Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Exploring glycosidic neo-epitopes of degenerative hippocampal granules in aged mice and humans: implications for ageing and dementia (GLYCONEOBRAIN)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2017-09-01
End date: 2019-08-31
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

Ageing is the main correlate of dementia and several other neurodegenerative diseases which currently affect more than 6 million people in Europe. Molecular understanding of these brain conditions is important for their prevention and treatment. In mice, pathological granular structures positive for periodic acid-Schiff stain have been found in the hippocampus with increasing age. The degenerative process of granule formation appears to originate in astrocytes, but adjacent neuronal structures are affected and, accordingly, associated memory impairments have been described. Recent studies reported that granules express glycosidic neo-epitopes, a hallmark of the degenerative granule formation process. This neo-epitope has additionally been found in Lafora bodies of a mouse model of Lafora disease, a fatal neurodegenerative condition. On the other hand, mice serum contains natural IgM antibodies that recognise the glycosidic neo-epitope, suggesting a potentional removal mechanism. In this project, I aim to describe the structure of the glycosidic neo-epitopes of the hippocampal granules as well as the composition of the degenerative granules and Lafora bodies. To achieve these goals, I will employ a multidisciplinary approach exploiting glycomics and neurobiology, with the application of leading-edge technologies that include histological methods, analytical techniques, MALDI-MS imaging and laser-capture microdissection. Moreover, the binding patterns of the anti-neo-epitope natural IgMs will also be explored. Finally and importantly, the expression of the glycosidic neo-epitope in human brain will be assessed. Overall, the knowledge generated will provide new data on brain degenerative processes underlying age-related memory impairments in humans. Ultimately this project will generate new insights for the use of glycosidic neoepitopes as biomarkers for ageing and neurodegenerative diseases, and for prevention and therapeutic strategies using natural antibodies.

Keywords: ageing,dementia,neo epitope,glycoconjugate,periodic acid schiff,lafora bodies,corpora amylacea,natural antibodies,hippocampus,maldi imaging,laser capture microdissection,biomarker
Development of a high-performance nanofluidic osmotic diode for efficient voltage-driven desalination and pumping (NanoOsmDiode)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Reintegration panel
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: France
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Duration (months): 24.0
Total project cost (EUR): 173076.0
EU funding (EUR): 173076.0
Participants: 1
Project status: CLOSED

Water scarcity is an urgent global challenge and one of the greatest societal threats posed by climate change. Despite growing concern over water availability, processes to expand water supplies beyond current freshwater reserves, such as desalination and wastewater reclamation, still suffer from insufficient rejection of contaminants and relatively high energy requirements. Nanofluidic technologies have the potential to revolutionize water treatment owing to the extraordinary transport characteristics of confined pores. The objective of the proposed project is to develop a new nanofluidic device—the osmotic diode—for voltage-driven desalination and pumping. To control water and ion transport, the device requires a nanopore with tailored asymmetric surface charge. An applied voltage difference can be used to drive water molecules through the nanopore while ions are rejected, desalinating source water. The system is advantageous because permeability and selectivity properties can be tuned based on nanopore characteristics, and it offers improved versatility compared to existing desalination processes. To realize the technology, the proposed work will (i) fabricate a single pore osmotic diode with tailored surface charge, (ii) characterize water transport across such a nanopore utilizing ultrasensitive flow measurement techniques, and (iii) use knowledge from the single pore system to scale up performance to many-pored membranes. Throughout the project, advanced modeling techniques will be utilized to fundamentally understand transport and further optimize the system. The proposed research action will address Horizon 2020 Societal Challenges related to water security and resource efficiency while advancing the field of nanotechnology through the development of new fabrication and flow measurement methods. The research action will also represent the first proof-of-concept for an osmotic diode system and lay the foundation for further commercialization of the process.

