A Descriptive Analysis of the Fastest Race Courses for Triathletes

BACKGROUND: For Ironman® triathlon, it has been reported that most of the fnishers and the fastest women and men in Ironman® Hawaii originated from the United States of America (USA). We have, however, no knowledge ofwhere the fastest race courses in the Ironman® 70.3 triathlon took place. We aim to analyse where the Ironman® 70.3 races were held and where the fastest split and overall race times were achieved. METHODS: The athletes’ sex, age group, country of origin, and split times for swimming, running, cycling, and transitioning were obtained from the official Ironman® website. To investigate the locations of the fastest Ironman® 70.3 competitions between 2004 and 2020, a full sample of 852,721 qualifying records throughout 197 different event locations was processed. These race records were aggregated by location, and each location’s split and full finish times were calculated. Data analysis was performed first for the full sample (all race records), and then for an elite sub-sample consisting of the top 100 males and top 100 females records in each location. RESULTS: For the full sample, the fastest overall race times were achieved in Ironman® 70.3 Zell am See (Austria). For the top 100 athletes sub-sample, the Ironman® 70.3 European Championship Elsinore and Ironman® 70.3 World Championship were the fastest courses. CONCLUSION: These results are useful for athletes’ strategic planning and inform event organisers about the strengths of different courses, aiding in the optimisation and promotion of future Ironman® 70.3 races worldwide

3-(2,4-Dibromo­anilino)-2,2-dimethyl-2,3-dihydro­naphtho[1,2-b]furan-4,5-dione: a new substituted aryl­amino nor-β-lapachone derivative

The title compound, C20H15Br2NO3, shows the furan ring to adopt a half-chair conformation and the two ring systems to be approximately perpendicular [dihedral angle = 71.0 (2)°]. In the crystal structure, inter­molecular C—H⋯O contacts link the mol­ecules

A machine learning approach to finding the fastest race course for professional athletes competing in Ironman® 70.3 races between 2004 and 2020

Our purpose was to find the fastest race courses for elite Ironman® 70.3 athletes, using machine learning (ML) algorithms. We collected the data of all professional triathletes competing between 2004 and 2020 in Ironman 70.3 races held worldwide. A sample of 16,611 professional athletes originating from 97 different countries and competing in 163 different races was thus obtained. Four different ML regression models were built, with gender, country of origin, and event location considered as independent variables to predict the final race time. For all the models, gender was the most important variable in predicting finish times. Attending to the single decision tree model, the fastest race times in the Ironman® 70.3 World Championship of around ~4 h 03 min would be achieved by men from Austria, Australia, Belgium, Brazil, Switzerland, Germany, France, the United Kingdom, South Africa, Canada, and New Zealand. Considering the World Championship is the target event for most professional athletes, it is expected that training is planned so that they attain their best performance in this event.info:eu-repo/semantics/publishedVersio

Whole-genome sequencing of 1,171 elderly admixed individuals from Brazil

As whole-genome sequencing (WGS) becomes the gold standard tool for studying population genomics and medical applications, data on diverse non-European and admixed individuals are still scarce. Here, we present a high-coverage WGS dataset of 1,171 highly admixed elderly Brazilians from a census-based cohort, providing over 76 million variants, of which ~2 million are absent from large public databases. WGS enables identification of ~2,000 previously undescribed mobile element insertions without previous description, nearly 5 Mb of genomic segments absent from the human genome reference, and over 140 alleles from HLA genes absent from public resources. We reclassify and curate pathogenicity assertions for nearly four hundred variants in genes associated with dominantly-inherited Mendelian disorders and calculate the incidence for selected recessive disorders, demonstrating the clinical usefulness of the present study. Finally, we observe that whole-genome and HLA imputation could be significantly improved compared to available datasets since rare variation represents the largest proportion of input from WGS. These results demonstrate that even smaller sample sizes of underrepresented populations bring relevant data for genomic studies, especially when exploring analyses allowed only by WGS