Growth kinetics of lead resistant <i>Bacillus infantis</i> isolated from battery industry waste
Bibliographic record
Abstract
The current investigation presents an innovative approach to address the challenge of removing heavy metal lead from industrial waste through advanced biological remediation techniques. By amalgamating theoretical insights with empirically acquired data, this research endeavours to develop efficient bioreactor strategies suitable for large-scale applications. Initially, bacteria naturally endowed with lead resistance has been isolated from a native source. Extensive microbiological assessments, including a 16S rDNA study, verified the identity of the lead-resistant bacterial cells as Bacillus infantis 4352-1T. In order to evaluate the efficacy of Bacillus infantis 4352-1T for lead removal an attempt has been made to study the growth dynamics of Bacillus infantis 4352-1T cells in batch mode, using lead amended selective media. It has been observed that Monod's equation effectively defined the cell growth behaviour within the lead concentration range of 0.05–0.25 kg lead/m 3 . Notably, the experiment was also facilitated the derivation of essential intrinsic kinetic parameters, such as the maximum specific cell growth rate (0.0237 h −1 ) and substrate saturation constant (0.018 kg/m 3 ). Beyond lead concentrations of 0.25 kg lead/m 3 , up to 0.43 kg lead/m 3 , it has also been observed the pronounced influence of substrate inhibition which is quantitatively elucidated by the Haldane equation.
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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 | 0.000 |
| 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 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".