We present a 2-dimensional chemical evolution code applied to a Milky Way type galaxy, incorporating the role of spiral arms in shaping azimuthal abundance variations, and confront the predicted behaviour with recent observations taken with integral field units. To the usual radial distribution of mass, we add the surface density of the spiral wave and study its effect on star formation and elemental abundances. We compute five different models: one with azimuthal symmetry which depends only on radius, while the other four are subjected to the effect of a spiral density wave. At early times, the imprint of the spiral density wave is carried by both the stellar and star formation surface densities; conversely, the elemental abundance pattern is less affected. At later epochs, however, differences among the models are diluted, becoming almost indistinguishable given current observational uncertainties. At the present time, the largest differences appear in the star formation rate and/or in the outer disc (R≥ 18 kpc). The predicted azimuthal oxygen abundance patterns for t ≤ 2 Gyr are in reasonable agreement with recent observations obtained with VLT/MUSE for NGC 6754.

Generalized relativistic field equations have been derived for dynamics in a non-inertial reference frame interpreted as a Finsler space where events are specified by both spacetime coordinates and corresponding velocities (tangent vectors). The field equations follow in two alternative forms from exact general conservation laws derived through application of Cartan covariant differentiation within the framework of Finsler geometry. Velocity-dependent (curvature) terms in the field equations can account for the anisotropy of the gravitational field, together with the associated acceleration and expansion of the universe.

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The Vanishing & Appearing Sources during a Century of Observations (VASCO) project investigates astronomical surveys spanning a 70 years time interval, searching for unusual and exotic transients. We present herein the VASCO Citizen Science Project, that uses three different approaches to the identification of unusual transients in a given set of candidates: hypothesis-driven, exploratory-driven and machine learning-driven (which is of particular benefit for SETI searches). To address the big data challenge, VASCO combines methods from the Virtual Observatory, a user-aided machine learning and visual inspection through citizen science. In this article, we demonstrate the citizen science project, the new and improved candidate selection process and give a progress report. We also present the VASCO citizen science network led by amateur astronomy associations mainly located in Algeria, Cameroon and Nigeria. At the moment of writing, the citizen science project has carefully examined 12,000 candidate image pairs in the data, and has so far identified 713 objects classified as "vanished". The most interesting candidates will be followed up with optical and infrared imaging, together with the observations by the most potent radio telescopes.