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Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
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The Regulation of Ant Colony Foraging Activity without Spatial Information

The Regulation of Ant Colony Foraging Activity without Spatial Information | Social Foraging | Scoop.it

Many dynamical networks, such as the ones that produce the collective behavior of social insects, operate without any central control, instead arising from local interactions among individuals. A well-studied example is the formation of recruitment trails in ant colonies, but many ant species do not use pheromone trails. We present a model of the regulation of foraging by harvester ant (Pogonomyrmex barbatus) colonies. This species forages for scattered seeds that one ant can retrieve on its own, so there is no need for spatial information such as pheromone trails that lead ants to specific locations. Previous work shows that colony foraging activity, the rate at which ants go out to search individually for seeds, is regulated in response to current food availability throughout the colony's foraging area.

 

Ants use the rate of brief antennal contacts inside the nest between foragers returning with food and outgoing foragers available to leave the nest on the next foraging trip. Here we present a feedback-based algorithm that captures the main features of data from field experiments in which the rate of returning foragers was manipulated. The algorithm draws on our finding that the distribution of intervals between successive ants returning to the nest is a Poisson process. We fitted the parameter that estimates the effect of each returning forager on the rate at which outgoing foragers leave the nest. We found that correlations between observed rates of returning foragers and simulated rates of outgoing foragers, using our model, were similar to those in the data. Our simple stochastic model shows how the regulation of ant colony foraging can operate without spatial information, describing a process at the level of individual ants that predicts the overall foraging activity of the colony.

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Evolutionary Dynamics of Strategic Behavior in a Collective-Risk Dilemma

Evolutionary Dynamics of Strategic Behavior in a Collective-Risk Dilemma | Social Foraging | Scoop.it

A collective-risk social dilemma arises when a group must cooperate to reach a common target in order to avoid the risk of collective loss while each individual is tempted to free-ride on the contributions of others. In contrast to the prisoners' dilemma or public goods games, the collective-risk dilemma encompasses the risk that all individuals lose everything. These characteristics have potential relevance for dangerous climate change and other risky social dilemmas. Cooperation is costly to the individual and it only benefits all individuals if the common target is reached.

 

An individual thus invests without guarantee that the investment is worthwhile for anyone. If there are several subsequent stages of investment, it is not clear when individuals should contribute. For example, they could invest early, thereby signaling their willingness to cooperate in the future, constantly invest their fair share, or wait and compensate missing contributions. To investigate the strategic behavior in such situations, we have simulated the evolutionary dynamics of such collective-risk dilemmas in a finite population. Contributions depend individually on the stage of the game and on the sum of contributions made so far. Every individual takes part in many games and successful behaviors spread in the population. It turns out that constant contributors, such as constant fair sharers, quickly lose out against those who initially do not contribute, but compensate this in later stages of the game. In particular for high risks, such late contributors are favored.

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End of Life Predictive Model

A system that combines the use of artificial intelligence to predict the end of life period in patient. A preferred embodiment discloses a system for identifying patients needing healthcare, comprising: a first module for preparation of patient data for input to statistical modeling submodules; a second module for evaluating outcome data of the statistical modeling submodules and establishing the predictive values meeting a predetermined criteria and applying the values to a first set of neural net models; and a third module configured to apply the results from the first set of neural net models to a second set of neural net models and generate a results set indicative of patients needing healthcare, wherein the patient data comprises data from a pre-determined population set. Patient data can be government health data, insurance healthcare data, or commercial healthcare data. The predetermined criterion is the risk of death in a predetermined time frame. The results set identifies patients eligible for or needing end of life care. The system identifies patients at risk of death. The system may also identify patients who are predicted to die within a predetermined time frame.

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Facebook Founders Back Union City Startup’s Artificial Intelligence Research

Facebook Founders Back Union City Startup’s Artificial Intelligence Research | Social Foraging | Scoop.it

Union City-based Vicarious will receive $15 million in financing from various investors, including groups led by Facebook, PayPal and Napster founders.

