Treatment of wastewater using a combined biological and electrochemical technique
Bibliographic record
Abstract
Abstract Simulated wastewater containing propylene glycol methyl ether, Ni2+ and Zn2+ was treated using an aerated packed column. An electrochemical cell was also installed beneath the packing support in the bottom section of the column. The flowrate of water through the column was maintained at 8.94 kg m−2 s−1. For 72 h of treatment using aeration alone, the BOD5 was reduced by 43%, 56%, and 54% for air flowrates of 0.00094, 0.00141, and 0.00188 kg m−2 s−1 respectively. On the other hand, when the electrochemical cell was activated without aeration, the BOD5 was reduced by 15%, 17%, and 23% at the applied voltages of 8, 16, and 25 V respectively. When both aeration of the wastewater and a voltage of 25 V were used, the percentage removal of BOD5, on the average, was about 65% for all air flowrates used. The concentrations of Ni2+ and Zn2+ were also reduced by 57% and 61% respectively, in the absence of the supporting electrolyte. The addition of potassium chloride (100 ppm) as the supporting electrolyte enhanced the metal removal by 30%. Copyright © 2003 Society of Chemical Industry
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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".