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Dynamics of Social Interaction
Curated by Ashish Umre
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Social Vocalizations of Big Brown Bats Vary with Behavioral Context

Social Vocalizations of Big Brown Bats Vary with Behavioral Context | Social Foraging | Scoop.it

Bats are among the most gregarious and vocal mammals, with some species demonstrating a diverse repertoire of syllables under a variety of behavioral contexts. Despite extensive characterization of big brown bat (Eptesicus fuscus) biosonar signals, there have been no detailed studies of adult social vocalizations. We recorded and analyzed social vocalizations and associated behaviors of captive big brown bats under four behavioral contexts: low aggression, medium aggression, high aggression, and appeasement. Even limited to these contexts, big brown bats possess a rich repertoire of social vocalizations, with 18 distinct syllable types automatically classified using a spectrogram cross-correlation procedure.

 

For each behavioral context, we describe vocalizations in terms of syllable acoustics, temporal emission patterns, and typical syllable sequences. Emotion-related acoustic cues are evident within the call structure by context-specific syllable types or variations in the temporal emission pattern. We designed a paradigm that could evoke aggressive vocalizations while monitoring heart rate as an objective measure of internal physiological state. Changes in the magnitude and duration of elevated heart rate scaled to the level of evoked aggression, confirming the behavioral state classifications assessed by vocalizations and behavioral displays. These results reveal a complex acoustic communication system among big brown bats in which acoustic cues and call structure signal the emotional state of a caller.

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Predicting Human Preferences Using the Block Structure of Complex Social Networks

Predicting Human Preferences Using the Block Structure of Complex Social Networks | Social Foraging | Scoop.it

With ever-increasing available data, predicting individuals' preferences and helping them locate the most relevant information has become a pressing need. Understanding and predicting preferences is also important from a fundamental point of view, as part of what has been called a “new” computational social science. Here, we propose a novel approach based on stochastic block models, which have been developed by sociologists as plausible models of complex networks of social interactions. Our model is in the spirit of predicting individuals' preferences based on the preferences of others but, rather than fitting a particular model, we rely on a Bayesian approach that samples over the ensemble of all possible models. We show that our approach is considerably more accurate than leading recommender algorithms, with major relative improvements between 38% and 99% over industry-level algorithms. Besides, our approach sheds light on decision-making processes by identifying groups of individuals that have consistently similar preferences, and enabling the analysis of the characteristics of those groups.

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Evolving Righteousness in a Corrupt World

Evolving Righteousness in a Corrupt World | Social Foraging | Scoop.it

Punishment offers a powerful mechanism for the maintenance of cooperation in human and animal societies, but the maintenance of costly punishment itself remains problematic. Game theory has shown that corruption, where punishers can defect without being punished themselves, may sustain cooperation. However, in many human societies and some insect ones, high levels of cooperation coexist with low levels of corruption, and such societies show greater wellbeing than societies with high corruption. Here we show that small payments from cooperators to punishers can destabilize corrupt societies and lead to the spread of punishment without corruption (righteousness). Righteousness can prevail even in the face of persistent power inequalities. The resultant righteous societies are highly stable and have higher wellbeing than corrupt ones. This result may help to explain the persistence of costly punishing behavior, and indicates that corruption is a sub-optimal tool for maintaining cooperation in human societies.

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Sexual Selection of Human Cooperative Behaviour: An Experimental Study in Rural Senegal

Human cooperation in large groups and between non-kin individuals remains a Darwinian puzzle. Investigations into whether and how sexual selection is involved in the evolution of cooperation represent a new and important research direction. Here, 69 groups of four men or four women recruited from a rural population in Senegal played a sequential public-good game in the presence of out-group observers, either of the same sex or of the opposite sex. At the end of the game, participants could donate part of their gain to the village school in the presence of the same observers. Both contributions to the public good and donations to the school, which reflect different components of cooperativeness, were influenced by the sex of the observers. The results suggest that in this non-Western population, sexual selection acts mainly on men’s cooperative behaviour with non-kin, whereas women’s cooperativeness is mainly influenced by nonsexual social selection.

