Impact of airflow on body cooling in exercise: an exploratory study
Bibliographic record
Abstract
Objective: To analyze the body heat dissipation by thermography during indoor running treadmill with different airflow conditions. Materials and method: Nine male participants (23.0±2.5 years old) underwent three 45-minute moderate-intensity running sessions (60-70% reserve heart rate) on a treadmill. At each session, a different experimental condition was applied in a crossover design: without airflow (NF), and with low (LF) and high airflow (HF) generated by a fun. Thermograms were obtained with a thermal camera before exercise, during (every 10 minutes), and after exercise. Skin temperature (Tsk) was measured on regions of interest of the upper body: pectoral, brachial biceps, and upper back. A repeated measures ANOVA was used to compare Tsk over time and between conditions, considering p<0.05 as statistically significant. Results: In pectoral and brachial biceps, LF and HF conditions provided greater reductions in Tsk at all moments when compared to the NF (p<0.05). There was a higher reduction in Tsk to the HF vs LF in biceps at 30, 40, and 45 min during exercise (p<0.05). In the upper back, Tsk remained below baseline at all moments during exercise only in the HF condition (p<0.05). In NF and LF conditions, Tsk returned to baseline at 30 min during exercise (p>0.05). Conclusion: The frontal wind flow enhances body heat dissipation during moderate-intensity running in the pectoral, brachial biceps, and upper back, with a direct relationship of flow speed and Tsk reduction during exercise.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".