 

Founders of Facebook, PayPal and Napster are betting big bucks on a Union City technology startup’s research in artificial intelligence.

 

Vicarious, which creates “software that thinks and learns like a human,” announced yesterday that the research team had received $15 million in financing from various investment groups. Among them are Good Ventures, a firm started by Facebook co-founder Dustin Moskovitz, and Founders Fund, a group managed by PayPal co-founder Peter Thiel and Sean Parker, a co-founder of Napster and Facebook’s first president.

 

“The technology that Vicarious is developing has the potential to improve all lives and revolutionize every industry,” Moskovitz said in a statement released yesterday.

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Humans Have Ten Times More Bacteria Than Human Cells: How Do Microbial Communities Affect Human Health?

The number of bacteria living within the body of the average healthy adult human are estimated to outnumber human cells 10 to 1. Changes in these microbial communities may be responsible for digestive disorders, skin diseases, gum disease and even obesity. Despite their vital imporance in human health and disease, these communities residing within us remain largely unstudied and a concerted research effort needs to be made to better understand them, say researchers June 3 at the 108th General Meeting of the American Society for Microbiology in Boston.

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Psychologists link emotion to vividness of perception and creation of vivid memories

Psychologists link emotion to vividness of perception and creation of vivid memories | Social Foraging | Scoop.it

Have you ever wondered why you can remember things from long ago as if they happened yesterday, yet sometimes can't recall what you ate for dinner last night? According to a new study led by psychologists at the University of Toronto, it's because how much something means to you actually influences how you see it as well as how vividly you can recall it later.

 

"We've discovered that we see things that are emotionally arousing with greater clarity than those that are more mundane," says Rebecca Todd, a postdoctoral fellow in U of T's Department of Psychology and lead author of the study published recently in the Journal of Neuroscience. "Whether they're positive -- for example, a first kiss, the birth of a child, winning an award -- or negative, such as traumatic events, breakups, or a painful and humiliating childhood moment that we all carry with us, the effect is the same."

"What's more, we found that how vividly we perceive something in the first place predicts how vividly we will remember it later on," says Todd. "We call this 'emotionally enhanced vividness' and it is like the flash of a flashbub that illuminates an event as it's captured for memory."

 

By studying brain activity, Todd, psychology professor Adam Anderson and other colleagues at U of T, along with researchers at the University of Manchester and the University of California, San Diego found that the part of the brain responsible for tagging the emotional or motivational importance of things according to one's own past experience -- the amygdala -- is more active when looking at images that are rated as vivid. This increased activation in turn influences activity in both the visual cortex, enhancing activity linked to seeing objects, and in the posterior insula, a region that integrates sensations from the body.

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John Vollenbroek's curator insight, November 4, 2013 5:14 AM

Keep the stories in your organization alive !

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Bacteria Evolve to Go Against the Grain

Bacteria Evolve to Go Against the Grain | Social Foraging | Scoop.it

Drug gradients may give bacteria an evolutionary boost towards antibiotic resistance.

 

Since Alexander Fleming discovered in 1928 that a substance secreted by a mold could kill bacteria, we have become used to the ease of administering cocktails of antibiotics to fight bacterial infections. However, the use and misuse of antibiotics in human medicine and livestock farming over many decades has had the serious side effect of selecting for bacteria that survive drug attack: many bacterial strains have emerged that are resistant to antibiotics, most famously the multi-drug-resistant Staphylococcus aureus strain, the source of Staph infections, that represents a major threat to hospital patients. The pool of effective antibiotics is running out, and finding new strategies to prevent the rapid evolution of drug resistance has become a pressing challenge for global health.