Keywords: nanofluidics,membrane processes,desalination,aqueous separations,electro osmosis,water technology,microfluidics,nanoporous materials,transport phenomena,water energy nexus
Embodied Cognitive Neuromorphic Technology (ECogNeT)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Switzerland
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-04-01
End date: 2018-03-31
Duration (months): 24.0
Total project cost (EUR): 187419.6
EU funding (EUR): 187419.6
Participants: 1
Project status: CLOSED

Biological neuronal networks allow humans and animals to build representations of objects, complex scenes, and temporal sequences and to use these representations to plan and execute goal-directed actions, learn new skills, and constantly adapt to changing situations. Neuronal systems have evolved to be extremely powerful in perceiving and acting in complex and dynamic real-world environments. The field of neuromorphic engineering is realising neuronal computation in a new generation of hardware systems, aiming to enable computation with high efficiency and low energy cost, comparable to biological neuronal networks. In order to use this hardware to implement systems that can solve perceptual, motor, and cognitive tasks, cognitive architectures have to be developed, which integrate elementary cognitive processes in a coherent computational framework. The ECogNeT project aims to develop such a computational framework by realising neural-dynamic models of embodied cognition in neuromorphic hardware. In particular, the computational and conceptual framework of Dynamic Neural Fields will be used to create cognitive computational primitives in neuromorphic hardware, which will organise the hardware neurons in attractor-networks, capable to generate discrete, cognitive representations from sensory inputs. The developed neuromorphic cognitive architecture will be integrated with sensors and motors of a robotic agent and its capability to represent environmental situations and temporal sequences of events will be validated in benchmark scenarios, exploiting the potential of this new technology in development of novel, low-power, fast, and smart devices capable to work in real-world settings in order to advance future prosthetic systems, smart environments, and assistive robots.

Keywords: neurally inspired computing,neurorobotics,cognitive systems,neuromorphic engineering
Efficient Traffic Control with Variable Speed Limits: Bridging the gap between Theory and Practical Implementation (ETC-VSL)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Netherlands
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2017-02-01
End date: 2019-01-31
Duration (months): 24.0
Total project cost (EUR): 165598.8
EU funding (EUR): 165598.8
Participants: 1
Project status: CLOSED

The main objective ETC-VSL, the proposed MSCA, is the design and testing of a control algorithm for Variable Speed Limits (VSL) that approaches the behavior of an optimal controller and can, at the same time, be applied in practice to large traffic networks. When designing this controller, it has to be taken into account in general that a linear or logic-based controller for VSL, which can performs properly for one particular kind of congestion, is not going to approach an optimal behavior for other kinds of congestion. In fact, all the previously proposed algorithms for VSL performs suboptimally or are difficult to implement in practice. Therefore, this proposal suggests the use of two control levels: In the upper level, a scheduling controller detects online the main kinds of congestion (recurrent congestions, shock waves and unexpected capacity reductions) and, in the lower level, a practically implementable controller for each kind of congestion is used. In order to achieve this objective, the proposal considers the following steps: Step 1: The design or selection of a triggering rule that estimates what kind of congestion the system is showing (if any). Step 2: The design or selection of a controller that works for each kind of congestion. Step 3: The collection of a loop detector data set from the SE-30 ring-road in Spain. Step 4: The testing and evaluation of the proposed algorithm in two freeways (SE-30 in Spain and A12 in The Netherlands) that show the main kinds of congestion allowing an objective evaluation of the designed VSL control algorithm and a comparison with previously proposed techniques. Step 5: The analysis of the economic and social improvements that can be obtained by the implementation of VSL applying a Benefit-Cost Analysis. Step 6: Dissemination of results and communication towards the technical and non-technical community in order to show the potential performance that can be achieved using the newly developed VSL control strategy.

Keywords: variable speed limits,freeway traffic control
Strategic, Tactical, Operational Protection of water Infrastructure against cyber-physical Threats (STOP-IT)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure societies - protecting freedom and security of Europe and its citizens
Theme: Protect and improve the resilience of critical infrastructures, supply chains and tranport modes
Action type: Innovation actions
Countries involved: Spain,Israel,Germany,Spain,Spain,Spain,Italy,Germany,Germany,Belgium,Norway,Belgium,Norway,Norway,Greece,Netherlands,Netherlands
Call: Prevention, detection, response and mitigation of the combination of physical and cyber threats to the critical infrastructure of Europe. (CIP-2016-2017-1, 2016)
Start date: 2017-06-01
End date: 2021-10-31
Duration (months): 53.0
Total project cost (EUR): 9616525.18
EU funding (EUR): 8255319.5
Participants: 34
Project status: CLOSED

