Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Revolutionizing Renewable Energy Conversion: GaN-Based ANPC Converter and Advanced Predictive Control for Enhanced Efficiency (REnCon)

Framework: Horizon Europe — Widening Participation and Strengthening the European Research Area
Programme: Widening participation and spreading excellence
Theme: Attracting and mobilising the best talents
Destination: Attracting and mobilising the best talents
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Lithuania
Call: ERA Fellowships (HORIZON-WIDERA-2024-TALENTS-02, 2024)
Start date: 2025-09-01
End date: 2027-08-31
Duration (months): 24.0
Total project cost (EUR): 196976.16
EU funding (EUR): 196976.16
Participants: 1
Project status: SIGNED

The development of a cutting-edge Gallium Nitride (GaN) based Multilevel Active Neutral Point Clamped (ANPC) converter, integrated with a Model Predictive Controller (MPC), to significantly enhance the performance and efficiency of multi-energy systems. The focus of this study is to tackle critical challenges in power electronics by exploiting the superior characteristics of GaN devices, such as the unique advantages of GaN technology, which include its ability to operate at higher efficiencies compared to traditional silicon-based devices. This capability is particularly beneficial for reducing power losses and managing thermal performance, which are pivotal in the operation of high-power electronic systems. The incorporation of advanced MPC techniques will further optimize the control and operational performance of these converters. MPC's advanced control capabilities, which include real-time optimization and predictive control, will be leveraged to enhance the stability and efficiency of the ANPC converter. This will involve the development of sophisticated algorithms capable of handling the complexities associated with renewable energies such as solar and wind energy systems, ensuring optimal performance under varying operating conditions. Additionally, the improved converter systems will facilitate more effective energy distribution and management, contributing to the overall stability and efficiency of the smart grid.

Keywords: gallium nitride,anpc,mpc,renewable energy
How does Chaos drive Transport Dynamics in Porous Media ? (CHORUS)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Products and Processes Engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: France
Call: ERC STARTING GRANTS (ERC-2021-STG, 2021)
Start date: 2023-02-01
End date: 2028-01-31
Duration (months): 60.0
Total project cost (EUR): 1498929.0
EU funding (EUR): 1498929.0
Participants: 3
Project status: SIGNED

Fluid flow in porous media plays a central role in a large spectrum of geological, biological and industrial systems. Recent advances have shown that microscale chemical gradients are sustained by pore-scale chaotic flow dynamics. This fundamentally challenges the current macrodispersion paradigm that assumes that porous transport processes occurs under well-mixed microscale conditions. Using novel experimental, numerical and theoretical approaches, CHORUS will explore the origin, diversity and consequences of chaotic mixing in porous and fractured media. For this, the team will develop a new generation of imaging techniques coupling laser induced fluorescence, refractive index matching and additive manufacturing of complex and realistic porous and fractured architectures (WP1 and WP2). The CHORUS team will use these insights to develop new modelling concepts for describing scalar mixing and dispersion in microscale (WP3) and multiscale (WP4) systems. Building on these experimental, numerical and theoretical breakthroughs, CHORUS will design “smart” porous flows with porous architectures that selectively optimize mixing, dispersive or reactive properties (WP5). CHORUS will thus develop a new paradigm for transport dynamics in porous and fractured media, with far-reaching applications for the understanding, modelling and control of a range of natural and industrial processes, including contaminant transport and biogeochemical reactions in the subsurface, CO2 sequestration, membrane-less flow batteries, flow chemistry, chromatography or catalysis.