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Scholarometer: A Social Framework for Analyzing Impact across Disciplines

Scholarometer: A Social Framework for Analyzing Impact across Disciplines | Social Foraging | Scoop.it

The use of quantitative metrics to gauge the impact of scholarly publications, authors, and disciplines is predicated on the availability of reliable usage and annotation data. Citation and download counts are widely available from digital libraries. However, current annotation systems rely on proprietary labels, refer to journals but not articles or authors, and are manually curated. To address these limitations, we propose a social framework based on crowdsourced annotations of scholars, designed to keep up with the rapidly evolving disciplinary and interdisciplinary landscape. We describe a system called Scholarometer, which provides a service to scholars by computing citation-based impact measures.

 

This creates an incentive for users to provide disciplinary annotations of authors, which in turn can be used to compute disciplinary metrics. We first present the system architecture and several heuristics to deal with noisy bibliographic and annotation data. We report on data sharing and interactive visualization services enabled by Scholarometer. Usage statistics, illustrating the data collected and shared through the framework, suggest that the proposed crowdsourcing approach can be successful. Secondly, we illustrate how the disciplinary bibliometric indicators elicited by Scholarometer allow us to implement for the first time a universal impact measure proposed in the literature. Our evaluation suggests that this metric provides an effective means for comparing scholarly impact across disciplinary boundaries.

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Binary DNA Nanostructures for Data Encryption

Binary DNA Nanostructures for Data Encryption | Social Foraging | Scoop.it

We present a simple and secure system for encrypting and decrypting information using DNA self-assembly. Binary data is encoded in the geometry of DNA nanostructures with two distinct conformations. Removing or leaving out a single component reduces these structures to an encrypted solution of ssDNA, whereas adding back this missing “decryption key” causes the spontaneous formation of the message through self-assembly, enabling rapid read out via gel electrophoresis. Applications include authentication, secure messaging, and barcoding.

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Baboon foraging choices depend on their habitat and social status: study

Baboon foraging choices depend on their habitat and social status: study | Social Foraging | Scoop.it

In a study published today in The American Naturalist, a group of scientists led by the Zoological Society of London (ZSL) have used a technique developed to study human consumer choices to investigate what influences a baboon's foraging decisions. The technique, known as discrete choice modelling, has rarely been used before in animal behaviour research. It showed how baboons not only consider many social and non-social factors when making foraging decisions, but also how they change these factors depending on their habitat and their own social traits.

 

Over a six month period in Tsaobis Leopard Park in Namibia, ZSL scientists followed troops of chacma baboons (Papio ursinus) on foot from dawn to dusk. They recognised individual baboons by distinguishing features, and closely observed both the aggressive and friendly social relationships between baboons, noting which food patch they foraged in and who they foraged with. As expected, baboons were more likely to use patches containing more food. More interestingly, they also paid attention to their social relationships with other baboons in the patches. Harry Marshall, from ZSL and Imperial College London conducted the research. He says: "More dominant baboons preferred using patches containing animals who they were dominant to, and so more likely to be able to steal food from.

 

However, these less dominant baboons seemed to compensate for this by preferring patches containing animals with whom they had good social bonds and so were more likely to tolerate them."

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Scientists use prosthetic device to restore and improve impaired decision-making ability in animals

Scientists use prosthetic device to restore and improve impaired decision-making ability in animals | Social Foraging | Scoop.it

Imagine a prosthetic device capable of restoring decision-making in people who have reduced capacity due to brain disease or injury. While this may sound like science fiction, researchers at Wake Forest Baptist Medical Center have proven for the first time that it is possible in non-human primates, and believe that one day it will be possible in people.In essence, the scientists used an electronic prosthetic system to tap into existing circuitry in the brain at the cellular level and record the firing patterns of multiple neurons in the prefrontal cortex, the part of the brain involved in decision-making. They then "played" that recording back to the same brain area to electrically stimulate decision-based neural activity. Not only did it restore function, in some cases, it also improved it.

 

"The prosthetic device is like 'flipping a switch' to turn on a decision in real time," said Sam Deadwyler, Ph.D., professor of physiology and pharmacology at Wake Forest Baptist, and senior author of the study, which is published in the Sept. 14 issue of the Journal of Neural Engineering.

