Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
ComputationaL dEsign optimization for unpolluted wAteR (CLEAR)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Society and Enterprise panel
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: France
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-05-01
End date: 2022-04-30
Duration (months): 24.0
Total project cost (EUR): 196707.84
EU funding (EUR): 196707.84
Participants: 1
Project status: CLOSED

The increased use of pharmaceutical drugs and agriculture chemicals in the last five decades now results in a global contamination of the water cycle. Antibiotics, endocrine disruptors, pesticides are among the most alarming compounds found in wastewaters and even in treated waters. Currently, wastewater treatment plants are the most significant barriers to water contamination, but are known to fail in decreasing micropollutants concentrations to reasonable levels. Consequently, there is an urgent need to implement technologies for removal of micropollutants from wastewaters before they reach rivers, groundwater and marine waters. EDEN MICROFLUIDICS offers a compact, easy-to-deploy, cost-effective technology for micropollutant removal, thus giving access to quality water to the EU and beyond. The system uses microfluidics for treatment of high volume of effluent at low pressures, decreasing significantly energy consumption compared to current techniques. But the fluidic design, while efficient, fails to adapt for the wide range of pollutants and their properties. The fluidic architecture should be dependent on pollutant types, sizes, concentration, ... Designing with such a large array of parameters requires expertise in a specific computational method: Computational Design Optimisation. The objective of the research proposed here is to optimize the design of the devices developed by EDEN by means of computational methods. We will build the necessary physics-based or data-driven models to enable the use of numerical optimization algorithms to determine optimal design solutions for a variety of conditions and requirements. We will employ multidiscisplinary design optimization techniques to account for the interaction of different disciplines entailed in the treatment process, and will also formulate strategies for platform-based design of families of devices to derive different solutions at minimal cost and development lead times.

Keywords: numerical optimization,multidisciplinary design optimization,platform based product family design
Multimodal Extreme Scale Data Analytics for Smart Cities Environments (MARVEL)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Germany,Spain,Italy,Italy,Germany,Malta,Serbia,Finland,Switzerland,Poland,Greece,Greece,Greece,France,Denmark,Luxembourg
Call: Big Data technologies and extreme-scale analytics (H2020-ICT-2020-1, 2020)
Start date: 2021-01-01
End date: 2023-12-31
Duration (months): 36.0
Total project cost (EUR): 5998086.25
EU funding (EUR): 5998086.25
Participants: 19
Project status: SIGNED

The “Smart City” paradigm aims to support new forms of monitoring and managing of resources as well as to provide situational awareness in decision-making fulfilling the objective of servicing the citizen, while ensuring that it meets the needs of present and future generations with respect to economic, social and environmental aspects. Considering the city as a complex and dynamic system involving different interconnected spatial, social, economic, and physical processes subject to temporal changes and continually modified by human actions. Big Data, fog, and edge computing technologies have significant potential in various scenarios considering each city individual tactical strategy. However, one critical aspect is to encapsulate the complexity of a city and support accurate, cross-scale and in-time predictions based on the ubiquitous spatio-temporal data of high-volume, high-velocity and of high-variety. To address this challenge, MARVEL delivers a disruptive Edge-to-Fog-to-Cloud ubiquitous computing framework that enables multi-modal perception and intelligence for audio-visual scene recognition, event detection in a smart city environment. MARVEL aims to collect, analyse and data mine multi-modal audio-visual data streams of a Smart City and help decision makers to improve the quality of life and services to the citizens without violating ethical and privacy limits in an AI-responsible manner. This is achieved via: (i) fusing large scale distributed multi-modal audio-visual data in real-time; (ii) achieving fast time-to-insights; (iii) supporting automated decision making at all levels of the E2F2C stack; and iv) delivering a personalized federated learning approach, where joint multi modal representations and models are co-designed and improved continuously through privacy aware sharing of personalized fog and edge models of all interested parties.

