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In this paper, we propose a three-dimensional matrix named the letter interaction pattern matrix (LIPM) to characterize the information contained in the defining contrast subgroup of a regular two-level design.
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Since the main focus of Schurz et al. [39] was on the brain reflection of a length by lexicality (familiar vs. unfamiliar letter strings) interaction, pseudohomophones were deleted and this was also done in the present study.
Post-hoc analyses (Tukey; p<.05) revealed a significant decrease for HGF mode; Arabic Letter 2: The interaction between training session and period factors was significant (F 2,44) = 13.135 p<.05) Post-hoc analyses (Tukey test; p<.05) revealed a significant increase for HGF; Japanese-inspired Letter 3: The interaction between training mode and test was significant (F 2,44) = 11.559 p<.05).
Post-hoc analyses (Tukey test; p<.05) revealed a significant increase for HGF mode and no significant differences for NHG and HGP modes; Japanese-inspired Letter 4: The interaction between training mode and test was significant (F 2,44) = 7.744 p<.05).
Post-hoc analyses (Tukey test; p<.05) revealed a significant decrease for HGF (Pre-test: m = 9.42; post-test m = 7.06) mode and no significant difference for NHG and HGP modes; Japanese-inspired Letter 4: The interaction between training mode and test was significant (F 2,44) = 3.79; p<.05).
There's no easy way for a nontechnical mind like me to connect all these random APIs between disparate services, so IFTTT makes it both easy and, strangely, fun and addictive with its big bold letters and slick interaction.
And we want everything to be capable of animation and interaction — every letter, every tag, every structural element.
Also significant was the interaction of letter targetness × lexical category (F[1,12] = 9.30; p < 0.02).
ANOVA also revealed an interaction between letter targetness and hemisphere (F[1,12] = 4.80; p < 0.049), showing a significant target/non-target difference in the response recorded over the left but not the right hemisphere.
Lastly, the interaction of Letter targetness × Orientation (F[1,12] = 5, p < 0.04) and relative post-hoc comparisons evidenced a significant target effect for standard (target = 1.84; non-target = 1.3 μV) but not rotated (target = 1.3; non-target = 1.46 μV) strings.
The further interaction of letter targetness × electrode × hemisphere (F[2,24] = 4.57; p < 0.02) revealed a strong hemispheric asymmetry for target-related negativity at each electrode site, but especially the lateral occipital ones, as confirmed by post-hoc comparisons.
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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