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Therefore, our proposed algorithm can be found more applicable for non-stationary signal processing, such as radar chirp signals.
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Having high-level experience in both of those worlds, which of these two templates do you find more applicable, and why?
For the majority of study designs, we found more than one QAT to be applicable.
They have found more.
Interest/knowledge significantly correlated with applicability, r = .338, p < .001, such that people more knowledgeable about and interested in evolutionary theory also found it more applicable to their studies.
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Compared to the steady-state comfort model (i.e., PMV), the adaptive model was found to be more applicable to MM buildings, especially when NV was being utilized.
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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