Erasmus student mobility and the construction of European citizenship

The Erasmus student mobility programme allocates three explicit objectives to the experience of spending a few months studying in another European country: (1) to benefit students educationally, linguistically and culturally; (2) to promote co-operation between institutions and (3) to contribute to the development of a pool of well-qualified, open-minded and internationally experienced future professionals [European Commission. 1996. The Obstacles to Transnational Mobility. Green Paper. http://aei.pitt.edu/1226/1/education_mobility_obstacles_gp_COM_96_462.pdf (accessed April, 2015)]. The programme has also sometimes been referred to as one of the most powerful tools of European integration. However, little research has so far been undertaken on how it may alter students’ attitudes towards aspects of European identity and sense of European citizenship. Our study investigates the extent to which the Erasmus experience affects the sense of self as European citizens of a cohort of students from the University of Lleida (Catalonia, Spain). It also explores the students’ position towards the notion of European citizenship and how this relates to the development of their plurilingual competence. Two questionnaires, one before and one after the study-abroad experience, provided quantitative data while qualitative data were obtained through the analysis of discussion groups focusing on aspects of European vs. national identity and citizenship.The research on which this article is based was supported by: (1) Research grant [FFI2012-35834], Ministerio de Economía y Competitividad, Interculturalidad, ciudadanía europea e ingleś como lingua franca: entre las políticas y las prácticas en los programas de movilidad internacional universitaria, January 2013–June 2016, and (2) the Agència de Gestió d’Ajuts Universitaris i de Recerca de la Generaliat de Catalunya [2014SGR 1061

An evaluation of the feasibility of electrostatic separation for physical soil washing

[EN] We present the first application of electrostatic separation for soil washing. Soil samples were collected from the PTE-containing area of La Cruz in Linares, southern Spain. Using a single-phase high-tension roll separator with voltages ranging from 20 kV to 41.5 kV, we achieved yield values between 0.69% and 9%, with high recovery rates for certain elements such as Zn, Cu, and Mo. SEM-EDX analysis revealed three particle types, including a non-conductive fraction composed of feldspar, a middling fraction composed of mica, and a conductive fraction consisting of PTE-bearing slag grains. Attributive analysis showed that 41.5 kV was the optimal voltage for maximizing PTE concentration. Overall, electrostatic separation is a promising approach for treating soils contaminated with PTEs, particularly in dry climate areas impacted by mining activities.S

A review of canine babesiosis: The European perspective

Canine babesiosis is a significant tick-borne disease caused by various species of the protozoan genus Babesia. Although it occurs worldwide, data relating to European infections have now been collected for many years. These data have boosted the publication record and increased our working knowledge of these protozoan parasites. Both the large and small forms of Babesia species (B. canis, B. vogeli, B. gibsoni, and B. microti-like isolates also referred to as "B. vulpes" and "Theileria annae") infect dogs in Europe, and their geographical distribution, transmission, clinical signs, treatment, and prognosis vary widely for each species. The goal of this review is to provide veterinary practitioners with practical guidelines for the diagnosis, treatment and prevention of babesiosis in European dogs. Our hope is that these guidelines will answer the most frequently asked questions posed by veterinary practitioners

Asynchronous, Photometric Feature Tracking using Events and Frames

We present a method that leverages the complementarity of event cameras and standard cameras to track visual features with low-latency. Event cameras are novel sensors that output pixel-level brightness changes, called "events". They offer significant advantages over standard cameras, namely a very high dynamic range, no motion blur, and a latency in the order of microseconds. However, because the same scene pattern can produce different events depending on the motion direction, establishing event correspondences across time is challenging. By contrast, standard cameras provide intensity measurements (frames) that do not depend on motion direction. Our method extracts features on frames and subsequently tracks them asynchronously using events, thereby exploiting the best of both types of data: the frames provide a photometric representation that does not depend on motion direction and the events provide low-latency updates. In contrast to previous works, which are based on heuristics, this is the first principled method that uses raw intensity measurements directly, based on a generative event model within a maximum-likelihood framework. As a result, our method produces feature tracks that are both more accurate (subpixel accuracy) and longer than the state of the art, across a wide variety of scenes.Comment: 22 pages, 15 figures, Video: https://youtu.be/A7UfeUnG6c

Identification of volatile organic compounds (VOC) emitted from three European orchid species with different pollination strategies : two deceptive orchids (Himantoglossum robertianum and Ophrys apifera) and a rewarding (Gymnadenia conopsea)

Volatile organic compounds (VOC) emission was evaluated in the inflorescences of three species of the family Orchidaceae: Himantoglossum robertianum, Ophrys apifera and Gymnadenia conopsea, that comprise three different pollination strategies: non-rewarding food deceptive, non-rewarding sexually deceptive and nectar rewarding, respectively. VOC were dynamically sampled in custom packed glass multi-sorbent cartridge tubes (Carbotrap, Carbopack X and Carboxen 569). A modified Tedlar® gas sampling bag was placed in vivo covering the inflorescence of the studied orchid, a design that prevents the dilution of the VOC mixture emitted by the flower. Multi-sorbent bed tubes were analysed through automatic thermal desorption coupled with a capillary gas chromatography/mass spectrometry detector. A total of 106 different VOC were found in the scents emitted by the three different studied orchids. A 54% of these compounds had already been identified in floral scents. Generally, only 3 compounds were highly abundant in each species: α-pinene, β-pinene and limonene in Himantoglossum robertianum; 1-butanol, butyl ether and caryophyllene in Ophrys apifera; and phenethyl acetate, eugenol and benzaldehyde in Gymnadenia conopsea. The employment of the presented methodologyPostprint (published version

