Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Presidency event - Belgium. R&I policies for Better Health, Wellbeing and Prosperity : Policy for Research and InnOvation for better HEALTH (PRIOHealth)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Other health destinations
Action type: Coordination and support actions
Countries involved: Belgium
Call: Presidency event - Belgium. R&I policies for Better Health, Wellbeing and Prosperity (HORIZON-HLTH-2024-PBEL-12-IBA, 2024)
Start date: 2024-03-01
End date: 2025-02-28
Duration (months): 12.0
Total project cost (EUR): 491850.0
EU funding (EUR): 300000.0
Participants: 1
Project status: SIGNED

Europe is confronted with a multitude of health challenges for which strong research and innovation efforts may bring solutions. The strategies and policies governing R&I, however, need to be harmonized across different levels (EU, national, regional) and transcend geographical boundaries to defragment European research efforts. The need for European cross-border alignment of R&I efforts became particularly obvious during the COVID pandemic. Although there is an immense potential throughout Europe to become the preferred global hub to conduct clinical studies and trials, Europe largely failed to secure this potential. Besides the imminent urgency to provide a response in case of a pandemic, aligning R&I strategies and policies isalso crucial to develop healthcare of the future, which will be personalised and preventive, building on the convergence of cutting-edge technologies, such as bio-, nano-, digital technologies and engineering and integration of several types of data, including genomic data, health data, and real-world data. The transformative potential of such convergence, however, is frequently hindered by the challenge of translating scientific knowledge into practical innovations and effectively incorporating these innovations into healthcare systems as well as the lack of standardisation and harmonisation. The European partnerships and access to high-end research infrastructures play a pivotal role in addressing the fragmentation of European R&I efforts and realising the ultimate goals and ambitions of establishing Europe as a lead region in the world providing R&I-based answers to complex health challenges.

Keywords: pandemic preparedness,one health,european partnerships for health
BatterBattery Passport for Resilient Supply Chain and Implementation of Circular Economyy Passport for Resilient Supply Chain and Implementation of Circular Economy (BASE)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Energy
Destination: Cross-sectoral solutions for the climate transition
Action type: Innovation actions
Partnership: Batteries (co-programmed)
Countries involved: Germany,Spain,Lithuania,Belgium,Ireland,Congo, The Democratic Republic of the,Türkiye,Switzerland,Chile,United Kingdom,Netherlands,Norway
Call: Creating a digital passport to track battery materials, optimize battery performance and life, validate recycling, and promote a new business model based on data sharing (Batt4EU Partnership) (HORIZON-CL5-2023-D2-02, 2023)
Start date: 2024-06-01
End date: 2027-05-31
Duration (months): 36.0
Total project cost (EUR): 8944585.0
EU funding (EUR): 6154314.0
Participants: 19
Project status: SIGNED

The battery, although central to the green transition of road transport, currently suffers from a supply chain that lacks traceability, sustainability, resiliency, and circularity. Critical Raw Materials (CRMs) are essential for battery manufacturing. The explosive growth of electric vehicles, driven by climate neutrality policy objectives, will pressure the CRM supply chain and increase EU dependency on third countries, resulting in decreased competitiveness for EU automotive and battery manufacturers. Implementing the digital battery passport (DBP) concept in the battery value chain could resolve these issues. The main goal of the BASE project is to develop, validate, and implement a working DBP service, as mandated by the “Regulation.” This will be achieved by exploiting data collected through a number of constantly evolving tools and methods, ensuring a transparent, secure, and cost-efficient platform operation, while also catalyzing the growth of circular businesses. BASE will develop transparent methodologies to calculate battery performance and ESGE indicators, ensuring traceability down to the CRM level throughout the entire battery value chain. In the physical domain, this will be achieved through the mass balancing approach. On the data management side, by exploiting distributed ledger technology, BASE will ensure built-in data authenticity verification along the value chain, with no data duplication, avoiding data manipulation, assuring privacy by design, and promoting data interoperability. The DBP will provide up-to-date and accurate data on battery performance indicators, remaining useful life, dismantling, material composition, and safety. This will allow for an increase in the useful service life of batteries and more efficient recycling, which will enhance resource efficiency, reduce waste, and decrease EU dependency on CRMs from third countries. The applicability of the DBP will be demonstrated through four pilot use cases.