 

Now, two independent theoretical studies, one published in Physical Review Letters by Philip Greulich at the University of Edinburgh, UK, and colleagues [1], and the other by Rutger Hermsen at the Center for Theoretical Biological Physics, San Diego, and colleagues in Proceedings of the National Academy of Sciences [2], address how the evolution of drug resistance can be profoundly influenced by how drugs are distributed in biological tissues. Once administered, drugs do not spread evenly throughout the human body, which is compartmentalized and composed of tissues that have different affinity for retaining the drugs. The new research suggests that variations in the drug concentration may play an important role in selecting bacterial strains that are able to survive exposure to antibiotics.

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Lost Letter Measure of Variation in Altruistic Behaviour in 20 Neighbourhoods

Lost Letter Measure of Variation in Altruistic Behaviour in 20 Neighbourhoods | Social Foraging | Scoop.it

Altruistic behaviour varies across human populations and this variation is likely to be partly explained by variation in the ecological context of the populations. We hypothesise that area level socio-economic characteristics will determine the levels of altruism found in individuals living in an area and we use a lost letter experiment to measure altruism across 20 neighbourhoods with a wide range of income deprivation scores in London, UK. The results show a strong negative effect of neighbourhood income deprivation on altruistic behaviour, with letters dropped in the poorest neighbourhoods having 91% lower odds of being returned than letters dropped in the wealthiest neighbourhoods. We suggest that measures of altruism are strongly context dependant.

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Automatons Get Creative

Automatons Get Creative | Social Foraging | Scoop.it

Creative types tend to think of themselves as doing work that is beyond the reach of automation. Computers can't parse nuance, the thinking goes, or summon the imaginative powers that are required of writers, artists, technological innovators and policy-makers. As it turns out, however, this flattering assumption is mistaken. Computers can be creative after all.

 

The more we understand about creativity, the more we are able to distill it into the language of algorithms—the "brains" behind computer programs. An algorithm takes a series of inputs and then, moving through its own decision tree, issues an output or an answer. The gears can be as simple as binary questions of yes/no—or they can be a series of complicated differential equations that draw on outside databases.

 

The point, ultimately, is that algorithms are fast, repeatable and easy to use at massive scale. They are already determining some of the music that reaches our ears, movies that reach the big screen, decisions regarding national security and even the kind of people we often reach on the phone.

 

Music would seem an unlikely entry point for algorithms, but they have arrived. In 2004, the New Zealander Ben Novak was just another guitar-strummer songwriter hoping to crack into music with a record deal. On a whim, he paid $50 to upload one of his songs to a website that claimed to have an algorithm capable of finding hits. The algorithm gave Mr. Novak's song a rare and lofty score, putting it on par with classics such as "Take it Easy" by the Eagles and Steppenwolf's "Born to Be Wild."

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'DNA wires' could help physicians diagnose disease

In a discovery that defies the popular meaning of the word "wire," scientists have found that Mother Nature uses DNA as a wire to detect the constantly occurring genetic damage and mistakes that ― if left unrepaired ― can result in diseases like cancer and underpin the physical and mental decline of aging.

 

That topic ― DNA wires and their potential use in identifying people at risk for certain diseases ― is the focus of a plenary talk on August 19 during the 244th National Meeting & Exposition of the American Chemical Society in Philadelphia, Pennsylvania.

 

"DNA is a very fragile and special wire," said Jacqueline K. Barton, Ph.D., who delivered the talk. "You're never going to wire a house with it, and it isn't sturdy enough to use in popular electronic devices. But that fragile state is exactly what makes DNA so good as an electrical biosensor to identify DNA damage."

 

Barton won the U.S. National Medal of Science, the nation's highest honor for scientific achievement, for discovering that cells use the double strands of the DNA helix like a wire for signaling, which is critical to detecting and repairing genetic damage. She is a professor of chemistry and is chair of the division of chemistry and chemical engineering at the California Institute of Technology in Pasadena.

