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241.
For ski manufacturers, it is important to know how a given ski-binding system performs under different loading conditions.
Important performance parameters are the ski deformation and the resulting turn radius. This study focuses on carving turns. The aims of this study were: (1) to investigate the dependence of the turn radius on edging angle, load on the binding,
and snow hardness using a finite element (FE) simulation, and (2) to compare the results with predictions of a frequently
used model introduced by Howe. The FE simulation used a quasi-static approach (similar to Howe’s model), but the ski–snow
interaction model incorporated the groove that forms in the snow during a carved turn. Up to edging angles of 40°, the results
of the FE simulation agreed well with Howe’s model. However, for large edging angles (>50°) the calculated turn radius leveled
out, whereas Howe’s model tends to zero. This effect was more pronounced for soft snow than for hard snow conditions. Increasing
forces on the binding caused a decrease in the calculated turn radii. In summary, the FE simulation showed that particularly
at large edging angles the groove in the snow needs to be considered in models of the ski–snow interaction or in computations
of the turn radius. 相似文献
242.
Sebastian Ludyga Uwe Pühse Markus Gerber Christian Herrmann 《European Journal of Sport Science》2019,19(3):375-383
Background: Although accumulating evidence suggests that motor and cognitive development is interrelated, only a few studies have investigated links between executive function and motor control. Therefore, the present cross-sectional study examined the relationship between motor competences and core components of executive functioning, including inhibitory control, working memory and cognitive flexibility. Methods: In 89 preadolescent children, motor competences were assessed using the MOBAK-5 test battery. Additionally, all participants completed computer-based versions of the Flanker task, which included standard and switch blocks, and the 2-Back task. Results: Partial correlations (correcting for age, gender and body mass index) revealed that locomotor skills were associated with the adjusted hit-rate on the 2-Back task (r?=?0.34) whereas object control was linked with conflict score on the Flanker task (r?=??0.39). In contrast, there was no correlation between switch costs and motor competences. Conclusion: In preadolescent children, high competences in locomotor skills and object control skills are associated with high performance on specific executive function tasks. This finding supports the current view that motor competences and cognitive control share some common underlying processes. 相似文献
243.
Lars Gabrys Jens Baumert Christin Heidemann Markus Busch Jonas David Finger 《运动与健康科学(英文)》2021,10(4):439-446
BackgroundPhysical activity is favorable for health, and vigorous sports activity is particularly beneficial. This study investigates the association between changes in sports participation patterns over time and cardio-metabolic and self-perceived health outcomes.MethodsData from 3752 adults (18–79 years of age) who participated in 2 national health interview and examination surveys in 1997–1999 and 2008–2011 were included, with a mean follow-up time of about 12 years. A change in self-reported sports activity was analyzed with respect to the incidence of type 2 diabetes, coronary heart disease (CHD), hypertension, obesity, dyslipidemia, metabolic syndrome, and poor self-perceived health. Participants with pre-existing disease or risk factor of interest at baseline were excluded from the analysis. Being sufficiently active in sports was specified as doing sports for at least 1–2 h per week, and 4 activity categories were defined: 1) inactive at both time points (inactive–inactive), 2) inactive at baseline and active at follow-up (inactive–active), 3) active at baseline and inactive at follow-up (active–inactive), and 4) active at both time points (active–active). Associations between sports activity engagement and health outcomes were estimated by logistic regression models with different stages of adjustments.ResultsNot engaging in any regular sports activity at both time points (inactive–inactive) was associated with higher rates of type 2 diabetes (odds ratio (OR) = 1.82, 95% confidence interval (95%CI): 1.08–3.08), CHD (OR = 1.82, 95%CI: 1.16–2.84), hypertension (OR = 1.36, 95%CI: 1.03–1.81), metabolic syndrome (OR = 1.58, 95%CI: 1.08–2.32), and poor self-perceived health (OR = 2.54, 95%CI: 1.83–3.53) compared to doing regular sports for a minimum of 1–2 h per week over time (active–active). In case of change from inactivity to any regular sports activity (inactive–active), the rate of risk factor occurrence was not statistically different from the active–active reference group except for poor self-perceived health, but it was higher for type 2 diabetes (OR = 2.15, 95%CI: 1.12–4.14) and CHD (OR = 1.77, 95%CI: 1.03–3.03). Being active at baseline but inactive at follow-up (active–inactive) was not associated with higher disease incidence of type 2 diabetes (OR = 0.70, 95%CI: 0.25–1.97) or CHD (OR = 1.20, 95%CI: 0.49–2.99), but was associated with higher rates of hypertension (OR = 1.61, 95%CI: 1.11–2.34), obesity (OR = 2.34, 95%CI: 1.53–3.57), metabolic syndrome (OR = 1.70, 95%CI: 1.11–2.63), and poor self-perceived health (OR = 2.16, 95%CI: 1.53–3.07) at follow-up.ConclusionEven a low weekly quantity (1–2 h) of regular sports activity is partly associated with health benefits. Being formerly but not currently active was not associated with an increased disease incidence, but was associated with a higher risk-factor development compared to the reference group (active–active). Becoming active was preventive for risk-factor development but was not preventive for disease incidence, which probably means that the health benefits from sports activity are not sustainable and disease incidence is only shifted to a later period in life. For this reason, the promotion of and commitment to regular sports activity should be addressed as early as possible over the lifespan to achieve the best health benefits. 相似文献
244.
Elisabeth Bauer Martin Greisel Ilia Kuznetsov Markus Berndt Ingo Kollar Markus Dresel Martin R. Fischer Frank Fischer 《British journal of educational technology : journal of the Council for Educational Technology》2023,54(5):1222-1245
Advancements in artificial intelligence are rapidly increasing. The new-generation large language models, such as ChatGPT and GPT-4, bear the potential to transform educational approaches, such as peer-feedback. To investigate peer-feedback at the intersection of natural language processing (NLP) and educational research, this paper suggests a cross-disciplinary framework that aims to facilitate the development of NLP-based adaptive measures for supporting peer-feedback processes in digital learning environments. To conceptualize this process, we introduce a peer-feedback process model, which describes learners' activities and textual products. Further, we introduce a terminological and procedural scheme that facilitates systematically deriving measures to foster the peer-feedback process and how NLP may enhance the adaptivity of such learning support. Building on prior research on education and NLP, we apply this scheme to all learner activities of the peer-feedback process model to exemplify a range of NLP-based adaptive support measures. We also discuss the current challenges and suggest directions for future cross-disciplinary research on the effectiveness and other dimensions of NLP-based adaptive support for peer-feedback. Building on our suggested framework, future research and collaborations at the intersection of education and NLP can innovate peer-feedback in digital learning environments.
Practitioner notes
What is already known about this topic- There is considerable research in educational science on peer-feedback processes.
- Natural language processing facilitates the analysis of students' textual data.
- There is a lack of systematic orientation regarding which NLP techniques can be applied to which data to effectively support the peer-feedback process.
- A comprehensive overview model that describes the relevant activities and products in the peer-feedback process.
- A terminological and procedural scheme for designing NLP-based adaptive support measures.
- An application of this scheme to the peer-feedback process results in exemplifying the use cases of how NLP may be employed to support each learner activity during peer-feedback.
- To boost the effectiveness of their peer-feedback scenarios, instructors and instructional designers should identify relevant leverage points, corresponding support measures, adaptation targets and automation goals based on theory and empirical findings.
- Management and IT departments of higher education institutions should strive to provide digital tools based on modern NLP models and integrate them into the respective learning management systems; those tools should help in translating the automation goals requested by their instructors into prediction targets, take relevant data as input and allow for evaluating the predictions.