Suchergebnisse

La evolución de la radio en los últimos años ha derivado en una creciente presencia y utilización de las redes sociales como canal de comunicación con sus audiencias y la aparición de nuevas narrativas. Esta investigación explora el tratamiento que las cuatro principales cadenas radiofónicas españolas -SER, COPE, Onda Cero y Radio Nacional de España- realizaron en Instagram durante la investidura de Pedro Sánchez como presidente del Gobierno de España. Del análisis de contenido cuantitativo y cualitativo realizado se deriva que la implantación de la radio en Instagram es, todavía, incipiente en algunos casos, pero que, sin embargo, cadenas como SER y COPE ya aplican nuevas narrativas en la red social. La radio emplea Instagram para informar y también como espacio para los géneros opinativos, y lo hace con un impacto notable en las comunidades de seguidores. ; Radio's evolution in recent years is characterised by the growing presence and use of social networks as communication channels with their audiences and the emergence of new narratives. This research explores the coverage carried out by the four main Spanish radio stations - Cadena SER, COPE, Onda Cero and Radio Nacional de España - through their Instagram accounts during the inauguration of Pedro Sánchez as President of the Government of Spain. The results obtained from an analysis of quantitative and qualitative content reveal that, in some cases, the introduction of radio on Instagram is still in its infancy. However, stations such as SER and COPE have already implemented new narratives in this social network. The radio uses Instagram to inform and also as a platform for opinion genres having a significant impact on the communities of followers. ; Este trabajo ha sido realizado en el marco del Grupo de Investigación en Comunicación e Información Digital (GICID) de la Universidad de Zaragoza, reconocido como grupo de referencia por el Gobierno de Aragón con el código S29_20R (Núm. 62 del Boletín Oficial de Aragón, de fecha 26/03/2020), dentro del área de Ciencias Sociales y financiado por el Fondo Social Europeo de Desarrollo Regional, FEDER "Construyendo Europa desde Aragón".

A policy change in the European Union's Emissions Trading Scheme (EU ETS) provides us with a unique opportunity to measure the impact of carbon pricing on aviation, the most climate-intensive mode of transport. We implement a difference-in-differences strategy on a sample based on all flights within Europe from 2010 to 2016 to examine the causal impact of the EU ETS on emissions and supply. We find that the EU ETS reduced emissions by 4.7% in the regulated routes relative to the counterfactual. When we restrict the sample to short-haul flights, routes on which competition from other means of transport may exist (less than 1,000 km), the reduction in emissions is 10.7%. Finally, the reduction in emissions is also high for low-cost airlines (−11%) but it is not statistically significant for network airlines. In sum, the EU ETS has helped to mitigate emission growth by 3 Mt CO2 per year during the period analyzed, but not to reduce absolute emissions in the sector, as needed.

Glyphosate is the active ingredient of some of the most highly produced and used herbicides worldwide. The intensive applications of glyphosate-based herbicides and its half-life in water lead to its presence in many aquatic ecosystems. Whereas recent studies have reported neurotoxic effects of glyphosate including autism-related effects, most of them used extremely high (mg/L to g/L) concentrations, so it is still unclear if chronic, low environmentally relevant concentrations of this compound (ng/L to μg/L) can induce neurotoxicity. In this study we analyzed the neurotoxicity of glyphosate in adult zebrafish after waterborne exposure to environmentally relevant concentrations (0.3 and 3 μg/L) for two weeks. Our data showed that exposed fish presented a significant impairment of exploratory and social behaviors consistent with increased anxiety. The anterior brain of the exposed fish presented a significant increase in dopamine and serotonin levels, as well as in the DOPAC/dopamine and homovanillic acid/dopamine turnover ratios. Moreover, the expression of genes involved in the dopaminergic system, as th1, th2, comtb, and scl6a3 was downregulated. Finally, the brain of exposed fish presented a significant increase in the catalase and superoxide dismutase activities, with a concomitant decrease of glutathione stores. These changes in the antioxidant defense system are consistent with the observed increase in oxidative stress, reflected by the increase in the levels of lipid peroxidation in the brain. The presented results show that current glyphosate concentrations commonly found in many aquatic ecosystems may have detrimental consequences on fish survival by decreasing exploration of the environment or altering social interactions. Furthermore, as zebrafish is also a vertebrate model widely used in human neurobehavioral studies, these results are relevant not only for environmental risk assessment, but also for understanding the risk of chronic low-dose exposures on human health. ; This work was supported by the Spanish Government with FEDER Funds (CTM2017-83242-R; D.R.) and the network of recognized research groups by the Catalan Government (2017 SGR_902). J.B. was supported by a Spanish fellowship PRE2018-083513. Mention of specific products or trade names does not indicate endorsement by the US federal government. ; Peer reviewed

