Urban experimentation has become central to sustainability transitions, evolving from grassroots initiatives toward mainstream adoption in European Union policy programs. While this shift expands resources and visibility, it also embeds experiments within managerial politics that demand standardized proposals aligned with EU priorities and evaluation templates. Within this context, the proposal-writing stage becomes a formative yet overlooked moment where experimental trajectories are fixed before implementation begins. This paper develops and illustrates a heuristic framework for analyzing how (de)politicization shapes EU-funded urban experiments during the proposal phase. Drawing on Chantal Mouffe's distinction between politics and the Political, the framework identifies four domains - representation, agenda-setting, legitimation, and distribution - where institutional embedding intersects with political contestation. The framework is illustrated through expert interviews with EU funding practitioners and a case study of the ATELIER Horizon 2020 project on Positive Energy Districts. The analysis illustrates how proposal frameworks may privilege established actors and measurable outputs while marginalizing uncertain or radical ambitions, even as internal debates reveal traces of contestation that rarely stabilize in final texts. The paper closes with implications for urban experimentation scholarship and recommendations for designing more politically reflexive EU funding architectures.
Electricity generation relies on a set of complex facilities where mechanical engineering plays an essential role in ensuring the performance, reliability, safety, and sustainability of systems. This document presents a non-exhaustive overview of the contribution of mechanics in the nuclear, hydraulic, and wind power sectors, from a fundamental understanding of the phenomena to advanced methods of design, experimentation, and numerical modeling. We show how fluid mechanics, structural mechanics, and materials science complement each other in order to design, dimension, control, and optimize the components and structures necessary for electricity generation. This complementarity of mechanical sciences is made possible by advanced scientific work providing detailed knowledge of flows, heat transfer, mechanical stresses, vibration phenomena, and damage mechanisms, which occur in various contexts such as reactor cooling, dam resistance, wind turbine stability, and nuclear fuel performance. This summary highlights an important feature of mechanical sciences, namely the parallel evolution of experimental and numerical approaches, which complement each other in understanding the complex phenomena affecting energy facilities. Scale model testing, real-world measurements, and modern imaging techniques provide data that is essential for validating three-dimensional simulations. Numerical models, on the other hand, make it possible to explore extreme conditions that are difficult to reproduce in the laboratory and to test multiple design variants. These models are becoming bigger thanks to high performance computing and allow today chaining or coupling different physics and scales. The decarbonization of energy and the resulting increase in electricity production are associated with several scientific challenges that must be addressed: realistic consideration of dynamic phenomena, improvement of physical models, control of material aging, management of fluid-structure interactions, simulation of two-phase flows, and evaluation of uncertainties in calculations. These challenges will be met more easily if industry and research actively collaborate to maintain a high level of innovation and thus guarantee the safety of production facilities.
Bycatch from pelagic longline fisheries poses a serious threat to the endangered leatherback turtle in the Atlantic Ocean. However, the spatiotemporal distribution of bycatch risk remains poorly understood, largely due to data limitations such as sparse observer coverage, zero-inflation, and inconsistent temporal sampling. Here, we analyze 18 years (2002–2019) of Japanese longline observer data to identify seasonal high-risk areas for turtle bycatch, using a zero-inflated binomial model based on stochastic partial differential equations (SPDE) combined with hotspot analysis. This framework allows us to extract meaningful spatial patterns from data-poor situations and generate spatially explicit estimates of relative leatherback density and bycatch risk. Our results reveal that bycatch hotspots occur predominantly near the African coast in the first quarter and expand across both the African coast and the broader North Atlantic in the fourth quarter. Seasonal differences in risk were more pronounced than interannual fluctuations, aligning with known migratory behaviors of leatherbacks. These findings underscore the importance of season-specific conservation strategies such as time-area closures or dynamic bycatch avoidance measures, providing actionable spatial and seasonal risk maps that could inform the design and timing of mitigation measures. More broadly, our approach offers a practical solution for assessing risk in other threatened marine taxa under data-limited conditions and enhances evidence-based conservation planning in marine ecosystems.
Coastal areas include various habitats of living organisms, such as mud flats at river mouths, seagrass beds, seaweed communities, rocky intertidal shores, sandy beaches, coral reefs, and mangroves. In this chapter, we review the modeling pathways for this system of ecosystem networks, called the "coastal ecosystem complex" (CEC), from concepts to numerical representations. Four important ecological features of the CEC concept are identified (population connectivity, habitat heterogeneity, trophic interactions, and ontogeny of organisms), and we discovered the link between each factor and models of population connectivity, species distributions, food webs, and organisms' life histories, respectively. We also review several existing integrated model frameworks, examining their potential capacities to simulate CEC processes, and identify the importance of habitat function, ontogenetic development in early life stages, and variability recruitment to the development of the CEC model.
& horbar;In coho salmon Oncorhynchus kisutch challenged with piscine orthoreovirus 2 (PRV-2), hematocrit values showed an immediate decline, reaching their lowest point at 40 days post-challenge (dpc), followed by a gradual recovery. Erythrocytic inclusion bodies were observed only between 20 and 40 dpc. The viral genome copy numbers peaked at 30 dpc. These findings suggest that the disease progressed until 40 dpc, after which recovery took place. The presence of ELISA antibodies against the virus was detected after 60 dpc, with a significant increase noted at 80 dpc.
