Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Beyond the tipping point: Cascading transitions in the behavioral and social sciences (Cascade)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: The Human Mind and Its Compl exity
Panel description: Cognitive science, psychology, linguistics
Countries involved: Netherlands
Call: ERC ADVANCED GRANTS (ERC-2021-ADG, 2021)
Start date: 2023-01-01
End date: 2027-12-31
Duration (months): 60.0
Total project cost (EUR): 2493576.0
EU funding (EUR): 2493576.0
Participants: 1
Project status: SIGNED

Tipping points or phase transitions separate stable states in psycho-social systems. Examples are quitting smoking, radicalization, and dropping-out of school. Two knowledge gaps prevent our ability to predict and control these tipping points. First, we miss explanatory mathematical models of such non-linear processes. Second, we ignore the multilevel character of psycho-social transitions. I contend that important changes in many psycho-social systems are cascading transitions, where individual transitions trigger or are triggered by social transitions. The cascade of radicalization of individuals in the context of political polarization in societies is an example of such a multilevel process. Being able to predict and control cascading transitions in psycho-social systems would be a major scientific breakthrough. As an expert of complex systems research in the behavioural and social sciences, with an extensive track record in studying single level psychological transition processes (e.g., in perception, sleep, disorders, cognition, and attitudes), my key objective is to develop a novel and broadly applicable methodology to study multilevel cascading transitions in psycho-social systems. This methodology comprises theory construction in the form of mathematical modelling and innovative empirical analyses. I will do so by studying three important examples: a) opinion change from individuals to populations and back, b) learning, where progression and drop-out are embedded in collective processes, c) addiction, where transitions to addiction or abstinence within individuals are part of cascading epidemiological changes of substance use in populations. Beyond its immediate utility in these three cases, I envisage this novel, highly interdisciplinary project to stimulate future scientific research on cascading transitions in other disciplines, such as climate research, and to have significant impact on practices in conflict management, healthcare, and education.

Keywords: phase transitions,complexity,learning,attitudes,addiction
Advanced Clean Combustion for hydrogen-basEd Power Technology (ACCEPT)

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: Netherlands,Germany,United Kingdom,Ireland,Norway,Greece,Italy
Call: Improved characterisation, prediction and optimisation of flame stabilisation in high-pressure premixed hydrogen combustion at gas-turbine conditions (HORIZON-JTI-CLEANH2-2024, 2024)
Start date: 2025-05-01
End date: 2029-04-30
Duration (months): 48.0
Total project cost (EUR): 4145509.21
EU funding (EUR): 3999022.96
Participants: 11
Project status: SIGNED

Hydrogen-fired gas turbines can potentially produce electric power (or mechanical work) at unmatched scale with zero carbon emissions. Furthermore, they will yield this potential at high cycle efficiency and with virtually zero emissions of atmospheric pollutants once advanced Dry Low Emission (DLE) combustion systems, able to robustly and reliably stabilise premixed hydrogen flames at high pressures, are successfully developed. However, the development of such advanced DLE combustion systems is presently hampered by the existence of knowledge gaps about premixed hydrogen combustion at high pressure. More specifically, a crucial lack of knowledge concerns the pressure dependence of the turbulent burning rate in premixed hydrogen flames. This is due to the fundamental combustion characteristics of premixed hydrogen flames, largely deviating from those of natural gas and other more conventional hydrocarbons and affects our ability to accurately predict the stability limits of these flames.

Keywords: high pressure,turbulent combustion,gas turbine,injection strategies,fuel staging
Code Obfuscation in a Quantum World (ObfusQation)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Computer Science and Informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Italy
Call: ERC STARTING GRANTS (ERC-2022-STG, 2022)
Start date: 2024-01-01
End date: 2028-12-31
Duration (months): 60.0
Total project cost (EUR): 1458750.0
EU funding (EUR): 1458750.0
Participants: 1
Project status: SIGNED

Program obfuscation is a central building block in cryptography and has been conjectured to be crypto-complete: It subsumes virtually all known cryptographic primitives, and extends the scope of cryptography with new capabilities. Yet, when bringing quantum computation into the picture, our understanding of obfuscation is inadequate: (i) On the one hand, quantum algorithms break most known constructions of obfuscation, and the few that survive are based on poorly understood computational assumptions. (ii) On the other hand, obfuscation is limited to classical programs and thus fails to cater the potential advantages of quantum computation. The notion of obfuscation of quantum programs is largely unexplored. At present, we do not even know a heuristic construction of quantum obfuscation, let alone a provably-secure one. The goal of this research program is to place obfuscation on firm footing, even in a quantum world. We will develop new constructions of classical obfuscation that are provably secure against quantum algorithms. Then, using this cryptographic tool, we will systematically tackle the question of obfuscating quantum programs. Quantum obfuscation will provide the theoretical foundation for cryptography secure against quantum attacks, and will open the floodgate for new applications of cryptography in a quantum world.
Data-driven Reduction Of Pesticide Spread in high volume orchard treatments with smart sprayers. (DROPS)

