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Finally, we discuss alternating automata in relation to our framework, and provide a determinizing functor.
Finally, we integrate rules with equality and negative constraints to our framework.
A flow's requirements are made visible to our framework by using just 3 bits in the packet header.
According to our framework, firms at each period in time weigh the benefits against the costs of being an RJV member.
Finally, we show how using a particular topology as a seed to our framework significantly reduces the time to compute the final topology.
Finally, we explore the effects of DNase I sequence bias on inference of factor binding using a simple extension to our framework that allows for a more flexible background model.
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It would, however, be interesting to modify our framework to consider mosquito populations that are transient due to micro-environment variability.
Finally, we discuss what is needed to apply our framework to other species.
We proceed to apply our framework to develop and analyze KroMagnon: a novel, parallel, sparse stochastic variance-reduced gradient (SVRG) algorithm.
In this case, we have to extend our framework to non-numerical values, mostly string values.
As such, we plan to extend our framework to include more complex patterns together with temporal units and their conversion.
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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