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Biomimicry is the conscious study of nature

Biomimicry is the conscious study of nature | Social Foraging | Scoop.it

Biomimicry is by its nature (pun intended), the science of learning from nature, rather than the technology of what we can take from it. The system of exploiting nature is unsustainable, short-sighted and to put it bluntly, unintelligent.

 

Nature on the other hand is pure genius, intelligent and creative. It has taken billions of years for this earth and its billions of species to adapt to each other in a sustainable manner.

 

Biomimicry consciously studies nature’s successful models and then emulates these forms, processes, systems, and strategies to solve human problems sustainably.

 

By necessity, nature has solved many of the problems that we as one species – man – are still grappling with. For instance food, water, energy, climate, transport, packaging and systems that incorporate all of these issues have been solved by nature.

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Queens are 'lined up' in wasp colony

When the queen wasp of the colony dies, who takes over? Is the royal hierarchy decided beforehand or does the exit of the queen trigger the succession process? What happens if queen number two dies or is eliminated from the colony somehow?

 

A fascinating new piece of research1 inside tiny colonies of these social insects has found that there is a succession of 'cryptic heir designates' to the queen who reveal their identity only upon the removal of the queen from their abodes.

 

Two researchers from the Centre for Ecological Sciences at Bangalore-based Indian Institute of Science have pried deep into the world of wasps — Ropalidia marginata — to study their social order more closely.

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Deciphering Interactions in Moving Animal Groups

Deciphering Interactions in Moving Animal Groups | Social Foraging | Scoop.it

Collective motion phenomena in large groups of social organisms have long fascinated the observer, especially in cases, such as bird flocks or fish schools, where large-scale highly coordinated actions emerge in the absence of obvious leaders. However, the mechanisms involved in this self-organized behavior are still poorly understood, because the individual-level interactions underlying them remain elusive.

 

Here, we demonstrate the power of a bottom-up methodology to build models for animal group motion from data gathered at the individual scale. Using video tracks of fish shoal in a tank, we show how a careful, incremental analysis at the local scale allows for the determination of the stimulus/response function governing an individual's moving decisions. We find in particular that both positional and orientational effects are present, act upon the fish turning speed, and depend on the swimming speed, yielding a novel schooling model whose parameters are all estimated from data. Our approach also leads to identify a density-dependent effect that results in a behavioral change for the largest groups considered. This suggests that, in confined environment, the behavioral state of fish and their reaction patterns change with group size. We debate the applicability, beyond the particular case studied here, of this novel framework for deciphering interactions in moving animal groups.

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Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts

Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts | Social Foraging | Scoop.it

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions.

 

However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein.

 

With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed.

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Living Analytics Research Centre (LARC)

Living Analytics Research Centre (LARC) | Social Foraging | Scoop.it

Living Analytics is a new joint research initiative between Singapore Management University (SMU) and Carnegie Mellon University (CMU) to conduct research on behavioural and social network analytics and behavioural experiments so as to discover and harness the laws of information network evolution for networks of people, organisations and businesses.

 

SMU and Carnegie Mellon are convinced that the Living Analytics Research Centre provides a unique opportunity to bring together i) machine learning, ii) statistics, iii) social and behavior science, iv) management science, and v) the science of social and behavioral networks, in ways that can transform and expand computational social science.

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Consistent Implementation of Decisions in the Brain

Consistent Implementation of Decisions in the Brain | Social Foraging | Scoop.it

Despite the complexity and variability of decision processes, motor responses are generally stereotypical and independent of decision difficulty. How is this consistency achieved? Through an engineering analogy we consider how and why a system should be designed to realise not only flexible decision-making, but also consistent decision implementation. We specifically consider neurobiologically-plausible accumulator models of decision-making, in which decisions are made when a decision threshold is reached. To trade-off between the speed and accuracy of the decision in these models, one can either adjust the thresholds themselves or, equivalently, fix the thresholds and adjust baseline activation.

 

Here we review how this equivalence can be implemented in such models. We then argue that manipulating baseline activation is preferable as it realises consistent decision implementation by ensuring consistency of motor inputs, summarise empirical evidence in support of this hypothesis, and suggest that it could be a general principle of decision making and implementation. Our goal is therefore to review how neurobiologically-plausible models of decision-making can manipulate speed-accuracy trade-offs using different mechanisms, to consider which of these mechanisms has more desirable decision-implementation properties, and then review the relevant neuroscientific data on which mechanism brains actually use.

