Introduction/purpose: This study's purpose was to develop and employ a technique to determine the fastest masters marathon world records (WR), ages 35-79 years, adjusted for age (WRadj).
Methods: From single-age WR data, a best-fit polynomial curve (WRpred1) was developed for the larger age range of 29-80 years for women and 30-80 years for men to improve curve stability in the 35-79 years range. Due to the relatively large degree of data scatter about the curve and the resultant age bias in favor of older runners, a subsample was constituted consisting of those with the lowest WR/WRpred1 ratio within each five-year age group (N = 11). A new polynomial best-fit curve (WRpred2) was developed from this subsample to become the standard against which WR would be compared across age. WRadj was computed from WR/WRpred2 for all runners, 35-79 years, from which the top ten fastest were then determined.
Results: The WRpred2 model reduced data scatter and eliminated the age bias. Tatyana Pozdniakova, 50 years, WR = 2:31:05, WRadj = 2:12:40; and Ed Whitlock, 73 years, WR = 2:54:48, WRadj = 1:59:57, had the fastest WRadj for women and men, respectively.
Conclusions: This technique of iterative curve-fitting may be an optimal way of determining the fastest masters WRadj and may also be useful in better understanding the upper limits of human performance by age.
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http://dx.doi.org/10.1186/s40064-016-3190-5 | DOI Listing |
Sci Rep
December 2024
Department of Production Engineering, KTH Royal Institute of Technology, 11428, Stockholm, Sweden.
This study investigates the implementation of collaborative route planning between trucks and drones within rural logistics to improve distribution efficiency and service quality. The paper commences with an analysis of the unique characteristics and challenges inherent in rural logistics, emphasizing the limitations of traditional methods while highlighting the advantages of integrating truck and drone technologies. It proceeds to review the current state of development for these two technologies and presents case studies that illustrate their application in rural logistics.
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December 2024
Marine Biology Laboratory, Earth and Life Institute, Université Catholique de Louvain, Croix du Sud 3, 1348, Louvain-La-Neuve, Belgium.
The bioluminescent European brittle star Amphiura filiformis produces blue light at the arm-spine level thanks to a biochemical reaction involving coelenterazine as substrate and a Renilla-like luciferase as an enzyme. This echinoderm light production depends on a trophic acquisition of the coelenterazine substrate. Without an exogenous supply of coelenterazine, this species loses its luminous capabilities.
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December 2024
Shandong Agricultural University, Taian, 271018, China.
Acoustic emission information can describe the damage degree of rock samples in the process of failure. However, as a discrete non-stationary signal, acoustic emission information is difficult to be effectively processed by conventional methods, while wavelet analysis is an effective method for non-stationary signal processing. Therefore, acoustic emission signal is deeply studied by using wavelet analysis method.
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December 2024
School of Psychology, Inner Mongolia Normal University, Hohhot, China.
The purpose of this study was to evaluate the psychometric properties of the Chinese version of the Revised Indebtedness Scale (IS-R-C) in mainland China. A total of 1057 university students participated in this study using a two-wave whole-group sampling method. Sample 1, consisting of 537 participants, was used for item analysis and exploratory factor analysis (EFA) of the Revised Indebtedness Scale (IS-R).
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December 2024
School of Physical Education, Shanghai University of Sport, Shanghai, 200438, China.
Objective: This study aimed to examine the levels of physical activity (PA), sleep, and mental health (MH), specifically depression, anxiety, and stress, among Chinese university students. It also aimed to analyze the influencing factors of MH, providing a theoretical foundation for developing intervention programs to improve college students' mental health.
Methods: A stratified, clustered, and phased sampling method was employed.
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