scholarly journals PROPERTIES OF WEIGHTED COMPLEX NETWORKS

2006 ◽  
Vol 17 (04) ◽  
pp. 521-529 ◽  
Author(s):  
XIN-JIAN XU ◽  
ZHI-XI WU ◽  
YING-HAI WANG
Keyword(s):  
Small World ◽  
Epidemic Spreading ◽  
Spreading Process ◽  
Scale Free ◽  
Weighted Networks ◽  
Link Weight ◽  
Long Time ◽  
Si Model ◽  
Time Propagation

We study two kinds of weighted networks, weighted small-world (WSW) and weighted scale-free (WSF). The weight wij of a link between nodes i and j in the network is defined as the product of endpoint node degrees; that is wij =(ki kj)θ. In contrast to adding weights to links when networks are being constructed, we only consider weights depending on the "popularity" of the nodes represented by their connectivity. It was found that both weighted networks have broad distributions on the characterization of the link weight, the vertex strength, and the average shortest path length. Furthermore, as a survey of the model, the epidemic spreading process in both weighted networks was studied based on the standard susceptible-infected (SI) model. The spreading velocity reaches a peak very quickly after the infection outbreaks and an exponential decay was found in the long time propagation.

Epidemic spreading on evolving networks

2019 ◽  
Vol 33 (23) ◽  
pp. 1950266 ◽  
Author(s):  
Jin-Xuan Yang
Keyword(s):  
Preferential Attachment ◽  
Small World ◽  
Network Evolution ◽  
Epidemic Spreading ◽  
Epidemic Threshold ◽  
Scale Free ◽  
Evolving Networks ◽  
Power Law Exponent ◽  
Free Network ◽  
Over Time

Network structure will evolve over time, which will lead to changes in the spread of the epidemic. In this work, a network evolution model based on the principle of preferential attachment is proposed. The network will evolve into a scale-free network with a power-law exponent between 2 and 3 by our model, where the exponent is determined by the evolution parameters. We analyze the epidemic spreading process as the network evolves from a small-world one to a scale-free one, including the changes in epidemic threshold over time. The condition of epidemic threshold to increase is given with the evolution processes. The simulated results of real-world networks and synthetic networks show that as the network evolves at a low evolution rate, it is more conducive to preventing epidemic spreading.

EFFECTS OF MOTION ON EPIDEMIC SPREADING

2010 ◽  
Vol 20 (03) ◽  
pp. 765-773 ◽  
Author(s):  
ARTURO BUSCARINO ◽  
AGNESE DI STEFANO ◽  
LUIGI FORTUNA ◽  
MATTIA FRASCA ◽  
VITO LATORA
Keyword(s):  
Mobile Agents ◽  
Small World ◽  
Small World Networks ◽  
Epidemic Spreading ◽  
Long Distance ◽  
Dynamical Networks ◽  
Scale Free ◽  
Random Walkers ◽  
Human Movements ◽  
Disease Spreading

The study of social networks, and in particular those aspects related to disease spreading, has recently attracted considerable attention in the scientific community. In this paper, we investigate the effect of motion on the spread of diseases in dynamical networks of mobile agents. In order to simulate the long distance displacements empirically observed in real human movements, we consider different motion rules, such as random walks with the addition of jumps or Lévy flights. We compare the epidemic thresholds found in dynamical networks of mobile agents with the analogous expressions for static networks. We discuss the existing relations between dynamical networks of random walkers with jumps and static small-world networks, and those between systems of Lévy walkers and scale-free networks.

Epidemic spreading on networks based on stress response

2017 ◽  
Vol 31 (16) ◽  
pp. 1750131 ◽  
Author(s):  
Fuzhong Nian ◽  
Shuanglong Yao
Keyword(s):  
Stress Response ◽  
Infectious Diseases ◽  
Stress Responses ◽  
Epidemic Model ◽  
Small World ◽  
Small World Networks ◽  
Epidemic Spreading ◽  
Spreading Resistance ◽  
Scale Free ◽  
Scale Free Networks

Based on the stress responses of individuals, the susceptible-infected-susceptible epidemic model was improved on the small-world networks and BA scale-free networks and the simulations were implemented and analyzed. Results indicate that the behaviors of individual’s stress responses could induce the epidemic spreading resistance and adaptation at the network level. This phenomenon showed that networks were learning how to adapt to the disease and the evolution process could improve their immunization to future infectious diseases and would effectively prevent the spreading of infectious diseases.

