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In addition to scaling the output, we also used a step filter on the data to make the mouse easier to use.
Users may activate or deactivate this step, filter getter and setter methods, set the Levenshtein value, and perform manual control for annotated concerns identified with our clustering algorithm.
Therefore, in a first step, filter pots were produced from local clay, mixed with sawdust or rice husks as pore-forming material to assess the suitability of the material.
The sample was then filtered through a Thomson Single StEP Filter vial 0.45 μm PVDF Thomson Instrument Companyy, Oceanside, CA, USA) and analysed via RP-HPLC on a Discovery BioWide Pore C18 (15 cm × 2.1 mm; 3 μm) column.
We further adjusted the threshold of the second step filter to limit dye-swap artifacts.
The next step (filter 1), filtering out reads with more than ten best matches in the genome, is just described in plain text, presumably because no special software is necessary to perform the filtering.
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The second step filters this representation to produce a compact user-based representation that discriminates the specific user from the population.
A two step filtering method and a dynamic data storing and managing method are proposed.
Especially a two step filtering method and a dynamic data storing and managing method are proposed.
This step filters out all but 443 of the 10,369 unique sequences we started with.
To address this concern, we employed a two step filtering procedure.
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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