Medical artificial intelligence (AI) systems have been remarkably successful, even outperforming human performance at certain tasks. There is no doubt that AI is important to improve human health in many ways and will disrupt various medical workflows in the future. Using AI to solve problems in medicine beyond the lab, in routine environments, we need to do more than to just improve the performance of existing AI methods. Robust AI solutions must be able to cope with imprecision, missing and incorrect information, and explain both the result and the process of how it was obtained to a medical expert. Using conceptual knowledge as a guiding model of reality can help to develop more robust, explainable, and less biased machine learning models that can ideally learn from less data. Achieving these goals will require an orchestrated effort that combines three complementary Frontier Research Areas: (1) Complex Networks and their Inference, (2) Graph causal models and counterfactuals, and (3) Verification and Explainability methods. The goal of this paper is to describe these three areas from a unified view and to motivate how information fusion in a comprehensive and integrative manner can not only help bring these three areas together, but also have a transformative role by bridging the gap between research and practical applications in the context of future trustworthy medical AI. This makes it imperative to include ethical and legal aspects as a cross-cutting discipline, because all future solutions must not only be ethically responsible, but also legally compliant. ; Andreas Holzinger acknowledges funding support from the Austrian Science Fund (FWF), Project: P-32554 explainable Artificial Intelligenceand from the European Union's Horizon 2020 research and innovationprogram under grant agreement 826078 (Feature Cloud). This publi-cation reflects only the authors' view and the European Commissionis not responsible for any use that may be made of the informationit contains; Natalia Díaz-Rodríguez is supported by the Spanish Gov-ernment Juan de la Cierva Incorporación contract (IJC2019-039152-I); Isabelle Augenstein's research is partially funded by a DFF Sapere Auderesearch leader grant; Javier Del Ser acknowledges funding supportfrom the Basque Government through the ELKARTEK program (3KIAproject, KK-2020/00049) and the consolidated research group MATH-MODE (ref. T1294-19); Wojciech Samek acknowledges funding Support from the European Union's Horizon 2020 research and innovationprogram under grant agreement No. 965221 (iToBoS), and the German Federal Ministry of Education and Research (ref. 01IS18025 A, ref. 01IS18037I and ref. 0310L0207C); Igor Jurisica acknowledges funding support from Ontario Research Fund (RDI 34876), Natural Sciences Research Council (NSERC 203475), CIHR Research Grant (93579),Canada Foundation for Innovation (CFI 29272, 225404, 33536), IBM, Ian Lawson van Toch Fund, the Schroeder Arthritis Institute via theToronto General and Western Hospital Foundation.

Previous studies have shown that the use of zinc (Zn) chelate fertilizers combined with a nitrogen (N) fertilizer (urea) can lead to both agronomic (i.e., yields and Zn and N biofortification due to the synergies between both nutrients) and environmental (i.e., by reducing the emissions of nitrous oxide, NO, derived from N fertilization) benefits under rainfed semi-arid conditions. However, little is known about the effect of Zn-N co-fertilization on greenhouse gas (GHG) emissions or soil microbial processes involved in NO fluxes under non-flooded irrigated conditions (during the dry season). Under these conditions, water-filled pore space continuously fluctuates following a periodic pattern and soil temperatures are in the optimum range for soil microorganisms. In this context, a field experiment was conducted using a maize (Zea mays L.) crop treated with two N levels (no N application and 120 kg N ha as urea), and three Zn sources (no Zn application, Zn sulphate, and Zn applied with a mixture of chelating compounds, DTPA-HEDTA-EDTA). Nitrous oxide, methane (CH) and carbon dioxide (CO) fluxes were measured using opaque chambers, as well as the total abundances of soil bacteria, archaea and nitrifier and denitrifier communities. Zn-N co-fertilization increased cumulative NO emissions from 0.36 kg N-NO ha (for urea combined with Zn chelates) to 0.76 kg N-NO ha (for urea combined with Zn sulphate), with respect to urea without Zn application. The NO emission factors were lower (0.34%–0.72%) than the IPCC default value of 1%. Total abundances of the nosZ denitrification gene, which is involved in the reduction in NO to dinitrogen (N), were reduced by 75% on average in the plots that received Zn fertilizers. This reduction may explain the higher NO emissions in these treatments. In contrast with the case with non-irrigated crops, Zn-N co-fertilization cannot be recommended as a strategy to mitigate NO emissions in irrigated maize under semi-arid conditions, despite of the enhancement of Zn availability in soil. ; Financial support was provided by an ERDF-cofinanced grant AGL2015-64582-C3-3-R (MINECO-FEDER) from the Ministerio de Economía y Competitividad (Spanish Government). We are grateful to the Comunidad de Madrid (Spain) and Structural Funds 2014-2020 (ERDF and ESF) for the financial support (project AGRISOST-CM S2013/ABI-2717). The authors are also grateful to the SIRENA network (Ref. AGL2015-68881-REDT), funded by MINECO, for supporting the stay at the Department of Microbiology and Symbiotic System, Estación Experimental del Zaidín, CSIC. M. Montoya and A. Castellano-Hinojosa are the recipients of the FPI grant BES-2016-076712 and a grant of MECD (FPU 2014/01633), respectively. Special thanks are given to the field assistants working with us at Centro Nacional de Tecnología de Regadíos (CENTER), particularly to Alejandro Sánchez de Ribera. We also thank the technicians of the Department of Chemistry and Food Technology of the ETSIAAB. This work was done within the framework of the Moncloa Campus of International Excellence (UCM-UPM).

