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It sounds like a great idea: experimentally mutate a rare but deadly virus so that scientists can do a better job of recognizing dangerous emerging strains. But it also sounds like a terrible idea — the studies could create a virus that is easier to transmit and produce findings that are useful to bioterrorists.
Controversial research: Good science bad science
Geoff Brumfiel
Nature 484, 432–434 (26 April 2012) http://dx.doi.org/10.1038/484432a
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Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to adaptive success. This target article critically examines this “hierarchical prediction machine” approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action.
Whatever next? Predictive brains, situated agents, and the future of cognitive science Behavioral and Brain Sciences / Volume 36 / Issue 03 / June 2013, pp 181-204 Delete the scoop?
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A small but growing number of people are finding interesting parallels between ecosystems as studied by ecologists (think of a Savanna or the Amazon rain forest or a Coral reef) and tumours1-3. The idea of viewing cancer from an ecological perspective has many implications but fundamentally, it means that we should not see cancer just as a group of mutated cells. A more useful definition of cancer is to consider it a disruption in the complex balance of many interacting cellular and microenvironmental elements in a specific organ. This perspective means that organs undergoing carcinogenesis should be seen as sophisticated ecosystems in homeostasis that cancer cells can disrupt. It also makes cancer seem even more complex but may ultimately provides isights that make it more treatable. Here we discuss how ecological principles can be used to better understand cancer progression and treatment, using several mathematical and computational models to illustrate our argument.
Exploiting ecological principles to better understand cancer progression and treatment David Basanta, Alexander R. A. Anderson Delete the scoop?
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We make use of information provided in the titles and abstracts of over half a million publications that were published by the American Physical Society during the past 119 years. By identifying all unique words and phrases and determining their monthly usage patterns, we obtain quantifiable insights into the trends of physics discovery from the end of the 19th century to today. We show that the magnitudes of upward and downward trends yield heavy-tailed distributions, and that their emergence is due to the Matthew effect. This indicates that both the rise and fall of scientific paradigms is driven by robust principles of self-organization. Data also confirm that periods of war decelerate scientific progress, and that the later is very much subject to globalization.
Self-organization of progress across the century of physics Matjaz Perc Delete the scoop?
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Buildings that consume no outside energy are being developed today -- with existing technology. So much innovative work has been done in green building that a growing number of people are now shifting their focus from means to ends. Their goal: Create buildings that generate as much energy as they need to operate, called net-zero energy buildings (NZEB). Efforts to achieve NZEB are underway in all sectors -- government, academia, the military, not-for-profits and business -- and at all scales: residential, community and commercial. While it is still early days, the results have been impressive. Delete the scoop?
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We map cell-state transition rules of elementary cellular automata (ECA) onto the cognitive control versus schizotypy spectrum phase space and interpret cellular automaton behaviour in terms of creativity. To implement the mapping we draw analogies between a degree of schizotypy and generative diversity of ECA rules, and between cognitive control and robustness of ECA rules (expressed via Derrida coefficient). We found that null and fixed point ECA rules lie in the autistic domain and chaotic rules are 'schizophrenic'. There are no highly articulated 'creative' ECA rules. Rules closest to 'creativity' domains are two-cycle rules exhibiting wave-like patterns in the space-time evolution.
On Creativity of Elementary Cellular Automata Andrew Adamatzky, Andrew Wuensche Delete the scoop?
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So what would it mean for us? For a person – start feeling as part of the whole body or real-time sensor/motor cell of entire humanity organism, with every your search query, email, chat message or mouse click making it a bit more clever and strong, and every your action to some extent inspired by it. For software developers – get ready for emerging market of intellectual agent software (with first lonely players like Siri, Google Now and Sherpa), either keeping in mind business model of a «pilot fish», operating in biocenosis with one of the «Big Sharks» or having a good exit strategy for the case when your functionality may get on the way of some of major players (like it has happened to Yandex Wonder). For business – for competitive business promotion, understand how to craft «double-sided» web pages looking attractive for fellow people on one side and rich of true semantic markup on the other side. That kind of markup, invisible to human eye (see http://schema.org/ for more details) is to be indexed by «semantic crawler» at Google, collecting the thought-food for its Knowledge Graph — so that your site could get returned to user as single right answer on user's query, instead of being on 10th row of second page of search results. For government – be clear that ability to enable national projects of intellectual globalization might turn into a key for national security in the very close future. That does not necessarily mean any governmental funding of certain developments, as we have seen couple business enterprises managed to capture the third of the world in few years, so the most efficient option would be creation of appropriate business environments for high technology and information technology businesses within national borders. For humanity – get ready to pass through the next (since invention of computers and internet) pivotal point of development, with all coming surprises, frustrations and openings of new opportunities. For evolution – prepare to record forthcoming meta-system transition (since assembly of atoms in the molecule, molecules in the cell, cells into organism and neurons in the brain) in the Universe's diary book. Delete the scoop?
