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In one model, deactivation of different internal protein motions at high temperatures (near 300 K) is sufficient to predict a dynamical transition near 200 K (Lee and Wand, 2001).
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Changes in the model deactivation kinetics were based on the relative changes in the fast component of deactivation obtained from the experiments.
Modeling the deactivation of heavy oil hydrotreating catalyst was carried out by using a pore plugging model.
A kinetic model for the deactivation of catalyst (based on a HZSM5 zeolite) in the transformation of methanol into gasoline is proposed from results obtained in an isothermal fixed bed integral reactor.
Besides the validated predictions concerning the fast receptor kinetics, the model predicted that deactivation of PP2A located at the IKK following UVB radiation does not occur directly through UVB modifications of PP2A.
Percolation theory is applied to the modeling of the deactivation of ZMS-5 by instantaneous coke formation leading to site coverage and pore blockage.
The validity of a kinetic model for describing the deactivation of a catalyst based on a HZSM5 zeolite has been studied by carrying out reaction in fixed and fluidized bed reactors.
The interpretation of the CDK fingerprint does not produce an interpretation localised to the aziridine moiety, standard + SVM misses the feature, standard + RF finds it in a larger context, extended + SVM again finds it in a larger context and finally the extended + RF model has found a deactivation of the aziridine moiety and moved to a larger context.
For in-silico mutagenesis of EA model, we consider the deactivation of binding sites by setting E, A or both to zero in Eq. (3).
The model considers the rapid deactivation of chemoattractant receptor signaling upon ligand binding and the subsequent receptor recycling, and shows that the preferred cell orientation toward the distant ligand gradient over the local competing ligand gradient is critically enabled by receptor desensitization.
Based on the experimental results, a multi-site kinetic model is developed to predict deactivation of Fe-BEA.
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