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Each candidate molecule can then be tested by computing estimated property values and comparing those to prespecified target values.
Once the algorithm has converged, the quality of the solution can be tested by computing an FDTD simulation using the obtained CPML calibration parameters.
For a non-negative stochastic process, almost sure convergence to 0 can be tested by computing the (approximation over finitely many paths, of the) mean of sample paths.
Performance changes in this task that are expected when the sounds have a perceptual effect on how the plws are perceived can be tested by computing whether differences in performance scores between particular conditions turn out to be positive.
The independence of QT interval from previous RR interval can be tested by computing the correlation coefficients.
This hypothesis may be tested by computing the sensitivity (i.e. the probability that spatial neglect occurs as a consequence of damage to the region) and specificity (i.e. the probability that no neglect occurs when the region is spared) of STG and IPL damage as predictors of the occurrence of spatial neglect (Table 2).
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The internal consistency of the survey data are tested by computing Cronbach's alpha.
Regression models are tested by computing various statistics that calculate the difference between the predicted values and the expected values.
B0 dependence was tested by computing the angle θz between the normal of the surface and the direction of B0, then fitting T2* θz) using model from the literature.
Further, the numerical method is tested by computing the spherical Couette flow between two concentric spheres with the inner one rotating.
The method is tested by computing the formation of Taylor vortices in a rotating Couette flow for both axisymmetric and non-axisymmetric configurations.
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