Water critical infrastructures (CIs) are essential for human society, life and health and they can be endangered by physical/cyber threats with severe societal consequences. To address this, STOP-IT assembles a team of major Water Utilities, industrial technology developers, high tech SMEs and top EU R&D providers. It organizes communities of practice for water systems protection to identify current and future risk landscapes and to co-develop an all-hazards risk management framework for the physical and cyber protection of water CIs. Prevention, Detection, Response and Mitigation of relevant risks at strategic, tactical and operational levels of planning will be taken into account to generate modular solutions (technologies, tools and guidelines) and an integrated software platform. STOP-IT solutions are based on: a) mature technologies improved via their combination and embedment (incl. public warning systems, smart locks) and b) novel technologies whose TRL will be increased (incl. cyber threat incident services, secure wireless sensor communications modules, context-aware anomaly detection technologies; fault-tolerant control strategies for SCADA integrated sensors, high-volume real-time sensor data protection via blockchain schemes; authorization engines; irregular human detection using new computer vision methods and WiFi and efficient water contamination detection algorithms). STOP-IT solutions are demonstrated through a front-runner/follower approach where 4 advanced utilities, Aigües de Barcelona (ES), Berliner Wasserbetriebe (DE), MEKOROT (IL) and Oslo VAV (NO) are twinned with 4 less advanced, but ambitious ones, to stimulate mutual learning, transfer and uptake. Building on this solid basis STOP-IT delivers high impact through the creation of hands-on training, best practice guidelines, support for certification and standardization as well as by fostering market opportunities, also leveraging the EU water technology platform's multi-stakeholder network.

Keywords: protection of networks,cybersecurity,physical threat,integrated risk management,water critical infrastructure,safety,resilience,community of practice,detection,preparedness,mitigation
An Automated HEV and EV Vehicle Fire Early Warning and Suppression System (Li-IonFire)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: SME instrument
Countries involved: Sweden
Call: Small business innovation research for Transport (H2020-SMEINST-1-2015, 2015)
Start date: 2015-07-01
End date: 2015-12-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The developing hybrid electric vehicles and pure electric vehicles industry has led to the adoption of lithium ion batteries as the source of power. The durability and high energy density of Li-ion batteries makes them more favourable than other alternatives. Li-ion batteries are inherently weak concerning to fire management systems. Short circuiting, overcharging, high temperatures and overheating cause thermal runaway and the release of a flammable electrolyte which makes fire extinguishing very difficult and this has stalled the progress of the HEV and EV industry. Current fire suppressing systems have failed to effectively deal with li-ion fires and Dafo Brand has come up with an innovative HEV/EVLi-ionFire project aimed at fire management and suppression for heavy commercial HEV and EV such as buses and trucks. Our proposed innovation would be 12% cheaper than current available technologies which use different li-ion fire suppression techniques. Phase 1 will focus on market study, partners search, optimisation of the technology used in internal combustion engines to suit HEV and EV standards as well as formulation of an IP management strategy in preparation for full project implementation in Phase 2. Technology validation and testing will be done in Phase 2.

Keywords: fire suppression system for li ion battery fires
Support Unit for the Deep Geothermal Implementation Working Group (SU-DG-IWG)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: Coordination and support actions
Countries involved: Germany,Iceland,Belgium,Netherlands,Portugal,Portugal
Call: Support to the realisation of the Implementation Plans of the SET Plan (H2020-LC-SC3-2018-Joint-Actions-2, 2018)
Start date: 2019-02-01
End date: 2022-07-31
Duration (months): 42.0
Total project cost (EUR): 1006750.0
EU funding (EUR): 1006750.0
Participants: 7
Project status: SIGNED

Following the endorsement of the Deep Geothermal Implementation Plan (DG-IP) by the SET-Plan Steering Group, a Deep Geothermal Implementation Working Group (DG-IWG) is being established to advance the DG-IP, with the aim of reaching collectively the technology targets that will place Europe at the forefront of the next generation of low carbon technologies. The objective of this project proposal is to create a support unit for the DG-IWG to achieve its goals efficiently and productively. The support unit will have three main work streams, 1) to provide the DG-IWG with relevant information and data from the various stakeholder groups to support the decisionmaking process and the implementations actions of DG-IWG on required actions; 2) to promote and organise initiatives to mobilize growth of and implementation within the geothermal community, e.g.: workshops, brokerages, consortium building and exploitation of RD&I results; 3) provide a secretariat for the DG-IWG for assistance on administrative issues and synergies & strategy support. The consortium will push forward a broad mobilisation of the Geothermal community to implement the action in the IP. Furthermore the project will focus on the development of synergies and strategies. New ways will be explored to maximize the impact of knowledge, funding and market growth at european, national and regional scale. This aproach supports to creation of a durable and long-lasting R&I ecosystem in the different Member-Sates and regions. The partners will focus on a multi-actor, multidisciplinary and cross-sectoral approach. As such the project will support the collaboration and networking among representatives of the triple helix (research, industry and government) at the regional and national level and with their counterparts from the Horizon 2020 Associated Countries.

