scholarly article | Q13442814 |
P819 | ADS bibcode | 2019PNAS..116...23Z |
P356 | DOI | 10.1073/PNAS.1801545116 |
P932 | PMC publication ID | 6320510 |
P698 | PubMed publication ID | 30591562 |
P50 | author | H. Eugene Stanley | Q870027 |
Gao Ziyou | Q15943024 | ||
Shlomo Havlin | Q1632961 | ||
Shengmin Guo | Q104107727 | ||
P2093 | author name string | Liang Gao | |
Daqing Li | |||
Guanwen Zeng | |||
P2860 | cites work | Networks: teasing out the missing links. | Q51887277 |
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Ising model in small-world networks | Q74632262 | ||
Structural and dynamical properties of long-range correlated percolation | Q77866899 | ||
Epidemic Spreading in Scale-Free Networks | Q27450819 | ||
Collective dynamics of 'small-world' networks | Q27861064 | ||
The hidden geometry of complex, network-driven contagion phenomena. | Q30356804 | ||
Percolation transition in dynamical traffic network with evolving critical bottlenecks | Q34456200 | ||
Universality in network dynamics | Q37367267 | ||
Traffic-driven epidemic spreading in finite-size scale-free networks | Q37385972 | ||
Universal resilience patterns in complex networks | Q39287725 | ||
A global map of travel time to cities to assess inequalities in accessibility in 2015. | Q48021512 | ||
P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
P6216 | copyright status | copyrighted | Q50423863 |
P433 | issue | 1 | |
P407 | language of work or name | English | Q1860 |
P1104 | number of pages | 6 | |
P304 | page(s) | 23-28 | |
P577 | publication date | 2019-01-02 | |
P1433 | published in | Proceedings of the National Academy of Sciences of the United States of America | Q1146531 |
P1476 | title | Switch between critical percolation modes in city traffic dynamics | |
P478 | volume | 116 |
Q91708471 | A simple contagion process describes spreading of traffic jams in urban networks |
Q99710846 | Anomalous supply shortages from dynamic pricing in on-demand mobility |
Q90408692 | Unraveling reaction-diffusion-like dynamics in urban congestion propagation: Insights from a large-scale road network |
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