Applications of electrified dust and dust devil electrodynamics to Martian atmospheric electricity

Atmospheric transport and suspension of dust frequently brings electrification, which may be substantial. Electric fields of 10 kVm-1 to 100 kVm-1 have been observed at the surface beneath suspended dust in the terrestrial atmosphere, and some electrification has been observed to persist in dust at levels to 5 km, as well as in volcanic plumes. The interaction between individual particles which causes the electrification is incompletely understood, and multiple processes are thought to be acting. A variation in particle charge with particle size, and the effect of gravitational separation explains to, some extent, the charge structures observed in terrestrial dust storms. More extensive flow-based modelling demonstrates that bulk electric fields in excess of 10 kV m-1 can be obtained rapidly (in less than 10 s) from rotating dust systems (dust devils) and that terrestrial breakdown fields can be obtained. Modelled profiles of electrical conductivity in the Martian atmosphere suggest the possibility of dust electrification, and dust devils have been suggested as a mechanism of charge separation able to maintain current flow between one region of the atmosphere and another, through a global circuit. Fundamental new understanding of Martian atmospheric electricity will result from the ExoMars mission, which carries the DREAMS (Dust characterization, Risk Assessment, and Environment Analyser on the Martian Surface)-MicroARES (Atmospheric Radiation and Electricity Sensor) instrumentation to Mars in 2016 for the first in situ measurements

An Adaptive Agent Model for the Emergence of Recurring Dream Scripts Based on Hebbian Learning

Abstract. In this paper an adaptive agent model is presented that models how recurrent dreams such as nightmares occur. The approach addresses dreaming as internal simulation incorporating memory elements in the form of sensory representations and their associated emotions. In the agent model recurring dreams emerge as scripts of connected dream episodes in which the connections between the episodes strengthen over time by Hebbian learning. The model was evaluated by a number of simulation experiments for different scenarios.