The polymicrobial nature of biofilm infection

The model of biofilm infection was first proposed over a decade ago. Recent scientific advances have added much to our understanding of biofilms, usually polymicrobial communities, which are commonly associated with chronic infection. Metagenomics has demonstrated that bacteria pursuing a biofilm strategy possess many mechanisms for encouraging diversity. By including multiple bacterial and/or fungal species in a single community, biofilms obtain numerous advantages, such as passive resistance, metabolic cooperation, byproduct influence, quorum sensing systems, an enlarged gene pool with more efficient DNA sharing, and many other synergies, which give them a competitive advantage. Routine clinical cultures are ill-suited for evaluating polymicrobial infections. DNA methods utilizing PCR methods, PCR/mass spectroscopy and sequencing have demonstrated their ability to identify microorganisms and quantitate their contribution to biofilms in clinical infections. A more robust model of biofilm infection along with more accurate diagnosis is rapidly translating into improved clinical outcomes

Walking the walk: a phenomenological study of long distance walking

Evidence suggests that regular walking can elicit significant psychological benefits although little evidence exists concerning long distance walking. The purpose of this study was to provide detailed accounts of the experiences of long distance walkers. Phenomenological interviews were conducted with six long distance walkers. Data were transcribed verbatim before researchers independently analyzed the transcripts. Participants reported a cumulative effect with positive feelings increasing throughout the duration of the walk. Long distance walking elicited positive emotions, reduced the effects of life-stress, and promoted an increased sense of well-being and personal growth. Results are aligned to theories and concepts from positive psychology

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

The MINERν\nuA Data Acquisition System and Infrastructure

MINER$\nu$A (Main INjector ExpeRiment $\nu$-A) is a new few-GeV neutrino cross section experiment that began taking data in the FNAL NuMI (Fermi National Accelerator Laboratory Neutrinos at the Main Injector) beam-line in March of 2010. MINER$\nu$A employs a fine-grained scintillator detector capable of complete kinematic characterization of neutrino interactions. This paper describes the MINER$\nu$A data acquisition system (DAQ) including the read-out electronics, software, and computing architecture.Comment: 34 pages, 16 figure

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

Evaluating the Dimensionality of First-Grade Written Composition

Purpose—We examined dimensions of written composition using multiple evaluative approaches such as an adapted 6+1 trait scoring, syntactic complexity measures, and productivity measures. We further examined unique relations of oral language and literacy skills to the identified dimensions of written composition. Method—A large sample of first grade students (N = 527) was assessed on their language, reading, spelling, letter writing automaticity, and writing in the spring. Data were analyzed using a latent variable approach including confirmatory factor analysis and structural equation modeling. Results—The seven traits in the 6+1 trait system were best described as two constructs: substantive quality, and spelling and writing conventions. When the other evaluation procedures such as productivity and syntactic complexity indicators were included, four dimensions emerged: substantive quality, productivity, syntactic complexity, and spelling and writing conventions. Language and literacy predictors were differentially related to each dimension in written composition. Conclusions—These four dimensions may be a useful guideline for evaluating developing beginning writer’s compositions

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

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

MINERvA neutrino detector response measured with test beam data

The MINERvA collaboration operated a scaled-down replica of the solid scintillator tracking and sampling calorimeter regions of the MINERvA detector in a hadron test beam at the Fermilab Test Beam Facility. This article reports measurements with samples of protons, pions, and electrons from 0.35 to 2.0 GeV/c momentum. The calorimetric response to protons, pions, and electrons are obtained from these data. A measurement of the parameter in Birks' law and an estimate of the tracking efficiency are extracted from the proton sample. Overall the data are well described by a Geant4-based Monte Carlo simulation of the detector and particle interactions with agreements better than 4%, though some features of the data are not precisely modeled. These measurements are used to tune the MINERvA detector simulation and evaluate systematic uncertainties in support of the MINERvA neutrino cross section measurement program.Comment: as accepted by NIM