ERRATA: FERMIONIC AND BOSONIC SELF-ORGANIZED NETWORKS: A REPRESENTATION OF QUANTUM STATISTICS

2001 ◽  
Vol 15 (03) ◽  
pp. 313-320 ◽  
Author(s):  
GINESTRA BIANCONI
Keyword(s):  
Cayley Tree ◽  
Self Organization ◽  
High Tc Superconductors ◽  
Quantum Distribution ◽  
High Tc ◽  
Scale Free ◽  
New Class ◽  
Self Organized ◽  
The Right ◽  
Quantum Distributions

A new class of self organized networks is described that is relevant to understand the emerging order in a large number of complex systems such as biological systems, the web, and heterogeneous phases in high Tc superconductors. The Bose and Fermi quantum distributions are shown to be the right tool to describe the two extreme limit distributions, the scale-free and the Cayley-tree network respectively. The new class of self-organized networks is described by a 'mixed' quantum distribution. Here the bosonic and fermionic types of self organization coexists, maintaining the same 'ergodic' nature.

SELF-ORGANIZED NETWORKS AS A REPRESENTATION OF QUANTUM STATISTICS

2000 ◽  
Vol 14 (29n31) ◽  
pp. 3356-3361 ◽  
Author(s):  
GINESTRA BIANCONI
Keyword(s):  
Cayley Tree ◽  
Scale Free Network ◽  
Quantum Distribution ◽  
Scale Free ◽  
New Class ◽  
Self Organized ◽  
Different Types ◽  
Free Network ◽  
The Right ◽  
Quantum Distributions

A new class of self organized networks is described that is relevant to understand the emerging order in a large number of complex systems such as growing biological systems, the web, and heterogeneous phases of correlated condensed matter systems formed by doping. The Bose and Fermi quantum distributions are shown to be the right tool to describe the two extreme limit distributions, the fermionic Cayley-tree network and the bosonic scale-free network. In this new large class of self-organized networks the two different types of self organization coexists, maintaining the same 'ergodic' nature and are described by a 'mixed' quantum distribution.

Self-organized critical state in High-Tc superconductors

1991 ◽  
Vol 185-189 ◽  
pp. 2181-2182 ◽  
Author(s):  
X.S. Ling ◽  
D. Shi ◽  
J.L. Budnick
Keyword(s):  
Critical State ◽  
High Tc Superconductors ◽  
High Tc ◽  
Self Organized

SELF-ORGANIZED CORONA GRAPHS: A DETERMINISTIC COMPLEX NETWORK MODEL WITH HIERARCHICAL STRUCTURE

2019 ◽  
Vol 22 (06) ◽  
pp. 1950019
Author(s):  
ROHAN SHARMA ◽  
BIBHAS ADHIKARI ◽  
TYLL KRUEGER
Keyword(s):  
Power Law ◽  
Small World ◽  
Self Organization ◽  
Scale Free ◽  
Self Organized ◽  
Power Law Exponent ◽  
Growing Networks ◽  
Growing Network ◽  
Hierarchical Pattern ◽  
Corona Graphs

In this paper, we propose a self-organization mechanism for newly appeared nodes during the formation of corona graphs that define a hierarchical pattern in the resulting corona graphs and we call it self-organized corona graphs (SoCG). We show that the degree distribution of SoCG follows power-law in its tail with power-law exponent approximately 2. We also show that the diameter is less equal to 4 for SoCG defined by any seed graph and for certain seed graphs, the diameter remains constant during its formation. We derive lower bounds of clustering coefficients of SoCG defined by certain seed graphs. Thus, the proposed SoCG can be considered as a growing network generative model which is defined by using the corona graphs and a self-organization process such that the resulting graphs are scale-free small-world highly clustered growing networks. The SoCG defined by a seed graph can also be considered as a network with a desired motif which is the seed graph itself.

Pnictide Oxides: A New Class of High-TC Superconductors

2008 ◽  
Vol 47 (26) ◽  
pp. 4782-4784 ◽  
Author(s):  
Dirk Johrendt ◽  
Rainer Pöttgen
Keyword(s):  
High Tc Superconductors ◽  
High Tc ◽  
New Class

scholarly journals Lévy walk process in self-organization of pedestrian crowds

2019 ◽  
Vol 16 (153) ◽  
pp. 20180939 ◽  
Author(s):  
Hisashi Murakami ◽  
Claudio Feliciani ◽  
Katsuhiro Nishinari
Keyword(s):  
Self Organization ◽  
Pedestrian Flow ◽  
Direct Path ◽  
Distributed Resources ◽  
Scale Free ◽  
Lévy Walk ◽  
Self Organized ◽  
Levy Walk ◽  
Movement Strategy ◽  
Lane Formation

Similar to other animal groups, human crowds exhibit various collective patterns that emerge from self-organization. Recent studies have emphasized that individuals anticipate their neighbours' motions to seek their paths in dynamical pedestrian flow. This path-seeking behaviour results in deviation of pedestrians from their desired directions (i.e. the direct path to their destination). However, the strategies that individuals adopt for the behaviour and how the deviation of individual movements impact the emergent organization are poorly understood. We here show that the path-seeking behaviour is performed through a scale-free movement strategy called a Lévy walk, which might facilitate transition to the group-level behaviour. In an experiment of lane formation, a striking example of self-organized patterning in human crowds, we observed how flows of oppositely moving pedestrians spontaneously separate into several unidirectional lanes. We found that before (but not after) lane formation, pedestrians deviate from the desired direction by Lévy walk process, which is considered optimal when searching unpredictably distributed resources. Pedestrians balance a trade-off between seeking their direct paths and reaching their goals as quickly as possible; they may achieve their optimal paths through Lévy walk process, facilitating the emergent lane formation.

