The New Science of Cities presents a herculean attempt to bring together widely fragmented approaches to making sense of human social organization with the goal of eventually establishing a consolidated “science of cities” able to answer our questions. Michael Batty bases his argument on the interplay among space, dynamics, and relations. He holds that “to understand place, we must understand flows, and to understand flows we must understand networks.” Batty (a geographer at University College London) also stresses two other principles: an intrinsic order of scale determines a city's form and function, and a science of cities should not merely observe but also predict. The book draws on the work of urbanists, economists, mathematicians, and physicists as well as almost five decades of his own contributions to urban studies.
People rely on having persistent Internet connectivity from their homes and mobile devices. However, unlike links in the core of the Internet, the links that connect people's homes and mobile devices, known as "last-mile" links, are not redundant. As a result, the reliability of any given link is of paramount concern: when last-mile links fail, people can be completely disconnected from the Internet. In addition to lacking redundancy, Internet last-mile links are vulnerable to failure. Such links can fail because the cables and equipment that make up last-mile links are exposed to the elements; for example, weather can cause tree limbs to fall on overhead cables, and flooding can destroy underground equipment. They can also fail, eventually, because cellular last-mile links can drain a smartphone's battery if an application tries to communicate when signal strength is weak. In this dissertation, I defend the following thesis: By building on existing infrastructure, it is possible to (1) observe the reliability of Internet last-mile links across different weather conditions and link types; (2) improve the energy efficiency of cellular Internet last-mile links; and (3) provide an incrementally deployable, energy-efficient Internet last-mile downlink that is highly resilient to weather-related failures. I defend this thesis by designing, implementing, and evaluating systems.
Ashish Umre's insight:
Winner of the the 2013 ACM SIGCOMM Doctoral Dissertation Award
Deprived of sight, blind people manage to squeeze an amazing amount of information out of their other senses. Doing this requires their brains to do some reorganizing. To learn about some of these changes, scientists studied the brains of blind people who’ve learned to use an augmented reality system that converts images into soundscapes.
The system was invented in the early ’90s, but it’s not widely used. The way it works is a person puts on a pair of goggles with a built-in camera and software that converts images captured by the camera into sounds. For example, the pitch of the sound (high or low) indicates the vertical position of an object; the timing and duration of the sound indicate the object’s horizontal position and width (you can see and hear a demo of a similar technology here). For real world scenes, the sounds are complex — in fact, they sound a bit like a garbled transmission from an alien spacecraft.
But with enough practice people can learn to interpret the sounds and form a mental image of objects — including people — that appear in front of them.
Quorum sensing (QS) is a cell–cell communication system that controls gene expression in many bacterial species, mediated by diffusible signal molecules. Although the intracellular regulatory mechanisms of QS are often well-understood, the functional roles of QS remain controversial. In particular, the use of multiple signals by many bacterial species poses a serious challenge to current functional theories. Here, we address this challenge by showing that bacteria can use multiple QS signals to infer both their social (density) and physical (mass-transfer) environment. Analytical and evolutionary simulation models show that the detection of, and response to, complex social/physical contrasts requires multiple signals with distinct half-lives and combinatorial (nonadditive) responses to signal concentrations. We test these predictions using the opportunistic pathogen Pseudomonas aeruginosa and demonstrate significant differences in signal decay between its two primary signal molecules, as well as diverse combinatorial responses to dual-signal inputs. QS is associated with the control of secreted factors, and we show that secretome genes are preferentially controlled by synergistic “AND-gate” responses to multiple signal inputs, ensuring the effective expression of secreted factors in high-density and low mass-transfer environments. Our results support a new functional hypothesis for the use of multiple signals and, more generally, show that bacteria are capable of combinatorial communication.
A super-secure place for sensitive data to mingle could free companies to get the benefits of sharing it without risking leaks.
As companies from the financial sector to the health industry amass ever larger, more detailed databases of information about people, it is clear that combining different data sets can offer powerful insights. But to protect users’ privacy, many of these data sets stay locked up inside corporate firewalls.
Chipmaker Intel thinks it has a way to let valuable data be combined and analyzed without endangering anyone’s privacy. Its researchers are testing a super-secure data locker where a company could combine its sensitive data with that from another party without either side risking that raw information being seen or stolen.
