From Youth Team to First Team: An Investigation into the Transition Experiences of Young Professional Athletes in Football

Using Wylleman and Lavallee (2004) and Stambulova (2003) models of transition as conceptual frameworks for the current study, we aimed to explore United Kingdom (UK) professional soccer players’ (N = 5) experiences going through a youth-to-senior career transition to first team level, and assess the immediate changes that occur during the move. Few studies have assessed this process, and no studies have focused on assessing the changes that may occur between pre and post transition. Data collection lasted 1 month with players interviewed twice, 2 weeks before, and 2 weeks after their transition to the first team. Data were abductively thematically content analyzed. Prior to transition, players reported high motivation to be successful, but also feeling anxious about the transition to senior sport. Post-transition, players felt more confident about their ability to succeed in senior sport and maintained high levels of motivation to succeed. Family, friends, coaches, and teammates provided emotional, technical, and tangible support to the players throughout the transition, but were also sources of stress for athletes moving to senior sport. These findings suggest ways to assist transitioning athletes, such as the use of buddy systems with senior players

A Mathematical Framework for Agent Based Models of Complex Biological Networks

Agent-based modeling and simulation is a useful method to study biological phenomena in a wide range of fields, from molecular biology to ecology. Since there is currently no agreed-upon standard way to specify such models it is not always easy to use published models. Also, since model descriptions are not usually given in mathematical terms, it is difficult to bring mathematical analysis tools to bear, so that models are typically studied through simulation. In order to address this issue, Grimm et al. proposed a protocol for model specification, the so-called ODD protocol, which provides a standard way to describe models. This paper proposes an addition to the ODD protocol which allows the description of an agent-based model as a dynamical system, which provides access to computational and theoretical tools for its analysis. The mathematical framework is that of algebraic models, that is, time-discrete dynamical systems with algebraic structure. It is shown by way of several examples how this mathematical specification can help with model analysis.Comment: To appear in Bulletin of Mathematical Biolog

On the Computational Complexity of Measuring Global Stability of Banking Networks

Threats on the stability of a financial system may severely affect the functioning of the entire economy, and thus considerable emphasis is placed on the analyzing the cause and effect of such threats. The financial crisis in the current and past decade has shown that one important cause of instability in global markets is the so-called financial contagion, namely the spreading of instabilities or failures of individual components of the network to other, perhaps healthier, components. This leads to a natural question of whether the regulatory authorities could have predicted and perhaps mitigated the current economic crisis by effective computations of some stability measure of the banking networks. Motivated by such observations, we consider the problem of defining and evaluating stabilities of both homogeneous and heterogeneous banking networks against propagation of synchronous idiosyncratic shocks given to a subset of banks. We formalize the homogeneous banking network model of Nier et al. and its corresponding heterogeneous version, formalize the synchronous shock propagation procedures, define two appropriate stability measures and investigate the computational complexities of evaluating these measures for various network topologies and parameters of interest. Our results and proofs also shed some light on the properties of topologies and parameters of the network that may lead to higher or lower stabilities.Comment: to appear in Algorithmic

Sequential Data-Adaptive Bandwidth Selection by Cross-Validation for Nonparametric Prediction

We consider the problem of bandwidth selection by cross-validation from a sequential point of view in a nonparametric regression model. Having in mind that in applications one often aims at estimation, prediction and change detection simultaneously, we investigate that approach for sequential kernel smoothers in order to base these tasks on a single statistic. We provide uniform weak laws of large numbers and weak consistency results for the cross-validated bandwidth. Extensions to weakly dependent error terms are discussed as well. The errors may be {\alpha}-mixing or L2-near epoch dependent, which guarantees that the uniform convergence of the cross validation sum and the consistency of the cross-validated bandwidth hold true for a large class of time series. The method is illustrated by analyzing photovoltaic data.Comment: 26 page

Social stress-enhanced severity of Citrobacter rodentium-induced colitis is CCL2-dependent and attenuated by probiotic Lactobacillus reuteri

