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Another successful example was introduced by Izadi et al. [30] to fuse a sequence of depth maps generated by a kinect camera.
In consequence, the depth maps are not processed frame-by-frame, but instead we download from a circular buffer a sequence of depth maps acquired prior to the fall and then process them to authenticate fall event.
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"This data is used to create a sequence of 2D images and depth maps, which are digitally signed and sent to the Secure Enclave," the white paper continues.
In this study, SLAFs with a sequence depth of less than 148 were defined as low-depth SLAFs.
In our present study, SLAFs with a sequence depth of less than 10 were defined as low-depth SLAFs and filtered out in the following analysis.
In this study, SLAFs with a sequence depth of less than 100 were defined as low-depth SLAFs and were filtered out.
We aimed for a genome coverage of around 2% and a sequence depth of 25x.
Initially we isolated fragments in the size range from 150-250 BL (BL and WL), which resulted in genome coverage of around 1.4% and a sequence depth of 45x.
This is of note because in most publications currently a sequence depth of 20 million reads is standard for RNA deep sequencing [ 34, 35].
For example, 85,879 sequence reads for sample JPN33 that was imbalanced at DRB1*04:06:01 was assigned with a sequence depth of 58.9.
For a trait with a heritability of 0.94, we expect a sequencing depth of 500× to detect a QTL of at least 5% effect ~70% of the time.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com