This study aims at presenting for the first time merged GEO (geostationary elevation orbit) MSG and LEO (low elevation orbit) EPS albedo products over Europe issued from an operational production center. The assets of the merging is to complete the high latitude coverage from existing GEO products with a resolution grid adapted. Spectral norms were applied for product matching and also standard atmospheric correction. Still aerosol removal need to be timely performed.

To handle the large number of malware samples appearing in the wild each day, security analysts and vendors employ automated tools to detect, classify and analyze malicious code. Because malware is typically resistant to static analysis, automated dynamic analysis is widely used for this purpose. Executing malicious software in a controlled environment while observing its behavior can provide rich information on a malware's capabilities. However, running each malware sample even for a few minutes is expensive. For this reason, malware analysis efforts need to select a subset of samples for analysis. To date, this selection has been performed either randomly or using techniques focused on avoiding re-analysis of polymorphic malware variants [41, 23].

Abstract virology has seen the apparition of successive viral models, all based on Turing-equivalent formalisms. Considering recent malware, these are only partially covered because functional formalisms do not support interactive computations. This article provides a basis for a unified malware model, founded on the Join-Calculus. In terms of expressiveness, the process-based model supports the fundamental notion of self-replication but also interactions, concurrency and non-termination to cover evolved malware. In terms of protection, detection undecidability and prevention by isolation still hold. Additional results are established: calculus fragments where detection is decidable, definition of a non-infection property, potential solutions to restrict propagation.