Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Early Identification of Dyslexia and DLD using Speech Production Measures with Children: An Innovative Cross-Language Approach (DISORDERED-SPEECH)

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: United Kingdom,Spain,France
Call: ERC ADVANCED GRANTS (ERC-2024-ADG, 2024)
Start date: 2026-01-01
End date: 2030-12-31
Duration (months): 60.0
Total project cost (EUR): 2498644.0
EU funding (EUR): 2498644.0
Participants: 3
Project status: SIGNED

Language problems are common in children, with ~7% incidence of significant spoken language problems (Developmental Language Disorder, DLD) and a further ~7% for written language problems (Developmental Dyslexia, DD). While there can be overlap in behavioural indices of DLD and DD (eg prosodic difficulties), no accepted causal theories satisfactorily explain such overlaps, and early identification remains difficult: only half of “late talkers”, toddlers who are not speaking by age 2, go on to develop DLD. Here we combine our innovative neural theory of child language acquisition (temporal sampling [TS] theory) with a novel speech production task to open a new research front in developmental language disorders, based on speech rhythm and the accurate production of prosodic patterns. We test both pre-school children aged 2.5 – 6 years and children with DD and DLD in 4 languages varying in rhythm type, English, French, Spanish and Basque. We apply our in-house state-of-the-art methods for measuring the similarity between the child’s speech amplitude envelope (AE) and pitch contour (PC) of multisyllabic items to oral targets. Prior English data show impaired AE and intact PC for DD, impaired AE and impaired PC for DLD, and consistent links between AE/PC production in typically-developing (TD) children and phonology/vocabulary. We test whether similar patterns characterise TD, DD and DLD across languages. Our focus on the accurate production of the AE/PC is entirely novel, exploits an automatic aspect of linguistic processing, applies to all languages, and may suggest new avenues for remediation. The speech production data acquired from >1000 children will further enable a machine learning approach to early diagnosis based on AE/PC. Our goal is to develop new tools for identifying DD and DLD which can apply across European languages. The frontier vision is that as AEs and PCs describe words in all languages, our approach may reveal new universals in language disorders.

Keywords: speech production,developmental dyslexia,developmental language disorder,machine learning
Memory Practices of the Afghan and Somali Diasporas in the USA and Italy. (MEMODIAS)

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: Social Sciences and Humanities
Countries involved: Italy,United States
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2022-11-01
End date: 2025-10-31
Duration (months): 36.0
Total project cost (EUR): 288859.2
EU funding (EUR): 288859.2
Participants: 2
Project status: SIGNED

Memory is a crucial resource for people in exile who have to deal with new and often hostile environments, since it keeps their transnational ties alive and shapes their collective identifications. Memory, however, is today increasingly subject to challenges, rearticulations and negotiations, especially when it refers to individual and collective practices, more and more confronted with global dynamics. MEMODIAS aims to explore these dynamics through an ethnographic inquire on the memory of conflict, exile and return among Afghan and Somali diasporas in Italy and the USA. Reflecting my previous mixed experience as researcher and practitioner in the field of migrant memories, my project enhances the implementation of participatory research methods and practices which can facilitate a circularity between the researcher and diaspora members as “co-researchers”. While exploring the interdiasporic forms of mnemonic solidarity in the transnational space between US and Italy, the project’s scientific and societal impacts will be strictly entangled and interdependent. MEMODIAS overall theoretical framework draws from Memory and Migration/Diaspora studies, Media, Art and Performance studies, Cultural studies, and Critical Global studies, subjects of my training activities which will include Gender studies. Research methods will be particularly focused on self-narrative practices. This approach will enhance the capability of participants to become active in policy making processes and to envisage new future possibilities of cohabitation. MEMODIAS dissemination and communication target scholars (through scientific publications), diasporas members, policy makers, journalists, educators and a broader public (through social media, civic events and an educational toolkit). Inspired by two brilliant supervisors while working in stimulating research environments in Italy and the US, I will have the chance to broaden my network and build future collaborations.

