Intelligent Connectivity for Seamless Urban Mobility explores a future vision for urban mobility which includes new choices for individual trip-making, better information for smarter decision-making, and system optimization to utilize infrastructure efficiently; all in service of fostering a seamless, safe and sustainable travel experience.
DNA origami—nanostructures created by programming the assembly of single-stranded DNA through base pairing—can create intricate structures. However, such structures lack the flexible and reversible interactions more typical of biomolecular recognition. Gerling et al. created three-dimensional DNA nanostructures that assemble though nucleotide base-stacking interactions (see the Perspective by Shih). These structures cycled from open to closed states with changes in salt concentration or temperature.
Dynamic DNA devices and assemblies formed by shape-complementary, non–base pairing 3D components Thomas Gerling, Klaus F. Wagenbauer, Andrea M. Neuner, Hendrik Dietz
To understand the contact patterns of a population -- who is in contact with whom, and when the contacts happen -- is crucial for modeling outbreaks of infectious disease. Traditional theoretical epidemiology assumes that any individual can meet any with equal probability. A more modern approach, network epidemiology, assumes people are connected into a static network over which the disease spreads. Newer yet, temporal network epidemiology, includes the time in the contact representations. In this paper, we investigate the effect of these successive inclusions of more information. Using empirical proximity data, we study both outbreak sizes from unknown sources, and from known states of ongoing outbreaks. In the first case, there are large differences going from a fully mixed simulation to a network, and from a network to a temporal network. In the second case, differences are smaller. We interpret these observations in terms of the temporal network structure of the data sets. For example, a fast overturn of nodes and links seem to make the temporal information more important.
Information content of contact-pattern representations and predictability of epidemic outbreaks Petter Holme
Humans are the most effective integrators and producers of information, directly and through the use of information-processing inventions. As these inventions become increasingly sophisticated, the substantive role of humans in processing information will tend toward capabilities that derive from our most complex cognitive processes, e.g., abstraction, creativity, and applied world knowledge. Through the advancement of human computation - methods that leverage the respective strengths of humans and machines in distributed information-processing systems - formerly discrete processes will combine synergistically into increasingly integrated and complex information processing systems. These new, collective systems will exhibit an unprecedented degree of predictive accuracy in modeling physical and techno-social processes, and may ultimately coalesce into a single unified predictive organism, with the capacity to address societies most wicked problems and achieve planetary homeostasis.
Human Computation and Convergence Pietro Michelucci
Mounting evidence indicates that our planet might experience runaway effects associated to rising temperatures and ecosystem overexploitation, leading to catastrophic shifts on short time scales. Remediation scenarios capable of counterbalancing these effects involve geoengineering, sustainable practices and carbon sequestration, among others. None of these scenarios seems powerful enough to achieve the desired restoration of safe boundaries. We hypothesise that synthetic organisms with the appropriate engineering design could be used to safely prevent declines in some stressed ecosystems and help improving carbon sequestration. Such schemes would include engineering mutualistic dependencies preventing undesired evolutionary processes. We hypothesise that some particular design principles introduce unescapable constraints to the engineered organisms that act as effective firewalls. Testing this designed organisms can be achieved by using controlled bioreactor models and accurate computational models including different scales (from genetic constructs and metabolic pathways to population dynamics). Our hypothesis heads towards a future anthropogenic action that should effectively act as Terraforming agents. It also implies a major challenge in the existing biosafety policies, since we suggest release of modified organisms as potentially necessary strategy for success.
Imagine millions of creatures settling on a new planet. How would they repopulate this new world? If they were viruses, they would choose five individuals, at random, to do the job. When viruses infect new cells within a host, they invade that cell with thousands of genomes, but only a small number, on the order of 4 or 5, are successfully replicated (Fig. 1). Why do viruses use this strategy, and how did this arise? A recent study in PLOS Biology by Shuhei Miyashita, Masayuki Ishikawa, and colleagues seeks to understand why cell-to-cell (also known as tissue) viral infection involves such a small number of genomes and how this is advantageous to the virus. Fascinatingly, the authors find that genomes are essentially determined at random, but through this inherently random—or stochastic—process, beneficial genomes are selected and defective genomes are expunged.
We have a limited understanding of the factors that make people influential and topics popular in social media. Are users who comment on a variety of matters more likely to achieve high influence than those who stay focused? Do general subjects tend to be more popular than specific ones? Questions like these demand a way to detect the topics hidden behind messages associated with an individual or a keyword, and a gauge of similarity among these topics. Here we develop such an approach to identi
This study investigates the counterintuitive emergence of self-regulation in the Russian construction sector. Despite its proclivity for centralizing political authority, the government acted as the catalyst for the delegation of regulatory powers to private industry groups. The article argues that a factor little considered in extant literature—namely, a weak and corrupt bureaucracy—is key to explaining why the normally control-oriented executive branch began to promote private governance despite industry's preference for continued state regulation. The article's signal contribution is to theoretically explain and empirically demonstrate how a government's prior inability to establish intrastate control over an ineffective and bribable public bureaucracy creates incentives for political authorities to search for alternative means for policy implementation outside of existing state agencies. These findings are important for understanding the impetus and logic behind particular regulatory shifts in countries where the state apparatus is both deficient and corrupt.