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Multi-Scale Modeling in Morphogenesis: A Critical Analysis of the Cellular Potts Model

Multi-Scale Modeling in Morphogenesis: A Critical Analysis of the Cellular Potts Model | Social Foraging | Scoop.it

Cellular Potts models (CPMs) are used as a modeling framework to elucidate mechanisms of biological development. They allow a spatial resolution below the cellular scale and are applied particularly when problems are studied where multiple spatial and temporal scales are involved. Despite the increasing usage of CPMs in theoretical biology, this model class has received little attention from mathematical theory. To narrow this gap, the CPMs are subjected to a theoretical study here. It is asked to which extent the updating rules establish an appropriate dynamical model of intercellular interactions and what the principal behavior at different time scales characterizes. It is shown that the longtime behavior of a CPM is degenerate in the sense that the cells consecutively die out, independent of the specific interdependence structure that characterizes the model.

 

While CPMs are naturally defined on finite, spatially bounded lattices, possible extensions to spatially unbounded systems are explored to assess to which extent spatio-temporal limit procedures can be applied to describe the emergent behavior at the tissue scale. To elucidate the mechanistic structure of CPMs, the model class is integrated into a general multiscale framework. It is shown that the central role of the surface fluctuations, which subsume several cellular and intercellular factors, entails substantial limitations for a CPM's exploitation both as a mechanistic and as a phenomenological model.

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Negative Feedback Enables Fast and Flexible Collective Decision-Making in Ants

Negative Feedback Enables Fast and Flexible Collective Decision-Making in Ants | Social Foraging | Scoop.it

Positive feedback plays a major role in the emergence of many collective animal behaviours. In many ants pheromone trails recruit and direct nestmate foragers to food sources. The strong positive feedback caused by trail pheromones allows fast collective responses but can compromise flexibility. Previous laboratory experiments have shown that when the environment changes, colonies are often unable to reallocate their foragers to a more rewarding food source.

 

Here we show both experimentally, using colonies of Lasius niger, and with an agent-based simulation model, that negative feedback caused by crowding at feeding sites allows ant colonies to maintain foraging flexibility even with strong recruitment to food sources. In a constant environment, negative feedback prevents the frequently found bias towards one feeder (symmetry breaking) and leads to equal distribution of foragers. In a changing environment, negative feedback allows a colony to quickly reallocate the majority of its foragers to a superior food patch that becomes available when foraging at an inferior patch is already well underway. The model confirms these experimental findings and shows that the ability of colonies to switch to a superior food source does not require the decay of trail pheromones. Our results help to resolve inconsistencies between collective foraging patterns seen in laboratory studies and observations in the wild, and show that the simultaneous action of negative and positive feedback is important for efficient foraging in mass-recruiting insect colonies.

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Coevolution of Trustful Buyers and Cooperative Sellers in the Trust Game

Coevolution of Trustful Buyers and Cooperative Sellers in the Trust Game | Social Foraging | Scoop.it

Many online marketplaces enjoy great success. Buyers and sellers in successful markets carry out cooperative transactions even if they do not know each other in advance and a moral hazard exists. An indispensable component that enables cooperation in such social dilemma situations is the reputation system. Under the reputation system, a buyer can avoid transacting with a seller with a bad reputation. A transaction in online marketplaces is better modeled by the trust game than other social dilemma games, including the donation game and the prisoner's dilemma.

 

In addition, most individuals participate mostly as buyers or sellers; each individual does not play the two roles with equal probability. Although the reputation mechanism is known to be able to remove the moral hazard in games with asymmetric roles, competition between different strategies and population dynamics of such a game are not sufficiently understood. On the other hand, existing models of reputation-based cooperation, also known as indirect reciprocity, are based on the symmetric donation game. We analyze the trust game with two fixed roles, where trustees (i.e., sellers) but not investors (i.e., buyers) possess reputation scores.

