Removal of odorous sulphur-containing gases by a new isolate from activated sludge
Bibliographic record
Abstract
Biological treatment of odorous sulphur-containing compounds is attracting attention due to its benign eco-friendliness, energy-savings and low operating costs. As the biological treatment efficiency of dimethylsulphide (DMS) reported was often low and variable, selection of useful DMS-degrading microorganisms is of importance for the enhancement of the biological deodorizing process. This paper reports the successful isolation of a DMS-degrading bacterium from activated sludge, using the enrichment isolation technique. The isolate was identified by 16S rRNA gene sequencing, and found to belong to the alpha group of Proteobacteria, with an identity of 99.4% and 99.1% to the 16S rRNA gene sequences of Afipia felis and Pseudomonas carboxydohydrogena, respectively. The isolate was able to metabolize DMS as well as hydrogen sulphide (H2S). A batch experiment was performed to assess the removal characteristics of DMS by the isolate. The results showed that over half of DMS could be removed by the isolate in 3 hours when the initial DMS amount was approximately 10 micromol and 25 micromol. Removal of H2S by the isolate was evaluated by a continuous test in a 2-L gas-bubbling bottle. Although part of the H2S removal by the mineral medium itself was observed in the control test, the majority of H2S removal was believed to be attributed to the metabolic activity of the isolate. In conclusion, the isolate might be potentially useful for the enhancement of the biological deodorizing processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".