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All literature quoted in the text were converted to the NH3 scale for 15N by adding 380 ppm.
1. Audio-to-audio alignment: Here, the text is converted to speech using a TTS system, and the synthesized speech is aligned with the audio [6, 7].
The encrypted text passes through a communicative channel of two individuals and the second person could decrypt the text by using the key and the text is converted into a context text.
You can see clearly where a new column will begin after the text is converted to table.
The "Errata" included with Tamil lexicon have been applied to the data when this text was converted into a database.
The resulting text was converted to lower case and split on whitespace, leaving only tokens with no whitespace, and no empty tokens.
The remaining text was converted to lower case and split into individual words.
In this case, the context text is converted into the encrypted text.
A closer look shows that the difference is due to conversion issues for the full-text articles (i.e. in article PMID: 9927033, C676T → Arg226Stop in the abstract versus the C676T → Arg226Stop in the HTML version of the full text, which was converted to the non-standard C676T_Arg226Stop during pre-processing) that resulted in EMU missing some mention in the full text.
When reading aloud, the text is necessarily converted into the speed of speech.
The 9 TB of loose text files was converted into a binary format for readability in social science settings.
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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