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It is conventional in labor economics to treat all workers who are seeking new jobs as belonging to a labor pool, and all firms that have job vacancies as an employer pool, and then match workers to jobs. Here we develop a new approach to study labor and firm dynamics. By combining the emerging science of networks with newly available employment micro-data, comprehensive at the level of whole countries, we are able to broadly characterize the process through which workers move between firms. Specifically, for each firm in an economy as a node in a graph, we draw edges between firms if a worker has migrated between them, possibly with a spell of unemployment in between. An economy's overall graph of firm-worker interactions is an object we call the labor flow network (LFN). This is the first study that characterizes a LFN for an entire economy. We explore the properties of this network, including its topology, its community structure, and its relationship to economic variables. It is shown that LFNs can be useful in identifying firms with high growth potential. We relate LFNs to other notions of high performance firms. Specifically, it is shown that fewer than 10% of firms account for nearly 90% of all employment growth. We conclude with a model in which empirically-salient LFNs emerge from the interaction of heterogeneous adaptive agents in a decentralized labor market.
Guerrero OA, Axtell RL (2013) Employment Growth through Labor Flow Networks. PLoS ONE 8(5): e60808. http://dx.doi.org/10.1371/journal.pone.0060808 Delete the scoop?
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Logic gates evoke images of circuit boards, but cells are arguably equally good in relying on logic computations. A classic example is the Lac operon, which activates itself upon the condition “lactose AND NOT glucose” (1). In recent years, there have been multiple reports on rationally designed, genetically encoded logic gates and circuits in living cells (2). Just like the Lac operon, these gates receive two or more molecular signals (inputs) and generate a product (output) whose level is logically linked to the inputs. Sixteen different logic connections are possible with two inputs and one output, but many of these operations have remained refractory to rational design. The trickiest of these gates usually make general statements about the inputs without referring to their exact values, such as “both inputs are the same” (an XNOR gate) or “two inputs are different” (an XOR gate). Two studies, one on page 599 of this issue by Bonnet et al. (3) and one by Siuti et al. (4), describe approaches that produce any of the 16 gates, including the notorious XNOR and XOR, in a compact manner by making relatively minor tweaks to the gates' genetic building blocks.
Recombinatorial Logic Science 3 May 2013: Delete the scoop?
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The study of scientific models has become an active and important focus in history and philosophy of science, and to a lesser extent in sociology of science. Such attention acknowledges that models are central to scientific practice and that they are distinct from both theory and data, but there is a growing realization that modeling practices differ between and within disciplines. This special issue uses this realization to extend the discussion on models into new areas and different uses in the human and social sciences.
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Task-partitioning is an important organisational principle in insect colonies and is thought to increase colony efficiency. In task-partitioning, tasks such as the collection of resources are divided into subtasks in which the material is passed from one worker to another. We used an agent-based simulation model to explore how non-random interactions during task-partitioning with direct transfer affect colony work efficiency. Delete the scoop?
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The fixation of cooperation among unrelated individuals is one of the fundamental problems in biology and social sciences. It is investigated by means of public goods games, the generalization of the prisoner's dilemma to more than two players. In compulsory public goods games, defect is the dominant strategy, while voluntary participation overcomes the social dilemma by allowing a cyclic coexistence of cooperators, defectors, and non-participants. [...] a milder punishing mechanism, where defectors only risk a fixed penalty per round—as in many real situations—and the cost of punishment is shared among the punishers. The payoffs for the four strategies—cooperate, defect, abstain, and cooperate-&-punish—are derived and the corresponding replicator dynamics analyzed in full detail. Delete the scoop?
