Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
NATPROLUB HOP-ON: Macroscale bioengineered vaginal 3D models for screening nature-inspired prophylactic lubricants against viral infections (NatProLub Hop-ON)

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: Research and Innovation actions
Countries involved: Sweden,Portugal
Call: Hop on Facility (HORIZON-WIDERA-2023-ACCESS-06, 2023)
Duration (months): 34.0
Total project cost (EUR): 598767.5
EU funding (EUR): 598767.5
Participants: 2
Project status: CLOSED

Sexually transmitted infections like HIV and herpes simplex virus (HSV) are underdiagnosed due to asymptomatic cases, stigma, and limited access to testing, particularly affecting women in high-risk regions. Currently, condoms are the most effective means of prevention, but women often lack control over their use, contributing to a gender imbalance in sexual health. Antiviral drugs, while available, face issues like resistance development and low adherence. Co-infection with HIV and HSV worsens outcomes, as HSV increases the risk of HIV transmission. The NatProLub project aims to develop antiviral lubricants inspired by natural mechanisms offering a new approach to HIV and HSV prevention, with a low risk of side effects or resistance. Such lubricants will be bio-safe, efficient, and stable before being excreted naturally, ensuring the trapping and clearing of viruses away from the vaginal lumen. NatProLub HOP-ON aims to achieve the same goal by adding value to the pre-clinical validation of the NatProLub lubricants. The introduction of Cellularis Biomodels (CEBIOM) as the new widening partner will bring unique expertise to the development of organotypic vaginal models that will contribute to enhancing the validation of hydrogel lubricants and to a reduction in the usage of animal models initially proposed in the project. The widening partner will develop a Vaginal 3D model recapitulating the tissue-like density, anatomic scale, and bioarchitecture of the vaginal epithelium. Such physio-mimetic model termed Vaginal Cellgels will contribute to test mucin hydrogels safety, prophylactic and retention efficacy, under dynamic flow and vaginal physiological conditions. The introduction of a deep tech SME as an additional widening partner will bring new expertise and ideas that will be beneficial both for the existing consortium as well as for the new partner, contributing to improve dissemination, visibility and strengthen the links with international partners.

Keywords: sexually transmitted infections,lubricants,anti hiv 1 dipeptides,anti virals,vaginal infections,living materials,3d in vitro models
Mapping the Connectome Dynamics of Trauma Psychopathology (TraumaNeuroInsight)

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: Israel
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): 2499750.0
EU funding (EUR): 2499750.0
Participants: 1
Project status: SIGNED

Exposure to a traumatic event can induce psycho-physiological reactions and symptoms that in most people recede over time. A minority of trauma-exposed individuals develop posttraumatic stress disorder (PTSD), characterized by severe functional and emotional impairment. The global burden of PTSD is estimated in the hundreds of billions of Euros and millions of years lived with disability. Individual differences in neurobiological vulnerability to traumatic stress have been studied extensively, yet the impact of neuroscience on clinical application is minimal. The proposed work aims to address this gap using three work packages (WPs). WP1 will establish a detailed open-access database to study the impact of traumatic stress on brain structure/function connectome: 1000 participants with PTSD, 1000 trauma-exposed healthy, 1000 non-exposed. WP2 is a longitudinal study of the effects of trauma exposure. It will delineate long-term trajectories of stress-related symptoms and corresponding connectome dynamics. Building on already collected data from 579 veterans who were followed over four years, starting with a pre-exposure baseline, we will add two new data points, at 7- and 9-year post-exposure, to reveal long-term adaptation patterns. WP3 is a 3-armed randomized controlled trial to test the impact of MRI-guided neurostimulation of cortico-hippocampal networks on brain connectivity patterns and severity of memory symptoms. We target cortico-hippocampal connections with broad impact on cortical circuitry, consistent with our focus on whole-brain connectome correlates. Moving beyond separate analyses of brain structure and function in relation to a heterogeneous definition of PTSD, we will use combined structure/function modeling in relation to specific symptoms. Together the proposed work is expected to redetermine the transaction between neuroscience and clinical research in relation to trauma psychopathology.

