Social media have quickly become a prevalent channel to access information, spread ideas, and influence opinions. However, it has been suggested that social and algorithmic filtering may cause exposure to less diverse points of view, and even foster polarization and misinformation. Here we explore and validate this hypothesis quantitatively for the first time, at the collective and individual levels, by mining three massive datasets of web traffic, search logs, and Twitter posts. Our analysis shows that collectively, people access information from a significantly narrower spectrum of sources through social media and email, compared to search. The significance of this finding for individual exposure is revealed by investigating the relationship between the diversity of information sources experienced by users at the collective and individual level. There is a strong correlation between collective and individual diversity, supporting the notion that when we use social media we find ourselves inside "social bubbles". Our results could lead to a deeper understanding of how technology biases our exposure to new information.
Measuring Online Social Bubbles Dimitar Nikolov, Diego F. M. Oliveira, Alessandro Flammini, Filippo Menczer
The quality of web sources has been traditionally evaluated using exogenous signals such as the hyperlink structure of the graph. We propose a new approach that relies on endogenous signals, namely, the correctness of factual information provided by the source. A source that has few false facts is considered to be trustworthy. The facts are automatically extracted from each source by information extraction methods commonly used to construct knowledge bases. We propose a way to distinguish errors made in the extraction process from factual errors in the web source per se, by using joint inference in a novel multi-layer probabilistic model. We call the trustworthiness score we computed Knowledge-Based Trust (KBT). On synthetic data, we show that our method can reliably compute the true trustworthiness levels of the sources. We then apply it to a database of 2.8B facts extracted from the web, and thereby estimate the trustworthiness of 119M webpages. Manual evaluation of a subset of the results confirms the effectiveness of the method.
Knowledge-Based Trust: Estimating the Trustworthiness of Web Sources Xin Luna Dong, Evgeniy Gabrilovich, Kevin Murphy, Van Dang, Wilko Horn, Camillo Lugaresi, Shaohua Sun, Wei Zhang
The lipid bilayer membrane, which is the foundation of life on Earth, is not viable outside of biology based on liquid water. This fact has caused astronomers who seek conditions suitable for life to search for exoplanets within the “habitable zone,” the narrow band in which liquid water can exist. However, can cell membranes be created and function at temperatures far below those at which water is a liquid? We take a step toward answering this question by proposing a new type of membrane, composed of small organic nitrogen compounds, that is capable of forming and functioning in liquid methane at cryogenic temperatures. Using molecular simulations, we demonstrate that these membranes in cryogenic solvent have an elasticity equal to that of lipid bilayers in water at room temperature. As a proof of concept, we also demonstrate that stable cryogenic membranes could arise from compounds observed in the atmosphere of Saturn’s moon, Titan, known for the existence of seas of liquid methane on its surface.
Membrane alternatives in worlds without oxygen: Creation of an azotosome James Stevenson, Jonathan Lunine, Paulette Clancy
For over half a century, the biological roles of nucleic acids as catalytic enzymes, intracellular regulatory molecules, and the carriers of genetic information have been studied extensively. More recently, the sequence-specific binding properties of DNA have been exploited to direct the assembly of materials at the nanoscale. Integral to any methodology focused on assembling matter from smaller pieces is the idea that final structures have well-defined spacings, orientations, and stereo-relationships. This requirement can be met by using DNA-based constructs that present oriented nanoscale bonding elements from rigid core units. Here, we draw analogy between such building blocks and the familiar chemical concepts of “bonds” and “valency” and review two distinct but related strategies that have used this design principle in constructing new configurations of matter.
Programmable materials and the nature of the DNA bond Matthew R. Jones, Nadrian C. Seeman, Chad A. Mirkin
A great deal of research to inform environmental conservation and management takes a predict-and-prescribe strategy in which improving forecasts about future states of ecosystems is the primary goal. But sufficiently thorough understanding of ecosystems needed to reduce deep uncertainties is probably not achievable, seriously limiting the potential effectiveness of the predict-and-prescribe approach. Instead, research should integrate more closely with policy development to identify the range of alternative plausible futures and develop strategies that are robust across these scenarios and responsive to unpredictable ecosystem dynamics.
