Soccer seasonal variations in sprint mechanical properties and vertical jump performance

The aim of this study was to quantify possible differences in countermovement jump (CMJ) height, sprint performance and underlying mechanical properties as a function of time during a soccer season. Fortyfour male professional soccer players were identified in the Norwegian Olympic Federation’s test database. Each of these players had performed 40-m sprint and CMJ tests at least once within pre-season, in-season and off-season over the course of one year. The players sprinted, possibly to most likely, faster over 40 m during off-season compared to in-season (mean difference, ±90%CL: 0.04, ±0.03 s; small) and pre-season (0.08, ±0.02 s; small). Maximal horizontal power production was likely to most likely greater off-season compared to in-season (mean difference, ±90%CL: 0.5, ±0.4 W∙kg-1; small) and pre-season (0.8, ±0.4 W∙kg-1; small). Maximal horizontal force production was likely greater off-season compared to in-season (0.2, ±0.2 N∙kg-1; small). Theoretical maximal velocity obtained during pre-season was, possibly to very likely, lower compared to in-season (0.09, ±0.12 m∙s-1; small) and off-season (0.14, ±0.09 m∙s-1; small). The force-velocity slope values relative to body mass were, possibly to likely, higher off-season compared to in-season (0.02, ±0.03; small) and pre-season (0.01, ±0.02; small). CMJ results obtained off-season were, likely better, than those for pre-season (1.2, ±0.6 cm; small). The present study shows that anaerobic fitness variables, believed to be relevant for the on-field soccer performance, are sensitive to the varying season times

Eulerian and modified Lagrangian approaches to multi-dimensional condensation and collection

Turbulence is argued to play a crucial role in cloud droplet growth. The combined problem of turbulence and cloud droplet growth is numerically challenging. Here, an Eulerian scheme based on the Smoluchowski equation is compared with two Lagrangian superparticle (or su- perdroplet) schemes in the presence of condensation and collection. The growth processes are studied either separately or in combination using either two-dimensional turbulence, a steady flow, or just gravitational acceleration without gas flow. Good agreement between the differ- ent schemes for the time evolution of the size spectra is observed in the presence of gravity or turbulence. Higher moments of the size spectra are found to be a useful tool to characterize the growth of the largest drops through collection. Remarkably, the tails of the size spectra are reasonably well described by a gamma distribution in cases with gravity or turbulence. The Lagrangian schemes are generally found to be superior over the Eulerian one in terms of computational performance. However, it is shown that the use of interpolation schemes such as the cloud-in-cell algorithm is detrimental in connection with superparticle or superdroplet approaches. Furthermore, the use of symmetric over asymmetric collection schemes is shown to reduce the amount of scatter in the results.Comment: 36 pages, 17 figure

Magmatic Evolution of Early Subduction Zones: Geochemical Modeling and Chemical Stratigraphy of Boninite and Fore Arc Basalt from the Bonin Fore Arc

The Izu-Bonin-Mariana arc stretches south from Japan to Guam in the Western Pacific. International Ocean Discovery Project Expedition 352 drilled four core in the fore arc of the Izu-Bonin arc east of the Bonin Islands: U1439C, U1440B, U1441A, and U1442A. From the four core, 124 samples were retrieved and analyzed for major and trace elements. Two main rock types were identified: FAB and boninite. FAB is a Mid-Ocean Ridge Basalt (MORB)-like tholeiite with variable fluid mobile element enrichment such as Rb, Ba, and Sr, and low Ti/V ratios more similar to an island arc volcanic than a mid-ocean ridge volcanic. Boninite is a hydrous high-Mg andesite with low TiO2 and distinctive subduction zone characteristics in the form of elevated fluid mobile elements and melt mobile elements. FAB was assumed to be formed from a Depleted MORB-Mantle (DMM) source and the boninite was formed from a depleted mantle source, presumably the mantle after FAB melt was extracted. Here, we used the Rare Earth Elements (REE) of the samples to model melt scenarios for the FAB and boninite in order to better understand the initial volcanic product of subduction zones. This research was funded by in joint by the National Science Foundation, Consortium for Ocean Leadership, and International Ocean Discovery Program. 124 samples were analyzed using an X-Ray Fluorescence (XRF) and Inductively Coupled Plasma - Mass Spectrometer (ICP-MS) to determine the major and trace elements. These analyses were then used to recreate the chemostratigraphy defined by the shipboard crew and determine variations within the core. We found that there was variability as the magma evolved over time and mixed with other melts, seen in magma mixing horizons. Boninite samples were separated based on their SiO2 and MgO concentrations into Basaltic Boninite (BB), Low-Silica Boninite (LSB), and High-Silica Boninite (HSB) with BB being more primitive and HSB being more evolved. These volcanics are the first known products of the subduction zone and were used to model the early evolution of the subduction zone. FAB was the first product due to its proximity to the trench and greater age than the boninite. Assumed to be generated from DMM, FAB was modeled with a total melt extraction of ~20% spinel lherzolite and 1% garnet lherzolite. Boninite was assumed to be generated from the FAB residue because it requires a depleted source and because the FAB residue was within the hydrous flux melt zone of the subduction factory. Boninite was modeled at high degree of melt from the FAB residue, however an additional melt must be added to the model to match the observed samples. We proposed a small fraction of FAB melt mixed with the models because it is still present in the subduction factory, observed in core U1439C with a FAB sample in the HSB regime

