Self-organizing nervous systems for robot swarms.

We present the self-organizing nervous system (SoNS), a robot swarm architecture based on self-organized hierarchy. The SoNS approach enables robots to autonomously establish, maintain, and reconfigure dynamic multilevel system architectures. For example, a robot swarm consisting of independent robots could transform into a single -robot SoNS and then into several independent smaller SoNSs, where each SoNS uses a temporary and dynamic hierarchy.

An update for (Stål, 1855) (Hemiptera, Pentatomidae) distribution in Belgium.

The brown marmorated stink bug, , represents an important insect pest and subsequently an important agricultural threat due to its polyphagous feeding habits and adaptability to diverse climates. Native from East Asia, its recent establishment in various regions, including North America and Europe, has led to substantial yield losses and economic impacts, which highlight the need for comprehensive research efforts, based on data occurrence by combining those from expert entomologists and citizen scientists. We reported here 14 new occurrences of this insect pest in the three regions of Belgium.

Life tables in entomology: A discussion on tables' parameters and the importance of raw data.

Life tables are one of the most common tools to describe the biology of insect species and their response to environmental conditions. Although the benefits of life tables are beyond question, we raise some doubts about the completeness of the information reported in life tables. To substantiate these doubts, we consider a case study (Corcyra cephalonica) for which the raw dataset is available.

Self-Reconfigurable Hierarchical Frameworks for Formation Control of Robot Swarms.

Hierarchical frameworks-a special class of directed frameworks with a layer-by-layer architecture-can be an effective mechanism to coordinate robot swarms. Their effectiveness was recently demonstrated by the mergeable nervous systems paradigm (Mathews et al., 2017), in which a robot swarm can switch dynamically between distributed and centralized control depending on the task, using self-organized hierarchical frameworks.

On the effect of the number of tests and their time of application in tracing policies against COVID-19.

In this paper we explore the effect of the number of daily tests on an epidemics control policy purely based on testing and selective quarantine, and the impact of these actions depending on the time their application starts. We introduce a general model incorporating a stochastic disease evolution, a particular weighted graph representing the population, and an optimal contact tracing strategy to allocate available tests. Simulations on a community of 50'000 individuals show that the evolution of the epidemic produces a clear non-linear response to the variation of the number of tests used and to the starting time of their application.