RESUMEN
To determine if photobiomodulation (PBM) has ergogenic effects on the anaerobic performance of well-trained cyclists. Fifteen healthy male road or mountain bike cyclists participated in this randomized, double-blinded, placebo-controlled, crossover study. Athletes were randomly assigned to receive photobiomodulation (630 nm, 4.6 J/cm2, 6 J per point, 16 points, PBM session) or placebo intervention (PLA session) in the first session. The athletes then performed a 30-s Wingate test to determine mean and peak average power, relative power, mean and peak velocity, mean and peak RPM, fatigue index, total distance, time to peak power, explosive strength, and power drop. After 48 h, athletes returned to the laboratory for the crossover intervention. The repeated-measures ANOVA test followed by Bonferroni post hoc test or Friedman test with Dunn's post hoc test (p < 0.05), and Cohen's d statistic were used for comparisons. Performance in the Wingate test was not significantly different (p > 0.05) between PBM and PLA sessions for any variable. Only a small effect size was detected for time to peak power (-0.40; 1.11 to 0.31) and explosive strength (0.38; -0.34 to 1.09). We conclude that irradiation with red light, under a low energy density, does not promote ergogenic effects on the anaerobic performance of cycling athletes.
Asunto(s)
Rendimiento Atlético , Sustancias para Mejorar el Rendimiento , Humanos , Masculino , Estudios Cruzados , Anaerobiosis , Método Doble Ciego , PoliésteresRESUMEN
Milk is an important dietary requirement for many populations due to its high nutritional value. However, increased demand has also made it prone to fraudulent activity. In this sense, scientists have sought to develop simple, low-cost, and portable techniques to achieve quality control of milk in industry and farms as well. This work proposes a new instrumentation system based on acoustic propagation and advanced signal processing techniques to identify milk adulteration by industrial contaminants. A pair of transmitter-receiver low-cost piezoelectric transducers, configured in a pitch-catch mode, propagated acoustic waves in the bovine milk samples contaminated with 0.5% of sodium bicarbonate, urea, and hydrogen peroxide. Signal processing approaches such as chromatic technique and statistical indexes like the correlation coefficient, Euclidian norm and cross-correlation square difference were applied to identify the contaminants. According to the presented results, CCSD and RMSD metrics presented more effectiveness to perform the identification of milk contaminants. However, CCSD was 2.28 × 105 more sensitivity to distinguish adulteration in relation to RMSD. For chromatic clustering technique, the major selectivity was observed between the contamination performed by sodium bicarbonate and urea. Therefore, results indicate that the proposed approach can be an effective and quick alternative to assess the milk condition and classify its contaminants.