Social Foraging
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Dynamics of Social Interaction
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Early Warnings of Regime Shift When the Ecosystem Structure Is Unknown

Early Warnings of Regime Shift When the Ecosystem Structure Is Unknown | Social Foraging | Scoop.it

Abrupt changes in dynamics of an ecosystem can sometimes be detected using monitoring data. Using nonparametric methods that assume minimal knowledge of the underlying structure, we compute separate estimates of the drift (deterministic) and diffusion (stochastic) components of a general dynamical process, as well as an indicator of the conditional variance. Theory and simulations show that nonparametric conditional variance rises prior to critical transition. Nonparametric diffusion rises also, in cases where the true diffusion function involves a critical transition (sometimes called a noise-induced transition). Thus it is possible to discriminate noise-induced transitions from other kinds of critical transitions by comparing time series for the conditional variance and the diffusion function. Monte Carlo analysis shows that the indicators generally increase prior to the transition, but uncertainties of the indicators become large as the ecosystem approaches the transition point.

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Understanding Patchy Landscape Dynamics: Towards a Landscape Language

Understanding Patchy Landscape Dynamics: Towards a Landscape Language | Social Foraging | Scoop.it

Patchy landscapes driven by human decisions and/or natural forces are still a challenge to be understood and modelled. No attempt has been made up to now to describe them by a coherent framework and to formalize landscape changing rules. Overcoming this lacuna was our first objective here, and this was largely based on the notion of Rewriting Systems, also called Formal Grammars. We used complicated scenarios of agricultural dynamics to model landscapes and to write their corresponding driving rule equations. Our second objective was to illustrate the relevance of this landscape language concept for landscape modelling through various grassland managements, with the final aim to assess their respective impacts on biological conservation. For this purpose, we made the assumptions that a higher grassland appearance frequency and higher land cover connectivity are favourable to species conservation. Ecological results revealed that dairy and beef livestock production systems are more favourable to wild species than is hog farming, although in different ways. Methodological results allowed us to efficiently model and formalize these landscape dynamics. This study demonstrates the applicability of the Rewriting System framework to the modelling of agricultural landscapes and, hopefully, to other patchy landscapes. The newly defined grammar is able to explain changes that are neither necessarily local nor Markovian, and opens a way to analytical modelling of landscape dynamics.

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The Social Brain: Transcriptome Assembly and Characterization of the Hippocampus from a Social Subterranean Rodent, the Colonial Tuco-Tuco (Ctenomys sociabilis)

The Social Brain: Transcriptome Assembly and Characterization of the Hippocampus from a Social Subterranean Rodent, the Colonial Tuco-Tuco (Ctenomys sociabilis) | Social Foraging | Scoop.it

Elucidating the genetic mechanisms that underlie complex adaptive phenotypes is a central problem in evolutionary biology. For behavioral biologists, the ability to link variation in gene expression to the occurrence of specific behavioral traits has long been a largely unobtainable goal. Social interactions with conspecifics represent a fundamental component of the behavior of most animal species. Although several studies of mammals have attempted to uncover the genetic bases for social relationships using a candidate gene approach, none have attempted more comprehensive, transcriptome-based analyses using high throughout sequencing. As a first step toward improved understanding of the genetic underpinnings of mammalian sociality, we generated a reference transcriptome for the colonial tuco-tuco (Ctenomys sociabilis), a social species of subterranean rodent that is endemic to southwestern Argentina. Specifically, we analyzed over 500 million Illumina sequencing reads derived from the hippocampi of 10 colonial tuco-tucos housed in captivity under a variety of social conditions. The resulting reference transcriptome provides a critical tool for future studies aimed at exploring relationships between social environment and gene expression in this non-model species of social mammal.

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‘Green Brain’ project to create an autonomous flying robot with a honey bee brain

‘Green Brain’ project to create an autonomous flying robot with a honey bee brain | Social Foraging | Scoop.it

The team will build models of the systems in the brain that govern a honey bee's vision and sense of smell. Using this information, the researchers aim to create the first flying robot able to sense and act as autonomously as a bee, rather than just carry out a pre-programmed set of instructions.

 

If successful, this project will meet one of the major challenges of modern science: building a robot brain that can perform complex tasks as well as the brain of an animal. Tasks the robot will be expected to perform, for example, will include finding the source of particular odours or gases in the same way that a bee can identify particular flowers.

