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It is expected that this behaviour occurs wherever solids inertia is important, such as with strong large aggregate formation (the example studied here was wood pulp) or with high solids loading (milled coal suspension).
The example studied here is the optimal temperature control of a stirred-tank catalytic reactor in which the time constant of the catalyst decay is appreciable compared to the mean residence time.
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An important property of the adversarial examples studied here is that they were originally created without the human visual system in mind.
As discussed above, the three examples studied here show no significant difference between the GCI model and a model in which pair-wise dependencies among the SNPs are included through logistic regression.
In each of these potentially limiting examples, a new corpus would have to be characteristically different from the testing and training examples studied here.
The examples studied here underline the fact that there does seem to be a common pattern of CO2 emissions development during industrialisation.
This crude approximation, inspired in part by the "sloppiness" property of biological systems, worked surprisingly well for the examples studied here.
In contrast the results from the EMRE/IOS methods agree well with those obtained from the SSA for the examples studied here.
The examples studied here display large uncertainties associated with small (<60 measurements) datasets, while uncertainty varies little with datasets of larger than 60 measurements.
In the specific examples studied here, the different rpoS, hfq, and spoT mutations may have similar benefits under Pi-limitation but very different fitness profiles in other environments.
The same procedure is used for the examples studied here but the linear framework can accommodate the irreversible dynamics of mRNA polymerase (initiation, open complex formation, promoter escape, elongation, pausing, etc).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com