Continuous production and recirculation of plasma‐activated water bubbles under different flow regimes for mixed‐species bacterial biofilm inactivation inside pipelines
Bibliographic record
Abstract
Abstract Biofilm formation in broiler drinking water systems is a public health concern. Bacterial detachment from the pipes into the drinking water subsequently increases the risk of waterborne transmission and has detrimental effects on animal and human health. The study evaluated the antimicrobial effectiveness of plasma‐activated water bubbles (PAWBs) recirculated under different flow regimes against the mixed‐species biofilms of Salmonella Typhimurium ATCC13311 and Aeromonas australiensis 03‐09 grown on the inner surfaces of polyvinyl chloride (PVC) pipes. A benchtop pipeline model representing broiler drinker lines was developed to compare the biofilm inactivation efficacy of PAWB recirculated at different flow rates, corresponding to Reynold's number of 1000, 2500, and 4000. The synergistic mechanical and oxidative recirculation using PAWB resulted in a higher biofilm inactivation from the pipe walls as compared to recirculation using distilled water alone. Apart from the flow regimes, various parameters including the volume of PAWB circulated, the concentration of the major plasma reactive species, and treatment time affected the susceptibility of the mixed‐species biofilms to PAWB treatment. Under all tested conditions, the bacterial cells were below the detection limit of 1 log CFU/mL in water after PAWB treatments. A better understanding of the hydrodynamic variations prevalent in the drinking water system is important for designing an effective disinfection protocol using PAWB. The results obtained from the study provide important information on the use of PAWB for biofilm control strategies.
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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) | 0.000 | 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 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".