Social networks predict selective observation and information spread in ravens

Animals are predicted to selectively observe and learn from the conspecifics with whom they share social connections. Yet, hardly anything is known about the role of different connections in observation and learning. To address the relationships between social connections, observation, and learning patterns, we investigated information transmission in two raven (Corvus corax) groups. First, we quantified social connections in each group by constructing networks on affiliative interactions, aggressive interactions, and proximity. We then seeded novel information by training one group member on a novel task and allowing others to observe. In each group, an observation network based on who observed whose task-solving behavior was strongly correlated with networks based on affiliative interactions and proximity. Ravens with high social centrality (strength, eigenvector, information centrality) in the affiliative interaction network were also central in the observation network, possibly as a result of solving the task sooner and being observed frequently. Network-Based Diffusion Analysis (NBDA) revealed that the order in which ravens first solved the task was best predicted by connections in the affiliative interaction network in a group of subadult ravens, and by social rank and kinship (which influenced affiliative interactions) in a group of juvenile ravens from three families. Our results demonstrate that not all social connections are equally effective at predicting the patterns of selective observation and information transmission

Theoretical Bounds on Control-Plane Self-Monitoring in Routing Protocols

Routing protocols rely on the cooperation of nodes in the network to both forward packets and to select the forwarding routes. There have been several instances in which an entire network's routing collapsed simply because a seemingly insignificant set of nodes reported erroneous routing information to their neighbors. It may have been possible for other nodes to trigger an automated response and prevent the problem by analyzing received routing information for inconsistencies that revealed the errors. Our theoretical study seeks to understand when nodes can detect the existence of errors in the implementation of route selection elsewhere in the network through monitoring their own routing states for inconsistencies. We start by constructing a methodology, called Strong-Detection, that helps answer the question. We then apply Strong-Detection to three classes of routing protocols: distance-vector, path-vector, and link-state. For each class, we derive low-complexity, self-monitoring algorithms that use the routing state created by these routing protocols to identify any detectable anomalies. These algorithms are then used to compare and contrast the self-monitoring power these various classes of protocols possess. We also study the trade-off between their state-information complexity and ability to identify routing anomalies

A Stochastic Approach to Shortcut Bridging in Programmable Matter

In a self-organizing particle system, an abstraction of programmable matter, simple computational elements called particles with limited memory and communication self-organize to solve system-wide problems of movement, coordination, and configuration. In this paper, we consider a stochastic, distributed, local, asynchronous algorithm for "shortcut bridging", in which particles self-assemble bridges over gaps that simultaneously balance minimizing the length and cost of the bridge. Army ants of the genus Eciton have been observed exhibiting a similar behavior in their foraging trails, dynamically adjusting their bridges to satisfy an efficiency trade-off using local interactions. Using techniques from Markov chain analysis, we rigorously analyze our algorithm, show it achieves a near-optimal balance between the competing factors of path length and bridge cost, and prove that it exhibits a dependence on the angle of the gap being "shortcut" similar to that of the ant bridges. We also present simulation results that qualitatively compare our algorithm with the army ant bridging behavior. Our work gives a plausible explanation of how convergence to globally optimal configurations can be achieved via local interactions by simple organisms (e.g., ants) with some limited computational power and access to random bits. The proposed algorithm also demonstrates the robustness of the stochastic approach to algorithms for programmable matter, as it is a surprisingly simple extension of our previous stochastic algorithm for compression.Comment: Published in Proc. of DNA23: DNA Computing and Molecular Programming - 23rd International Conference, 2017. An updated journal version will appear in the DNA23 Special Issue of Natural Computin

Outbursts on normal stars. FH Leo misclassified as a novalike variable

We present high resolution spectroscopy of the common proper motion system FH Leo (components HD 96273 and BD+07 2411B), which has been classified as a novalike variable due to an outburst observed by Hipparcos, and we present and review the available photometry. We show from our spectra that neither star can possibly be a cataclysmic variable, instead they are perfectly normal late-F and early-G stars. We measured their radial velocities and derived the atmospheric fundamental parameters, abundances of several elements including Fe, Ni, Cr, Co, V, Sc, Ti, Ca and Mg, and we derive the age of the system. From our analysis we conclude that the stars do indeed constitute a physical binary. However, the observed outburst cannot be readily explained. We examine several explanations, including pollution with scattered light from Jupiter, binarity, microlensing, background supernovae, interaction with unseen companions and planetary engulfment. While no explanation is fully satisfactory, the scattered light and star-planet interaction scenarios emerge as the least unlikely ones, and we give suggestions for further study.Comment: 8 pages, 7 figures. Accepted for publication in A&

Variation in grouping patterns, mating systems and social structure: what socio-ecological models attempt to explain

Socio-ecological models aim to predict the variation in social systems based on a limited number of ecological parameters. Since the 1960s, the original model has taken two paths: one relating to grouping patterns and mating systems and one relating to grouping patterns and female social structure. Here, we review the basic ideas specifically with regard to non-human primates, present new results and point to open questions. While most primates live in permanent groups and exhibit female defence polygyny, recent studies indicate more flexibility with cooperative male resource defence occurring repeatedly in all radiations. In contrast to other animals, the potential link between ecology and these mating systems remains, however, largely unexplored. The model of the ecology of female social structure has often been deemed successful, but has recently been criticized. We show that the predicted association of agonistic rates and despotism (directional consistency of relationships) was not supported in a comparative test. The overall variation in despotism is probably due to phylogenetic grade shifts. At the same time, it varies within clades more or less in the direction predicted by the model. This suggests that the model's utility may lie in predicting social variation within but not across clades

A Holistic Approach to Service Survivability

We present SABER (Survivability Architecture: Block, Evade, React), a proposed survivability architecture that blocks, evades and reacts to a variety of attacks by using several security and survivability mechanisms in an automated and coordinated fashion. Contrary to the ad hoc manner in which contemporary survivable systems are built--using isolated, independent security mechanisms such as firewalls, intrusion detection systems and software sandboxes--SABER integrates several different technologies in an attempt to provide a unified framework for responding to the wide range of attacks malicious insiders and outsiders can launch. This coordinated multi-layer approach will be capable of defending against attacks targeted at various levels of the network stack, such as congestion-based DoS attacks, software-based DoS or code-injection attacks, and others. Our fundamental insight is that while multiple lines of defense are useful, most conventional, uncoordinated approaches fail to exploit the full range of available responses to incidents. By coordinating the response, the ability to survive even in the face of successful security breaches increases substantially. We discuss the key components of SABER, how they will be integrated together, and how we can leverage on the promising results of the individual components to improve survivability in a variety of coordinated attack scenarios. SABER is currently in the prototyping stages, with several interesting open research topics

The quest for companions to post-common envelope binaries. II. NSVS14256825 and HS0705+6700

We report new mid-eclipse times of the two close binaries NSVS14256825 and HS0705+6700, harboring an sdB primary and a low-mass main-sequence secondary. Both objects display clear variations in the measured orbital period, which can be explained by the action of a third object orbiting the binary. If this interpretation is correct, the third object in NSVS14256825 is a giant planet with a mass of roughly 12 M_Jup. For HS0705+6700, we provide evidence that strengthens the case for the suggested periodic nature of the eclipse time variation and reduces the uncertainties in the parameters of the brown dwarf implied by that model. The derived period is 8.4 yr and the mass is 31 M_Jup, if the orbit is coplanar with the binary. This research is part of the PlanetFinders project, an ongoing collaboration between professional astronomers and student groups at high schools.Comment: Accepted by Astron. and Astrophy