Keywords: porous media,transport,mixing,dispersion,fractured media,lagrangian chaos
Antivirus Pandemic Preparedness EuropeAn pLatform (APPEAL)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Tackling diseases and reducing disease burden
Action type: Research and Innovation actions
Countries involved: Germany,Spain,United Kingdom,France,Belgium,Netherlands,Slovakia
Call: Pandemic preparedness and response: Broad spectrum anti-viral therapeutics for infectious diseases with epidemic potential (HORIZON-HLTH-2023-DISEASE-03, 2023)
Start date: 2024-01-01
End date: 2028-12-31
Duration (months): 60.0
Total project cost (EUR): 7565673.75
EU funding (EUR): 7565673.75
Participants: 14
Project status: SIGNED

Developing new antiviral treatment against viruses and particularly high-priority emerging and re-emerging viruses as listed by the WHO, remains crucial as, among other aspects, the viruses evolve under selection. Broad spectrum host-directed antiviral drugs (HDA) are promising therapeutic options, however the robust identification of relevant host factors by genome-wide knockout screens is challenging due to low consistency in the resulting hits. Our project aims to (1) establish a computational and experimental pipeline to identify and validate an antiviral for these viruses, and (2) identify at least one broad spectrum antiviral drug against potential emerging and re-emerging viruses as listed by the WHO. To address these, we will implement a drug selection pipeline following several strategies: We will employ (i) machine learning, based on data from knockout screens, proteomics, protein interaction, transcriptomics of infected cells with pandemic-related viruses, Genome-Wide Association Studies, and generic gene descriptors, (ii) High Density Cell Arrays, which provide much more detailed readouts compared to state of the art pooled knockout screens, (iii) primary cell cultures obtained from a diverse array of human tissues, as they are more appropriate to study the host cell physiology during infection, compared to cancer cell lines, and (iv) use the pipeline to identify host restriction factors, which, when activated, challenge the virus; followed by innovative drug development and delivery based on small activating RNA. The pipeline comprises an Expedited Arm for which broad spectrum antiviral drugs for repurposing will be selected followed by in vitro and in vivo efficacy testing, and a clinical trial as a proof of concept. The elaborated Arm includes all strategies (i)-(iv) and will provide a sustainable pandemic preparedness pipeline ready-to-operate to identify the appropriate treatment against the emerging virus at the early time of a new outbreak.

Keywords: novel platform for developing broad spectrum antivirals bsa,machine learning,host dependency factor,host restriction factor,cell arrays,crispr cas9 screening
A revolution in the understanding of the mercury-selenium interaction in biota (SeMER)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Earth System Science
Panel description: Physical geography, geo logy, geophysics, atmospheric sciences, oceanography, climatology, cryology, ecology, global environmental change, biogeochemical cycles, natural resources management
Countries involved: France
Call: ERC CONSOLIDATOR GRANTS (ERC-2024-COG, 2024)
Start date: 2025-10-01
End date: 2030-09-30
Duration (months): 60.0
Total project cost (EUR): 2000000.0
EU funding (EUR): 2000000.0
Participants: 2
Project status: SIGNED

Mercury (Hg) pollution is a major environmental problem. Due to its extreme toxicity, Hg has recently been included in the top ten chemicals of major public health concern by the World Health Organization. Once released in the environment, it can be transformed, principally by aquatic microorganisms, into methylmercury. Methylmercury’s hazardous effects are biomagnified through food webs, resulting in negative health effects. However, Hg metabolic pathways in biota remain poorly understood. Therefore understanding these complex processes is crucial to elucidate potential (eco)toxic effects as well as factors governing Hg biogeochemical cycling. Hg binding with proteins has been evoked as a cause for toxicity and the role of selenium (Se) as antagonist for Hg toxicity is acknowledged but thus far not well understood. SeMER is an ambitious and multidisciplinary research project with a main objective to revolutionize the understanding of Hg metabolic pathways in living organisms in the context of (antagonist) interactions with Se. The project is based on the development of novel analytical approaches that combine speciation and natural isotopic fractionation in a unique pattern. Speciation provides valuable information about reactivity and potential toxicity of metabolites. Furthermore, the natural abundance isotopic signatures add a dynamic dimension, comprising the life history of target elements, pollution sources, and reaction tracking. The resulting (bio)molecular and isotopic signatures will provide valuable insights of Hg in biota and potential detoxification mechanisms. Developed methodologies will be assessed in both freshwater and marine ecosystems in order to characterize important differences in Hg:Se interactions across contrasting habitat types. SeMER concept will revolutionize the sources and tracing of Hg and its metabolites, that could be extended to other metals and push back frontiers in life and environmental sciences related to them.

