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Among these models, our interest is focused on the ETU channel model, whose parameters are shown in Table 1.
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Having in mind that we have available a mice experimental model, our interest was focused in the knowledge of the effect produced by the antibiotics more frequently used to treat the respiratory infections on the kinetics of colonization of both microorganisms, either separately or combined.
We refer to these as onset models as our interest is in the effect of lifetime self harm among those not currently exhibiting symptoms of each outcome measure.
We believe as a rule that as long as a simple model satisfies our interest and can reproduce desired behavior, there is no advantage to increasing model complexity.
The model was congruent with our interest in women's intended/actual use of maternity services and the facilitators and barriers impacting their access to care.
Regardless of which model we may fit, our interest is in estimating the effect parameters represented by the various \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\eta $$\end{documentt} parameters above.
Our interest in models based on description logics is justified given recent results on the importance of ontologies in organizing information that can be used in link prediction [2, 4, 30].
We use phenomenological models in this paper as our interest is in the feedback between receptors and an external chemokine field, and not so much in the detailed mechanism of chemotaxis.
Such a result emphasizes our interest in modeling the received signal more accurately.
In the next two sections we introduce the model of coupled cavities of our interest (Section 2) and the quantities we are going to address, namely the energy gaps, and the staggered number-number correlations (Section 3).
As our pathway mapping efforts have continued to develop and been driven by our interest in modeling a diverse range of biological pathways and concepts, we found it necessary to further refine the EPN scheme.
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