Psychological stressors are known to affect colonic diseases but the mechanisms by which this occurs, and whether probiotics can prevent stressor effects, are not understood. Because inflammatory monocytes that traffic into the colon can exacerbate colitis, we tested whether CCL2, a chemokine involved in monocyte recruitment, was necessary for stressor-induced exacerbation of infectious colitis. Mice were exposed to a social disruption stressor that entails repeated social defeat. During stressor exposure, mice were orally challenged with Citrobacter rodentium to induce a colonic inflammatory response. Exposure to the stressor during challenge resulted in significantly higher colonic pathogen levels, translocation to the spleen, increases in colonic macrophages, and increases in inflammatory cytokines and chemokines. The stressor-enhanced severity of C. rodentium-induced colitis was not evident in CCL2[superscript −/−] mice, indicating the effects of the stressor are CCL2-dependent. In addition, we tested whether probiotic intervention could attenuate stressor-enhanced infectious colitis by reducing monocyte/macrophage accumulation. Treating mice with probiotic Lactobacillus reuteri reduced CCL2 mRNA levels in the colon and attenuated stressor-enhanced infectious colitis. These data demonstrate that probiotic L. reuteri can prevent the exacerbating effects of stressor exposure on pathogen-induced colitis, and suggest that one mechanism by which this occurs is through downregulation of the chemokine CCL2.National Cancer Institute (U.S.) (Grants AT006552-01A1, P30-CA016058, and T32-DE014320

Sport psychology consulting in professional rugby union in the United Kingdom

This article describes my experiences of working within professional rugby union in South Wales, United Kingdom. Initially, I locate the context of professional rugby union in the country alongside how my various subcultural understandings of the sport were obtained. After outlining my consulting philosophy developed for working in a professional rugby union context, subsequent cultural challenges for practitioners working in the sport are then explored, together with example strategies used to account for such cultural considerations. I conclude by reflecting upon the importance of practitioners possessing and developing contextual intelligence and cultural competency to work effectively in high performance environments

Don't bleach chaotic data

A common first step in time series signal analysis involves digitally filtering the data to remove linear correlations. The residual data is spectrally white (it is ``bleached''), but in principle retains the nonlinear structure of the original time series. It is well known that simple linear autocorrelation can give rise to spurious results in algorithms for estimating nonlinear invariants, such as fractal dimension and Lyapunov exponents. In theory, bleached data avoids these pitfalls. But in practice, bleaching obscures the underlying deterministic structure of a low-dimensional chaotic process. This appears to be a property of the chaos itself, since nonchaotic data are not similarly affected. The adverse effects of bleaching are demonstrated in a series of numerical experiments on known chaotic data. Some theoretical aspects are also discussed.Comment: 12 dense pages (82K) of ordinary LaTeX; uses macro psfig.tex for inclusion of figures in text; figures are uufile'd into a single file of size 306K; the final dvips'd postscript file is about 1.3mb Replaced 9/30/93 to incorporate final changes in the proofs and to make the LaTeX more portable; the paper will appear in CHAOS 4 (Dec, 1993

Morphosyntactic processing in late second-language learners

The goal of the present study was to investigate the electro- physiological correlates of second-language (L2) morphosyn- tactic processing in highly proficient late learners of an L2 with long exposure to the L2 environment. ERPs were col- lected from 22 English–Spanish late learners while they read sentences in which morphosyntactic features of the L2 present or not present in the first language (number and gender agree- ment, respectively) were manipulated at two different sentence positions—within and across phrases. The results for a control group of age-matched native-speaker Spanish participants in- cluded an ERP pattern of LAN-type early negativity followed by P600 effect in response to both agreement violations and for both sentence positions. The late L2 learner results included a similar pattern, consisting of early negativity followed by P600, in the first sentence position (within-phrase agreement viola- tions) but only P600 effects in the second sentence position (across-phrase agreement violation), as well as significant am- plitude and onset latency differences between the gender and the number violation effects in both sentence positions. These results reveal that highly proficient learners can show electro- physiological correlates during L2 processing that are qualita- tively similar to those of native speakers, but the results also indicate the contribution of factors such as age of acquisition and transfer processes from first language to L

Singular Value Decomposition of Operators on Reproducing Kernel Hilbert Spaces

Reproducing kernel Hilbert spaces (RKHSs) play an important role in many statistics and machine learning applications ranging from support vector machines to Gaussian processes and kernel embeddings of distributions. Operators acting on such spaces are, for instance, required to embed conditional probability distributions in order to implement the kernel Bayes rule and build sequential data models. It was recently shown that transfer operators such as the Perron-Frobenius or Koopman operator can also be approximated in a similar fashion using covariance and cross-covariance operators and that eigenfunctions of these operators can be obtained by solving associated matrix eigenvalue problems. The goal of this paper is to provide a solid functional analytic foundation for the eigenvalue decomposition of RKHS operators and to extend the approach to the singular value decomposition. The results are illustrated with simple guiding examples