Three billion years ago, more or less, life crossed a threshold and began moving toward a multicellular existence. Evidence from multiple directions is showing how this hard-to-fathom leap might have been less difficult than once believed. The evolutionary histories of some groups of organisms record numerous transitions from single-celled to multicellular forms, suggesting the hurdles could not have been so high. Genetic comparisons between simple multicellular organisms and their single-celled relatives have revealed that much of the molecular equipment needed for cells to band together and coordinate their activities may have been in place well before multicellularity evolved. And clever experiments have shown that in the test tube, single-celled life can evolve the beginnings of multicellularity in just a few hundred generations—an evolutionary instant. The end result: the incredible diversity of life seen today.
The power of many
Science 29 Jun 2018:
Vol. 360, Issue 6396, pp. 1388-1391
In the post year 2000 era the technologies that facilitate human communication have rapidly multiplied. While the adoption of these technologies has hugely impacted the behaviour and sociality of people, specifically in urban but also in rural environments, their "digital footprints" on different data bases have become an active area of research. The existence and accessibility of such large population-level datasets, has allowed scientists to study and model innate human tendencies and social patterns in an unprecedented way that complements traditional research approaches like questionnaire studies. In this review we focus on data analytics and modelling research – we call Social Physics – as it has been carried out using the mobile phone data sets to get insight into the various aspects of human sociality, burstiness in communication, mobility patterns, and daily rhythms.
Social Physics: Uncovering Human Behaviour from Communication
Kunal Bhattacharya, Kimmo Kaski
Diversity, understood as the variety of different elements or configurations that an extensive system has, is a crucial property that allows maintaining the system’s functionality in a changing environment, where failures, random events or malicious attacks are often unavoidable. Despite the relevance of preserving diversity in the context of ecology, biology, transport, finances, etc., the elements or configurations that more contribute to the diversity are often unknown, and thus, they can not be protected against failures or environmental crises. This is due to the fact that there is no generic framework that allows identifying which elements or configurations have crucial roles in preserving the diversity of the system. Existing methods treat the level of heterogeneity of a system as a measure of its diversity, being unsuitable when systems are composed of a large number of elements with different attributes and types of interactions. Besides, with limited resources, one needs to find the best preservation policy, i.e., one needs to solve an optimization problem. Here we aim to bridge this gap by developing a metric between labeled graphs to compute the diversity of the system, which allows identifying the most relevant components, based on their contribution to a global diversity value. The proposed framework is suitable for large multiplex structures, which are constituted by a set of elements represented as nodes, which have different types of interactions, represented as layers. The proposed method allows us to find, in a genetic network (HIV-1), the elements with the highest diversity values, while in a European airline network, we systematically identify the companies that maximize (and those that less compromise) the variety of options for routes connecting different airports.
Assessing diversity in multiplex networks
L.C. Carpi, T.A. Schieber, P.M. Pardalos, G. Marfany, C. Masoller, A. Díaz-Guilera, M.G. Ravetti
Life and other dissipative structures involve nonlinear dynamics that are not amenable to conventional analysis. Advances are being made in theory, modeling, and simulation techniques, but we do not have general principles for designing, controlling, stabilizing, or eliminating these systems. There is thus a need for tools that can transform high-level descriptions of these systems into useful guidance for their modification and design. In this article we introduce new methods for quantifying the viability of dissipative structures. We then present an information-theoretical approach for evaluating the quality of viability indicators, measurable quantities that covary with, and thus can be used to predict or influence, a system’s viability.
Methods for Measuring Viability and Evaluating Viability Indicators
Matthew D. Egbert and Juan Pérez-Mercader
Volume 24 | Issue 2 | Spring 2018
We examine salient trends of influenza pandemics in Australia, a rapidly urbanizing nation. To do so, we implement state-of-the-art influenza transmission and progression models within a large-scale stochastic computer simulation, generated using comprehensive Australian census datasets from 2006, 2011, and 2016. Our results offer the first simulation-based investigation of a population’s sensitivity to pandemics across multiple historical time points, and highlight three significant trends in pandemic patterns over the years: increased peak prevalence, faster spreading rates, and decreasing spatiotemporal bimodality. We attribute these pandemic trends to increases in two key quantities indicative of urbanization: population fraction residing in major cities, and international air traffic. In addition, we identify features of the pandemic’s geographic spread that can only be attributed to changes in the commuter mobility network. The generic nature of our model and the ubiquity of urbanization trends around the world make it likely for our results to be applicable in other rapidly urbanizing nations.
Vulnerability to pandemics in a rapidly urbanizing society
Cameron Zachreson, Kristopher M. Fair, Oliver M. Cliff, Nathan Harding, Mahendra Piraveenan, Mikhail Prokopenko