Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Historic Landscape and Soil Sustainability (HiLSS)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-10-01
End date: 2022-12-31
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 1
Project status: CLOSED

The HiLSS Project aims to investigate the relationships between sustainability and landscape heritage with particular reference to soil loss and degradation over the long term. The project will take a multidisciplinary approach that combines archaeology, Historical Landscape Characterisation (HLC), geosciences, and computer-based geospatial analysis (GIS - Geographical Information Systems) and modelling (RUSLE - Revisited Universal Soil Loss Equation). The research objectives of the HiLSS project are to quantify the impact of human activities during the Late Holocene in order to create spatial models which can inform the development of sustainable conservation strategies for rural landscape heritage. This project will focus on two mountainous regions that present historical and cultural similarities but located in different climatic zones of Europe (1- Tuscan-Emilian Apennines, Italy; 2- Northern-mid Galicia, Spain). In previous HLC studies, land-use has been evaluated from the perspective of cultural heritage, whereas RUSLE have used it as a proxy for the land-cover of an area and its effect on soil erosion. The HiLSS project will propose an innovative methodology that combines both the historic/cultural values and the environmental values of land-use to inform development of a model for the sustainable conservation. By considering the different agricultural land-use HLC types in GIS-RUSLE modelling, it will be possible to quantify the effect on soil loss for each HLC type and consequently to devise more environmentally sustainable management for each type. Environmental sustainability and historic landscape conservation are typically treated as two separate fields, but the HiLSS project will develop a transformative model for interdisciplinary research, proposing a new way to embrace both cultural and natural values as components of the same landscape management plans.
Towards automated fission-track age determination via artificial intelligence (FTAIGE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Environment and Geosciences
Countries involved: Germany
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-10-01
End date: 2022-10-31
Duration (months): 13.0
Total project cost (EUR): 94686.8
EU funding (EUR): 94686.8
Participants: 1
Project status: CLOSED

Understanding and predicting the continuous change of the environment is crucial for scientists, economists, policy makers and ultimately for the entire society. Geochronology is the art of measuring the timing of processes on Earth and thus the key for understanding the past and making accurate predictions for the future. Techniques to model past and future events have evolved to an advanced state and geochronology has to keep track with this by providing accurate, precise and statistically robust age data. Fission-track dating is a well-established geochronological method, which is based on the manual counting and length measurement of nuclear damage tracks (i.e. fission tracks) in minerals by means of optical microscopy. Due to the complexity of microscopic images and objects to be studied, the operator-based optical counting remains the most widely applied approach until these days. However, the manual approach has serious limitations especially with respect to the number of grains being dated as well as the comparability and reproducibility of the results. This project is an attempt to automatize large parts of the slow and tedious manual procedure. It will combine fission-track dating with artificial-intelligence (AI)-assisted image analysis exploiting the capability of convoluted neural nets (the AI) to be ‘taught’ to detect user defined objects in an image. The expected result is a protocol that can be freely used and refined by all geochronology laboratories to produce age data meeting the high requirements of cutting-edge research. On the way of developing this protocol the experienced researcher will obtain hands-on training in the Python language and artificial intelligence, whereas the supervisor will get a deep insight into fission-track geochronology. The results will be communicated to a broad audience and provide a stable basis for future research inside and hopefully far outside geosciences thereby underlining the project’s societal importance.

Keywords: fission track,thermochronology,apatite,image analysis,climate controlled processes
Mathematical modelling of soft tissues (SOFT-TISSUES)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Mathematics
Countries involved: Ireland
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2017-03-01
End date: 2019-02-28
Duration (months): 24.0
Total project cost (EUR): 175866.0
EU funding (EUR): 175866.0
Participants: 1
Project status: CLOSED

Dr Valentina Balbi is an Italian national, trained in Applied Mathematics in Italy and in Mechanics in France and at Stanford University. She publishes articles in high-impact factor journals, at the frontiers of applied mathematics and other disciplines. She is requesting funds for two years, to work with Professor Michel Destrade and join his group of Biomechanics at NUI Galway, Ireland. The overall scientific aim of the Project is to improve understanding of the nonlinear mechanics of soft biological tissues, including growth, buckling and pattern formation, mechanics of organs such as the eye, the brain and the skin. Ongoing work in these areas is still in its infancy, and the project proposes a bottom-up approach to their investigation. There is particular attention placed on applications of the results to biomedical engineering, numerical simulations and engagement with the general public, especially through a judicious choice of secondment periods. As the work progresses, the emphasis will shift from theoretical modelling (relying on the Applicant’s expertise) to experimental validation and numerical simulations (using the Host Laboratory’s expertise and facilities), with a view to medical applications (taking advantage of the partners institutions’ experience in training, communication, scientific management, intellectual property, etc.) The training programme is exhaustive, and will allow the researcher to grow as a world-class leader for these issues, which are fundamental in healthcare for the benefit of society. She will possess a unique blend of knowledge and expertise, allowing her to communicate and work with applied mathematicians, biomedical engineers and clinicians in industry, health services and academia.

