The purpose of this study was to investigate the chronic effect of a contrast training program designed to elicit an acute short term enhancement (STE) effect during training. A matched pairs training study design was implemented with a contrast (STE affected) and complex (control) training group completing a seven week training intervention. Twenty subjects participated. The contrast training group completed training based on a preloading protocol that had previously been shown to induce an acute STE effect within the subject population. The control group completed the same volume and type of training in a complex training format. Changes in squat 4RM strength and kinetic and kinematic performance in vertical and horizontal countermovement jump (CMJ) and drop jump (DJ) were measured via a Force Plate. Differences between the experimental and control group in change of mean strength (effect size 0.03 ± 0.33), vertical DJ (effect size: contact time -0.22 ± 0.52; peak force 0.20 ± 0.30; mean force 0.30 ± 0.74) and horizontal DJ (effect size: contact time -0.47 ± 0.73; peak force 0.03 ± 0.36; mean force 0.13 ± 0.56) were not meaningful. However, differences in mean change of vertical and horizontal CMJ measures of force (effect size range 0.40 - 0.46 ± 0.37 - 0.63), vertical CMJ peak velocity (effect size 0.84 ±0.66) and mean velocity (0.62 ± 0.88) were meaningful. These findings demonstrate that eliciting an acute STE response in dynamic training movements through contrast training can produce a chronic improvement in dynamic movements as a training effect.
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http://dx.doi.org/10.1519/JSC.0000000000000874 | DOI Listing |
Phys Rev Lett
December 2024
Xi'an Jiaotong University, School of Microelectronics & State Key Laboratory for Mechanical Behavior of Materials, Xi'an 710049, China.
The bismuth monolayer has recently been experimentally identified as a novel platform for the investigation of two-dimensional single-element ferroelectric system. Here, we model the potential energy surface of a bismuth monolayer by employing a message-passing neural network and achieve an error smaller than 1.2 meV per atom.
View Article and Find Full Text PDFJAMA
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