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Starting in the 19th century (...) and culminating with a 1963 paper by MIT meteorologist Edward Lorenz (...), a series of developments revealed that the notion of deterministic predictability, although appealingly intuitive, is in practice false for most systems. Small uncertainties in an initial state can indeed become large errors in a final one. Even simple systems for which all forces are known can behave unpredictably. Determinism, surprisingly enough, does not preclude chaos.
Chaos at fifty Delete the scoop?
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Social networking services (e.g., Twitter, Facebook) are now major sources of World Wide Web (called “Web”) dynamics, together with Web search services (e.g., Google). These two types of Web services mutually influence each other but generate different dynamics. In this paper, we distinguish two modes of Web dynamics: the reactive mode and the default mode. It is assumed that Twitter messages (called “tweets”) and Google search queries react to significant social movements and events, but they also demonstrate signs of becoming self-activated, thereby forming a baseline Web activity. We define the former as the reactive mode and the latter as the default mode of the Web. In this paper, we investigate these reactive and default modes of the Web's dynamics using transfer entropy (TE). The amount of information transferred between a time series of 1,000 frequent keywords in Twitter and the same keywords in Google queries is investigated across an 11-month time period.(...)
Oka M, Ikegami T (2013) Exploring Default Mode and Information Flow on the Web. PLoS ONE 8(4): e60398. http://dx.doi.org/10.1371/journal.pone.0060398 
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This paper explored how to define the Web's reactive and default modes by information transfer by computing TE to characterize the inherent structure of the Web dynamics. First, we defined whether a keyword is in default or reactive mode in terms of how burst events are caused internally or externally. There are reports on YouTube page views and Twitter hashtags, whereby internally and externally caused bursts are distinguished by certain criteria[17], [19]. Our analysis of the number of bursts in relation to keyword frequency revealed that while low-frequency keywords tend to burst more, keywords are more influenced by real-world events, when compared to high-frequency keywords. From this observation, we defined that high-frequency keywords form the Web's default mode network and low-frequency keywords constitute the Web's reactive mode. When analyzing the information transfer between Google and Twitter, we found that information is mostly transferred from Twitter to Google and that this tendency is more apparent for high-frequency keywords than for low-frequency keywords. We also studied the information flow network formed among Twitter keywords by taking the keywords as nodes and flow direction as the edges of a network. We found that high-frequency keywords tend to become information sources and low-frequency keywords tend to become information sinks. These findings suggest that we can use high-frequency keywords (or default mode of the Web) to reduce uncertainty with the externally driven low-frequency keywords (or reactive mode of the Web). However, it is fair to assume that frequently searched keywords in Google are different from the frequent keywords found on Twitter. Thus, if we investigated the high-frequency keywords found in Google queries, the results may be different. The concept of reactive and default modes originates from brain science [20]–[22]. A brain region responsible for a given task is identified by measuring the neural activity that is observably higher compared to the baseline activity. Raichle et al. [23] examined the baseline activity by analyzing the regions that become less active when a specific task is given. This successful approach uncovered some remarkable perspectives and characteristics of the default mode; based on Buckner's [22] and Raichle's [24] reviews, these are: i) the area associated with the default mode is found as the integration of various subsystems in the brain - the medial prefrontal cortex and posterior cingulate cortex subsystems seem to play central roles. ii) The neural activity of the aforementioned subsystems were observed as noisy fMRI signals at a low frequency of about 0.1 Hz or less, showing global synchronization. iii) The default mode is to do with spontaneous cognition e.g., day dreaming and internal thoughts such as future planning. iv) The activity of the default mode is anti-correlated with the other brain regions that are responsible for focusing attention on the external world; and v) the brain region associated with the default mode overlaps with those involved in the construction of episodic memory. This notion of the default mode can be generalized for any living systems with or without brain systems. In the case of the Web system, it can be said that 1) frequent keywords constitute the default mode (mostly everyday keywords), 2) these frequent keywords display less frequent bursting behaviors and are an information source for other keywords, 3) the default mode may help reduce uncertainty in the entire Web system, and 4) the default mode comprises quasi-periodic time series. From this comparison with the default mode network in brain systems, and in particular with the possibility that high-frequency keywords may help to predict essentially unpredictable events, it becomes apparent the Web's default mode may have the same property as the default modes in the brain. Differentiating between these two modes, the reactive and the default, provides a useful perspective for understanding Web dynamics and predicting the future of bursting behavior in the time series of keyword frequencies in tweets in Twitter, as well as in the time series of search queries in Google. With respect to the examples of complex networks in general, we believe that the default mode is key for understanding autonomy in complex systems in general. Any autonomous system (e.g., robots) possesses primitive forms of the default mode with different time scales [25]. Delete the scoop?
