Development of a Tissue Dielectric Properties Model Based on Maxwell-Fricke Mixture Theory

Author(s):  
Sevde Etoz ◽  
William Greisch ◽  
Christopher L. Brace
Textiles ◽  
2022 ◽  
Vol 2 (1) ◽  
pp. 50-80
Author(s):  
Yusuke Yamada

Deciphering how the dielectric properties of textile materials are orchestrated by their internal components has far-reaching implications. For the development of textile-based electronics, which have gained ever-increasing attention for their uniquely combined features of electronics and traditional fabrics, both performance and form factor are critically dependent on the dielectric properties. The knowledge of the dielectric properties of textile materials is thus crucial in successful design and operation of textile-based electronics. While the dielectric properties of textile materials could be estimated to some extent from the compositional profiles, recent studies have identified various additional factors that have also substantial influence. From the viewpoint of materials characterization, such dependence of the dielectric properties of textile materials have given rise to a new possibility—information on various internal components could be, upon successful correlation, extracted by measuring the dielectric properties. In view of these considerable implications, this invited review paper summarizes various fundamental theories and principles related to the dielectric properties of textile materials. In order to provide an imperative basis for uncovering various factors that intricately influence the dielectric properties of textile materials, the foundations of the dielectrics and polarization mechanisms are first recapitulated, followed by an overview on the concept of homogenization and the dielectric mixture theory. The principal advantages, challenges and opportunities in the analytical approximations of the dielectric properties of textile materials are then discussed based on the findings from the recent literature, and finally a variety of characterization methods suitable for measuring the dielectric properties of textile materials are described. It is among the objectives of this paper to build a practical signpost for scientists and engineers in this rapidly evolving, cross-disciplinary field.


2002 ◽  
Vol 32 (6) ◽  
pp. 465-469 ◽  
Author(s):  
J. Monzó-Cabrera ◽  
J. M. Catalá-Civera ◽  
A. Díaz-Morcillo ◽  
D. Sánchez-Hernández ◽  
P. J. Plaza-González ◽  
...  

2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.


2001 ◽  
Vol 7 (S2) ◽  
pp. 578-579
Author(s):  
David W. Knowles ◽  
Sophie A. Lelièvre ◽  
Carlos Ortiz de Solόrzano ◽  
Stephen J. Lockett ◽  
Mina J. Bissell ◽  
...  

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.


Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery

Author(s):  
Jonathan Jacky ◽  
Margus Veanes ◽  
Colin Campbell ◽  
Wolfram Schulte
Keyword(s):  

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