Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Alliance for Research on Cultural Heritage in Europe (ARCHE)

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 the European Cultural Heritage and the Cultural and Creative Industries
Action type: Coordination and support actions
Countries involved: France,Italy,Spain,Netherlands,Slovakia,Germany,Czechia,Portugal,Cyprus,Slovenia,Austria,Poland,Belgium,Romania,United Kingdom,Norway,Greece,Sweden
Call: Coordination of European cultural heritage research and innovation among Member States (HORIZON-CL2-2021-HERITAGE-02, 2021)
Start date: 2022-09-01
End date: 2025-09-30
Duration (months): 37.0
Total project cost (EUR): 2913136.25
EU funding (EUR): 2913136.0
Participants: 31
Project status: SIGNED

The Cultural Heritage (CH) Research and Innovation (R&I) landscape has changed significantly over the past few years. New political, technological and socio-economic parameters put emphasis on improving protection, conservation and restoration efficiency of European CH with green technologies, as well as developing and further exploiting high quality digitisation, open access and curation of digital assets. The need also exists to enhance the innovation potential and competitive edge of the Cultural and Creative Sector (CCS) to drive sustainable growth and job creation against global competition. Responding to these challenges, the project will develop a pan European framework for a holistic approach to CH R&I, by creating the Alliance for Research on Cultural Heritage in Europe (ARCHE), a spearheading coordination network of researchers, innovators, heritage professionals, institutional bodies and citizens. The objective is to engage all CH actors in member States / Associated Countries in the co-design of R&I strategies and roadmaps that lead to R&I initiatives requiring multidisciplinary approaches and skills A detailed assessment of R&I gaps and needs for the next decade will be the basis for designing a Strategic Research and Innovation Agenda (SRIA) for joint programming aiming to increase awareness of heritage and European sense of belonging. A new purpose-built governance structure will be proposed that will effectively involve existing networks and new partners from relevant scientific disciplines and industries. It will also promote intensive and wide-ranging collaboration between cultural heritage, the arts, and the CCS. The SRIA and governance structure will be tested in a pilot operation in the third and final year. ARCHE will be a strong basis for a European Partnership in CH, by pooling, developing and upscaling transnational collaboration on CH R&I and by involving all stakeholders and funding mechanisms related to CH R&I policy and action.

Keywords: heritage science,cultural heritage research and innovation,cultural heritage conservation and protection,cultural and creative sectors,arts
Discovery of a novel phenylalanine degradation pathway in plants (Phe-Degradation)

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: Germany
Call: MSCA Postdoctoral Fellowships 2022 (HORIZON-MSCA-2022-PF-01, 2022)
Start date: 2023-04-01
End date: 2025-03-31
Duration (months): 24.0
Total project cost (EUR): 189687.36
EU funding (EUR): 189687.36
Participants: 1
Project status: CLOSED

Plants are anticipated to be a more sustainable platform for chemical production than fossil-fuel-based chemical production, as plants can produce various natural products using CO2 as a solo carbon source. In plants, phenylalanine (Phe) is an aromatic amino acid that acts as precursors of numerous Phe-derived specialized metabolites, many of which are utilized for nutritional, pharmaceutical, and biomaterial uses in our society. Whereas plants produce a large amount of Phe to produce such abundant Phe derivatives, Phe itself is so toxic and must be somehow safely detoxified to balance its biosynthesis and degradation. Despite a growing body of knowledge on Phe biosynthesis, however, little is known about Phe degradation, because a plant Phe degradation pathway has not been discovered, unlike the well-characterized Phe degradation in animals. This knowledge gap has been a long-term mystery in the plant metabolism research field for decades, making plant-based chemical production for Phe-derived natural products difficult on a commercial scale. The applicant has studied the biosynthesis of Phe in plants and found a piece of evidence for a putative Phe degradation pathway in Arabidopsis. Combining biochemistry and plant genetics with start-of-art metabolomics, this proposal will aim to identify enzymes mediating a novel Phe degradation pathway and elucidate the roles of Phe degradation in plant metabolism. These potential findings will uncover the unique plant Phe degradation that has never been described in animals and accelerate the development of plant-based chemical production for Phe-derived high-value chemicals.

