Sentence examples for improved translation from inspiring English sources

Attempts at enhancing the IMT translation efficiency through the modification of its translational context [ 36, 37] resulted in somewhat improved translation levels at 20 DAP under the phaseolin promoter when a dA nucleotide was positioned at the -3 position and a dC nucleotide at each of positions -2 and -1 of the initiation codon (transgenic line Ph3-19, Table  1 and Figure  4A).

Thomas Prince's own "Revised and Improved" translation was published in 1758, in time for one of his psalms to be read over his grave.

Although improved translation software and a growing zeal for grammatically unassailable English has slowed the output of new Chinglishisms, Mr. Mair said he still received about five new examples a day from people who knew he was good at deciphering what went wrong.

And improved translation equations can make the simplified model more accurate under low irradiance levels.

The results of experiment 1 found that adding synapomorphies dramatically improved translation accuracy for students with both stronger and weaker biology backgrounds, and similarly so for both: Δ = 0.17 for stronger background, Δ = 0.19 for weaker background.

In 2010, wrote Mr Rashid, Microsoft researchers working with scientists at the University of Toronto improved translation further using deep neural networks that learn to recognise sound in much the same way as brains do.

This system takes advantage of deep neural networks to translate entire sentences — not just phrases — for greatly improved translations.

Last fall, Google introduced a new system for machine-assisted language translations, Google Neural Machine Translation system (GNMT), which takes advantage of deep neural networks to translate entire sentences – not just phrases – for greatly improved translations.

Alternatively, it has been also suggested to use translational enhancers to improve translation efficiency of the parthenocarpic gene of interest [ 20].

Part of the initial motivation for developing "thought vectors" was to improve translation software, such as Google Translate, which currently uses dictionaries to translate individual words and searches through previously translated documents to find typical translations for phrases.

In particular, it highlighted two translational 'gaps': the need to improve translation from the laboratory to the creation of new products and treatments; and then the need for translation of those new products and approaches into routine clinical practice [ 58].