Prediction, precaution, and policy under global change Daniel E. Schindler, Ray Hilborn
Corruption is one of the most serious obstacles for ecosystem management and biodiversity conservation. In particular, more than half of the loss of forested area in many tropical countries is due to illegal logging, with corruption implicated in a lack of enforcement. Here we study an evolutionary game model to analyze the illegal harvesting of forest trees, coupled with the corruption of rule enforcers.
Economic games such as the public goods game are increasingly being used to measure social behaviours in humans and non-human primates. The results of such games have been used to argue that people are pro-social, and that humans are uniquely altruistic, willingly sacrificing their own welfare in order to benefit others. However, an alternative explanation for the empirical observations is that individuals are mistaken, but learn, during the game, how to improve their personal payoff.
Contemporary complexity theory has been instrumental in providing novel rigorous definitions for some classic philosophical concepts, including emergence. In an attempt to provide an account of emergence that is consistent with complexity and dynamical systems theory, several authors have turned to the notion of constraints on state transitions. Drawing on complexity theory directly, this paper builds on those accounts, further developing the constraint-based interpretation of emergence and arguing that such accounts recover many of the features of more traditional accounts. We show that the constraint-based account of emergence also leads naturally into a meaningful definition of self-organization, another concept that has received increasing attention recently. Along the way, we distinguish between order and organization, two concepts which are frequently conflated. Finally, we consider possibilities for future research in the philosophy of complex systems, as well as applications of the distinctions made in this paper.
Self-Organization, Emergence, and Constraint in Complex Natural Systems Jonathan Lawhead
From glorious rainbows to the intricate mechanics of the human eye, light lies at the heart of phenomena that have fascinated scientists for millennia. Today, the latest optical technologies — from lasers to solar cells — harness light to advance physics and to serve society's needs.
To put light itself in the spotlight, the United Nations designated 2015 the International Year of Light and Light-based Technologies. The celebration is also pegged to a string of anniversaries: Augustin-Jean Fresnel's proposal in 1815 that light is a wave; James Clerk Maxwell's 1865 electromagnetic theory; Albert Einstein's 1915 general theory of relativity; and in 1965, discovery of the cosmic microwave background (CMB) radiation and the development of optical fibres for communication.
The planetary boundaries framework defines a safe operating space for humanity based on the intrinsic biophysical processes that regulate the stability of the Earth system. Here, we revise and update the planetary boundary framework, with a focus on the underpinning biophysical science, based on targeted input from expert research communities and on more general scientific advances over the past 5 years. Several of the boundaries now have a two-tier approach, reflecting the importance of cross-scale interactions and the regional-level heterogeneity of the processes that underpin the boundaries. Two core boundaries—climate change and biosphere integrity—have been identified, each of which has the potential on its own to drive the Earth system into a new state should they be substantially and persistently transgressed.
Planetary boundaries: Guiding human development on a changing planet Will Steffen, Katherine Richardson, Johan Rockström, Sarah E. Cornell, Ingo Fetzer, Elena M. Bennett, Reinette Biggs, Stephen R. Carpenter, Wim de Vries, Cynthia A. de Wit, Carl Folke, Dieter Gerten, Jens Heinke, Georgina M. Mace, Linn M. Persson, Veerabhadran Ramanathan, Belinda Reyers, and Sverker Sörlin Science 13 February 2015: 1259855 http://dx.doi.org/10.1126/science.1259855
Metasystem transitions are events representing the evolutionary emergence of a higher level of organization through the integration of subsystems into a higher “metasystem” (A1+A2+A3=B). Such events have occurred several times throughout the history of life (e.g., emergence of life, multicellular life, sexual reproduction). The emergence of new levels of organization has occurred within the human system three times, and has resulted in three broadly defined levels of higher control, producing three broadly defined levels of group selection (e.g., band/tribe, chiefdom/kingdom, nation-state/international). These are “Human Metasystem Transitions” (HMST). Throughout these HMST several common system-level patterns have manifested that are fundamental to understanding the nature and evolution of the human system, as well as our potential future development. First, HMST have been built around the control of three mostly distinct primary energy sources (e.g., hunting, agriculture, industry). Second, the control of new energy sources has always been achieved and stabilized by utilizing the evolutionary emergence of a more powerful information-processing medium (e.g., language, writing, printing press). Third, new controls emerge with the capability of organizing energy flows over larger expanses of space in shorter durations of time: bands/tribes controlled regional space and stabilized for hundreds of thousand of years, chiefdoms/kingdoms controlled semi-continental expanses of space and stabilized for thousands of years, and nation-states control continental expanses of space and have stabilized for centuries. This space-time component of hierarchical metasystem emergence can be conceptualized as the active compression of space-time-energy-matter (STEM compression) enabled by higher informational and energetic properties within the human system, which allow for more complex organization (i.e., higher subsystem integration). In this framework, increased information-energy control and feedback, and the consequent metasystem compression of space-time, represent the theoretical pillars of HMST theory. Most importantly, HMST theory may have practical application in modeling the future of the human system and the nature of the next human metasystem.