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A common goal in the control of a large network is to minimize the number of driver nodes or control inputs. Yet, the physical determination of control signals and the properties of the resulting control trajectories remain widely underexplored. Here we show that (i) numerical control fails in practice even for linear systems if the controllability Gramian is ill conditioned, which occurs frequently even when existing controllability criteria are satisfied unambiguously, (ii) the control trajectories are generally nonlocal in the phase space, and their lengths are strongly anti-correlated with the numerical success rate and number of control inputs, and (iii) numerical success rate increases abruptly from zero to nearly one as the number of control inputs is increased, a transformation we term numerical controllability transition. This reveals a trade-off between nonlocality of the control trajectory in the phase space and nonlocality of the control inputs in the network itself. The failure of numerical control cannot be overcome in general by merely increasing numerical precision—successful control requires instead increasing the number of control inputs beyond the numerical controllability transition.
Controllability Transition and Nonlocality in Network Control Delete the scoop?
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Life on Earth is perhaps greater than three and a half billion years old and it would appear that once it started it never stopped. During this period a number of dramatic shocks and drivers have affected the Earth. These include the impacts of massive asteroids, runaway climate change and increases in brightness of the Sun. Has life on Earth simply been lucky in withstanding such perturbations? Are there any self-regulating or homeostatic processes operating in the Earth system that would reduce the severity of such perturbations? If such planetary processes exist, to what extent are they the result of the actions of life? In this study, we show how the regulation of environmental conditions can emerge as a consequence of life's effects. If life is both affected by and affects it environment, then this coupled system can self-organise into a robust control system that was first described during the early cybernetics movement around the middle of the twentieth century. Our findings are in principle applicable to a wide range of real world systems - from microbial mats to aquatic ecosystems up to and including the entire biosphere.
Dyke JG, Weaver IS (2013) The Emergence of Environmental Homeostasis in Complex Ecosystems. PLoS Comput Biol 9(5): e1003050. http://dx.doi.org/10.1371/journal.pcbi.1003050 Delete the scoop?
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We discuss how spreading processes on temporal networks are impacted by the shape of their inter-event time distributions. Through simple mathematical arguments and toy examples, we find that the key factor is the ordering in which events take place, a property that tends to be affected by the bulk of the distributions and not only by their tail, as usually considered in the literature. We show that a detailed modeling of the temporal patterns observed in complex networks can change dramatically the properties of a spreading process, such as the ergodicity of a random walk process or the persistence of an epidemic.
Burstiness and spreading on temporal networks Renaud Lambiotte, Lionel Tabourier, Jean-Charles Delvenne Delete the scoop?
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Plants represent almost 99.9% of the biomass of our planet. This means that virtually every environment that can be colonized by life has been explored and populated by plants. To achieve such amazing results while being unable to move from the site of seed germination, plants have evolved an arsenal of solutions that make them suitable for life in the most demanding and extreme conditions. In addition, it is well established that plants are able to show considerable plasticity in their morphology and physiology in response to variability within their environment and to survive extremely diverse environmental conditions and stresses (Fujita et al (2006)). Thus the mechanical properties of plants, the morphology of their structures and their characteristic movements represent a goldmine of solutions that, with appropriate investigation, could be used to obtain new design rules for advanced bioinspired systems and materials in countless applications. Meanwhile, advances in technology, partly related to the adoption of such bio-inspired approaches in design, are opening new opportunities for the application of bioinspired artefacts in biological research.
