Muscle atrophy, pain, and damage in bed rest reduced by resistive (vibration) exercise

The purpose of this study was to investigate the effectiveness of a short-duration (5-6 min, 3 d·wk) resistive exercise program with (RVE) or without (RE) whole-body vibration in reducing muscle atrophy in the lower limb during prolonged inactivity when compared with that in an inactive control group. METHODS: As part of the second Berlin BedRest Study, 24 male subjects underwent 60 d of head-down tilt bed rest. Using magnetic resonance imaging, muscle volumes of the individual muscles of the lower limb were calculated before and at various intervals during and after bed rest. Pain levels and markers of muscle damage were also evaluated during and after bed rest. Adjustment of P values to guard against false positives was performed via the false discovery rate method. RESULTS: On the "intent-to-treat" analysis, RE reduced atrophy of the medial and lateral gastrocnemius, soleus, vasti, tibialis posterior, flexor hallucis longus, and flexor digitorum longus (P ≤ 0.045 vs control group) and RVE reduced atrophy of the medial and lateral gastrocnemius and tibialis posterior (P ≤ 0.044). Pain intensity reports after bed rest were lower in RE at the foot (P ≤ 0.033) and whole lower limb (P = 0.01) and in RVE at the thigh (P ≤ 0.041), lower leg (P ≤ 0.01), and whole lower limb (P ≤ 0.036). Increases in sarcomere-specific creatine kinase after bed rest were less in RE (P = 0.020) and RVE (P = 0.020). No differences between RE and RVE were observed. CONCLUSIONS: In conclusion, a short-duration RVE or RE can be effective in reducing the effect of prolonged bed rest on lower extremity muscle volume loss during bed rest and muscle damage and pain after bed rest. Copyright © 2014 by the American College of Sports Medicine.

Reliability and variability of day-to-day vault training measures in artistic gymnastics

Inter-day training reliability and variability in artistic gymnastics vaulting was determined using a customised infra-red timing gate and contact mat timing system. Thirteen Australian high performance gymnasts (eight males and five females) aged 11-23 years were assessed during two consecutive days of normal training. Each gymnast completed a number of vault repetitions per daily session. Inter-day variability of vault run-up velocities (at -18 to -12 m, -12 to -6 m, -6 to -2 m, and -2 to 0 m from the nearest edge of the beat board), and board contact, pre-flight, and table contact times were determined using mixed modelling statistics to account for random (within-subject variability) and fixed effects (gender, number of subjects, number of trials). The difference in the mean (Mdiff) and Cohen's effect sizes for reliability assessment and intra-class correlation coefficients, and the coefficient of variation percentage (CV%) were calculated for variability assessment. Approach velocity (-18 to -2 m, CV = 2.4-7.8%) and board contact time (CV = 3.5%) were less variable measures when accounting for day-to-day performance differences, than pre-flight time (CV = 17.7%) and table contact time (CV = 20.5%). While pre-flight and table contact times are relevant training measures, approach velocity and board contact time are more reliable when quantifying vaulting performance.

Neural network training by hybrid accelerated cuckoo particle swarm optimization algorithm

Metaheuristic algorithm is one of the most popular methods in solving many optimization problems. This paper presents a new hybrid approach comprising of two natures inspired metaheuristic algorithms i.e. Cuckoo Search (CS) and Accelerated Particle Swarm Optimization (APSO) for training Artificial Neural Networks (ANN). In order to increase the probability of the egg’s survival, the cuckoo bird migrates by traversing more search space. It can successfully search better solutions by performing levy flight with APSO. In the proposed Hybrid Accelerated Cuckoo Particle Swarm Optimization (HACPSO) algorithm, the communication ability for the cuckoo birds have been provided by APSO, thus making cuckoo bird capable of searching for the best nest with better solution. Experimental results are carried-out on benchmarked datasets, and the performance of the proposed hybrid algorithm is compared with Artificial Bee Colony (ABC) and similar hybrid variants. The results show that the proposed HACPSO algorithm performs better than other algorithms in terms of convergence and accuracy.