Keywords: environmental chemistry,mercury,selenium,pollutants,speciation,isotopic fractionation,
Quantum-secure multi-party deep learning (QSDL)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Israel,United States
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2025-06-01
End date: 2028-05-31
Duration (months): 36.0
Total project cost (EUR): 415823.64
EU funding (EUR): 415823.64
Participants: 2
Project status: SIGNED

Deep Neural Networks (DNNs) have sparked a revolution across multiple domains. However, the escalating computational demands of advanced DNNs have led to the need for high-power consumption accelerators, which hinders their deployment on low-power devices. To enable advanced DNNs on such devices, the industry has resorted to offloading computationally intensive DNN inference to cloud servers. Nevertheless, this offloading architecture introduces vulnerabilities that compromise data security, presenting a pressing challenge, particularly in AI applications where data privacy is essential. In response, I propose a pioneering approach that harnesses the quantum nature of light to establish a practical paradigm for information-theoretically secure deep learning, where clients safeguard their sensitive data, and servers protect their proprietary AI models. This project delves into information science, aiming to explore theoretically and experimentally whether quantum science can offer practical advantages in privacy-preserving inner products against limited adversaries. The innovative essence of this proposal lies in the demonstration of quantum private deep learning in Prof. Englund's lab at MIT, utilizing an optical network. The experimental validation of the protocol with real-life healthcare devices in collaboration with Prof. Katz (HUJI) will unlock a new era of machine learning applications, including the secure utilization of AI in healthcare (e.g., IBM's Watson, Aidoc’s aiOS) and AI assistance (e.g., ChatGPT, Bard). This work may also reshape regulations like the EU General Data Protection Regulation.

Keywords: quantum cryptography,optical communication,secure computation,deep learning
Tracing human cortical neurons involved in epileptic processes at multiple scales (EpiNeuron)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: France
Call: MSCA Postdoctoral Fellowships 2022 (HORIZON-MSCA-2022-PF-01, 2022)
Start date: 2023-09-01
End date: 2025-08-31
Duration (months): 24.0
Total project cost (EUR): 195914.88
EU funding (EUR): 195914.88
Participants: 1
Project status: SIGNED

Epilepsy is one of the most common chronic neurological diseases in humans, affecting 50 million people worldwide. This brain disorder is characterised by hypersynchronous neural activity resulting in seizures. Abnormal recruitment of cells induces unusual behaviour, sensations or loss of awareness. Epilepsy has a substantial economic effect on health care needs or the loss of productivity in work. Investigating the role of different neuron types in generating pathological activities is essential for identifying what makes a brain region predisposed to generate epileptic events. Most information regarding the properties of neuronal circuits during epileptic activity comes from animal models. However, recent studies have shown substantial differences when comparing human tissue to animals and epilepsy models to disease. I aim to utilise a unique multilevel approach to follow how neurons are recruited into epileptic events and categorise them at an unprecedented level of detail in human epileptic patients. I plan to analyse cellular activity in recordings obtained in vivo and characterise human cortical neurons in vitro with simultaneous intra- and extracellular electrophysiology completed with post hoc histology. This will be the first study examining neuronal behaviour and subtypes in the same epileptic patients, both in vivo (before surgery) and in vitro (after surgery). This innovative approach will provide valuable information on the role of the different neuron types in the generation of epileptiform activity. The fundamental knowledge of the cellular mechanisms of epileptic events specific to humans could help us understand the human disease deeply and thus achieve a significant breakthrough in epilepsy treatment. Enhancement in the diagnostics and cure of epilepsy would considerably decrease the cost of medical care and promise an invaluable improvement in the quality of life on the individual level.

