43,530 research outputs found
[[alternative]]Application of critical concepts, anaerobic power and energy expenditure in predicting rowing performance
No full text[[abstract]]Application of critical concepts, anaerobic power and energy expenditure in predicting rowing performance
June,2005 Hsin-Fu Lin
Advisor: Jung-Charng Lin,
Abstract
Critical velocity (CV) and critical power (CP) have been proposed to be effective indirect anaerobic threshold methods in monitoring training and predicting performance of rowing respectively. The purpose of this study was to compare these two indexes in predicting indoor rowing performance by combining different physiological variables, including maximal oxygen uptake ( VO2max ), anaerobic threshold (AT4) and modified Wingate test, which are important physiological variables in endurance performance. In addition, whether or not the physiological variables (VO2, VCO2, VE, HR, [La-]) under these two critical intensities were stable was also examined. Fifteen elite female rowers (age 20.73± 1.44 years, height 1.64 ±0.35m, weight 56.64±4.38kg) were recruited in this study. VO2max (2.47 ±0.47L) and AT4(157.81 ±22.08W) were measured during a discontinuous graded exercise test, starting at 100W, on a Concept II ergometer increased by 25 W for each 3-min stage. Four test times of duration 90s, 240s, 600s, and 1200s were used to determine CP (139.49 ±20.37W), whereas CV( 4.00 ±0.14m/s) was estimated by 400m, 600m, 800m, 1000m maximal exertion trials in different days as well by using Linear distance-time model. Peak power (353.48 ±27.71W), maximum power (350.12 ±26.72W), minimum power (336.85 ±21.58W), mean power (314.44 ±27.87W), fatigue index (max power - min power/ mean power) were obtained using a modified Wingate test protocol (30s sprint) on the ergometer. Physiological variation of intensity at CV and CP, including VO2, VCO2, VE, HR, [La-], were measured every 5 minutes in 20-min constant rowing tests. The results of study showed that VO2max, AT4, CP, CV, peak power, mean power were significantly correlated with 2000 indoor rowing performance (r=?0.84, ?0.85, ?0.81, ?0.97, ?0.66, ?0.67, P<0.01). By submitting mean power, fatigue index, VO2max, AT4 with each index to a stepwise regression analysis, it produced two individual critical concept models as following to predict 2000 indoor rowing performance: CV model: T2000= ?131.83 CV(m/s)?1.00 fatugue index(%) +1023.91 (R2=0.96, SEE=4.10, p<.05); CP model: T2000=?22.59 VO2max(L/min)?.38AT4(W)+608.58 (R2 =0.82, SEE=8.05, p<.05). When rowing at CV on indoor ergometer (14±4 min), VO2, VE, HR, [La-] didn’t reach steady state and VCO2 was not different at different time points. Under CP, VO2, VCO2 didn’t change with time, however, there were significant difference of VE, HR, [La-] at different time points. Our findings in this study indicated that CV has more predictive power, representing as anaerobic threshold, than AT4 to predict rowing performance. Besides CV, fatigue index from modified Wingate test is also an important determinant for 2000-m performance of female rowers. Therefore, comparing with CP, CV could be used when applying critical concept in training and evaluate indoor performance in rowing. In addition, both two-parameter-derived CV and CP in rowing do not represent sustainable steady state intensities.
Key words: critical velocity, critical power, anaerobic power, energy expenditure, rowing, performance.
