Social Foraging
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Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
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A Cross-Taxon Analysis of Insect-Associated Bacterial Diversity

A Cross-Taxon Analysis of Insect-Associated Bacterial Diversity | Social Foraging | Scoop.it

Although it is well known that plants and animals harbor microbial symbionts that can influence host traits, the factors regulating the structure of these microbial communities often remain largely undetermined. This is particularly true for insect-associated microbial communities, as few cross-taxon comparisons have been conducted to date. To address this knowledge gap and determine how host phylogeny and ecology affect insect-associated microbial communities, we collected 137 insect specimens representing 39 species, 28 families, and 8 orders, and characterized the bacterial communities associated with each specimen via 16S rRNA gene sequencing. Bacterial taxa within the phylum Proteobacteria were dominant in nearly all insects sampled. On average, the insect-associated bacterial communities were not very diverse, with individuals typically harboring fewer than 8 bacterial phylotypes. Bacterial communities also tended to be dominated by a single phylotype; on average, the most abundant phylotype represented 54.7% of community membership. Bacterial communities were significantly more similar among closely related insects than among less-related insects, a pattern driven by within-species community similarity but detected at every level of insect taxonomy tested. Diet was a poor predictor of bacterial community composition. Individual insect species harbored remarkably unique communities: the distribution of 69.0% of bacterial phylotypes was limited to unique insect species, whereas only 5.7% of phylotypes were detected in more than five insect species. Together these results suggest that host characteristics strongly regulate the colonization and assembly of bacterial communities across insect lineages, patterns that are driven either by co-evolution between insects and their symbionts or by closely related insects sharing conserved traits that directly select for similar bacterial communities.

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Brain Activation in Motor Sequence Learning Is Related to the Level of Native Cortical Excitability

Brain Activation in Motor Sequence Learning Is Related to the Level of Native Cortical Excitability | Social Foraging | Scoop.it

Cortical excitability may be subject to changes through training and learning. Motor training can increase cortical excitability in motor cortex, and facilitation of motor cortical excitability has been shown to be positively correlated with improvements in performance in simple motor tasks. Thus cortical excitability may tentatively be considered as a marker of learning and use-dependent plasticity. Previous studies focused on changes in cortical excitability brought about by learning processes, however, the relation between native levels of cortical excitability on the one hand and brain activation and behavioral parameters on the other is as yet unknown. In the present study we investigated the role of differential native motor cortical excitability for learning a motor sequencing task with regard to post-training changes in excitability, behavioral performance and involvement of brain regions. Our motor task required our participants to reproduce and improvise over a pre-learned motor sequence. Over both task conditions, participants with low cortical excitability (CElo) showed significantly higher BOLD activation in task-relevant brain regions than participants with high cortical excitability (CEhi). In contrast, CElo and CEhi groups did not exhibit differences in percentage of correct responses and improvisation level. Moreover, cortical excitability did not change significantly after learning and training in either group, with the exception of a significant decrease in facilitatory excitability in the CEhi group. The present data suggest that the native, unmanipulated level of cortical excitability is related to brain activation intensity, but not to performance quality. The higher BOLD mean signal intensity during the motor task might reflect a compensatory mechanism in CElo participants.

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Can We Predict Personality in Fish? Searching for Consistency over Time and across Contexts

Can We Predict Personality in Fish? Searching for Consistency over Time and across Contexts | Social Foraging | Scoop.it

The interest in animal personality, broadly defined as consistency of individual behavioural traits over time and across contexts, has increased dramatically over the last years. Individual differences in behaviour are no longer recognised as noise around a mean but rather as adaptive variation and thus, essentially, raw material for evolution. Animal personality has been considered evolutionary conserved and has been shown to be present in all vertebrates including fish. Despite the importance of evolutionary and comparative aspects in this field, few studies have actually documented consistency across situations in fish. In addition, most studies are done with individually housed fish which may pose additional challenges when interpreting data from social species. Here, we investigate, for the first time in fish, whether individual differences in behavioural responses to a variety of challenges are consistent over time and across contexts using both individual and grouped-based tests. Twenty-four juveniles of Gilthead seabream Sparus aurata were subjected to three individual-based tests: feed intake recovery in a novel environment, novel object and restraining and to two group-based tests: risk-taking and hypoxia. Each test was repeated twice to assess consistency of behavioural responses over time. Risk taking and escape behaviours during restraining were shown to be significantly consistent over time. In addition, consistency across contexts was also observed: individuals that took longer to recover feed intake after transfer into a novel environment exhibited higher escape attempts during a restraining test and escaped faster from hypoxia conditions. These results highlight the possibility to predict behaviour in groups from individual personality traits.

