The results surprisingly show that charge distribution based model was able to predict the selectivity coefficients of MIP based potentiometric sensors.
However, the prediction accuracy on independent dataset; representing a true unknown prediction showed that PSSM based model was able to predict 53 out of 54 sequences (as compared to 50 by hybrid-6 and HMM profiles of Pfam database).
For the first time, a parameter-free physics-based model is able to predict the yield stress in superalloys with complex microstructures, including unimodal and multimodal γ′ size.
This data-based model is able to reproduce the nonlinear dynamic behavior of a complex office building split into different zones.
Our sigmoid-based model is able to reproduce: (i) oil remobilization induced by gas injection in water-wet media; (ii) a smooth transition towards the layer-drainage regime for low oil saturations; and (iii) the consequent reduction of residual oil saturation in a three-phase system.
In contrast to the other refining strategies, the turbulence-based model is able to describe the meteorological and climatological conditions in a more plausible way without adding arbitrary noise terms to the variances of the observations in any form.
The theory-based model is able to extrapolate to new words while it simultaneously generalizes across participants, demonstrating the generativity of the theory.
Once quasi-steady state has been reached, we find a good agreement in terms of the chemical-compound concentrations between the two approaches inside the reactive zones, whereas the exposure-time based model is not able to capture reactions occurring in the zones with zero electron-donor release.
The CFD based empirical model is able to predict corrosion rate of pipelines, with the modeling results validated by actual measurements.
The present mean field based micromechanics model is able to account for the morphological and topological textures of the multiferroics heterogeneities.