Guideline for veterinary practitioners on canine ehrlichiosis and anaplasmosis in Europe

Canine ehrlichiosis and anaplasmosis are important tick-borne diseases with a worldwide distribution. Information has been continuously collected on these infections in Europe, and publications have increased in recent years. Prevalence rates are high for Ehrlichia and Anaplasma spp. infections in dogs from different European countries. The goal of this article was to provide a practical guideline for veterinary practitioners on the diagnosis, treatment, and prevention of ehrlichiosis and anaplasmosis in dogs from Europe. This guideline is intended to answer the most common questions on these diseases from a practical point of view

Simulating Turbulence Using the Astrophysical Discontinuous Galerkin Code TENET

In astrophysics, the two main methods traditionally in use for solving the Euler equations of ideal fluid dynamics are smoothed particle hydrodynamics and finite volume discretization on a stationary mesh. However, the goal to efficiently make use of future exascale machines with their ever higher degree of parallel concurrency motivates the search for more efficient and more accurate techniques for computing hydrodynamics. Discontinuous Galerkin (DG) methods represent a promising class of methods in this regard, as they can be straightforwardly extended to arbitrarily high order while requiring only small stencils. Especially for applications involving comparatively smooth problems, higher-order approaches promise significant gains in computational speed for reaching a desired target accuracy. Here, we introduce our new astrophysical DG code TENET designed for applications in cosmology, and discuss our first results for 3D simulations of subsonic turbulence. We show that our new DG implementation provides accurate results for subsonic turbulence, at considerably reduced computational cost compared with traditional finite volume methods. In particular, we find that DG needs about 1.8 times fewer degrees of freedom to achieve the same accuracy and at the same time is more than 1.5 times faster, confirming its substantial promise for astrophysical applications.Comment: 21 pages, 7 figures, to appear in Proceedings of the SPPEXA symposium, Lecture Notes in Computational Science and Engineering (LNCSE), Springe

An evaluation of the feasibility of electrostatic separation for physical soil washing

We present the first application of electrostatic separation for soil washing. Soil samples were collected from the PTE-containing area of La Cruz in Linares, southern Spain. Using a single-phase high-tension roll separator with voltages ranging from 20 kV to 41.5 kV, we achieved yield values between 0.69% and 9%, with high recovery rates for certain elements such as Zn, Cu, and Mo. SEM-EDX analysis revealed three particle types, including a non-conductive fraction composed of feldspar, a middling fraction composed of mica, and a conductive fraction consisting of PTE-bearing slag grains. Attributive analysis showed that 41.5 kV was the optimal voltage for maximizing PTE concentration. Overall, electrostatic separation is a promising approach for treating soils contaminated with PTEs, particularly in dry climate areas impacted by mining activities.Diego Baragaño would like to express his gratitude to the European Union-Next Generation EU, the Spanish Ministry of Universities, and The Recovery, Transformation and Resilience Plan for providing the funding for his postdoctoral grant which was administered by the University of Oviedo (Ref. MU-21-UP2021-03032892642). Carlos Sierra thanks the EURECA-PRO phase I 2020–2023 co-funded by the Erasmus+ Programme of the European Union (Ref.: 101004049)

A novel heuristic tool for selecting the best upgrading conditions for the removal of potentially toxic elements by soil washing

Here, we propose two-parameter penalized attributive analysis, PPAA-U, a novel heuristic tool for selecting the best upgrading conditions (BUCs) for soil washing. Given a multi-component feed and a specific set of operating conditions, PPAA-U generates a quality index based on how well recoveries for key components are maximized while minimizing the yield. We demonstrate, through the calculation of families of curves, that this quality index is related linearly to recovery and to the inverse of the yield, meaning that reducing yield values is more important than maximizing recovery. To evaluate our method, electrostatic separation at 12 different voltages was carried out on soil samples from an ex-industrial site in Spain. Values of recovery, yield, and grade were analyzed using basic attributive analysis and PPAA-U with and without target-to-distance correction. Both methods identified the same optimal separation voltage, and the power of PPAA-U to correct for high variation in yields and recoveries was observed as a divergence between results produced by each method at low voltages where variation in these values was greatest. PPAA-U thus offers a convenient tool for soil washing optimization, and we suggest that it could be applied successfully to other industrial processes

Video synthesis from Intensity and Event Frames

Event cameras, neuromorphic devices that naturally respond to brightness changes, have multiple advantages with respect to traditional cameras. However, the difficulty of applying traditional computer vision algorithms on event data limits their usability. Therefore, in this paper we investigate the use of a deep learning-based architecture that combines an initial grayscale frame and a series of event data to estimate the following intensity frames. In particular, a fully-convolutional encoder-decoder network is employed and evaluated for the frame synthesis task on an automotive event-based dataset. Performance obtained with pixel-wise metrics confirms the quality of the images synthesized by the proposed architecture