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Both endpoints have been developed largely to evaluate outcomes in unselected populations in which a fraction of patients are anticipated to derive significant benefit.
This table suggested that the overlap rates of endpoint E are always greater than those of endpoint D. For normal models, the number of features for both endpoints have no significant difference (F = 0.9507, T-test = 0.5748) and there is either no significant difference for that of swap models (F = 0.1236, T-test = 1.2238, degree of freedom = 23.6263).
Plus, if both endpoints of an inversion are still intact in a genome, the inversion is scored twice, if only a single endpoint remains the inversion is counted only once, and if both endpoints have been lost (through further mutation) the inversion will not be included at all.
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Both SCTP endpoints have two asymmetric paths (denoted path 1 and path 2) with different networking parameters.
Since then, both the western and eastern endpoints have shifted slightly, but the route otherwise remains the same.
Recently, both clinical and immunological endpoints have shown improvement.
Such endpoints have been successfully used in cancer trials in the past.
The data from the different endpoints have been subjected to a statistical analysis, and a preliminary prediction model is proposed.
In gammarids, these endpoints have been proven sensitive endocrine modulated reactions [40].
The observations between the endpoints have higher energy than those around the endpoints, and they have different spacial distributions with those around the endpoints too.
In particular, the cities running the endpoints have committed to continue to do so in the future.
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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