A model-based approach to compensate for the dynamics convolution effect on nanomechanical property measurement

2010 ◽  
Vol 107 (6) ◽  
pp. 064315 ◽  
Author(s):  
Zhonghua Xu ◽  
Qingze Zou
Keyword(s):  
Nanomechanical Property ◽  
Model Based ◽  
Property Measurement ◽  
Convolution Effect

scholarly journals Recent Development of Nanomechanical Property Measurement

2008 ◽  
Vol 36 (2) ◽  
pp. 99-106 ◽  
Author(s):  
Sae Nagai ◽  
So Fujinami ◽  
Ken Nakajima ◽  
Toshio Nishi
Keyword(s):  
Nanomechanical Property ◽  
Property Measurement

High-Speed Nanomechanical Property Measurement in Liquid Using Inversion-Based Iterative Feedforward-Feedback Control

2011 ◽  
Author(s):  
Yan Zhang ◽  
Qingze Zou
Keyword(s):  
High Speed ◽  
Signal To Noise Ratio ◽  
Soft Materials ◽  
Nanomechanical Property ◽  
Force Curve ◽  
Vibrational Dynamics ◽  
Rate Dependent ◽  
Property Measurement ◽  
Soft Samples ◽  
Liquid Measurement

This article presents an inversion-based iterative feedforward-feedback (II-FF/FB) approach to achieve high-speed nanomechanical property measurement of soft materials in liquid. Measurement of nanomechanical properties in liquid is needed for studying a wide variety of soft materials, particularly live biological samples such as live cell. Moreover, high-speed nanomechanical property measurement is needed when dynamic evolution of the sample occurs and/or the rate-dependent viscoelasticity of materials is measured. Nanomechanical measurement in liquid, however, is challenged by the adverse effects including the thermal drift effect, the reduction of the signal to noise ratio, and the hysteresis and the vibrational dynamics effects of the piezoelectric actuators (used to position the probe relative to the sample). Thus, the main contribution of the article is the development of the II-FF/FB approach to tackle these challenges. The proposed method is illustrated through force-curve measurement on a poly (dimethylsiloxane) (PDMS) sample in liquid at high-speed. The experimental results demonstrated the efficacy of the proposed approach in achieving high-speed force-curve measurements of soft samples in liquid.

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.

Model-Based Clustering and Classification for Data Science

2019 ◽  
Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery
Keyword(s):  
Data Science ◽  
Model Based Clustering ◽  
Model Based ◽  
Clustering And Classification

Model-Based Software Testing and Analysis with C#

2007 ◽  
Author(s):  
Jonathan Jacky ◽  
Margus Veanes ◽  
Colin Campbell ◽  
Wolfram Schulte
Keyword(s):  
Software Testing ◽  
Model Based
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