Keywords: soft tissues,skin,brain,morphogenesis,nonlinear elasticity,linear and nonlinear stability analysis,buckling,numerical simulations,finite element methods,experimental techniques
BoneScreen: Opportunistic Osteoporosis Screening in Computed Tomography (BoneScreen)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Prevention, Diagnosis and Treatment of Human Diseases
Panel description: Medical technologies and tools for prevention, diagnosis and treatment of human diseases, therapeutic approaches and interventions, pharmacology, preventative medicine, epidemiology and public health, digital medicine
Countries involved: Germany
Call: Call for proposals for ERC Proof of Concept Grant (ERC-2020-PoC, 2020)
Start date: 2020-11-01
End date: 2022-04-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Worldwide, an osteoporotic fracture occurs every three seconds; most of them in Europe, where the economic burden has been estimated at €37 billion per year and lost years of life surpass most major cancers. This is hard to comprehend, given that osteoporosis is a preventable, treatable disease, if diagnosed at an early stage. As current state-of-the-art screening methods are neither sufficiently available nor accurate, there is an urgent need for readily available and accurate screening systems. BoneScreen will fill this gap and provide a low-cost and accurate screening method, available for millions of patients. BoneScreen introduces a fully automated solution to evaluate existing computed tomography data of patients. BoneScreen will calculate volumetric bone mineral density (vBMD), the most reliable and accurate single predictor of a patient’s fracture risk. In contrast to existing methods, BoneScreen is fully automated; it is purely non-invasive and excludes any additional radiation dose or patient discomfort; it is fully calibrated, yielding high precision and allowing for the application of established diagnostic categories; it works for all vertebral levels, allowing for inclusion of scans with variable coverage. Additionally, the functionality of BoneScreen is easily extendable, e.g. for detecting fractures or metastasis. The overall goal of this proposal is to initiate the start-up process for a company commercializing the research developments to date. Specific objectives are to (1) increase the technology readiness level of our current research software to reliably work in different hospital environments; in particular we will include an automated calibration, allowing for accurate processing in >98% of cases; (2) increase the awareness of the possibilities provided by such a screening tool, both in the academic and non-academic radiology community; and (3) develop a strategy for marketing and securing IPR.

Keywords: osteoporosis,screening,fracture,life quality,computed tomography,artificial intelligence,machine learning,image processing,bone mineral density
TRANSATLANTIC APPROACHES TO CONTEMPORARY LITERATURE IN THE ERA OF TRUMP (TRAMP)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Ireland,United States
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-10-01
End date: 2023-09-30
Duration (months): 36.0
Total project cost (EUR): 257561.28
EU funding (EUR): 257561.28
Participants: 2
Project status: CLOSED

This Action addresses one of the societal challenges addressed by the EU’s H2020 strategy, “Europe in a changing world—inclusive, innovative and reflective societies,” by focusing attention on the breakdown of the postwar liberal consensus between Europe and the United States—visible in the resurgence of right-wing populisms and hegemonic nationalisms in the last decade—by means of interdisciplinary research in in the fields of literature, cultural studies, and politics. By applying a transatlantic approach to the analysis of contemporary American and European literary texts, the research component of the Action aims to renew and actualize the modes of interpretation in the field of transatlantic literary studies, to produce critically-informed readings of contemporary fiction that is responding to the crisis of transatlanticism (understood as a shared belief system), and thus to offer insight into systems of representation, the articulation of structures of power and knowledge, and how these can be re-imagined through literary fiction. The Action will be undertaken by Dr. Resano at Dartmouth College (United States) and UCD (Ireland) under the supervision of Prof. Donald Pease and Prof. Liam Kennedy, two leading experts in the fields of American Studies, literary theory, and cultural studies. It is designed to contribute to the Fellow’s career development and employability through the acquisition of core research and transferable skills, to strengthen the existing collaboration between two leading research centers in Europe and the US—thus contributing to the H2020 strategy of spreading excellence and strengthening Europe’s competitiveness—and to inform public opinion and wield influence in the debates around the rise of populisms in Europe and the US in the last decade, offering a renewed and innovative perspective on some of the priorities identified in the EU’s H2020 framework, thus contributing to Europe's ability to address societal challenges in the future.