 

We study the equilibria and the replicator dynamics of the game. We show that the reputation mechanism enables cooperation between unacquainted buyers and sellers under fairly generous conditions, even when such a cooperative equilibrium coexists with an asocial equilibrium in which buyers do not buy and sellers cheat. In addition, we show that not many buyers may care about the seller's reputation under cooperative equilibrium. Buyers' trusting behavior and sellers' reputation-driven cooperative behavior coevolve to alleviate the social dilemma.

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Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games

Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games | Social Foraging | Scoop.it

By combining evolutionary game theory and graph theory, “games on graphs” study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner’s dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games.

 

To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner’s dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures.

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Target's customer tracking algorithms are so good, they figured out a teen was pregnant and broke the news to her father by accident

Target's customer tracking algorithms are so good, they figured out a teen was pregnant and broke the news to her father by accident | Social Foraging | Scoop.it

Every time you go shopping, you share intimate details about your consumption patterns with retailers. And many of those retailers are studying those details to figure out what you like, what you need, and which coupons are most likely to make you happy. Target, for example, has figured out how to data-mine its way into your womb, to figure out whether you have a baby on the way long before you need to start buying diapers.

 

Target keeps close tabs on everything its customers buy. They tag their customers with guest IDs and store all the detailed information they get from each customer. They then analyze the information and track it. They’ve become so accurate at tracking that they’ve been able to predict with extreme accuracy when women become pregnant. Target has created a system that allows them to send coupons for expecting mothers. They have an algorithm that includes 25 very specific products. When a person buys those products, they can predict a pregnancy with decent confidence. What's even scarier is that they can even guess when the person's going to be due based on what they buy!

 

What they’ve found is that they freak out their customers by congratulating them on their pregnancies before the customer has formally set up any registry or anything with Target, or even told their own family!

 

A father in Minneapolis went to a local Target demanding to speak with a manager. He was livid that his daughter had received coupons and information on maternity clothing and baby items. It was inappropriate for Target to be sending his daughter, who was still in high school, information like that promoting pregnancy.

 

Later, the manager called the father to apologize again and was told that the father had spoken to his daughter. She admitted that she was pregnant and due in August, so the father apologized to the manager.

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Who (and what) can you trust? How non-verbal cues can predict a person's (and a robot's) trustworthiness

Who (and what) can you trust? How non-verbal cues can predict a person's (and a robot's) trustworthiness | Social Foraging | Scoop.it

People face this predicament all the time -- can you determine a person's character in a single interaction? Can you judge whether someone you just met can be trusted when you have only a few minutes together? And if you can, how do you do it? Using a robot named Nexi, Northeastern University psychology professor David DeSteno and collaborators Cynthia Breazeal from MIT's Media Lab and Robert Frank and David Pizarro from Cornell University have figured out the answer.The findings were recently published in the journal Psychological Science, a journal of the Association for Psychological Science.

 

It's What You're Not Saying…

 

In the absence of reliable information about a person's reputation, nonverbal cues can offer a look into a person's likely actions. This concept has been known for years, but the cues that convey trustworthiness or untrustworthiness have remained a mystery. Collecting data from face-to-face conversations with research participants where money was on the line, DeSteno and his team realized that it's not one single non-verbal movement or cue that determines a person's trustworthiness, but rather sets of cues. When participants expressed these cues, they cheated their partners more, and, at a gut level, their partners expected it. "Scientists haven't been able to unlock the cues to trust because they've been going about it the wrong way," DeSteno said. "There's no one golden-cue. Context and coordination of movements is what matters."

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Scientists use prosthetic device to restore and improve impaired decision-making ability in animals

Scientists use prosthetic device to restore and improve impaired decision-making ability in animals | Social Foraging | Scoop.it

Imagine a prosthetic device capable of restoring decision-making in people who have reduced capacity due to brain disease or injury. While this may sound like science fiction, researchers at Wake Forest Baptist Medical Center have proven for the first time that it is possible in non-human primates, and believe that one day it will be possible in people.In essence, the scientists used an electronic prosthetic system to tap into existing circuitry in the brain at the cellular level and record the firing patterns of multiple neurons in the prefrontal cortex, the part of the brain involved in decision-making. They then "played" that recording back to the same brain area to electrically stimulate decision-based neural activity. Not only did it restore function, in some cases, it also improved it.