Top-Down Self-Organization: State Logics, Substitutional Delegation, and Private Governance in Russia Masha Hedberg
The exponential growth in the number of scientific papers makes it increasingly difficult for researchers to keep track of all the publications relevant to their work. Consequently, the attention that can be devoted to individual papers, measured by their citation counts, is bound to decay rapidly. In this work we make a thorough study of the life-cycle of papers in different disciplines. Typically, the citation rate of a paper increases up to a few years after its publication, reaches a peak and then decreases rapidly. This decay can be described by an exponential or a power law behavior, as in ultradiffusive processes, with exponential fitting better than power law for the majority of cases. The decay is also becoming faster over the years, signaling that nowadays papers are forgotten more quickly. However, when time is counted in terms of the number of published papers, the rate of decay of citations is fairly independent of the period considered. This indicates that the attention of scholars depends on the number of published items, and not on real time.
Attention decay in science Pietro Della Briotta Parolo, Raj Kumar Pan, Rumi Ghosh, Bernardo A. Huberman, Kimmo Kaski, Santo Fortunato
Evolution is driven by genetic mutations. While some mutations affect an organism’s ability to survive and reproduce, most are neutral and have no effect. Neutral mutations play an important role in the study of evolution because they generally accrue at a consistent rate over time. This result, first discovered 50 years ago, allows neutral mutations to be used as a “molecular clock” to estimate, for example, how long ago humans diverged from chimpanzees and bonobos. We used mathematical modeling to study how the rates of these molecular clocks are affected by the spatial arrangement of a population in its habitat. We find that asymmetry in this spatial structure can either slow down or speed up the rate at which neutral mutations accrue. This effect could potentially skew our estimates of past events from genetic data. It also has implications for a number of other fields. For example, we show that the architecture of intestinal tissue can limit the rate of genetic substitutions leading to cancer. We also show that the structure of social networks affects the rate at which new ideas replace old ones. Surprisingly, we find that most Twitter networks slow down the rate of idea replacement.
Allen B, Sample C, Dementieva Y, Medeiros RC, Paoletti C, Nowak MA. (2015) The Molecular Clock of Neutral Evolution Can Be Accelerated or Slowed by Asymmetric Spatial Structure. PLoS Comput Biol 11(2): e1004108. http://dx.doi.org/10.1371/journal.pcbi.1004108 ;
Following the emergence of a transmissible disease epidemic, interventions and resources need to be prioritized to efficiently control its spread. While the knowledge of the pattern of disease-transmission contacts among hosts would be ideal for this task, the continuously changing nature of such pattern makes its use less practical in real public health emergencies (or otherwise highly resource-demanding when possible). We show that in such situations critical knowledge to assess the real-time risk of infection can be extracted from past temporal contact data. An index expressing the conservation of contacts over time is proposed as an effective tool to prioritize interventions, and its efficiency is tested considering real data on livestock movements and on human sexual encounters.
The world is changing at an ever-increasing pace. And it has changed in a much more fundamental way than one would think, primarily because it has become more connected and interdependent than in our entire history. Every new product, every new invention can be combined with those that existed before, thereby creating an explosion of complexity: structural complexity, dynamic complexity, functional complexity, and algorithmic complexity. How to respond to this challenge?
Responding to Complexity in Socio-Economic Systems: How to Build a Smart and Resilient Society?
This paper presents a model of urban traffic congestion that allows for hypercongestion. Hypercongestion has fundamental importance for the costs of congestion and the effect of policies such as road pricing, transit provision and traffic management, treated in the paper. In the simplest version of the model, the unregulated Nash equilibrium is also the social optimum among a wide range of potential outcomes and any reasonable road pricing scheme will be welfare decreasing. Large welfare gains can be achieved through road pricing when there is hypercongestion and travelers are heterogeneous.
Fosgerau, Mogens (2015): Congestion in the bathtub.
It has been hypothesized that the evolution of modern human cognition was catalyzed by the development of jointly intentional modes of behaviour. From an early age (1-2 years), human infants outperform apes at tasks that involve collaborative activity. Specifically, human infants excel at joint action motivated by reasoning of the form "we will do X" (shared intentions), as opposed to reasoning of the form "I will do X [because he is doing X]" (individual intentions). The mechanism behind the evolution of shared intentionality is unknown. Here we formally model the evolution of jointly intentional action and show under what conditions it is likely to have emerged in humans. Modelling the interaction of hunter-gatherers as a coordination game, we find that when the benefits from adopting new technologies or norms are low but positive, the sharing of intentions does not evolve, despite being a mutualistic behaviour that directly benefits all participants. When the benefits from adopting new technologies or norms are high, such as may be the case during a period of rapid environmental change, shared intentionality evolves and rapidly becomes dominant in the population. Our results shed new light on the evolution of collaborative behaviours.