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Why are elderly duped? Area in brain where doubt arises changes with age

Why are elderly duped? Area in brain where doubt arises changes with age | Social Foraging | Scoop.it

Everyone knows the adage: "If something sounds too good to be true, then it probably is." Why, then, do some people fall for scams and why are older folks especially prone to being duped?

 

An answer, it seems, is because a specific area of the brain has deteriorated or is damaged, according to researchers at the University of Iowa. By examining patients with various forms of brain damage, the researchers report they've pinpointed the precise location in the human brain, called the ventromedial prefrontal cortex, that controls belief and doubt, and which explains why some of us are more gullible than others.

 

"The current study provides the first direct evidence beyond anecdotal reports that damage to the vmPFC (ventromedial prefrontal cortex) increases credulity. Indeed, this specific deficit may explain why highly intelligent vmPFC patients can fall victim to seemingly obvious fraud schemes," the researchers wrote in the paper published in a special issue of the journal Frontiers in Neuroscience.

 

A study conducted for the National Institute of Justice in 2009 concluded that nearly 12 percent of Americans 60 and older had been exploited financially by a family member or a stranger. And, a report last year by insurer MetLife Inc. estimated the annual loss by victims of elder financial abuse at $2.9 billion.

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Harvard cracks DNA storage, crams 700 terabytes of data into a single gram

Harvard cracks DNA storage, crams 700 terabytes of data into a single gram | Social Foraging | Scoop.it

A bioengineer and geneticist at Harvard's Wyss Institute have successfully stored 5.5 petabits of data -- around 700 terabytes -- in a single gram of DNA, smashing the previous DNA data density record by a thousand times.

 

The work, carried out by George Church and Sri Kosuri, basically treats DNA as just another digital storage device. Instead of binary data being encoded as magnetic regions on a hard drive platter, strands of DNA that store 96 bits are synthesized, with each of the bases (TGAC) representing a binary value (T and G = 1, A and C = 0).

 

To read the data stored in DNA, you simply sequence it — just as if you were sequencing the human genome — and convert each of the TGAC bases back into binary. To aid with sequencing, each strand of DNA has a 19-bit address block at the start (the red bits in the image below) — so a whole vat of DNA can be sequenced out of order, and then sorted into usable data using the addresses.

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Ngozi Odochi (Godwell) Nwokocha's comment, August 19, 2012 2:41 PM
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Maintaining a Cognitive Map in Darkness: The Need to Fuse Boundary Knowledge with Path Integration

Maintaining a Cognitive Map in Darkness: The Need to Fuse Boundary Knowledge with Path Integration | Social Foraging | Scoop.it

Spatial navigation requires the processing of complex, disparate and often ambiguous sensory data. The neurocomputations underpinning this vital ability remain poorly understood. Controversy remains as to whether multimodal sensory information must be combined into a unified representation, consistent with Tolman's “cognitive map”, or whether differential activation of independent navigation modules suffice to explain observed navigation behaviour. Here we demonstrate that key neural correlates of spatial navigation in darkness cannot be explained if the path integration system acted independently of boundary (landmark) information. In vivo recordings demonstrate that the rodent head direction (HD) system becomes unstable within three minutes without vision. In contrast, rodents maintain stable place fields and grid fields for over half an hour without vision.

 

Using a simple HD error model, we show analytically that idiothetic path integration (iPI) alone cannot be used to maintain any stable place representation beyond two to three minutes. We then use a measure of place stability based on information theoretic principles to prove that featureless boundaries alone cannot be used to improve localization above chance level. Having shown that neither iPI nor boundaries alone are sufficient, we then address the question of whether their combination is sufficient and – we conjecture – necessary to maintain place stability for prolonged periods without vision. We addressed this question in simulations and robot experiments using a navigation model comprising of a particle filter and boundary map. The model replicates published experimental results on place field and grid field stability without vision, and makes testable predictions including place field splitting and grid field rescaling if the true arena geometry differs from the acquired boundary map. We discuss our findings in light of current theories of animal navigation and neuronal computation, and elaborate on their implications and significance for the design, analysis and interpretation of experiments.

