Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Tourists’ city trip activity program planning:a personalized stated choice experiment

New digital technologies support personalized recommender systems that can assist a tourist who wants to make a city tour. To develop a smart system that can give tourists an optimized complete activity program for their trip, it is not only important to know the preferences and interests of tourists but also whether they like combinations of activities/points of interest (POIs) or not. The aim of this study is to measure and predict tourists’ preferences for combinations of activities in planning a program during a city trip. A personalized stated choice experiment is developed and presented in a survey to a random sample of 238 respondents. Binary mixed logit models are estimated on the choice data collected. An advantage of this approach is that it allows estimation of covariances between city trip activities indicating whether they would act as complements or substitutes for a specific tourist in his/her city trip activity program. The model parameters provide information on combinations of activities and themes that tourists prefer during their city trip and that the recommender system can use to further fine-tune the recommendations of city trip programs and optimize the tourist experience