The Final Volume of the Groundbreaking Trilogy on Agent-Based Modeling In this pioneering synthesis, Joshua Epstein introduces a new theoretical entity: Agent_Zero. This software individual, or "agent," is endowed with distinct emotional/affective, cognitive/deliberative, and social modules. Grounded in contemporary neuroscience, these internal components interact to generate observed, often far-from-rational, individual behavior. When multiple agents of this new type move and interact spatially, they collectively generate an astonishing range of dynamics spanning the fields of social conflict, psychology, public health, law, network science, and economics. Epstein weaves a computational tapestry with threads from Plato, Hume, Darwin, Pavlov, Smith, Tolstoy, Marx, James, and Dostoevsky, among others. This transformative synthesis of social philosophy, cognitive neuroscience, and agent-based modeling will fascinate scholars and students of every stripe. Epstein's computer programs are provided in the book or on its Princeton University Press website, along with movies of his "computational parables." Agent_Zero is a signal departure in what it includes (e.g., a new synthesis of neurally grounded internal modules), what it eschews (e.g., standard behavioral imitation), the phenomena it generates (from genocide to financial panic), and the modeling arsenal it offers the scientific community. For generative social science, Agent_Zero presents a groundbreaking vision and the tools to realize it.
We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are not effective and sufficient to contain them. The failure of many conventional approaches results from their neglection of feedback loops, instabilities and/or cascade effects, due to which equilibrium models do often not provide a good picture of the actual system behavior. However, the complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be understood by means of complexity science, which enables one to address the aforementioned problems more successfully. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.
How to Save Human Lives with Complexity Science Dirk Helbing, Dirk Brockmann, Thomas Chadefaux, Karsten Donnay, Ulf Blanke, Olivia Woolley-Meza, Mehdi Moussaid, Anders Johansson, Jens Krause, Sebastian Schutte, Matjaz Perc
The brain must extract linguistic bits like vowels and consonants from background acoustics, categorizing them, to make sense of what others say. Scientists have known that a brain region called the superior temporal gyrus (STG) plays a role; specifically, it helps map speech sounds possessing certain acoustic properties to their phonetic representations in the brain. But, scientists haven’t understood exactly how the process works, how the individual neurons of the STG extract different sounds from acoustic vibrations and represent them all. To shed some light, Nima Mesgarani and colleagues directly recorded neuronal responses in the STGs of patients while they listened to continuous speech from 400 natural American English speakers. Certain neurons showed clear responses to vowels, and others to consonants. Some were more sensitive to changes in pitch. The analysis ultimately divided the STG neurons into two distinct groups, each responding to different speech sound types. These findings reveal the specially designed nature of the acoustic-to-phonetic transformation process in the human STG, the authors say. Its complex layout is necessary for us to understand the words all around us.
Researchers are finding that online, crowd-sourced collaboration can speed up their work — if they choose the right problem.
At the end of January 2009, Timothy Gowers embarked on what he later called “one of the most exciting six weeks of my mathematical life”.
Inspired by the online citizen-science movement, Gowers, a mathematician at the University of Cambridge, UK, posted an esoteric theorem on his blog and challenged his readers to prove it — together.
Crowd-source your expertise, he urged them: “If a large group of mathematicians could connect their brains efficiently, they could perhaps solve problems very efficiently as well.”
They could. Within hours of the problem being posted, Gowers' blog was abuzz with back-and-forth brainstorming, as mathematicians chimed in with ideas and possible avenues of attack. Gowers had hoped for new insights, but even he was surprised that by March, after nearly 1,000 comments, he was able to declare the theorem proved. “The quite unexpected result — an actual solution to the problem — added an extra layer of excitement to the whole thing,” he says. The proof was published1 under the collective pseudonym D. H. J. Polymath.
Despite widespread interest in neural mechanisms of decision-making, most investigations focus on decisions between just two options. Here we adapt a biophysically plausible model of decision-making to predict how a key decision variable, the value difference signal—encoding how much better one choice is than another—changes with the value of a third, but unavailable, alternative. The model predicts a surprising failure of optimal decision-making: greater difficulty choosing between two options in the presence of a third very poor, as opposed to very good, alternative. Both investigation of human decision-making and functional magnetic resonance imaging–based measurements of value difference signals in ventromedial prefrontal cortex (vmPFC) bore out this prediction. The vmPFC signal decreased in the presence of low-value third alternatives, and vmPFC effect sizes predicted individual variation in suboptimal decision-making in the presence of multiple alternatives. The effect contrasts with that of divisive normalization in parietal cortex.
