Task partitioning in swarms of robots: an adaptive method for strategy selection

Task partitioning is the decomposition of a task into two or more sub-tasks that can be tackled separately. Task partitioning can be observed in many species of social insects, as it is often an advantageous way of organizing the work of a group of individuals. Potential advantages of task partitioning are, among others: reduction of interference between workers, exploitation of individuals?? skills and specializations, energy efficiency, and higher parallelism. Even though swarms of robots can benefit from task partitioning in the same way as social insects do, only few works in swarm robotics are dedicated to this subject. In this paper, we study the case in which a swarm of robots has to tackle a task that can be partitioned into a sequence of two sub-tasks. We propose a method that allows the individual robots in the swarm to decide whether to partition the given task or not. The method is self-organized, relies on the experience of each individual, and does not require explicit communication between robots. We evaluate the method in simulation experiments, using foraging as testbed. We study cases in which task partitioning is preferable and cases in which it is not. We show that the proposed method leads to good performance of the swarm in both cases, by employing task partitioning only when it is advantageous. We also show that the swarm is able to react to changes in the environmental conditions by adapting the behavior on-line. Scalability experiments show that the proposed method performs well across all the tested group sizes.     

A Simple,Realistic Stochastic Model of Gastric Emptying

Several models of Gastric Emptying (GE) have been employed in the past to represent the rate of delivery of stomach contents to the duodenum and jejunum. These models have all used a deterministic form (algebraic equations or ordinary differential equations), considering GE as a continuous, smooth process in time. However, GE is known to occur as a sequence of spurts, irregular both in size and in timing. Hence, we formulate a simple stochastic process model, able to represent the irregular decrements of gastric contents after a meal. The model is calibrated on existing literature data and provides consistent predictions of the observed variability in the emptying trajectories. This approach may be useful in metabolic modeling, since it describes well and explains the apparently heterogeneous GE experimental results in situations where common gastric mechanics across subjects would be expected.     

Recombinant hTRBP and hPACT Modulate hAgo2-Catalyzed siRNA-Mediated Target RNA Cleavage In Vitro

The human TAR RNA-binding protein (hTRBP) and protein activator of protein kinase R (hPACT) are important players in RNA interference (RNAi). Together with hArgonaute2 (hAgo2) and hDicer they have been reported to form the RISC-loading complex (RLC). Among other functions, hTRBP was suggested to assist the loading of hAgo2 with small interfering RNAs (siRNAs) within the RLC. Although several studies have been conducted to evaluate the specific functions of hTRBP and hPACT in RNAi, exact mechanisms and modes of action are still unknown. Here, we present a biochemical study further evaluating the role of hTRBP and hPACT in hAgo2-loading. We found that both proteins enhance hAgo2-mediated RNA cleavage significantly; even a hAgo2 mutant impaired in siRNA binding shows full cleavage activity in the presence of hTRBP or hPACT. Pre-steady state binding studies reveal that the assembly of wildtype-hAgo2 (wt-hAgo2) and siRNAs remains largely unaffected, whereas the binding of mutant hAgo2-PAZ9 to siRNA is restored by adding either hTRBP or hPACT. We conclude that both proteins assist in positioning the siRNA within hAgo2 to ensure optimal binding and cleavage. Overall, our data indicate that hTRBP and hPACT are part of a regulative system of RNAi that is important for efficient target RNA cleavage.     

Compositional Discrimination of Decompression and Decomposition Gas Bubbles in Bycaught Seals and Dolphins

Gas bubbles in marine mammals entangled and drowned in gillnets have been previously described by computed tomography, gross examination and histopathology. The absence of bacteria or autolytic changes in the tissues of those animals suggested that the gas was produced peri- or post-mortem by a fast decompression, probably by quickly hauling animals entangled in the net at depth to the surface. Gas composition analysis and gas scoring are two new diagnostic tools available to distinguish gas embolisms from putrefaction gases. With this goal, these methods have been successfully applied to pathological studies of marine mammals. In this study, we characterized the flux and composition of the gas bubbles from bycaught marine mammals in anchored sink gillnets and bottom otter trawls. We compared these data with marine mammals stranded on Cape Cod, MA, USA. Fresh animals or with moderate decomposition (decomposition scores of 2 and 3) were prioritized. Results showed that bycaught animals presented with significantly higher gas scores than stranded animals. Gas composition analyses indicate that gas was formed by decompression, confirming the decompression hypothesis.     