An SIS Epidemic Model with Feedback Mechanism in Scale-Free Networks

2011 ◽  
Vol 204-210 ◽  
pp. 354-358 ◽  
Author(s):  
Guang Wu Gong ◽  
Da Min Zhang
Keyword(s):  
Epidemic Model ◽  
Feedback Mechanism ◽  
Epidemic Spreading ◽  
Epidemic Threshold ◽  
Spreading Process ◽  
Scale Free ◽  
Sis Epidemic Model ◽  
Scale Free Networks ◽  
Controlling Measures ◽  
Sis Epidemic

A new susceptible-infected-susceptible model with feedback mechanism is proposed. The dynamic behavior of the epidemic model with feedback mechanism in scale-free networks is researched by theoretical analysis and computer simulation. The results show that feedback mechanism can reduce the stable infective ratio of system; however, it can not influence the epidemic threshold of system. The results can help us to understand rightly epidemic spreading process in reality networks and guide people to design effective epidemic preventive and controlling measures when epidemic outbreaks.

scholarly journals Minimal physicalism as a scale-free substrate for cognition and consciousness

2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
Chris Fields ◽  
James F Glazebrook ◽  
Michael Levin
Keyword(s):  
Small World ◽  
Coarse Graining ◽  
Experimental Manipulation ◽  
Attention Switching ◽  
Scale Free ◽  
Basic Functions ◽  
Hierarchical Bayesian Inference ◽  
And Function ◽  
Minimal Physicalism

Abstract Theories of consciousness and cognition that assume a neural substrate automatically regard phylogenetically basal, nonneural systems as nonconscious and noncognitive. Here, we advance a scale-free characterization of consciousness and cognition that regards basal systems, including synthetic constructs, as not only informative about the structure and function of experience in more complex systems but also as offering distinct advantages for experimental manipulation. Our “minimal physicalist” approach makes no assumptions beyond those of quantum information theory, and hence is applicable from the molecular scale upwards. We show that standard concepts including integrated information, state broadcasting via small-world networks, and hierarchical Bayesian inference emerge naturally in this setting, and that common phenomena including stigmergic memory, perceptual coarse-graining, and attention switching follow directly from the thermodynamic requirements of classical computation. We show that the self-representation that lies at the heart of human autonoetic awareness can be traced as far back as, and serves the same basic functions as, the stress response in bacteria and other basal systems.

scholarly journals Characterization of real-world networks through quantum potentials

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254384
Author(s):  
Nicola Amoroso ◽  
Loredana Bellantuono ◽  
Saverio Pascazio ◽  
Alfonso Monaco ◽  
Roberto Bellotti
Keyword(s):  
Social Sciences ◽  
Real World ◽  
Network Connectivity ◽  
Small World ◽  
Formation Mechanisms ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network ◽  
Network Ensembles

Network connectivity has been thoroughly investigated in several domains, including physics, neuroscience, and social sciences. This work tackles the possibility of characterizing the topological properties of real-world networks from a quantum-inspired perspective. Starting from the normalized Laplacian of a network, we use a well-defined procedure, based on the dressing transformations, to derive a 1-dimensional Schrödinger-like equation characterized by the same eigenvalues. We investigate the shape and properties of the potential appearing in this equation in simulated small-world and scale-free network ensembles, using measures of fractality. Besides, we employ the proposed framework to compare real-world networks with the Erdős-Rényi, Watts-Strogatz and Barabási-Albert benchmark models. Reconstructed potentials allow to assess to which extent real-world networks approach these models, providing further insight on their formation mechanisms and connectivity properties.

scholarly journals Complex networks description of ionosphere

2017 ◽  
Author(s):  
Shikun Lu ◽  
Hao Zhang ◽  
Xihai Li ◽  
Yihong Li ◽  
Chao Niu ◽  
...  
Keyword(s):  
Complex Networks ◽  
Spatial Variation ◽  
Information Flow ◽  
Current System ◽  
Small World ◽  
Spatial Distance ◽  
Information Network ◽  
Scale Free ◽  
Self Organized ◽  
Long Time

Abstract. Complex networks have emerged as an important area of geoscience to generate novel insights into nature of complex systems. To investigate the information flow in ionosphere, the directed complex network is constructed based on the conditional independence theory. The results of the power-law hypothesis testing show that both the out-degree and in-degree distribution of the ionospheric network are not scale-free. The topological structure of the ionospheric information network is homogeneous. The spatial variation of the ionospheric network shows the connection principally exist between the neighbors in space, indicating that in ionosphere the information transmission is mainly based on the spatial distance. Moreover, the spatial edge distributions show that the information travels further along the latitude than along the longitude. Perhaps, this is because the dramatic variation of ionosphere along the geomagnetic field interrupts the information flow. Moreover, the analysis of small-world-ness shows the ionospheric information network is small-world, which may result from the current system in the ionosphere. The fractal analysis shows the ionospheric network is not self-organized, indicating the complexity of the spatial variation for long time in ionosphere.