6 figures, 6 tables.-- Supplementary material available. ; Coronavirus disease 2019 (COVID19), caused by SARS-CoV-2, is a complex disease, with a variety of clinical manifestations ranging from asymptomatic infection or mild cold-like symptoms to more severe cases requiring hospitalization and critical care. The most severe presentations seem to be related with a delayed, deregulated immune response leading to exacerbated inflammation and organ damage with close similarities to sepsis. ; [Methods]: In order to improve the understanding on the relation between host immune response and disease course, we have studied the differences in the cellular (monocytes, CD8+ T and NK cells) and soluble (cytokines, chemokines and immunoregulatory ligands) immune response in blood between Healthy Donors (HD), COVID19 and a group of patients with non-COVID19 respiratory tract infections (NON-COV-RTI). In addition, the immune response profile has been analyzed in COVID19 patients according to disease severity. ; [Results]: In comparison to HDs and patients with NON-COV-RTI, COVID19 patients show a heterogeneous immune response with the presence of both activated and exhausted CD8+ T and NK cells characterised by the expression of the immune checkpoint LAG3 and the presence of the adaptive NK cell subset. An increased frequency of adaptive NK cells and a reduction of NK cells expressing the activating receptors NKp30 and NKp46 correlated with disease severity. Although both activated and exhausted NK cells expressing LAG3 were increased in moderate/severe cases, unsupervised cell clustering analyses revealed a more complex scenario with single NK cells expressing more than one immune checkpoint (PD1, TIM3 and/or LAG3). A general increased level of inflammatory cytokines and chemokines was found in COVID19 patients, some of which like IL18, IL1RA, IL36B and IL31, IL2, IFNα and TNFα, CXCL10, CCL2 and CCL8 were able to differentiate between COVID19 and NON-COV-RTI and correlated with bad prognosis (IL2, TNFα, IL1RA, CCL2, CXCL10 and CXCL9). Notably, we found that soluble NKG2D ligands from the MIC and ULBPs families were increased in COVID19 compared to NON-COV-RTI and correlated with disease severity. ; [Conclusions:] Our results provide a detailed comprehensive analysis of the presence of activated and exhausted CD8+T, NK and monocyte cell subsets as well as extracellular inflammatory factors beyond cytokines/chemokines, specifically associated to COVID19. Importantly, multivariate analysis including clinical, demographical and immunological experimental variables have allowed us to reveal specific immune signatures to i) differentiate COVID19 from other infections and ii) predict disease severity and the risk of death. ; The authors would like to thank the Biobank of the Aragon Health System integrated in the Spanish National Biobanks Network and the Servicios Científico Técnicos de Citometria de Flujo del CIBA for their collaboration. Work in the JP laboratory is funded by the FEDER (Fondo Europeo de Desarrollo Regional, Gobierno de Aragón, Group B29_17R), Health National Institute Carlos III (COV20-00308), Aragón Government (Fondo COVID-19), Fundación Santander-Universidad de Zaragoza (Programa COVID-19), Agencia Estatal de Investigación (SAF2017-83120-C2-1-R; PID2020-113963RBI00), Fundación Inocente, ASPANOA and Carrera de la Mujer de Monzón. EMG is funded by Agencia Estatal de Investigación (SAF2017-83120-C2-1-R and PID2020-113963RB-I00). IUM and SH are supported by a PhD fellowship from Aragon Government, CP by a PhD fellowship from AECC, LS by a PhD fellowship (FPI) from the Ministry of Science, Innovation and Universities. DDM is supported by a postdoctoral fellowship 'Sara Borrell', and MA is supported by a postdoctoral fellowship 'Juan de la Cierva-incorporacion' from the Ministry of Science, Innovation and Universities. EM and BGT are supported by Rio Hortega contract. JP is supported by the ARAID Foundation. ; Peer reviewed