Large,Omega-3 Rich,Pelagic Diatoms under Arctic Sea Ice: Sources and Implications for Food Webs

Pelagic primary production in Arctic seas has traditionally been viewed as biologically insignificant until after the ice breakup. There is growing evidence however, that under-ice blooms of pelagic phytoplankton may be a recurrent occurrence. During the springs of 2011 and 2012, we found substantial numbers (201–5713 cells m⁻³) of the large centric diatom (diameter >250 µm) Coscinodiscus centralis under the sea ice in the Canadian Arctic Archipelago near Resolute Bay, Nunavut. The highest numbers of these pelagic diatoms were observed in Barrow Strait. Spatial patterns of fatty acid profiles and stable isotopes indicated two source populations for C. centralis: a western origin with low light conditions and high nutrients, and a northern origin with lower nutrient levels and higher irradiances. Fatty acid analysis revealed that pelagic diatoms had significantly higher levels of polyunsaturated fatty acids (mean ± SD: 50.3±8.9%) compared to ice-associated producers (30.6±10.3%) in our study area. In particular, C. centralis had significantly greater proportions of the long chain omega-3 fatty acid, eicosapentaenoic acid (EPA), than ice algae (24.4±5.1% versus 13.7±5.1%, respectively). Thus, C. centralis represented a significantly higher quality food source for local herbivores than ice algae, although feeding experiments did not show clear evidence of copepod grazing on C. centralis. Our results suggest that C. centralis are able to initiate growth under pack ice in this area and provide further evidence that biological productivity in ice-covered seas may be substantially higher than previously recognized.     

Variable Combinations of Specific Ephrin Ligand/Eph Receptor Pairs Control Embryonic Tissue Separation

Ephrins and Eph receptors are involved in the establishment of vertebrate tissue boundaries. The complexity of the system is puzzling, however in many instances, tissues express multiple ephrins and Ephs on both sides of the boundary, a situation that should in principle cause repulsion between cells within each tissue. Although co-expression of ephrins and Eph receptors is widespread in embryonic tissues, neurons, and cancer cells, it is still unresolved how the respective signals are integrated into a coherent output. We present a simple explanation for the confinement of repulsion to the tissue interface: Using the dorsal ectoderm–mesoderm boundary of the Xenopus embryo as a model, we identify selective functional interactions between ephrin–Eph pairs that are expressed in partial complementary patterns. The combined repulsive signals add up to be strongest across the boundary, where they reach sufficient intensity to trigger cell detachments. The process can be largely explained using a simple model based exclusively on relative ephrin and Eph concentrations and binding affinities. We generalize these findings for the ventral ectoderm–mesoderm boundary and the notochord boundary, both of which appear to function on the same principles. These results provide a paradigm for how developmental systems may integrate multiple cues to generate discrete local outcomes.     

From hybrids to hermaphrodites in population genetics

A report on the 46th annual PopGroup conference, Glasgow, UK, December 18-21, 2012.     

Starling Flock Networks Manage Uncertainty in Consensus at Low Cost

Flocks of starlings exhibit a remarkable ability to maintain cohesion as a group in highly uncertain environments and with limited, noisy information. Recent work demonstrated that individual starlings within large flocks respond to a fixed number of nearest neighbors, but until now it was not understood why this number is seven. We analyze robustness to uncertainty of consensus in empirical data from multiple starling flocks and show that the flock interaction networks with six or seven neighbors optimize the trade-off between group cohesion and individual effort. We can distinguish these numbers of neighbors from fewer or greater numbers using our systems-theoretic approach to measuring robustness of interaction networks as a function of the network structure, i.e., who is sensing whom. The metric quantifies the disagreement within the network due to disturbances and noise during consensus behavior and can be evaluated over a parameterized family of hypothesized sensing strategies (here the parameter is number of neighbors). We use this approach to further show that for the range of flocks studied the optimal number of neighbors does not depend on the number of birds within a flock; rather, it depends on the shape, notably the thickness, of the flock. The results suggest that robustness to uncertainty may have been a factor in the evolution of flocking for starlings. More generally, our results elucidate the role of the interaction network on uncertainty management in collective behavior, and motivate the application of our approach to other biological networks.