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Life Span Evolution in Eusocial Workers—A Theoretical Approach to Understanding the Effects of Extrinsic Mortality in a Hierarchical System

Life Span Evolution in Eusocial Workers—A Theoretical Approach to Understanding the Effects of Extrinsic Mortality in a Hierarchical System | Social Foraging | Scoop.it

While the extraordinary life span of queens and division of labor in eusocial societies have been well studied, it is less clear which selective forces act on the short life span of workers. The disparity of life span between the queen and the workers is linked to a basic issue in sociobiology: How are the resources in a colony allocated between colony maintenance and reproduction? Resources for somatic maintenance of the colony can either be invested into quality or quantity of workers. Here, we present a theoretical optimization model that uses a hierarchical trade-off within insect colonies and extrinsic mortality to explain how different aging phenotypes could have evolved to keep resources secure in the colony. The model points to the significance of two factors. First, any investment that would generate a longer intrinsic life span for workers is lost if the individual dies from external causes while foraging. As a consequence, risky environments favor the evolution of workers with a shorter life span. Second, shorter-lived workers require less investment than long-lived ones, allowing the colony to allocate these resources to sexual reproduction or colony growth.

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Ecological and Evolutionary Processes Drive the Origin and Maintenance of Imperfect Mimicry

Ecological and Evolutionary Processes Drive the Origin and Maintenance of Imperfect Mimicry | Social Foraging | Scoop.it

Although the forces behind the evolution of imperfect mimicry remain poorly studied, recent hypotheses suggest that relaxed selection on small-bodied individuals leads to imperfect mimicry. While evolutionary history undoubtedly affects the development of imperfect mimicry, ecological community context has largely been ignored and may be an important driver of imperfect mimicry. Here we investigate how evolutionary and ecological contexts might influence mimetic fidelity in Müllerian and Batesian mimicry systems. In Batesian hoverfly systems we find that body size is not a strong predictor of mimetic fidelity. However, in Müllerian velvet ants we find a weak positive relationship between body size and mimetic fidelity when evolutionary context is controlled for and a much stronger relationship between community diversity and mimetic fidelity. These results suggest that reduced selection on small-bodied individuals may not be a major driver of the evolution of imperfect mimicry and that other factors, such as ecological community context, should be considered when studying the evolution of imperfect mimicry.

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Interdependent Multi-Layer Networks: Modeling and Survivability Analysis with Applications to Space-Based Networks

Interdependent Multi-Layer Networks: Modeling and Survivability Analysis with Applications to Space-Based Networks | Social Foraging | Scoop.it

This article develops a novel approach and algorithmic tools for the modeling and survivability analysis of networks with heterogeneous nodes, and examines their application to space-based networks. Space-based networks (SBNs) allow the sharing of spacecraft on-orbit resources, such as data storage, processing, and downlink. Each spacecraft in the network can have different subsystem composition and functionality, thus resulting in node heterogeneity. Most traditional survivability analyses of networks assume node homogeneity and as a result, are not suited for the analysis of SBNs. This work proposes that heterogeneous networks can be modeled as interdependent multi-layer networks, which enables their survivability analysis. The multi-layer aspect captures the breakdown of the network according to common functionalities across the different nodes, and it allows the emergence of homogeneous sub-networks, while the interdependency aspect constrains the network to capture the physical characteristics of each node. Definitions of primitives of failure propagation are devised. Formal characterization of interdependent multi-layer networks, as well as algorithmic tools for the analysis of failure propagation across the network are developed and illustrated with space applications. The SBN applications considered consist of several networked spacecraft that can tap into each other's Command and Data Handling subsystem, in case of failure of its own, including the Telemetry, Tracking and Command, the Control Processor, and the Data Handling sub-subsystems. Various design insights are derived and discussed, and the capability to perform trade-space analysis with the proposed approach for various network characteristics is indicated. The select results here shown quantify the incremental survivability gains (with respect to a particular class of threats) of the SBN over the traditional monolith spacecraft. Failure of the connectivity between nodes is also examined, and the results highlight the importance of the reliability of the wireless links between spacecraft (nodes) to enable any survivability improvements for space-based networks.

