The solar siblings in the Gaia era

We perform realistic simulations of the Sun's birth cluster in order to predict the current distribution of solar siblings in the Galaxy. We study the possibility of finding the solar siblings in the Gaia catalogue by using only positional and kinematic information. We find that the number of solar siblings predicted to be observed by Gaia will be around 100 in the most optimistic case, and that a phase space only search in the Gaia catalogue will be extremely difficult. It is therefore mandatory to combine the chemical tagging technique with phase space selection criteria in order to have any hope of finding the solar siblings.Comment: To be published in the proceedings of the GREAT-ITN conference "The Milky Way Unravelled by Gaia: GREAT Science from the Gaia Data Releases", 1-5 December 2014, University of Barcelona, Spain, EAS Publications Series, eds Nicholas Walton, Francesca Figueras, and Caroline Soubira

Who students interact with? A social network analysis perspective on the use of Twitter in language learning

This paper reports student interaction patterns and self-reported results of using Twitter microblogging environment. The study employs longitudinal probabilistic social network analysis (SNA) to identify the patterns and trends of network dynamics. It is building on earlier works that explore associations of student achievement records with the observed network measures. It integrates gender as an additional variable and reports some relation with interaction patterns. Additionally, the paper reports the results of a questionnaire that enables further discussion on the communication patterns

Arcsine Laws in Stochastic Thermodynamics

We show that the fraction of time a thermodynamic current spends above its average value follows the arcsine law, a prominent result obtained by L\'evy for Brownian motion. Stochastic currents with long streaks above or below their average are much more likely than those that spend similar fractions of time above and below their average. Our result is confirmed with experimental data from a Brownian Carnot engine. We also conjecture that two other random times associated with currents obey the arcsine law: the time a current reaches its maximum value and the last time a current crosses its average value. These results apply to, inter alia, molecular motors, quantum dots and colloidal systems.Comment: 11 pages, 11 figure