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Artificial Neural Networks Trained to Detect Viral and Phage Structural Proteins

Artificial Neural Networks Trained to Detect Viral and Phage Structural Proteins | Social Foraging | Scoop.it

Phages play critical roles in the survival and pathogenicity of their hosts, via lysogenic conversion factors, and in nutrient redistribution, via cell lysis. Analyses of phage- and viral-encoded genes in environmental samples provide insights into the physiological impact of viruses on microbial communities and human health. However, phage ORFs are extremely diverse of which over 70% of them are dissimilar to any genes with annotated functions in GenBank. Better identification of viruses would also aid in better detection and diagnosis of disease, in vaccine development, and generally in better understanding the physiological potential of any environment. In contrast to enzymes, viral structural protein function can be much more challenging to detect from sequence data because of low sequence conservation, few known conserved catalytic sites or sequence domains, and relatively limited experimental data.

 

We have designed a method of predicting phage structural protein sequences that uses Artificial Neural Networks (ANNs). First, we trained ANNs to classify viral structural proteins using amino acid frequency; these correctly classify a large fraction of test cases with a high degree of specificity and sensitivity. Subsequently, we added estimates of protein isoelectric points as a feature to ANNs that classify specialized families of proteins, namely major capsid and tail proteins. As expected, these more specialized ANNs are more accurate than the structural ANNs. To experimentally validate the ANN predictions, several ORFs with no significant similarities to known sequences that are ANN-predicted structural proteins were examined by transmission electron microscopy. Some of these self-assembled into structures strongly resembling virion structures.

 

Thus, our ANNs are new tools for identifying phage and potential prophage structural proteins that are difficult or impossible to detect by other bioinformatic analysis. The networks will be valuable when sequence is available but in vitro propagation of the phage may not be practical or possible.

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Russian brains behind closest ever AI attempt

Russian brains behind closest ever AI attempt | Social Foraging | Scoop.it

Russian scientists are closer than they have ever been to creating artificial intelligence. The program called “Eugene” has almost passed the famous Turing test, which checks a machine’s ability to exhibit intelligent behavior.

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The program-emulating a personality of a 13-year old boy was exhibited at an international science contest in the United Kingdom along with four other programs.

 

Even with the exacting criteria, “Eugene” has left all its competitors far behind.

 

The test was designed by mathematician and computer scientist, Alan Turing over 60 years ago. During the examination a human judge engages in a text conversation with a machine and an actual human being without seeing them. If the judge fails to tell the machine from the human in at least 30 percent of the answers, the program passes.

 

So far no program has managed to pass successfully but Russia’s “Eugene” has come strikingly close. It deceived human judges in 29,2 percent of the answers.

 

A total of 29 judges took part in the test with some 150 dialogues taking place.

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Teaching robots to learn like little children

Teaching robots to learn like little children | Social Foraging | Scoop.it

Robots are everywhere. But for them to be useful, they have to be programmed by people. Computer scientists are now looking for ways to teach robots how to teach themselves.

 

Lars Schillingmann, a computer scientist at CoR-Lab, a research institute for Cognition and Robotics at the University of Bielefeld, is playing with toy cups.

 

"Look, the green cup goes in the blue one, the yellow one goes in the green one and the red one goes in the yellow one."

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Algorithms that can help us spend, spend, spend

Algorithms that can help us spend, spend, spend | Social Foraging | Scoop.it

Intelligent algorithms are changing the way we do business, whether it’s in tempting us to buy designer shoes, or leading multi-million pound investments.

 

We've all heard it. That little imaginary companion, sitting on your shoulder. "Go on," it says. "You deserve a treat. Buy it."

 

That "it" could be anything. Clothes, shoes, gadgets - we all have our vices. But what if that imaginary voice - which is, willpower permitting, under your control - one day became real?

