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Step 3. Local heat energy diffusion (Section 4.3).
In this paper, it is shown how this neural model can be applied to three common tasks in control engineering: modelling of a diffusion section in a sugar industry, prediction in a wastewater plant, and neural model-based predictive control in a sugar factory.
The device consists of the driving section including a typical electron cyclotron resonance (ECR) plasma source operating at 2.45 GHz wave frequency and the diffusion section where a cylindrical chamber is surrounded by a pair of solenoid coils for generating various curved magnetic field structures.
Step 3. Local heat energy diffusion (Section 4.3) For each image I k, the object likelihoods of the heat sources L k ∗, 2 ( Z k ) are diffused to other superpixels U k = S k -Z k via random walks [15], obtaining L k ∗, 2 ( U k ).
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A parametrized diffusion cross section library was prepared for the HPLWR assembly with the MULTICELL neutronic transport code.
In this paper, under the assumption of the uniqueness of the solution to the singular diffusion (1.1), Section 2 discusses the regular properties of the solution of (1.1) in the interior points of Q T by using the method as the Chapter 2 of [1].
Hydrophobic intracellular encounters are consistent with "soft" interactions exerting important modulatory effects on translational diffusion (see section 2.3.4).
We have added substantially more details on modeling in the main text and in "The diffusion model" section of Materials and methods.
To generate group-averaged VCPs, the individual connectivity probability maps (defined in the 'Diffusion Tractography' section above) were first warped into standard space using Niftyreg.
However, when one considers the average hydrodynamic radii of IDP aggregates (∼90 nm for fibrillar tau, for instance), oligomeric IDP species may exhibit reduced intracellular diffusion (see section 2.3.2).
We begin by presenting the necessary background materials and problem formulation regarding switching diffusions in Section 2.
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