Keywords: edge fog cloud computing,decision making
Upscaling and optimizing subsurface, in situ carbon mineralization as an economically viable industrial option (CarbFix2)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Low-cost, low-carbon energy supply
Action type: Research and Innovation actions
Countries involved: Iceland,Spain,Switzerland,France
Call: Geological storage pilots (H2020-LCE-2017-RES-CCS-RIA, 2017)
Start date: 2017-08-01
End date: 2021-01-31
Duration (months): 42.0
Total project cost (EUR): 2200318.75
EU funding (EUR): 2200318.0
Participants: 5
Project status: CLOSED

This CarbFix2 proposal builds upon the success of the recently completed 7th framework CarbFix EC project. The original CarbFix received worldwide recognition for developing novel, safe, and efficient geologic carbon storage method, which successfully converted injected CO2 into stable carbonate rocks within two years. This CarbFix2 project has been designed to make the CarbFix geological storage method both economically viable with a complete CCS chain, and to make the technology transportable throughout Europe. This will be done through a comprehensive project consisting of 1) the co-injection of impure CO2 and other water-soluble polluting gases into the subsurface, 2) developing the technology to perform the CarbFix geological carbon storage method using seawater injection into submarine basalts, and 3) by integrating the CarbFix method with novel air-capture technology. This novel CarbFix2 project is described in detail in this document.

Keywords: co2 injection,impure co2,mineral storage,on shore injection,off shore injection,air capture,modelling,monitoring,cost,safety
On a Nuclear Waste Deep Repository Simulator (NuWaSim)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Spain
Call: ERC-Proof of Concept-2016 (ERC-2016-PoC, 2016)
Start date: 2016-11-01
End date: 2018-04-30
Duration (months): 18.0
Total project cost (EUR): 149250.0
EU funding (EUR): 149250.0
Participants: 1
Project status: CLOSED

Nuclear waste is generated during the operation and maintenance of nuclear power plants. The waste is first transferred to an interim storage, where it remains for tens of years, till radioactivity and heat generation of the spent fuel is reduced to a level that allows its final disposal. It is generally accepted that the final waste will be disposed of in a deep geological repository. However, not a single country worldwide has an operational underground repository. In the design process of these repositories, simulation tools capable to model their long term behavior (hundreds of years) are required. However, such simulations are extremely challenging, due to the complicated nature of the physical phenomena of multiscale and multiphysics nature. Current numerical tools being used by some of the most advanced deep repository projects use CODE_BRIGHT (developed at UPC-CIMNE), a very rich code in terms of modelling capabilities, which benefits from 20 years of intensive validation against in-situ experiments. However, CODE_BRIGHT is a serial structured FORTRAN 90 code with very limited capabilities in terms of parallel performance. As a result, actual analyses of prototypical deep repositories require strong and not validated simplification assumptions, in order to reduce by some orders of magnitude the computational cost of the target simulations. In this project, we want to change the situation by developing extremely scalable simulation software for nuclear waste management in repositories. The strategy is to port CODE_BRIGHT modelling capabilities to FEMPAR, the extremely scalable scientific computing code that resulted from the Starting Grant COMFUS. The result of this work will be a new software that (1) produces the same results as CODE_BRIGHT for a wide set of benchmark tests (to validate the code), and (2) with proven excellent scalability on hundreds of thousands of processors.

Keywords: simulation,modelling,computational engineering,scientific software,nuclear waste management,finite element method,parallel computing
General-purpose virus-neutralizing engulfing shells with modular target-specificity (VIROFIGHT)

Framework: Horizon 2020 — Excellent Science
Programme: Future and Emerging Technologies (FET)
Theme: EIC Pathfinder
Destination: Novel ideas for radically new technologies
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Slovenia,France,Denmark
Call: FET-Open Challenging Current Thinking (H2020-FETOPEN-2018-2019-2020-01, 2019)
Start date: 2020-06-01
End date: 2024-05-31
Duration (months): 48.0
Total project cost (EUR): 3880942.5
EU funding (EUR): 3880942.5
Participants: 6
Project status: SIGNED

