Ontogeny of superorganisms: Social control of queen specialization in ants

International audienceThe functioning of biological systems relies on the cooperation of specialized components and understanding the processes that produce such specialization is a major challenge in biology. Here, we study the ontogeny of biological systems at a new phenotypic level: the superorganisms (i.e. insect societies with specialized individuals). We investigate how founding queens, the earliest developmental stage of ant colonies, transition from expressing behavioural pluripotency to becoming strictly specialized in egg production. We demonstrate that the presence of workers both initiates and maintains this queen specialization, and propose that such a social control of queen behaviour is common in ants and regulated by ancestral mechanisms. These findings contradict the traditional view of social insect queens as being intrinsically specialized in egg production and may reshape our understanding of the division of labour in insect societies

Integration of electric vehicles and wind energy in power systems

Today, internal combustion engines are considered as essential equipment of transportation industry and business. Concerns about oil price fluctuation and climate changes are reasons to find an alternative for fossil fuel-based vehicles. Electric vehicle (EV) with electric drive, good efficiency and no pollution can be a suitable alternative for conventional vehicles. The presence of EVs in the distribution network, especially those with the ability to connect to the grid (V2G), allows the distribution network to meet its required reserve at a lower cost. An individual EV does not have a significant impact on the grid; however, the optimal charge/discharge aggregation of EVs may lead to the better technical and economic performance of the distribution network. In this chapter, an optimal operation model of EVs is presented in the presence of wind turbines and the effects of the coordinate and non-coordinate operation of EVs on the stochastic generation of wind turbines are assessed. The stochastic generation of wind turbine are modeled through Weibull distribution function under various scenarios