scholarly journals Cell density modulates intracellular mass transport in neural networks

2017 ◽  
Vol 91 (5) ◽  
pp. 503-509 ◽  
Author(s):  
Patricia Cintora ◽  
Jyothi Arikkath ◽  
Mikhail Kandel ◽  
Gabriel Popescu ◽  
Catherine Best-Popescu
Keyword(s):  
Neural Networks ◽  
Mass Transport ◽  
Cell Density

scholarly journals An intravascular bioartificial pancreas device (iBAP) with silicon nanopore membranes (SNM) for islet encapsulation under convective mass transport

Lab on a Chip ◽  
2017 ◽  
Vol 17 (10) ◽  
pp. 1778-1792 ◽  
Author(s):  
Shang Song ◽  
Charles Blaha ◽  
Willieford Moses ◽  
Jaehyun Park ◽  
Nathan Wright ◽  
...  
Keyword(s):  
Mass Transport ◽  
Cell Density ◽  
Porcine Model ◽  
Convective Transport ◽  
Bioartificial Pancreas ◽  
Islet Encapsulation ◽  
Nanopore Membranes

The SNM-based iBAP demonstrates viability and functionality at clinically relevant cell density and hemocompatibility under convective transport in a porcine model.

scholarly journals On-line prediction of the feeding phase in high-cell density cultivation of rE. coli using constructive neural networks

2013 ◽  
Vol 111 (1) ◽  
pp. 228-248 ◽  
Author(s):  
M.C. Nicoletti ◽  
J.R. Bertini ◽  
M.M. Tanizaki ◽  
T.C. Zangirolami ◽  
V.M. Gonçalves ◽  
...  
Keyword(s):  
Neural Networks ◽  
Cell Density ◽  
High Cell Density ◽  
High Cell ◽  
High Cell Density Cultivation ◽  
Constructive Neural Networks ◽  
On Line

scholarly journals Large-Scale Statistical Learning for Mass Transport Prediction in Porous Materials Using 90,000 Artificially Generated Microstructures

2021 ◽  
Vol 8 ◽  
Author(s):  
Benedikt Prifling ◽  
Magnus Röding ◽  
Philip Townsend ◽  
Matthias Neumann ◽  
Volker Schmidt
Keyword(s):  
Neural Networks ◽  
Mass Transport ◽  
Statistical Learning ◽  
Convolutional Neural Networks ◽  
Large Scale ◽  
Effective Properties ◽  
Functional Materials ◽  
Analytical Prediction ◽  
Learning Approaches ◽  
3D Microstructure

Effective properties of functional materials crucially depend on their 3D microstructure. In this paper, we investigate quantitative relationships between descriptors of two-phase microstructures, consisting of solid and pores and their mass transport properties. To that end, we generate a vast database comprising 90,000 microstructures drawn from nine different stochastic models, and compute their effective diffusivity and permeability as well as various microstructural descriptors. To the best of our knowledge, this is the largest and most diverse dataset created for studying the influence of 3D microstructure on mass transport. In particular, we establish microstructure-property relationships using analytical prediction formulas, artificial (fully-connected) neural networks, and convolutional neural networks. Again, to the best of our knowledge, this is the first time that these three statistical learning approaches are quantitatively compared on the same dataset. The diversity of the dataset increases the generality of the determined relationships, and its size is vital for robust training of convolutional neural networks. We make the 3D microstructures, their structural descriptors and effective properties, as well as the code used to study the relationships between them available open access.

Models of Thermodynamic Properties of Prominences

1979 ◽  
Vol 44 ◽  
pp. 349-355
Author(s):  
R.W. Milkey
Keyword(s):  
Thermodynamic Properties ◽  
Mass Transport ◽  
Emission Spectrum ◽  
Thermodynamic Parameters ◽  
Working Group ◽  
Physical Processes ◽  
Theoretical Concepts ◽  
Group 3 ◽  
Observational Techniques

The focus of discussion in Working Group 3 was on the Thermodynamic Properties as determined spectroscopically, including the observational techniques and the theoretical modeling of physical processes responsible for the emission spectrum. Recent advances in observational techniques and theoretical concepts make this discussion particularly timely. It is wise to remember that the determination of thermodynamic parameters is not an end in itself and that these are interesting chiefly for what they can tell us about the energetics and mass transport in prominences.

Increassed parietal cell density in patients with perfurated duodenal ulcer: Comparison with non-complicated duodenal ulcer patients

2001 ◽  
Vol 120 (5) ◽  
pp. A250-A250
Author(s):  
A BARBOSA ◽  
C MENDES ◽  
L COELHO ◽  
C RODRIGUES ◽  
M MACHADO ◽  
...  
Keyword(s):  
Duodenal Ulcer ◽  
Cell Density ◽  
Parietal Cell
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