Keywords: dlt,dbp,circularity,4r
Future Oriented Renewable and Reliable Energy SIC Solutions (FOR2ENSICS)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Energy
Destination: Sustainable, secure and competitive energy supply
Action type: Innovation actions
Countries involved: Spain,Sweden,Switzerland,France,Germany,United Kingdom
Call: Demonstration of advanced Power Electronics for application in the energy sector (HORIZON-CL5-2021-D3-02, 2021)
Start date: 2023-01-01
End date: 2026-12-31
Duration (months): 48.0
Total project cost (EUR): 5533910.0
EU funding (EUR): 4393517.5
Participants: 8
Project status: SIGNED

Driven by the continued effort to combat the climate change and achieve carbon neutrality, the composition of the energy sources and consumers connected to the electrical grid is rapidly changing. An increasing amount of issues are being experienced by distribution system operators while trying to accommodate new systems like renewable energy sources or electric vehicles charging infrastructure. One of the possible solutions is to develop a DC distribution infrastructure, which is especially interesting as most of the new connections mentioned above are native DC sources and loads, respectively. This requires low cost, very efficient and compact DC/DC converters from LV (<1500V) up to MV (>10kV). However, currently no commercial solutions exist on the market. The aim of this project is to develop and demonstrate a commercial DC/DC converter prototype which can be introduced to the market within short timescale (<3 years) after completion of the project. To achieve such an ambitious target, the project team has decided to focus on the development of ultra- high voltage (UHV) SiC based switching devices which would allow for a remarkable simplification of the converter topology as well as a very compact design when coupled with high frequency operation. For this purpose, the project aims at the design, fabrication and testing of 15 kV SiC IGBTs modules. The choice of the device technology is based on previous studies, which point towards a break-even voltage between SiC MOSFET and SiC IGBT just above 10 kV. Highly relevant, both cost and environmental impact reduction of the fabrication processes will be targeted, using novel approaches for material growth and semiconductor processing. At the same time, another major target of the project is to understand reliability issues affecting different converter components such as UHV switching devices, passive components, and medium frequency transformer associated with high switching frequency and high voltage environment.

Keywords: silicon carbide,igbt,reliability,mvdc,dc dc converter
SArkisov Program in HIgher Dimension, over Imperfect fields and for birRegulous maps (Saphidir)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: France
Call: ERC STARTING GRANTS (ERC-2022-STG, 2022)
Start date: 2023-01-01
End date: 2027-12-31
Duration (months): 60.0
Total project cost (EUR): 1485725.0
EU funding (EUR): 1485725.0
Participants: 1
Project status: CLOSED

A fundamental goal of Algebraic Geometry is to classify algebraic varieties up to isomorphism. This is extremely hard, already for surfaces, and open in general. It has become clear that we can only hope for a classification up to birational maps, that is, isomorphisms between dense open sets. Understanding birational maps is therefore a key step towards the classification of algebraic varieties. For one of the largest families of algebraic varieties, so-called Mori fibre spaces, any birational map between any two of them is composed of special birational maps called Sarkisov links. For surfaces over nice fields, Sarkisov links are well-understood, but little is known about them in dimension three or higher, over any field. The understanding of Sarkisov links will mean an enormous advance in the study of birational maps and a substantial leap towards a classification of a large family of algebraic varieties. The very ambitious aim of this project is to describe all Sarkisov links completely in any dimension and in several non-classical settings in terms of base-locus, contracted hypersurfaces and induced rational map on the bases of the implicated Mori fibre spaces. If achieved, it will revolutionize the study of birational maps and provide new exciting tools to determine classes of algebraic varieties in several settings. In dimension three and higher, already the classification of Sarkisov links over the field of complex numbers is extremely ambitious. Another very difficult task is to classify Sarkisov links over a field of positive characteristic, as the geometry of algebraic varieties over such fields is even more challenging than it is over the field of complex numbers. The Minimal Model program, a major active research area in Biratonal Geometry, has made tremendous advances in the last decades. Recently developed ideas and techniques allow the attack on birational maps between algebraic varieties by studying Sarkisov links.

