Relative Contribution among Physical Fitness Factors Contributing to the Performance of Modern Pentathlon.

This study reveals the relationship between physical fitness factors and performance in modern pentathlon and identifies the contribution of each physical factor to overall performance. The physical fitness assessment data and the competition records collected by the Korean national team pentathletes for the years 2005 to 2019 were tracked. The correlation between the competition records and fitness factors was confirmed by correlation analysis. In addition, the physical factors affecting performance were identified through multiple regression analysis, and the average difference between national and international competitions was verified by t-test. The first result was that fencing, swimming, and horseback riding rankings were more relevant to the overall pentathlon performance score than the combined rankings in national competitions. In the international competitions, performance in the combined running and shooting event was more relevant than fencing, swimming, and horseback riding. Second, the basic fitness factors of grip strength and sergeant jump and the specific fitness factors of leg strength-left and right average flexor were correlated with overall pentathlon performance national competitions. However, in international competitions, sergeant jump, 20 m shuttle run, reaction time, lung capacity, and back strength were correlated (presented in high to low order). In terms of the specific fitness factors, relative (%BW) and absolute (Nm) leg strength-left and right average flexor, lower body anaerobic fatigue rate, half squat, relative (W/kg) and absolute (Watts) maximal lower body anaerobic power were correlated accordingly with overall pentathlon performance. Third, we analyzed the differences between average performance in national and international competitions. Only the combined running and shooting event out of the five modern pentathlon events showed a difference. Grip strength and relative leg strength-average extensor AP (%BW) appeared to be different among the physical fitness factors. Fourth, we examined the level of contribution of each of the fitness factors on overall performance. The model's goodness of fit was confirmed, and grip strength was found to have a significant contribution on overall performance. Furthermore, the level of contribution was higher in the following order: relative leg strength-left and right average flexor (%BW), bench press, half squat, relative leg strength-average extensor AP(%BW), GXT-time to exhaustion, relative lower body anaerobic average power (W/kg), and maximal lactic acid concentration. With the 2020 Tokyo Olympics just around the corner, combined running and shooting performance appeared to be a decisive factor in the final ranking in modern pentathlon according to the analysis of the basic and specific fitness factors of pentathletes. The basic fitness factors are critical in order of sergeant jump, grip strength, reaction time, lung capacity, side-step, back strength, 20m shuttle run, sit-and-reach, sit-ups, and single leg standing. With respect to the specific fitness factors, relative leg strength-left and right average flexor (%BW), bench press, half squat, relative leg strength-average extensor AP (%BW), GXT-time to exhaustion, relative lower body anaerobic average power (W/kg), and maximal lactic acid concentration showed their relevance accordingly.

Victory Prediction of Ladies Professional Golf Association Players: Influential Factors and Comparison of Prediction Models.

This study aims to identify the most accurate prediction model for the possibility of victory from the annual average data of 25 seasons (1993-2017) of the Ladies Professional Golf Association (LPGA), and to determine the importance of the predicting factors. The four prediction models considered in this study were a decision tree, discriminant analysis, logistic regression, and artificial neural network analysis. The mean difference in the classification accuracy of these models was analyzed using SPSS 22.0 software (IBM Corp., Armonk, NY, USA) and the one-way analysis of variance (ANOVA). When the prediction was based on technical variables, the most important predicting variables for determining victory were greens in regulation (GIR) and putting average (PA) in all four prediction models. When the prediction was based on the output of the technical variables, the most important predicting variable for determining victory was birdies in all four prediction models. When the prediction was based on the season outcome, the most important predicting variables for determining victory were the top 10 finish% (T10) and official money. A significant mean difference in classification accuracy was observed while performing the one-way ANOVA, and the least significant difference post-hoc test showed that artificial neural network analysis exhibited higher accuracy than the other models, especially, for larger data sizes. From the results of this study, it can be inferred that the player who wants to win the LPGA should aim to increase GIR, reduce PA, and improve driving distance and accuracy through training to increase the birdies chance at each hole, which can lead to lower average strokes and increased possibility of being within T10.

Ranking Prediction Model Using the Competition Record of Ladies Professional Golf Association Players.

Chae, JS, Park, J, and So, W-Y. Ranking prediction model using the competition record of ladies professional golf association players. J Strength Cond Res 32(8): 2363-2374, 2018-The purpose of this study was to suggest a ranking prediction model using the competition record of the Ladies Professional Golf Association (LPGA) players. The top 100 players on the tour money list from the 2013-2016 US Open were analyzed in this model. Stepwise regression analysis was conducted to examine the effect of performance and independent variables (i.e., driving accuracy, green in regulation, putts per round, driving distance, percentage of sand saves, par-3 average, par-4 average, par-5 average, birdies average, and eagle average) on dependent variables (i.e., scoring average, official money, top-10 finishes, winning percentage, and 60-strokes average). The following prediction model was suggested:(Equation is included in full-text article.)(Equation is included in full-text article.)(Equation is included in full-text article.)(Equation is included in full-text article.)(Equation is included in full-text article.)Scoring of the above 5 prediction models and the prediction of golf ranking in the 2016 Women's Golf Olympic competition in Rio revealed a significant correlation between the predicted and real ranking (r = 0.689, p < 0.001) and between the predicted and the real average score (r = 0.653, p < 0.001). Our ranking prediction model using LPGA data may help coaches and players to identify which players are likely to participate in Olympic and World competitions, based on their performance.

Compact soft x-ray transmission microscopy with sub-50 nm spatial resolution.

In this paper, the development of compact transmission soft x-ray microscopy (XM) with sub-50 nm spatial resolution for biomedical applications is described. The compact transmission soft x-ray microscope operates at lambda = 2.88 nm (430 eV) and is based on a tabletop regenerative x-ray source in combination with a tandem ellipsoidal condenser mirror for sample illumination, an objective micro zone plate and a thinned back-illuminated charge coupled device to record an x-ray image. The new, compact x-ray microscope system requires the fabrication of proper x-ray optical devices in order to obtain high-quality images. For an application-oriented microscope, the alignment procedure is fully automated via computer control through a graphic user interface. In imaging studies using our compact XM system, a gold mesh image was obtained with 45 nm resolution at x580 magnification and 1 min exposure. Images of a biological sample (Coscinodiscus oculoides) were recorded.