Preparation, electron microscopy and superconductivity of a new class of high Tc superconductors: Pb2Sr2Y1-xCaxCu3O8+δ (x = 0.5; 0.25)

1989 ◽  
Vol 71 (6) ◽  
pp. 485-488 ◽  
Author(s):  
M. Gasnier ◽  
M.O. Rauult ◽  
R. Suryanarayanan ◽  
H. Pankowska ◽  
G.T. Bhandage ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
High Tc Superconductors ◽  
High Tc ◽  
New Class

scholarly journals Self-Organization Toward Criticality by Synaptic Plasticity

2021 ◽  
Vol 9 ◽  
Author(s):  
Roxana Zeraati ◽  
Viola Priesemann ◽  
Anna Levina
Keyword(s):  
Synaptic Plasticity ◽  
Network Models ◽  
Self Organization ◽  
Scale Free ◽  
Neural Recordings ◽  
Self Organized ◽  
Self Organized Criticality ◽  
The Brain ◽  
Universal Mechanism

Self-organized criticality has been proposed to be a universal mechanism for the emergence of scale-free dynamics in many complex systems, and possibly in the brain. While such scale-free patterns were identified experimentally in many different types of neural recordings, the biological principles behind their emergence remained unknown. Utilizing different network models and motivated by experimental observations, synaptic plasticity was proposed as a possible mechanism to self-organize brain dynamics toward a critical point. In this review, we discuss how various biologically plausible plasticity rules operating across multiple timescales are implemented in the models and how they alter the network’s dynamical state through modification of number and strength of the connections between the neurons. Some of these rules help to stabilize criticality, some need additional mechanisms to prevent divergence from the critical state. We propose that rules that are capable of bringing the network to criticality can be classified by how long the near-critical dynamics persists after their disabling. Finally, we discuss the role of self-organization and criticality in computation. Overall, the concept of criticality helps to shed light on brain function and self-organization, yet the overall dynamics of living neural networks seem to harnesses not only criticality for computation, but also deviations thereof.

scholarly journals Mutual anticipation can contribute to self-organization in human crowds

2020 ◽  
Author(s):  
Hisashi Murakami ◽  
Claudio Feliciani ◽  
Yuta Nishiyama ◽  
Katsuhiro Nishinari
Keyword(s):  
Collective Behavior ◽  
Movement Pattern ◽  
Self Organization ◽  
Scale Free ◽  
Crowd Management ◽  
Self Organized ◽  
Seeking Behavior ◽  
Physical Particle ◽  
Lane Formation ◽  
Walking Speeds

AbstractHuman crowds provide paradigmatic examples of collective behavior emerging through self-organization. Although the underlying interaction has been considered to obey the distance-dependent law, resembling physical particle systems, recent findings emphasized that pedestrian motions are fundamentally influenced by the anticipated future positions of their neighbors rather than their current positions. Therefore, anticipatory interaction may play a crucial role in collective patterning. However, whether and how individual anticipation functionally benefits the group is not well-understood. We suggest that collective patterning in human crowds is promoted by anticipatory path-seeking behavior resulting in a scale-free movement pattern, called the Lévy walk. In our experiments of lane formation, a striking example of self-organized patterning in human crowds where people moving in opposite directions spontaneously segregate into several unidirectional lanes, we manipulated some pedestrians’ ability to anticipate by having them type on a mobile phone while walking. The manipulation slowed overall walking speeds and delayed the onset of global patterning, and the distracted pedestrians sometimes failed to achieve their usual walking strategy. Moreover, we observed that the delay of global patterning depends on decisions made by pedestrians who were moving toward the distracted ones and had no choice but to take sudden large steps, presumably because of difficulty in anticipating the motions of their counterparts. These results imply that mutual anticipation between pedestrians facilitates efficient transition to emergent patterning in situations where nobody within a crowd is distracted. Our findings may contribute to efficient crowd management and inform future models of self-organizing systems.

scholarly journals Injectable therapeutic organoids using sacrificial hydrogels

2020 ◽  
Author(s):  
Ninna S. Rossen ◽  
Priya N. Anandakumaran ◽  
Rafael zur Nieden ◽  
Kahmun Lo ◽  
Wenjie Luo ◽  
...  
Keyword(s):  
Cell Therapy ◽  
Large Scale ◽  
Self Organization ◽  
Therapeutic Modality ◽  
Dynamic Nature ◽  
Simple Method ◽  
New Class ◽  
Self Organized ◽  
Multicellular Aggregates ◽  
High Yields

AbstractOrganoids, by promoting self-organization of cells into native-like structures, are becoming widespread in drug-screening technologies, but have so far been used sparingly for cell therapy as current approaches for producing self-organized cell clusters lack scalability or reproducibility in size and cellular organization. We introduce a method of using hydrogels as sacrificial scaffolds, which allow cells to form self-organized clusters followed by gentle release, resulting in highly reproducible multicellular structures on a large scale. We demonstrated this strategy for endothelial cells and mesenchymal stem cells to self-organize into blood-vessel units, which were injected into mice using hypodermic needles, and observed in real time to rapidly form perfusing vasculature. As cell therapy transforms into a new class of therapeutic modality, this simple method – by making use of the dynamic nature of hydrogels – could offer high yields of self-organized multicellular aggregates with reproducible sizes and cellular architectures.

Sign in / Sign up

Export Citation Format

Share Document