Tootfinder

Rapid onset of a Comptonisation zone in the repeating tidal disruption event XMMSL2 J140446.9-251135
R. D. Saxton, T. Wevers, S. van Velzen, K. Alexander, Z. Liu, A. Mummery, M. Giustini, G. Miniutti, F. Fuerst, J. J. E. Kajava, A. M. Read, P. G. Jonker, A. Rau, D. -Y. Li
https://arxiv.org/abs/2510.02905

Rapid onset of a Comptonisation zone in the repeating tidal disruption event XMMSL2 J140446.9-251135
We report here on observations of a tidal disruption event, XMMSL2 J1404-2511, discovered in an XMM-Newton slew, in a quiescent galaxy at z=0.043. X-ray monitoring covered the epoch when the accretion disc transitioned from a thermal state, with kT~80 eV, to a harder state dominated by a warm, optically-thick corona. The bulk of the coronal formation took place within 7 days and was coincident with a temporary drop in the emitted radiation by a factor 4. After a plateau phase of ~100 days, the …

Predicting First Year Dropout from Pre Enrolment Motivation Statements Using Text Mining
K. F. B. Soppe, A. Bagheri, S. Nadi, I. G. Klugkist, T. Wubbels, L. D. N. V. Wijngaards-De Meij
https://arxiv.org/abs/2509.16224

Predicting First Year Dropout from Pre Enrolment Motivation Statements Using Text Mining
Preventing student dropout is a major challenge in higher education and it is difficult to predict prior to enrolment which students are likely to drop out and which students are likely to succeed. High School GPA is a strong predictor of dropout, but much variance in dropout remains to be explained. This study focused on predicting university dropout by using text mining techniques with the aim of exhuming information contained in motivation statements written by students. By combining text da…