Starvation resilience in anammox-based bioreactors: A stable nitrogen removal route on partial denitrification/anammox (PD/A)
Bibliographic record
Abstract
This study investigates the performance, resilience and microbial community dynamics of two anaerobic processes, i.e. pure anammox (R1) and partial denitrification/anammox (PD/A) (R2), following a 30-day starvation period. The tolerance to starvation was assessed by comparing nitrogen removal efficiency and microbial activity across both reactors. Results show that the PD/A process recovery to pre-starvation performance levels within just one day, as compared to the pure anammox process. Notably, although the activity of anammox bacteria decreased in both processes during starvation, the decay rate in R1 was 69.59 % higher than in R2, potentially explaining the quicker recovery of R2. Furthermore, enhanced secretion of extracellular polymeric substance (EPS) during starvation served as a protective mechanism. The potential functions and genes in microorganisms, as well as the pathway of nitrogen cycling, were demonstrated through analyses using the KEGG database. This research reveals essential mechanistic insights and strategic guidance for the effective implementation of anammox-based biological nitrogen removal 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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".