The performance difference between the sexes (in percent) across age groups for split disciplines and overall race times. by Beat Knechtle (5504402)

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Participants by event status and sex. by Beat Knechtle (5504402)

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S1 Data - by Beat Knechtle (5504402)

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Sex difference in swimming by split disciplines by the type of swim, bike, and run course. by Beat Knechtle (5504402)

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Average split and overall race times (HH:MM:SS). by Beat Knechtle (5504402)

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Split and overall race times for women and by age group. by Beat Knechtle (5504402)

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Trends of average and best race times for IRONMAN^® age group triathletes. by Beat Knechtle (5504402)

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S2 Data - by Beat Knechtle (5504402)

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Number of finishers by sex and men-to-women ratio over the years between 2002 and 2022. by Beat Knechtle (5504402)

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Split and overall IRONMAN^® race times histograms for women and men. by Beat Knechtle (5504402)

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Men-to-women ratio across age groups. by Beat Knechtle (5504402)

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Trend of the sex difference across years in overall race time. by Beat Knechtle (5504402)

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Actual measurement of shape errors. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Average body weight trends for the four groups during the pre-challenge period. by Oumayma Arbani (21001472)

Average body weight trends for the four groups during the post-challenge period. by Oumayma Arbani (21001472)

Innovation and night light in large and small cities. by Saul Estrin (8629173)

(A) Shape of the osteotomies during the 3-step MIPS drilling procedure. by Marsel Ganeyev (21453399)

AdMSC-EVs enhanced colony formation and migration of LECs and decreased proliferation. by Xiaoqin Li (1399105)

Mode shapes of the first six modes. by Xueting Ma (390540)

Comprehensive prediction process of shape errors. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”