scholarly journals Link-usage asymmetry and collective patterns emerging from rich-club organization of complex networks

2020 ◽  
Vol 117 (31) ◽  
pp. 18332-18340 ◽  
Author(s):  
Paolo Moretti ◽  
Marc-Thorsten Hütt
Keyword(s):  
Complex Networks ◽  
Network Topology ◽  
Numerical Results ◽  
Topological Characterization ◽  
Rich Club ◽  
Self Organized ◽  
Local Patterns ◽  
Directional Preference ◽  
Average Orientation ◽  
The Difference

In models of excitable dynamics on graphs, excitations can travel in both directions of an undirected link. However, as a striking interplay of dynamics and network topology, excitations often establish a directional preference. Some of these cases of “link-usage asymmetry” are local in nature and can be mechanistically understood, for instance, from the degree gradient of a link (i.e., the difference in node degrees at both ends of the link). Other contributions to the link-usage asymmetry are instead, as we show, self-organized in nature, and strictly nonlocal. This is the case for excitation waves, where the preferential propagation of excitations along a link depends on its orientation with respect to a hub acting as a source, even if the link in question is several steps away from the hub itself. Here, we identify and quantify the contribution of such self-organized patterns to link-usage asymmetry and show that they extend to ranges significantly longer than those ascribed to local patterns. We introduce a topological characterization, the hub-set-orientation prevalence of a link, which indicates its average orientation with respect to the hubs of a graph. Our numerical results show that the hub-set-orientation prevalence of a link strongly correlates with the preferential usage of the link in the direction of propagation away from the hub core of the graph. Our methodology is embedding-agnostic and allows for the measurement of wave signals and the sizes of the cores from which they originate.

Information on evolutionary age in redundancy of complex network

2019 ◽  
Vol 33 (27) ◽  
pp. 1950331
Author(s):  
Shiguo Deng ◽  
Henggang Ren ◽  
Tongfeng Weng ◽  
Changgui Gu ◽  
Huijie Yang
Keyword(s):  
Principal Component Analysis ◽  
Complex Networks ◽  
Metabolic Network ◽  
Complex Network ◽  
Cellular Networks ◽  
Topological Structure ◽  
Quantitative Measure ◽  
Principal Component ◽  
Evolutionary Information ◽  
Local Patterns

Evolutionary processes of many complex networks in reality are dominated by duplication and divergence. This mechanism leads to redundant structures, i.e. some nodes share most of their neighbors and some local patterns are similar, called redundancy of network. An interesting reverse problem is to discover evolutionary information from the present topological structure. We propose a quantitative measure of redundancy of network from the perspective of principal component analysis. The redundancy of a community in the empirical human metabolic network is negatively and closely related with its evolutionary age, which is consistent with that for the communities in the modeling protein–protein network. This behavior can be used to find the evolutionary difference stored in cellular networks.

Experimental and Numerical Study on Grinding Temperature during Surface Grinding with Different Cooling Methods

2009 ◽  
Vol 416 ◽  
pp. 514-518 ◽  
Author(s):  
Qing Long An ◽  
Yu Can Fu ◽  
Jiu Hua Xu
Keyword(s):  
Numerical Study ◽  
Specific Energy Consumption ◽  
Ground Surface ◽  
Numerical Results ◽  
Surface Grinding ◽  
Grinding Temperature ◽  
Air Jet ◽  
The Difference ◽  
High Specific Energy ◽  
Cooling Methods

Grinding, characterized by its high specific energy consumption, may generate high grinding zone temperature. These can cause thermal damage to the ground surface and poor surface integrity, especially in the grinding of difficult-to-machine materials. In this paper, experimental and fem study on grinding temperature during surface grinding of Ti-6Al-4V with different cooling methods. A comparison between the experimental and numerical results is made. It is indicated that the difference between experimental and numerical results is below 15% and the numerical results can be considered reliable. Grinding temperature can be more effectively reduced with CPMJ than that with cold air jet and flood cooling method.

scholarly journals Growth, collapse and self-organized criticality in complex networks

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Yafeng Wang ◽  
Huawei Fan ◽  
Weijie Lin ◽  
Ying-Cheng Lai ◽  
Xingang Wang
Keyword(s):  
Complex Networks ◽  
Self Organized ◽  
Self Organized Criticality

NUMERICAL REEXAMINATION OF SUPERSYMMETRIC AND NONSUPERSYMMETRIC SU(5)-LIKE GRAND UNIFIED MODELS

1989 ◽  
Vol 04 (10) ◽  
pp. 2531-2559 ◽  
Author(s):  
DARIUSZ K. GRECH
Keyword(s):  
Numerical Analysis ◽  
Numerical Computation ◽  
Numerical Results ◽  
Yukawa Couplings ◽  
Loop Level ◽  
Grand Unified Theories ◽  
Unified Theories ◽  
Supersymmetric Particles ◽  
The Difference

The significance of numerical analysis in both nonsupersymmetric and supersymmetric Grand Unified Theories is pointed out. The exact analytical and numerical analysis we present shows a need of larger corrections to the values of unifying parameters, i.e. sin 2 θw, Mx, τp than those often quoted in literature. When an unmodified nonsupersymmetric version of SU(5) is considered we show that numerical computation allows some of the models still to be experimentally admissible. The difference between analytical and numerical results for the supersymmetric SU(5) model is also stressed. In particular, corrections due to the mass threshold of additional generations or supersymmetric particles are calculated both analytically and numerically at the two-loop level. We found them far more important for the final values of sin 2 θw, Mx and τp than the effects of Higgs-Yukawa couplings between scalars and fermions.

