This study aimed to investigate the consistency of attacking tactical and technical behaviour, and physical characteristics, over multiple bouts, and variability across days, of a specific rugby union forwards small-sided game (SSG). Data was collected from 21 professional rugby union forwards during four training sessions. The SSG, consisting of five bouts of work (150-s) interspersed by passive recovery (75-s), aimed to elicit specific attacking tactical behaviour. Tactical behaviour (i.e., regularity of attacking shape [entropy]), and technical (e.g., passes) and physical (e.g., total distance) characteristics were quantified. Results showed that technical characteristics remained consistent, whereas the regularity of width of the attacking shape and two physical characteristics (i.e., total distance, training impulse) varied across bouts. However, these effects had limited practical significance. Technical characteristics were consistent across days, but minimal variability was observed for tactical behaviour and physical characteristics, as shown by their small random effects with 95% profile likelihood confidence intervals (PLCI) including zero (e.g., SD[95%PLCI] = 0.03[0.00, 0.06]). Consequently, consistency of stimulus over bouts and days is achievable for the majority of the variables investigated, thus supporting the use of SSG to elicit consistent attacking behaviour, but also technical and physical characteristics in rugby union forwards.
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http://dx.doi.org/10.1080/02640414.2022.2156101 | DOI Listing |
Mayo Clin Proc Digit Health
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Department Radiology, Stanford University, Stanford, CA.
Artificial intelligence (AI) and machine learning (ML) are driving innovation in biosciences and are already affecting key elements of medical scholarship and clinical care. Many schools of medicine are capitalizing on the promise of these new technologies by establishing academic units to catalyze and grow research and innovation in AI/ML. At Stanford University, we have developed a successful model for an AI/ML research center with support from academic leaders, clinical departments, extramural grants, and industry partners.
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Fisheries College, Guangdong Ocean University, Zhanjiang 524088, China; Pearl Breeding and Processing Engineering Technology Research Centre of Guangdong Province, Zhanjiang 524088, China; Guangdong Provincial Key Laboratory of Aquatic Animal Disease Control and Healthy Culture, Zhanjiang, 524088, China; Pearl Research Institute, Guangdong Ocean University, Zhanjiang, China.
Plastic pollution, particularly microplastics and nanoplastics, poses a significant threat to marine ecosystems. Bivalves, vital filter feeders that accumulate plastic particles, underscore the necessity for advanced omics technologies to grasp their molecular reactions to plastic exposure. This review delves into the impact of microplastics and nanoplastics on bivalves utilizing advanced omics technologies.
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December 2024
Department of Psychiatry, Erasmus Medical Center, Rotterdam, Netherlands.
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J Econ Entomol
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Department of Entomology and Plant Pathology and the North Carolina Plant Sciences Institute, NC State University, Raleigh, NC, USA.
Debate over resistance management tactics for genetically engineered (GE) crops expressing insecticidal toxins is not new. For several decades, researchers, regulators, and agricultural industry scientists have developed strategies to limit the evolution of resistance in populations of lepidopteran and coleopteran pests. A key attribute of many of these events was insecticide resistance management (IRM) strategies designed around a presumed high-dose expression sufficient to kill 99.
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