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Our modeling assumed a single influenza case in the bedroom and evaluated the levels of the virus in the bedroom and outside the bedroom.
The modeling assumed a linear dose response and used the health outcome associated with the RfD or RfC (e.g., liver toxicity, renal toxicity).
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Curves were modelled assuming a simple 1 1 interaction to generate the kinetic data.
Rates across sites were modeled assuming a discrete gamma distribution with four categories.
rs1495741 was modeled assuming an additive model.
However, ODE modeling assumes a 'mixed-bag' environment, and cannot account for non-homogenous distributions of model components.
But a freemium model assumed a single-sided market – one where the users became the payers.
All these models assumed a vertical B0.
Further models assumed a clumpy distribution of the torus (Nenkova et al., 2002, 2008).
To reduce complexity, our model assumed a fixed vaccination schedule over a 100 year period.
For simplicity, the model assumed a sample area that was featureless, flat and 1 m deep.
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CEO of Professional Science Editing for Scientists @ prosciediting.com