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Computational quantification in intact animals requires object recognition solutions in 3D, which can be achieved with confocal microscopy.
For the computational quantification, the program Xcalibur 2.1 (2.1.0 SP1.1160, Thermo Scientific, Dreieich, Germany) was employed.
When designing therapeutic short-interfering RNAs (siRNAs), off-target effects (OTEs) are usually predicted by computational quantification of messenger RNAs (mRNAs) that contain matches to the siRNA seed sequence in their 3′ UTRs.
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Computational quantifications of uncertainties are carried out by using numerical simulations of homogeneous ignition subject to Monte-Carlo sampling of the concentration of impurities.
Even histopathological and radiological images which are traditionally evaluated and scored by trained experts are now subjected to computational quantifications (i.e. imaging informatics) [ 10– 12, 33].
The positions of the text overlay were determined by varying the balance and symmetry in order to validate computational aesthetic quantification algorithms with subjective ratings.
In the first experiment, 30 black and white geometric images were developed by systematically varying these three attributes in order to validate computational aesthetic quantification algorithms with subject ratings.
Irrespective of what choice of method that is preferred, there is a definite need for better computational methods for quantification of interactions.
Results comparison included computational and user time, quantification of the deteriorated area error between manual and automatically detected zones.
The result showed that the gPC method reduces computational effort for uncertainty quantification of complex chemical processes with an acceptable accuracy.
Increasingly the spectral stochastic finite element method (SSFEM) has become a popular computational tool for uncertainty quantification in numerous practical engineering problems.
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