Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
BEhavioural ReplicaTion of Human drivers for CCAM (BERTHA)

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
Partnership: CCAM (co-programmed)
Countries involved: Spain,France,Germany,Portugal,Austria,Sweden
Call: Human behavioural model to assess the performance of CCAM solutions compared to human driven vehicles (CCAM Partnership) (HORIZON-CL5-2022-D6-01, 2022)
Start date: 2023-11-01
End date: 2026-10-31
Duration (months): 36.0
Total project cost (EUR): 7981796.25
EU funding (EUR): 7981796.25
Participants: 17
Project status: SIGNED

Europe must seize the opportunities presented by connected, cooperative, and automated mobility (CCAM). For its deployment, powerful tools enabling the design and analysis of CCAM components, digitally and with a common language between TIERs an OEMs are needed. The lack of a validated - and scientifically based - Driver Behavioural Model (DBM) to cover the aspects of human driving performance is one of the main shortcomings of CCAM development. It allows to understand and test the interaction of CCAM with other cars in a safer and predictable way from a human perspective. DBM is the cornerstone for the development of CCAM components. It will guarantee its digital validation and, if incorporated in the ECUs software, will generate a more human-like response of autonomous vehicles (at any level) and increase its acceptance. The main objective of BERTHA is to develop a scalable and probabilistic DBM based mostly on Bayesian Belief Network (BBN). The DBM will be implemented on an open-source, HUB (repository) to validate technological and practical feasibility of the solution with industry and become a unique approach for the model worldwide scalability. The resulting DBM will be translated into a simulating platform, CARLA, using diverse demos which allows building new driving models in the platform. BERTHA will also include a methodology which, due to the HUB, will share the model to the scientific community to ease its growth. The project includes a set of interrelated demonstrators to show this DBM approach as a reference to design human-like, easily predictable and acceptable behaviour of automated driving functions in mixed traffic scenarios. BERTHA is expected to go from a TRL 2 a TRL 4. The requested EU contribution is €7,981,801. The consortium, 14 entities from 6 countries, including South Korea, deem this Project as vitally relevant to the CCAM industry due to its impact for safer and more human-like CAVs and its market and societal adoption.

Keywords: connected,cooperative,and automated mobility,connected and autonomous vehicles,driver behavioural model,human autonomous vehicle,bayesian belief network,advanced driver assistance systems
Solving differential equations fast, precisely, and reliably (ODELIX)

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: France
Call: ERC ADVANCED GRANTS (ERC-2023-ADG, 2023)
Start date: 2024-10-01
End date: 2029-09-30
Duration (months): 60.0
Total project cost (EUR): 2396711.0
EU funding (EUR): 2396711.0
Participants: 1
Project status: SIGNED

Being a language of nature, differential equations are ubiquitous in science and technology. Solving them is a fundamental computational task with a long and rich history. Applications usually require approximate solutions, which can be computed using numerical methods such as Runge-Kutta schemes. Alternatively, one may search for symbolic solutions, which have the advantage of presenting the solutions in an exact and more intelligible way. However, such solutions do not always exist and may be hard to compute. The present proposal aims at making the resolution of differential equations both faster and more reliable. We will undertake a systematic analysis of the cost to compute both numeric and symbolic solutions, as a function of the required precision, special properties of the equation and its solutions, and hardware specifics of the computer. This includes the cost to certify approximate numeric solutions, e.g. through the computation of provable error bounds. In order to compute symbolic solutions more efficiently, we will develop a new theory that relies on two techniques from computer algebra that were improved significantly in the past decade: numerical homotopy continuation and sparse interpolation. Theoretical progress on the above problems will be accompanied by open source implementations. For this purpose, we will also implement several high performance libraries of independent interest: non-conventional medium precision arithmetic, reliable homotopy continuation, sparse interpolation, faster-than-just-in-time compilation, etc. Altogether, these implementations will validate the correctness and efficiency of our approach. They should also allow us to tackle problems from applications that are currently out of reach.

