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10.1063/5.0007422 http://scihub22266oqcxt.onion/10.1063/5.0007422 32357655!7192348!32357655     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Chaos 2020 ; 30 (4): 041101 Nephropedia Template TP {{tp|p=32357655|t=2020. Growing networks with communities: A distributive link model |pdf=|usr=}}{{32357655}} gab.com Text Growing networks with communities: A distributive link model JO: Chaos http://www.kidney.de/pget.php?&tw=1&pmid=32357655 #FOAvip Evolution and popularity are two keys of the Barabasi-Albert model, which generates a power law distribution of network degrees. Evolving network generation models are important as they offer an explanation of both how and why complex networks (and scale-free networks, in particular) are ubiquitous. We adopt the evolution principle and then propose a very simple and intuitive new model for network growth, which naturally evolves modular networks with multiple communities. The number and size of the communities evolve over time and are primarily subjected to a single free parameter. Surprisingly, under some circumstances, our framework can construct a tree-like network with clear community structures-branches and leaves of a tree. Results also show that new communities will absorb a link resource to weaken the degree growth of hub nodes. Our models have a common explanation for the community of regular and tree-like networks and also breaks the tyranny of the early adopter; unlike the standard popularity principle, newer nodes and communities will come to dominance over time. Importantly, our model can fit well with the construction of the SARS-Cov-2 haplotype evolutionary network. Twit Text FOAVip Growing networks with communities: A distributive link model ????Chaos http://www.kidney.de/pget.php?&tw=1&pmid=32357655 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32357655 #FOAvip English Wikipedia <ref>{{Cite pmid|32357655}}</ref> Growing networks with communities: A distributive link model #MMPMID32357655 Shang KK; Yang B; Moore JM; Ji Q; Small M Chaos 2020[Apr]; 30 (4): 041101 PMID32357655show ga Evolution and popularity are two keys of the Barabasi-Albert model, which generates a power law distribution of network degrees. Evolving network generation models are important as they offer an explanation of both how and why complex networks (and scale-free networks, in particular) are ubiquitous. We adopt the evolution principle and then propose a very simple and intuitive new model for network growth, which naturally evolves modular networks with multiple communities. The number and size of the communities evolve over time and are primarily subjected to a single free parameter. Surprisingly, under some circumstances, our framework can construct a tree-like network with clear community structures-branches and leaves of a tree. Results also show that new communities will absorb a link resource to weaken the degree growth of hub nodes. Our models have a common explanation for the community of regular and tree-like networks and also breaks the tyranny of the early adopter; unlike the standard popularity principle, newer nodes and communities will come to dominance over time. Importantly, our model can fit well with the construction of the SARS-Cov-2 haplotype evolutionary network. |*Community Networks[MESH] |*Models, Theoretical[MESH] |Algorithms[MESH] |Biological Evolution[MESH]Growing networks with communities: A distributive link model (epmc).pdf DeepDyve Pubget Overpricing