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: Environment and Geosciences
Countries involved: Spain,Belgium
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2026-03-02
End date: 2028-09-01
Duration (months): 30.0
Total project cost (EUR): 242593.2
EU funding (EUR): 242593.2
Participants: 3
Project status: SIGNED

In fruit tree crops, which are vital to EU agriculture, efficient pesticide use is crucial for maintaining high yields and assuring market quality. However, traditional spraying methods often result in significant pesticide losses through drift and runoff, posing environmental and health risks. Although new smart sprayers equipped with pulse width modulation (PWM) valves are designed to control flow rates and minimise off-target losses, the droplet size variations caused by pressure fluctuations when spraying high volumes to control pests and diseases are still poorly understood, and often lead to uncontrolled pesticide dispersion to the environment. The DROPS project will optimise pesticide application in orchards by developing a novel methodology for predicting pesticide dispersion and improving spraying practices. Specifically, DROPS will directly measure droplet size in orchards and integrate computational fluid dynamics (CFD) models with machine learning to create a Decision Support System (DSS) that guides farmers in optimising pesticide applications. The project will adapt and validate droplet size measurement techniques for dynamic outdoor orchard conditions, using PWM-based sprayers. This will provide accurate data on droplet behaviour under varying environmental conditions and sprayer settings. The data will inform predictive models of droplet size variation, enhanced by machine learning algorithms for greater accuracy. These models will then be integrated into CFD simulations to predict pesticide dispersion in different orchard environments. In the final phase, the DSS will be developed and field-validated to provide real-time recommendations for minimising off-target pesticide dispersion. The system will be implemented in smart sprayers and tested with an industry partner to ensure practical application under real-world conditions.

Keywords: precision agriculture,pesticide dispersion,droplet size measurement,orchard,cfd modelling,smart sprayer,pwm
The ontogenesis of abstract thought – higher-order representations in the maturing brain (REPRESENT)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: The Human Mind and Its Compl exity
Panel description: Cognitive science, psychology, linguistics
Countries involved: Germany
Call: ERC STARTING GRANTS (ERC-2023-STG, 2023)
Start date: 2024-11-01
End date: 2029-10-31
Duration (months): 60.0
Total project cost (EUR): 1647655.0
EU funding (EUR): 1647655.0
Participants: 2
Project status: SIGNED

Thinking about the world–what is and what might be–is fundamental to human life. The foundation for this world-understanding is laid in the preschool years of childhood. Around the age of 4, children begin to reason not only about the real world but also about what is possible or what people believe about the world. The acquisition of these abstract representations of the world is reflected in a major developmental breakthrough across domains of human cognition. The mechanisms that drive this breakthrough, however, are unknown. REPRESENT aims to clarify the cognitive and neural foundation of how we, in early childhood, come to represent the world in abstract terms. Based on novel findings, I propose that the maturation of a core network of the human brain–the Default Mode Network–allows children to decouple representations from sensory input and thus entertain several different representations of the world simultaneously. Increased connectivity to prefrontal regions and coupling to other cognitive networks are proposed to enable children to compute the relation between these representations, providing the foundation for abstract reasoning. REPRESENT will, for the first time, connect multivariate and connectivity methods in early childhood combined with novel task designs to reveal the precise neural representations that underlie reasoning about (a) different beliefs and (b) possibilities and their functional interplay in maturing networks of the brain. WP1 targets change in these representations and networks in preschool-age as mature abstract reasoning emerges. WP2 aims to reveal how infants, compared to preschoolers, represent situations involving multiple beliefs or possibilities. This new approach will allow REPRESENT to resolve longstanding questions of how uniquely human abstract thought develops, and how it is implemented in the human brain. This has myriad implications for developmental and cognitive theory, and for our understanding of the human brain.