Keywords: ordinary differential equations,numerical methods,multiple precision arithmetic,homotopy continuation,sparse interpolation,high performance computing,asymptotic differential algebra
Point-of-Care Devices for Urgent Care Triage (POC4TRIAGE)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Unlocking the full potential of new tools, technologies and digital solutions for a healthy society
Action type: Innovation actions
Countries involved: Finland,Austria,Israel,Spain,Türkiye,Italy,Germany,France,Belgium,Netherlands,Sweden
Call: Harnessing the potential of real-time data analysis and secure Point-of-Care computing for the benefit of person-centred health and care delivery (HORIZON-HLTH-2023-TOOL-05, 2023)
Start date: 2024-07-01
End date: 2028-06-30
Duration (months): 48.0
Total project cost (EUR): 10592908.75
EU funding (EUR): 9442595.13
Participants: 18
Project status: SIGNED

Cardiorespiratory diseases and stroke are among the top four leading causes of death in the EU in prehospital settings. Urgent care services are in huge need of novel Point of care (POC) computing technologies that can specifically detect patient condition and enable Hospital information system (HIS) with real-time data for triaging patients for right care. Our goal in POC4TRIAGE is to develop robust and accurate POC technologies, from POC testing (devices) to POC systems (platform) that is capable of fast diagnosis and efficient transfer of data to HIS. We will develop and clinically validate four rapid (<10 min) easy-to-use, compact, cost- and energy-efficient POC devices with Edge AI computing models, to be used in ambulance & emergency room settings. POC4TRIAGE devices include a multimodal patch for real-time monitoring of cardiorespiratory data, novel sub-hairline non-invasive EEG based head caps for rapid stroke diagnosis, including detection of large vessel occlusion stroke, and a handheld, rapid immunodetector to diagnose stroke with clinical utility for various conditions. These devices integrate into a new Device Hospital Connectivity Platform (DHCP) that visualizes data, uses AI from multiple devices to triage and seamlessly integrates with hospital systems and clinical workflows. The POC devices and DHCP will be clinically validated. POC4TRIAGE brings together some of Europe's leading POC device developers, medical professionals and clinicians, patient representatives, ethics experts, data scientists, and health economists. POC4TRIAGE will shorten the time to treatment and improve clinical outcome. POC4TRIAGE has potential to revolutionize healthcare delivery, making it more accessible and efficient, traceable, and interpretable for patients and providers alike. As the POC device and computation market is growing fast, the new POC devices, real-time data analysis, and secure computing have potential for major economic impact.

Keywords: point of care technologies,urgent care triaging,edgeai,stroke eeg triaging,cardiorespiratory devices,poc platform,electrolateral flow device,signal processing,machine learning,imaging devices
For trustful, participatory and inclusive public policies (INVOLVE)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Culture, creativity and inclusive society
Theme: Culture, creativity and inclusive society
Destination: Innovative Research on Democracy and Governance
Action type: Research and Innovation actions
Countries involved: Belgium,Poland,Switzerland,France,Germany,Ireland,Portugal,Italy
Call: The impact of inequalities on democracy (HORIZON-CL2-2022-DEMOCRACY-01, 2022)
Start date: 2023-01-01
End date: 2026-12-31
Duration (months): 48.0
Total project cost (EUR): 3211355.0
EU funding (EUR): 3211354.0
Participants: 11
Project status: SIGNED

INVOLVE For trustful, participatory and inclusive public policies Across Europe there is evidence of the existing distrust in political institutions and the increased stratification of political involvement across Europe, with more vulnerable citizens having less access and influence in the decision-making process. The COVID 19 pandemic has exposed and reinforced these trends. These shifts pose a great challenge to the democratic welfare state. INVOLVE’s main objective is to help design scalable and generalizable strategies to reduce social, economic, and political inequalities. The project builds on systematic quantitative research into the trends, causes and complex relationships between democracy and inequalities. The project also focuses on how public and social services engage with vulnerable groups of citizens, especially in the age of digitalization. It will involve vulnerable groups in 8 European countries as co-researchers to complement and refine the results. In a series of concrete pilots of action-research, their aspirational capacity and their power of voice are strengthened to bring about concrete change in public services and social policies. INVOLVE will not only involve vulnerable citizens facing multiple inequalities, but also political and public decision-makers, NGOs representing vulnerable groups and experts to develop viable political strategies in order to achieve more trust-based governance in public services, to contribute to the development of a more participatory and socially responsible society. The final stage of INVOLVE aims to contribute to democratic participation in social policies at local, national, transnational and European level through campaigns with viable policy recommendations. INVOLVE also aims to enrich future research with an encompassing and innovative perspective on inequality and democracy, based on an ‘alliance of knowledge’.