Robust Scoring Functions for Protein-Ligand Interactions with Quantum Chemical Charge Models
No full textOrdinary least-squares (OLS) regression has been used widely for constructing the scoring functions for protein–ligand interactions. However, OLS is very sensitive to the existence of outliers, and models constructed using it are easily affected by the outliers or even the choice of the data set. On the other hand, determination of atomic charges is regarded as of central importance, because the electrostatic interaction is known to be a key contributing factor for biomolecular association. In the development of the AutoDock4 scoring function, only OLS was conducted, and the simple Gasteiger method was adopted. It is therefore of considerable interest to see whether more rigorous charge models could improve the statistical performance of the AutoDock4 scoring function. In this study, we have employed two well-established quantum chemical approaches, namely the restrained electrostatic potential (RESP) and the Austin- model 1-bond charge correction (AM1-BCC) methods, to obtain atomic partial charges, and we have compared how different charge models affect the performance of AutoDock4 scoring functions. In combination with robust regression analysis and outlier exclusion, our new protein–ligand free energy regression model with AM1-BCC charges for ligands and Amber 99SB charges for proteins achieve lowest root-mean- squared error of 1.637 kcal/mol for the training set of 147 complexes and 2.176 kcal/mol for the external test set of 1427 complexes. The assessment for binding pose prediction with the 100 external decoy sets indicates very high success rate of 87% with the criteria of predicted root-mean- squared deviation of less than 2 Å. The success rates and statistical performance of our robust scoring functions are only weakly class-dependent (hydrophobic, hydrophilic, or mixed)
Deriving Interfacial Properties of Small Unilamellar Vesicles Via Multiscale Computer Simulations
No full text
Supplemental Material - Mitochondrial transplantation attenuates traumatic neuropathic pain, neuroinflammation, and apoptosis in rats with nerve root ligation
No full textSupplemental Material for Mitochondrial transplantation attenuates traumatic neuropathic pain, neuroinflammation, and apoptosis in rats with nerve root ligation by Chi-Chen Huang, Hsin-Yi Chiu, Po-Hsuan Lee, Shih-Yuan Fang, Ming-Wei Lin, Hui-Fang Chen and Jung-Shun Lee in Molecular Pain</p
MEDock: a Web Server for Efficient Prediction of Ligand Binding Sites Based on a Novel Optimization Algorithm
No full textSupplemental material for Immunomodulatory properties of medicinal mushrooms: differential effects of water and ethanol extracts on NK cell-mediated cytotoxicity
No full textSupplemental Material for Immunomodulatory properties of medicinal mushrooms: differential effects of water and ethanol extracts on NK cell-mediated cytotoxicity by Chia-Chen Lu, Ya-Jing Hsu, Chih-Jung Chang, Chuan-Sheng Lin, Jan Martel, David M Ojcius, Yun-Fei Ko, Hsin-Chih Lai and John D Young in Innate Immunity</p
Dataset supporting publication "Femtosecond thulium fiber laser utilizing a gain-switched laser diode"
No full textThis dataset supports the publication: Femtosecond thulium fiber laser utilizing a gain-switched laser diode
AUTHORS: Ibrahim H. Abughazaleh, Matthew D. Gerard, Panuwat Srisamran, Duanyang Xu, Yongmin Jung, and Lin Xu
TITLE:Femtosecond thulium fiber laser utilizing a gain-switched laser diode
JOURNAL: optics letters
PAPER DOI IF KNOWN: https://doi.org/10.1364/OL.564071</span
MEDock: a Web Server for Efficient Prediction of Ligand Binding Sites Based on a Novel Optimization Algorithm
No full textSupplemental Material - Predicting Fatigue-Associated Aberrant Driving Behaviors Using a Dynamic Weighted Moving Average Model With a Long Short-Term Memory Network Based on Heart Rate Variability
No full textSupplemental Material for Predicting Fatigue-Associated Aberrant Driving Behaviors Using a Dynamic Weighted Moving Average Model With a Long Short-Term Memory Network Based on Heart Rate Variability by Cheng-Yu Tsai, He-in Cheong, Robert Houghton, Wen-Hua Hsu, Kang-Yun Lee, Jiunn-Horng Kang, Yi-Chun Kuan, Hsin-Chien Lee, Cheng-Jung Wu, Lok-Yee Joyce Li, Yin-Tzu Lin, Shang-Yang Lin, Iulia Manole, Arnab Majumdar in Human Factors</p
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