Viral infections affect millions of people every year and cause tremendous human suffering and costs to society. For approximately 70% of all WHO listed viruses, no treatment is available and the antiviral drugs that do exist typically must be applied very early after infection to be effective. The VIROFIGHT consortium proposes a radically new approach to fight viral infections, to help reduce the scale and sheer impact of viral infections, to address the problem of a lack of broadly applicable antiviral treatments, and to create means for combating emerging pathogens. Instead of targeting virus-specific proteins or enzymes by small molecules as current antivirals do, we will construct synthetic nano-shells that can specifically recognize and engulf entire viruses to efficiently neutralize the pathogen by occlusion. To achieve this technological target, our interdisciplinary project integrates supramolecular chemistry, molecular nanoengineering, and virology with the mission to develop and test prototypes of engulfing nano-shells that have the principal capacity to neutralize any given virus. We will fabricate biocompatible nano-shells through DNA origami and protein design and attach modularly virus-specific molecules to them in a multivalent fashion, to exploit avidity effects for strong virus binding. The virus binders will be identified through rapid in vitro selection processes designed to be applicable to any target virus. Neutralization assays will be used to test our concept on a variety of viruses. VIROFIGHT has the potential to attain revolutionary properties: shell prototypes can be developed and produced in the course of weeks after discovery of a viral pathogen, and the drug concept can be used and adapted for a wide variety of viral pathogens, without having detailed knowledge about the virus. The VIROFIGHT concept aimed at eradicating multiple viruses thus has great potential for decreasing the burden for patients and saving costs to society.

Keywords: dna nanotechnology,protein design,aptamers,multivalency,virus neutralization,nanomedicine
Multimodal, high-resolution modeling of the thalamus for neuroimaging studies: application to dyslexia (THALAMODEL)

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: Spain
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-06-01
End date: 2017-05-31
Duration (months): 24.0
Total project cost (EUR): 170121.6
EU funding (EUR): 170121.6
Participants: 1
Project status: CLOSED

The thalamus is a brain structure that is responsible for important functions (e.g., sensory systems, sleep, the motor system, spoken language) which are distributed over its 12 nuclei . While recent advances in MRI technology have made it possible to image the thalamic nuclei in vivo, the lack of specific computational tools to analyze the images forces most research studies to either treat the thalamus as a single structure (limiting the spatial specificity of the analysis) or to rely on the excruciating process of manually labeling the data. Since very few sites currently possess the anatomical expertise and staffing resources to carry out studies based on manual delineations, the lack of tools to analyze MRI data of the thalamus is hampering progress in different branches of neuroscience. Here we present an interdisciplinary project to build tools to automatically analyze the thalamic nuclei in MRI data. The tools will be based on a statistical atlas of the thalamus built upon ultra-high resolution MRI and histological data from autopsy samples. We will use the tools in a study of the relation between thalamus and dyslexia, where they promise to increase our understanding of the pathology by testing which nuclei are affected and to what extent. In addition, the tools will be distributed as part of the software package FreeSurfer, allowing its over 10,000 worldwide users to carry out cognitive neuroscience experiments at the nucleus level, and to discover new imaging biomarkers of other diseases related to the thalamus, e.g. Alzheimer's, Parkinson's, MS and ALS. This project will allow the host to acquire knowledge in medical image analysis from the applicant and to establish collaborations with Harvard and Oxford (host of the proposed secondment). The project will also expand the applicant’s research network and train him in areas (ex vivo MRI, psycholinguistic studies) that complement his image analysis skills, preparing him for a future faculty position.

Keywords: thalamus,statistical atlas,dyslexia,neuroimaging
Upgrading and implementing mathematical models to increase nitrogen use efficiency of lactating dairy cows. (CowficieNcy)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Environment and Geosciences
Countries involved: Italy,Spain,Italy,Greece,Greece,Greece,Greece,United States,United Kingdom,United Kingdom,United Kingdom,United Kingdom,United Kingdom
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2017, 2017)
Start date: 2018-01-01
End date: 2023-06-30
Duration (months): 66.0
Total project cost (EUR): 1102500.0
EU funding (EUR): 994500.0
Participants: 16
Project status: SIGNED