The PhD thesis was embedded in the Energy for Smart Objects (EnSO) project, which is part of the Electronic Components and Systems for European Leadership (ECSEL) Joint Undertaking in collaboration with the European Union's H2020 Framework Program (H2020/2014-2020) and National Authorities, with the aim to develop Autonomous Micro Energy Sources (AMES) for smart objects. In the framework of the EnSO project, the goal of the thesis was to develop a solid electrolyte for all-solid Li-metal microbatteries as energy storage device in AMES. Lithium metal is the anode material of choice because of its very high theoretical specific capacity of 3861 mAh/g, which is one of the important requirements for miniaturized batteries. However, inhomogeneous lithium depositions known as dendrites, which reduce the life time and can connect both electrodes and create a short circuit, are often observed when using Li-metal as anode. The aim is therefore to develop a solid electrolyte, which presents a high ionic conductivity for the Li ion transport and a high mechanical stability to hinder dendritic growth. Electrolyte solutions based on ionic liquids (ILs) with dissolved lithium salt can be confined into inorganic porous networks forming so called ionogels (IGs), which are investigated as quasi-solid electrolyte materials. In a first step, the synthesis in a one-pot sol-gel process for silica-based ionogels is developed and in a second step tested as quasi-solid electrolyte in Li/LiCoO2 systems. IGs were obtained by a sol-gel reaction between TMOS as silica precursor and TFA as catalyst in PYR13-FSI (IL) and LiTFSI (Li+ source). It was possible to synthesize transparent IG monoliths with gelation times of 2-3 h, which is a suitable time for the IG film preparation on the LCO cathodes. Four IGs with different compositions were prepared and characterized. Two types of silica matrices built of mostly threefold-condensed Si centers could be distinguished: a densely packed structure and an open-porous structure, the latter one corresponding to IG B with the molar ratios IL/TMOS=3, TFA/TMOS=0.3, H2O/TMOS=2.3. The ionic conductivity of the IGs could be linked to the silica matrix structure. Only the IG with the open-pore structure (IG B) has a good ionic conductivity (10−4 S/cm). Equally, the examination of the four IGs as thin film electrolytes in LCO/Li batteries show promising results for batteries containing IG B. However, the capacity lies under the theoretical value (89 mAh/g instead of 136 mAh/g) due to high cell resistance. Therefore, the ionic conductivity of IG B was improved by changing the synthesis process while keeping the composition unaltered. The new IG B∗ has a very good ionic conductivity (10−3 S/cm) but a poor mechanical stability due to a matrix structure of loosely connected silica particles. IG B∗ was not able to hinder dendritic growth. Thus, the PVDF-HFP polymer (20 wt.%) was added to B∗ (B∗-p), which enhanced the mechanical stability and the cyclability of the Li-ion batteries with B∗-p as electrolyte layer. No indication of dendrites was visible in the charge/discharge curve for minimum 30 cycles at C/5. The capacities are low (≤ 80 mAh/g) due to the decreased liquid (IL) to solid (SiO2 + PVDF-HFP) ratio, which results in a lower lithium ion mobility. In order to increase the battery capacity, the silica amount in the IG formulation was reduced, the LiTFSI lithium salt concentration was increased, and the Li+ source was modified by taking IL-based electrolyte solution with different concentrations of LiFSI. Indeed, the capacity increases with decreasing silica amount due to improved ion mobility. The change of the lithium concentration from 1M to 3M and 5M enhanced the capacity. A battery with the combination of the reduced silica amount (0.5 TMOS) and 5M electrolyte solution has a good capacity (> 100 mAh/g) for at least 10 cycles at C/5. The lithium salt LiFSI has a smaller anion than LiTFSI and thus, it can further improve the ion mobility in the IG electrolyte film. All IGs containing LiFSI have a higher ionic conductivity than the corresponding gels with LiTFSI. Overall the battery performance and reproducibility could be greatly improved. Batteries containing a solid electrolyte with 20 wt.% PVDF-HFP and the reduced TMOS amount with a 3M LiFSI solution are able to cycle without the appearance of dendrites for 13 cycles at C/5 followed by 12 cycles at C/2 with a rather good coulombic efficiency around 95%. However, the capacity remains under the theoretical maximum.