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Computing statistical quantities of interest of the solution of PDE on random domains is an important and challenging task in engineering.
We propose a fully Bayesian approach that allows for global recovery of the stochastic solutions, in both spatial and random domains, by coupling Bayesian model uncertainty and regularization regression methods.
In such cases, this topological uncertainty can be efficiently handled by treating rough boundaries as random fields, so that an underlying physical phenomenon is described by deterministic or stochastic differential equations in random domains.
N was set as 4 in human, and 3 in mouse to ensure that random domains were less than 15%.
Comparing to a set of random domains also helps to verify that our observations are due to the observed sequence of domains and not the distribution of domain lengths.
One way to test this is to scramble the data so that networks are given random domains (but leaving the relative numbers the same. that is 32 bacterial networks, six arch, and five eukaryotic networks).
Similar(54)
Although SFE is one of the most widely accepted approaches, its integrations into general-purpose finite element software are rare in literatures due to difficulties in its intrusive formulation and managing two different meshes for discretizing the physical and random field domains subjected to different meshing criteria.
Methods for creating random domain insertion libraries are described.
Now, however, the new botnet uses seemingly random domain names for command and control.
Here, we report the facile construction of random domain insertion libraries using an engineered transposon.
The basic idea of the proposed methodology is to adaptively decompose the random domain into subdomains.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com