University of Mons

About: University of Mons is a education organization based out in Mons, Belgium. It is known for research contribution in the topics: Large Hadron Collider & Standard Model. The organization has 3073 authors who have published 9465 publications receiving 294776 citations.

Azimuthal anisotropy of charged particles at high transverse momenta in Pb-Pb collisions at √s NN=2.76TeV

Abstract: The azimuthal anisotropy of charged particles in PbPb collisions at nucleon-nucleon center-of-mass energy of 2.76 TeV is measured with the CMS detector at the LHC over an extended transverse momentum (pt) range up to approximately 60 GeV. The data cover both the low-pt region associated with hydrodynamic flow phenomena and the high-pt region where the anisotropies may reflect the path-length dependence of parton energy loss in the created medium. The anisotropy parameter (v2) of the particles is extracted by correlating charged tracks with respect to the event-plane reconstructed by using the energy deposited in forward-angle calorimeters. For the six bins of collision centrality studied, spanning the range of 0-60% most-central events, the observed v2 values are found to first increase with pt, reaching a maximum around pt = 3 GeV, and then to gradually decrease to almost zero, with the decline persisting up to at least pt = 40 GeV over the full centrality range measured.

Improving Processability and Efficiency of Resonant TADF Emitters: A Design Strategy

Abstract: This work is funded by the EC through the Horizon 2020 Marie Sklodowska-Curie ITN project TADFlife. The St Andrews team would also like to thank the Leverhulme Trust (RPG-2016- 047) and EPSRC (EP/P010482/1) for financial support. Computational resources have been provided by the Consortium des Equipements de Calcul Intensif (CECI), funded by the Fonds de la Recherche Scientifiques de Belgique (F.R.S.-FNRS) under Grant No. 2.5020.11, as well as the Tier-1 supercomputer of the Federation Wallonie-Bruxelles, infrastructure funded by the Walloon Region under the grant agreement n1117545. AP acknowledges the financial support from the Marie Curie Fellowship (MILORD project, N°. 748042). DB is a FNRS Research Director. We thank Franck-Julian Kahle for support with data analysis.

An empirical comparison of dependency network evolution in seven software packaging ecosystems

Abstract: Nearly every popular programming language comes with one or more package managers. The software packages distributed by such package managers form large software ecosystems. These packaging ecosystems contain a large number of package releases that are updated regularly and that have many dependencies to other package releases. While packaging ecosystems are extremely useful for their respective communities of developers, they face challenges related to their scale, complexity, and rate of evolution. Typical problems are backward incompatible package updates, and the risk of (transitively) depending on packages that have become obsolete or inactive. This manuscript uses the libraries.io dataset to carry out a quantitative empirical analysis of the similarities and differences between the evolution of package dependency networks for seven packaging ecosystems of varying sizes and ages: Cargo for Rust, CPAN for Perl, CRAN for R, npm for JavaScript, NuGet for the .NET platform, Packagist for PHP, and RubyGems for Ruby. We propose novel metrics to capture the growth, changeability, reusability and fragility of these dependency networks, and use these metrics to analyze and compare their evolution. We observe that the dependency networks tend to grow over time, both in size and in number of package updates, while a minority of packages are responsible for most of the package updates. The majority of packages depend on other packages, but only a small proportion of packages accounts for most of the reverse dependencies. We observe a high proportion of “fragile” packages due to a high and increasing number of transitive dependencies. These findings are instrumental for assessing the quality of a package dependency network, and improving it through dependency management tools and imposed policies.