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10.1038/s41598-017-08828-8 http://scihub22266oqcxt.onion/10.1038/s41598-017-08828-8 C5587719!5587719!28878381     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28878381&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Rep 2017 ; 7 (ä): ä Nephropedia Template TP {{tp|p=28878381|t=2017. Large order fluctuations, switching, and control in complex networks |pdf=|usr=}}{{28878381}} gab.com Text Large order fluctuations, switching, and control in complex networks JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=28878381 #FOAvip We propose an analytical technique to study large fluctuations and switching from internal noise in complex networks. Using order-disorder kinetics as a generic example, we construct and analyze the most probable, or optimal path of fluctuations from one ordered state to another in real and synthetic networks. The method allows us to compute the distribution of large fluctuations and the time scale associated with switching between ordered states for networks consistent with mean-field assumptions. In general, we quantify how network heterogeneity influences the scaling patterns and probabilities of fluctuations. For instance, we find that the probability of a large fluctuation near an order-disorder transition decreases exponentially with the participation ratio of a network?s principle eigenvector ? measuring how many nodes effectively contribute to an ordered state. Finally, the proposed theory is used to answer how and where a network should be targeted in order to optimize the time needed to observe a switch. Twit Text FOAVip Large order fluctuations, switching, and control in complex networks ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=28878381 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28878381 #FOAvip English Wikipedia <ref>{{Cite pmid|28878381}}</ref> Large order fluctuations, switching, and control in complex networks #MMPMID28878381 Hindes J; Schwartz IB Sci Rep 2017[]; 7 (ä): ä PMID28878381show ga We propose an analytical technique to study large fluctuations and switching from internal noise in complex networks. Using order-disorder kinetics as a generic example, we construct and analyze the most probable, or optimal path of fluctuations from one ordered state to another in real and synthetic networks. The method allows us to compute the distribution of large fluctuations and the time scale associated with switching between ordered states for networks consistent with mean-field assumptions. In general, we quantify how network heterogeneity influences the scaling patterns and probabilities of fluctuations. For instance, we find that the probability of a large fluctuation near an order-disorder transition decreases exponentially with the participation ratio of a network?s principle eigenvector ? measuring how many nodes effectively contribute to an ordered state. Finally, the proposed theory is used to answer how and where a network should be targeted in order to optimize the time needed to observe a switch. äLarge order fluctuations, switching, and control in complex networks (epmc).pdf DeepDyve Pubget Overpricing