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Very flexible classes of models result.
These two models result in different habitat configurations.
Too often approximate, less than optimal models result.
Consequently, optimization efforts basing on these impractical models result in inefficient solutions.
Erdős-Rényi and Watts-Strogatz models result in networks with almost homogeneous degree distribution.
NeuCube models result in a better accuracy of STBD classification than standard machine learning techniques.
With regard to behaviour prediction, the most frequently used uniaxial constitutive models result in similar responses.
Assembled component models result in a 12% error norm at the system level.
Subjective models result in a confidence indicator for the solutions' feasibility.
The simplest cyclotron sweep models result in convection-dominated transport, contradicting observations.
Both models result in local endothelial cell damage leading to the exposure of subendothelial matrix components (tissue factor; P-selectin).
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