Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Motion Control Systems of Multi-Actuated Ground Vehicles (MOCO)

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: Information Science and Engineering
Countries involved: Lithuania,Poland,France,Spain,Belgium,Netherlands,Austria,Germany,Korea, Republic of,Mexico,South Africa,Japan
Call: MSCA Staff Exchanges 2023 (HORIZON-MSCA-2023-SE-01, 2023)
Start date: 2025-01-01
End date: 2028-12-31
Duration (months): 48.0
Total project cost (EUR): 627571.43
EU funding (EUR): 598000.0
Participants: 14
Project status: SIGNED

MOCO is based on an intensive staff exchange to promote joint research and training between 14 universities and industrial companies from 8 European countries, Japan, the Republic of Korea, Mexico and South Africa. The proposal innovates the methods of motion control and creates a comprehensive framework for the design, identification and validation of systems for the domain of multi-actuated vehicles. With a focus on driving and functional safety, energy efficiency, driving performance and ride comfort, MOCO is dedicated to improving the robust operation of automated and electric vehicles under various driving conditions, including uncertain road surfaces, severe conditions and terrains, as well as scenarios characterised by limited information and communication infrastructures. Research and innovation activities will focus on the following: (i) Development of sophisticated tools for estimating parameter variations and identifying system characteristics using hybrid model-based and data-driven methods; ii) Design of advanced vehicle motion control systems considering automated driving functions, multi- actuated configurations and different electric powertrain topologies using robust and predictive approaches; iii) Validation and verification of real-time software and hardware-based demonstrators using state-of-the-art methods; iv) Facilitate practical recommendations, based on the MOCO results, for researchers, OEMs and suppliers working on automotive and interdisciplinary applications; v) Professional development of participating research and engineering staff; vi) Knowledge transfer and promotion of the exchange of expertise between the partners. In addition to research and training, the project will focus on relevant networking, dissemination and exploitation initiatives to maximise its impact. MOCO will cultivate the necessary competences and skills that are essential to foster successful innovation in the emerging mobility domains.

Keywords: vehicle dynamics,automotive engineering,electric vehicles,vehicle state estimation,motion control
Against prostheses abandonment: immersive and low-cost platform for the rehabilitation of upper-limb amputees (BRAINmade)

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: Italy
Call: ERC PROOF OF CONCEPT GRANTS (ERC-2023-POC, 2023)
Start date: 2024-01-01
End date: 2025-12-31
Duration (months): 24.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: SIGNED

Up to 44% is the abandonment rate of upper-limb prostheses. The lack of training and rehabilitation is among the reasons underlying the high rejection rate. When available, traditional treatments lead to ineffective results because they are repetitive, tedious, and discouraging. When considering the EU investments in prosthetic development (173.5 million, period 2019-2022) and the costs granted by the national health system for assistance, this problem gets worse. BRAINmade proposes a paradigm shift to change the current situation. Within the ERC-funded HANDmade project, we exploit the idea that natural hand usage shapes behavior and brain activity. We reinforced the conviction that long-term, continuous, specialized training is prodromal for prosthesis acceptance. By integrating virtual reality (VR) scenarios controlled by electromyographic (EMG) activity in upper-limb amputees, our experimental data on a 4-week long motor training show high motor performance and embodiment even of non-anthropomorphic prosthesis (e.g., tweezers). Beyond being highly specialized as it contains the hand degrees of freedom, we realized that this virtual bionic tool simplifies action intention and execution by exploiting motor properties hardwired in the brain. Thus, the difficult transition toward prosthesis acceptance may imply a progressive acquisition of new motor skills and adopting BRAINmade prosthetic devices built on an individual's expertise (and neural resources). The proposed motor training protocol also integrates fully-customized inkjet-printed and low-cost EMG sensors - designed on the patient's stump and residual muscle activity - and daily monitoring of the motor performance. Those data will serve prosthesis fabrication and feed freely-available databases for developers in the R&D sectors of upper-limb prostheses. With the ultimate project goal of reducing prosthesis abandonment, our idea can significantly impact amputees' lives and transform rehabilitation practice.
Implantable sensors and ultrasonic data link with triggered bioresorption for next-gen wireless cardiac monitoring (2ND-CHANCE)