 

DBS Bank calls it a "personal concierge", and it's best understood by picturing yourself in an expensive designer clothes shop.

 

Your smartphone knows where you are - thanks to the GPS location technology found in many apps these days - and it alerts your bank through an automated system that you've signed up to. As well as knowing you've got a history of buying from similar stores, your bank also knows that you're running a bit low on cash at the moment.

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Researchers make quantum processor capable of factoring a composite number into prime factors

Researchers make quantum processor capable of factoring a composite number into prime factors | Social Foraging | Scoop.it

Computing prime factors may sound like an elementary math problem, but try it with a large number, say one that contains more than 600 digits, and the task becomes enormously challenging and impossibly time-consuming. Now, a group of researchers at UC Santa Barbara has designed and fabricated a quantum processor capable of factoring a composite number -- in this case the number 15 -- into its constituent prime factors, 3 and 5.

 

Although modest compared to a 600-digit number, the achievement represents a milestone on the road map to building a quantum computer capable of factoring much larger numbers, with significant implications for cryptography and cybersecurity. The results are published in the advance online issue of the journal Nature Physics.

 

"Fifteen is a small number, but what's important is we've shown that we can run a version of Peter Shor's prime factoring algorithm on a solid state quantum processor. This is really exciting and has never been done before," said Erik Lucero, the paper's lead author. Now a postdoctoral researcher in experimental quantum computing at IBM, Lucero was a doctoral student in physics at UCSB when the research was conducted and the paper was written.

 

"What is important is that the concepts used in factoring this small number remain the same when factoring much larger numbers," said Andrew Cleland, a professor of physics at UCSB and a collaborator on the experiment. "We just need to scale up the size of this processor to something much larger. This won't be easy, but the path forward is clear."

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Powerful new chip helps diagnose disease, analyzes protein interactions

Researchers at the Stanford University School of Medicine and Intel Corp. have collaborated to synthesize and study a grid-like array of short pieces of a disease-associated protein on silicon chips normally used in computer microprocessors. They used this chip, which was created through a process used to make semiconductors, to identify patients with a particularly severe form of the autoimmune disease lupus.

 

Although the new technology is focused on research applications, it has the potential to eventually improve diagnoses of a multitude of diseases, as well as to determine more quickly what drugs may be most effective for a particular patient. It may also speed drug development by enabling researchers to better understand how proteins interact in the body.

 

"When I see patients in the clinic right now, I may know they have arthritis, but I don't know which of the 20 or 30 types of the disease they have," said associate professor of medicine Paul (P.J.) Utz, MD, noting that existing methods can take days or even weeks to answer such questions. "Now we can measure thousands of protein interactions at a time, integrate this information to diagnose the disease and even determine how severe it may be. We may soon be able to do this routinely while the patient is still in the physician's office."

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Who's Reading And Using Scientific Papers? Academia Will Find Out

Who's Reading And Using Scientific Papers? Academia Will Find Out | Social Foraging | Scoop.it

One of the best things about the widespread adoption of the internet and social media has been the ability of scientists to share their research quickly. Sites like ArXiv and ResearchGate allow papers and other data to be shared among like-minded academics and the public alike prior to journal publication. But despite the easy spread of information, one problem remains: how can academics determine how influential and impactful their work truly is? That’s where Academia.edu, one of the largest academic social networks, has stepped in.

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Winning isn't everything: Evolutionary stability of Zero Determinant strategies

Zero Determinant (ZD) strategies are a new class of probabilistic and conditional strategies that are able to unilaterally set the expected payoff of an opponent in iterated plays of the Prisoner's Dilemma irrespective of the opponent's strategy, or else to set the ratio between a ZD player's and their opponent's expected payoff. Here we show that while ZD strategies are weakly dominant, they are not evolutionarily stable and will instead evolve into less coercive strategies. We suggest that ZD strategies with an informational advantage over other players that allows them to recognize other ZD strategies will be evolutionarily stable (and able to exploit other players). However, such an advantage is bound to be short-lived as opposing strategies evolve to counteract the recognition

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Artificial intelligence helps detect subtle differences in mutant worms

Artificial intelligence helps detect subtle differences in mutant worms | Social Foraging | Scoop.it

Research into the genetic factors behind certain disease mechanisms, illness progression and response to new drugs is frequently carried out using tiny multi-cellular animals such as nematodes, fruit flies or zebra fish.