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The Science of What We Do (and Don't) Know About Data Visualization

The Science of What We Do (and Don't) Know About Data Visualization | Social Foraging | Scoop.it

Visualization is easy, right? After all, it's just some colorful shapes and a few text labels. But things are more complex than they seem, largely due to the the ways we see and digest charts, graphs, and other data-driven images. While scientifically-backed studies do exist, there are actually many things we don't know about how and why visualization works. To help you make better decisions when visualizing your data, here's a brief tour of the research.

 

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Researchers Map Shortcuts between all Human Genes

Researchers Map Shortcuts between all Human Genes | Social Foraging | Scoop.it

Some diseases are caused by single gene mutations. Current techniques for identifying the disease-causing gene in a patient produce hundreds of potential gene candidates, making it difficult for scientists to pinpoint the single causative gene. Now, a team of researchers led by Rockefeller University scientists has created a map of gene “shortcuts” to simplify the hunt for disease-causing genes.

 

The investigation, spearheaded by Yuval Itan, a postdoctoral fellow in the St. Giles Laboratory of Human Genetics of Infectious Diseases, has led to the creation of what he calls the human gene connectome, the full set of distances, routes (the genes on the way) and degrees of separation between any two human genes. Itan, a computational biologist, says the computer program he developed to generate the connectome uses the same principles that GPS navigation devices use to plan a trip between two locations. The research is reported in the online early edition of the journal Proceedings of the National Academy of Sciences.

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The economy needs agent-based modelling

In this article the authors propose the used of agent-based models to assess policies that address economic recovery. The authors are critical of the econometric and dynamic stochastic general equilibrium models employ by U.S. administration arguing that the models have fatal flaws. Thus, the authors discuss the advantages and application of agent-based models, which is a computerized simulation of a number of decision-makers and institutions that interact under prescribed rules.
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Michael Holder's comment, April 19, 2013 11:55 PM
free version of above not easily found - here's a pdf version: http://tuvalu.santafe.edu/~jdf/papers/EconomyNeeds.pdf
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From Data to Decisions: A Value Chain for Big Data

With exponential growth in data, enterprises must act to make the most of the vast data landscape—to thoughtfully apply multiple technologies, carefully select key data for specific investigations, and innovatively tailor large integrated datasets to support specific queries and analyses. All these actions will flow from a data value chain—a framework to manage data holistically from capture to decision making and to support a variety of stakeholders and their technologies.

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Negative feedback in ants: crowding results in less trail pheromone deposition

Crowding in human transport networks reduces efficiency. Efficiency can be increased by appropriate control mechanisms, which are often imposed externally. Ant colonies also have distribution networks to feeding sites outside the nest and can experience crowding. However, ants do not have external controllers or leaders. Here, we report a self-organized negative feedback mechanism, based on local information, which downregulates the production of recruitment signals in crowded parts of a network by Lasius niger ants. We controlled crowding by manipulating trail width and the number of ants on a trail, and observed a 5.6-fold reduction in the number of ants depositing trail pheromone from least to most crowded conditions. We also simulated crowding by placing glass beads covered in nest-mate cuticular hydrocarbons on the trail. After 10 bead encounters over 20 cm, forager ants were 45 per cent less likely to deposit pheromone. The mechanism of negative feedback reported here is unusual in that it acts by downregulating the production of a positive feedback signal, rather than by direct inhibition or the production of an inhibitory signal.