Keywords: traumatic stress,ptsd,mri
Advanced nanospectroscopy for mapping local conductivity in conductive metal-organic framework (NAPOLEON)

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: Chemistry
Countries involved: Spain
Call: MSCA Postdoctoral Fellowships 2022 (HORIZON-MSCA-2022-PF-01, 2022)
Start date: 2024-09-01
End date: 2026-08-31
Duration (months): 24.0
Total project cost (EUR): 181152.96
EU funding (EUR): 181152.96
Participants: 1
Project status: SIGNED

NAPOLEON’s main objective is the development and demonstration of mapping ultra-broadband optical conductivity of novel conductive metal-organic frameworks (MOFs) by infrared nanospectroscopy (nano-FTIR). Conductive MOFs are critically important for the development of a highly efficient and low cost electrocatalysis for electric energy storage and retrieval. MOFs development needs the understanding of its conductive properties down to the nanoscale, which is not possible with traditional electrical transport measurements. Nano-FITR offers several advantages compared to traditional transport measurements: no contacts are needed, there are no problems with contact resistances, nanoscale materials can be measured, and the frequency-dependent response provides deeper insights into conduction properties than just DC measurements. However, current tabletop nano-FTIR systems are not able to characterise conductive MOFs due to the limited spectral coverage of the employed laser sources. To overcome this challenge I will introduce a novel plasma source-based nano-FTIR spectrometer, which will ensure the broadest spectral coverage. Then, I will develop a new model from which the anisotropic conductivity of MOFs can be extracted from nano-FTIR spectra. Finally, I will use the improved nano-FTIR system and the new model to study a highly conductive MOF sample, the CU-BHT, which demonstrated high electrocatalytic activity. NAPOLEON will provide innovative technologies, original methods and breakthrough knowledge in the fields of chemistry, nanooptics and solid-state physics. Specifically, NAPOLEON will develop the first methodology to measure optical conductivity in conductive MOFs with nanoscale resolution, which will contribute to boost the development of these materials. The results envisioned by NAPOLEON in terms of characterisation and understudying of new materials for electrocatalysis will be a key piece to achieve the EU target of carbon neutrality by 2050.

Keywords: conductivity,s snom,nano ftir,conductive metal organic framework,infrared nanospectrosocy,infrared nanoimaging
Optimisation of the DAMIC Instrument at Modane (ODIM)

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: Physics
Countries involved: France
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2025-10-01
End date: 2027-09-30
Duration (months): 24.0
Total project cost (EUR): 226420.56
EU funding (EUR): 226420.56
Participants: 1
Project status: SIGNED

Dark matter, identified primarily by its gravitational effects, is not composed of Standard Model (SM) particles, posing significant challenges that require coordinated and comprehensive responses. To optimize detection methods, it is important to understand the true nature of dark matter, which contributes to the generation and dissemination of experimental evidence, and to implement effective techniques and simulations. These mysterious particles have changed our knowledge of cosmological observations and nonbaryonic particles. The insights gained from this discovery are crucial for improving precise techniques for distinguishing dark matter from various background noise sources and for exploring potential candidates beyond the traditional weakly interacting massive particles (WIMPs). The DAMIC-M experiment at the Laboratoire Souterrain de Modane uses advanced CCD technology to increase sensitivity to dark matter candidates, particularly light WIMPs, and other exotic particles. With support from the Marie Skłodowska-Curie Action Program, the ODIM (Optimisation of the DAMIC Instrument at Modane) project aims to optimize detection techniques and minimize background noise, which is crucial for distinguishing dark matter signals from other sources. Ongoing research emphasizes the importance of simulations and material selection to improve detector performance and sensitivity. Further exploration of dark matter candidates beyond WIMPs is important, as is the development of new detection technologies. International cooperation and multidisciplinary collaboration will be vital in overcoming existing challenges and advancing our understanding of dark matter.

Keywords: ccd detectors,underground laboratories,shielding
Controlling Soft Robots for Advanced Adaptivity and Versatility in Confined Spaces (Soft-Scout)

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: Netherlands
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2025-11-01
End date: 2027-10-31
Duration (months): 24.0
Total project cost (EUR): 217076.16
EU funding (EUR): 217076.16
Participants: 1
Project status: SIGNED

