7,640 research outputs found

    No effect of arm exercise on diaphragmatic fatigue or ventilatory constraint in Paralympic athletes with cervical spinal cord injury

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    Cervical spinal cord injury (CSCI) results in a decrease in the capacity of the lungs and chest wall for pressure, volume, and airflow generation. We asked whether such impairments might increase the potential for exercise-induced diaphragmatic fatigue and mechanical ventilatory constraint in this population. Seven Paralympic wheelchair rugby players (mean ± SD peak oxygen uptake = 16.9 ± 4.9 ml·kg–1·min–1) with traumatic CSCI (C5–C7) performed arm-crank exercise to the limit of tolerance at 90% of their predetermined peak work rate. Diaphragm function was assessed before and 15 and 30 min after exercise by measuring the twitch transdiaphragmatic pressure (Pdi,tw) response to bilateral anterolateral magnetic stimulation of the phrenic nerves. Ventilatory constraint was assessed by measuring the tidal flow volume responses to exercise in relation to the maximal flow volume envelope. Pdi,tw was not different from baseline at any time after exercise (unpotentiated Pdi,tw = 19.3 ± 5.6 cmH2O at baseline, 19.8 ± 5.0 cmH2O at 15 min after exercise, and 19.4 ± 5.7 cmH2O at 30 min after exercise; P = 0.16). During exercise, there was a sudden, sustained rise in operating lung volumes and an eightfold increase in the work of breathing. However, only two subjects showed expiratory flow limitation, and there was substantial capacity to increase both flow and volume (<50% of maximal breathing reserve). In conclusion, highly trained athletes with CSCI do not develop exercise-induced diaphragmatic fatigue and rarely reach mechanical ventilatory constraint

    Action for the eleven dimensional multiple M-wave system

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    We present the covariant supersymmetric and kappa-symmetric action for a system of N nearly coincident M-waves (multiple M0-brane system) in flat eleven dimensional superspace.Comment: 4+ pages, RevTeX4, no figures. V2: misprints corrected, discussion extended, references added, LaTeX, 10 pages. V3: misprints corrected. V4, extended version, 1+13 pages, to appear in JHE

    Tracking Target Signal Strengths on a Grid using Sparsity

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    Multi-target tracking is mainly challenged by the nonlinearity present in the measurement equation, and the difficulty in fast and accurate data association. To overcome these challenges, the present paper introduces a grid-based model in which the state captures target signal strengths on a known spatial grid (TSSG). This model leads to \emph{linear} state and measurement equations, which bypass data association and can afford state estimation via sparsity-aware Kalman filtering (KF). Leveraging the grid-induced sparsity of the novel model, two types of sparsity-cognizant TSSG-KF trackers are developed: one effects sparsity through 1\ell_1-norm regularization, and the other invokes sparsity as an extra measurement. Iterative extended KF and Gauss-Newton algorithms are developed for reduced-complexity tracking, along with accurate error covariance updates for assessing performance of the resultant sparsity-aware state estimators. Based on TSSG state estimates, more informative target position and track estimates can be obtained in a follow-up step, ensuring that track association and position estimation errors do not propagate back into TSSG state estimates. The novel TSSG trackers do not require knowing the number of targets or their signal strengths, and exhibit considerably lower complexity than the benchmark hidden Markov model filter, especially for a large number of targets. Numerical simulations demonstrate that sparsity-cognizant trackers enjoy improved root mean-square error performance at reduced complexity when compared to their sparsity-agnostic counterparts.Comment: Submitted to IEEE Trans. on Signal Processin

    Pattern scaling using ClimGen: monthly-resolution future climate scenarios including changes in the variability of precipitation