Keywords: birational geometry sarkisov programm algebraic geometry over non closed fields
Georgian Artificial Intelligence Networking and Twinning Initiative (GAIN)

Framework: Horizon Europe — Widening Participation and Strengthening the European Research Area
Programme: Widening participation and spreading excellence
Theme: Improved access to Excellence
Destination: Improved access to Excellence
Action type: Coordination and support actions
Countries involved: Georgia,Germany,France
Call: Twinning (HORIZON-WIDERA-2021-ACCESS-03, 2021)
Start date: 2022-10-01
End date: 2025-09-30
Duration (months): 36.0
Total project cost (EUR): 1319250.0
EU funding (EUR): 1319250.0
Participants: 4
Project status: SIGNED

GAIN will take a strategic step towards integrating Georgia, one of the Widening countries, into the system of European efforts aimed at ensuring the Europe’s leadership in one of the most transformative technologies of today and tomorrow – Artificial Intelligence (AI). It will be achieved by research profile adjusting and linking the central Georgian ICT research institute - Muskhelishvili Institute of Computational Mathematics (MICM), to the European AI research and innovation community. Two absolutely leading European research organizations (DFKI and INRIA) supported by the high-tech company EXOLAUNCH will support MICM in this endeavour. The Strategic Research and Innovation Programme (SRIP) designed by the partnership will provide the environment for the Georgian colleagues to get involved in the research projects of the European partners addressing a clearly delineated set of AI topics. Jointly, the partners will advance in capacity building and networking within the area of AI Methods and Tools for Human Activities Recognition and Evaluation, which also will contribute to strengthening core competences in such fundamental technologies as e.g. Machine (Deep) Learning. The results of the cooperation presented through the series of scientific publications and events will inform the European AI community about the potential of MICM and trigger new partnerships building, addressing e.g. Horizon Europe. The project will contribute to career development of a cohort of young researchers at MICM through joint supervision and targeted capacity building measures. Innovation and Research Administration and Management capacities of MICM will also be strengthen to allow the Institute to be better connected to the local, regional and European innovation activities. Using their extensive research and innovation networking capacities DFKI and INRIA will introduce MICM to the European AI research community by connecting to such networks as CLAIRE, ELLIS, ADRA, AI NoEs, etc.

Keywords: human activities recognition
Shaping the bacterial envelope: Interplay between the components and impact on antibiotic resistance (Shape-En-Resist)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Immunity, Infection and I mmunotherapy
Panel description: The immune system , related disorders  and their mechanisms , biology of infectious agents and infection, biological basis of prevention and treatment of infectious diseases , innovative imm unological tools and approaches , including  therapies
Countries involved: Israel
Call: ERC STARTING GRANTS (ERC-2024-STG, 2024)
Start date: 2025-01-01
End date: 2029-12-31
Duration (months): 60.0
Total project cost (EUR): 1499894.0
EU funding (EUR): 1499894.0
Participants: 1
Project status: SIGNED

Gram-negative bacteria are notoriously resilient, dominating the list of pathogens requiring urgent medical attention. Fundamental to their remarkable antibiotic resistance is a tripartite envelope comprised of an inner-membrane (IM), peptidoglycan cell wall (PG) and an outer membrane (OM). While these layers were previously viewed as separate compartments, it is becoming apparent that they work together in order to maintain envelope integrity. However, little is known about the crosstalk between components and molecular mechanisms orchestrating envelope assembly and functionality. Our latest work has identified a key interaction between the PG and the BAM complex which inserts new OM proteins (OMPs), revealing a mechanism coordinating PG and OMP biogenesis and directing them both to the cell center. We posit that coordination is a key principle of envelope assembly and multiple interactions among envelope constituents are waiting to be discovered. In Shape-En-Resist we will uncover novel physical and genetic interactions, identify coordination mechanisms and elucidate their impact on bacterial physiology and antibiotic resistance. To this end, we will focus on three aims: (i) Explore the assembly of lipopolysaccharide (LPS), an endotoxin covering the bacterial surface, and characterize its interplay with envelope biogenesis. (ii) Comprehensively map PG-OMPs interactions and study how they affect bacterial response to antibiotics. (iii) Uncover the outcomes of spatially heterogenous envelope biogenesis and whether this process is a source of phenotypic diversity. To address these questions, a multidisciplinary approach will be taken, combining cutting-edge microscopy, advanced genetic screens, proteomics and novel functionality assays. We expect this project to uncover the interaction network amongst envelope components, reveal how it impacts the physiology of both single cells and bacterial populations, and ultimately expose the secrets of bacterial resilience.

