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http://dx.doi.org/10.1016/S2213-2600(17)30138-8 | DOI Listing |
Sports Med Health Sci
March 2025
Department of Allied Health, Otterbein University, Westerville, OH, 43081, USA.
Marching band (MB) artists are often part of the general student population and not required to complete a pre-participation health screening to identify predisposing medical conditions or risks for injury/illness. Anecdotally, exertional heat illnesses (EHI) are a concern for MB artists. As more athletic trainers provide MB healthcare, research is needed on EHI occurrence and MB associated EHI risk factors.
View Article and Find Full Text PDFNutrients
December 2024
Drum Corps International, Inc., Indianapolis, IN 46241, USA.
Exercise-associated hyponatremia (EAH) is commonly observed in endurance athletes, where prolonged physical exertion combined with being unaware of personal hydration needs can lead to excessive water consumption or inadequate sodium intake. Marching band (MB) is an emerging setting for sports medicine professionals. However, there is little research on non-musculoskeletal illnesses among these performing artists.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR, China.
This paper compares three automated path-planning algorithms based on publicly available data. The algorithms include a Dijkstra-based algorithm (DBA) that improves on the straightforward application of Dijkstra's algorithm, which restricts the path only to the grid edges. We present a fair and comprehensive comparison method for evaluating multiple algorithms-DBA, the Fast Marching Method (FMM), and a great circle-based method.
View Article and Find Full Text PDFBone
February 2025
Department of Mechanical Engineering, University of Alberta, Edmonton, AB, Canada; Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada; School of Dentistry, University of Alberta, Edmonton, AB, Canada. Electronic address:
Quant Imaging Med Surg
October 2024
International School of Information Science & Engineering (DUT-RUISE), Dalian University of Technology, Dalian, China.
Background: Accurate delineation of knee bone boundaries is crucial for computer-aided diagnosis (CAD) and effective treatment planning in knee diseases. Current methods often struggle with precise segmentation due to the knee joint's complexity, which includes intricate bone structures and overlapping soft tissues. These challenges are further complicated by variations in patient anatomy and image quality, highlighting the need for improved techniques.
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