Time-Ordered Networks Reveal Limitations to Information Flow in Ant Colonies

BACKGROUND: An important function of many complex networks is to inhibit or promote the transmission of disease, resources, or information between individuals. However, little is known about how the temporal dynamics of individual-level interactions affect these networks and constrain their function. Ant colonies are a model comparative system for understanding general principles linking individual-level interactions to network-level functions because interactions among individuals enable integration of multiple sources of information to collectively make decisions, and allocate tasks and resources. METHODOLOGY/FINDINGS: Here we show how the temporal and spatial dynamics of such individual interactions provide upper bounds to rates of colony-level information flow in the ant Temnothorax rugatulus. We develop a general framework for analyzing dynamic networks and a mathematical model that predicts how information flow scales with individual mobility and group size. CONCLUSIONS/SIGNIFICANCE: Using thousands of time-stamped interactions between uniquely marked ants in four colonies of a range of sizes, we demonstrate that observed maximum rates of information flow are always slower than predicted, and are constrained by regulation of individual mobility and contact rate. By accounting for the ordering and timing of interactions, we can resolve important difficulties with network sampling frequency and duration, enabling a broader understanding of interaction network functioning across systems and scales

Spatial effects, sampling errors, and task specialization in the honey bee

Task allocation patterns should depend on the spatial distribution of work within the nest, variation in task demand, and the movement patterns of workers, however, relatively little research has focused on these topics. This study uses a spatially explicit agent based model to determine whether such factors alone can generate biases in task performance at the individual level in the honey bees, Apis mellifera. Specialization (bias in task performance) is shown to result from strong sampling error due to localized task demand, relatively slow moving workers relative to nest size, and strong spatial variation in task demand. To date, specialization has been primarily interpreted with the response threshold concept, which is focused on intrinsic (typically genotypic) differences between workers. Response threshold variation and sampling error due to spatial effects are not mutually exclusive, however, and this study suggests that both contribute to patterns of task bias at the individual level. While spatial effects are strong enough to explain some documented cases of specialization; they are relatively short term and not explanatory for long term cases of specialization. In general, this study suggests that the spatial layout of tasks and fluctuations in their demand must be explicitly controlled for in studies focused on identifying genotypic specialists

SiC Nanorods Grown on Electrospun Nanofibers Using Tb as Catalyst: Fabrication, Characterization, and Photoluminescence Properties

Well-crystallizedβ-SiC nanorods grown on electrospun nanofibers were synthesized by carbothermal reduction of Tb doped SiO2(SiO2:Tb) nanofibers at 1,250 °C. The as-synthesized SiC nanorods were 100–300 nm in diameter and 2–3 μm in length. Scanning electron microscopy (SEM) results suggested that the growth of the SiC nanorods should be governed by vapor-liquid-solid (VLS) mechanism with Tb metal as catalyst. Tb(NO3)3particles on the surface of the electrospun nanofibers were decomposed at 500 °C and later reduced to the formation of Tb nanoclusters at 1,200 °C, and finally the formation of a Si–C–Tb ally droplet will stimulate the VLS growth at 1,250 °C. Microstructure of the nanorod was further investigated by transmission electron microscopy (TEM). It was found that SiC <111> is the preferred initial growth direction. The liquid droplet was identified to be Si86Tb14, which acted as effective catalyst. Strong green emissions were observed from the SiC nanorod samples. Four characteristic photoluminescence (PL) peaks of Tb ions were also identified

Migration control: A distance compensation strategy in ants

©The Author(s) 2016. This article is published with open access at Springerlink.com. Migratory behaviour forms an intrinsic part of the life histories of many organisms but is often a high-risk process. Consequently, varied strategies have evolved to negate such risks, but empirical data relating to their functioning are limited. In this study, we use the model system of the househunting ant Temnothorax albipennis to demonstrate a key strategy that can shorten migration exposure times in a group of social insects. Colonies of these ants frequently migrate to new nest sites, and due to the nature of their habitat, the distances over which they do so are variable, leading to fluctuating potential costs dependent on migration parameters. We show that colonies of this species facultatively alter the dynamics of a migration and so compensate for the distance over which a given migration occurs. Specifically, they achieve this by modulating the rate of ‘tandem running’, in which workers teach each other the route to a new nest site. Using this method, colonies are able to engage a larger number of individuals in the migration process when the distance to be traversed is greater, and furthermore, the system appears to be based on perceived encounter rate at the individual level. This form of decentralised control highlights the adaptive nature of a behaviour of ecological importance, and indicates that the key to its robustness lies in the use of simple rules. Additionally, our results suggest that such coordinated group reactions are central to achieving the high levels of ecological success seen in many eusocial organisms

NURBS distance fields for extremely curved cracks

This paper presents the first methodology that combines a meshless method and the exact representation of cracks using Non-Uniform Rational B-Splines (NURBS). The methodology consists on developing an enrichment function based on distance functions to NURBS curves.The examples show the potential of the proposed approach and demonstrate the applicability to problems involving complex cracks that appear in sol-gel films

Ab initio calculations of optical properties of silver clusters: cross-over from molecular to nanoscale behavior

Electronic and optical properties of silver clusters were calculated using two different \textit{ab initio} approaches: 1) based on all-electron full-potential linearized-augmented plane-wave method and 2) local basis function pseudopotential approach. Agreement is found between the two methods for small and intermediate sized clusters for which the former method is limited due to its all-electron formulation. The latter, due to non-periodic boundary conditions, is the more natural approach to simulate small clusters. The effect of cluster size is then explored using the local basis function approach. We find that as the cluster size increases, the electronic structure undergoes a transition from molecular behavior to nanoparticle behavior at a cluster size of 140 atoms (diameter $\sim 1.7$\,nm). Above this cluster size the step-like electronic structure, evident as several features in the imaginary part of the polarizability of all clusters smaller than Ag$_\mathrm{147}$, gives way to a dominant plasmon peak localized at wavelengths 350\,nm$\le\lambda\le$ 600\,nm. It is, thus, at this length-scale that the conduction electrons' collective oscillations that are responsible for plasmonic resonances begin to dominate the opto-electronic properties of silver nanoclusters

Dynamic social networks in guppies (Poecilia reticulata)

One of the main challenges in the study of social networks in vertebrates is to close the gap between group patterns and dynamics. Usually scan samples or transect data are recorded to provide information about social patterns of animals, but these techniques themselves do not shed much light on the underlying dynamics of such groups. Here we show an approach which captures the fission-fusion dynamics of a fish population in the wild and demonstrates how the gap between pattern and dynamics may be closed. Our analysis revealed that guppies have complex association patterns that are characterised by close strong connections between individuals of similar behavioural type. Intriguingly, the preference for particular social partners is not expressed in the length of associations but in their frequency. Finally, we show that the observed association preferences could have important consequences for transmission processes in animal social networks, thus moving the emphasis of network research from descriptive mechanistic studies to functional and predictive ones. © 2014 Springer-Verlag Berlin Heidelberg