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Levner says the malaria test used the same underlying technologies they are now redeploying for OLO — including "common sample-preparation methods, microscope design, and artificial-intelligence based algorithms".
The unit root test used the log-transformed of daily returns of all five funds under analysis.
The test used the latest in a series of "modular snake robots" developed at the Pittsburgh-based research centre over the past decade.
A third and final complementation test used the LL3scG2 sub-clone to generate 5 overlapping fragments i.e. LL3scG2a, LL3scG2b, LL3scG2e, LL3scG2g and LL3scG2c for transformation (Figure3e).
Regardless of the size of sample group, the level of study, or the type of language proficiency test used, the results have been mixed and inconclusive.
The fourth learning test used the word presented in phase 3 as the sample (e.g., Mido) and the blank comparison, a familiar figure and an undefined figure as the comparison stimuli.
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In a test, using the scale was a little complicated.
The tests used the Needleman-Wunsch algorithm [3].
While the ECD classifier was derived using cross-normalized dataset as input, the classifiers derived using PAM, EDGE, WT and t-test used the original MAS5-normalized data as input.
Post hoc tests used the Dunnett correction.
Significance tests used the Fisher exact χ.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com