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: Türkiye
Call: ERC STARTING GRANTS (ERC-2021-STG, 2021)
Start date: 2022-06-01
End date: 2027-05-31
Duration (months): 60.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 1
Project status: SIGNED

Cardiovascular diseases are the leading cause of death globally. Monitoring heart functions and ischemia is critical for survival after cardiac surgery. Standard monitoring methods such as echocardiogram and ELISA blood test provide single-time measurements. They are available only in hospitals, and there is no continuous monitoring method after patients are discharged, leading to a high rate of recurrent heart failures and rehospitalization. Implantable medical devices are used for treatment of various disorders. However, their non-resorbable nature necessitates an implant removal surgery that puts additional risk of infection and stress on patients and limits their use in postoperative monitoring. Bioresorbable implants may soon revolutionize postoperative monitoring methods. The surgeon will implant a small patch onto the heart during surgery, enabling continuous cardiac monitoring and early alerts for heart failure. This will reduce sudden attacks, rehospitalizations, and financial burden of health care. Then, once the monitoring period ends, triggering with a light source will dissolve the implant; thus, providing a significant second chance for the survivors of cardiac failure without the burden of secondary surgery. The technological advancements to bring this vision to the clinic are not available yet. 2ND-CHANCE will facilitate this vision by building components of next-generation wireless implants with triggered bioresorption for cardiac surgery through ground-breaking approaches. This interdisciplinary project aims to develop 1) bioresorbable sensors compatible with the in-body environment, 2) battery-free ultrasonic communication, and 3) encapsulation layer with triggered bioresorption, followed by 4) integration and animal tests. The versatility of the 2ND-CHANCE will also yield potential breakthroughs in fields where monitoring of tissues and biomarkers is crucial such as neurology and ophthalmology, and open new research perspectives.

Keywords: implantable medical device,stretchable sensor,ultrasonic transducer,bioresorbable materials,electrochemical sensor,triggered bioresorption,wireless data transmission
Enabling personalised breast cancer pathways and community based risk profiling and screening, through wholly novel RF tissue measurement (Micrima Mi-Scan)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: United Kingdom
Call: EIC Accelerator 2024 - Short application (HORIZON-EIC-2024-ACCELERATOR-01, 2024)
Duration (months): 18.0
Total project cost (EUR): 2400000.0
EU funding (EUR): 2400000.0
Participants: 1
Project status: SIGNED

12.9% of women are estimated to experience breast cancer, at some point in the lifetime. The great news is there is a 99% survival rate, if caught whilst still localised in the breast. Unfortunately survival drops to 37% once that cancer has been able to spread to lymph nodes and beyond. Ultimately around 10% of women, who get breast cancer, will die as a result of late detection. Micrima has been at the forefront of breast cancer diagnostics for some 20 years, developing wholly novel radio wave technology. for the first 17 years the company focused on breast imaging but a change of management team brought a change of direction. Their experience of the breast diagnostics market led them to look at how the technology could most impact the patient pathway. The main issue with current detection is its reliance on X-Ray Mammography. It's use of ionising radiation means it can only be used infrequently (giving cancer time to spread between scans) and its poor detection rates in "dense" breasts limits detection. This impacts detection in ~50% of women who are currently screened and prevents screening of younger women who have a much high proportion of dense breasts. Significant investment is being made to develop new mammography techniques and wholly novel technologies to address dense breast sensitivity. However, they all require an initial Mammogram to identify dense breasts, before they are used. The Mi~Scan device can quickly, safely and efficiently measure breast density before an imaging technique is selected, meaning women can have the best test to identify cancer, in their specific tissue type first time. Furthermore, with enough data collected the Mi~Scan data should identify the signs of cancer from it's quick 1 minute scan, that can be performed on all women, quickly, safely, in any location and pain free broadening the scope of screening to all women and only referring in women who are high risk or identified as having cancer.