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    Development, testing and example applications of the pattern-scaling approach for generating future climate change projections are reported here, with a focus on a particular software application called “ClimGen”. A number of innovations have been implemented, including using exponential and logistic functions of global-mean temperature to represent changes in local precipitation and cloud cover, and interpolation from climate model grids to a finer grid while taking into account land-sea contrasts in the climate change patterns. Of particular significance is a new approach for incorporating changes in the inter-annual variability of monthly precipitation simulated by climate models. This is achieved by diagnosing simulated changes in the shape of the gamma distribution of monthly precipitation totals, applying the pattern-scaling approach to estimate changes in the shape parameter under a future scenario, and then perturbing sequences of observed precipitation anomalies so that their distribution changes according to the projected change in the shape parameter. The approach cannot represent changes to the structure of climate timeseries (e.g. changed autocorrelation or teleconnection patterns) were they to occur, but is shown here to be more successful at representing changes in low precipitation extremes than previous pattern-scaling methods

    Field evidence for the upwind velocity shift at the crest of low dunes

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    Wind topographically forced by hills and sand dunes accelerates on the upwind (stoss) slopes and reduces on the downwind (lee) slopes. This secondary wind regime, however, possesses a subtle effect, reported here for the first time from field measurements of near-surface wind velocity over a low dune: the wind velocity close to the surface reaches its maximum upwind of the crest. Our field-measured data show that this upwind phase shift of velocity with respect to topography is found to be in quantitative agreement with the prediction of hydrodynamical linear analysis for turbulent flows with first order closures. This effect, together with sand transport spatial relaxation, is at the origin of the mechanisms of dune initiation, instability and growth.Comment: 13 pages, 6 figures. Version accepted for publication in Boundary-Layer Meteorolog

    Atypical disengagement from faces and its modulation by the control of eye fixation in children with Autism Spectrum Disorder

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    By using the gap overlap task, we investigated disengagement from faces and objects in children (9–17 years old) with and without autism spectrum disorder (ASD) and its neurophysiological correlates. In typically developing (TD) children, faces elicited larger gap effect, an index of attentional engagement, and larger saccade-related event-related potentials (ERPs), compared to objects. In children with ASD, by contrast, neither gap effect nor ERPs differ between faces and objects. Follow-up experiments demonstrated that instructed fixation on the eyes induces larger gap effect for faces in children with ASD, whereas instructed fixation on the mouth can disrupt larger gap effect in TD children. These results suggest a critical role of eye fixation on attentional engagement to faces in both groups

    Methodological criteria for the assessment of moderators in systematic reviews of randomised controlled trials : a consensus study

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    Background: Current methodological guidelines provide advice about the assessment of sub-group analysis within RCTs, but do not specify explicit criteria for assessment. Our objective was to provide researchers with a set of criteria that will facilitate the grading of evidence for moderators, in systematic reviews. Method: We developed a set of criteria from methodological manuscripts (n = 18) using snowballing technique, and electronic database searches. Criteria were reviewed by an international Delphi panel (n = 21), comprising authors who have published methodological papers in this area, and researchers who have been active in the study of sub-group analysis in RCTs. We used the Research ANd Development/University of California Los Angeles appropriateness method to assess consensus on the quantitative data. Free responses were coded for consensus and disagreement. In a subsequent round additional criteria were extracted from the Cochrane Reviewers’ Handbook, and the process was repeated. Results: The recommendations are that meta-analysts report both confirmatory and exploratory findings for subgroups analysis. Confirmatory findings must only come from studies in which a specific theory/evidence based apriori statement is made. Exploratory findings may be used to inform future/subsequent trials. However, for inclusion in the meta-analysis of moderators, the following additional criteria should be applied to each study: Baseline factors should be measured prior to randomisation, measurement of baseline factors should be of adequate reliability and validity, and a specific test of the interaction between baseline factors and interventions must be presented. Conclusions: There is consensus from a group of 21 international experts that methodological criteria to assess moderators within systematic reviews of RCTs is both timely and necessary. The consensus from the experts resulted in five criteria divided into two groups when synthesising evidence: confirmatory findings to support hypotheses about moderators and exploratory findings to inform future research. These recommendations are discussed in reference to previous recommendations for evaluating and reporting moderator studies

    A global assessment of the impact of climate change on water scarcity

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    This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2°C, followed by stabilisation to 4°C
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