The flight of the GAPS prototype experiment

The General AntiParticle Spectrometer experiment (GAPS) is foreseen to carry out a dark matter search using low-energy cosmic ray antideuterons at stratospheric altitudes with a novel detection approach. A prototype flight from Taiki, Japan was carried out in June 2012 to prove the performance of the GAPS instrument subsystems (Lithium-drifted Silicon tracker and time-of-flight) and the thermal cooling concept as well as to measure background levels. The flight was a success and the stable flight operation of the GAPS detector concept was proven. During the flight about 106 charged particle triggers were recorded, extensive X-ray calibrations of the individual tracker modules were performed by using an onboard X-ray tube, and the background level of atmospheric and cosmic X-rays was measured. The behavior of the tracker performance as a function of temperature was investigated. The tracks of charged particle events were reconstructed and used to study the tracking resolution, the detection efficiency of the tracker, and coherent X-ray backgrounds. A timing calibration of the time-of-flight subsystem was performed to measure the particle velocity. The flux as a function of flight altitude and as a function of velocity was extracted taking into account systematic instrumental effects. The developed analysis techniques will form the basis for future flights

The Early Bird Catches The Term: Combining Twitter and News Data For Event Detection and Situational Awareness

Twitter updates now represent an enormous stream of information originating from a wide variety of formal and informal sources, much of which is relevant to real-world events. In this paper we adapt existing bio-surveillance algorithms to detect localised spikes in Twitter activity corresponding to real events with a high level of confidence. We then develop a methodology to automatically summarise these events, both by providing the tweets which fully describe the event and by linking to highly relevant news articles. We apply our methods to outbreaks of illness and events strongly affecting sentiment. In both case studies we are able to detect events verifiable by third party sources and produce high quality summaries