Influence of an Amino Acid Composition enhanced with Cold Plasma Radiation on Psychological Stress: A Blood Test, Gas Discharge Visualisation and Biofeedback Approach
Bibliographic record
Abstract
This study aimed to demonstrate the effect of enhanced amino acid compositions with cold plasma on human psychological stress by using blood tests, biofeedback, and gas discharge visualisation (GDV) techniques for stress measurements. An open, randomised, placebo-controlled trial for 30 days was conducted. 70 healthy people aged 35-65, men and women, were measured initially, randomly divided into three groups (experimental, control, and placebo), and measured 30 days later for changes in stress levels. Twenty people used amino acid composition; 30 used the same amino acid composition processed with cold plasma radiation, while 20 used a placebo. The ethics committee of the Federal State Budget Institution "Saint-Petersburg Scientific-Research Institute for Physical Culture," St. Petersburg, Russia, approved the study protocol. All participants signed an informed consent form, where a written and oral explanation of the research protocol was provided. Blood, biofeedback, and GDV test results were presented to show differences in stress levels during the experiment. After 30 days, results for experimental and control groups were presented. Amino acids processed by the radiation of a cold plasma – enhanced with Igniton particles - had the most significant effect on stress levels. The results suggested that enhanced amino acid compositions significantly affected human stress levels during the longitude period. Stress reduction in humans can significantly influence disease prevention and health maintenance, ultimately extending human life expectancy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".