Questioning policy, youth participation and lifestyle sports

Young people have been identified as a key target group for whom participation in sport and physical activity could have important benefits to health and wellbeing and consequently have been the focus of several government policies to increase participation in the UK. Lifestyle sports represent one such strategy for encouraging and sustaining new engagements in sport and physical activity in youth groups, however, there is at present a lack of understanding of the use of these activities within policy contexts. This paper presents findings from a government initiative which sought to increase participation in sport for young people through provision of facilities for mountain biking in a forest in south-east England. Findings from qualitative research with 40 young people who participated in mountain biking at the case study location highlight the importance of non-traditional sports as a means to experience the natural environments through forms of consumption which are healthy, active and appeal to their identities. In addition, however, the paper raises questions over the accessibility of schemes for some individuals and social groups, and the ability to incorporate sports which are inherently participant-led into state-managed schemes. Lifestyle sports such as mountain biking involve distinct forms of participation which present a challenge for policy-makers who seek to create and maintain sustainable communities of youth participants

First evidence of coherent K+K^{+} meson production in neutrino-nucleus scattering

Neutrino-induced charged-current coherent kaon production, $\nu_{\mu}A\rightarrow\mu^{-}K^{+}A$, is a rare, inelastic electroweak process that brings a $K^+$ on shell and leaves the target nucleus intact in its ground state. This process is significantly lower in rate than neutrino-induced charged-current coherent pion production, because of Cabibbo suppression and a kinematic suppression due to the larger kaon mass. We search for such events in the scintillator tracker of MINERvA by observing the final state $K^+$, $\mu^-$ and no other detector activity, and by using the kinematics of the final state particles to reconstruct the small momentum transfer to the nucleus, which is a model-independent characteristic of coherent scattering. We find the first experimental evidence for the process at $3\sigma$ significance.Comment: added ancillary file with information about the six kaon candidate

Direct Measurement of Nuclear Dependence of Charged Current Quasielastic-like Neutrino Interactions using MINERvA

Charged-current $\nu_{\mu}$ interactions on carbon, iron, and lead with a final state hadronic system of one or more protons with zero mesons are used to investigate the influence of the nuclear environment on quasielastic-like interactions. The transfered four-momentum squared to the target nucleus, $Q^2$, is reconstructed based on the kinematics of the leading proton, and differential cross sections versus $Q^2$ and the cross-section ratios of iron, lead and carbon to scintillator are measured for the first time in a single experiment. The measurements show a dependence on atomic number. While the quasielastic-like scattering on carbon is compatible with predictions, the trends exhibited by scattering on iron and lead favor a prediction with intranuclear rescattering of hadrons accounted for by a conventional particle cascade treatment. These measurements help discriminate between different models of both initial state nucleons and final state interactions used in the neutrino oscillation experiments

Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINERvA experiment

We present a simulation-based study using deep convolutional neural networks (DCNNs) to identify neutrino interaction vertices in the MINERvA passive targets region, and illustrate the application of domain adversarial neural networks (DANNs) in this context. DANNs are designed to be trained in one domain (simulated data) but tested in a second domain (physics data) and utilize unlabeled data from the second domain so that during training only features which are unable to discriminate between the domains are promoted. MINERvA is a neutrino-nucleus scattering experiment using the NuMI beamline at Fermilab. $A$-dependent cross sections are an important part of the physics program, and these measurements require vertex finding in complicated events. To illustrate the impact of the DANN we used a modified set of simulation in place of physics data during the training of the DANN and then used the label of the modified simulation during the evaluation of the DANN. We find that deep learning based methods offer significant advantages over our prior track-based reconstruction for the task of vertex finding, and that DANNs are able to improve the performance of deep networks by leveraging available unlabeled data and by mitigating network performance degradation rooted in biases in the physics models used for training.Comment: 41 page

Single neutral pion production by charged-current νˉμ\bar{\nu}_\mu interactions on hydrocarbon at ⟨Eν⟩=\langle E_\nu \rangle = 3.6 GeV

Single neutral pion production via muon antineutrino charged-current interactions in plastic scintillator (CH) is studied using the \minerva detector exposed to the NuMI low-energy, wideband antineutrino beam at Fermilab. Measurement of this process constrains models of neutral pion production in nuclei, which is important because the neutral-current analog is a background for $\bar{\nu}_e$ appearance oscillation experiments. The differential cross sections for $\pi^0$ momentum and production angle, for events with a single observed $\pi^0$ and no charged pions, are presented and compared to model predictions. These results comprise the first measurement of the $\pi^0$ kinematics for this process.Comment: 6 pages, 5 figures, submitted to Physics Letters