Context. Over ten mid-infrared (mid-IR) and X-ray models are currently attempting to describe the nuclear obscuring material of active galactic nuclei (AGNs), but many questions remain unresolved. Aims. This study aims to determine the physical parameters of the obscuring material in nearby AGNs and explore their relationship with nuclear activity

The Wide Angle Search for Planets (WASP) survey provided some of the first transiting hot Jupiter candidates. With the addition of the Transiting Exoplanet Survey Satellite (TESS), many WASP planet candidates have now been revisited and given updated transit parameters. Here, we present nine transiting planets orbiting FGK stars that were

Magnetic fields play a significant role in star-forming processes on core to clump scales. We investigate magnetic field orientations and strengths in the massive star-forming clump P2 within the filamentary infrared dark cloud G28.34+0.06 using dust polarization observations made using SCUBA-2/POL-2 on the James Clerk Maxwell Telescope (JCMT) as

Context. The connection between galaxies and their host dark matter halos encompasses a range of intricate and interrelated processes, playing a pivotal role in our understanding of galaxy formation and evolution. Traditionally, this link has been established through physical or empirical models. On the other hand, machine learning techniques are

Thanks to Integral Field Unit survey data, it is possible to explore in detail the link between the formation of the stellar content in galaxies and the drivers of evolution. Traditionally, scaling relations have connected galaxy-wide parameters such as stellar mass (M $_s$), morphology or average velocity dispersion ( $\sigma$) to the star

Once galaxies settle their discs and become self-gravitating, stellar bars can form, driving the subsequent evolution of their host galaxy. Determining the ages of bars can therefore shed light on the epoch of the onset of secular evolution. For this work we applied the first broadly applicable methodology to derive bar ages to a sample of 20