Soccer seasonal variations in sprint mechanical properties and vertical jump performance

The aim of this study was to quantify possible differences in countermovement jump (CMJ) height, sprint performance and underlying mechanical properties as a function of time during a soccer season. Fortyfour male professional soccer players were identified in the Norwegian Olympic Federation’s test database. Each of these players had performed 40-m sprint and CMJ tests at least once within pre-season, in-season and off-season over the course of one year. The players sprinted, possibly to most likely, faster over 40 m during off-season compared to in-season (mean difference, ±90%CL: 0.04, ±0.03 s; small) and pre-season (0.08, ±0.02 s; small). Maximal horizontal power production was likely to most likely greater off-season compared to in-season (mean difference, ±90%CL: 0.5, ±0.4 W∙kg-1; small) and pre-season (0.8, ±0.4 W∙kg-1; small). Maximal horizontal force production was likely greater off-season compared to in-season (0.2, ±0.2 N∙kg-1; small). Theoretical maximal velocity obtained during pre-season was, possibly to very likely, lower compared to in-season (0.09, ±0.12 m∙s-1; small) and off-season (0.14, ±0.09 m∙s-1; small). The force-velocity slope values relative to body mass were, possibly to likely, higher off-season compared to in-season (0.02, ±0.03; small) and pre-season (0.01, ±0.02; small). CMJ results obtained off-season were, likely better, than those for pre-season (1.2, ±0.6 cm; small). The present study shows that anaerobic fitness variables, believed to be relevant for the on-field soccer performance, are sensitive to the varying season times

Evolving turbulence and magnetic fields in galaxy clusters

We discuss, using simple analytical models and MHD simulations, the origin and parameters of turbulence and magnetic fields in galaxy clusters. Three physically distinct regimes can be identified in the evolution of cluster turbulence and magnetic fields. Firstly, the fluctuation dynamo will produce microgauss-strong, random magnetic fields during cluster formation and major mergers. Turbulent velocity of about 300 km/s can be maintained at scales 100-200 kpc. The magnetic field is intermittent, has a smaller scale of 20-30 kpc and average strength of 2 microgauss. Secondly, when major mergers end, turbulent speed and magnetic field undergo a power-law decay, decreasing in strength but increasing in scale by a factor of about two. Thirdly, smaller-mass subclusters and cluster galaxies produce turbulent wakes, with turbulent speeds and magnetic field strengths similar to those quoted above. The velocity scales are about 200 kpc and 10 kpc respectively, and the magnetic field scale is about 6 times smaller. Although these wakes may fill only a small fraction of the cluster volume, their area covering factor can be close to unity. So one can potentially reconcile observations that indicate the coexistence of turbulence with ordered filamentary gas structures, as in the Perseus cluster. Random Faraday rotation measure is estimated to be typically 100-200 rad/m^2, in agreement with observations. We predict detectable synchrotron polarization from cluster radio halos at wavelengths 3-6 cm, if observed at sufficiently high resolution (abridged).Comment: 20 pages, 9 figures, Replaced to match version accepted by MNRA

Is nonhelical hydromagnetic turbulence peaked at small scales?

Nonhelical hydromagnetic turbulence without an imposed magnetic field is considered in the case where the magnetic Prandtl number is unity. The magnetic field is entirely due to dynamo action. The magnetic energy spectrum peaks at a wavenumber of about 5 times the minimum wavenumber in the domain, and not at the resistive scale, as has previously been argued. Throughout the inertial range the spectral magnetic energy exceeds the kinetic energy by a factor of about 2.5, and both spectra are approximately parallel. At first glance, the total energy spectrum seems to be close to k^{-3/2}, but there is a strong bottleneck effect and it is suggested that the asymptotic spectrum is k^{-5/3}. This is supported by the value of the second order structure function exponent that is found to be \zeta_2=0.70, suggesting a k^{-1.70} spectrum.Comment: 6 pages, 6 figure

Effect of turbulence on collisional growth of cloud droplets

We investigate the effect of turbulence on the collisional growth of um-sized droplets through high- resolution numerical simulations with well resolved Kolmogorov scales, assuming a collision and coalescence efficiency of unity. The droplet dynamics and collisions are approximated using a superparticle approach. In the absence of gravity, we show that the time evolution of the shape of the droplet-size distribution due to turbulence-induced collisions depends strongly on the turbulent energy-dissipation rate, but only weakly on the Reynolds number. This can be explained through the energy dissipation rate dependence of the mean collision rate described by the Saffman-Turner collision model. Consistent with the Saffman-Turner collision model and its extensions, the collision rate increases as the square root of the energy dissipation rate even when coalescence is invoked. The size distribution exhibits power law behavior with a slope of -3.7 between a maximum at approximately 10 um up to about 40 um. When gravity is invoked, turbulence is found to dominate the time evolution of an initially monodisperse droplet distribution at early times. At later times, however, gravity takes over and dominates the collisional growth. We find that the formation of large droplets is very sensitive to the turbulent energy dissipation rate. This is due to the fact that turbulence enhances the collisional growth between similar sized droplets at the early stage of raindrop formation. The mean collision rate grows exponentially, which is consistent with the theoretical prediction of the continuous collisional growth even when turbulence-generated collisions are invoked. This consistency only reflects the mean effect of turbulence on collisional growth