The National Autonomous University of Mexico (UNAM) has an open call for postdoctoral fellowships to start in September, 2014 or March, 2015. Candidates should have obtained a PhD degree within the last three years and be under 36 years, both to the date of the beginning of the fellowship.
The area of interests of candidates should fall within complex systems, artificial life, information, evolution, cognition, robotics, and/or philosophy.
The wide adoption of social media has increased the competition among ideas for our finite attention. We employ a parsimonious agent-based model to study whether such a competition may affect the popularity of different memes, the diversity of information we are exposed to, and the fading of our collective interests for specific topics. Agents share messages on a social network but can only pay attention to a portion of the information they receive. In the emerging dynamics of information diffusion, a few memes go viral while most do not. The predictions of our model are consistent with empirical data from Twitter, a popular microblogging platform. Surprisingly, we can explain the massive heterogeneity in the popularity and persistence of memes as deriving from a combination of the competition for our limited attention and the structure of the social network, without the need to assume different intrinsic values among ideas.
GitHub today announced the GitHub Developer Program to provide all developers with the resources they need to “build integrations for better collaboration, higher code quality, easy deployment and so much more.” In other words, GitHub wants to do more than just offer an API.
Nanotechnology doesn’t get as much attention these days as genetic and stem cell approaches to medicine, but all three aim to target the causes of illness with greater precision and less collateral damage in the rest of the body than conventional approaches.
Nanotech breakthroughs have come more slowly than many had hoped, but a recent success shows progress toward the goal of using tiny nanomachines to repair or destroy only specific diseased cells. But before nanomachines can deliver medicine directly to cells’ door, they have to work properly in a biological environment.
Researchers have made an important step in that direction, navigating nanomotors inside living human cells for what they say is the first time.
The search for neuronal and psychological underpinnings of pathological gambling in humans would benefit from investigating related phenomena also outside of our species. In this paper, we present a survey of studies in three widely different populations of agents, namely rodents, non-human primates, and robots. Each of these populations offer valuable and complementary insights on the topic, as the literature demonstrates. In addition, we highlight the deep and complex connections between relevant results across these different areas of research (i.e., cognitive and computational neuroscience, neuroethology, cognitive primatology, neuropsychiatry, evolutionary robotics), to make the case for a greater degree of methodological integration in future studies on pathological gambling.
Social networks readily transmit information, albeit with less than perfect fidelity. We present a large-scale measurement of this imperfect information copying mechanism by examining the dissemination and evolution of thousands of memes, collectively replicated hundreds of millions of times in the online social network Facebook. The information undergoes an evolutionary process that exhibits several regularities. A meme's mutation rate characterizes the population distribution of its variants, in accordance with the Yule process. Variants further apart in the diffusion cascade have greater edit distance, as would be expected in an iterative, imperfect replication process. Some text sequences can confer a replicative advantage; these sequences are abundant and transfer "laterally" between different memes. Subpopulations of the social network can preferentially transmit a specific variant of a meme if the variant matches their beliefs or culture. Understanding the mechanism driving change in diffusing information has important implications for how we interpret and harness the information that reaches us through our social networks.
Information Evolution in Social Networks Lada A. Adamic, Thomas M. Lento, Eytan Adar, Pauline C. Ng
This interview with Alessandro Vespignani is about the future of modelling and forecasting of epidemics and is part of the Futurium Talking Futures interview series. More information is available here:
A few weeks into the making of Her, Spike Jonze’s new flick about romance in the age of artificial intelligence, the director had something of a breakthrough. After poring over the work of Ray Kurzweil and other futurists trying to figure out how, exactly, his artificially intelligent female lead should operate, Jonze arrived at a critical insight: Her, he realized, isn’t a movie about technology. It’s a movie about people. With that, the film took shape. Sure, it takes place in the future, but what it’s really concerned with are human relationships, as fragile and complicated as they’ve been from the start.
