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More precisely, assume that for every bounded subset of a given metric space.
More precisely, assume that F and G have the same number of functions, and let π F and π G be the respective coordinate maps.
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More precisely, assuming that the average sequence length is L and the motif length is l, the probability that a randomly selected sequence is a binding site is 1/(L - l + 1).
Precisely, assuming DnaA-ADP is not limiting, this would change the model by the substitution of k R with k R - ρ Λ ∕ F where ρ is a fixed recycling rate.
More precisely, assuming that the neuron indices are sorted by increasing BF, and the bands are of equal size consisting of B neurons each (i.e., the first band is neurons 0 to B − 1, the second from B to 2B − 1, etc.; we used B = 40), we compute the dot product ψ j = (r | r | ).
More precisely, we assume that the pair (A,B) is exactly observable for the continuous model, and we derive uniform observability inequalities for suitable time-discretization schemes within the class of conveniently filtered initial data.
More precisely, we assume that during each step in the execution of the system, each message may be lost with a certain predefined probability.
More precisely, we assume that successive frames "generated" by a certain state are independent, moreover, that frames generated in one state are independent of those generated by a different state.
More precisely, we assume that the parameters are estimated by exponential smoothing, where past parameters are down-weighted and the weight of recent observations does not decrease with time.
More precisely, we assume that we know.
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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