Communiqué Issues in MANET and VANET Protocols With Network Security Disquiet

2020 ◽  
pp. 195-220 ◽  
Author(s):  
Mamata Rath ◽  
Bibudhendu Pati ◽  
Jhum Swain
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Network Topology ◽  
Mobile Networks ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Course Of Action ◽  
Mobile Stations ◽  
The Difference ◽  
Hoc Networks

With faster expansion of mobile networks and quicker increment of web clients, more individuals approach worldwide data and communication innovation, because of which the issues of utilizing web as a worldwide stage and empowering the savvy protests and machines to coordinate, discuss, register, and ascertain slowly develops. In mobile ad-hoc networks (MANETs) and vehicular ad-hoc networks (VANET), the mobile stations and vehicles are self-reconfigurable as per the difference in network topology. Joint action between convenient centers is more basic because of the way that they confront significant difficulties, for example, frailty to work securely while protecting its advantages and performing secure guiding among center points. In the presence of vindictive hubs, one of the rule challenges in MANET is to plot ground-breaking security course of action that can shield MANET from different routing assaults.

scholarly journals The distribution of wasted spaces in the M/M/∞ queue with ranked servers

2008 ◽  
Vol 40 (03) ◽  
pp. 835-855 ◽  
Author(s):  
Eunju Sohn ◽  
Charles Knessl
Keyword(s):  
Probability Distribution ◽  
Numerical Results ◽  
Tail Behavior ◽  
Service Rates ◽  
The Difference

We consider the M/M/∞ queue with m primary servers and infinitely many secondary servers. All the servers are numbered and ordered. An arriving customer takes the lowest available server. We define the wasted spaces as the difference between the highest numbered occupied server and the total number of occupied servers. Letting ρ = λ0/μ be the ratio of arrival to service rates, we study the probability distribution of the wasted spaces asymptotically for ρ → ∞. We also give some numerical results and the tail behavior for ρ = O(1).

scholarly journals Characterizing the Complexity of Weighted Networks via Graph Embedding and Point Pattern Analysis

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 925
Author(s):  
Shuo Chen ◽  
Zhen Zhang ◽  
Chen Mo ◽  
Qiong Wu ◽  
Peter Kochunov ◽  
...  
Keyword(s):  
Complex Networks ◽  
Pattern Analysis ◽  
Brain Connectivity ◽  
Graph Embedding ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Healthy Controls ◽  
Weighted Networks ◽  
The Difference ◽  
Weighted Complex Networks

We propose a new metric to characterize the complexity of weighted complex networks. Weighted complex networks represent a highly organized interactive process, for example, co-varying returns between stocks (financial networks) and coordination between brain regions (brain connectivity networks). Although network entropy methods have been developed for binary networks, the measurement of non-randomness and complexity for large weighted networks remains challenging. We develop a new analytical framework to measure the complexity of a weighted network via graph embedding and point pattern analysis techniques in order to address this unmet need. We first perform graph embedding to project all nodes of the weighted adjacency matrix to a low dimensional vector space. Next, we analyze the point distribution pattern in the projected space, and measure its deviation from the complete spatial randomness. We evaluate our method via extensive simulation studies and find that our method can sensitively detect the difference of complexity and is robust to noise. Last, we apply the approach to a functional magnetic resonance imaging study and compare the complexity metrics of functional brain connectivity networks from 124 patients with schizophrenia and 103 healthy controls. The results show that the brain circuitry is more organized in healthy controls than schizophrenic patients for male subjects while the difference is minimal in female subjects. These findings are well aligned with the established sex difference in schizophrenia.

Well-defined solutions of the difference equation xn = xn−3kxn−4kxn−5k xn−kxn−2k(±1±xn−3kxn−4kxn−5k)

2019 ◽  
Vol 12 (06) ◽  
pp. 2040016
Author(s):  
Güven Çi̇nar ◽  
Ali̇ Geli̇şken ◽  
Ozan Özkan
Keyword(s):  
Difference Equation ◽  
Initial Conditions ◽  
Numerical Results ◽  
Real Numbers ◽  
The Difference

We investigate the behavior of well-defined solutions of the difference equation [Formula: see text] where the initial conditions [Formula: see text], [Formula: see text] are arbitrary nonzero real numbers. Also, we give some special results and numerical results.

scholarly journals Identification of key regulators in prostate cancer from gene expression datasets of patients

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Irengbam Rocky Mangangcha ◽  
Md. Zubbair Malik ◽  
Ömer Küçük ◽  
Shakir Ali ◽  
R. K. Brojen Singh
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Regulatory Pathways ◽  
Scale Free ◽  
Topological Parameters ◽  
Rich Club ◽  
Self Organized ◽  
Mutational Status ◽  
Interactome Network ◽  
The Rich

Abstract Identification of key regulators and regulatory pathways is an important step in the discovery of genes involved in cancer. Here, we propose a method to identify key regulators in prostate cancer (PCa) from a network constructed from gene expression datasets of PCa patients. Overexpressed genes were identified using BioXpress, having a mutational status according to COSMIC, followed by the construction of PCa Interactome network using the curated genes. The topological parameters of the network exhibited power law nature indicating hierarchical scale-free properties and five levels of organization. Highest degree hubs (k ≥ 65) were selected from the PCa network, traced, and 19 of them was identified as novel key regulators, as they participated at all network levels serving as backbone. Of the 19 hubs, some have been reported in literature to be associated with PCa and other cancers. Based on participation coefficient values most of these are connector or kinless hubs suggesting significant roles in modular linkage. The observation of non-monotonicity in the rich club formation suggested the importance of intermediate hubs in network integration, and they may play crucial roles in network stabilization. The network was self-organized as evident from fractal nature in topological parameters of it and lacked a central control mechanism.

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