 

It is anticipated that the artificial brain could eventually be used in applications such as search and rescue missions, or even mechanical pollination of crops.

 

Dr James Marshall, leading the £1 million Engineering and Physical Sciences Research Council (EPSRC) funded project in Sheffield, said: "The development of an artificial brain is one of the greatest challenges in Artificial Intelligence. So far, researchers have typically studied brains such as those of rats, monkeys, and humans, but actually 'simpler' organisms such as social insects have surprisingly advanced cognitive abilities."

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Stemmer Imaging readies two new algorithms for Vision 2012

Stemmer Imaging readies two new algorithms for Vision 2012 | Social Foraging | Scoop.it

Motion detection algorithms have been widely deployed in the field of surveillance where they have been used to analyze traffic flow and movement of people in video image frames.

 

One of the common means used to determine and analyze the so-called optical flow of objects in such videos is to use a block matching algorithm. In use, the algorithm divides image frames into blocks, and then matches the block of pixels in one frame to a block of pixels in a consecutive frame.

 

While there are obviously many applications for the software in the surveillance field, engineers at Stemmer Imaging (Puchheim, Germany) also believe that such an optical flow algorithm could be usefully employed in an industrial vision system.

 

According to Peter Keppler, Stemmer Imaging's Sales Manager, such an algorithm could be deployed, for example, to enable the flow of products such as bottles on a production line to be analyzed.

 

As such, the company plans to launch its own optical flow algorithm for the first time at the upcoming Vision 2012 show in Stuttgart in November. According to Keppler, the algorithm will be rolled out as part of the company's Common Vision Blox (CVB) software.

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Predatory bacterial crowdsourcing

Predatory bacterial crowdsourcing | Social Foraging | Scoop.it

Myxococcus xanthus is a predatory bacterium that exhibits various collective behaviors throughout its lifecycle. At left, M. xanthus cells self-organize into traveling waves when preying upon E. coli. At right, in areas without prey, M. xanthus self-organizes into haystack-shaped spore-filled structures.

 

That's the winning formula of one of the world's smallest predators, the soil bacteria Myxococcus xanthus, and a new study by scientists at Rice University and the University of Texas Health Science Center at Houston (UTHealth) Medical School shows how M. xanthus uses the formula to spread, engulf and devour other bacteria. The study, featured on the cover of this month's online issue of the journal PLOS Computational Biology, shows how the simple motions of individual bacteria are amplified within colonies of M. xanthus to form millions-strong waves moving outward in unison.

 

The findings answer longstanding questions about how the waves form and the competitive edge they provide M. xanthus. "When the cells at the edge of the colony are moving outward, they are unlikely to encounter another M. xanthus cell, so they keep moving forward," said lead author Oleg Igoshin, assistant professor of bioengineering at Rice. "When they are traveling the other way, back toward the rest of the colony, they are likely to encounter other cells of their kind, and when they pass beside one of these and touch, they get the signal to turn around." Igoshin said the net effect is that the cells "spend more time moving outward than inward, and as a result, they spread faster."

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Risk-Sensitivity in Bayesian Sensorimotor Integration

Risk-Sensitivity in Bayesian Sensorimotor Integration | Social Foraging | Scoop.it

Information processing in the nervous system during sensorimotor tasks with inherent uncertainty has been shown to be consistent with Bayesian integration. Bayes optimal decision-makers are, however, risk-neutral in the sense that they weigh all possibilities based on prior expectation and sensory evidence when they choose the action with highest expected value. In contrast, risk-sensitive decision-makers are sensitive to model uncertainty and bias their decision-making processes when they do inference over unobserved variables. In particular, they allow deviations from their probabilistic model in cases where this model makes imprecise predictions. Here we test for risk-sensitivity in a sensorimotor integration task where subjects exhibit Bayesian information integration when they infer the position of a target from noisy sensory feedback. When introducing a cost associated with subjects' response, we found that subjects exhibited a characteristic bias towards low cost responses when their uncertainty was high. This result is in accordance with risk-sensitive decision-making processes that allow for deviations from Bayes optimal decision-making in the face of uncertainty. Our results suggest that both Bayesian integration and risk-sensitivity are important factors to understand sensorimotor integration in a quantitative fashion.

