Efficacy of Polarized Fibreglass Filters Irradiated by Ultraviolet Light in Capture and Inactivation of Aerosolized <i>Bacillus Subtilis</i> Spores
Bibliographic record
Abstract
In this study, spores of Bacillus subtilis were used as a surrogate for spores of Bacillus anthracis. The mock-up air purification system consisted of one or two V-shaped banks of electrostatically polarized fibreglass filters that were installed within a rectangular wooden duct. Ultraviolet (UV) lights that swept across the surface of the filters were installed in front and back of the bank of filters. A nebulizer that contained a suspension of B. subtilis spores was placed in the duct in front of the filters. Air entering the duct passed through a high-efficiency particulate arresting (HEPA) filter and was drawn by a fan at the exit. Tests on up-stream and down-stream air collected with an Anderson air sampler showed that electrostatic polarization increased the efficiency of the filters in capturing spores by 51% or 38% at air speeds of 1.52 m/s or 2.54 m/s, respectively. Filter efficiency was also based on the number of spores that could be washed from the filters, and polarization increased this by as much as 92%. Challenge to the polarized filters with increasing levels of dust did not significantly reduce their efficacy in trapping spores (P>0.05) until the pressure drop across the filters exceeded 15 Pa. Ultraviolet irradiation for 5 minutes was sufficient to kill 73% of the spores on the front filters. The conclusion was that an air purification system consisting of polarized filters irradiated by UV light could be used to reduce spore contamination of the environment, including those of B. anthracis, and thereby reduce the risk of spreading disease.
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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) | 0.001 | 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".