Keywords: early childhood cognitive development brain maturation default mode network developmental cognitive neuroscience theory of mind possibility reasoning
Nonverbal Multimodal Social Intention Modelling (NEON)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Computer Science and Informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Netherlands
Call: ERC CONSOLIDATOR GRANTS (ERC-2022-COG, 2022)
Start date: 2024-01-01
End date: 2028-12-31
Duration (months): 60.0
Total project cost (EUR): 1996795.0
EU funding (EUR): 1996795.0
Participants: 1
Project status: SIGNED

An under-explored problem in Social Signal Processing (SSP) is human social intent detection. SSP develops automated systems to interpret human social behaviour from sensors such as cameras, microphones, and wearables. Prior work estimating intent uses scenarios that are constrained enough so that the intent is determined by a congruent outcome. In reality, this is not true, otherwise emergent leaders are never female because they do not speak up and black minorities are criminals because they are often seen interacting with police. NEON addresses intention detection in more open-ended contexts involving large unstructured social gatherings such as networking or mingling events. During these events, there are no prearranged conversations, multiple conversations can occur at the same time, and all conversation come about via coordination with multiple independent actors with their own possibly conflicting goals. How do we train machines to perceive plausible intentions? Asking the individual to continuously report on their immediate intentions would contaminate their spontaneous social behaviour. NEON hypothesises that plausible social intentions are perceivable by external observers though the explanations of why (based on the behaviours of the individual and the surround social context) may vary depending on the perceivers own life experiences. To this end, NEON will develop a novel framework to harvest and learn from social intentions and their relation to future outcomes using a novel multi-task learning set up that clusters both on the traits of the perceivers as well as the observed individuals, a unified theory that situates conversations in free standing groups in both space and time and a novel Graphical Neural Network architecture to model it through multi-sensor cross modal learned neural representations. Aside from being a significant advance for SSP, NEON also benefits a range of other fields from human-robot interaction to organisational psychology

Keywords: social signal processing,human behavior analysis,multimodal interaction,affective computing
Bottom-up manufacturing of artificial anti-tumor T cells (ArTCell)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Pathfinder
Destination: Open to supporting projects in all areas of science, technology,...
Action type: EIC actions
Countries involved: Belgium,Poland,Italy,Netherlands
Call: EIC Pathfinder Open (HORIZON-EIC-2023-PATHFINDEROPEN-01, 2023)
Start date: 2024-02-01
End date: 2029-01-31
Duration (months): 60.0
Total project cost (EUR): 3391796.25
EU funding (EUR): 3391796.25
Participants: 4
Project status: SIGNED

T cells play a central role in anti-tumor immune protection. While their ability to target and eliminate emerging tumor cells is increasingly recognized, fully-established tumors can efficiently evade T cell response. Significant efforts spanning several decades of research have been made to develop T cell-based therapies manufactured from donor-derived T cells. The use of tumor-directed T cells engineered to express chimeric antigen receptors (CARs) represents, to date, one of the most successful applications for treatment of chemoresistant cancers. However, several major drawbacks, including economic factors, suboptimal functioning and life-threatening side effects, are still hindering the full potential of T cell-based therapies. To address this issue, we aim to generate Artificial T cells (ArTCell) that will mimic the anti-tumor function of a T cell-based therapy but in a safer, more efficient and less expensive product. ArTCells will incorporate two key features of activated T cells into Giant Unilamellar Vesicles (GUVs): the specificity of tumor cell recognition and the cytotoxic activity achieved through death ligands and cytolytic proteins. Functionalization of the GUVs will be confirmed by immunofluorescent labelling of membrane proteins (i.e., TRAIL, LFA-1 and CAR) and detection with flow cytometry. The morphology of ArTCell will be monitored via cryo-EM, SEM, and confocal microscopy. The ability of ArTCell to target and kill tumour cells will be thoroughly validated in vitro by a combination of functional and high resolution live imaging assays as well as in vivo with two cell line- and patient-xenografts mouse models. The ArTCell could allow to circumvent many of the current technological limitations that hinder a more wide-spread applicability of cell-based therapies, without being subject to tumor-mediated inactivation

Keywords: artificial cells,car t cell,blood cancer,cell therapy,guvs
The first European cargo drone airline (Dronamics)

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: Bulgaria,Ireland
Call: EIC Accelerator Open (HORIZON-EIC-2022-ACCELERATOR-01, 2022)
Start date: 2022-06-01
End date: 2025-07-31
Duration (months): 38.0
Total project cost (EUR): 3569750.0
EU funding (EUR): 2498825.0
Participants: 2
Project status: CLOSED

