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The hybrid kinetic mechanism reduction scheme is a promising approach to address combustion problems in complex reactive flow environment, especially for enabling the computational simulations of transport-intensive applications.
Here, we employ a new approach that uses an unbiased decomposition of total network activity under diverse task conditions, enabling the computational extraction of latent structure in functional network interactions and post-hoc examination of its dynamic evolution during behavior".
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Atomate also enables the computational characterization of materials by providing workflows that calculate X-ray absorption (XAS), Electron energy loss (EELS) and Raman spectra.
Our topological approach could therefore enable the computational design of tough inorganic solids, which has long been a "holy grail" within the non-metallic materials chemistry community.
The diversity of the command line programs enables the computational chemists to customize the data processing workflows, and thus to provide Vortex spreadsheets that enable analysis from different perspectives.
These advanced kinematics enable the computational costs to be reduced while the accuracy of the classical layer-wise theories in which the number of physical and numerical layers coincide, is maintained.
Here, we use some of the TOMOCOMD-CARDD molecular descriptors and linear discriminant analysis (LDA) to derive individual linear classification functions in order to discriminate between antiprotozoan and non-antiprotozoan compounds as a way to enable the computational screening of virtual combinatorial datasets and/or drugs already approved.
Qualitative (ie, parameter-free) models enable the computational representation and analysis of even large-scale signaling networks.
Such models enable the computational analysis and contextualization of experimental data, for instance, for the quantification of network perturbation, which is further described in this perspective.
However, the grouping of reactions offers insights which enable the computational cost to be reduced significantly by generating additional solutions without solving the MILP, using group substitutability analysis (Step 3).
The approach combines broadband neural recording of brain activity at high spatial and temporal resolution with big data analytical techniques to enable the computational extraction of latent structure in functional network dynamics.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com