Bibliographic record
Abstract
Laccase, as a developmental preparation from an industrial enzyme producer, catalyzes the oxidation of selected aromatic compounds. The polymers formed from the reaction are insoluble and are readily removed from solution. Experiments were conducted to evaluate the potential use of laccase in an alternative enzyme-based technology to remove cresols from synthetic wastewater. Reaction parameters were optimized in unbuffered tap water for the removal of o-, m-, and p-cresols. The effects of pH, enzyme dose, PEG addition, dissolved oxygen availability, and hydrogen peroxide addition were investigated. All tests were conducted in continuously stirred batch reactors. Nearly 90% of o-cresol was removed at optimum conditions of pH and enzyme dose, while p- and m-cresols' removals were 80% and 70%, respectively. The optimum pH for the cresols ranged from 5.6 to 7.0. For each substrate, the optimum enzyme dose varied from 0.3 standardized units of catalytic activity for p-cresol to 0.6 standardized units of catalytic activity for m-cresol. Aeration, at higher concentrations of substrate, increased the initial rate of reaction for substrate removal and improved the efficiency of the reaction. The addition of PEG or hydrogen peroxide did not have significant effects on substrate removal. The results from this study have demonstrated the applicability of laccase for the reduction of cresols from wastewater. This study provides a basis for further investigation's into similar enzymatic treatment.Dept. of Civil and Environmental Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2000 .V37. Source: Masters Abstracts International, Volume: 39-02, page: 0556. Advisers: J. K. Bewtra; K. E. Taylor. Thesis (M.A.Sc.)--University of Windsor (Canada), 2000.
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How this classification was reachedexpand
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".