A study of the turbulence of the neutral medium in two nearby spiral galaxies

The width of the 21 cm line (HI) emitted by spiral galaxies depends on the physical processes that release energy in the Interstellar Medium (ISM). This quantity is called velocity dispersion (σ) and it is proportional first of all to the thermal kinetic energy of the gas. The accepted theoretical picture predicts that the neutral hydrogen component (HI) exists in the ISM in two stable phases: a cold one (CNM, with σ~0.8 km/s) and a warm one (WNM, with σ~8 km/s). However, this is called into question by the observation that the HI gas has usually larger velocity dispersions. This suggests the presence of turbulence in the ISM, although the energy sources remain unknown. In this thesis we want to shed new light on this topic. We have studied the HI line emission of two nearby galaxies: NGC6946 and M101. For the latter we used new deep observations obtained with the Westerbork radio interferometer. Through a gaussian fitting procedure, we produced dispersion maps of the two galaxies. For both of them, we compared the σ values measured in the spiral arms with those in the interarms. In NGC6946 we found that, in both arms and interarms, σ grows with the column density, while we obtained the opposite for M 101. Using a statistical analysis we did not find a significant difference between arm and interarm dispersion distributions. Producing star formation rate density maps (SFRD) of the galaxies, we studied their global and local relations with the HI kinetic energy, as inferred from the measured dispersions. For NGC6946 we obtained a good log-log correlation, in agreement with a simple model of supernova feedback driven turbulence. This shows that in this galaxy turbulent motions are mainly induced by the stellar activity. For M 101 we did not find an analogous correlation, since the gas kinetic energy appears constant with the SFRD. We think that this may indicate that in this galaxy turbulence is driven also by accretion of extragalactic material.

Integrating an Emotion Recognition Model for the Flobi System

This thesis investigates if emotional states of users interacting with a virtual robot can be recognized reliably and if specific interaction strategy can change the users’ emotional state and affect users’ risk decision. For this investigation, the OpenFace [1] emotion recognition model was intended to be integrated into the Flobi [2] system, to allow the agent to be aware of the current emotional state of the user and to react appropriately. There was an open source ROS [3] bridge available online to integrate OpenFace to the Flobi simulation but it was not consistent with some other projects in Flobi distribution. Then due to technical reasons DeepFace was selected. In a human-agent interaction, the system is compared to a system without using emotion recognition. Evaluation could happen at different levels: evaluation of emotion recognition model, evaluation of the interaction strategy, and evaluation of effect of interaction on user decision. The results showed that the happy emotion induction was 58% and fear emotion induction 77% successful. Risk decision results show that: in happy induction after interaction 16.6% of participants switched to a lower risk decision and 75% of them did not change their decision and the remaining switched to a higher risk decision. In fear inducted participants 33.3% decreased risk 66.6 % did not change their decision The emotion recognition accuracy was and had bias to. The sensitivity and specificity is calculated for each emotion class. The emotion recognition model classifies happy emotions as neutral in most of the time.