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Evidence Shows Slave Ants Rebel Against Oppressors

Evidence Shows Slave Ants Rebel Against Oppressors | Social Foraging | Scoop.it

There’s new evidence today ants that have been captured and made slaves by other ants aren’t simply taking their plights lying down. According to a new study, these slave ants are prone to try and take down their oppressors by sabotaging their families.

 

The first signs of this kind of ant rebellion were noted by Johannes Gutenberg University Mainz (JGU) research professor Dr. Susanne Foitzik in 2009. However, in the nearly 3 years since this discovery, Dr. Foitzik says this behavior occurs frequently among enslaved ants and has become quite widespread. For example, enslaved ants in Ohio, New York and West Virginia were all found to neglect and even kill the offspring of their oppressors, rather than care and provide for them as they should. By systematically killing off the young, these slave ants have been able to ensure only 45% of the ruling ants’ offspring survive long enough to become adult ants. This kind of “long con” by the slave ants will one day weaken the other species, increasing the chances of the survival of the slave ants and their colonies.

 

According to a statement made by Dr. Foitzik, this sort of parasitic relationship isn’t uncommon and slave ants are often observed taking advantage or sabotaging the host species.

 

Normally, the slave-making ants begin the process by attacking the nests of another ant colony. During these attacks, the slave-making ants will kill the adults of the other ant colony and steal their offspring. These slave-making ants will then bring the soon-to-be slaves back to their nests of hollowed acorns or nutshells and raise them to do their bidding.

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New research shows ants share decision-making to lessen "information overload"

New research shows ants share decision-making to lessen "information overload" | Social Foraging | Scoop.it

Scientists at Arizona State University have discovered that ants utilize a strategy to handle “information overload.” Temnothorax rugatulus ants, commonly found living in rock crevices in the Southwest, place the burden of making complicated decisions on the backs of the entire colony, rather than on an individual ant.

 

In a study published online in the scientific journal Current Biology, Stephen Pratt, an associate professor in ASU’s School of Life Sciences in the College of Liberal Arts and Sciences, and Takao Sasaki, a graduate student in Pratt’s lab, suggest that the key to preventing cognitive overload is found in collective decision-making, rather than in multi-tasking.

 

"I think the reason people are interested in this is because as humans, we can become overloaded with information – and that can possibly be detrimental both to our health and to how effectively we make decisions,” Pratt said. “There's a sense that as a society, we are being more and more overwhelmed by information.”

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Blue Brain Project Accurately Predicts Connections Between Neurons

Blue Brain Project Accurately Predicts Connections Between Neurons | Social Foraging | Scoop.it

One of the greatest challenges in neuroscience is to identify the map of synaptic connections between neurons. Called the “connectome,” it is the holy grail that will explain how information flows in the brain. In a landmark paper, published the week of 17th of September in PNAS, the EPFL’s Blue Brain Project (BBP) has identified key principles that determine synapse-scale connectivity by virtually reconstructing a cortical microcircuit and comparing it to a mammalian sample. These principles now make it possible to predict the locations of synapses in the neocortex.

 

“This is a major breakthrough, because it would otherwise take decades, if not centuries, to map the location of each synapse in the brain and it also makes it so much easier now to build accurate models,” says Henry Markram, head of the BBP.

 

A longstanding neuroscientific mystery has been whether all the neurons grow independently and just take what they get as their branches bump into each other, or are the branches of each neuron specifically guided by chemical signals to find all its target. To solve the mystery, researchers looked in a virtual reconstruction of a cortical microcircuit to see where the branches bumped into each other. To their great surprise, they found that the locations on the model matched that of synapses found in the equivalent real-brain circuit with an accuracy ranging from 75 percent to 95 percent.

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Body’s clock loops with neurons to wake us up

Body’s clock loops with neurons to wake us up | Social Foraging | Scoop.it

Biologists have uncovered one way that biological clocks control neuronal activity—a discovery that sheds new light on sleep-wake cycles.“The findings answer a significant question—how biological clocks drive the activity of clock neurons, which, in turn, regulate behavioral rhythms,” explains Justin Blau, an associate professor in New York University’s department of biology and the study’s senior author.

 

Their findings, which also offer potential new directions for research into ways to address sleep disorders and jetlag, appear in the Journal of Biological Rhythms.

