Kinetics of hydrogen‐dependent denitrification under varying pH and temperature conditions
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
It is important to determine the effect of changing environmental conditions on the microbial kinetics for design and modeling of biological treatment processes. In this research, the kinetics of nitrate and nitrite reduction by autotrophic hydrogen-dependent denitrifying bacteria and the possible role of acetogens were studied in two sequencing batch reactors (SBR) under varying pH and temperature conditions. A zero order kinetic model was proposed for nitrate and nitrite reduction and kinetic coefficients were obtained at two temperatures (25 +/- 1 and 12 +/- 1 degrees C), and pH ranging from 7 to 9.5. Nitrate and nitrite reduction was inhibited at pH of 7 at both temperatures of 12 +/- 1 and 25 +/- 1 degrees C. The optimum pH conditions for nitrate and nitrite reduction were 9.5 at 25 +/- 1 degrees C and 8.5 at 12 +/- 1 degrees C. Nitrate and nitrite reduction rates were compared, when they were used separately as the sole electron acceptor. It was shown that nitrite reduction rates consistently exceeded nitrate reduction rates, regardless of temperature and pH. The observed transitional accumulation of nitrite, when nitrate was used as an electron acceptor, indicated that nitrite reduction was slowed down by the presence of nitrate. No activity of acetogenic bacteria was observed in the hydrogenotrophic biomass and no residual acetate was detected, verifying that the kinetic parameters obtained were not influenced by heterotrophic denitrification and accurately represented autotrophic activity.
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.
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 | 0.000 |
| 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 it