Keywords: diaspora,memory,participatory methods,media,arts,afghanistan,somalia,usa,italy
Beyond neuroInflammation: new Concepts to Elucidate the immune system’s vital role in Parkinson’s disease (BICEPS)

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: Life Sciences
Countries involved: Netherlands,Denmark,Germany,Serbia,Greece,Belgium,Türkiye,United Kingdom
Call: MSCA Doctoral Networks 2023 (HORIZON-MSCA-2023-DN-01, 2023)
Start date: 2024-11-01
End date: 2028-10-31
Duration (months): 48.0
Total project cost (EUR): 4520032.46
EU funding (EUR): 3946888.8
Participants: 17
Project status: SIGNED

Decades of research into Parkinson's disease (PD) have fallen short in fully comprehending its mechanisms, leaving us without a cure. Current treatments merely alleviate symptoms temporarily, but are unable to impede the progression of the disease. Clearly, PD research has hit a wall, and new approaches are needed. Recent discoveries of the involvement of the peripheral immune system in PD have sparked a groundbreaking proposition by BICEPS: PD must be considered a systemic disease with an immune response involving both brain and periphery. Thus, to revolutionize PD research, we must shift away from the neuro-centric approach of past decades and extend our focus to studying the immune system outside the brain. Furthermore, recent advancements, such as systems biology and artificial intelligence (AI)-driven data mining, diagnosis, and drug development, hold significant promise for advancing PD research. Therefore, BICEPS is uniting PD researchers, immunologists, and experts in AI and systems biology from leading European academic institutions, startup companies, and established pharmaceutical firms into a unique consortium. The primary objective is to train a new generation of PD researchers with interdisciplinary expertise in these fields. This ambitious goal will be realized through an intensive training program that encompasses cutting-edge methodologies, encourages innovation, nurtures transferable skills, and provides immersive, hands-on research experiences. Thereby, the BICEPS network aims to shape the future of PD research by adopting a fresh perspective and expediting the development of diagnostics and therapies for PD, with a particular focus on the immune system.

Keywords: peripheral immune system,macrophages,t cells,parkinson s disease,disease mechanisms
Targeting rogue DNA repair and genomic instability as novel toxicity mechanisms in C9orf72 ALS/FTD (epiC9repair)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Neuroscience and Disorders of the Nervous System
Panel description: Nervous system development, homeostasis and ageing , nervous system  function and dysfunction , systems neuroscience  and modelling , biological basis of cognitive processes and of behaviour, neurological and mental disorders – In humans and all other organisms
Countries involved: Germany
Call: ERC ADVANCED GRANTS (ERC-2024-ADG, 2024)
Start date: 2025-11-01
End date: 2030-10-31
Duration (months): 60.0
Total project cost (EUR): 2498905.0
EU funding (EUR): 2498905.0
Participants: 1
Project status: SIGNED

Repeat expansions are a major cause of neurodegenerative diseases, but causal therapies are not available. A (G4C2)n repeat expansion in C9orf72 is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) in Europe. Despite extensive research, the mechanisms linking these expansions to selective neurodegeneration remain poorly understood. Our project, epiC9repair, explores the novel hypothesis that genomic instability at the C9orf72 locus, driven by aberrant DNA repair and repeat-induced chromatin changes, is a critical factor in ALS/FTD pathogenesis. This project builds on our recent observation that the C9orf72 repeat is also a hotspot of DNA synthesis in post-mitotic neurons, and on recent findings in Huntington’s disease that cell type-specific somatic expansion of the pathogenic (CAG)n repeat drives neurodegeneration by unknown mechanisms. Using advanced CRISPR screens and innovative chromatin mapping techniques, we aim to uncover the DNA repair pathways that drive genomic instability in C9orf72 ALS/FTD and how these pathways contribute to neurodegeneration. In addition, we will investigate the role of epigenetic modifications in cell culture models and patient tissues, with a focus on identifying biomarkers that correlate with disease progression and regional neurodegeneration. These findings will inform studies in mouse models to test the therapeutic potential of targeting genomic instability. This multidisciplinary approach has the potential to transform our understanding of C9orf72-related diseases and paves the way for targeted therapeutic strategies that address the root causes of genomic instability in neurodegeneration.

Keywords: genomic instability,repeat expansion diseases,c9orf72,amyotrophic lateral sclerosis,frontotemporal dementia
Geometry Processing as Inference (EMERGE)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Computer Science and Informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Germany
Call: ERC ADVANCED GRANTS (ERC-2021-ADG, 2021)
Start date: 2022-09-01
End date: 2027-08-31
Duration (months): 60.0
Total project cost (EUR): 2496559.0
EU funding (EUR): 2496559.0
Participants: 1
Project status: SIGNED

