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This article makes the central argument that basic democratic values such as justice, autonomy and participation run the risk of being neglected when designing ‘nudges’ (i.e., indirect suggestions to influence individual behaviour) for sustainable behaviour change in the context of food governance, potentially complicating a democratisation of the food system. ‘Nudges’ uphold freedom of choice while simultaneously advocating a non-coercive soft force of paternalism to help people realise their preferences, maximise societal well-being and meet macro-sustainability goals. While the promises of the ‘nudge’ approach are widely echoed, nudging is also being contested because of its possible anti-democratic effects, such as individualisation, depoliticization and the emphasis of the status of citizens as ‘consumer-citizens.’ From a food democracy perspective, these dangers may undermine efforts to organise collective political action and impede alternative visions of a future food system. Empirically, the article examines specifically how behavioural-economic approaches imagine transitions to a more sustainable food system. By using the “COOP Supermarket of the Future” as a case study, the following analysis will illustrate how private actors are increasingly involved in steering consumer choice towards socially desirable actions. The analysis suggests that the design of choice environments may under specific circumstances increase the susceptibility of individuals to the influence of corporate preferences and simultaneously decrease the prospects for democratic legitimation and decision-making. The article therefore critically assesses whether reforming the food system by altering consumers’ choice-sets and the attribution of personal responsibility, may in fact point towards implicit anti-democratic tenets underlying the ‘will to nudge’ citizens.

"Egal ob Pump- oder Druckspeicher, Batterien oder "virtuelle" Pufferung im Netz - alle Technologien zur Stromspeicherung besitzen ihre spezifischen Vor- und Nachteile. Angesichts wachsender Marktanteile regenerativer Stromerzeugung nimmt die Bedeutung effizienter Techniken zur Energiespeicherung zu. Nur so werden "fluktuierende" Quellen wie Windkraft und Photovoltaik planbar."

In 2008 the Large Hadron Collider (LHC) and its experiments started operation at the European Centre of Nuclear Research (CERN) in Geneva with the main aim of finding or excluding the Higgs boson. Only four years later, on the 4th of July 2012, the discovery of a Higgs-like particle was proven and first published by the two main experiments ATLAS and CMS. Even though proton–proton collisions are the main operation mode of the LHC, it also acts as an heavy-ion collider. Here, the term “heavy-ion collisions” refers to the collision between fully stripped nuclei. While the major hardware system of the LHC is compatible with heavy-ion operation, the beam dynamics and performance limits of ion beams are quite different from those of protons. Because of the higher mass and charge of the ions, beam dynamic effects like intra-beam scattering and radiation damping are stronger. Also the electromagnetic cross-sections in the collisions are larger, leading to significantly faster intensity decay and thus shorter luminosity lifetimes. As the production cross-sections for various physics processes under study of the experiments are still small at energies reachable with the LHC and because the heavy-ion run time is limited to a few days per year, it is essential to obtain the highest possible collision rate, i.e. maximise the instantaneous luminosity, in order to obtain enough events and therefore low statistical errors. Within this thesis, the past performance of the LHC in lead-lead (Pb-Pb) collisions, at a centre-of-mass energy of 2.76 TeV per colliding nucleon pair, is analysed and potential luminosity limitations are identified. Tools are developed to predict future performance and techniques are presented to further increase the luminosity. Finally, a perspective on the future of high energy heavy-ion colliders is given.

International audience Solar resource and forecasting in very short spatial and timescales (0–100 m, 0–30 min) is a challenging task that cannot be accurately achieved by satellite products or numerical weather predictions due to technical and methodological restrictions. For this reason, sky images from ground-based cameras are widely used during the last decade to deal with the high spatial and temporal variability of clouds and provide the needed inputs for numerical models for the current and forecasted (in short-term) solar irradiance. In this chapter, the available types of all-sky cameras/imagers are shortly presented. The chapter is focused on the state-of-the-art methodologies used to derive parameters needed for the estimations of solar resource and forecasting by a calibrated all-sky camera: cloud coverage, type, height, and velocity as well as aerosol optical properties. The application of these methodologies at Plataforma Solar de Almeria, in the frame of project: “Direct Normal Irradiance Nowcasting methods for optimized operation of concentrating solar technologies” (DNICast, http://www.dnicast-project.net/) is discussed. Finally, the chapter finishes with some propositions for future work in the recent, but quickly, developed research area.