Keywords: amino acid,phenylalanine,plant specialized metabolism,volatile,enzyme
Learning from Bats: New Strategies to Extend Healthspan and Improve Disease Resistance (BATPROTECT)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Synergy grants
Action type: ERC actions
Countries involved: Ireland,Singapore,Germany
Call: ERC Synergy Grants (ERC-2023-SyG, 2023)
Start date: 2024-06-01
End date: 2030-05-31
Duration (months): 72.0
Total project cost (EUR): 11882510.0
EU funding (EUR): 11882510.0
Participants: 4
Project status: SIGNED

The medical, financial, and emotional costs imposed by ageing and infectious diseases are major challenges for our societies. Strikingly, while past research has not provided solutions for extending human healthspan and preventing the harmful consequences of infections, nature has solved both problems in the only flying mammals – the bats. Among mammals, bats exhibit an exceptional longevity with little signs of age-related diseases. Despite being reservoirs for numerous deadly viruses, viral infections in bats are mostly asymptomatic due to unique immune system adaptations. The overarching goal of BATPROTECT is to achieve breakthroughs in our understanding of the molecular basis of bats’ extended healthspan and disease resistance to ultimately discover new directions to improve human healthspan and disease outcome. BATPROTECT integrates a team of world-leading experts in bat biology, genomics, immunology and gerontology to synergistically: (i) elucidate the molecular mechanisms that bats use to slow down expected ageing; (ii) identify the driving molecular mechanisms behind bats’ viral tolerance and limited age-related inflammation; (iii) uncover the genomic basis and evolution of extended healthspan and disease tolerance in bats; and, (iv) develop transgenic animal models to functionally validate the uncovered bat adaptations. We will generate 150 reference quality bat genomes, the novel immunological, bioinformatic, cellular and molecular tools required to take an integrative multi-omics approach and uncover the age and immune changes that occur in wild and captive bats across the ageing spectrum. We will identify the top regulators of longevity and immunity, using deep neural networks analyses, to functionally validate in our cellular systems and novel transgenic animal models- BatWorms and BatMice. Ultimately, we will provide a deeper understanding of extended healthspan and disease resistance and will pave the way for future therapeutics.

Keywords: bat biology,healthy ageing,antiviral responses,c elegans,genome sequencing,comparative gerontology,wildlife immunology,multi omics,ecology,evolution
Unlocking The Full Potential Of Quantum Computing and Quantum Ops Platform For Organizations Of All Sizes (QCentroid)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Spain
Call: EIC Accelerator 2024 - Short application (HORIZON-EIC-2024-ACCELERATOR-01, 2024)
Duration (months): 24.0
Total project cost (EUR): 1960000.0
EU funding (EUR): 1960000.0
Participants: 1
Project status: SIGNED

QCentroid Labs SL is a startup dedicated to making quantum computing accessible and affordable for companies and organizations of all sizes. The company offers the QuantumOps Suite, a unique platform designed to accelerate the development, testing, and deployment of quantum applications. This platform combines powerful benchmarking, orchestration, and AI tools to simplify quantum experimentation, reducing the time required from months to weeks. It enhances quantum application performance, integrates Quantum Processing Units with control electronics, and manages scalable systems capable of handling tens of thousands of qubits. Pending European patent protection, the platform integrates quantum and classical computing and automatically defines the best combination of algorithms and hardware for each use case. Quantum computing has the potential to revolutionize industries such as chemicals, finance, logistics, and climate tech. However, challenges like a lack of skilled talent, integration complexities, and the need for standardized tools hinder adoption. QCentroid addresses these issues by providing AI-assisted use case definition, synthetic data generation, intelligent integration of quantum and classical resources, and parallel execution of algorithms. QCentroid's user-friendly tools and APIs enable companies with limited quantum expertise to leverage this technology, ensuring seamless integration with existing IT infrastructure. The platform's ability to democratize access to quantum computing positions QCentroid as a strategic partner in advancing European quantum leadership. The business model includes a pay-as-you-go pricing model, licensing and subscription fees, and revenue sharing from algorithm execution and cloud and quantum computing reselling. By strategically navigating market dynamics, QCentroid aims to capture a significant share of the growing global QCaaS market, driving innovation, enhancing competitiveness, and promoting sustainability.

