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The clipped image was rotated so that the longitudinal axis was in a horizontal direction (Supplementary Fig. 2B).
In the case of Experiment 3, the whole image was rotated 180°, but this was done before the addition of the black cue bracket.
To assess the position of univalents relative to the bivalents, each 3D image was rotated in 'Surpass' view to allow for a view showing aligned bivalents (using midbivalent ring location as a guide).
It was assumed that the ground truths of rotational differences between images were acquired by computer generation, so the first image was rotated by a fixed degree using the bicubic interpolation to generate the third image.
To verify the rotation invariance, a binary image was rotated clockwise to various degrees from the original degree (from 10° to 90°).
A contaminant-free method, rolling by a soft-rubber roller was used for post treatment, and then the Ni film emitter (the image was rotated 180°) with free standing CNTs on its surface was achieved. .
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Then the image is rotated about that point by the specified amount and scaled.
The image is rotated vertically and horizontally followed by a shuffle using 3D Cat map and Standard map.
As an example, one such competition will be: implement a rotation algorithm (that runs within a time limit), such that when an image is rotated by 1 degree 360 times, it's as close as possible to the original.
Each image is rotated until the line joining the centers of eyes becomes horizontal.
Figure 4 b depicts the variation in the embedded information, when the image is rotated by 50°.
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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