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- W2621283962 abstract "Abstract During the isobaric-isothermal inactivation of the enzyme α-amylase a simple first order inactivation kinetic is observed. However, the pressure and temperature dependence of the inactivation rate constant k [1/min] is more complex. A non synergetic (cumulative) model inspired by the Arrhenius law is proposed. Significant model deficiency is observed at nonintermediate values of pressure and temperature. Due to the lack of sufficient knowledge of the underlying biological mechanisms, a black box modeling approach is made using Artificial Neural Networks . Several network structures are evaluated. The resulting artificial neural network structure relaxes the model deficiency at non-intermediate pressure and temperature values, without increase of the model complexity as compared to the Arrhenius type model. As a result, the model is able to describe the combinatory effect of pressure and temperature on the inactivation rate constant of α-amylase." @default.
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- W2621283962 date "1997-05-01" @default.
- W2621283962 modified "2023-09-26" @default.
- W2621283962 title "Modeling the Kinetics of Isobaric-Isothermal Inactivation of Bacillus Subtilis α-Amylase with Artifical Neural Networks" @default.
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- W2621283962 doi "https://doi.org/10.1016/s1474-6670(17)44429-6" @default.
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