Cooperative object transport with a swarm of e-puck robots: robustness and scalability of evolved collective strategies

Cooperative object transport in distributed multi-robot systems requires the coordination and synchronisation of pushing/pulling forces by a group of autonomous robots in order to transport items that cannot be transported by a single agent. The results of this study show that fairly robust and scalable collective transport strategies can be generated by robots equipped with a relatively simple sensory apparatus (i.e. no force sensors and no devices for direct communication). In the experiments described in this paper, homogeneous groups of physical e-puck robots are required to coordinate and synchronise their actions in order to transport a heavy rectangular cuboid object as far as possible from its starting position to an arbitrary direction. The robots are controlled by dynamic neural networks synthesised using evolutionary computation techniques. The best evolved controller demonstrates an effective group transport strategy that is robust to variability in the physical characteristics of the object (i.e. object mass and size of the longest object’s side) and scalable to different group sizes. To run these experiments, we designed, built, and mounted on the robots a new sensor that returns the agents’ displacement on a 2D plane. The study shows that the feedback generated by the robots’ sensors relative to the object’s movement is sufficient to allow the robots to coordinate their efforts and to sustain the transports for an extended period of time. By extensively analysing successful behavioural strategies, we illustrate the nature of the operational mechanisms underpinning the coordination and synchronisation of actions during group transport

A Graph Algorithmic Approach to Separate Direct from Indirect Neural Interactions

Network graphs have become a popular tool to represent complex systems composed of many interacting subunits; especially in neuroscience, network graphs are increasingly used to represent and analyze functional interactions between neural sources. Interactions are often reconstructed using pairwise bivariate analyses, overlooking their multivariate nature: it is neglected that investigating the effect of one source on a target necessitates to take all other sources as potential nuisance variables into account; also combinations of sources may act jointly on a given target. Bivariate analyses produce networks that may contain spurious interactions, which reduce the interpretability of the network and its graph metrics. A truly multivariate reconstruction, however, is computationally intractable due to combinatorial explosion in the number of potential interactions. Thus, we have to resort to approximative methods to handle the intractability of multivariate interaction reconstruction, and thereby enable the use of networks in neuroscience. Here, we suggest such an approximative approach in the form of an algorithm that extends fast bivariate interaction reconstruction by identifying potentially spurious interactions post-hoc: the algorithm flags potentially spurious edges, which may then be pruned from the network. This produces a statistically conservative network approximation that is guaranteed to contain non-spurious interactions only. We describe the algorithm and present a reference implementation to test its performance. We discuss the algorithm in relation to other approximative multivariate methods and highlight suitable application scenarios. Our approach is a tractable and data-efficient way of reconstructing approximative networks of multivariate interactions. It is preferable if available data are limited or if fully multivariate approaches are computationally infeasible.Comment: 24 pages, 8 figures, published in PLOS On

Latitudinal gradient in dairy production with the introduction of farming in Atlantic Europe

International audienceThe introduction of farming had far-reaching impacts on health, social structure and demography. Although the spread of domesticated plants and animals has been extensively tracked, it is unclear how these nascent economies developed within different environmental and cultural settings. Using molecular and isotopic analysis of lipids from pottery, here we investigate the foods prepared by the earliest farming communities of the European Atlantic seaboard. Surprisingly, we find an absence of aquatic foods, including in ceramics from coastal sites, except in the Western Baltic where this tradition continued from indigenous ceramic using hunter-gatherer-fishers. The frequency of dairy products in pottery increased as farming was progressively introduced along a northerly latitudinal gradient. This finding implies that early farming communities needed time to adapt their economic practices before expanding into more northerly areas. Latitudinal differences in the scale of dairy production might also have influenced the evolution of adult lactase persistence across Europe

