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In this spike neural network, we are taking into account two relevant ideas the use of Spike neural network which is the best model for oculo-motor control and the role of geometric computing.
Long-term video-EEG monitoring for epilepsy provide a technical basis for monitoring over many days and the use of spike and seizure detectors.
This model will, for the first time, allow engineers to specify, with confidence, the use of spike anchors as a method to anchor FRP sheets and plates to structural concrete members.
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The use of spikes in the design of hypersonic vehicles yields a considerable reduction in drag and aerodynamic heating.
More empirical alternatives include the use of spike-in data and re-sampling.
More empirical alternatives include the use of re-sampling methods (to compare genes from small subsets of samples and those from the full dataset) [3], [19], and the use of spike-in data for which a set of genes are differentially expressed by design [12], [20].
We describe the use of spike-in external control to normalize a low-density microarray.
However, the recommended use of spike-in RNA might not always be feasible.
The aim of the work is to study the use of spike-in controls to normalize low-density microarrays.
We showed that the use of spike-in-based normalization produced consistent results with qPCR validations, and provided us with deeper insights into KC biology.
Normalization using a reference gene was not possible, due to the varying abundance of degradation intermediates, and fractionation into the poly(A)+ and poly(A)− RNA impeded the use of spike-ins for this purpose.
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