 

Scientists have known that our biological clocks control neuronal activity. But not previously understood is how this process occurs—that is, how does information from biological clocks drive rhythms in the electrical activity of pacemaker neurons that, in turn, drives daily rhythms?

 

To understand this mechanism, the researchers examined the biological, or circadian, clocks of Drosophila fruit flies, which are commonly used for research in this area. Earlier studies of “clock genes” in fruit flies allowed the identification of similarly functioning genes in humans.

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Controlling behavior, remotely: Researchers use precise lasers to manipulate neurons in worms’ brains

Controlling behavior, remotely: Researchers use precise lasers to manipulate neurons in worms’ brains | Social Foraging | Scoop.it

In the quest to understand how the brain turns sensory input into behavior, Harvard scientists have crossed a major threshold. Using precisely targeted lasers, researchers have been able to take over a tiny animal’s brain, instruct it to turn in any direction they wish, and even implant false sensory information, fooling the animal into thinking food was nearby.

 

As described in a Sept. 23 paper published in the journal Nature, a team made up of Sharad Ramanathan, an assistant professor of molecular and cellular biology and of applied physics; Askin Kocabas, a postdoctoral fellow in molecular and cellular biology; Ching-Han Shen, a research assistant in molecular and cellular biology; and Zengcai V. Guo, from the Howard Hughes Medical Institute, were able to take control of Caenorhabditis elegans — tiny, transparent worms — by manipulating neurons in the worms’ brain.

 

The work, Ramanathan said, is important because, by taking control of complex behaviors in a relatively simple animal — C. elegans have just 302 neurons ­— researchers can understand how its nervous system functions.

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Grey parrot number acquisition: The inference of cardinal value from ordinal position on the numeral list

A Grey parrot (Psittacus erithacus) had previously been taught to use English count words (“one” through “sih” [six]) to label sets of one to six individual items (Pepperberg, 1994). He had also been taught to use the same count words to label the Arabic numerals 1 through 6. Without training, he inferred the relationship between the Arabic numerals and the sets of objects (Pepperberg, 2006b). In the present study, he was then trained to label vocally the Arabic numerals 7 and 8 (“sih-none”, “eight”, respectively) and to order these Arabic numerals with respect to the numeral 6. He subsequently inferred the ordinality of 7 and 8 with respect to the smaller numerals and he inferred use of the appropriate label for the cardinal values of seven and eight items. These data suggest that he constructed the cardinal meanings of “seven” (“sih–none”) and “eight” from his knowledge of the cardinal meanings of one through six, together with the place of “seven” (“sih–none”) and “eight” in the ordered count list.

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Why The Current Facebook Engagement Rate Calculation Is Inaccurate

As the social media analytics field is pretty new, it’s really important to understand how the metrics are computed.

 

Let’s take for example, one of the main metrics in measuring one’s page performance : the “Engagement Rate”.

 

What is supposed to be measured with the Engagement Rate ?

 

“The Engagement Rate measures how well your Fans interact with your content”. That’s a common definition.

 

What’s that supposed to mean ? If you have a 0.02%

 

Engagement Rate, it means 0.02% of your fans have engaged

with your content, isn’t it ?

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Towards a Unified Understanding of Event-Related Changes in the EEG: The Firefly Model of Synchronization through Cross-Frequency Phase Modulation

Towards a Unified Understanding of Event-Related Changes in the EEG: The Firefly Model of Synchronization through Cross-Frequency Phase Modulation | Social Foraging | Scoop.it

Although event-related potentials (ERPs) are widely used to study sensory, perceptual and cognitive processes, it remains unknown whether they are phase-locked signals superimposed upon the ongoing electroencephalogram (EEG) or result from phase-alignment of the EEG. Previous attempts to discriminate between these hypotheses have been unsuccessful but here a new test is presented based on the prediction that ERPs generated by phase-alignment will be associated with event-related changes in frequency whereas evoked-ERPs will not.

 

Using empirical mode decomposition (EMD), which allows measurement of narrow-band changes in the EEG without predefining frequency bands, evidence was found for transient frequency slowing in recognition memory ERPs but not in simulated data derived from the evoked model. Furthermore, the timing of phase-alignment was frequency dependent with the earliest alignment occurring at high frequencies. Based on these findings, the Firefly model was developed, which proposes that both evoked and induced power changes derive from frequency-dependent phase-alignment of the ongoing EEG. Simulated data derived from the Firefly model provided a close match with empirical data and the model was able to account for i) the shape and timing of ERPs at different scalp sites, ii) the event-related desynchronization in alpha and synchronization in theta, and iii) changes in the power density spectrum from the pre-stimulus baseline to the post-stimulus period. The Firefly Model, therefore, provides not only a unifying account of event-related changes in the EEG but also a possible mechanism for cross-frequency information processing.