 
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Artificial Intelligence Can Now Beat Super Mario Bros.

Artificial Intelligence Can Now Beat Super Mario Bros. | Social Foraging | Scoop.it

Tired of playing video games now that the sun is starting to make regular appearances and the outside world is looking more inviting? Good news! Now there’s a computer program that can play your video games for you! Computer scientist Tom Murphy has developed an artificial intelligence that can play NES games like Super Mario Bros. all by itself. It doesn’t even have to trade off the controller with its kid brother every other life.

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Shocking Paper Claims That Microsoft Excel Coding Error Is Behind The Reinhart-Rogoff Study On Debt

Shocking Paper Claims That Microsoft Excel Coding Error Is Behind The Reinhart-Rogoff Study On Debt | Social Foraging | Scoop.it

In 2010, economists Carmen Reinhart and Kenneth Rogoff released a paper, "Growth in a Time of Debt." Their "main result is that...median growth rates for countries with public debt over 90 percent of GDP are roughly one percent lower than otherwise; average (mean) growth rates are several percent lower." Countries with debt-to-GDP ratios above 90 percent have a slightly negative average growth rate, in fact.

 

This has been one of the most cited stats in the public debate during the Great Recession. Paul Ryan's Path to Prosperity budget states their study "found conclusive empirical evidence that [debt] exceeding 90 percent of the economy has a significant negative effect on economic growth." The Washington Post editorial board takes it as an economic consensus view, stating that "debt-to-GDP could keep rising — and stick dangerously near the 90 percent mark that economists regard as a threat to sustainable economic growth." 

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Cooperation and Defection at the Crossroads

Cooperation and Defection at the Crossroads | Social Foraging | Scoop.it

We study a simple traffic model with a non-signalized road intersection. In this model the car arriving from the right has precedence. The vehicle dynamics far from the crossing are governed by the rules introduced by Nagel and Paczuski, which define how drivers behave when braking or accelerating. We measure the average velocity of the ensemble of cars and its flow as a function of the density of cars on the roadway. An additional set of rules is defined to describe the dynamics at the intersection assuming a fraction of drivers that do not obey the rule of precedence. This problem is treated within a game-theory framework, where the drivers that obey the rule are cooperators and those who ignore it are defectors. We study the consequences of these behaviors as a function of the fraction of cooperators and defectors. The results show that cooperation is the best strategy because it maximizes the flow of vehicles and minimizes the number of accidents. A rather paradoxical effect is observed: for any percentage of defectors the number of accidents is larger when the density of cars is low because of the higher average velocity.

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Metastability and Inter-Band Frequency Modulation in Networks of Oscillating Spiking Neuron Populations

Metastability and Inter-Band Frequency Modulation in Networks of Oscillating Spiking Neuron Populations | Social Foraging | Scoop.it

Groups of neurons firing synchronously are hypothesized to underlie many cognitive functions such as attention, associative learning, memory, and sensory selection. Recent theories suggest that transient periods of synchronization and desynchronization provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in different structures and interacting with each other. This paper explores inter-band frequency modulation between neural oscillators using models of quadratic integrate-and-fire neurons and Hodgkin-Huxley neurons. We vary the structural connectivity in a network of neural oscillators, assess the spectral complexity, and correlate the inter-band frequency modulation. We contrast this correlation against measures of metastable coalition entropy and synchrony. Our results show that oscillations in different neural populations modulate each other so as to change frequency, and that the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Further to this, we locate an area in the connectivity space in which the system directs itself in this way so as to explore a large repertoire of synchronous coalitions. We suggest that such dynamics facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby supports sophisticated cognitive processing in the brain.

