Treatment of fracturing wastewater using microalgae‐bacteria consortium
Bibliographic record
Abstract
Abstract The symbiotic relationships between Chlorella vulgaris and Bacillus bacteria in fracturing wastewater treatment were investigated under different conditions, including varying dilution ratios of fracturing wastewater (2‐4), dosages of bacteria (20 mg/L‐80 mg/L), and pH (6.5‐8.5). The effects of process variables on the response of algal density were optimized and investigated via the Box‐Behnken response surface design. The individual and interactive effects of process variables on the response were studied by a second‐order polynomial model and three‐dimensional response surface plots. The optimal treatment conditions were a dilution ratio of 2, bacteria dose of 72.13 mg/L, and pH of 6.5, and the maximum biomass concentration of Chlorella vulgaris was 2.23 g/L. Moreover, Bacillus bacteria can increase the activity of superoxide dismutase (SOD) and acetyl‐CoA carboxylase (ACCase) of Chlorella vulgaris. Compared to the free Chlorella vulgaris, the co‐cultivation of Chlorella and Bacillus bacteria can improve the algal growth and degradation of organic pollutants.
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 | 0.000 | 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".