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Why Wasp Foundresses Change Nests: Relatedness, Dominance, and Nest Quality

Why Wasp Foundresses Change Nests: Relatedness, Dominance, and Nest Quality | Social Foraging | Scoop.it

The costs and benefits of different social options are best understood when individuals can be followed as they make different choices, something that can be difficult in social insects. In this detailed study, we follow overwintered females of the social wasp Polistes carolina through different nesting strategies in a stratified habitat where nest site quality varies with proximity to a foraging area, and genetic relatedness among females is known. Females may initiate nests, join nests temporarily or permanently, or abandon nests. Females can become helpers or egglayers, effectively workers or queens. What they actually do can be predicted by a combination of ecological and relatedness factors. Advantages through increased lifetime success of individuals and nests drives foundresses of the social wasp Polistes from solitary to social nest founding.

 

We studied reproductive options of spring foundresses of P. carolina by monitoring individually-marked wasps and assessing reproductive success of each foundress by using DNA microsatellites. We examined what behavioral decisions foundresses make after relaxing a strong ecological constraint, shortage of nesting sites. We also look at the reproductive consequences of different behaviors. As in other Polistes, the most successful strategy for a foundress was to initiate a nest as early as possible and then accept others as subordinates. A common feature for many P. carolina foundresses was, however, that they reassessed their reproductive options by actively monitoring other nests at the field site and sometimes moving permanently to new nests should that offer better (inclusive) fitness prospects compared to their original nests. A clear motivation for moving to new nests was high genetic relatedness; by the end of the foundress period all females were on nests with full sisters.

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Bioengineers introduce 'Bi-Fi' -- The biological 'Internet'

Bioengineers introduce 'Bi-Fi' -- The biological 'Internet' | Social Foraging | Scoop.it

If you were a bacterium, the virus M13 might seem innocuous enough. It insinuates more than it invades, setting up shop like a freeloading houseguest, not a killer. Once inside it makes itself at home, eating your food, texting indiscriminately. Recently, however, bioengineers at Stanford University have given M13 a bit of a makeover.

 

The researchers, Monica Ortiz, a doctoral candidate in bioengineering, and Drew Endy, PhD, an assistant professor of bioengineering, have parasitized the parasite and harnessed M13's key attributes -- its non-lethality and its ability to package and broadcast arbitrary DNA strands -- to create what might be termed the biological Internet, or "Bi-Fi." Their findings were published online Sept. 7 in the Journal of Biological Engineering.

 

Using the virus, Ortiz and Endy have created a biological mechanism to send genetic messages from cell to cell. The system greatly increases the complexity and amount of data that can be communicated between cells and could lead to greater control of biological functions within cell communities. The advance could prove a boon to bioengineers looking to create complex, multicellular communities that work in concert to accomplish important biological functions.

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Snakes on a plane slither in engines

Snakes on a plane slither in engines | Social Foraging | Scoop.it

After algorithms spot a problem, snake-like robots may one day be used to investigate faulty engines, saving time and money

 

JUST sometimes, snakes on a plane can be a good thing. Snake-like robots wielding UV lasers may soon slither deep inside aircraft engines to seek out and repair damage, according to the British jet engine maker Rolls-Royce. Once it is up and running, the technology should help airlines deal with potential engine problems on the spot to keep planes in the air and avoid delays for passengers.

 

The idea for the snake robot stems partly from the fact that engine makers like Rolls-Royce and General Electric in the US routinely use intelligent algorithms to monitor the health of plane engines in flight. The software analyses data sent from around 100 pressure, temperature and vibration sensors embedded in each engine. These algorithms flag up trouble spots. But taking a plane out of service to strip down the engine can cost an airline millions of dollars - so technologies that can quickly inspect them are needed.