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Holding Multiple Items in Short Term Memory: A Neural Mechanism

Holding Multiple Items in Short Term Memory: A Neural Mechanism | Social Foraging | Scoop.it

Human short term memory has a capacity of several items maintained simultaneously. We show how the number of short term memory representations that an attractor network modeling a cortical local network can simultaneously maintain active is increased by using synaptic facilitation of the type found in the prefrontal cortex. We have been able to maintain 9 short term memories active simultaneously in integrate-and-fire simulations where the proportion of neurons in each population, the sparseness, is 0.1, and have confirmed the stability of such a system with mean field analyses. Without synaptic facilitation the system can maintain many fewer memories active in the same network. The system operates because of the effectively increased synaptic strengths formed by the synaptic facilitation just for those pools to which the cue is applied, and then maintenance of this synaptic facilitation in just those pools when the cue is removed by the continuing neuronal firing in those pools. The findings have implications for understanding how several items can be maintained simultaneously in short term memory, how this may be relevant to the implementation of language in the brain, and suggest new approaches to understanding and treating the decline in short term memory that can occur with normal aging.

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Does Habitat Variability Really Promote Metabolic Network Modularity?

Does Habitat Variability Really Promote Metabolic Network Modularity? | Social Foraging | Scoop.it

The hypothesis that variability in natural habitats promotes modular organization is widely accepted for cellular networks. However, results of some data analyses and theoretical studies have begun to cast doubt on the impact of habitat variability on modularity in metabolic networks. Therefore, we re-evaluated this hypothesis using statistical data analysis and current metabolic information. We were unable to conclude that an increase in modularity was the result of habitat variability. Although horizontal gene transfer was also considered because it may contribute for survival in a variety of environments, closely related to habitat variability, and is known to be positively correlated with network modularity, such a positive correlation was not concluded in the latest version of metabolic networks. Furthermore, we demonstrated that the previously observed increase in network modularity due to habitat variability and horizontal gene transfer was probably due to a lack of available data on metabolic reactions. Instead, we determined that modularity in metabolic networks is dependent on species growth conditions. These results may not entirely discount the impact of habitat variability and horizontal gene transfer. Rather, they highlight the need for a more suitable definition of habitat variability and a more careful examination of relationships of the network modularity with horizontal gene transfer, habitats, and environments.

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The Role of Pre-Existing Disturbances in the Effect of Marine Reserves on Coastal Ecosystems: A Modelling Approach

The Role of Pre-Existing Disturbances in the Effect of Marine Reserves on Coastal Ecosystems: A Modelling Approach | Social Foraging | Scoop.it

We have used an end-to-end ecosystem model to explore responses over 30 years to coastal no-take reserves covering up to 6% of the fifty thousand square kilometres of continental shelf and slope off the coast of New South Wales (Australia). The model is based on the Atlantis framework, which includes a deterministic, spatially resolved three-dimensional biophysical model that tracks nutrient flows through key biological groups, as well as extraction by a range of fisheries. The model results support previous empirical studies in finding clear benefits of reserves to top predators such as sharks and rays throughout the region, while also showing how many of their major prey groups (including commercial species) experienced significant declines. It was found that the net impact of marine reserves was dependent on the pre-existing levels of disturbance (i.e. fishing pressure), and to a lesser extent on the size of the marine reserves. The high fishing scenario resulted in a strongly perturbed system, where the introduction of marine reserves had clear and mostly direct effects on biomass and functional biodiversity. However, under the lower fishing pressure scenario, the introduction of marine reserves caused both direct positive effects, mainly on shark groups, and indirect negative effects through trophic cascades. Our study illustrates the need to carefully align the design and implementation of marine reserves with policy and management objectives. Trade-offs may exist not only between fisheries and conservation objectives, but also among conservation objectives.

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An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection

An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection | Social Foraging | Scoop.it

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.

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Together We’re Smarter: Tips for Using Digital Learning to Make the Most of Collective Intelligence

Together We’re Smarter: Tips for Using Digital Learning to Make the Most of Collective Intelligence | Social Foraging | Scoop.it
Whenever I speak at a conference I take the same approach – I look for ways to get people talking to one-another and contributing to the session. I figure; we’ve got a room full of smart, highly ex...

