The use of used automobile tyres in a partitioning bioreactor for the biodegradation of xenobiotic mixtures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Waste tyres were utilized as the sorption phase in a two-phase partitioning bioreactor (TPPB) for the biodegradation of a binary mixture of 2,4-dichlorophenol (DCP) and 4-nitrophenol (4NP). These compounds are extensively used in the chemical industry and are found in many industrial effluents. Although both compounds are toxic and are on the EPA list of priority pollutants, a higher inhibitory effect on microorganisms is exerted by DCP, and our experimental tests were focused on strategies to reduce its negative impact on microbial activity. Sorption/desorption tests for the DCP-4NP mixture were first performed to verify the related uptake/release rates by the tyres, which showed that the tyres had a higher capacity for DCP uptake and practically no affinity for 4NP. An acclimatized mixed culture was then utilized in a sequencing batch reactor (SBR) operated in conventional and two-phase mode. For the binary DCP-4NP mixture a significant reduction in DCP toxicity, and a concomitant enhancement in substrate removal efficiency (up to 83%for DCP and approximate 100% for 4NP) were clearly seen for the TPPB operated with 10% and 15% v/v tyres, for influent concentrations up to 180 mg/L, with practically negligible biodegradation in the conventional single phase reactor. The long-term utilization of tyres was confirmed at an influent loading of 180 mg/L with a test performed over 20 work cycles showing an improvement of the removal performance for both compounds.
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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 | 0.000 | 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 | 0.001 |
| 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 it