Self-Organized Molecular Films with Long-Range Quasiperiodic Order

ACS Nano ◽  
2014 ◽  
Vol 8 (4) ◽  
pp. 3646-3653 ◽  
Author(s):  
Vincent Fournée ◽  
Émilie Gaudry ◽  
Julian Ledieu ◽  
Marie-Cécile de Weerd ◽  
Dongmei Wu ◽  
...  
Keyword(s):  
Long Range ◽  
Molecular Films ◽  
Self Organized

Self-Organized Hybrid Silica with Long-Range Ordered Lamellar Structure

2001 ◽  
Vol 123 (32) ◽  
pp. 7957-7958 ◽  
Author(s):  
Joël J. E. Moreau ◽  
Luc Vellutini ◽  
Michel Wong Chi Man ◽  
Catherine Bied ◽  
Jean-Louis Bantignies ◽  
...  
Keyword(s):  
Long Range ◽  
Lamellar Structure ◽  
Self Organized ◽  
Hybrid Silica

ON A COMBINED SHORT-RANGE AND LONG-RANGE INTERACTING EARTHQUAKE MODEL

2000 ◽  
Vol 11 (05) ◽  
pp. 913-919
Author(s):  
A. S. ELGAZZAR ◽  
E. AHMED
Keyword(s):  
Long Range ◽  
Short Range ◽  
Self Organized ◽  
Long Range Interactions ◽  
Earthquake Model

A self-organized critical earthquake model is proposed taking into account the effect of both short-range and long-range interactions. The model obeys both Gutenberg–Richter and Omori laws in addition to being more realistic than other models.

scholarly journals Self-Organized Structuring of Recurrent Neuronal Networks for Reliable Information Transmission

Biology ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 577
Author(s):  
Daniel Miner ◽  
Florentin Wörgötter ◽  
Christian Tetzlaff ◽  
Michael Fauth
Keyword(s):  
Long Range ◽  
Network Structure ◽  
Network Architecture ◽  
Metabolic Cost ◽  
Network Activity ◽  
Self Organization ◽  
Stimulus Information ◽  
Hierarchical Network ◽  
Self Organized ◽  
Input And Output

Our brains process information using a layered hierarchical network architecture, with abundant connections within each layer and sparse long-range connections between layers. As these long-range connections are mostly unchanged after development, each layer has to locally self-organize in response to new inputs to enable information routing between the sparse in- and output connections. Here we demonstrate that this can be achieved by a well-established model of cortical self-organization based on a well-orchestrated interplay between several plasticity processes. After this self-organization, stimuli conveyed by sparse inputs can be rapidly read out from a layer using only very few long-range connections. To achieve this information routing, the neurons that are stimulated form feed-forward projections into the unstimulated parts of the same layer and get more neurons to represent the stimulus. Hereby, the plasticity processes ensure that each neuron only receives projections from and responds to only one stimulus such that the network is partitioned into parts with different preferred stimuli. Along this line, we show that the relation between the network activity and connectivity self-organizes into a biologically plausible regime. Finally, we argue how the emerging connectivity may minimize the metabolic cost for maintaining a network structure that rapidly transmits stimulus information despite sparse input and output connectivity.

scholarly journals Numerical statistical analysis on self-organizing behavior of microfracturing events in rock failure

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771876899 ◽  
Author(s):  
Houquan Zhang ◽  
Hao Shi ◽  
Yu Wu ◽  
Hai Pu
Keyword(s):  
Long Range ◽  
Failure Process ◽  
Rock Failure ◽  
The Self ◽  
In Situ Monitoring ◽  
Power Exponent ◽  
Self Organized ◽  
Rescaled Range Analysis ◽  
Rock Failure Process ◽  
Self Organized Criticality

Current experimental investigations on microfracturing (or acoustic emission) events mainly focus on their location and distribution. A new function in rock failure process analysis (RFPA2D) code was developed to capture the size and number of damage element groups in each loading step. The rock failure process evolving from the initiation, propagation, and nucleation of microcracks was visually simulated by RFPA2D in this research. Based on the newly developed function, the statistical quantitative analysis of microfracturing events in rock was effectively conducted. The results show that microfracturing (failed element) events in the whole failure process accord with negative power law distribution, showing fractal features. When approaching a self-organized criticality state, the power exponent does not vary drastically, which ranges around 1.5 approximately. The power exponent decreases correspondingly as the stress increases. Through the analysis of the frequency and size of damaged element groups by rescaled range analysis method, the time series of microfracturing events exhibits the self-similar scale-invariant properties. Through the analysis by the correlation function method, the absolute value of the self-correlation coefficient of microfracturing sequence demonstrates a subsequent precursory increase after a long time delay, exhibiting long-range correlation characteristics. These fractal configuration and long-range correlations are two fingerprints of self-organized criticality, which indicates the occurrence of self-organized criticality in rock failure. Compared with the limited in situ monitoring data, this simulation can supply more sufficient information for the prediction of unstable failure and good understanding of the failure mechanism.

Femtosecond laser-induced long-range self-organized periodic planar nanocracks for applications in biophotonics

2007 ◽  
Author(s):  
Eli Simova ◽  
Cyril Hnatovsky ◽  
Rod S. Taylor ◽  
David M. Rayner ◽  
Paul B. Corkum
Keyword(s):  
Femtosecond Laser ◽  
Long Range ◽  
Self Organized
Sign in / Sign up

Export Citation Format

Share Document