Keywords: quantum as a service,benchmarking,quantum hardware integration,qubo computation,quantum confidential computing,quantum machine learning
Deep ice - Deep learning. Artificial intelligence revealing the oldest ice climate signals (AiCE)

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: Italy,Germany
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): 1980998.0
EU funding (EUR): 1980998.0
Participants: 2
Project status: SIGNED

We are missing a central piece in the puzzle to understanding our Earth’s climate: Its dynamics fundamentally changed during the “Mid-Pleistocene Transition”, when some 1.2 million years ago the oscillation between warm periods and ice ages shifted its periodicity from 41 to 100 ka. A key set of information about this change was archived in the snow that fell at that time in Antarctica. At unique locations, that snow is still preserved today in the deepest ice layers– but does it still contain its original message? AiCE will answer this key question specifically using chemical impurity signals which make up a large part of the ice core record about past atmospheric conditions. For this purpose, we take a new approach to study the oldest and highly thinned layers at unprecedented detail. While conventional meltwater analysis delivers 1D cm-resolution signals, we go into 2D by imaging the chemical impurity distribution at micro-metric scale in the solid ice core. This way, we can retrieve crucial information that is inevitably lost by melting: The same ice matrix preserving the climatic record can act on it and ultimately destroy it through various processes, causing impurities to relocate away from their original layer. Hence, the goal is to identify the original layering, by detecting post-depositional change through analyzing highly-dimensional chemical images. However, human observers have clear limitations in detecting all the important details in such complex visual datasets. This is why AiCE will add deep learning to deep ice: Artificial intelligence (Ai) image analysis will be established through a comprehensive understanding of the chemical image features and their connection to post-depositional processes. With this, we can address the fundamental climate questions through deciphering deep ice – in Antarctica and elsewhere. Ultimately, AiCE could revolutionize how we interpret the oldest paleoclimate signals in ice cores and other archives.

Keywords: polar ice cores,ice core impurities,ice core record preservation,laser ablation,computer vision,beyond epica
Digital Forest Twins for AI-based Wildfire Assessment (WildfireTwins)

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: Germany
Call: ERC CONSOLIDATOR GRANTS (ERC-2024-COG, 2024)
Start date: 2025-06-01
End date: 2030-05-31
Duration (months): 60.0
Total project cost (EUR): 1986200.0
EU funding (EUR): 1986200.0
Participants: 1
Project status: SIGNED

Wildfires have a devastating impact on the environment, infrastructure, animals, and human lives. The complex physical dynamics paired with their unpredictable development makes wildfires a dangerous natural phenomenon that is difficult to counteract. Recently, digital twins have emerged as a concept that combines geometric modeling, image synthesis, and physical simulation with broad applications in predicting real world processes. This proposal aims to develop digital twins for wildfires – 3D models of ecosystems coupled with physical simulations – and to build AI-based tools for wildfire assessment. A wildfire twin with realistic physical simulations will have ground-breaking implications for firefighting services who will be able to use my framework as part of their decision making, resulting in an improved ability to combat wildfires, keep human lives safe and protect the environment. In contrast to existing wildfire simulations, a novel digital twin will provide real-time simulations of wildfires and complex 3D representations of ecosystems. By relying on state-of-the-art computer graphics technology, a digital twin will support generating photorealistic images and videos of wildfires. Synthetically generated data with high visual fidelity will profoundly accelerate the development and adoption of AI-based solutions for managing wildfires, as it addresses the bottleneck of capturing and curating expensive real-world training datasets. A digital twin that supports fast and accurate simulations of wildfires will have major impact on the analytical investigation conducted by the scientific community interested in understanding wildfires by accelerating the evaluation of hypotheses. Additionally, I plan to use the digital twin as a RobotGym – a virtual training environment for autonomous agents. A risk of this proposal is that a digital twin may not attain the required degree of realism – in which case it is still possible to identify options for higher quality.

Keywords: digital twin,wildfire modeling and simulation,tree combustion,neural networks for wildfire prevention,synthetic data generation
Satgeno bASKet Trial: Turning gene repair for devastating muscular dystrophies into reality (MyoPax)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Germany
Call: EIC Accelerator 2024 - Short application (HORIZON-EIC-2024-ACCELERATOR-01, 2024)
Duration (months): 60.0
Total project cost (EUR): 2499999.0
EU funding (EUR): 2499999.0
Participants: 1
Project status: SIGNED

