Abstract
The European Union (EU) has been promoting diverse initiatives towards sustainable development and environment protection. One of these initiatives is the reduction of the greenhouse gas (GHG) emissions in 60% below their 1990 level, by 2050. As the transport sector is responsible for more than 22% of those emissions some strategies need to be taken towards a more sustainable mobility, as the ones proposed in 2011 White Paper on transport. Under this context, this study aims to evaluate the environmental performance of the transport sector in the 28 EU countries towards these goals, from 2015 to 2017. The transport environmental performance is measured through the composite indicator derived from the Benefit of the Doubt (BoD) model. The country transport environmental performance is assessed through the aggregation of multiple sub-indicators using the composite indicator derived from the Data Envelopment Analysis (DEA) model. The results indicate that the EU countries slightly improved their transport environmental performance, on average 2.8%. The areas where the inefficient countries need more improvement were also identified: reducing the GHG emissions from fossil fuels, increasing the share of transport energy from renewable sources and improving the public transport share of the total passenger transport.

Abstract
ECIR 2020 1 was one of the many conferences affected by the COVID-19 pandemic. The Conference Chairs decided to keep the initially planned dates (April 14-17, 2020) and move to a fully online event. In this report, we describe the experience of organising the ECIR 2020 Workshops in this scenario from two perspectives: the workshop organisers and the workshop participants. We provide a report on the organisational aspect of these events and the consequences for participants. Covering the scientific dimension of each workshop is outside the scope of this article. A detailed account of the main conference can be found in the Spring 2020 edition of BCS Informer [BCS, 2020].

Abstract

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
Lubricant oil is an essential element in wind and hydropower generation. We present a lifecycle assessment (LCA) of the lubricant oils (mineral, synthetic and biodegradable) used in hydropower and wind power generation. The results are given in terms of energy used, associated emissions and costs. We find that, for the oil turbines and regulation systems considered here, biodegradable oil is a better option in terms of energy and CO2 equivalent emissions than mineral or synthetic oils, from production and recycling through to handling. However, synthetic and mineral oils are better options due to the potential risks associated with the use of biodegradable oil, generally when it comes into contact with water. There are also significant savings to be made in the operation of wind turbines when using an improved type of synthetic oil.

Abstract
Nuisance or unsolicited calls and instant messages come at any time in a variety of different ways. These calls would not only exasperate recipients with the unwanted ringing, impacting their productivity, but also lead to a direct financial loss to users and service providers. Telecommunication Service Providers (TSPs) often employ standalone detection systems to classify call originators as spammers or non-spammers using their behavioral patterns. These approaches perform well when spammers target a large number of recipients of one service provider. However, professional spammers try to evade the standalone systems by intelligently reducing the number of spam calls sent to one service provider, and instead distribute calls to the recipients of many service providers. Naturally, collaboration among service providers could provide an effective defense, but it brings the challenge of privacy protection and system resources required for the collaboration process. In this paper, we propose a novel decentralized collaborative system named privy for the effective blocking of spammers who target multiple TSPs. More specifically, we develop a system that aggregates the feedback scores reported by the collaborating TSPs without employing any trusted third party system, while preserving the privacy of users and collaborators. We evaluate the system performance of privy using both the synthetic and real call detail records. We find that privy can correctly block spammers in a quicker time, as compared to standalone systems. Further, we also analyze the security and privacy properties of the privy system under different adversarial models.