Keywords: democracy inequalities political trust vulnerable groups public services social policies cross talk receiver,doer,judge participatory action research intersectionality alliance of knowledge
Investigation of the ignition of a wall-impinging jet on a hot surface: fuel jet and liquid gas jet (Hephaestus)

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: Belgium,United States
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2022-10-01
End date: 2025-09-30
Duration (months): 36.0
Total project cost (EUR): 266684.16
EU funding (EUR): 266684.16
Participants: 2
Project status: CLOSED

Accidental ignition of liquid fuels is a critical safety and economic concern for the chemical, aerospace, automotive, and petroleum industries. A fundamental understanding of ignition processes is crucial to reduce accidents and exacerbated pollution emissions through safer and more optimized designs. Even though hot surface ignition is a well-recognized hazard, it is only superficially understood, and safety guidelines tend to oversimplify the phenomenon. Hephaestus project is born from the will of two recognized research centers to merge their expertise to address this issue: the von Karman Institute for Fluid Dynamics (VKI) in Belgium and the Explosion Dynamics Laboratory (EDL) of the California Institute of Technology (Caltech), USA. Hephaestus aims at improving the knowledge on the ignition processes of a jet impinging a hot surface. A world unique experimental setup will be designed to provide an in-depth optical investigation of the fuel jet ignition. An experimental database will be generated, analyzed, and diffused into the scientific and safety community. The data will be first used to test the existing numerical models. It will be extensively analyzed to detail the different ignition mechanisms. Finally, it will be applied to test engineering models and propose new safety guidelines. VKI is developing a new laboratory on the use of flammable liquid gas for propulsion. The knowledge acquired during the project's first stage about experimental analysis of ignition mechanisms will be used to support the development of this new leading-edge laboratory. An existing VKI setup will be adapted for ignition characterization by implementing the newly learned experimental technique, and the experimental protocol will be optimized. Hephaestus project will improve safety via an enhancement of the ignition processes understanding and the diffusion of a fundamental scientific database to be used for future research.

Keywords: combustion ignition experimental design safety
Artificial Intelligence controller able to manage Air traffic Control (ATC) and Air Traffic Flow Management (ATFM) within a single framework (HYPERSOLVER)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Public-private partnerships
Destination: Single European Sky Air Traffic Management Research
Action type: Research and Innovation actions
Partnership: SESAR (JU-JTI)
Countries involved: France,Belgium,Sweden,Singapore,United Kingdom
Call: Fundamental Science and Outreach for Connected and Automated ATM (HORIZON-SESAR-2022-DES-ER-01, 2022)
Start date: 2023-06-01
End date: 2025-11-30
Duration (months): 30.0
Total project cost (EUR): 1291438.75
EU funding (EUR): 759200.0
Participants: 7
Project status: SIGNED

Air Traffic Flow Management (ATFM) is the problem of adjusting the traffic demand in each traffic volume using ATFM measures so that aircraft can be safely separated during the subsequent Air Traffic Control (ATC) process. On the other hand, ATC officers (ATCOs) give different aircraft heading, speed, and flight level change instructions to separate them in flight. Both ATFM and ATC problems have been subject of research during decades, however, all previous works addressed the ATFM and ATC problems independently. The project aims to develop an HyperSolver based on advanced Artificial Intelligent Reinforcement Learning method with continuous reassessment and dynamic updates, i.e. an holistic solver from end-to-end, covering the whole process to manage, density of aircraft, complexity of trajectories, interactions (potential conflict in Dynamic Capacity Balancing timeframe) of trajectories, conflict of trajectories at medium-term and conflict of trajectories at short-term.

Keywords: atfm,atc,conflict resolution,artificial intelligent reinforcement learning,optimisation,simulation
Relaxed Semantics Across the Data Analytics Stack (RELAX)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Doctoral Networks
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Sweden,United Kingdom,Greece,Ireland,Denmark,Germany,France,Netherlands
Call: MSCA Doctoral Networks 2021 (HORIZON-MSCA-2021-DN-01, 2021)
Start date: 2023-03-01
End date: 2027-02-28
Duration (months): 48.0
Total project cost (EUR): 2537877.6
EU funding (EUR): 2537877.6
Participants: 14
Project status: SIGNED

The RELAX European Doctoral Network aims to train a cohort of highly mobile and adaptable researchers to become experts in the design of scalable and efficient data-intensive software systems. These experts will master the specific skill of navigating the semantics or correctness conditions of applications, with the goal of enhancing scalability, response times, and availability. Working across the disciplinary specialisms of data science, data management, distributed computing and computing systems, the Fellows will develop knowledge of the broad issues underpinning data analytics systems. The bespoke training programme fosters intellectual enquiry and combines technical and scientific research training with courses in innovation, management and leadership. The training network addresses a critical skills gap in data analytics expertise, which needs urgently addressed to support innovation and employment in a fast-growing European data economy. The 14 partner organisations representing 8 countries will benefit first-hand through intersectoral collaboration and an Open Innovation model.

