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"Determinants of synaptic integration and heterogeneity in rebound firing explored with data driven models of deep cerebellar nucleus cells". Journal of Computational Neuroscience 30: 630-658.).
The application of global sensitivity and uncertainty analysis techniques to groundwater models of deep sedimentary basins are typically challenged by large computational burdens combined with associated numerical stability issues.
Models of deep brain stimulation and spinal cord stimulation have advanced over recent decades from simple, stereotyped models to sophisticated patient-specific models that can incorporate many important details of the stimulation system and the attributes of individual subjects.
Compared with the several other models of deep learning, the recurrent neural network has been widely applied in NLP but RNN is seldom used in text feature extraction, and the basic reason is that RNN mainly targets data with time sequence.
The role of NETs was further examined using experimental models of deep vein thrombosis [ 39].
Experimental models of deep hypothermia and rewarming confirm and explain these clinical findings [ 15, 16].
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Modifications: Make models of deep-sea trenches and submarine canyons.
Constructing geologically accurate reservoir models of deep-water strata is challenging due to the reliance on incomplete or limited resolution datasets.
In addition, the reference conditions for superficial gas velocity are important in modeling of deep gas solids systems where there is a considerable pressure drop.
However, the functioning and numerical modeling of deep borehole heat exchangers (DBHE), in contrast to those of shallow conventional systems, remain poorly known.
We offer a model of deep inclusion that was developed by applying concepts from work on deliberative democracy and development ethics.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com