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For the cat models, this difference is even larger.
We found that the estimation of O3 across monitoring sites was more accurate with the BME-LUR model compared with other models; this difference was close to 20% in R and around 2 ppb in RMSE.
In murine knockout models, this difference contributes to distinct phenotypes: CTLA-4-deficient mice die within a few weeks from multi-organ immune-related reactions, while PD-1 deficient mice develop organ-specific immune reactions over a course of several months [ 59, 60].
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The difference in the dynamics of the two systems can be attributed solely to the joint; modelling this difference in the dynamics enables us to construct a non-parametric model for the joint dynamics.
On the Unequal Consideration Model, this difference consists in its being the case that the interests of paradigmatic persons matter more, in and of themselves, than the equal interests of merely sentient animals.
Though it seems that there is an increase in BV associated with the use of full MC collimator modelling, this difference is not statistically significant owing to the large variability in the values.
In our model this difference in fetal metabolic state is present at the time that growth is slowed, but prior to reaching a pathological threshold.
According to our model, this difference might largely be dependent on the action of nuclear phosphatases that affects more ERK1 because of its longer retention time in the nucleus.
In our model this difference is due to the fact that, when the frontal bias is ineffective, competition in the parietal module is not biased by novelty and attention is guided purely by the output of competition in the model's ventral stream, which is driven by bottom-up stimulus factors combined with the top-down attention modulation related to the task (search target object).
Furthermore, when the preexisting antibodies against γ-intimin C280 were included in the model, this difference became even more significant.
In the adjusted model, this difference reached a value of 0.2 U/L (CI, -0.4 to -0.02; P = 0.03) (Table 2).
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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