Via Viktor Markowski
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Viktor Markowski's curator insight, April 18, 2013 11:30 AM

A simple but sound advice

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Tynker Launches Revolutionary New Platform for Teaching Programming Skills to Young Learners

Tynker Launches Revolutionary New Platform for Teaching Programming Skills to Young Learners | Social Foraging | Scoop.it

(http://www.Tynker.com), a new company focused on helping children develop computational thinking and programming skills, today announced the general availability of the Tynker Learning Platform. After successfully piloting Tynker with young learners in over 20 elementary and middle schools, the company’s programming skills platform is now available to teachers and schools across the United States and Canada. Teachers can set up a programming skills classroom at http://www.Tynker.com to immediately try out this highly interactive computational learning platform for free.

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Sue Blough's curator insight, April 21, 2013 11:20 PM

This sounds particularly attractive to those who favor Logical/Mathematical and Spatial learning experiences. The program focusses on building a strong foundation in STEM skills (science, technology, engineering and math).

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Agents of influence: Giving those 'who fly the economy more information and a better control stick'

Models of complex systems have become a staple of business strategy, and now they are showing early promise for improving economic forecasts.

For cargo carriers, the most direct route is not always the cheapest. In the early 2000s, Southwest Airlines adopted a new approach to shipping: Rather than switching cargo from one flight to another to minimize the distance it covered, the airline would take circuitous routes to destinations on fewer flights. The strategy seemed counterintuitive, but it has saved the company millions of dollars in storage rentals and cargo handlers’ wages.

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Ants are good at crowd control!

Ants are good at crowd control! | Social Foraging | Scoop.it

"Go to the ant," is the instruction. But when ants are crowded, they cannot get around their trails so easily. Without external control on the Lasius niger colony, crowding could easily lower the efficiency of working of the whole colony. In this series of experiments, Tomer J. Czaczkes, Christoph Gruter and Francis L. W. Ratnieks found that crowding reduced pheromone deposition by workers.

 

They publish their paper today in the Journal of the Royal Society Interface. The ants' trail pheromones are normally deposited regularly on trails, but when experimentation reduced "crowding" artificially, their deposition reduced by a factor of 5 or 6.

 

While humans and other species coordinate their individuals with top-down instruction, complex control mechanisms can be necessary in routing procedures For example the "dynamic task allocation" you can hear about in a factory or similar institution. Insects are expert, on the other hand, in using bottom-up mechanisms like these in order to regulate collective behaviour.

 

The black garden ant in the grounds of the University of Sussex is a common but useful member of the community. Collected in the University grounds, plastic 40x30x20cm plastic boxes housed the foraging activity of 500-1000 workers with no queen involved. Some brood encouraged normal behaviours in Plaster-of Paris nests, forming living quarters within the plastic boxes. As there were no complaints, we assume the ants were comfortable with the accommodation, all meals provided (with experiments).

 

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Alt Text: Your Guide to Data After Death

Alt Text: Your Guide to Data After Death | Social Foraging | Scoop.it
Google has introduced the “Inactive Account Manager,” which is a polite way of saying “Decide what you want us to do with your data after you’re dead, because we will outlive you and your children and your children’s children. Google is forever. Google is eternal. Look upon my Web, ye mighty, and despair.” Or something like that.

 

Now we all know that Google is rarely the first to do things. It generally takes existing services — search, e-mail, ignoring your privacy settings — and attempts to improve on them. This is no exception. Here are some other services that actually exist to help you deal with your data after you’ve kicked the bit bucket.

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Court transcripts, military reports reveal telling patterns in information

Court transcripts, military reports reveal telling patterns in information | Social Foraging | Scoop.it

If you were to wander the halls of a courthouse during a murder trail, could you predict the verdict from the conversations you would overhear? And what would be the smallest amount of information you would require to make that prediction? 

 

Discovering patterns in information is more than a game of courtroom prescience; it is a serious matter with applications in warfare, stock markets, human health, and other complex systems. 

 

Finding a reliable technique for detecting such patterns, however, is difficult. SFI Research Fellow Simon DeDeo, SFI Graduate Fellow Sara Klingenstein, and undergraduate researcher Robert Hawkins are drawing on information theory and a couple of remarkable data sets for help. 

In one example, the researchers analyzed some 250 years of transcripts from the Old Bailey criminal court in England to look for patterns in trials that led to guilty verdicts.

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