Ants work harder during consensus decision-making in small groups

Individuals derive many benefits from being social, one of which is improved accuracy of decision-making, the so-called ‘wisdom of the crowds’ effect. This advantage arises because larger groups can pool information from more individuals. At present, limited empirical data indicate that larger groups outperform smaller ones during consensus decision-making in human and non-human animals. Inaccurate decisions can lead to significant costs, and we might therefore expect individuals in small groups to employ mechanisms to compensate for the lack of numbers. Small groups may be able to maintain decision accuracy if individuals are better informed than those in larger groups and/or by increasing the proportion of the group involved in collective decision-making relative to larger groups. In this study, we use interactive computer vision software to investigate individual contributions to consensus decision-making during house-hunting in different sized groups of the ant Myrmecina nipponica. We show that individuals in small colonies invest greater effort in the consensus decision process than those in large colonies and should be better informed as a result. This may act to ameliorate the limitations of group size, but could leave smaller groups more susceptible to additional stresses.     

Optimal control of distributed hyperbolic systems with deviating arguments

In this paper optimal control problems for hyperbolic systems in which deviating arguments appear in the integral form both in the state equations and in the boundary conditions are considered. Making use of Lion's scheme, necessary and sufficient conditions of optimality for the Neumann problem are derived. A simple example of application is also provided.     

Decision rules extraction from data stream in the presence of changing context for diabetes treatment

The knowledge extraction is an important element of the e-Health system. In this paper, we introduce a new method for decision rules extraction called Graph-based Rules Inducer to support the medical interview in the diabetes treatment. The emphasis is put on the capability of hidden context change tracking. The context is understood as a set of all factors affecting patient condition. In order to follow context changes, a forgetting mechanism with a forgetting factor is implemented in the proposed algorithm. Moreover, to aggregate data, a graph representation is used and a limitation of the search space is proposed to protect from overfitting. We demonstrate the advantages of our approach in comparison with other methods through an empirical study on the Electricity benchmark data set in the classification task. Subsequently, our method is applied in the diabetes treatment as a tool supporting medical interviews.     

To boldly go: an occam-π mission to engineer emergence

Future systems will be too complex to design and implement explicitly. Instead, we will have to learn to engineer complex behaviours indirectly: through the discovery and application of local rules of behaviour, applied to simple process components, from which desired behaviours predictably emerge through dynamic interactions between massive numbers of instances. This paper describes a process-oriented architecture for fine-grained concurrent systems that enables experiments with such indirect engineering. Examples are presented showing the differing complex behaviours that can arise from minor (non-linear) adjustments to low-level parameters, the difficulties in suppressing the emergence of unwanted (bad) behaviour, the unexpected relationships between apparently unrelated physical phenomena (shown up by their separate emergence from the same primordial process swamp) and the ability to explore and engineer completely new physics (such as force fields) by their emergence from low-level process interactions whose mechanisms can only be imagined, but not built, at the current time.     

Synthesis and characterisation of fluorescent pyrene‐end‐capped polylactide fibres

Fluorescent markers are critical for tracking the position and movement of molecules both in vivo and in vitro. Conventionally, synthetic dyes are non‐covalently added to polymers for fluorescent tracking, but often diffuse away. Here we demonstrate, for the first time, a facile method for the synthesis of fluorescent poly(lactic acid) nano‐/microfibres for biomedical applications using solution spin blowing. Pyrene‐end‐capped poly(l ‐lactide) (PLLA) derivatives were synthesised using the ring‐opening polymerisation of l ‐lactide and they were characterised using spectroscopic and thermal analyses. Submicrometre‐sized fluorescent fibres were produced from these PLLA derivatives using solution blow spinning techniques generating polymer blends and core–shell fibres. Such system could be further exploited to incorporate electrically conductive carbon allotropes via the pyrene aromaticity, producing fluorescent and electrically active fibres for in vitro monitoring and electrical stimulation. © 2018 Society of Chemical Industry     

Investigating fuel-cell transport limitations using hydrogen limiting current

Reducing mass-transport losses in polymer-electrolyte fuel cells (PEFCs) is essential to increase their power density and reduce overall stack cost. At the same time, cost also motivates the reduction in expensive precious-metal catalysts, which results in higher local transport losses in the catalyst layers. In this paper, we use a hydrogen-pump limiting-current setup to explore the gas-phase transport losses through PEFC catalyst layers and various gas-diffusion and microporous layers. It is shown that the effective diffusivity in the gas-diffusion layers is a strong function of liquid saturation. In addition, it is shown how the catalyst layer unexpectedly contributes significantly to the overall measured transport resistance. This is especially true for low catalyst loadings. It is also shown how the various losses can be separated into different mechanisms including diffusional processes and mass-dependent and independent ones, where the data suggests that a large part of the transport resistance in catalyst layers cannot be attributed to a gas-phase diffusional process. The technique is promising for deconvoluting transport losses in PEFCs.     

Self Assembly–Assisted Additive Manufacturing: Direct Ink Write 3D Printing of Epoxy–Amine Thermosets

The use of self‐assembling, pre‐polymer materials in 3D printing is rare, due to difficulties of facilitating printing with low molecular weight species and preserving their reactivity and/or functions on the macroscale. Akin to 3D printing of small molecules, examples of extrusion‐based printing of pre‐polymer thermosets are uncommon, arising from their limited rheological tuneability and slow reactions kinetics. The direct ink write (DIW) 3D printing of a two‐part resin, Epon 828 and Jeffamine D230, using a self‐assembly approach is reported. Through the addition of self‐assembling, ureidopyrimidinone‐modified Jeffamine D230 and nanoclay filler, suitable viscoelastic properties are obtained, enabling 3D printing of the epoxy–amine pre‐polymer resin. A significant increase in viscosity is observed, with an infinite shear rate viscosity of approximately two orders of magnitude higher than control resins, in addition to, an increase in yield strength and thixotropic behavior. Printing of simple geometries is demonstrated with parts showing excellent interlayer adhesion, unachievable using control resins.