Metal enrichment processes

There are many processes that can transport gas from the galaxies to their environment and enrich the environment in this way with metals. These metal enrichment processes have a large influence on the evolution of both the galaxies and their environment. Various processes can contribute to the gas transfer: ram-pressure stripping, galactic winds, AGN outflows, galaxy-galaxy interactions and others. We review their observational evidence, corresponding simulations, their efficiencies, and their time scales as far as they are known to date. It seems that all processes can contribute to the enrichment. There is not a single process that always dominates the enrichment, because the efficiencies of the processes vary strongly with galaxy and environmental properties.Comment: 18 pages, 8 figures, accepted for publication in Space Science Reviews, special issue "Clusters of galaxies: beyond the thermal view", Editor J.S. Kaastra, Chapter 17; work done by an international team at the International Space Science Institute (ISSI), Bern, organised by J.S. Kaastra, A.M. Bykov, S. Schindler & J.A.M. Bleeke

A Survey on Program Analysis and Transformation

© 2019, Springer Nature Switzerland AG. Program transformation is a process in which an input program is transformed into another program that achieves a specific goal. Such transformation is done by applying a sequence of transformation rules on the input program to generate another program as the output. Such transformations can be done manually with human intervention (software developer) or automatically by a transformation program applying a transformation algorithm. Automating this process has been of an interest to a myriad of researchers in the past years. Several researches were done to automatically find good transformation sequences to achieve different transformation goals including program optimization and test case generation. The most popular techniques used are search-based meta-heuristic algorithms including genetic algorithm. In this paper, we will survey previous works that used genetic algorithm to achieve optimization goals under the umbrella of program transformation