Access to confined spaces is highly crucial, whether for repairing hard-to-reach aircraft engine parts, performing minimally invasive surgeries, or inspecting infrastructure after severe weather events. The Soft-Scout (Controlling Soft Robots for Advanced Adaptivity and Versatility in Confined Spaces) project addresses these challenges by enabling a soft-bodied robot to autonomously navigate and accurately conduct tasks within confined areas, which leads to reduced human effort in these demanding environments and improved quality of inspection and maintenance. To address the complexity of a soft robotic system, the overarching objective of Soft-Scout is the development and deployment of the control and learning frameworks for a soft robot that provide guarantees for the robot’s precision and reliability, while equipping it with the autonomy and robustness to navigate unknown confined areas. Maja Trumic will carry out the Soft-Scout project under the supervision of Dr. Cosimo Della Santina at the Delft University of Technology, The Netherlands. The project is aligned with the United Nations Sustainable Development Goals and the European objectives (European Strategic Agenda and Horizon Europe Mission). Compared to state-of-the-art solutions, the elasticity of a soft robot’s body allows safe navigation through confined areas, while the proposed framework enables robust and dexterous operation with guaranteed precision and reliability margins. The Soft-Scout’s vision will be accomplished through three specific objectives: 1) an advanced shape control framework will enable a soft robot to perform various tasks; 2) the twofold learning strategy for autonomous navigation and robustness in confined space will endow a soft robot with the capability to deal with uncertainties in the real-world settings; and 3) the overall control and learning framework will be experimentally validated on a tentacle-shaped soft robot, collecting and integrating user feedback as well.

Keywords: nonlinear control theory,soft robotics
Carbon dioxide (CO2) Storage In deep volcaNic areas (CO2SINk)

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: Spain
Call: ERC PROOF OF CONCEPT GRANTS2 (ERC-2022-POC2, 2022)
Start date: 2023-06-01
End date: 2024-11-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

CO2SINk aims at proving the effectiveness of an innovative CO2 storage concept in deep volcanic areas that reduces the leakage risk. Humans need to take urgent action to achieve a climate-neutral society. Among the necessary actions, Carbon Capture and Storage (CCS) will enable decarbonizing the hard-to-abate industry, which represents some 10% of the current CO2 emissions and can even provide net-carbon removal if it is combined with bioenergy (BECCS) or direct air capture (DACCS). To effectively mitigate climate change, CCS should scale up from the current 40 Mt/yr of stored CO2 to the gigatonne scale by 2050. Yet, one of the main risks of CCS is CO2 leakage because CO2 is buoyant in the conventional concept of storing CO2 in deep sedimentary formations. The leakage risk can be significantly reduced by storing CO2 in deep volcanic areas where water stays in supercritical state because at these pressure and temperature conditions CO2 is denser than water and thus, sinks. Therefore, this novel storage concept, if proven effective, would improve the safety of CCS and would amplify the storage options. We estimate that a few hundreds of wells could be storing CO2 in deep volcanic areas by 2050, representing a storage on the order of 1 Gt/yr. This storage capacity highlights the high gain of the proposal. Nonetheless, injecting CO2 in deep volcanic areas also entails high risks: (1) potential long-term CO2 leakage due to convective fluid flow and (2) potential induced seismicity above acceptable levels. We will investigate the extent of these risks and propose mitigation measures to manage them. We will disseminate and communicate the project outcome to the scientific community, society, policy makers and companies. We plan to patent this storage concept if it is proved to be effective and will establish a commercialization roadmap with the advice of industrial collaborators and experts in knowledge transfer.
The Global Viral Ecosystem Research and Preparedness Initiative (VERPI)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Staff Exchanges
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Ireland,Congo, The Democratic Republic of the,United States,Japan,Denmark,Poland,United Kingdom,Uganda
Call: MSCA Staff Exchanges 2024 (HORIZON-MSCA-2024-SE-01, 2024)
Start date: 2025-10-01
End date: 2029-09-30
Duration (months): 48.0
Total project cost (EUR): 1613220.0
EU funding (EUR): 1613220.0
Participants: 10
Project status: SIGNED

The Global Viral Ecosystem Research and Preparedness Initiative (VERPI) is a comprehensive research programme addressing emerging infectious diseases through a One Health approach. VERPI project unites ten partners from eight countries across four continents — Europe, Asia, Africa, Northern America— to strengthen global research capacity for equitable pandemic preparedness. The VERPI scientific programme is structured around four main objectives 1. Strengthening capacity for pathogen discovery and characterisation 2. Accelerating countermeasures development: broad-spectrum antivirals, monoclonal antibodies and diagnostics 3. Enhancing biomarker discovery for viral pathogenesis and long-term health impacts 4. Leveraging community engagement to enhance public trust through transparent health communication. VERPI's innovative "triple I" —interdisciplinary, international, and intersectoral—framework leverages diverse expertise, transcends national boundaries, and bridges academic and clinical sectors. Central to VERPI's strategy are embedded secondments, fostering interdisciplinary collaboration and a dynamic approach to translational research in emerging viral epidemics. This promotes a broad R&I platform for rapid response to future viral threats, supporting EU Sustainable Development Goals to strengthen early warning systems and health risk management capacities globally.

