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Samuel Johnson

Researcher at University of Birmingham

Publications -  67
Citations -  902

Samuel Johnson is an academic researcher from University of Birmingham. The author has contributed to research in topics: Artificial neural network & Population. The author has an hindex of 14, co-authored 60 publications receiving 672 citations. Previous affiliations of Samuel Johnson include The Turing Institute & Imperial College London.

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Entropic origin of disassortativity in complex networks.

TL;DR: This work defines the ensemble of correlated networks and obtains the associated Shannon entropy, providing a neutral model from which, in the absence of further knowledge regarding network evolution, one can obtain the expected value of correlations.
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Trophic coherence determines food-web stability

TL;DR: It is shown that trophic coherence—a hitherto ignored feature of food webs that current structural models fail to reproduce—is a better statistical predictor of linear stability than size or complexity, and it is proved that a maximally coherent network with constant interaction strengths will always be linearly stable.
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Resilience or robustness: identifying topological vulnerabilities in rail networks

TL;DR: The research conducted through this paper examines the interdependent rail networks in Greater London and surrounding commuter area and shows that resilience, not robustness, has a strong correlation with the consumer experience statistics.
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Looplessness in networks is linked to trophic coherence.

TL;DR: It is shown that trophic coherence, a structural property of ecosystems, is key to the extent of feedback in these as well as in many other systems, including networks related to genes, neurons, metabolites, words, computers, and trading nations.
Posted ContentDOI

Structures of the stator complex that drives rotation of the bacterial flagellum

TL;DR: Comparison to novel structures of other ion-driven motors indicates that this A5B2 architecture is fundamental to bacterial systems that couple energy from ion-flow to generate mechanical work at a distance, and suggests that such events involve rotation in the motor structures.