Theory of cosmic ray and gamma-ray production in the supernova remnant RX J0852.0-4622

Aims. The properties of the Galactic supernova remnant (SNR) RX J0852.0-4622 are theoretically analysed. Methods. An explicitly time-dependent, nonlinear kinetic model of cosmic ray (CR) acceleration in SNRs is used to describe the properties of SNR RX J0852.0-4622, the accelerated CRs and the nonthermal emission. The source is assumed to be at a distance of ~1 kpc in the wind bubble of a massive progenitor star. An estimate of the thermal X-ray flux in such a configuration is given. Results. We find that the overall synchrotron spectrum of RX J0852.0-4622 as well as the filamentary structures in hard X-rays lead to an amplified magnetic field B > 100 muG in the SNR interior. This implies that the leptonic very high energy (VHE) gamma-ray emission is suppressed, and that the VHE gamma-rays are hadronically dominated. The energy spectrum of protons produced over the life-time of the remnant until now may well reach ''knee'' energies. The derived gamma-ray morphology is consistent with the H.E.S.S. measurements. The amount of energy in energetic particles corresponds to about 35% of the hydrodynamic explosion energy. A remaining uncertainty concerns the thermal X-ray flux at 1 keV. A rough estimate, possibly not quite appropriate for the assumed wind bubble configuration, results in it being larger than the nonthermal flux at this energy. Conclusions. It is concluded that this SNR expanding into the wind bubble of a massive star in a dense gas environment can be a hadronic gamma-ray source that is consistent with all existing multi-wavelength constraints, except possibly the thermal X-ray emission.Comment: 14 pages, 8 figures, accepted for publication in A&

EVALUATING SUBJECTIVE ASPECTS OF HCI ON AN EXAMPLE OF A NON-TASK ORIENTED CONVERSATIONAL SYSTEM

The evaluation of subjective aspects of HCI, such as human-likeness, likeability or users' emotions towards computers is still quite a neglected issue, especially in the field of non-task oriented conversational systems (chatterbots). In this paper we try to bridge this gap by proposing a new methodology of evaluation. The methods presented were tested in our research on humor-equipped chatterbots. We describe them in details, discuss their drawbacks and usability. In one of the presented methods we used an emotiveness analysis system, which itself can be considered an AI tool, as it was used to detect users' emotions towards conversational systems, and to perform their automatic evaluation. We also propose some methods that we have not used yet, which, however, seem applicable in this field, such as brain scanning techniques. Finally, we give some ideas that should be addressed in the future

Exploring eye activity as an indication of emotional states using an eye-tracking sensor

The automatic detection of human emotional states has been of great interest lately for its applications not only in the Human-Computer Interaction field, but also for its applications in psychological studies. Using an emotion elicitation paradigm, we investigate whether eye activity holds discriminative power for detecting affective states. Our emotion elicitation paradigm includes induced emotions by watching emotional movie clips and spontaneous emotions elicited by interviewing participants about emotional events in their life. To reduce gender variability, the selected participants were 60 female native Arabic speakers (30 young adults, and 30 mature adults). In general, the automatic classification results using eye activity were reasonable, giving 66% correct recognition rate on average. Statistical measures show statistically significant differences in eye activity patterns between positive and negative emotions. We conclude that eye activity, including eye movement, pupil dilation and pupil invisibility could be used as a complementary cues for the automatic recognition of human emotional states