THE SIS MODEL WITH TIME DELAY ON COMPLEX NETWORKS

2009 ◽  
Vol 19 (02) ◽  
pp. 623-628 ◽  
Author(s):  
XIN-JIAN XU ◽  
GUANRONG CHEN
Keyword(s):  
Complex Networks ◽  
Delay Time ◽  
Transmission Rate ◽  
Small World ◽  
Small World Networks ◽  
Epidemic Spreading ◽  
Epidemic Threshold ◽  
Exponential Form ◽  
Sis Model ◽  
Scale Free

We present a time-delayed SIS model on complex networks to study epidemic spreading. We found that the existence of delay will affect, and oftentimes enhance, both outbreak and prevalence of infectious diseases in the networks. For small-world networks, we found that the epidemic threshold and the delay time have a power-law relation. For scale-free networks, we found that for a given transmission rate, the epidemic prevalence has an exponential form, which can be analytically obtained, and it decays as the delay time increases. We confirm all results by sufficient numerical simulations.

A Thorough Theoretical Exploration of Intriguing Characteristics of Cyclo[18]carbon: Geometry, Bonding Nature, Aromaticity, Weak Interaction, Reactivity, Excited States, Vibrations, Molecular Dynamics and Various Molecular Properties

2019 ◽  
Author(s):  
Tian Lu ◽  
Qinxue Chen ◽  
Zeyu Liu
Keyword(s):  
Molecular Dynamics ◽  
Excited States ◽  
Electronic Excitation ◽  
Ring Structure ◽  
Molecular Properties ◽  
Molecular Vibration ◽  
Full Characterization ◽  
Long Time ◽  
Almost All

Although cyclo[18]carbon has been theoretically and experimentally investigated since long time ago, only very recently it was prepared and directly observed by means of STM/AFM in condensed phase (Kaiser et al., <i>Science</i>, <b>365</b>, 1299 (2019)). The unique ring structure and dual 18-center π delocalization feature bring a variety of unusual characteristics and properties to the cyclo[18]carbon, which are quite worth to be explored. In this work, we present an extremely comprehensive and detailed investigation on almost all aspects of the cyclo[18]carbon, including (1) Geometric characteristics (2) Bonding nature (3) Electron delocalization and aromaticity (4) Intermolecular interaction (5) Reactivity (6) Electronic excitation and UV/Vis spectrum (7) Molecular vibration and IR/Raman spectrum (8) Molecular dynamics (9) Response to external field (10) Electron ionization, affinity and accompanied process (11) Various molecular properties. We believe that our full characterization of the cyclo[18]carbon will greatly deepen researchers' understanding of this system, and thereby help them to utilize it in practice and design its various valuable derivatives.

A Thorough Theoretical Exploration of Intriguing Characteristics of Cyclo[18]carbon: Geometry, Bonding Nature, Aromaticity, Weak Interaction, Reactivity, Excited States, Vibrations, Molecular Dynamics and Various Molecular Properties

2019 ◽  
Author(s):  
Tian Lu ◽  
Qinxue Chen ◽  
Zeyu Liu
Keyword(s):  
Molecular Dynamics ◽  
Excited States ◽  
Electronic Excitation ◽  
Ring Structure ◽  
Molecular Properties ◽  
Molecular Vibration ◽  
Full Characterization ◽  
Long Time ◽  
Almost All

Although cyclo[18]carbon has been theoretically and experimentally investigated since long time ago, only very recently it was prepared and directly observed by means of STM/AFM in condensed phase (Kaiser et al., <i>Science</i>, <b>365</b>, 1299 (2019)). The unique ring structure and dual 18-center π delocalization feature bring a variety of unusual characteristics and properties to the cyclo[18]carbon, which are quite worth to be explored. In this work, we present an extremely comprehensive and detailed investigation on almost all aspects of the cyclo[18]carbon, including (1) Geometric characteristics (2) Bonding nature (3) Electron delocalization and aromaticity (4) Intermolecular interaction (5) Reactivity (6) Electronic excitation and UV/Vis spectrum (7) Molecular vibration and IR/Raman spectrum (8) Molecular dynamics (9) Response to external field (10) Electron ionization, affinity and accompanied process (11) Various molecular properties. We believe that our full characterization of the cyclo[18]carbon will greatly deepen researchers' understanding of this system, and thereby help them to utilize it in practice and design its various valuable derivatives.

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