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H. Eugene Stanley

Researcher at Boston University

Publications -  1208
Citations -  134813

H. Eugene Stanley is an academic researcher from Boston University. The author has contributed to research in topics: Complex network & Phase transition. The author has an hindex of 154, co-authored 1190 publications receiving 122321 citations. Previous affiliations of H. Eugene Stanley include University of North Carolina at Chapel Hill & Wesleyan University.

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Asymmetric interdependent networks with multiple-dependence relation.

TL;DR: A two-layered asymmetric interdependent network (AIN) model is proposed to address the robustness of interdependent networks with multiple-dependence (MD) relation, and a heuristic theory based on message-passing approach is developed to understand the structural feature of inter dependent networks.
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Density anomalies and reentrant spinodal behavior

TL;DR: In this paper, a lattice model that displays anomalous density behavior and exhibits a reentrant spinodal is developed, and the interplay between local energy and local entropy is found to control the thermodynamics of the system.
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Clustering of identical oligomers in coding and noncoding DNA sequences.

TL;DR: A quantitative method for analyzing repetitions of identical short oligomers in coding and noncoding DNA sequences for primate, mammal, vertebrate, rodent, invertebrate and plant taxonomic partitions finds that some oligomer "cluster" more than they would if randomly distributed, while other oligomers "repel" each other.
Posted Content

Predicting the rise of right-wing populism in response to unbalanced immigration

TL;DR: Analyzing poll data from a group of EU countries affected by the recent migrant crisis, it is found that over the last three years the percentage of right-wing (RW) populist voters in a given country depends on the prevalence of immigrants in this country’s population and the total immigration inflow into the entire EU.
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From the eden model to the kinetic growth walk: A generalized growth model with a finite lifetime of growth sites

TL;DR: In this article, a scaling theory for the time evolution of the mean end-to-end distance between the seed and the last-added site, and for the average number of growth sites by which the kinetics of the growth process can be characterized is presented.