 

Right now, such checks are performed using a fibre-optic instrument called a borescope, a heavy-duty version of a medical endoscope. It is inserted in one of many 10 millimetre-wide ports dotted around a jet engine, allowing an engineer to look for, say, bird-strike damage to a fan or compressor blade. The trouble is, with Rolls-Royce monitoring 14,000 of its engines, flown by 500 airlines on 4000 aircraft worldwide, there are not enough borescope experts at all the airports the planes visit to do this diagnostic work.

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Facebook Seeks Next-Generation Big Data Tools

Social network giant Facebook and venture capital blue chip Accel Partners think emerging platforms like Hadoop deserve new business intelligence, data visualization, and analytics tools.

 

Forget about the business intelligence suites from IBM, Oracle, and SAP Business Objects, the analytics from SAS, and even the hot data visualization tools like Tableau Software. New platforms like Hadoop and NoSQL databases demand new tools that are purpose built for these environments.This is a core theme that Jay Parikh, VP of infrastructure engineering at Facebook, and Ping Li, a partner at venture capital firm Accel Partners, discussed on stage on Thursday at the DataWeek 2012

Conference in San Francisco. Their talk was about the challenges and opportunities facing startups and young companies in the big data arena, and Parikh and Li shared their message with InformationWeek by phone just hours before they took to the stage.

 

There's little doubt that Hadoop, NoSQL databases, and other emerging big data platforms are quickly evolving, says Li, "but we're hoping to see more new applications on top of these platforms." Parikh and Li are encouraging more innovation because there's not enough speed and breadth of development to truly feed a rich big data community, they say.

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Ten Simple Rules for Online Learning

The success of online courseware such as that offered by the Massachusetts Institute of Technology (MIT) (http://ocw.mit.edu) and now by many other institutions, together with a plethora of recent announcements of major new initiatives in this arena such as Coursera (https://www.coursera.org), Udacity (http://www.udacity.com), and the Harvard-MIT partnership edX (http://www.edxonline.org), have made it clear that online learning has reached a tipping point. Many signs point to the possibility in the near future of getting a quality, university-level education at a distance, and for free. As exciting as this prospect may be, it behooves online students to follow a few simple rules for getting the most out of the experience, while being realistic in their expectations.

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Bees decrease food intake, live longer when given compound found in red wine

Bees decrease food intake, live longer when given compound found in red wine | Social Foraging | Scoop.it

The idea that drinking red wine may provide health benefits – or possibly even extend your life – is an appealing thought for many people. Now, there may be added attraction. Researchers have found that when given resveratrol, a compound found in red wine, bees consume less food.

 

Previous scientific studies on resveratrol show that it lengthens the lifespan of diverse organisms ranging from unicellular yeast to fruit flies and mice. Since bees are social animals like humans, a team of scientists from Arizona State University, the Norwegian University of Life Sciences, and Harvard Medical School, decided to test the effects of the chemical on the honey bee.

 

In a series of experiments published in the journal Aging, the scientists tested the effects of resveratrol on the lifespan, learning ability, and food perception in honey bees.

 

Their research has confirmed that not only does this compound extend the lifespan of honey bees by 33 to 38 percent, it also changes the decisions that bees make about food by triggering a “moderation effect” when they eat.

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Artificially intelligent game bots pass the Turing test on Turing's centenary

Artificially intelligent game bots pass the Turing test on Turing's centenary | Social Foraging | Scoop.it

An artificially intelligent virtual gamer created by computer scientists at The University of Texas at Austin has won the BotPrize by convincing a panel of judges that it was more human-like than half the humans it competed against.

 

The competition was sponsored by 2K Games and was set inside the virtual world of "Unreal Tournament 2004," a first-person shooter video game. The winners were announced this month at the IEEE Conference on Computational Intelligence and Games.

 

"The idea is to evaluate how we can make game bots, which are nonplayer characters (NPCs) controlled by AI algorithms, appear as human as possible," said Risto Miikkulainen, professor of computer science in the College of Natural Sciences. Miikkulainen created the bot, called the UT^2 game bot, with doctoral students Jacob Schrum and Igor Karpov.

 

The bots face off in a tournament against one another and about an equal number of humans, with each player trying to score points by eliminating its opponents. Each player also has a "judging gun" in addition to its usual complement of weapons. That gun is used to tag opponents as human or bot.

 

The bot that is scored as most human-like by the human judges is named the winner. UT^2, which won a warm-up competition last month, shared the honors with MirrorBot, which was programmed by Romanian computer scientist Mihai Polceanu.

