A Deformable Fast Computation Elastic Model Based on Element Reduction and Reconstruction

2004 ◽  
Author(s):  
S. Miyazaki ◽  
M. Endo ◽  
M. Yamada ◽  
J. Hasegawa ◽  
T. Yasuda ◽  
...  
Keyword(s):  
Elastic Model ◽  
Fast Computation ◽  
Model Based

Elastic model-based segmentation of 3-D neuroradiological data sets

1999 ◽  
Vol 18 (10) ◽  
pp. 828-839 ◽  
Author(s):  
A. Kelemen ◽  
G. Szekely ◽  
G. Gerig
Keyword(s):  
Elastic Model ◽  
Data Sets ◽  
Model Based

scholarly journals Interpretation of increased deformation rate in aquifer IV due to groundwater pumping in Shanghai

2013 ◽  
Vol 50 (11) ◽  
pp. 1129-1142 ◽  
Author(s):  
Shui-Long Shen ◽  
Lei Ma ◽  
Ye-Shuang Xu ◽  
Zhen-Yu Yin
Keyword(s):  
Groundwater Flow ◽  
Land Subsidence ◽  
Deformation Rate ◽  
Flow Theory ◽  
Groundwater Potential ◽  
Creep Model ◽  
Elastic Model ◽  
Groundwater Pumping ◽  
Model Based ◽  
Spatial Domains

Shanghai is a typical example of a region in China suffering from severe land subsidence. Previous investigations have shown that land subsidence is strongly related to groundwater pumping in both the temporal and spatial domains. A series of field investigations shows that the deformation rate of aquifer IV (AqIV) has increased, contributing significantly to the total subsidence in Shanghai. To predict the deformation behavior of AqIV in Shanghai due to groundwater pumping, four different models have been applied in this study: (i) a model based on groundwater flow theory, (ii) an elastic model based on Cauchy mechanics, (iii) a creep model incorporated into Cauchy mechanics, and (iv) a recently proposed land subsidence model by Budhu based on Cosserat mechanics. Based on a number of assumptions, Budhu’s concept was extended to consider the time-dependent behavior of groundwater potential in aquifers and the consolidation behavior of overburdened aquitards. The calculated results of AqIV’s deformation were compared with the field-measured data. The results show that when using groundwater flow theory and Cauchy mechanics, it is difficult to predict the increased deformation rate of the sandy layers in aquifers even when the creep behavior is incorporated into the calculation. However, Budhu’s method based on Cosserat mechanics can predict this increased deformation rate well. The predicted result indicates that increased deformation of aquifer IV is due to volumetric contraction caused by shear stress rather than the creep of aquifer sand. The phenomenon of deformation delay in aquifers can also be interpreted with the proposed model.

Representation, abstraction, and simple-minded sophisticates

2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan
Keyword(s):  
Decision Theory ◽  
Predictive Coding ◽  
Bayesian Decision Theory ◽  
Bayesian Decision ◽  
Model Based ◽  
Model Free

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.

Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

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 ◽  
...  
Keyword(s):  
Image Analysis ◽  
Mammary Epithelial Cells ◽  
Nuclear Organization ◽  
Critical Role ◽  
Quantitative Model ◽  
Mammary Epithelial ◽  
Cell Phenotype ◽  
Proliferating Cells ◽  
Mitotic Apparatus ◽  
Model Based

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.

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