Human Metasystem Transition (HMST) Theory Cadell Last
Journal of Evolution and Technology - Vol. 25 Issue 1 – January 2015 - pgs 1-16
Understanding how information about external stimuli is transformed into behavior is one of the central goals of neuroscience. Here we characterize the information flow through a complete sensorimotor circuit: from stimulus, to sensory neurons, to interneurons, to motor neurons, to muscles, to motion. Specifically, we apply a recently developed framework for quantifying information flow to a previously published ensemble of models of salt klinotaxis in the nematode worm C. elegans. The models are grounded in the neuroanatomy and currently known neurophysiology of the worm. The unknown model parameters were optimized to reproduce the worm's behavior. Information flow analysis reveals several key principles underlying how the models operate: (1) Interneuron class AIY is responsible for integrating information about positive and negative changes in concentration, and exhibits a strong left/right information asymmetry. (2) Gap junctions play a crucial role in the transfer of information responsible for the information symmetry observed in interneuron class AIZ. (3) Neck motor neuron class SMB implements an information gating mechanism that underlies the circuit's state-dependent response. (4) The neck carries non-uniform distribution about changes in concentration. Thus, not all directions of movement are equally informative. Each of these findings corresponds to an experimental prediction that could be tested in the worm to greatly refine our understanding of the neural circuit underlying klinotaxis. Information flow analysis also allows us to explore how information flow relates to underlying electrophysiology. Despite large variations in the neural parameters of individual circuits, the overall information flow architecture circuit is remarkably consistent across the ensemble, suggesting that information flow analysis captures general principles of operation for the klinotaxis circuit.
"Information flow through a model of the C. elegans klinotaxis circuit" Eduardo J. Izquierdo, Paul L. Williams, Randall D. Beer arXiv:1502.04262, 2015 http://arxiv.org/abs/1502.04262
Antony van Leeuwenhoek wrote to the Royal Society of London in a letter dated September 17, 1683, describing “very little animalcules, very prettily a-moving,” which he had seen under a microscope in plaque scraped from his teeth. For more than three centuries after van Leeuwenhoek's observation, the human “microbiome”—the 100 trillion or so microbes that live in various nooks and crannies of the human body—remained largely unstudied, mainly because it is not so easy to extract and culture them in a laboratory. A decade ago the advent of sequencing technologies finally opened up this microbiological frontier. The Human Microbiome Project reference database, established in 2012, revealed in unprecedented detail the diverse microbial community that inhabits our bodies.
The Microbes Within David Grogan Nature 518, S2 (26 February 2015)
A key property of modern cities is increasing returns to scale—the finding that many socioeconomic outputs increase more rapidly than their population size. Recent theoretical work proposes that this phenomenon is the result of general network effects typical of human social networks embedded in space and, thus, is not necessarily limited to modern settlements. We examine the extent to which increasing returns are apparent in archaeological settlement data from the pre-Hispanic Basin of Mexico. We review previous work on the quantitative relationship between population size and average settled area in this society and then present a general analysis of their patterns of monument construction and house sizes. Estimated scaling parameter values and residual statistics support the hypothesis that increasing returns to scale characterized various forms of socioeconomic production available in the archaeological record and are found to be consistent with key expectations from settlement scaling theory. As a consequence, these results provide evidence that the essential processes that lead to increasing returns in contemporary cities may have characterized human settlements throughout history, and demonstrate that increasing returns do not require modern forms of political or economic organization.
