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Browsing ESECS - Artigos em revistas internacionais by Field of Science and Technology (FOS) "Ciências Médicas::Outras Ciências Médicas"
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- Are Young Swimmers Short and Middle Distances Energy Cost Sex-Specific?Publication . Massini, Danilo A.; Almeida, Tiago A. F.; Vasconcelos, Camila M. T.; Macedo, Anderson G.; Espada, Mário A. C.; Reis, Joana F.; Alves, Francisco J. B.; Fernandes, Ricardo J. P.; Filho, Dalton M. PessôaThis study assessed the energy cost in swimming (C) during short and middle distances to analyze the sex-specific responses of C during supramaximal velocity and whether body composition account to the expected differences. Twenty-six swimmers (13 men and 13 women: 16.7 ± 1.9 vs. 15.5 ± 2.8 years old and 70.8 ± 10.6 vs. 55.9 ± 7.0 kg of weight) performed maximal front crawl swimming trials in 50, 100, and 200 m. The oxygen uptake ((Formula presented.) O2) was analyzed along with the tests (and post-exercise) through a portable gas analyser connected to a respiratory snorkel. Blood samples were collected before and after exercise (at the 1st, 3rd, 5th, and 7th min) to determine blood lactate concentration [La–]. The lean mass of the trunk (LMTrunk), upper limb (LMUL), and lower limb (LMLL) was assessed using dual X-ray energy absorptiometry. Anaerobic energy demand was calculated from the phosphagen and glycolytic components, with the first corresponding to the fast component of the (Formula presented.) O2 bi-exponential recovery phase and the second from the 2.72 ml × kg–1 equivalent for each 1.0 mmol × L–1 [La–] variation above the baseline value. The aerobic demand was obtained from the integral value of the (Formula presented.) O2 vs. swimming time curve. The C was estimated by the rate between total energy releasing (in Joules) and swimming velocity. The sex effect on C for each swimming trial was verified by the two-way ANOVA (Bonferroni post hoc test) and the relationships between LMTrunk, LMUL, and LMLL to C were tested by Pearson coefficient. The C was higher for men than women in 50 (1.8 ± 0.3 vs. 1.3 ± 0.3 kJ × m–1), 100 (1.4 ± 0.1 vs. 1.0 ± 0.2 kJ × m–1), and 200 m (1.0 ± 0.2 vs. 0.8 ± 0.1 kJ × m–1) with p < 0.01 for all comparisons. In addition, C differed between distances for each sex (p < 0.01). The regional LMTrunk (26.5 ± 3.6 vs. 20.1 ± 2.6 kg), LMUL (6.8 ± 1.0 vs. 4.3 ± 0.8 kg), and LMLL (20.4 ± 2.6 vs. 13.6 ± 2.5 kg) for men vs. women were significantly correlated to C in 50 (R2adj = 0.73), 100 (R2adj = 0.61), and 200 m (R2adj = 0.60, p < 0.01). Therefore, the increase in C with distance is higher for men than women and is determined by the lean mass in trunk and upper and lower limbs independent of the differences in body composition between sexes.
- Estimation of an Elite Road Cyclist Performance in Different Positions Based on Numerical Simulations and Analytical ProceduresPublication . Forte, Pedro; Marinho, Daniel A.; Barbosa, Tiago M.; Morouço, Pedro; Morais, Jorge E.The aim of this study was to use numerical simulations and analytical procedures to compare a cyclist's performance in three different cycling positions. An elite level road cyclist competing at a national level was recruited for this research. The bicycle was 7 kg and the cyclist 55 kg. A 3D scan was taken of the subject on the competition bicycle, wearing race gear and helmet in the upright position, in the handlebar drops (dropped position) and leaning on the elbows (elbows position). Numerical simulations by computer fluid dynamics in Fluent CFD code assessed the coefficient of drag at 11.11 m/s. Following that, a set of assumptions were employed to assess cycling performance from 1 to 22 m/s. Drag values ranged between 0.16 and 99.51 N across the different speeds and positions. The cyclist mechanical power in the elbows position differed from the upright position between 0 and 23% and from the dropped position from 0 to 21%. The cyclist's energy cost in the upright position differed 2 to 16% in comparison to the elbows position and the elbows position had less 2 to 14% energy cost in comparison to the dropped position. The estimated time of arrival was computed for a 220,000 m distance and it varied between 7,715.03 s (2 h:8 min:24 s) and 220,000 s (61 h:6 min:40 s) across the different speeds and positions. In the elbows position, is expected that a cyclist may improve the winning time up to 23% in comparison to he upright and dropped position across the studied speeds.
- Quantification of Maximal Force Produced in Standard and Contra-Standard Sculling in Synchronized Swimming. A Pilot StudyPublication . Diogo, V.; Soares, S.; Tourino, C.; Carmo, C.; Aleixo, I.; Morouço, P.; Figueiredo, P.; Vilas-Boas, J. P.; Fernandes, R. J.Studies carried out in synchronized swimming are very scarce, namely those which include biomechanical analysis of the sculling technique. The purpose of this study was to measure the maximal force produced in standard and contra-standard sculling, using a 30s maximal tethered synchronized swimming test. One former female synchronized swimmer and one former female swimmer performed a 2x30s maximum intensity tethered synchronized swimming test, in standard and contra-standard sculling conditions, respectively. Parameters studied were maximal, mean and minimum force, the time when maximal and minimum force occurred, and fatigue index. Results showed that the higher values of maximal and mean force were found in standard sculling, both for the synchronized swimmer and the swimmer. The swimmer attained higher values of absolute and relative maximal force in the standard sculling, but lower values in the contra-standard technique, when compared to the synchronized swimmer. Fatigue Index results evidence that the maximal force declined during the 30s in both participants and in both sculling conditions. This parameter was higher for the contra-standard sculling performed by the swimmer, and for the standard sculling for the synchronized swimmer. In conclusion, there were differences in force production in standard and contra-standard sculling between a swimmer and a synchronized swimming. Those differences could probably be explained by differences in skill competence.
- Significant bivariate correlations: to be or not to be?Publication . Morouço, PedroJust like in many other fields of research, sport sciences use statistics to infer about the associations between variables. For example, aiming to examine the relationship between squat jump with sprint running velocity has brought several experiments, demonstrating a strong to very strong association between variables (e.g., Sleivert & Taingahue, 2004; Wisløff et al., 2004). From there on, there have been researchers proposing training programs for improving the squat jump, and consequently, the sprint running (e.g., Chelly et al., 2009). While this example seems unanimous, other emerging ideas may be questionable.