this paper, we disagree with Aranyosi. We argue that by the standards he presents in his first argument, bodybuilding should be considered a sport. Further, we argue that his alternative approach on how to evaluate a discipline as more sport- or art-like on a spectrum, is not a valid basis to make such a judgment regarding bodybuilding. Further, even if his spectrum was modified to enable such a judgment, again it would result in bodybuilding being evaluated as a sport. Therefore, we conclude that everyone who accepts Aranyosi´s (or any less restrictive) requirements to decide whether bodybuilding is a sport, has to consider bodybuilding as a sport or refrain from making claims about its status.Peer Reviewe

Modelling the influence of the process inputs on the removal of surface contaminants from Ti-6Al-4V linear friction welds

The linear friction welding (LFW) process is finding increasing interest from industry for the fabrication of near-net-shape, titanium alloy Ti–6Al–4V, aerospace components. Currently, the removal of surface contaminants, such as oxides and foreign particles, from the weld interface into the flash is not fully understood. To address this problem, two-dimensional (2D) computational models were developed using the finite element analysis (FEA) software DEFORM and validated with experiments. The key findings showed that the welds made with higher applied forces required less burn-off to completely remove the surface contaminants from the interface into the flash; the interface temperature increased as the applied force was decreased or the rubbing velocity increased; and the boundary temperature between the rapid flash formation and negligible material flow was approximately 970 °C. An understanding of these phenomena is of particular interest for the industrialisation of near-net-shape titanium alloy aerospace components.EPSRC, Boeing Company, Welding Institut

U4D: Unsupervised 4D Dynamic Scene Understanding

We introduce the first approach to solve the challenging problem of unsupervised 4D visual scene understanding for complex dynamic scenes with multiple interacting people from multi-view video. Our approach simultaneously estimates a detailed model that includes a per-pixel semantically and temporally coherent reconstruction, together with instance-level segmentation exploiting photo-consistency, semantic and motion information. We further leverage recent advances in 3D pose estimation to constrain the joint semantic instance segmentation and 4D temporally coherent reconstruction. This enables per person semantic instance segmentation of multiple interacting people in complex dynamic scenes. Extensive evaluation of the joint visual scene understanding framework against state-of-the-art methods on challenging indoor and outdoor sequences demonstrates a significant (approx 40%) improvement in semantic segmentation, reconstruction and scene flow accuracy.Comment: To appear in IEEE International Conference in Computer Vision ICCV 201

Analysing speeding behaviour: A multilevel modelling approach

This paper examines the variability in speeding for 147 motorists over a five-week period using data collected from Global Positioning System (GPS) technology. A multilevel modelling approach is employed to decompose speeding behaviour into four major levels of variation, namely: inter-individual variation, temporal variation, trip-level variation, and segment level variation. Initially, we estimate a null model (i.e., excludes the explanatory variables) to assess the variations at each level. Results suggest that the driver is more of a factor in speeding as the speed limit increases but that the majority of variation in speeding goes unexplained. This is followed by progressively including explanatory variables (e.g., age, gender, vehicle type, trips purpose etc) at each of the four levels to assess how much more of the variation in speeding can be explained. Results suggest that the reduction in unexplained variance in speeding varies markedly by speed zone, indicating the disproportionately different impacts of explanatory factors

Assessment of the learning curve in health technologies: a systematic review

Objective: We reviewed and appraised the methods by which the issue of the learning curve has been addressed during health technology assessment in the past. Method: We performed a systematic review of papers in clinical databases (BIOSIS, CINAHL, Cochrane Library, EMBASE, HealthSTAR, MEDLINE, Science Citation Index, and Social Science Citation Index) using the search term "learning curve:" Results: The clinical search retrieved 4,571 abstracts for assessment, of which 559 (12%) published articles were eligible for review. Of these, 272 were judged to have formally assessed a learning curve. The procedures assessed were minimal access (51%), other surgical (41%), and diagnostic (8%). The majority of the studies were case series (95%). Some 47% of studies addressed only individual operator performance and 52% addressed institutional performance. The data were collected prospectively in 40%, retrospectively in 26%, and the method was unclear for 31%. The statistical methods used were simple graphs (44%), splitting the data chronologically and performing a t test or chi-squared test (60%), curve fitting (12%), and other model fitting (5%). Conclusions: Learning curves are rarely considered formally in health technology assessment. Where they are, the reporting of the studies and the statistical methods used are weak. As a minimum, reporting of learning should include the number and experience of the operators and a detailed description of data collection. Improved statistical methods would enhance the assessment of health technologies that require learning