In The Science of Storytelling & Memory and Their Impact on CRO , author Ankit Oberoi describes how Rob Walker and Joshua Glenn increased the selling price of items by 6,000%… with stories! This is a long, detailed post at ConversionXL with plenty of examples, not to mention the science behind why stories embed themselves in your memory.
Laura Hudson of Wired shows the surprising effect that screen symbols can have in The Human Brain Now Reacts to Emoticons Like Real Faces. Emoticons, particularly the most common version of the “smiley,” are processed like facial expressions. Read it, you’ll smile!
We all know that art lives in the right brain and math in the left… except it’s not true. In fact, beauty in art and mathematics have a lot in common. Even though a simple, powerful equation would seem to have little in common with a Renoir sketch, Dr. Jeremy Dean talks about how beauty in both areas of endeavor lights up the same part of the brain: Beauty in Art and Mathematics Activates The Same Brain Region.
Two monkeys sit at computer screens, eyeing one another as they wait for a promised reward: apple juice. Each has a choice — it can either select a symbol that results in juice being shared equally, or pick one that delivers most of the juice to itself. But being selfish is risky. If its partner also chooses not to share, neither gets much juice.
This game, the ‘prisoner’s dilemma’, is a classic test of strategy that involves the simultaneous evaluation of an opponent’s thinking. Researchers have now discovered — and manipulated — specific brain circuits in rhesus macaques (Macaca mulatta) that seem to be involved in the animals’ choices, and in their assessments of their partners’ choices. Investigating the connections could shed light on how social context affects decision-making in humans, and how disorders that affect social skills, such as autism spectrum disorder, disrupt brain circuitry.
“Once we have identified that there are particular neural signals necessary to drive the processes, we can begin to tinker,” says Michael Platt, a neurobiologist at Duke University in Durham, North Carolina.
In this pioneering synthesis, Joshua Epstein introduces a new theoretical entity: Agent_Zero. This software individual, or "agent," is endowed with distinct emotional/affective, cognitive/deliberative, and social modules. Grounded in contemporary neuroscience, these internal components interact to generate observed, often far-from-rational, individual behavior. When multiple agents of this new type move and interact spatially, they collectively generate an astonishing range of dynamics spanning the fields of social conflict, psychology, public health, law, network science, and economics.
Epstein weaves a computational tapestry with threads from Plato, Hume, Darwin, Pavlov, Smith, Tolstoy, Marx, James, and Dostoevsky, among others. This transformative synthesis of social philosophy, cognitive neuroscience, and agent-based modeling will fascinate scholars and students of every stripe. Epstein's computer programs are provided in the book or on its Princeton University Press website, along with movies of his "computational parables."
Agent_Zero is a signal departure in what it includes (e.g., a new synthesis of neurally grounded internal modules), what it eschews (e.g., standard behavioral imitation), the phenomena it generates (from genocide to financial panic), and the modeling arsenal it offers the scientific community.
For generative social science, Agent_Zero presents a groundbreaking vision and the tools to realize it.
Collective animal behavior studies have led the way in developing models that account for a large number of individuals, but mostly have considered situations in which alignment and attraction play a key role, such as in schooling and flocking. By quantifying how animals react to one another’s presence, when interaction is via conspecific avoidance rather than alignment or attraction, we present a mechanistic insight that enables us to link individual behavior and space use patterns. As animals respond to both current and past positions of their neighbors, the assumption that the relative location of individuals is statistically and history independent is not tenable, underscoring the limitations of traditional space use studies. We move beyond that assumption by constructing a framework to analyze spatial segregation of mobile animals when neighbor proximity may elicit a retreat, and by linking conspecific encounter rate to history-dependent avoidance behavior. Our approach rests on the knowledge that animals communicate by modifying the environment in which they live, providing a method to analyze social cohesion as stigmergy, a form of mediated animal–animal interaction. By considering a population of animals that mark the terrain as they move, we predict how the spatiotemporal patterns that emerge depend on the degree of stigmergy of the interaction processes. We find in particular that nonlocal decision rules may generate a nonmonotonic dependence of the animal encounter rate as a function of the tendency to retreat from locations recently visited by other conspecifics, which has fundamental implications for epidemic disease spread and animal sociality.