Shared intentions and the advance of cumulative culture in hunter-gatherers Simon D. Angus, Jonathan Newton
Inspiration for artificial biologically inspired computing is often drawn from neural systems. This article shows how to analyze neural systems using information theory with the aim of obtaining constraints that help to identify the algorithms run by neural systems and the information they represent. Algorithms and representations identified this way may then guide the design of biologically inspired computing systems. The material covered includes the necessary introduction to information theory and to the estimation of information-theoretic quantities from neural recordings. We then show how to analyze the information encoded in a system about its environment, and also discuss recent methodological developments on the question of how much information each agent carries about the environment either uniquely or redundantly or synergistically together with others. Last, we introduce the framework of local information dynamics, where information processing is partitioned into component processes of information storage, transfer, and modification – locally in space and time. We close by discussing example applications of these measures to neural data and other complex systems.
Perhaps the only good news from the tragic Ebola epidemic in Guinea, Sierra Leone, and Liberia is that it may serve as a wake-up call: we must prepare for future epidemics of diseases that may spread more effectively than Ebola. There is a significant chance that an epidemic of a substantially more infectious disease will occur sometime in the next 20 years; after all, we saw major epidemics during the 20th century, including the Spanish influenza epidemic of 1918–1919 and the ongoing pandemic of human immunodeficiency virus. In fact, of all the things that could kill more than 10 million people around the world, the most likely is an epidemic stemming from either natural causes or bioterrorism.
Functional networks, i.e. networks representing dynamic relationships between the components of a complex system, have been instrumental for our understanding of, among others, the human brain. Due to limited data availability, the multi-layer nature of numerous functional networks has hitherto been neglected, and nodes are endowed with a single type of links even when multiple relationships coexist at different physical levels. A relevant problem is the assessment of the benefits yielded by studying a multi-layer functional network, against the simplicity guaranteed by the reconstruction and use of the corresponding single layer projection. Here, I tackle this issue by using as a test case, the functional network representing the dynamics of delay propagation through European airports. Neglecting the multi-layer structure of a functional network has dramatic consequences on our understanding of the underlying system, a fact to be taken into account when a projection is the only available information.
Can we neglect the multi-layer structure of functional networks? Massimiliano Zanin
The Football World Cup as world's favorite sporting event is a source of both entertainment and overwhelming amount of data about the games played. In this paper we analyse the available data on football world championships since 1930 until today. Our goal is to rank the national teams based on all matches during the championships. For this purpose, we apply the PageRank with restarts algorithm to a graph built from the games played during the tournaments. Several statistics such as matches won and goals scored are combined in different metrics that assign weights to the links in the graph. Finally, our results indicate that the Random walk approach with the use of right metrics can indeed produce relevant rankings comparable to the FIFA official all-time ranking board.
PageRank Approach to Ranking National Football Teams Verica Lazova, Lasko Basnarkov
Population genetics studies the genetic composition of biological populations, and the changes in this composition that result from the action of four different processes: natural selection, random drift, mutation and migration. The modern evolutionary synthesis combines Darwin's thesis on natural selection and Mendel's theory of inheritance.
Time is divided by geologists according to marked shifts in Earth’s state. Recent global environmental changes suggest that Earth may have entered a new human-dominated geological epoch, the Anthropocene. Here we review the historical genesis of the idea and assess anthropogenic signatures in the geological record against the formal requirements for the recognition of a new epoch. The evidence suggests that of the various proposed dates two do appear to conform to the criteria to mark the beginning of the Anthropocene: 1610 and 1964. The formal establishment of an Anthropocene Epoch would mark a fundamental change in the relationship between humans and the Earth system.
Defining the Anthropocene Simon L. Lewis & Mark A. Maslin
From humans to social insects and bacteria, decision-making is often influenced by some form of collective signaling, be it quorum, information exchange, pledges or announcements. Here we investigate how such signaling systems evolve when collective action entails a public good, and how meanings co-evolve with individual choices, given Nature’s most prevalent states. We find a rich scenario, showing how natural selection is able to evolve a costly quorum signaling system that allows individuals to coordinate their action so as to provide the appropriate response to different states of Nature. We show that signaling robustly and selectively promotes cooperative collective action when coordinated action is most needed. In light of our results, and despite the complexity that collective action relying on quorum signaling may entail, it is not so surprising how signaling is a ubiquitous property of the living world.
Rule 1. Cultivate Lifelong Learning as a “Style of Thinking” That Concentrates on Fundamental Principles Rather Than on Facts Rule 2. Structure Your Learning to Ride the Information Tsunami Rather Than Drown in It Rule 3. Be Prepared to Compete and Interact with a Greater and More Rapidly Increasing Number of Scientists Than at Any Time in the Past Rule 4. Focus on the Future but Don’t Ignore the Past Rule 5. Look for the Personal Angle Rule 6. Learn from the Successes of Others Rule 7. Use Trial and Error to Find the Style of Learning That Suits You Rule 8. No Matter How Much Advice You Get and How Much Talent You Possess, It Is Still You Who Must Do the Learning and Put in the Time Rule 9. Have a Vision to Give You a General Direction Rule 10. Make Your Life Count: Struggle for Excellence
Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health.
Modeling infectious disease dynamics in the complex landscape of global health Hans Heesterbeek, et al.
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