Geometry Processing is concerned with algorithms and data structures for representing and processing three-dimensional shapes. Techniques in geometry processing have been developed over the last three decades and are now driving real-world applications in various industries. Geometry processing algorithms may be interpreted as components of digital signal processing or machine learning, solving inference problems: given an incomplete description of the geometry, commonly based on point samples, the concept or process underlying the observations - the surface - is recovered (unsupervised feature learning) and then may be smoothed (filtering), segmented (clustering), or interactively modified (semi-supervised learning). To facilitate these operations the surface representation is adjusted (transcoding, resampling). However, using the algorithms and data structures in geometry processing for data living in higher dimensional spaces requires fundamentally new methods in geometric computing. Emerge presents a research program aiming at making geometry processing methods available as a set of tools in data science. Emerge will introduce fundamentally new concepts for surface representations and computational methods for surface interrogation in dimension beyond three -- providing useful tools in various science and engineering disciplines. The thesis of Emerge is that the resulting extensions and generalizations of geometry processing techniques will be fruitfully complementing and adding to the state of the art in processing large amounts of data. Any progress in this direction will have profound impact, as the proliferation of sensors and data processing has led to most of the current societal challenges (climate change, global biological risks, population growth, global policy making, energy) coming with enormous amounts of unstructured quantitative data to be analyzed.
Exploration Information System (EIS)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Industry
Destination: Increased Autonomy in Key Strategic Value Chains for Resilient Industry
Action type: Research and Innovation actions
Countries involved: Finland,Germany,France,Sweden,Spain,South Africa,Czechia,Brazil
Call: Innovation for responsible EU sourcing of primary raw materials, the foundation of the Green Deal (RIA) (HORIZON-CL4-2021-RESILIENCE-01, 2021)
Start date: 2022-05-01
End date: 2025-10-31
Duration (months): 42.0
Total project cost (EUR): 7497035.0
EU funding (EUR): 7497032.0
Participants: 18
Project status: SIGNED

Exploration Information System (EIS) proposal has been compiled by a consortium, which consists of 18 partners from leading research institutes (4), academia (5), service providers (4) and industry (4). The consortium members come from six European Union member states (FI, FR, DE, ES, CZ, SE) and South Africa. One associate member of the consortium comes from Brazil. This consortium represents the main metal producing regions of Europe: Fennoscandian Shield, Iberian Pyrite Belt and Central European Belt. These economically most important metallogenic belts of the EU have diverse geology with evident potential for different types of new mineral resource. The mineral deposits in these belts are the most feasible sources of critical, high-tech and other economically important metals in the EU. Furthermore, the project has reference sites in South Africa and Brazil. The project consortium has also a vast international collaboration network, e.g. 50% of the Advisory Board members have been invited from outside EU. EIS will develop new data analysis methods by applying artificial intelligence, machine learning, deep learning into mineral prospectivity mapping together with new geomodels and mineral systems modelling. Methods developed reduce the current high exploration costs and improve the accuracy of the targeting of the early phase exploration. This makes mineral exploration responsible in terms of energy efficiency or minimizing footprint of mineral exploration on nature as the aim is to make most out of the already existing exploration data. Project will apply UNFC code to harmonize the diverse population of mineral deposits and occurrences which will be used as training sites and validation data sets in prospectivity mapping for critical raw materials within EU. In addition, tools will be tested for secondary raw materials prospectivity. Project will also raise awareness of general public on the importance of critical raw materials to the EU's economy and welfare.

Keywords: artificial intelligence,machine learning,mineral exploration,mineral prospectivity modelling,geographical information systems,geoinformatics,mineral systems,battery minerals
FAIR EArth Sciences & Environment services (FAIR-EASE)

Framework: Horizon Europe — Excellent Science
Programme: Research infrastructures
Theme: Research infrastructures
Destination: EOSC ecosystem
Action type: Research and Innovation actions
Partnership: EOSC (co-programmed)
Countries involved: France,Italy,Netherlands,Ireland,Belgium,United Kingdom,Portugal,Greece,Germany
Call: Innovative and customizable services for EOSC (HORIZON-INFRA-2021-EOSC-01, 2021)
Start date: 2022-09-01
End date: 2025-08-31
Duration (months): 36.0
Total project cost (EUR): 4871500.0
EU funding (EUR): 4738125.0
Participants: 27
Project status: SIGNED

