The magnetic activity of the Sun directly impacts the Earth and human life. Likewise, other stars will have an impact on the habitability of planets orbiting these host stars. Although the magnetic field at the surface of the Sun is reasonably well characterised by observations, the information on the magnetic field in the higher atmospheric layers

The advent of wide-field sky surveys has led to the growth of transient and variable source discoveries. The data deluge produced by these surveys has necessitated the use of machine learning (ML) and deep learning (DL) algorithms to sift through the vast incoming data stream. A problem that arises in real-world applications of learning algorithms

We present an analysis of the kinematics of 14 satellites of the Milky Way (MW). We use proper motions (PMs) from the Gaia Early Data Release 3 (EDR3) and line-of-sight velocities (v los) available in the literature to derive the systemic 3D motion of these systems. For six of them, namely the Carina, Draco, Fornax, Sculptor, Sextans, and Ursa