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Record W2135542204 · doi:10.1680/jees.2013.0031

An upflow fixed-bed anaerobic–aerobic reactor for removal of organic matter and nitrogen from L-lysine plant wastewater

2013· article· en· W2135542204 on OpenAlexvenueno aff
Moacir Messias de Araújo, Marcelo Zaiat

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsnot available
Fundersnot available
KeywordsKjeldahl methodWastewaterEffluentNitrogenOrganic matterChemistryHydraulic retention timeAnaerobic exerciseChemical oxygen demandPulp and paper industryEnvironmental engineeringEnvironmental scienceBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

This paper reports on the design of a new reactor configuration—an upflow fixed-bed combined anaerobic – aerobic reactor — can operate as a single treatment unit for the removal of nitrogen (≈150 mg N/L) and organic matter (≈1300 mg COD/L) from Lysine plant wastewater. L-Lysine, an essential amino acid for animal nutrition, is produced by fermentation from natural raw materials of agricultural origin, thus generating wastewater with high contents of organic matter and nitrogen. The best operational condition of the reactor was obtained with a hydraulic retention time of 35 h (21 h in the anaerobic zone and 14 h in the aerobic zone) and a recycling ratio (R) of 3·5. In this condition, the COD, total Kjeldahl nitrogen (TKN), and total nitrogen (TN) removal efficiencies were 97%, 96%, and 77%, respectively, with average effluent concentrations of 10 ± 36 mg COD/L, 2 ± 1 mg NH4+-N/L, 8 ± 3 mg Org-N/L, 1 ± 1 mg NH2−-N/L, and 26 ± 23 mg NH3−-N/L.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.005
GPT teacher head0.171
Teacher spread0.166 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2013
Admission routes1
Has abstractyes

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