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Nowadays, every public transportation company uses Automatic Vehicle Location (AVL) systems to track the services provided by each vehicle. Such information can be used to improve operational planning. This paper describes an AVL-based evaluation framework to test whether the actual Schedule Plan fits, in terms of days covered by each schedule, the network’s operational conditions. Firstly, clustering is employed to group days with similar profiles in terms of travel times (this is done for each different route). Secondly, consensus clustering is used to obtain a unique set of clusters for all routes. Finally, a set of rules about the groups content is drawn based on appropriate decision variables. Each group will correspond to a different schedule and the rules identify the days covered by each schedule. This methodology is simultaneously an evaluator of the schedules that are offered by the company (regarding its coverage) and an advisor on possible changes to such offer. It was tested by using data collected for one year in a company running in Porto, Portugal. The results are sound. The main contribution of this paper is that it proposes a way to combine Machine Learning techniques to add a novel dimension to the Schedule Plan evaluation methods: the day coverage. Such approach meets no parallel in the current literature. [ABSTRACT FROM AUTHOR]

We study the implications of recent lattice QCD results for the magnetic field dependence of the quarks dynamical masses on the 't Hooft determinant extended Nambu-Jona-Lasinio model in the light and strange quark sectors (up, down and strange). The parameter space is constrained at vanishing magnetic field, using the quarks dynamical masses and the meson spectra, whereas at nonvanishing magnetic field strength the dependence of the dynamical masses of two of the quark flavors is used to fit a magnetic field dependence on the model couplings, both the four-fermion Nambu-Jona-Lasinio interaction and the six-fermion 't Hooft flavor determinant. We found that this procedure reproduces the inverse magnetic catalysis, and the strength of the scalar coupling decreases with the magnetic field, while the strength of the six-fermion 't Hooft flavor determinant increases with the magnetic field. [ABSTRACT FROM AUTHOR]