Suggestions(1)
Exact(2)
As for protest frames, we found the same causal paths as in the previous analysis, but the raw coverage became 0.397.
After trying with different kinds of sequences, and for each sequence a different number of frames, we found that sequences which contain varying regions from homogenous to high-detail serve as good training sets.
Similar(58)
Thus, instead of searching all 9,000 frames, we find the most similar frame by looking at around 500 frames.
In subsequent frames, we find the C frame also have the same feature with A frame and B frame, but the feature point is in Y axis, distance is 5 pixels and 5 pixels in X axis.
Within a 6-hour time frame, we found that both negative and positive charged NPs expressed nearly the same amount of LC3-II.
In this time frame, we found more efficient uptake of HS-induced apoptotic leukemic cells by R848-treated MoDC as compared to control and CC-treated MoDC.
Second, we used ROC analyses to examine the degree to which the speaking character location was predicted by movement within the frame; we found that this was higher in TotTV than ATV.
Despite this narrow time frame, we found strong and consistent association between increasing time and higher ratings on all components of ethical practice we studied, especially respect for integrity.
Using the AKI classification with a seven-day instead of a 48-hour time frame, we found a higher incidence of AKI (39.5% instead of 34.4%; AKI I 19.3%, AKI II 6.7% and AKI III 13.5%).
Despite this narrow time frame, we found strong and consistent association between increasing time and higher ratings on all components of ethical practice: information, (β =.43), understanding (β =.52), respect for integrity (β =.60), and decision making (β =.43).
We are learning new modes of attention — say, favoring the ear more than the eye — but so long as we work within the old attention-frame we find X boring... e.g. listening for sense rather than sound (being too message-oriented).
Write better and faster with AI suggestions while staying true to your unique style.
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