Keywords: mi scan transforms breast cancer screening pathways in radiology through upfront tissue density measurement and in the community through integration with breast cancer risk models and cancer detectio
Battery Cell Assembly Twin (BatCAT)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Energy
Destination: Cross-sectoral solutions for the climate transition
Action type: Research and Innovation actions
Partnership: Batteries (co-programmed)
Countries involved: Norway,Germany,Spain,Italy,Luxembourg,United Kingdom,Slovenia,France,Austria,Denmark
Call: Advanced digital twins for battery cell production lines (Batt4EU Partnership) (HORIZON-CL5-2023-D2-01, 2023)
Start date: 2024-01-01
End date: 2027-06-30
Duration (months): 42.0
Total project cost (EUR): 5106384.0
EU funding (EUR): 5106384.0
Participants: 18
Project status: SIGNED

BatCAT is the project that realizes the manufacturability programme from the BATTERY 2030+ Roadmap, creating a digital twin for battery manufacturing that integrates data-driven and physics-based methods. It develops a cross-chemistry data space for two technologies, (1) Li-ion and Na-ion coin cells and (2) redox flow batteries, addressing a triple challenge in digital manufacturing: (i) Design, (ii) operation, and (iii) trust. (i) By improved product and process design and optimization, product quality and process efficiency increase. This requires decision support that makes complex decision problems accessible to human decision makers. The digital twin technology from BatCAT provides an interpretable industrial decision support system (IIDSS) based on multicriteria optimization. Surrogate modelling connects the high-level analysis firmly to ground-truth data. (ii) Process operation and control is improved by acquiring and analysing sensory and operando data at real time, facilitating live interventions within an Industry 5.0 real-time environment. BatCAT follows a rigorous approach to actionable modelling, combining data-driven methods with deductive reasoning based on ontologies and formal methods (answer set programming and BPMN-based model checking) to guarantee a reliable behaviour. (iii) The approach from BatCAT produces trustworthy models: Machine learning always retains a clearly characterized connection to the ground truth, and any decision support or decision making from inductive reasoning is safeguarded by constraints through formal deductive reasoning. All our models and methods are explainable, and all our data are FAIR and explainable-AI-ready (XAIR). The digital twin is validated in pilot production lines for (1) coin cells and (2) redox flow batteries, proving its transferability across chemistries. The project is closely connected to the Advanced Materials 2030 Initiative, BIG-MAP and BATTERY 2030+, BEPA, DigiPass CSA, EOSC, EMMC, and the Knowledge Graph Alliance, ensuring a community and industry uptake of the results.

Keywords: explainable artificial intelligence manufacturing of coin cells molecular and multiscale modelling process data technology redox flow battery manufacturing
Uncovering the cortical cellular basis of specificity and chronicity of pain (PAIN ENSEMBLES)

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-2023-ADG, 2023)
Start date: 2025-02-01
End date: 2030-01-31
Duration (months): 60.0
Total project cost (EUR): 2468700.0
EU funding (EUR): 2468700.0
Participants: 1
Project status: SIGNED

Chronic pain remains a fundamental unsolved puzzle in biology and an unmet global challenge in clinical practice. Progress is limited by major gaps in knowledge on neural substrates, owing to overwhelming redundancy of implicated regions and pathways with several pain-unrelated sensory, cognitive and emotional functions as well as lack of understanding on the origins of plasticity and cellular substrates for diverse psychosocial and environmental influences on pain. Here we propose that neocortical neuronal ensembles, i.e., discrete cohorts of co-active neurons intermingled within seemingly redundant pathways, represent a mechanistic correlate for imparting specificity to pain perception, while also providing adaptive flexibility to context and introspective bodily states, and serve as convergent substrates for divergent influences, such as past experience of pain, fear memory and expectation. Using cutting-edge in vivo methods, such as multiphoton imaging of activity and structure, electrophysiological parallel recordings of hundreds of neurons, fine-grained behavioral analyses, activity-based cell tagging approaches, opto-chemogenetic manipulations and single cell transcriptomics in mouse models of acute and chronic pain, we aim to (i) identify neocortical pain ensembles that delineate pain from other sensory percepts, valence states and cognitive functions, and determine their composition, connectivity, coordinated activity in local and across distant networks and functional relevance to pain, (ii) study their dynamic plasticity over the transition from acute to chronic pain and delineate bottom-up (peripheral-spinal) and top-down (brain intrinsic) influences, with a focus on studying the role of the salience network in channeling context, expectation and fear memory and its dysfunction in chronic pain and (iii) study the potential of reversing plasticity of neuronal ensembles by non-invasive neurostimulation and behavioral approaches for achieving pain relief.