Sustainability of agro-food supply chains has recently become the subject of greater interest from consumers, firms, governmental organizations and academia as the environment continues to deteriorate. One of the most critical factors influencing the sustainability of an agro-food supply chain is its network design. A particularly challenging aspect in this context is the broad range of influencing indicators associated with the Triple Bottom Line (TBL) of sustainability that need to be considered. However, many of these indicators could not be fully integrated or measured by single-step optimization problems. This paper presents a critical literature review of operational research methods for the design of sustainable supply chains. A novel two-stage hybrid solution methodology is proposed. In the first stage, a partner selection is performed using a hybrid multi criteria decision making based on Analytic Hierarchy Process (AHP) method and the Ordered Weighted Averaging (OWA) aggregation method. The result obtained in the first stage is used in the second stage to develop a multi-objective mathematical model to optimize the design of the supply chain network. This approach allows the simultaneous consideration of all three dimensions of sustainability including carbon footprint, water footprint, number of jobs created and the total cost of the supply chain design. The proposed approach generates a Pareto frontier to aid users in making decisions. Numerical experiments are completed utilizing data from an agro-food company to demonstrate the efficiency and effectiveness of the proposed solution methodology. The analyzes of the numerical results provide important organizational, practical and policy insights on (1) the impact of financial and environmental sustainability on supply chain network design (2) the tradeoff analysis between environmental emission, water footprint, societal implications and associated cost for making informed decision on supply chain investment.

Since the invention of fluorescent light sources, there is strong interest in Eu3+ activated phosphors as they are able to provide a high color rendering index (CRI) and luminous efficacy, which will also hold for phosphor converted light emitting diodes. Due to an efficient U6+ to Eu3+ energy transfer in Gd3Li3Te2O12:U6+,Eu3+, this inorganic composition shows red photoluminescence peaking at 611 nm. That means Eu3+ photoluminescence can be nicely sensitized via excitation into the U6+ excitation bands. Therefore, photoluminescence properties, such as temperature dependent emission and emission lifetime measurements, are presented. Charge transfer bands were investigated in detail. Additionally, density functional theory calculations reveal the band structure of the pure, i.e., non-doped host material. Obtained theoretical results were evaluated experimentally by the aid of diffuse UV reflectance spectroscopy.

Mixing under high pressure conditions plays a central role in several engineering applications, such as direct-injection engines and liquid rocket engines. Numerical flow simulations have become a complementary tool to study the mixing process under these conditions but require complex thermodynamic modeling as well as validation with accurate experimental data. For this reason, we use experiments of supercritical single-phase jet mixing from the literature, where the mixing is quantified by the mixture speed of sound, as a reference for our work. We here focus on the thermodynamic modeling of multi-component flows under high pressure conditions and the analytical calculation of the mixture speed of sound. Our thermodynamic model is based on cubic equations of state extended for multi-components. Using an extension of OpenFOAM, we perform large-eddy simulations of hexane and pentane injections and compare our results with the experimentally measured mixture speed of sound at specific positions. The simulation results show the same characteristic trends, indicating that the mixing effects are well reproduced in the simulations. Additionally, the effect of the sub-grid scale modeling is assessed by comparing results using different models (Smagorinsky, Vreman, and Wall-Adapting Local Eddy-viscosity). The comprehensive simulation data presented here, in combination with the experimental data, provide a benchmark for numerical simulations of jet mixing in high pressure conditions.