Just when leaders need fresh thinking and decisiveness, they tend to fall back on tried-and-true ways. Five actions can transform your relationship with
uncertainty and help you thrive.

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Yuanzhao Zhang, Vito Latora & Adilson E. Motter
Communications Physics volume 4, Article number: 195 (2021)

When describing complex interconnected systems, one often has to go beyond the standard network description to account for generalized interactions. Here, we establish a unified framework to simplify the stability analysis of cluster synchronization patterns for a wide range of generalized networks, including hypergraphs, multilayer networks, and temporal networks. The framework is based on finding a simultaneous block diagonalization of the matrices encoding the synchronization pattern and the network topology. As an application, we use simultaneous block diagonalization to unveil an intriguing type of chimera states that appear only in the presence of higher-order interactions. The unified framework established here can be extended to other dynamical processes and can facilitate the discovery of emergent phenomena in complex systems with generalized interactions. Recent studies have shown that complex systems are often best represented by generalized networks such as hypergraphs, multilayer networks, and temporal networks. Here, the authors propose a unified framework to investigate cluster synchronization patterns in generalized networks and demonstrate the existence of chimera states that emerge exclusively in the presence of higher-order interactions.

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Pratyush K Kollepara, M.Sc, Alexander F Siegenfeld, S.B, Nassim Nicholas Taleb, Ph.D, Yaneer Bar-Yam, Ph.D

Journal of Travel Medicine, taab144

Background: Pre-pandemic empirical studies have produced mixed statistical results on the effectiveness of masks against respiratory viruses, leading to confusion that may have contributed to organizations such as the WHO and CDC initially not recommending that the general public wear masks during the COVID-19 pandemic.

Methods: A threshold-based dose–response curve framework is used to analyse the effects of interventions on infection probabilities for both single and repeated exposure events. Empirical studies on mask effectiveness are evaluated with a statistical power analysis that includes the effect of adherence to mask usage protocols.

Results: When the adherence to mask-usage guidelines is taken into account, the empirical evidence indicates that masks prevent disease transmission: all studies we analysed that did not find surgical masks to be effective were under-powered to such an extent that even if masks were 100% effective, the studies in question would still have been unlikely to find a statistically significant effect. We also provide a framework for understanding the effect of masks on the probability of infection for single and repeated exposures. The framework demonstrates that masks can have a disproportionately large protective effect and that more frequently wearing a mask provides super-linearly compounding protection.

Conclusions: This work shows (1) that both theoretical and empirical evidence is consistent with masks protecting against respiratory infections and (2) that nonlinear effects and statistical considerations regarding the percentage of exposures for which masks are worn must be taken into account when designing empirical studies and interpreting their results.

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City planners and urban policy makers require simulation models to understand, predict, design and manage urban areas so that cities can become more sustainable, equitable and efficient. Recently, the idea that one might build ‘digital twins’ of cities has captured the imagination of many scientists, engineers and policy makers. To unleash the full potential of data, science, and technology, such an approach requires a clear idea of how similar a digital twin would have to be to the system of interest and in what way. We thus argue that we urgently need theories and methods from complexity science to guide the development and use of digital twins. Different applications-such as the avoidance of traffic congestion or the simulation of emergent social segregation-may actually require different kinds of data and different kinds of twins. Hence, the complexity science approach considers different perspectives on cities which-to some extent-evolve and self-organize themselves like living systems.

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