Star clusters near and far; tracing star formation across cosmic time

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00690-x.Star clusters are fundamental units of stellar feedback and unique tracers of their host galactic properties. In this review, we will first focus on their constituents, i.e.\ detailed insight into their stellar populations and their surrounding ionised, warm, neutral, and molecular gas. We, then, move beyond the Local Group to review star cluster populations at various evolutionary stages, and in diverse galactic environmental conditions accessible in the local Universe. At high redshift, where conditions for cluster formation and evolution are more extreme, we are only able to observe the integrated light of a handful of objects that we believe will become globular clusters. We therefore discuss how numerical and analytical methods, informed by the observed properties of cluster populations in the local Universe, are used to develop sophisticated simulations potentially capable of disentangling the genetic map of galaxy formation and assembly that is carried by globular cluster populations.Peer reviewedFinal Accepted Versio

Automatic Detection and Semantic Formalisation of Business Rules

International audienceExperts in construction engineering are overwhelmed by regulatory texts. It is a heavy task to go through these texts and get an unambiguous list of requirements they contain. Moreover, with regard to the number of texts and the diversity of their writers, we cannot neglect the possibility of getting inconsistencies. Finally, these requirements are to be put close to digital representation of buildings to detect potential non-conformities. This paper examines these problems and envisions solutions to help experts. We thus envisage to automate detection and extraction of business rules in regulatory texts. Next, we propose to formalise identified requirements as SPARQL queries. These queries will serve for conformity checking on OWL-representation of buildings. Moreover, we plan to leverage these queries to detect inconsistencies in regulatory texts