Earth and environmental sciences require a large panel and volume of data from satellite, in-situ observations, models, omics experiments... Earth system domains are interconnected and even if interfaces between domains appear of primary importance for several studies with large societal impacts, such as climate change, agriculture and food, human safety and health, the present digital architecture is based essentially on distributed and domain-dependent data repositories inducing real difficulties for integrated uses of all the environmental data. To go beyond this state-of-the-art, the overall objective of FAIR-EASE is to customize and operate distributed and integrated services for observation and modelling of the Earth system, environment and biodiversity by improving the TRL of their different components implemented in close cooperation with user-communities, the European Open Science Cloud and research infrastructures in their design and sustainable availability. The project will: (1) Improve a FAIR-EASE data discovery and data access service, relying on pre-operational existing services, in order to provide users with an easy and FAIR tool for discovery and access to environmental multidisciplinary and aggregated data-sets as managed and provided by a range of European data infrastructures; (2) Set up a FAIR-EASE Earth Analytical Lab, with EOSC connectivity supporting, through web-based interfaces, predefined processing tools and on-demand data visualization services for remote analysis and processing of heterogeneous data facilitating the cross-disciplinary collaboration, reducing the time to results and increasing productivity; and (3) Develop a number of multidisciplinary Use Cases (UCs) to contribute requirements for the FAIR-EASE system components and to validate and demonstrate the capabilities of the FAIR-EASE service for supporting open science.

Keywords: earth system sciences,multidisciplinary fair data discovery and access,virtual analysis platform,virtual research environment
Digital twin-based approach to improve resilience of slab tracks in a warming climate (TwinsTrack)

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: Italy,United Kingdom
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2025-12-01
End date: 2027-11-30
Duration (months): 24.0
Total project cost (EUR): 209483.28
EU funding (EUR): 209483.28
Participants: 2
Project status: SIGNED

We are in a warming climate. Predictions indicate that the world is on track for a warming of 1.5 ℃ in the most optimistic situation. This is very bad news for railway slab tracks utilized all around the world, since the intensified extreme heat waves in a warming climate can induce severe slab track failure and cause lethal outcomes like train derailments. Furthermore, the rise in life-cycle carbon emissions due to increased track maintenance workload and material consumption worldwide in a warming climate is estimated to be around 60 million tonnes, which can be used to manufacture about 120 million cars. However, we are not fully prepared to this challenge because of a lack of useful tools to predict track performance and arrange maintenance activities in a warming climate. Thus, this TwinsTrack project aims to contribute to a better understanding of slab tracks' mechanical behavior in a warming climate and practical maintenance strategies to improve their climate adaptability. In this project, the applicant will (i) develop integrated digital twin models of slab tracks for performance prediction in a warming climate; (ii) design various climate-adaptive maintenance measures for slab tracks; (iii) develop a multi-objective optimization approach to select optimal types and design details of maintenance measures to not only maximize the safety of slab tracks, but also ensure their best environmental and economic performance. The outcomes of this TwinsTrack project will not only prepare engineers for the climate crisis but also inform policymakers of the urgent need for action. This will not only reduce the risk of structural-failure-induced accidents but also decrease carbon emissions and maintenance costs of slab tracks by an estimated 20% to 30% in a warming climate.

Keywords: railway tracks slab tracks railway engineering digital twins
Morphological evolution in island birds: underlying molecular and ecological mechanisms (ISLADAPT)

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: Portugal
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2023-09-01
End date: 2025-08-31
Duration (months): 24.0
Total project cost (EUR): 172618.56
EU funding (EUR): 172618.56
Participants: 1
Project status: CLOSED

Understanding body size variation across and within species has been a main quest in evolutionary biology, but many of the mechanisms underlying body size evolution remain elusive. This is largely because of the complex interplay of different factors such as climate, diet and interactions with competitors and predators. Island are simplified ecosystems with a reduced number of habitats, species diversity and number of predators, and generally milder climate, making them ideal natural laboratories for dissecting the intricate mechanisms underlying body size evolution. ISLADAPT aims to unravel mechanisms of morphological evolution and species diversification in birds, using both macro and microecological-evolutionary approaches based on state-of-the-art methodologies such as metabarcoding and Bayesian analysis. First, this project will use data from museums and literature for endemic island species and their closest relatives from mainland worldwide (WP1) to unravel the underlying mechanisms, such as changes in the ecological niche, geographical features and phylogeny, that explain the systematic morphological changes on islands (WP2). Second, ISLADAPT will use field-based data to test the hypothesis that morphological changes on islands are linked to changes in the feeding niche breadth. To do this, faeces and biometric data will be analysed from 20 bird species from Gulf Guinean Island and the nearby mainland, and diet composition will be identified with metabarcoding techniques (WP3). Third, ISLADPT will examine the relationship between bird morphological evolution and lineage diversification on islands by using biometric data from museums and phylogenetic information for three archipelagos: New Caledonia, the Gulf of Guinea and Salomon Islands (WP4). ISLADAPT will therefore address central, open questions in island biology and reveal the underlying mechanisms, thereby providing a major contribution to our understanding of island adaptation.

Keywords: morphology,island patterns,birds,diet,metabarcoding