Dronamics is the first drone system for fuel-efficient, same-day, cross-border & long-haul middle-mile cargo deliveries. We will operate a proprietary drone fleet from within a network of standardised low-cost droneports using automated flight control systems. Our state-of-the-art drones can carry 350 kg payload within 2500 km flight range, require only 400 m of runway & are 50-90% cheaper than alternatives. Dronamics will enable international same-day deliveries for €5 or less with 40-70% lower CO2 emissions. We will provide e-commerce, pharma & urgent shipments at 3,000+ airstrips in the EU where our droneports can be easily deployed. We are partnering with DHL & Hellman for 4,000+ drones, recognized on DHL Innovation Radar & ready to create the new market for drone-based middle-mile delivery as early as 2023. We will start our 1st trial droneports in Bulgaria & expand EU-wide to serve non-hub, remote, or underserved communities, creating local manufacturing & operational jobs.

Keywords: cargo,sustainable transport,network infrastructures
Advances in Large-scale, Multilevel, and Hierarchical Optimisation for Challenging Applications (ALMOA)

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: Mathematics
Countries involved: Austria,Italy,France,Germany,Netherlands,Denmark
Call: MSCA Doctoral Networks 2024 (HORIZON-MSCA-2024-DN-01, 2024)
Start date: 2026-01-01
End date: 2029-12-31
Duration (months): 48.0
Total project cost (EUR): 4109703.43
EU funding (EUR): 3854093.04
Participants: 23
Project status: SIGNED

ALMOA will train the next generation of highly skilled researchers and managers in Applied Mathematics, Operations Research, and Computer Science, to face identified needs in areas such as Sustainable Energy Systems, Green Logistics, Green Data Science, and Natural Sciences. 13 Doctoral Candidates (DC) will be educated through an innovative and effective training programme based on individual, original research projects motivated by these applications. Through the complementary competencies in our research teams of preeminent optimisation experts and practitioners from leading European industries, we will employ multiple perspectives on optimisation to conceive and produce the mathematical foundations, solution methods, and corresponding software. Crossing borders between the optimisation areas often yields brilliant outcomes, hence we see great innovative potential by means of a combination of mixed-integer nonlinear, uncertainty, multilevel, matrix-valued, hierarchical, and large-scale aspects. Our consortium has an excellent track record of collaboration and training young researchers, having run four MSCA training networks in recent decades. In ALMOA we strive for even higher academic standards. Through secondments to different academic and industrial sites, the DC will be exposed to a broader range of methodological approaches, with the benefit of superior collaborative supervision by academic and industrial partners with international visibility. By gaining transferable skills, the DC will be entrepreneurial and resilient researchers, able to face current and future challenges and to convert knowledge and ideas into products and services. Cross-cultural experiences will broaden their horizons and ALMOA will promote global academic citizenship for individuals and institutions. The applications considered as well as following the recommendations in the MSCA Green Charter will have a positive impact towards an environmentally sustainable future.

Keywords: mixed integer nonlinear optimisation,optimisation under uncertainty,multilevel optimisation,large scale optimisation,hierarchical optimisation,applications energy,logistics,data science
Thermodynamically Robust Transfer Reagents for Molecular Editing (ChemEd)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Germany
Call: ERC PROOF OF CONCEPT GRANTS (ERC-2024-POC, 2024)
Start date: 2025-04-01
End date: 2026-09-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: SIGNED

The increasing demand of complex organic molecules, either because of their biological activity or technical interest are opening a new period in Organic Synthesis, which is mainly focused on the discovery of novel transformations that can be carried out in already (poly)functionalized substrates. As part of this trend, the development new reagents capable to transfer additional functional groups at the desired position of advanced synthetic intermediates is of paramount importance. Areas such as crop science and drug discovery make extensive use of this working methodology for the improvement of their original targets and the identification of new ones. Arguably, the most versatile group transfer reagents used in organic synthesis are those based on hypervalent I(III) structures. However, their implementation in industrial processes is seriously limited by their highly reactive nature. Hypervalent iodine (III) compounds are known to be potentially explosive and this limits their use to small scale. Restrictive safety conditions also apply for their synthesis and storage. To circumvent these drawbacks, we developed with the ERC Consolidator SULFOSOL (771295) a general approach for the straightforward preparation of thermodynamically more robust transfer reagents based on the use of low prize sulfur-containing platforms. Through the intervention of ChemEd, we will push the chemical space beyond the existing boundaries through the synthesis of reagents able to transfer the unique structural entities identified by our industrial partners. ChemEd will simultaneously address the scale-up synthesis of such reagents, to proceed with their commercialization.