Settlement scaling and increasing returns in an ancient society Scott G. Ortman, Andrew H. F. Cabaniss, Jennie O. Sturm, Luís M. A. Bettencourt
For an artificial agent to be considered truly intelligent it needs to excel at a variety of tasks considered challenging for humans. To date, it has only been possible to create individual algorithms able to master a single discipline — for example, IBM's Deep Blue beat the human world champion at chess but was not able to do anything else. Now a team working at Google's DeepMind subsidiary has developed an artificial agent — dubbed a deep Q-network — that learns to play 49 classic Atari 2600 'arcade' games directly from sensory experience, achieving performance on a par with that of an expert human player. By combining reinforcement learning (selecting actions that maximize reward — in this case the game score) with deep learning (multilayered feature extraction from high-dimensional data — in this case the pixels), the game-playing agent takes artificial intelligence a step nearer the goal of systems capable of learning a diversity of challenging tasks from scratch.
Human-level control through deep reinforcement learning • Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg & Demis Hassabis
What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita . This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method— the selective predictability scheme —in which we adopt a strategy similar to the methods of analogues , firstly introduced by Lorenz, to assess future evolution of countries.
Matthieu Cristelli , Andrea Tacchella, Luciano Pietronero
For many communicable diseases, knowledge of the underlying contact network through which the disease spreads is essential to determining appropriate control measures. When behavior change is the primary intervention for disease prevention, it is important to understand how to best modify network connectivity using the limited resources available to control disease spread. We describe and compare four algorithms for selecting a limited number of links to remove from a network
Indirect reciprocity means that my behavior towards you also depends on what you have done to others. Indirect reciprocity is associated with the evolution of social intelligence and human language. Most approaches to indirect reciprocity assume obligatory interactions, but here we explore optional interactions.
The question What is Complexity? has occupied a great deal of time and paper over the last 20 or so years. There are a myriad different perspectives and definitions but still no consensus. In this paper I take a phenomenological approach, identifying several factors that discriminate well between systems that would be consensually agreed to be simple versus others that would be consensually agreed to be complex - biological systems and human languages. I argue that a crucial component is that of structural building block hierarchies that, in the case of complex systems, correspond also to a functional hierarchy. I argue that complexity is an emergent property of this structural/functional hierarchy, induced by a property - fitness in the case of biological systems and meaning in the case of languages - that links the elements of this hierarchy across multiple scales. Additionally, I argue that non-complex systems "are" while complex systems "do" so that the latter, in distinction to physical systems, must be described not only in a space of states but also in a space of update rules (strategies) which we do not know how to specify. Further, the existence of structural/functional building block hierarchies allows for the functional specialisation of structural modules as amply observed in nature. Finally, we argue that there is at least one measuring apparatus capable of measuring complexity as characterised in the paper - the human brain itself.
We inspect a possible clustering structure of the corruption perception among 134 countries. Using the average linkage clustering, we uncover a well-defined hierarchy in the relationships among countries. Four main clusters are identified and they suggest that countries worldwide can be quite well separated according to their perception of corruption. Moreover, we find a strong connection between corruption levels and a stage of development inside the clusters. The ranking of countries according to their corruption perfectly copies the ranking according to the economic performance measured by the gross domestic product per capita of the member states. To the best of our knowledge, this study is the first one to present an application of hierarchical and clustering methods to the specific case of corruption.
Worldwide clustering of the corruption perception Michal Paulus, Ladislav Kristoufek
In the nearly 70 years since the first modern digital computer was built, the above specs have become all but synonymous with computing. But they need not be. A computer is defined not by a particular set of hardware, but by being able to take information as input; to change, or “process,” the information in some controllable way; and to deliver new information as output. This information and the hardware that processes it can take an almost endless variety of physical forms. Over nearly two centuries, scientists and engineers have experimented with designs that use mechanical gears, chemical reactions, fluid flows, light, DNA, living cells, and synthetic cells.
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