A Self-Organising Model of Thermoregulatory Huddling

Endotherms such as rats and mice huddle together to keep warm. The huddle is considered to be an example of a self-organising system, because complex properties of the collective group behaviour are thought to emerge spontaneously through simple interactions between individuals. Groups of rodent pups display two such emergent properties. First, huddling undergoes a ‘phase transition’, such that pups start to aggregate rapidly as the temperature of the environment falls below a critical temperature. Second, the huddle maintains a constant ‘pup flow’, where cooler pups at the periphery continually displace warmer pups at the centre. We set out to test whether these complex group behaviours can emerge spontaneously from local interactions between individuals. We designed a model using a minimal set of assumptions about how individual pups interact, by simply turning towards heat sources, and show in computer simulations that the model reproduces the first emergent property—the phase transition. However, this minimal model tends to produce an unnatural behaviour where several smaller aggregates emerge rather than one large huddle. We found that an extension of the minimal model to include heat exchange between pups allows the group to maintain one large huddle but eradicates the phase transition, whereas inclusion of an additional homeostatic term recovers the phase transition for large huddles. As an unanticipated consequence, the extended model also naturally gave rise to the second observed emergent property—a continuous pup flow. The model therefore serves as a minimal description of huddling as a self-organising system, and as an existence proof that group-level huddling dynamics emerge spontaneously through simple interactions between individuals. We derive a specific testable prediction: Increasing the capacity of the individual to generate or conserve heat will increase the range of ambient temperatures over which adaptive thermoregulatory huddling will emerge

Schemas d'ordre eleve en espace et/ou en temps pour l'equation des ondes acoustiques 1-D

Theme 4 - Simulation et optimisation de systemes complexes - Projet OndesAvailable from INIST (FR), Document Supply Service, under shelf-number : 14802 E, issue : a.1999 n.3759 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueSIGLEFRFranc

XIAP Restricts TNF- and RIP3-Dependent Cell Death and Inflammasome Activation

X-linked inhibitor of apoptosis protein (XIAP) has been identified as a potent regulator of innate immune responses, and loss-of-function mutations inXIAP cause the development of the X-linked lymphoproliferative syndrome type 2 (XLP-2) in humans. Using gene-targeted mice, we show that loss of XIAPor deletion of its RING domain lead to excessive cell death and IL-1β secretion from dendritic cells triggered by diverse Toll-like receptor stimuli. Aberrant IL-1β secretion is TNF dependent and requires RIP3 but is independent of cIAP1/cIAP2. The observed cell death also requires TNF and RIP3 but proceeds independently of caspase-1/caspase-11 or caspase-8 function. Loss of XIAP results in aberrantly elevated ubiquitylation of RIP1 outside of TNFR complex I. Virally infected Xiap-/- mice present with symptoms reminiscent of XLP-2. Our data show that XIAP controls RIP3-dependent cell death and IL-1β secretion in response to TNF, which might contribute to hyperinflammation in patients with XLP-2. © 2014 The Authors

XIAP restricts TNF- and RIP3-dependent cell death and inflammasome activation.

X-linked inhibitor of apoptosis protein (XIAP) has been identified as a potent regulator of innate immune responses, and loss-of-function mutations in XIAP cause the development of the X-linked lymphoproliferative syndrome type 2 (XLP-2) in humans. Using gene-targeted mice, we show that loss of XIAP or deletion of its RING domain lead to excessive cell death and IL-1β secretion from dendritic cells triggered by diverse Toll-like receptor stimuli. Aberrant IL-1β secretion is TNF dependent and requires RIP3 but is independent of cIAP1/cIAP2. The observed cell death also requires TNF and RIP3 but proceeds independently of caspase-1/caspase-11 or caspase-8 function. Loss of XIAP results in aberrantly elevated ubiquitylation of RIP1 outside of TNFR complex I. Virally infected Xiap(-/-) mice present with symptoms reminiscent of XLP-2. Our data show that XIAP controls RIP3-dependent cell death and IL-1β secretion in response to TNF, which might contribute to hyperinflammation in patients with XLP-2