Keywords: epilepsy,human,neocortex,hippocampus,seizure,single unit,pyramidal cell,interneuron
Connected and Adaptive Maintenance for Safer Urban and Secondary Roads (CAMBER)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Mobility
Destination: Safe, Resilient Transport and Smart Mobility services for passengers and goods
Action type: Research and Innovation actions
Countries involved: Slovenia,Belgium,Greece,Spain,United Kingdom,Netherlands,Portugal,Austria,Croatia
Call: Better infrastructure safety on urban and secondary rural roads throughout a combination of adaptable monitoring and maintenance solutions (HORIZON-CL5-2023-D6-01, 2023)
Start date: 2025-01-01
End date: 2027-12-31
Duration (months): 36.0
Total project cost (EUR): 3952195.5
EU funding (EUR): 3952195.5
Participants: 14
Project status: SIGNED

The Connected and Adaptive Maintenance for Safer Urban and Secondary Roads project (‘CAMBER’) aims to develop and demonstrate improved safety monitoring across urban and secondary rural road networks through real-time data feedback into road maintenance systems and proven low-cost interventions. Performance metrics based on new-generation data sources will provide road managers up-to-date information on safety issues, damage, and routine maintenance and upgrade needs. Data collated from a range of sources, such as telematics, vehicle and smartphone sensors, and road user feedback, will feed into safety assessment models to flag what measures are required to ensure a safe road environment for all road users, including road-user minority groups with varying design needs, such as powered two-wheelers (PTW). CAMBER will support this through much-need research and testing of low-cost road safety interventions and low-impact maintenance techniques, including those for vehicles with advanced driver-assistance systems (ADAS). The approaches will be demonstrated on urban and road networks in five European countries. CAMBER’s economically-sound solutions and new knowledge will be communicated through established networks to European road managers, policymakers and industry to support the decision-making and investment needed for more efficient maintenance for safer urban and secondary roads.

Keywords: road safety,asset management,digital twins,vehicle probe data,real time data,secondary roads,urban roads,low cost safety treatment,ccam,adas,vru,its,telematics,road maintenance,ptw
Breast self-reconstruction: The Promise of Breast Reconstruction with patients’ own tissue (MATTISSE)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Open to supporting projects in all areas of science, technology,...
Action type: EIC actions
Countries involved: France
Call: EIC Accelerator Open 2021 (HORIZON-EIC-2021-ACCELERATOROPEN-01, 2021)
Start date: 2022-10-01
End date: 2024-09-30
Duration (months): 24.0
Total project cost (EUR): 3483555.0
EU funding (EUR): 2438488.0
Participants: 1
Project status: CLOSED

LATTICE MEDICAL develops MATTISSE, a fully degradable 3D printed breast implant allowing a natural and custom breast reconstruction in a single and simple surgery. MATTISSE technology uses a Tissue Engineering Chamber implanted in the former breast and made of 3D printed biocompatible and bioabsorbable polymer. MATTISSE regenerates autologous adipose tissue within 3-6 months, women recover a full breast in 18 months with a fully degraded implant at an affordable price and free from numerous surgical procedures. There is no longer any risk related to silicone implants thanks to the complete recovery with natural tissue. After validating the effectiveness of the MATTISSE medical device on animal models, this project aims at performing the mandatory clinical studies to launch the product on the EU market with the CE mark. A commercial team will be recruited to define and implement a marketing plan to ensure the success of MATTISSE. Lattice Medical plans to support 40000 women by 2030.

