Motor Performance as Risk Factor for Lower Extremity Injuries in Children

Purpose: Physical activity related injuries in children constitute a costly public health matter. The influence of motor performance on injury risk is unclear. The purpose was to examine if motor performance was a risk factor of traumatic and overuse lower extremity injuries in a normal population of children. Methods: This study included 1244 participants from 8 to 14-years-old at baseline, all participating in "the Childhood Health, Activity and Motor Performance School Study Denmark". The follow-up period was up to 15 months. The motor performance tests were static balance, single leg hop for distance, core stability tests, vertical jump, shuttle run, and a cardiorespiratory fitness test. Lower extremity injuries were registered by clinicians by weekly questionnaires and classified according to the ICD-10 system. Results: Poor balance increased risk for traumatic injury in the foot region (IRR=1.09-1.15), and good performance in single leg hop for distance protected against traumatic knee injuries (IRR=0.66-0.68). Good performance in core stability tests and vertical jump increased the risk for traumatic injuries in the foot region (IRR=1.12-1.16). Poor balance increased the risk for overuse injuries in the foot region (IRR=1.65), as did good performance in core stability tests and shuttle run, especially for knee injuries (IRR=1.07-1.18). Conclusions: Poor balance (sway) performance was a consistent predictor of traumatic injuries, in particular for traumatic ankle injuries. Good motor performance (core stability, vertical jump, shuttle run) was positively associated with traumatic and overuse injuries, and negatively (single leg hop) associated with traumatic injuries, indicating different influence on injury risk. Previous injury was a confounder affecting the effect size and the significance. More studies are needed to consolidate the findings, to clarify the influence of different performance tests on different types of injuries and to examine the influence of behaviour in relation to injury ris

Modelling diverse root density dynamics and deep nitrogen uptake — a simple approach

We present a 2-D model for simulation of root density and plant nitrogen (N) uptake for crops grown in agricultural systems, based on a modification of the root density equation originally proposed by Gerwitz and Page in J Appl Ecol 11:773–781, (1974). A root system form parameter was introduced to describe the distribution of root length vertically and horizontally in the soil profile. The form parameter can vary from 0 where root density is evenly distributed through the soil profile, to 8 where practically all roots are found near the surface. The root model has other components describing root features, such as specific root length and plant N uptake kinetics. The same approach is used to distribute root length horizontally, allowing simulation of root growth and plant N uptake in row crops. The rooting depth penetration rate and depth distribution of root density were found to be the most important parameters controlling crop N uptake from deeper soil layers. The validity of the root distribution model was tested with field data for white cabbage, red beet, and leek. The model was able to simulate very different root distributions, but it was not able to simulate increasing root density with depth as seen in the experimental results for white cabbage. The model was able to simulate N depletion in different soil layers in two field studies. One included vegetable crops with very different rooting depths and the other compared effects of spring wheat and winter wheat. In both experiments variation in spring soil N availability and depth distribution was varied by the use of cover crops. This shows the model sensitivity to the form parameter value and the ability of the model to reproduce N depletion in soil layers. This work shows that the relatively simple root model developed, driven by degree days and simulated crop growth, can be used to simulate crop soil N uptake and depletion appropriately in low N input crop production systems, with a requirement of few measured parameters

An Internet-Based Tool for Use in Assessing the Likely Effect of Intensification on Losses of Nitrogen to the Environment

The EU Nitrates, Habitat and National Emissions Ceilings directives and the Kyoto Agreement mean that agricultural losses of NO3, NH3 and N2O are under scrutiny by national and international environmental authorities. When farmers wish to intensify their operations, the authorities must then assess the likely environmental impact of the change in operation. The FARM-N internet tool was developed to help farmers and authorities agree how the farm will be structured and managed in the future, and to provide an objective assessment of the environmental losses that will result

Temperature and volatile organic compound concentrations as controlling factors for chemical composition of alpha-pinene-derived secondary organic aerosol

This work investigates the individual and combined effects of temperature and volatile organic compound precursor concentrations on the chemical composition of particles formed in the dark ozonolysis of alpha-pinene. All experiments were conducted in a 5m(3) Teflon chamber at an initial ozone concentration of 100 ppb and initial alpha-pinene concentrations of 10 and 50 ppb, respectively; at constant temperatures of 20, 0, or -15 degrees C; and at changing temperatures (ramps) from -15 to 20 and from 20 to -15 degrees C. The chemical composition of the particles was probed using a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). A four-factor solution of a positive matrix factorization (PMF) analysis of the combined HR-ToF-AMS data is presented. The PMF analysis and the elemental composition analysis of individual experiments show that secondary organic aerosol particles with the highest oxidation level are formed from the lowest initial alpha-pinene concentration (10 ppb) and at the highest temperature (20 degrees C). A higher initial alpha-pinene concentration (50 ppb) and/or lower temperature (0 or -15 degrees C) results in a lower oxidation level of the molecules contained in the particles. With respect to the carbon oxidation state, particles formed at 0 degrees C are more comparable to particles formed at 15 degrees C than to those formed at 20 degrees C. A remarkable observation is that changes in temperature during particle formation result in only minor changes in the elemental composition of the particles. Thus, the temperature at which aerosol particle formation is induced seems to be a critical parameter for the particle elemental composition. Comparison of the HR-ToF-AMS-derived estimates of the content of organic acids in the particles based on m/z 44 in the mass spectra show good agreement with results from off-line molecular analysis of particle filter samples collected from the same experiments. Higher temperatures are associated with a decrease in the absolute mass concentrations of organic acids (R-COOH) and organic acid functionalities (-COOH), while the organic acid functionalities account for an increasing fraction of the measured particle mass.Peer reviewe

Realization of efficient quantum gates with a superconducting qubit-qutrit circuit

Building a quantum computer is a daunting challenge since it requires good control but also good isolation from the environment to minimize decoherence. It is therefore important to realize quantum gates efficiently, using as few operations as possible, to reduce the amount of required control and operation time and thus improve the quantum state coherence. Here we propose a superconducting circuit for implementing a tunable system consisting of a qutrit coupled to two qubits. This system can efficiently accomplish various quantum information tasks, including generation of entanglement of the two qubits and conditional three-qubit quantum gates, such as the Toffoli and Fredkin gates. Furthermore, the system realizes a conditional geometric gate which may be used for holonomic (non-adiabatic) quantum computing. The efficiency, robustness and universality of the presented circuit makes it a promising candidate to serve as a building block for larger networks capable of performing involved quantum computational tasks.Comment: 27 pages including technical supplementary information, 9 figures, comments are most welcom

Scalable Group Level Probabilistic Sparse Factor Analysis

Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a group level scalable probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex noise models than the presently considered.Comment: 10 pages plus 5 pages appendix, Submitted to ICASSP 1