Abstract
Inspired by the Daley-Kendall and Goffman-Newill models, we propose an Ignorant-Believer-Unbeliever rumor (or fake news) spreading model with the following characteristics: (i) a network contact between individuals that determines the spread of rumors; (ii) the value (cost versus benefit) for individuals who search for truthful information (learning); (iii) an impact measure that assesses the risk of believing the rumor; (iv) an individual search strategy based on the probability that an individual searches for truthful information; (v) the population search strategy based on the proportion of individuals of the population who decide to search for truthful information; (vi) a payoff for the individuals that depends on the parameters of the model and the strategies of the individuals. Furthermore, we introduce evolutionary information search dynamics and study the dynamics of population search strategies. For each value of searching for information, we compute evolutionarily stable information (ESI) search strategies (occurring in non-cooperative environments), which are the attractors of the information search dynamics, and the optimal information (OI) search strategy (occurring in (eventually forced) cooperative environments) that maximizes the expected information payoff for the population. For rumors that are advantageous or harmful to the population (positive or negative impact), we show the existence of distinct scenarios that depend on the value of searching for truthful information. We fully discuss which evolutionarily stable information (ESI) search strategies and which optimal information (OI) search strategies eradicate (or not) the rumor and the corresponding expected payoffs. As a corollary of our results, a recommendation for legislators and policymakers who aim to eradicate harmful rumors is to make the search for truthful information free or rewarding.

Abstract
Context. The nearby and young beta Pictoris system hosts a well resolved disk, a directly imaged massive giant planet orbiting at similar or equal to 9 au, as well as an inner planet orbiting at similar or equal to 2.7 au, which was recently detected through radial velocity (RV). As such, it offers several unique opportunities for detailed studies of planetary system formation and early evolution.Aims. We aim to further constrain the orbital and physical properties of beta Pictoris b and c using a combination of high contrast imaging, long base-line interferometry, and RV data. We also predict the closest approaches or the transit times of both planets, and we constrain the presence of additional planets in the system.Methods. We obtained six additional epochs of SPHERE data, six additional epochs of GRAVITY data, and five additional epochs of RV data. We combined these various types of data in a single Markov-chain Monte Carlo analysis to constrain the orbital parameters and masses of the two planets simultaneously. The analysis takes into account the gravitational influence of both planets on the star and hence their relative astrometry. Secondly, we used the RV and high contrast imaging data to derive the probabilities of presence of additional planets throughout the disk, and we tested the impact of absolute astrometry.Results. The orbital properties of both planets are constrained with a semi-major axis of 9.8 0.4 au and 2.7 +/- 0.02 au for b and c, respectively, and eccentricities of 0.09 +/- 0.1 and 0.27 +/- 0.07, assuming the HIPPARCOS distance. We note that despite these low fitting error bars, the eccentricity of beta Pictoris c might still be over-estimated. If no prior is provided on the mass of beta Pictoris b, we obtain a very low value that is inconsistent with what is derived from brightness-mass models. When we set an evolutionary model motivated prior to the mass of beta Pictoris b, we find a solution in the 10-11 M-Jup range. Conversely, beta Pictoris c's mass is well constrained, at 7.8 +/- 0.4 M-Jup, assuming both planets are on coplanar orbits. These values depend on the assumptions on the distance of the beta Pictoris system. The absolute astrometry HIPPARCOS-Gaia data are consistent with the solutions presented here at the 2 sigma level, but these solutions are fully driven by the relative astrometry plus RV data. Finally, we derive unprecedented limits on the presence of additional planets in the disk. We can now exclude the presence of planets that are more massive than about 2.5 M-Jup closer than 3 au, and more massive than 3.5 M-Jup between 3 and 7.5 au. Beyond 7.5 au, we exclude the presence of planets that are more massive than 1-2 M-Jup.Conclusions. Combining relative astrometry and RVs allows one to precisely constrain the orbital parameters of both planets and to give lower limits to potential additional planets throughout the disk. The mass of beta Pictoris c is also well constrained, while additional RV data with appropriate observing strategies are required to properly constrain the mass of beta Pictoris b.

Abstract
Human Activity Recognition is a machine learning task for the classification of human physical activities. Applications for that task have been extensively researched in recent literature, specially due to the benefits of improving quality of life. Since wearable technologies and smartphones have become more ubiquitous, a large amount of information about a person's life has become available. However, since each person has a unique way of performing physical activities, a Human Activity Recognition system needs to be adapted to the characteristics of a person in order to maintain or improve accuracy. Additionally, when smartphones devices are used to collect data, it is necessary to manage its limited resources, so the system can efficiently work for long periods of time. In this paper, we present a semi-supervised ensemble algorithm and an extensive study of the influence of hyperparameter configuration in classification accuracy. We also investigate how the classification accuracy is affected by the person and the activities performed. Experimental results show that it is possible to maintain classification accuracy by adjusting hyperparameters, like window size and window overlap, depending on the person and activity performed. These results motivate the development of a system able to automatically adapt hyperparameter settings for the activity performed by each person.

Abstract
This study intends to explore the phenomenon of intrapreneurship and the relevance of the innovation processes in mature organizations by conducting three case studies on traditional industry sectors such as the textile, metalworking, and electronic components sector. The aim is to explore the role of entrepreneurial teams in such companies, to understand the inhibiting factors of innovation, and to find the essential conditions for these organizations to continuously innovate and promote intrapreneurship within their organizations. The findings reveal that several factors constrain employee participation in this process, including lack of qualifications levels, limited resources, corporate bureaucracy, and reduced time and budget. In the conditions necessary to support the innovation process emerge the support given by the management team, the qualification of individuals and teams, and the existence of an organizational culture that promotes communication, collaboration, and tolerance to risk.

Abstract

Abstract
The Galactic center black hole Sagittarius A* is a variable near-infrared (NIR) source that exhibits bright flux excursions called flares. When flux from Sgr A* is detected, the light curve has been shown to exhibit red noise characteristics and the distribution of flux densities is non-linear, non-Gaussian, and skewed to higher flux densities. However, the low-flux density turnover of the flux distribution is below the sensitivity of current single-aperture telescopes. For this reason, the median NIR flux has only been inferred indirectly from model fitting, but it has not been directly measured. In order to explore the lowest flux ranges, to measure the median flux density, and to test if the previously proposed flux distributions fit the data, we use the unprecedented resolution of the GRAVITY instrument at the VLTI. We obtain light curves using interferometric model fitting and coherent flux measurements. Our light curves are unconfused, overcoming the confusion limit of previous photometric studies. We analyze the light curves using standard statistical methods and obtain the flux distribution. We find that the flux distribution of Sgr A* turns over at a median flux density of (1.1 +/- 0.3) mJy. We measure the percentiles of the flux distribution and use them to constrain the NIR K-band spectral energy distribution. Furthermore, we find that the flux distribution is intrinsically right-skewed to higher flux density in log space. Flux densities below 0.1 mJy are hardly ever observed. In consequence, a single powerlaw or lognormal distribution does not suffice to describe the observed flux distribution in its entirety. However, if one takes into account a power law component at high flux densities, a lognormal distribution can describe the lower end of the observed flux distribution. We confirm the rms-flux relation for Sgr A* and find it to be linear for all flux densities in our observation. We conclude that Sgr A* has two states: the bulk of the emission is generated in a lognormal process with a well-defined median flux density and this quiescent emission is supplemented by sporadic flares that create the observed power law extension of the flux distribution.