Keywords: chronic pain,neuronal ensembles,salience detection and plasticity
Validation of treatment decision algorithms for childhood tuberculosis at low levels of healthcare in high burden countries - effectiveness, implementation, and integration into policy and practices (Decide-TB)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Public-private partnerships
Destination: Global Health EDCTP3
Action type: Research and Innovation actions
Partnership: EDCTP3 (JU-JTI)
Countries involved: France,Zambia,South Africa,Mozambique,United Kingdom,Germany
Call: Promoting implementation of research results into policy and practice (HORIZON-JU-GH-EDCTP3-2022-01, 2022)
Start date: 2023-04-01
End date: 2027-03-31
Duration (months): 48.0
Total project cost (EUR): 5299965.0
EU funding (EUR): 5299965.0
Participants: 13
Project status: SIGNED

Childhood tuberculosis (TB) remains globally underdiagnosed and untreated. In 2022, WHO conditionally recommended the use of treatment decision algorithms (TDAs) to improve the diagnosis of pulmonary TB in children <10 years and called for the external validation of two suggested TDAs for children. The Decide-TB project aims to generate evidence for the implementation of a comprehensive TDA-based approach for TB in children living in high-burden, resource-limited countries, at district hospital and primary health centre levels, and to facilitate the integration of this evidence into practice and policy. As an interdisciplinary consortium of researchers and national TB programs (NTPs), we will conduct a programmatic pilot of WHO-suggested TDAs, also integrating specific TDAs for children living with HIV and/or those malnourished, and severity assessment for shorter treatment decision in non-severe TB disease. Clinical mentoring tools and a Clinical Decision Support System will be developed. District information systems will be strengthened to collect individual data for program monitoring and supervision by NTPs, and for research. The TDA-based approach will be tested in a pragmatic stepped wedge cluster-randomized trial, including effectiveness, implementation, socio-behavioural, economics and policy research components. The diagnostic accuracy of TDAs will be assessed in a parallel meta-analysis of children with presumptive TB from recent studies led by consortium members. The pragmatic trial and meta-analysis will contribute to external validation of the WHO-suggested TDAs. Engagement of key stakeholders and decision-makers throughout the project will support adoption into international and national policies and into clinical practice. Through validation of TDAs, widespread policy adoption, and translation into clinical practice, Decide-TB will increase access to safe and effective TB management for children, thus reduce TB mortality and contribute to SDG3.

Keywords: tuberculosis,children,treatment decision algorithms,digital,pragmatic trial,effectiveness,implementation,feasibility,acceptability,cost effectiveness,clinical practices,policy
Studying the landscape of axion models and providing software tools for the next generation of axion searches (AxiTools)

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: Italy
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2023-01-01
End date: 2024-12-31
Duration (months): 24.0
Total project cost (EUR): 172750.08
EU funding (EUR): 172750.08
Participants: 1
Project status: CLOSED

This project is to extend our knowledge about the landscape of viable axion models. Axions originally emerged as a solution to the strong CP problem and are excellent dark matter candidates, thus providing highly motivated extensions of the Standard Model. The project focuses in particular on models that solve further puzzles, e.g. improving the so-called Peccei-Quinn quality problem. To find such models, it considers QCD axions that are lighter or heavier than the usual benchmark models or axion-like particles from astrophysical sources. Moreover, the next generation of experimental searches need accurate computations that match the expected precision of the experiments. Advancing our understanding of the models and their predictions, and confronting them with experimental data, will require the development of new software codes and possibly new computational techniques. It will further require combining the expertises of the Researcher (phenomenology, statistical analyses) with those of the Supervisor/Host (theoretical computations, model building). Learning about the most viable axion models will not only increase our knowledge but also guide future experimental searches. By making software codes and data sets publicly available, the project will contribute to the sustained growth of this exciting field of research. These tools will provide researchers with a solid basis for ongoing and future research activities in axion physics. In turn, the project can benefit from community feedback on its open-science products, ultimately improving the efficiency and quality of the underlying research.

Keywords: axions,axion like particles,astroparticle physics,global fits,dark matter