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Agent-based modeling allows us to study the resulting global performance metrics of the simulator kernel.
Multiscale modeling allows us to examine parameter constraints, targets, waveform variations and temporal patterning, trying different ideas before moving to the animal or human platform.
This behavior was described by several ethologists and fuzzy modeling allows us to transform their verbal descriptions into a mathematical model.
In addition, the microfluidic modeling allows us to determine the mass flow rate for different thermal gradient profiles, obtained from the thermal simulations.
This behavior was described by several ethologists and fuzzy modeling allows us to transform their verbal descriptions into a well-defined mathematical model.
This modeling allows us to fit all the data with a model where the fault segments act as a seal whereas the relays between these segments allow for the regional flow from the Peloponnese topographic highs to the coast.
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Additionally, protein modeling allowed us to relate the results of phylogenetic studies with the predicted structures.
This model allows us combining data from different batches using the same microarray platform for analysis.
This model allows us to account autocorrelation within profiles.
A small modification of these models allows us to model a softer informational attitude.
This richer model allows us to formally define a variety of (soft) informational attitudes.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com