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Automatic building mapping could help emergency responders

Automatic building mapping could help emergency responders | Social Foraging | Scoop.it

MIT researchers have built a wearable sensor system that automatically creates a digital map of the environment through which the wearer is moving. The prototype system, described in a paper slated for the Intelligent Robots and Systems conference in Portugal next month, is envisioned as a tool to help emergency responders coordinate disaster response.In experiments conducted on the MIT campus, a graduate student wearing the sensor system wandered the halls, and the sensors wirelessly relayed data to a laptop in a distant conference room. Observers in the conference room were able to track the student’s progress on a map that sprang into being as he moved.

 

Connected to the array of sensors is a handheld pushbutton device that the wearer can use to annotate the map. In the prototype system, depressing the button simply designates a particular location as a point of interest. But the researchers envision that emergency responders could use a similar system to add voice or text tags to the map — indicating, say, structural damage or a toxic spill.

 

“The operational scenario that was envisioned for this was a hazmat situation where people are suited up with the full suit, and they go in and explore an environment,” says Maurice Fallon, a research scientist in MIT’s Computer Science and Artificial Intelligence Laboratory, and lead author on the new paper. “The current approach would be to textually summarize what they had seen afterward — ‘I went into this room on the left, I saw this, I went into the next room,’ and so on. We want to try to automate that.”

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Rapid acts of kindness: More cooperation in quick decisions, researchers find

Rapid acts of kindness: More cooperation in quick decisions, researchers find | Social Foraging | Scoop.it

Why are people sometimes willing to put “we” ahead of “me”? Perhaps our first impulse is to be selfish, and cooperation is all about reining in greed. Or maybe cooperation happens spontaneously, and too much thinking gets in the way.

 

Harvard scientists are getting closer to an answer, with research showing that people’s first response is to cooperate and that stopping to think encourages selfishness.

 

David Rand, a postdoctoral fellow in psychology, Joshua Greene, the John and Ruth Hazel Associate Professor of the Social Sciences, and Martin Nowak, professor of mathematics and of biology and director of the Program for Evolutionary Dynamics, published their findings in the Sept. 20 issue of Nature. They recruited thousands of participants to play a “public goods game.” Subjects were put into small groups and faced with a choice: keep the money you’ve been given, or contribute it to a common pool that grows and benefits the whole group. Hold onto the money and you come out ahead, but the group does best when everyone contributes.

 

The researchers wanted to know whether a person’s first impulse is cooperative or selfish. They started by looking at how quickly different people made their choices, and found that fast deciders were more likely to contribute to the common good.

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Fast algorithm extracts, compares document meaning

A computer program could compare two documents and work spot the differences in their meaning using a fast semantic algorithm developed by information scientists in Poland.

 

Writing in the International Journal of Intelligent Information and Database Systems, Andrzej Sieminski of the Technical University of Wroclaw, explains that extracting meaning and calculating the level of semantic similarity between two pieces of texts is a very difficult task, without human intervention. There have been various methods proposed by computer scientists for addressing this problem, but they all suffer from computational complexity, he says.

 

Sieminski has now attempted to reduce this complexity by merging a computationally efficient statistical approach to text analysis with a semantic component. Tests of the algorithm on English and Polish tests work well. The test set consisted of 4,890 English sentences with 142,116 words and 11,760 Polish sentences with 184,524 words scraped from online services via their newsfeeds over the course of five days. Sieminski points out that the complexity of the algorithm used on the Polish documents required an additional level of sophistication in terms of computing word means and disambiguation.

 

Traditional "manual" methods of indexing simply cannot now cope with the vast quantities of information generated on a daily basis by humanity as a whole in scientific research more specifically. The new algorithm once optimised could radically change the way in which we make archived documents searchable and allow knowledge to be extracted far more readily than is possible with standard indexing and search tools.

 

The approach also circumvents three critical problems faced by most users of conventional search engines: First, the lack of familiarity with the advanced search options of search engines, with a semantic algorithm advanced options become almost unnecessary. Secondly, the rigid nature of the options that are unable to catch the subtle nuance of user information needs, again a tool that understands the meaning of a search and the meaning of the results it offers avoids this problem. Finally, the unwillingness or unacceptably long time necessary to type a long query, semantically aware search will require only simply input.

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