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One 16 × 16 block is split into two 8 × 16 blocks, and a 16 × 8 block is split into two 8 × 8 blocks.
For a given faulty block, after some nonfaulty nodes have been removed, the block is split into a set of orthogonal convex polygons, each of which is the smallest orthogonal convex polygon that contains all the faults it covers.
In the bottom-up merge method, 16 × 16 block is split into 4 × 4 blocks, and then 4 × 4 blocks with the same class are merged based on MVs and the edge information.
As a result, the synteny block is split into two parts in the feature space, but the two parts are still located in the vicinity.
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Each block was split into un-trenched (Rs) and trenched (Rh) treatments.
This synteny block was split into two smaller ones when OrthoCluster was applied for detecting perfect synteny blocks.
Each block was split into four sessions of 96 trials each, with a break of 5 min between sessions.
If one mitogenome had a gap longer than to 15 bp in a sequence block, this block was split into two blocks at the gap.
Using the break points of all sequences, the block is split up into subblocks, which represent insertions or deletions in one or more of the aligned genomes.
When the lower quartile of edges is removed, the association blocks are splitted into more compact blocks (line segments Q1).
For a dataset with n observations, in the moving block bootstrap with block length l, the data is split into n − l + 1 blocks: block j consists of observations j to j + l − 1, j = 1,..., n − l + 1. [ n/b] blocks are randomly drawn from n − l + 1 blocks with replacement and are aligned in the order they are picked to form a bootstrap sample.
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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