Keywords: deep geothermal,set plan,implementation plan,implementation working group
Predicting the impacts of climate change and management actions for the invasiveness of alien species in Europe (Primer)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Environment and Geosciences
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2019-04-17
End date: 2021-04-16
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

In European temperate regions, predicting how climate change will affect rates of biological invasions is crucial for conserving native biodiversity. A European Regulation adopted in 2014 aims to prevent new introductions and stop existing alien species from developing invasions. This requires robust predictions on how introduced alien species will respond to climate change and the management actions designed to prevent invasions. Predictions of ‘invasiveness’, the ability of an introduced alien species to invade, tend to be based on climate envelope models, but these lack environmental and biological complexity and so produce erroneous predictions. Our primary aim is thus to develop novel agent-based models (ABMs) for predicting the consequences of climate change and management actions for the invasiveness of introduced alien species in Europe by integrating climatic, environmental, management and hydrological data. Model regions are Great Britain and France, providing a large latitudinal and climatic gradient suitable. Model species are alien freshwater fishes, as they strongly represent invasive animals in Europe. The experienced researcher (ER) will complete the following research objectives to meet the primary aim: (O1) select the species for modelling and collate the data for modelling; (O2) develop an initial ABM for current climate conditions; (O3) parameterise, for each model species, the initial ABM to predict current invasion probabilities; and (O4) use these final ABMs to predict, via simulations of climate change and management actions, the future invasiveness of the model alien fishes in freshwaters. As the ER has high expertise on invasive species then strong knowledge exchange activities in the Fellowship will: (1) provide the ER with new competencies in predictive ecology and modelling to enable completion of this novel and innovative research, and (2) enable the hosts to develop new research agendas on biological responses to environmental change.

Keywords: non native species,climate change,invasiveness,invasion management
Energy Oriented Center of Excellence : toward exascale for energy (EoCoE-II)

Framework: Horizon 2020 — Excellent Science
Programme: Research Infrastructures
Theme: Research infrastructures
Destination: European Data Infrastructure
Action type: Research and Innovation actions
Partnership: HPC PPP (cPPP)
Countries involved: Germany,Germany,Italy,Italy,Germany,Germany,Spain,Spain,Belgium,Poland,France,France,France,France,France,France,France,United Kingdom
Call: HPC PPP - Centres of Excellence on HPC (H2020-INFRAEDI-2018-1, 2018)
Start date: 2019-01-01
End date: 2022-06-30
Duration (months): 42.0
Total project cost (EUR): 8621955.25
EU funding (EUR): 8303454.75
Participants: 24
Project status: CLOSED

The Energy-oriented Centre of Excellence (EoCoE) applies cutting-edge computational methods in its mission to accelerate the transition to the production, storage and management of clean, decarbonized energy. EoCoE is anchored in the High Performance Computing (HPC) community and targets research institutes, key commercial players and SMEs who develop and enable energy-relevant numerical models to be run on exascale supercomputers, demonstrating their benefits for low-carbon energy technology. The present project will draw on a successful proof-of-principle phase of EoCoE-I, where a large set of diverse computer applications from four such energy domains achieved significant efficiency gains thanks to its multidisciplinary expertise in applied mathematics and supercomputing. During this 2nd round, EoCoE-II will channel its efforts into 5 scientific Exascale challenges in the low-carbon sectors of Energy Meteorology, Materials, Water, Wind and Fusion. This multidisciplinary effort will harness innovations in computer science and mathematical algorithms within a tightly integrated co-design approach to overcome performance bottlenecks and to anticipate future HPC hardware developments. A world-class consortium of 18 complementary partners from 7 countries will form a unique network of expertise in energy science, scientific computing and HPC, including 3 leading European supercomputing centres. New modelling capabilities in selected energy sectors will be created at unprecedented scale, demonstrating the potential benefits to the energy industry, such as accelerated design of storage devices, high-resolution probabilistic wind and solar forecasting for the power grid and quantitative understanding of plasma core-edge interactions in ITER-scale tokamaks. These flagship applications will provide a high-visibility platform for high-performance computational energy science, cross-fertilized through close working connections to the EERA and EUROfusion consortia.

Keywords: energy transition,high performance computing