Chapter X: The Tour de France: a success story in spite of competitive imbalance and doping

International audienceThe chapter goes as follows. In the first section it is demonstrated how the Tour de France is a high quality product. This is a result from its accurate design, its management, its economic model and its finance structure, both in comparison to other mega-sporting events and with reference to tournament theory. It is not easy to assess the competitive balance in the Tour de France since, as was demonstrated in chapter 10, it is at the same time an individual and a team sport contest. After reviewing some results published in literature so far, a new metrics for evaluating competitive balanced in the Tour de France is presented in section 2. Finally, the Tour de France cannot ignore doping as a potential threat to fan attendance and TV viewing. We therefore discuss the issue of doping and a new procedure to deal with doping in section 3

Professional Sports Firm Values: Bringing New Determinants to the Foreground? A Study of European Soccer, 2005-2013

Since 2004, Forbes has proposed a list of the most valuable soccer clubs. One year later, Transfermarkt began to estimate European soccer players’ value. This article estimate the determinants of firm values in European soccer over the period 2005-2013 incorporating player valuations, clubs’ operating income, and new ownership, three variables not included previously. The results of this study demonstrate that these variables are significant factors in club valuations. More generally, club assets including stadium age, club ownership type, supporter numbers and income, and past sports performances all have a significant impact

Prevalence of oropharyngeal beta-lactamase-producing Capnocytophaga spp. in pediatric oncology patients over a ten-year period

BACKGROUND: The aim of this study was to evaluate the prevalence of beta-lactamase-producing Capnocytophaga isolates in young children hospitalized in the Pediatric Oncology Department of Hôpital Sud (Rennes, France) over a ten-year period (1993–2002). METHODS: In neutropenic children, a periodic survey of the oral cavity allows a predictive evaluation of the risk of systemic infections by Capnocytophaga spp. In 449 children with cancer, 3,053 samples were collected by oral swabbing and plated on TBBP agar. The susceptibility of Capnocytophaga isolates to five beta-lactams was determined. RESULTS: A total of 440 strains of Capnocytophaga spp. were isolated, 309 (70%) of which were beta-lactamase producers. The beta-lactamase-producing strains were all resistant to cefazolin, 86% to amoxicillin, and 63% to ceftazidime. The proportion of strains resistant to third-generation cephalosporins remained high throughout the ten-year study, while susceptibility to imipenem and amoxicillin combined with clavulanic acid was always conserved. CONCLUSION: These results highlight the risk of antibiotic failure in Capnocytophaga infections and the importance of monitoring immunosuppressed patients and testing for antibiotic susceptibility and beta-lactamase production

Differential Effects of Attention-, Compassion-, and Socio-Cognitively Based Mental Practices on Self-Reports of Mindfulness and Compassion

Research on the effects of mindfulness- and compassion-based interventions is flourishing along with self-report scales to assess facets of these broad concepts. However, debates remain as to which mental practices are most appropriate to develop the attentional, cognitive, and socio-affective facets of mindfulness and compassion. One crucial question is whether present-moment, attention-focused mindfulness practices are sufficient to induce a cascade of changes across the different proposed facets of mindfulness, including nonjudgmental acceptance, as well as compassion or whether explicit socio-affective training is required. Here, we address these questions in the context of a 9-month longitudinal study (the ReSource Project) by examining the differential effects of three different 3-month mental training modules on subscales of mindfulness and compassion questionnaires. The “Presence” module, which aimed at cultivating present-moment-focused attention and body awareness, led to increases in the observing, nonreacting, and presence subscales, but not to increases in acceptance or nonjudging. These latter facets benefitted from specific cultivation through the socio-cognitive “Perspective” module and socio-affective, compassion-based “Affect” module, respectively. These modules also led to further increases in scores on the subscales affected by the Presence module. Moreover, scores on the compassion scales were uniquely influenced by the Affect module. Thus, whereas a present-moment attention-focused training, as implemented in many mindfulness-based programs, was indeed able to increase attentional facets of mindfulness, only socio-cognitive and compassion-based practices led to broad changes in ethical-motivational qualities like a nonjudgmental attitude, compassion, and self-compassion

Timescales of Multineuronal Activity Patterns Reflect Temporal Structure of Visual Stimuli

The investigation of distributed coding across multiple neurons in the cortex remains to this date a challenge. Our current understanding of collective encoding of information and the relevant timescales is still limited. Most results are restricted to disparate timescales, focused on either very fast, e.g., spike-synchrony, or slow timescales, e.g., firing rate. Here, we investigated systematically multineuronal activity patterns evolving on different timescales, spanning the whole range from spike-synchrony to mean firing rate. Using multi-electrode recordings from cat visual cortex, we show that cortical responses can be described as trajectories in a high-dimensional pattern space. Patterns evolve on a continuum of coexisting timescales that strongly relate to the temporal properties of stimuli. Timescales consistent with the time constants of neuronal membranes and fast synaptic transmission (5–20 ms) play a particularly salient role in encoding a large amount of stimulus-related information. Thus, to faithfully encode the properties of visual stimuli the brain engages multiple neurons into activity patterns evolving on multiple timescales

STDP Allows Fast Rate-Modulated Coding with Poisson-Like Spike Trains

Spike timing-dependent plasticity (STDP) has been shown to enable single neurons to detect repeatedly presented spatiotemporal spike patterns. This holds even when such patterns are embedded in equally dense random spiking activity, that is, in the absence of external reference times such as a stimulus onset. Here we demonstrate, both analytically and numerically, that STDP can also learn repeating rate-modulated patterns, which have received more experimental evidence, for example, through post-stimulus time histograms (PSTHs). Each input spike train is generated from a rate function using a stochastic sampling mechanism, chosen to be an inhomogeneous Poisson process here. Learning is feasible provided significant covarying rate modulations occur within the typical timescale of STDP (∼10–20 ms) for sufficiently many inputs (∼100 among 1000 in our simulations), a condition that is met by many experimental PSTHs. Repeated pattern presentations induce spike-time correlations that are captured by STDP. Despite imprecise input spike times and even variable spike counts, a single trained neuron robustly detects the pattern just a few milliseconds after its presentation. Therefore, temporal imprecision and Poisson-like firing variability are not an obstacle to fast temporal coding. STDP provides an appealing mechanism to learn such rate patterns, which, beyond sensory processing, may also be involved in many cognitive tasks

CuBIC: cumulant based inference of higher-order correlations in massively parallel spike trains

Recent developments in electrophysiological and optical recording techniques enable the simultaneous observation of large numbers of neurons. A meaningful interpretation of the resulting multivariate data, however, presents a serious challenge. In particular, the estimation of higher-order correlations that characterize the cooperative dynamics of groups of neurons is impeded by the combinatorial explosion of the parameter space. The resulting requirements with respect to sample size and recording time has rendered the detection of coordinated neuronal groups exceedingly difficult. Here we describe a novel approach to infer higher-order correlations in massively parallel spike trains that is less susceptible to these problems. Based on the superimposed activity of all recorded neurons, the cumulant-based inference of higher-order correlations (CuBIC) presented here exploits the fact that the absence of higher-order correlations imposes also strong constraints on correlations of lower order. Thus, estimates of only few lower-order cumulants suffice to infer higher-order correlations in the population. As a consequence, CuBIC is much better compatible with the constraints of in vivo recordings than previous approaches, which is shown by a systematic analysis of its parameter dependence