Muscular dystrophies (MDs) are a group of monogenetic diseases characterized by progressive irreversible muscle wasting and result in loss of personal autonomy and premature death. The vast majority of patients rely on palliative care. Recent approaches to therapy only slow down disease progression and do not tackle the underlying genetic cause, and sustainable and safe drug delivery to muscle remains a major challenge. We have developed the Satgeno platform: an autologous cell-based gene therapy in which patients’ own muscle stem cells are repaired using virus-free, mRNA-mediated, CRISPR-derived gene editing tools in a one-time treatement. Satgeno leverages MyoPax’s patented stem cell technology to manufacture highly regenerative muscle stem (“satellite”) cell products called Primary Human Satellite cells-derived muscle stem cells (PHSats). PHSats can rebuild muscle tissue and, very importantly, generate new muscle stem cells in their respective niche. This enables us to specifically correct single point mutations across different MDs, deliver gene corrected healthy stem cells to functionally important muscles in MD patients, and thereby sustainably rebuild healthy muscle function. The technology has been preclinically tested, including biodistribution, toxicity and tumorigenicity assessment of PHSats. We are now clinic-ready. With the help of the EIC, we will conduct the first-in-human bASKet trial for a specific clinical phenotype of muscular dystrophies, limb girdle muscular dystrophies to prove safety demonstrate first efficacy of lead candidates of gene corrected PhSats products. This trial has already been recognised by Nature Medicine as one of “11 Clinical trials that will shape Medicine in 2023”. The Satgeno platform has the potential to target additional disease-causing mutations in MDs. We envision a future where individuals with muscular dystrophies overcome their condition's severe limitations.

Keywords: muscular dystrophies,myoblasts,satellite cells,crispr cas9,base editor,limbgirdle muscular dystrophies,regenerative stem cell therapy,advanced therapy medicinal product atmp
Research Infrastructures in a changing global, environmental and societal context (BECORI)

Framework: Horizon Europe — Excellent Science
Programme: Research infrastructures
Theme: Research infrastructures
Destination: Other destinations
Action type: Coordination and support actions
Countries involved: Belgium
Call: Belgian Presidency conference on research infrastructures (HORIZON-INFRA-2024-BE-CONF-ART195-IBA, 2024)
Start date: 2024-02-06
End date: 2024-08-05
Duration (months): 6.0
Total project cost (EUR): 180250.0
EU funding (EUR): 100000.0
Participants: 1
Project status: CLOSED

The aim of this project is to organise a Conference on Research Infrastructures during the Belgian Presidency of the Council of the European Union in the first half of 2024. The Conference will take place on 4-6 June 2024 at the Royal Library of Belgium (KBR). It will be a 1.5 day event combined with a half day dedicated to the visit of research infrastructures. The conference will focus on 3 main issues: 1) RIs as key players of strategic autonomy in a changing global context; 2) the societal and environmental impact of RIs and 3) the broad ecosystems of research infrastructures.

Keywords: research infrastructures,presidency conference,ri ecosystem,impact
CLimate science for Evaluation of changing Socioeconomic ImpactS (KLESIS)

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,Germany
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2024-10-01
End date: 2027-03-31
Duration (months): 30.0
Total project cost (EUR): 206641.2
EU funding (EUR): 206641.2
Participants: 3
Project status: SIGNED

Climate change (CC) poses numerous risks to society. Amongst these, recent work has quantified the impacts which adverse climate conditions can exert on economic growth and inflation by applying empirical models (EMs) to historical data. Evaluation of the extent to which historical and future CC is changing such impacts is crucial for translating these empirical insights into actionable knowledge. Two key examples are quantifying the historical anthropogenic contribution to intensified impacts, and accurately projecting their near-term changes. These tasks face challenges because climate model ensembles often under-estimate forced changes in impact-relevant conditions such as extremes, and near-term changes are affected by both greenhouse forcing and internal variability, with the latter amplifying or masking impacts over decadal timescales. KLESIS proposes to extend recent methodological developments in climate science to overcome these obstacles to an accurate evaluation of how climate impacts are changing. First, we will develop and apply statistical methods to attribute historical changes in impact-relevant climate conditions directly from observations. These methods will be tested in climate models, applied to observations and combined with EMs to evaluate the anthropogenic contribution to historical changes in climate impacts on the economy, crucial for informing loss and damage debates. Second, we will extend state-of-the-art decadal climate prediction systems to include impact-relevant conditions. Combining these with EMs will provide near-term estimates of climate impacts which accurately reflect the important and otherwise neglected role of internal climate variability. Finally, near-term projections of impacts on economic growth and inflation will be disseminated to stakeholders at the European Central Bank via a 6-month non-academic placement, to develop a framework for the assessment of physical climate risk in their quarterly macroeconomic forecasts.

Keywords: climate impacts,detection attribution,decadal climate prediction,climate econometrics