Smart solutions from the plant kingdom Barbara Mazzolai and Stefano Mancuso 2013 Bioinspir. Biomim. 8 020301 http://dx.doi.org/10.1088/1748-3182/8/2/020301
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One area in which we have made great progress is in discovering the physical or neural correlates of consciousness – what consciousness in the brain "looks like", you might say. One way to investigate this question is to see what changes when consciousness is reduced or absent, as happens when people are in a vegetative state, with no sign of awareness. Brain scans show that such people usually have damage to the thalamus, a relay centre located smack-bang in the middle of the brain. Another common finding is damage to the connections between the thalamus and the prefrontal cortex, a region at the front of the brain, generally responsible for high-level complex thought. Delete the scoop?
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Twitter, even more than many other social media tools, can feel disconnected from the real world. But a group of students and professors at research site Floating Sheep have built a comprehensive map of some of Twitter's most distasteful content: the racist, homophobic, or ableist slurs that can proliferate online. Called Geography of Hate, the interactive map charts ten relatively common slurs across the continental US, either by general category or individually. Looking at the whole country, you'll often see a mass of red or what the map's creators call a "blue smog of hate." Zooming in, however, patches appear over individual regions or cities; some may be predictable, while others are not. Delete the scoop?
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Flies are among the most agile flying creatures on Earth. To mimic this aerial prowess in a similarly sized robot requires tiny, high-efficiency mechanical components that pose miniaturization challenges governed by force-scaling laws, suggesting unconventional solutions for propulsion, actuation, and manufacturing. To this end, we developed high-power-density piezoelectric flight muscles and a manufacturing methodology capable of rapidly prototyping articulated, flexure-based sub-millimeter mechanisms. We built an 80-milligram, insect-scale, flapping-wing robot modeled loosely on the morphology of flies. Using a modular approach to flight control that relies on limited information about the robot’s dynamics, we demonstrated tethered but unconstrained stable hovering and basic controlled flight maneuvers. The result validates a sufficient suite of innovations for achieving artificial, insect-like flight.
Controlled Flight of a Biologically Inspired, Insect-Scale Robot Science 3 May 2013: Delete the scoop?
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The cosmological natural selection (CNS) hypothesis holds that the fundamental constants of nature have been fine-tuned by an evolutionary process in which universes produce daughter universes via the formation of black holes. Here, we formulate the CNS hypothesis using standard mathematical tools of evolutionary biology. Specifically, we capture the dynamics of CNS using Price's equation, and we capture the adaptive purpose of the universe using an optimization program. We establish mathematical correspondences between the dynamics and optimization formalisms, confirming that CNS acts according to a formal design objective, with successive generations of universes appearing designed to produce black holes.
Cosmological natural selection and the purpose of the universe Andy Gardner, Joseph P. Conlon Complexity, Early View Delete the scoop?
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In socially foraging species resource information can be shared between individuals, increasing foraging success. In ant colonies, nestmate recruitment allows high exploitation rates at known resources however, to maximise foraging efficiency this must be balanced with searching for new resources. Delete the scoop?
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This paper proposes a control framework for biological systems subject to dynamics that exhibit adaptive behavior under evolutionary pressures. The control framework was formulated based on evolutionary game based modeling, which integrates both the internal dynamics and the population dynamics. Delete the scoop?
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In the last few years, the number of papers devoted to applications of agent-based technologies to traffic and transportation engineering has grown enormously. Thus, it seems to be the appropriate time to shed light over the achievements of the last decade, on the questions that have been successfully addressed, as well as on remaining challenging issues. In the present paper, we review the literature related to the areas of agent-based traffic modelling and simulation, and agent-based traffic control and management. Later we discuss and summarize the main achievements and the challenges.
A review on agent-based technology for traffic and transportation The Knowledge Engineering Review Delete the scoop?
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Why did this interest and work in complexity not lead to major changes in management practices? There are, I think, a few major reasons that it didn't — and that also suggest that the overdue change might now finally take place.
Why Managers Haven't Embraced Complexity http://blogs.hbr.org/cs/2013/05/why_managers_havent_embraced_c.html Delete the scoop?
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