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Record W2155787535 · doi:10.1002/jctb.4740

Parametric sensitivity of <scp>pH</scp> and steady state multiplicity in a continuous stirred tank bioreactor (<scp>CSTBR</scp>) using a lactic acid bacterium (<scp>LAB</scp>), <i>Pediococcus acidilactici</i>

2015· article· en· W2155787535 on OpenAlexaff
Subhashis Das, Aritro Banerjee, Ranjana Chowdhury, Pinaki Bhattacharya, Rajnish Kaur Calay

Bibliographic record

VenueJournal of Chemical Technology & Biotechnology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsHeritage College
Fundersnot available
KeywordsBioreactorParametric statisticsPediococcus acidilacticiSensitivity (control systems)Continuous stirred-tank reactorSteady state (chemistry)DilutionNonlinear systemLactic acidControl theory (sociology)ChemistryBiological systemMathematicsComputer sciencePhysicsThermodynamicsEngineeringChemical engineeringBacteriaControl (management)BiologyStatistics

Abstract

fetched live from OpenAlex

Abstract BACKGROUND A continuous stirred tank bioreactor ( CSTBR ) represents an open dynamic system with high probability to show nonlinear behavior such as parametric sensitivity and multiplicity of steady state. A priori determination of this behavior is needed to decide on the strategy of reactor operation. RESULTS The growth of a lactic acid bacterium, namely, Pediococcus acidilactici in a 2 L CSTBR is used to demonstrate the existence of parametric sensitivity of pH and the multiplicity of steady state in the system. A mathematical model has been developed and a dimensionless multiplicity criterion, ω, has been derived to indicate the set of values of input parameters corresponding to multiple steady states. Experiments have been conducted to study parametric sensitivity of pH with respect to input variables, namely, dilution rates and concentrations of nutrient and alkali stream for pH control in the regions of multiple and unique steady states. The CSTBR exhibited parametric sensitivity of pH over the entire region of operation under study. The experimental trends of parametric sensitivity of pH are also in agreement with those of theoretical parametric sensitivity of pH . CONCLUSION The nonlinear behavior of a CSTBR has been thoroughly portrayed in this article. The present study will add to the knowledge of control and operational strategies of CSTBRs . © 2015 Society of Chemical Industry

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)0.001
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
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 score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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.

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

Citations3
Published2015
Admission routes1
Has abstractyes

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