Nitrogen (N) is an essential nutrient of food production, but its extended use led to the N cascade phenomenon with considerable effects on atmospheric, freshwater and marine systems. The increased efficiency of N use in dairy production is proposed as key action to reduce N contamination, and mathematical models provide a powerful tool to help with this. We are planning to use two models: The Cornell Net Carbohydrate and Protein System (CNCPS; a cow based model) and the Lifetime Nitrogen Efficiency (LNE; a herd based model). The models will be updated on amino acid metabolism (CNCPS), heifer growth and cattle fertility and economics (LNE) increasing not only their accuracy but also their commercial potential. In parallel, an intensive outreach program will incorporate farms in each country to describe N balance situation. This step will provide the necessary time to familiarize and accommodate farms with current model use. The last phase of the project consists on the implementation of the upgraded models in our pilot farms. This will provide a real life example that can generate a shift in agricultural practice towards more efficient and less polluting dairy industry. The European Union has been taken several initiatives either at a research level (e.g. FP-7 project RedNex) or at a legislative level (e.g. the National Emission Ceilings directive 2001/81/EC; currently under revision) to reduce N pollution from dairy production. However, few strategies have been converted into agricultural practice because of the lack of an applied step linking research strategies with the dairy industry. This is the strength of the current project that includes four non-academic partners that consult on thousands of European dairy farms and six European and American academic institutions, two of which developed the models, but all highly prestigious in their countries and internationally.

Keywords: dairy cattle nutrition,farm nitrogen use efficiency,milk nitrogen use efficiency,nutritional modeling
pioneer technology for the reduction of natural fruit sugars in 100% juices (Better Juice)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Israel
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-04-01
End date: 2019-09-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

One of current challenges in Food and Beverage industry is linked with the need to reduce natural sugars. In fact, despite initial enthusiasm for natural fruit juices, recent studies have demonstrated the natural sugars are as much harmful as added sugars do. Thus, producers are focusing on the development of affordable and efficient technologies to deliver de-sugarized products. However, to date no optimal industrial solution in this domain has been implemented. The BetterJuice technology offers something that has not been reached yet by other companies. We reduce and even eliminate natural sugars from fruit and vegetable matrix, without affecting the organoleptic skills of the product and even improving its taste. Calories reduction is achieved to at least 50%. Moreover, we are able to offer a really healthy choice for consumers because beverages produced with our technology are naturally enriched with bio-available and thus easily absorbable Calcium. The technology does not require the modification of the existing production lines and its impact on the production costs has been assessed at € 0,1 per 1 litre fruit/vegetable matrix. This low cost factor, along with the ascertained readiness of consumers to switch to healthier hydration even if on higher price, offers the opportunity to producers to create novel product lines with appealing claims and thus setting the price point that can significantly maximize their profit margins. The BetterJuice technology uses disruptive bio-conversion approach delivered through enzymatic activity of food grade microorganisms. The technology is of interest of some of world leading juice producers. Current project will enable us to collect users' requirements and thus to properly engineer the industrial prototype of the device. Furthermore, a detailed market study will be done, so to verify and validate the intended business model and commercialization strategy, as well as related certification path.

Keywords: bio conversion,de sugarization,free from products,zero sugar products,natural sugars reduction,zero glucose,products for diabetes patients,premium segment fruit juice
Closed-Loop Flow Control to Enhance Aerodynamic and Aeroacoustic Performance of Wind-Turbine Blades (Rotary Wing CLFC)

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: Germany
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-05-01
End date: 2017-10-25
Duration (months): 24.0
Total project cost (EUR): 171460.8
EU funding (EUR): 171460.8
Participants: 1
Project status: CLOSED

Aerodynamic loads and noise emitted from rotating blades are of interest in many industrial applications, such as wind-turbines, aircraft propellers, helicopter blades, and cooling fans. This research project aims to achieve, for the first time, a combined aerodynamic and aeroacoustic optimization of rotary wing by experiments conducted in a controlled environment of gusting flow and rotating motion. In the current work focus will be made on wind-turbine applications. Both passive and active flow control technologies will be utilized to enhance the amount of energy harvested from the wind, while improving the aeroacoustic properties. Leading- and trailing-edge serration have proven to be effective in reducing the noise emitted from wind-turbine blades. However, their effectiveness under realistic flow conditions in a controlled environment has not been investigated. These experiments will be used for further development and validation of new aerodynamic and aeroacoustic models. The ultimate and final goal is to apply closed-loop flow control by utilizing a physics based model. Alongside these experiments, innovative and stand-alone technology for data acquisition and control in rotating blade environments will be developed and implemented. This holistic interdisciplinary approach, bringing together the aerodynamic and aeroacoustic behaviour of wind-turbine blades under realistic flow conditions into one comprehensive study is unique and novel, and will lead to major advances in our understanding of rotating blades aerodynamics and aeroacoustics.

Keywords: aeroacoustics,closed loop flow control