Continuous health care and the measurement of health-related physical fitness (HRPF) is necessary for prevention against chronic diseases; however, HRPF measurements including laboratory methods may not be practical for large populations owing to constraints such as time, cost, and the requirement for qualified technicians. This study aimed to develop a multiple linear regression model to estimate the HRPF of Korean adults, using easy-to-measure dependent variables, such as gender, age, body mass index, and percent body fat. The National Fitness Award datasets of South Korea were used in this analysis. The participants were aged 19–64 years, including 319,643 male and 147,600 females. HRPF included hand grip strength (HGS), flexibility (sit and reach), muscular endurance (sit-ups), and cardiorespiratory fitness (estimated VO2max). An estimation multiple linear regression model was developed using the stepwise technique. The outlier data in the multiple regression model was identified and removed when the absolute value of the studentized residual was ≥2. In the regression model, the coefficient of determination for HGS (adjusted R2: 0.870, P < 0.001), muscular endurance (adjusted R2: 0.751, P < 0.001), and cardiorespiratory fitness (adjusted R2: 0.885, P < 0.001) were significantly high. However, the coefficient of determination for flexibility was low (adjusted R2: 0.298, P < 0.001). Our findings suggest that easy-to-measure dependent variables can predict HGS, muscular endurance, and cardiorespiratory fitness in adults. The prediction equation will allow coaches, athletes, healthcare professionals, researchers, and the general public to better estimate the expected HRPF.
In taekwondo, poomsae (i.e., form) competitions have no quantitative scoring standards, unlike gyeorugi (i.e., full-contact sparring) in the Olympics. Consequently, there are diverse fairness issues regarding poomsae evaluation, and the demand for quantitative evaluation tools is increasing. Action recognition is a promising approach, but the extreme and rapid actions of taekwondo complicate its application. This study established the Taekwondo Unit technique Human Action Dataset (TUHAD), which consists of multimodal image sequences of poomsae actions. TUHAD contains 1936 action samples of eight unit techniques performed by 10 experts and captured by two camera views. A key frame-based convolutional neural network architecture was developed for taekwondo action recognition, and its accuracy was validated for various input configurations. A correlation analysis of the input configuration and accuracy demonstrated that the proposed model achieved a recognition accuracy of up to 95.833% (lowest accuracy of 74.49%). This study contributes to the research and development of taekwondo action recognition.
This paper deals with chiral enzymatic resolution of 4-arylthio-2-butanols by lipase to prepare potential intermediates of beta-lactam antibiotics. Among several lipases employed, lipase P type enzyme gave the highest ee value to prepare (R)-4-arylthio-2-butyl acetate. The enzymatic resolution of phenyl substituted alcohol (6a) using lipase P showed the highest ee value (99.7%) among those of 4-arylthio-2-butanol derivatives. Lipase P mediated hydrolysis of acylester 7a gave also (R)-alcohol 6a selectively. For determination of enantiomeric purity of these enzymatic resolved analytes, liquid chromatographic analysis was performed using two coupled Chiralcel OD and (R,R)-WhelkO chiral column.
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