Keywords: reconstruction,bioprosthesis,patient care,medical devices
Symmetry and Similarity (SymSim)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Computer Science and Informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Germany
Call: ERC ADVANCED GRANTS (ERC-2021-ADG, 2021)
Start date: 2022-10-01
End date: 2027-09-30
Duration (months): 60.0
Total project cost (EUR): 2495575.0
EU funding (EUR): 2495575.0
Participants: 1
Project status: SIGNED

The goal of this project is to develop an algorithmic theory of similarity between graphs. Graphs are versatile models for representing complex data ranging from chemical molecules to social interactions. Dealing with graphical data and enabling modern data analysis techniques, a fundamental task is to compare graphs and to measure their similarity, preferably in a semantically meaningful and algorithmically efficient way. However, it is not clear at all how to achieve this. In many application areas, for example, computer vision, database systems, and formal verification, researchers have proposed (often ad-hoc) solutions to this problem tailored for the specific application, but a general theory is missing. We will develop such a theory in this project. Similarity of graphs has many different facets. We will identify the common core of different approaches to similarity, but also exhibit their differences. We will design methods for comparing different similarity measures and for obtaining a semantic understanding of similarity. We will develop criteria for the suitability of various similarity measures for different types of applications. A particular focus of our research will be on efficient algorithms for computing similarity. There is little use in having a perfect similarity measure if we have no efficient way of determining how similar two graphs are. A classic algorithmic problem in this context is the graph isomorphism problem of deciding whether two graphs are structurally identical. Determining the precise computational complexity of this problem, or of the equivalent problem of computing all symmetries of a graph, is regarded to be one of the most important open questions in theoretical computer science. Building on recent progress, we will design new algorithms breaking barriers towards a polynomial-time algorithm for the isomorphism problem.

Keywords: graph similarity,graph isomorphism,vector embedding,constraint satisfaction,homomorphism counting
NaV1.5 regulation fine-tuning as a therapy for cardiac Conduction and Arrhythmic diseases at Risk of suddEn Death (NaV1.5-CARED)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Pathfinder
Destination: Challenges
Action type: EIC actions
Countries involved: France,Netherlands,Germany,Czechia
Call: EIC Pathfinder Challenge: Cardiogenomics (HORIZON-EIC-2022-PATHFINDERCHALLENGES-01, 2022)
Start date: 2023-10-01
End date: 2028-09-30
Duration (months): 60.0
Total project cost (EUR): 4892256.25
EU funding (EUR): 4892256.25
Participants: 9
Project status: SIGNED

The voltage-gated sodium channel (Na-channel; NaV1.5) is a central component of cardiac electrogenesis. Its dysfunction can lead to ventricular fibrillation and sudden cardiac death. While NaV1.5 represents a highly relevant therapeutic target for prevention of life-threatening cardiac arrhythmias, therapies that target the expression or function of this channel are non-existent. Such a therapy would provide for the first time an alternative for the invasive and costly cardioverter defibrillator or pacemaker therapies currently used. NaV1.5-CARED consortium proposes to capitalize on their largest worldwide cohorts of patients with inherited cardiac electrical and conduction defects to uncover regulatory regions and proteins that modulate NaV1.5 expression and function with the goal to develop and validate innovative therapies to restore the function of NaV1.5. We have three objectives: 1) predict the risk of (fatal) arrhythmia and conduction defect at the individual level by developing personalized polygenic risk score (PRS), 2) characterize the molecular mechanism associating regulatory DNA regions and genes with the cardiac diseases to uncover new therapeutic targets, 3) and develop new candidates for therapeutic intervention able to restore Nav1.5 loss of function. After databases harmonization, we will conduct whole genome genetic studies to identify variants associated with ventricular arrhythmia and conduction defects and generate PRS relevant to stratify the risk of arrhythmia and degree of conduction defect. Genetic studies will also be used to identify new therapeutic that will be evaluated in dedicated and high-throughput human cardiomyocytes derived induced pluripotent cell models.

Keywords: brugada syndrome,conduction defects,human genetics,risk score,ipsc cm,regulatory region,gene therapy