Keywords: virology pandemic preparedness emerging infections antivirals immunology bioprofiling pathogen discovery
Social aWareness for sErvicE roboTs (SWEET)

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: Italy,Korea, Republic of,Japan,Ireland,Germany,Spain,Norway,United Kingdom,France,Sweden
Call: MSCA Doctoral Networks 2023 (HORIZON-MSCA-2023-DN-01, 2023)
Start date: 2025-02-01
End date: 2029-01-31
Duration (months): 48.0
Total project cost (EUR): 3664699.2
EU funding (EUR): 3188527.2
Participants: 25
Project status: SIGNED

To develop autonomous robots that are able to comply with social conventions and expectations, and avoid rejection from humans requires that robots must be aware of the social context in which they operate. To this extent, robots need to be endowed with high levels of reactivity, proactivity, responsiveness, and intelligibility. The Doctoral Network - Industrial Doctorates on Social aWareness for sErvicE roboTs (SWEET) aims at training a new generation of research and professional figures able to advance the development of socially aware robots capable of perceiving, interpreting, and responding to human emotions, intentions, and cultural differences. The training program will offer a diverse curriculum, encompassing theoretical knowledge, hands-on technical skills, and real-world application scenarios. The network's interdisciplinary approach includes various fields, such as artificial intelligence, machine learning, human-robot interaction, computer vision, and cognitive sciences. Doctoral candidates will be immersed in cutting-edge research and innovation, gaining insights from the experience of both industrial and academic acclaimed research groups. The network will place a strong emphasis on ethical considerations and responsible innovation, deploying socially aware robots aligned with societal values and promoting inclusivity. Doctoral Candidates will also have the opportunity to participate in a unique coaching program for continuous professional development of their soft and leadership individual skills. Integration Milestones following a Scenario-Based Learning approach will provide co-working activities where collaborative design/implementation is fostered. The inter-sectoral collaboration between academia, user groups’ representatives, business developers, and robot manufacturers of the project will further strengthen the novelty and impact of the research and training, and that research results are economically, socially, and technically feasible.

Keywords: social awareness
Higher-Order Hodge Laplacians for Processing of multi-way Signals (HIGH-HOPeS)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Systems and Communication Engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: Germany
Call: ERC STARTING GRANTS (ERC-2021-STG, 2021)
Start date: 2023-01-01
End date: 2027-12-31
Duration (months): 60.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: SIGNED

Network analysis has revolutionized our understanding of complex systems, and graph-based methods have emerged as powerful tools to process signals on non-Euclidean domains via graph signal processing and graph neural networks. The graph Laplacian and related matrices are pivotal to such analyses: i) the Laplacian serves as algebraic descriptor of the relationships between nodes; moreover, it is key for the analysis of network structure, for local operations such as averaging over connected nodes, and for network dynamics like diffusion and consensus; ii) Laplacian eigenvectors are natural basis-functions for data on graphs and endowed with meaningful variability notions for graph signals, akin to Fourier analysis in Euclidean domains. However, graphs are ill-equipped to encode multi-way and higher-order relations that are becoming increasingly important to comprehend complex datasets and systems in many applications, e.g., to understand group-dynamics in social systems, multi-gene interactions in genetic data, or multi-way drug interactions. The goal of this project is to develop methods that can utilize such higher-order relations, going from mathematical models to efficient algorithms and software. Specifically, we will focus on ideas from algebraic topology and discrete calculus, according to which the graph Laplacian can be seen as part of a hierarchy of Hodge-Laplacians that emerge from treating graphs as instances of more general cell complexes that systematically encode couplings between node-tuples of any size. Our ambition is to i) provide more informative ways to represent and analyze the structure of complex systems, paying special attention to computational efficiency; ii) translate the success of graph-based signal processing to data on general topological spaces defined by cell complexes; and iii) by generalizing from graphs to neural networks on complexes, gain deeper theoretical insights on the principles of graph neural networks as special case.

Keywords: graph signal processing,complex systems,networks,cell complexes,algebraic topology,hodge laplacian