 

Often, progress relies on the microscopic visual examination of many individual animals to detect mutants worthy of further study.

 

Now, scientists have demonstrated an automated system that uses artificial intelligence and cutting-edge image processing to rapidly examine large numbers of individual Caenorhabditis elegans, a species of nematode widely used in biological research. Beyond replacing existing manual examination steps using microfluidics and automated hardware, the system's ability to detect subtle differences from worm-to-worm – without human intervention – can identify genetic mutations that might not have been detected otherwise.

 

By allowing thousands of worms to be examined autonomously in a fraction of the time required for conventional manual screening, the technique could change the way that high throughput genetic screening is carried out using C. elegans.

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Indigenous peoples at forefront of climate change offer lessons on plant biodiversity

Indigenous peoples at forefront of climate change offer lessons on plant biodiversity | Social Foraging | Scoop.it

Humans are frequently blamed for deforestation and the destruction of environments, yet there are also examples of peoples and cultures around the world that have learned to manage and conserve the precious resources around them. The Yanesha of the upper Peruvian Amazon and the Tibetans of the Himalayas are two groups of indigenous peoples carrying on traditional ways of life, even in the face of rapid environmental changes. Over the last 40 years, Dr. Jan Salick, senior curator and ethnobotanist with the William L. Brown Center of the Missouri Botanical Garden has worked with these two cultures.

 

She explains how their traditional knowledge and practices hold the key to conserving, managing and even creating new biodiversity in a paper released in the new text, "Biodiversity in Agriculture: Domestication, Evolution, and Sustainability," published by Cambridge University Press.

 

The Yanesha and Tibetans are dramatically different peoples living in radically dissimilar environments, but both cultures utilize and highly value plant biodiversity for their food, shelters, clothing and medicines.

 

"Both cultures use traditional knowledge to create, manage and conserve this biodiversity, and both are learning to adapt to and mitigate the effects of climate change," said Salick. "They have much to teach and to offer the world if we can successfully learn to integrate science and traditional knowledge.

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‘Superorganisations’ – Learning from Nature’s Networks

‘Superorganisations’ – Learning from Nature’s Networks | Social Foraging | Scoop.it

This is a complete version of a ‘long-blog’ written by Al Kennedy on behalf of ‘The Nature of Business’ blog and BCI: Biomimicry for Creative Innovation www.businessinspiredbynature.com

I hope you enjoy this ‘long-blog’, as it covers important issues for today’s business paradigm shift and looks at the alignment of digitisation, organisational evolution and ecological thinking (and has useful links throughout for further information).

 

Fritjof Capra, in his book ‘The Hidden Connections’ applies aspects of complexity theory, particularly the analysis of networks, to global capitalism and the state of the world; and eloquently argues the case that social systems such as organisations and networks are not just like living systems – they are living systems. The concept and theory of living systems (technically known as autopoiesis) was introduced in 1972 by Chilean biologists Humberto Maturana and Francisco Varela.

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Next-Generation Digital Information Storage in DNA

Digital information is accumulating at an astounding rate, straining our ability to store and archive it. DNA is among the most dense and stable information media known. The development of new technologies in both DNA synthesis and sequencing make DNA an increasingly feasible digital storage medium. Here, we develop a strategy to encode arbitrary digital information in DNA, write a 5.27-megabit book using DNA microchips, and read the book using next-generation DNA sequencing.

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