Keywords: data analytics,relaxed semantics,data quality and representation,coordination and synchronisation
UNlocking the potential of LOHCs through the development of KEy sustainable and efficient systems for Dehydrogenation (UnLOHCked)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Public-private partnerships
Destination: Clean Hydrogen
Action type: Research and Innovation actions
Partnership: CLEANH2 (JU-JTI)
Countries involved: Spain,France,Netherlands,Germany,South Africa
Call: Efficient system for dehydrogenation of liquid organic hydrogen carriers for application to long distance transportations (HORIZON-JTI-CLEANH2-2022-2, 2022)
Start date: 2023-06-01
End date: 2026-05-31
Duration (months): 36.0
Total project cost (EUR): 2941312.75
EU funding (EUR): 2941312.75
Participants: 11
Project status: SIGNED

By advancing breakthrough research on LOHC technologies, UnLOHCked aims at developing a radically disruptive, versatile and scalable LOHC-dehydrogenation plant. Firstly, highly active and stable catalysts without critical raw materials will be developed for reducing LOHC dehydrogenation at moderate temperatures. Secondly, an SOFC-system will be developed to be thermally integrated with the dehydrogenation process. The heat demand of the dehydrogenation unit will be fully covered by the fuel cell, while generating electric power. The surplus of hydrogen is exported. These innovative systems fully integrated will allow significant increase of overall efficiency (>50%) to hydrogen and electric power production from LOHC. Three industry partners, HERAEUS, HYGEAR and FRAMATOME, will collaborate with four universities and research centres, the University of Bilbao (Spain), CEA, CNRS-Lyon and North-West University of South Africa to develop scalable prototype system at TRL 5, validating the performance of the technology during at least 500 h. The ambition is to demonstrate the feasibility of a fully CO2-free dehydrogenation process for large-scale production of hydrogen (100-1,000 t H2/d) and electricity with competitive prices (hydrogen carrier delivery cost <2.5€/kg). Thus converting CO2-free LOHC to electricity and hydrogen instead of using NG or LPG as heat source. The UnLOHCked approach is clean & circular: it decreases energy consumption, does not use noble metals while generating CO2-free hydrogen and electricity. Techno-economic studies will demonstrate the potential of the technology to both supply hydrogen and renewable electricity to decarbonise the EU economy and to open-up hydrogen transportation by LOHC. FRAMATOME, HYGEAR AND HERAEUS will support the consortium preparing for fast market entry after the project.

Keywords: catalyst development,energy storage,liquid organic hydrogen carriers,dehydrogenation,thermal integration,co2 free process
Glucose variability patterns for precision nutrition in diabetes (GLUCOTYPES)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Pathfinder
Destination: Challenges
Action type: EIC actions
Countries involved: Denmark,Israel,Netherlands,Spain,Belgium,Croatia
Call: EIC Pathfinder Challenge: Precision Nutrition (HORIZON-EIC-2023-PATHFINDERCHALLENGES-01, 2023)
Start date: 2024-10-01
End date: 2028-09-30
Duration (months): 48.0
Total project cost (EUR): 4581331.25
EU funding (EUR): 4581331.25
Participants: 7
Project status: SIGNED

Type 2 diabetes (T2D) has emerged as a global epidemic, impacting 1 in 10 people worldwide and causing over 114,000 deaths annually in Europe. Despite extensive research, understanding the pathogenic mechanisms driving distinct disease subtypes and how diet influences glucose homeostasis has remained elusive. This knowledge gap leaves individuals with or at high risk of T2D without effective prevention or control strategies, urging a paradigm shift in our approach. The GLUCOTYPES project brings together leading experts in nutrition, metabolic diseases, glycobiology, gut microbiome, epidemiology, and machine learning from five European countries to tackle this challenge. Our strategy capitalises on advancements in wearable technologies, molecular biology, and bioinformatics. We propose to leverage high-temporal continuous glucose monitor data to identify patterns of early glycaemic alterations, a concept we refer to as glucotypes and forms the core hypothesis of our research program. Circulating and adipose tissue glycoproteomics profiling will be used to gain molecular insights into glucotypes. Machine learning algorithms will be applied to investigate the intersection between diet and glucotypes on clinical outcomes and gain mechanistic insights into how diet and gut microbiome influence glucose homeostasis in specific glucotypes. The knowledge derived from these activities will inform a proof-of-concept precision nutrition clinical study to test the efficacy of a precision-based diet on cardiometabolic outcomes and identify markers of beneficial responses to diet. In doing so, GLUCOTYPES will come closer to understanding the divergent mechanisms that influence early glycaemic alterations and how specific diets could ameliorate these alterations. Our work will establish a foundational yet comprehensive scientific groundwork to inform future precision diabetes nutrition strategies to prevent and improve the lives of all people affected by the disease.

Keywords: type 2 diabetes,diet,endotypes,continuous glucose monitoring,endocrinology