 

"The prosthetic device is like 'flipping a switch' to turn on a decision in real time," said Sam Deadwyler, Ph.D., professor of physiology and pharmacology at Wake Forest Baptist, and senior author of the study, which is published in the Sept. 14 issue of the Journal of Neural Engineering.

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Move Over Genetic-Engineering; Biomimicry Seems The Better Bet For Solving Global Hunger

Move Over Genetic-Engineering; Biomimicry Seems The Better Bet For Solving Global Hunger | Social Foraging | Scoop.it

Biomimicry is maybe the best idea you haven’t heard too much about. The term, for those unfamiliar, was coined by American inventor Otto Schmitt back in the 1970s, but it was author Janine Benyus 1997 book: Biomimicry: Inspiration Inspired by Nature, who truly popularized the notion.At the heart of this science, is the straight-forward fact that nature does a lot of things very well that we can’t do at all—so why not copy nature.

 

Now, for certain, we have been learning. For example, the Galapagos Shark was found to have no bacteria on its skin. How does it accomplish this feat? Not with chemicals, rather with architecture. The structure of its skin—literally the pattern formed by its skin cells—don’t allow bacteria to land and adhere. And it’s this pattern that now shows up Speedo bathing suits—helping Olympic athletes break all sorts of records.

 

There are hundreds of similar examples. My favorites are the ones we don’t even understand. For example, ecologists have known since the 1960s that keystone predators are critical to the health of an eco-system. They’ve also known that keystone predators need a lot of space to roam—far more than the confines of a single national park can provide. This is why there is now a huge movement to build “wildlife corridors,” essentially linked passages of wildlands connection huge swatches of national park.

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Understanding Sentiment Analysis with Hadoop

Understanding Sentiment Analysis with Hadoop | Social Foraging | Scoop.it

Sentiment Analysis is widely quoted as an ideal use case for Hadoop ecosystem usage. While certain research has gone to link machine analysis in conjunction with cognition and emotion research, we will limit our post to machine analysis.

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Inferring the Structure of Social Contacts from Demographic Data in the Analysis of Infectious Diseases Spread

Inferring the Structure of Social Contacts from Demographic Data in the Analysis of Infectious Diseases Spread | Social Foraging | Scoop.it

Social contact patterns among individuals encode the transmission route of infectious diseases and are a key ingredient in the realistic characterization and modeling of epidemics. Unfortunately, the gathering of high quality experimental data on contact patterns in human populations is a very difficult task even at the coarse level of mixing patterns among age groups.

 

Here we propose an alternative route to the estimation of mixing patterns that relies on the construction of virtual populations parametrized with highly detailed census and demographic data. We present the modeling of the population of 26 European countries and the generation of the corresponding synthetic contact matrices among the population age groups. The method is validated by a detailed comparison with the matrices obtained in six European countries by the most extensive survey study on mixing patterns.

 

The methodology presented here allows a large scale comparison of mixing patterns in Europe, highlighting general common features as well as country-specific differences. We find clear relations between epidemiologically relevant quantities (reproduction number and attack rate) and socio-demographic characteristics of the populations, such as the average age of the population and the duration of primary school cycle. This study provides a numerical approach for the generation of human mixing patterns that can be used to improve the accuracy of mathematical models in the absence of specific experimental data.

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The International Conference on Social Informatics: SocInfo 2012

The International Conference on Social Informatics: SocInfo 2012 | Social Foraging | Scoop.it

Full paper submission: July 14, 2012 (23:59 CEST)

Notification of acceptance: September 14, 2012

Submission of final version: September 30, 2012

 

 

The International Conference on Social Informatics (SocInfo 2012) is an interdisciplinary venue for researchers from Computer Science, Informatics, Social Sciences and Management Sciences to share ideas and opinions, and present original research work on studying the interplay between socially-centric platforms and social phenomena. The ultimate goal of Social Informatics is to create better understanding of socially-centric platforms not just as a technology, but also as a set of social phenomena. To that end, we are inviting interdisciplinary papers, on applying information technology in the study of social phenomena, on applying social concepts in the design of information systems, on applying methods from the social sciences in the study of social computing and information systems, on applying computational algorithms to facilitate the study of social systems and human social dynamics, and on designing information and communication technologies that consider social context.

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