Sodium bicarbonate ingestion increases glycolytic contribution and improves performance during simulated taekwondo combat     

João Paulo Lopes-Silva  Jonatas Ferreira Da Silva Santos  Guilherme Giannini Artioli  Irineu Loturco  Chris Abbiss  Emerson Franchini 《European Journal of Sport Science》2018,18(3):431-440

Purpose: To investigate the effect of sodium bicarbonate (NaHCO₃) on performance and estimated energy system contribution during simulated taekwondo combat. Methods: Nine taekwondo athletes completed two experimental sessions separated by at least 48?h. Athletes consumed 300?mg/kg body mass of NaHCO₃ or placebo (CaCO₃) 90?min before the combat simulation (three rounds of 2 min separated by 1 min passive recovery), in a double-blind, randomized, repeated-measures crossover design. All simulated combat was filmed to quantify the time spent fighting in each round. Lactate concentration [La^?] and rating of perceived exertion (RPE) were measured before and after each round, whereas heart rate (HR) and the estimated contribution of the oxidative (W_OXI), ATP (adenosine triphosphate)-phosphocreatine (PCr) (W_PCR), and glycolytic (W_{[ La^? ]}) systems were calculated during the combat simulation. Results: [La^?] increased significantly after NaHCO₃ ingestion, when compared with the placebo condition (+14%, P?=?0.04, d?=?3.70). NaHCO₃ ingestion resulted in greater estimated glycolytic energy contribution in the first round when compared with the placebo condition (+31%, P?=?0.01, d?=?3.48). Total attack time was significantly greater after NaHCO₃ when compared with placebo (+13%, P?=?0.05, d?=?1.15). W_OXI, W_PCR, VO₂, HR and RPE were not different between conditions (P?>?0.05). Conclusion: NaHCO₃ ingestion was able to increase the contribution of glycolytic metabolism and, therefore, improve performance during simulated taekwondo combat.  相似文献   

Time–frequency recurrent transformer with diversity constraint for dense video captioning     

《Information processing & management》2023,60(2):103204

  相似文献   

The first steps for adapting an artificial intelligence emotion expression recognition software for emotional management in the educational context     

Jorge Fernández Herrero  Francisco Gómez Donoso  Rosabel Roig Vila 《British journal of educational technology : journal of the Council for Educational Technology》2023,54(6):1939-1963

To test the suitability of an automatic system for emotional management in the classroom following the control-value theory of achievement emotions (CVT) framework, the performance of an emotional expression recognition software of our creation is evaluated in an online synchronous context. Sixty students from the Faculty of Education at the University of Alicante participated in 16 educational activities recording close-ups of their faces and completing the AEQ emotional self-report, as well as detailed reports from the subsequent review of their videos. In addition, they completed the VCQ-36 test to measure their volitional competencies and relate their influence on their emotional response. The results indicate a high coherence between the emotional expressions detected by the automatic system and the detailed emotional self-reports, but insufficient precision to meet the CVT requirements. On the other hand, both the AEQ test results and the emotion expression recognition software suggest students' preference for participative activities as opposed to passive ones. Meanwhile, statistical analysis results indicate that volitional competencies seem to influence the emotional response of students in the educational context, although the AI system does not show sufficient sensitivity in this field. Implications and limitations of this study for future work are discussed.

Practitioner notes

What is already known about this topic

• Student motivation and involvement in the learning process are highly related to appropriate emotional regulation, which can be associated with particular educational activities, strategies and methodologies.
• Deep learning technology based on convolutional neural networks feeds automatic systems focused on facial expression recognition from image analysis.

What this paper adds

• There is high coherence between the emotional expressions detected by the AI system and the students' emotional self-reports, but the AI system provides just emotional valences, insufficient to meet the CVT framework.
• Both emotional self-reports and the emotion recognition software suggest students' preference for active educational activities as opposed to passive ones.
• Volitional competencies seem to influence the emotional response of students in the educational context.

Implications for practice and/or policy

• It is possible to use automatic systems to effectively monitor the emotional response of students in the learning process.
• Only if sensitivity improved, a real-time, easy-to-interpret emotional expression recognition software interface could be implemented to assist teachers with the emotional management of their classes within the CVT framework, maximizing their motivation and engagement.

  相似文献   

Cross-modal image–text search via Efficient Discrete Class Alignment Hashing     

《Information processing & management》2022,59(3):102886

  相似文献