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Yamir Moreno
Researcher at University of Zaragoza
Publications - 394
Citations - 39008
Yamir Moreno is an academic researcher from University of Zaragoza. The author has contributed to research in topics: Complex network & Population. The author has an hindex of 75, co-authored 372 publications receiving 33623 citations. Previous affiliations of Yamir Moreno include International Centre for Theoretical Physics & Institute for Scientific Interchange.
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Complex networks: Structure and dynamics
TL;DR: The major concepts and results recently achieved in the study of the structure and dynamics of complex networks are reviewed, and the relevant applications of these ideas in many different disciplines are summarized, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
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Synchronization in complex networks
Alex Arenas,Alex Arenas,Albert Díaz-Guilera,Albert Díaz-Guilera,Jürgen Kurths,Jürgen Kurths,Yamir Moreno,Changsong Zhou +7 more
TL;DR: The advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology are reported and the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections are overviewed.
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Multilayer Networks
TL;DR: In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time, and include other types of complications.
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Evolutionary dynamics of group interactions on structured populations: a review.
TL;DR: The review particularly highlights that the study of the dynamics of group interactions, like several other important equilibrium and non-equilibrium dynamical processes in biological, economical and social sciences, benefits from the synergy between statistical physics, network science and evolutionary game theory.
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Epidemic outbreaks in complex heterogeneous networks
TL;DR: The large connectivity fluctuations usually found in these networks strengthen considerably the incidence of epidemic outbreaks and defines a new epidemiological framework characterized by a highly heterogeneous response of the system to the introduction of infected individuals with different connectivity.