Keywords: gram negative bacteria,bacterial envelope,envelope biogenesis,outer membrane,lps,peptidoglycan,phenotypic diversity
Store Electricity and Heat foR climatE Neutral Europe (SEHRENE)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Energy
Destination: Sustainable, secure and competitive energy supply
Action type: Research and Innovation actions
Countries involved: France,Belgium,Italy,United Kingdom,Spain,Türkiye,Portugal
Call: Development of novel long-term electricity storage technologies (HORIZON-CL5-2023-D3-01, 2023)
Start date: 2024-01-01
End date: 2027-06-30
Duration (months): 42.0
Total project cost (EUR): 3548416.75
EU funding (EUR): 3548416.75
Participants: 11
Project status: SIGNED

SEHRENE’s new electrothermal energy storage (ETES) concept is designed to store renewable electricity (RE) and heat and to restitute it as needed. It is very energy-efficient (80-85%), is geographically independant and uses no critical raw materials. It enables 8-12 times longer storage duration than Li-ion, with LCOS of 80 – 137 €/MWh, depending on the use-case. This is lower than pumped hydro, the lowest-cost commercial electricity storage. Its lifetime of 20-30 years is 2 – 3x longer than Li-ion. A TRL4 prototype and the digital twins of 3 full use-cases will be delivered: (i) ceramics plant storing excess, on-site PV power in a micro-grid and industrial waste-heat for continuous green H2 production and self-consumption, (ii) a smart-grid, and (iii) a geothermal power plant. The ETES integrates: (i) a novel heat-pump design with a coefficient of performance of 50% the theoretical maximum, (ii) a novel thermal energy storage system with energy density of 90 kWh/m3 (+30%), containing phase-change material in a novel metallic Kelvin cells-like foam and (iii) ORC with novel operating parameters. New digital tools will optimise the energy management of the storage and facilitate investment decisions by potential end-users taking LCA and technico-economic factors into account. SEHRENE unites 5 R&D teams with top-level expertise in prototyping, physics-based modelling, characterisation and digital twins of thermo-electric systems, thermal storage and AI-based energy-management; 1 RE producer, 1 DSO, 1 ceramics company, 1 SME developing decision-support tools, and 1 SME for dissemination and communication. The exploitation plan aims to implement the solution in the first factory in 2029. SEHRENE’s market penetration will enable to capture 1% of the market by 2040 avoiding 90Mm3 of NG and 15Mt CO2/year. R&D and industrial partners project to generate 5.8M€ in revenues by 2035 from sales of heat pumps, thermal storage, ORC, licenses to R&D results and consulting services.

Keywords: thermal storage,thermoelectric storage,heat pump,kelvin foam,lattice structure,power to x,digital twin,ems,decision support,lca,technico economic analysis,corrosion,phase change material
Provable Scalability for high-dimensional Bayesian Learning (PrSc-HDBayLe)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: Italy
Call: ERC STARTING GRANTS (ERC-2022-STG, 2022)
Start date: 2023-05-01
End date: 2028-04-30
Duration (months): 60.0
Total project cost (EUR): 1488673.0
EU funding (EUR): 1488673.0
Participants: 1
Project status: SIGNED

As the scale and complexity of available data increase, developing rigorous understanding of the computational properties of statistical procedures has become a key scientific priority of our century. In line with such priority, this project develops a mathematical theory of computational scalability for Bayesian learning methods, with a focus on extremely popular high-dimensional and hierarchical models. Unlike most recent literature, we will integrate computational and statistical aspects in the analysis of Bayesian learning algorithms, providing novel insight into the interaction between commonly used model structures and fitting algorithms. Key methodological breakthroughs will include a novel connection between computational algorithms for hierarchical models and random walks on the associated graphical models; the use of statistical asymptotics to derive computational scalability statements; and novel understanding of the computational implications of model misspecification and data heterogeneity. We will derive a broad collection of results for popular Bayesian computation algorithms, especially Markov chain Monte Carlo ones, in a variety of modeling frameworks, such as random-effect, shrinkage, hierarchical and nonparametric ones. These are routinely used for various statistical tasks, such as multilevel regression, factor analysis and variable selection in various disciplines ranging from political science to genomics. Our theoretical results will have direct implications on the design of novel and more scalable computational schemes, as well as on the optimization of existing ones. Focus will be given to develop algorithms with provably linear overall cost both in the number of datapoints and unknown parameters. The above contributions will dramatically reduce the gap between theory and practice in Bayesian computation and allow to fully benefit of the huge potential of the Bayesian paradigm.

Keywords: bayesian computation,markov chain monte carlo,hierarchical models