Order Structures on Böhm-Like Models

2005 ◽  
pp. 103-118 ◽  
Author(s):  
Paula Severi ◽  
Fer-Jan de Vries
Keyword(s):  
Order Structures

Microsized Structures Fabricated with Nanoparticles as Building Blocks

1998 ◽  
Vol 536 ◽  
Author(s):  
Yongchi Tian ◽  
A. D. Dinsmore ◽  
S. B. Qadri ◽  
B. R. Ratna
Keyword(s):  
Radial Growth ◽  
Building Blocks ◽  
Higher Order ◽  
Surfactant Templating ◽  
Order Structures

AbstractHere we report a nanoparticulate route to Y2O3 nanofibers (~50 nm in diameter and a few micrometers in length) and for the radial growth of ZnS spheres (200-800 nm diameter). Well-defined higher order structures are developed upon thermostatically aging the dispersions of monomeric nanocrystals. The shapes of the “macromolecules„ are correlated to primary monomeric nanocrystallites, the growing time and temperature, and surfactant templating agents. It is anticipated that this approach should inspire fabrication of nanoparticulate structures by using primary nanoparticles as monomers.

scholarly journals Dimerization and oligomerization of DNA-assembled building blocks for controlled multi-motion in high-order architectures

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ling Xin ◽  
Xiaoyang Duan ◽  
Na Liu
Keyword(s):  
Building Block ◽  
Degrees Of Freedom ◽  
Building Blocks ◽  
Single Type ◽  
Hierarchical Assembly ◽  
Optical Responses ◽  
Self Association ◽  
Living Organisms ◽  
Order Structures ◽  
Chiral System

AbstractIn living organisms, proteins are organized prevalently through a self-association mechanism to form dimers and oligomers, which often confer new functions at the intermolecular interfaces. Despite the progress on DNA-assembled artificial systems, endeavors have been largely paid to achieve monomeric nanostructures that mimic motor proteins for a single type of motion. Here, we demonstrate a DNA-assembled building block with rotary and walking modules, which can introduce new motion through dimerization and oligomerization. The building block is a chiral system, comprising two interacting gold nanorods to perform rotation and walking, respectively. Through dimerization, two building blocks can form a dimer to yield coordinated sliding. Further oligomerization leads to higher-order structures, containing alternating rotation and sliding dimer interfaces to impose structural twisting. Our hierarchical assembly scheme offers a design blueprint to construct DNA-assembled advanced architectures with high degrees of freedom to tailor the optical responses and regulate multi-motion on the nanoscale.

Investigation of the short range order structures in sodium thioborosilicate mixed glass former glasses

2019 ◽  
Vol 521 ◽  
pp. 119456 ◽  
Author(s):  
Brittany Curtis ◽  
Carter Francis ◽  
Steven Kmiec ◽  
Steve W. Martin
Keyword(s):  
Short Range ◽  
Short Range Order ◽  
Range Order ◽  
Order Structures

Logical quantizations of first-order structures

1996 ◽  
Vol 35 (3) ◽  
pp. 495-517 ◽  
Author(s):  
Hirokazu Nishimura
Keyword(s):  
First Order ◽  
Order Structures

External Correlates of the Personality Assessment Inventory Higher Order Structures

2013 ◽  
Vol 95 (4) ◽  
pp. 432-434 ◽  
Author(s):  
Jenelle Slavin-Mulford ◽  
Samuel Justin Sinclair ◽  
Johanna Malone ◽  
Michelle Stein ◽  
Iruma Bello ◽  
...  
Keyword(s):  
Personality Assessment ◽  
Personality Assessment Inventory ◽  
Higher Order ◽  
Order Structures

Bayesian Covariance Representation with Global Informative Prior for 3D Action Recognition

2021 ◽  
Vol 17 (4) ◽  
pp. 1-22
Author(s):  
Jianhai Zhang ◽  
Zhiyong Feng ◽  
Yong Su ◽  
Meng Xing
Keyword(s):  
Action Recognition ◽  
Temporal Order ◽  
State Of The Art ◽  
Feature Representation ◽  
Independent Action ◽  
Sufficient Statistics ◽  
Informative Prior ◽  
Global Action ◽  
High Order Statistics ◽  
Order Structures

For the merits of high-order statistics and Riemannian geometry, covariance matrix has become a generic feature representation for action recognition. An independent action can be represented by an empirical statistics over all of its pose samples. Two major problems of covariance include the following: (1) it is prone to be singular so that actions fail to be represented properly, and (2) it is short of global action/pose-aware information so that expressive and discriminative power is limited. In this article, we propose a novel Bayesian covariance representation by a prior regularization method to solve the preceding problems. Specifically, covariance is viewed as a parametric maximum likelihood estimate of Gaussian distribution over local poses from an independent action. Then, a Global Informative Prior (GIP) is generated over global poses with sufficient statistics to regularize covariance. In this way, (1) singularity is greatly relieved due to sufficient statistics, (2) global pose information of GIP makes Bayesian covariance theoretically equivalent to a saliency weighting covariance over global action poses so that discriminative characteristics of actions can be represented more clearly. Experimental results show that our Bayesian covariance with GIP efficiently improves the performance of action recognition. In some databases, it outperforms the state-of-the-art variant methods that are based on kernels, temporal-order structures, and saliency weighting attentions, among others.

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