It is necessary to study the rugby tackle as it is associated with successful performance outcomes and is responsible for the majority of contact injuries. A novel collision sport simulator was developed to study tackle performance. The main aim of this validation study was to assess tackle technique performance between two different conditions: simulator versus a standardised one-on-one tackle drill previously used to assess technique. Tackling proficiency was assessed using a list of technical criteria. Mean scores, standard deviations and Cohen's d effect sizes were calculated. Mean overall score for dynamic i.e. running simulator tackles was 7.78 (95%CI 7.58-7.99) (out of 9) or 87% (standard deviation or SD±8.94), and mean overall score for dynamic "live" tackles was 7.85 (95%CI 7.57-8.13) (out of 9) or 87% (SD±9.60) (effect size = 0.08; trivial; p > 0.05). Mean overall score for static i.e. standing simulator tackles was 7.45 (95%CI 7.20-7.69) (out of 9) or 83% (SD±10.71), and mean overall score for static "live" tackles was 8.05 (95%CI 7.83-8.27) (out of 9) or 89% (SD±7.53) (effect size = 0.72; moderate; p < 0.001). The simulator replicates dynamic tackle technique comparable to real-life tackle drills. It may be used for research analysing various aspects of the tackle in rugby and other contact sports.
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http://dx.doi.org/10.1080/02640414.2018.1482590 | DOI Listing |
Anal Methods
January 2025
Jiangsu Beier Machinery Co. Ltd, Jiangsu, 215600, China.
Plastic waste management is one of the key issues in global environmental protection. Integrating spectroscopy acquisition devices with deep learning algorithms has emerged as an effective method for rapid plastic classification. However, the challenges in collecting plastic samples and spectroscopy data have resulted in a limited number of data samples and an incomplete comparison of relevant classification algorithms.
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January 2025
Mineralogical Society of Antwerp, Boterlaarbaan 225, 2100 Deurne, Belgium.
ConspectusWhile photochromic natural sodalites, an aluminosilicate mineral, were originally considered as curiosities, articles published in the past ten years have radically changed this perspective. It has been proven that their artificial synthesis was easy and allowed compositional tuning. Combined with simulations, it has been shown that a wide range of photochromic properties were achievable for synthetic sodalites (color, activation energy, reversibility, etc.
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January 2025
CSIC - Insituto de Catálisis y Petroleoquímica, Madrid, Spain.
The extended use of a given product normally precedes concerns about it. The reactivity-based nanotoxicity is a major concern that must be tackled from its fundamental understanding to its regulatory management. Moreover, concepts and ideas must seamlessly flow between relevant performers.
View Article and Find Full Text PDFEnviron Int
January 2025
Ineos Oxford Institute for Antimicrobial Research, Department of Biology, University of Oxford, Oxford OX1 3RE, United Kingdom. Electronic address:
Antimicrobial resistance (AMR) and environmental degradation are existential global public health threats. Linking microplastics (MPs) and AMR is particularly concerning as MPs pollution would have significant ramifications on controlling of AMR; however, the effects of MPs on the spread and genetic mechanisms of AMR bacteria remain unclear. Herein, we performed Simonsen end-point conjugation to investigate the impact of four commonly used MPs on transfer of clinically relevant plasmids.
View Article and Find Full Text PDFNeural Netw
January 2025
School of Computer Engineering and Science, Shanghai University, Shanghai, 200444, China. Electronic address:
Conditional adversarial domain adaptation (CADA) is one of the most commonly used unsupervised domain adaptation (UDA) methods. CADA introduces multimodal information to the adversarial learning process to align the distributions of the labeled source domain and unlabeled target domain with mode match. However, CADA provides wrong multimodal information for challenging target features due to utilizing classifier predictions as the multimodal information, leading to distribution mismatch and less robust domain-invariant features.
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