Effects of Sweat and 3D-deformation on the Mechanical Behaviour of Nitrile Rubber Gloves
Bibliographic record
Abstract
Research has proven that mechanical deformations (MD) caused by hand flexing affect the structure of disposable protective gloves. However, these studies do not consider the presence of a physiological solution such as sweat. The combination of mechanical constraints and sweat might modify the mechanical and physical properties of the protective gloves and therefor their effectiveness. The main objective of this work is to evaluate the combined effects of human sweat and MDs on certain physical and mechanical phenomena that could affect the structure of nitrile rubber protective gloves. The strain energy, crystallinity, swelling and glove surface profile were investigated. Combined with MDs, the physiological solution significantly affects the structure of the gloves. Contact of the glove sample with the physiological solution modified the strain energy and induced a swelling that modified mechanical properties. Also, the deformation frequency greatly affected the strain energy and the number of deformations changed the degree of crystallinity. A qualitative analysis by SEM showed the deterioration of the surface of the gloves in contact with skin. Based on these results, further investigation is needed on the overall effect of sweat on the effectiveness of protective gloves against mechanical and chemical hazards.
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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) | 0.000 | 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) | 0.002 | 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".