Keywords: american studies
Optimal use of hospital resources and intervention using suPAR for improving prognosis and care for patients with COVID-19 (RISCinCOVID)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Denmark
Call: SME instrument (H2020-EIC-SMEInst-2018-2020-3, 2020)
Start date: 2020-08-01
End date: 2022-07-31
Duration (months): 24.0
Total project cost (EUR): 1470057.0
EU funding (EUR): 884990.0
Participants: 1
Project status: CLOSED

Optimal use of hospital resources and intervention using suPAR for improving prognosis and care for patients with COVID-19 To optimize hospital resources, it is necessary to test which patients that can be sent home (mild outcome of infection) and which patients that should be admitted to hospital (high risk patients). This will deliver on the tasks: 1) Identify patients that can safely cope with the infection at home and 2) Identify high risk patients early in the disease and 3) Select high-risk patients that may benefit of therapy. But how can we identify low- or high-risk patients? The suPARnostic test developed by ViroGates and CE/IVD approved for clinical use is highly prognostic marker for 30-day mortality. Some hospitals have suPAR in routine clinical assessment of patient risk, and preliminary data support that suPAR levels can triage whether patients with COVID-19 will have a mild or a severe outcome of COVID-19 and thereby select which patients that could be discharged or admitted. We aim to transfer manufacturing, upscale and implement the suPARnostic technology across hospitals in Europe to improve the risk stratification of COVID-19 patients and optimize hospital resources. We furthermore provide a test method that can identify high-risk patients that may benefit from experimental therapeutic interventions that may impact on outcome. The identification of patients in high risk of mortality (patients with high suPAR) provide a possibility to intervene.

Keywords: risk status biomarker supar,risk prediction,covid 19,antiinflammatory treatment
COGNITIVE PLATFORM TO ENHANCE 360º PERFORMANCE AND SUSTAINABILITY OF THE EUROPEAN PROCESS INDUSTRY (COGNIPLANT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Sustainable, resource-efficient and low-carbon technologies in energy-intensive process industries
Action type: Innovation actions
Countries involved: Germany,Austria,Spain,Spain,Ireland,Italy,Austria,Spain,Italy,Greece,France,Netherlands
Call: Digital technologies for improved performance in cognitive production plants (IA) (H2020-NMBP-SPIRE-2019, 2019)
Start date: 2019-10-01
End date: 2023-09-30
Duration (months): 48.0
Total project cost (EUR): 8562917.5
EU funding (EUR): 6718237.76
Participants: 19
Project status: SIGNED

COGNIPLANT project will develop and demonstrate an innovative approach for the advanced digitization and intelligent management of the process industries. This approach will be based on a novel vision to data monitoring and analysis, that will make the most of the latest developments on advanced analytics and cognitive reasoning, coupled with a disruptive use of the Digital Twin concept to improve Production plants’ operation performance by up to 68% in real time control of the productive environment, 65% in quality control of the final products and 70 % in response time to uncontrolled incidents. The concept will be implemented by four end-users from four different SPIRE industries, one chemical industry in Austria, one aluminum refinery in Ireland, one concrete manufacturing industry in Italy and one metal industry in Spain. The COGNIPLANT solution will provide a hierarchical monitoring and supervisory control that will give a comprehensive vision of the plants’ production performance as well as the energy and resource consumption. Advanced data analytics will be applied to extract valuable information from the data collected about the processes and their effect on the production plant’s overall performance enabling to design and simulate operation plans in digital twin models based on the conclusions. As a result, optimal operation plans will be obtained that will improve the performance of those cognitive production plants. In addition, the project will demonstrate the positive impact derived from the implementation of COGNIPLANT solution that will allow industries reducing their CO2 emissions up to 20%. A training strategy will be designed to provide a comprehensive framework for the dissemination of the project outcomes and a clear understanding of the new solution for the employees of the SPIRE sectors.

Keywords: digitisation,iot monitoring,big data management,process mining,cognitive production plants,reactive scheduling
Biomechanical analysis of in vivo directional collective migration (VIVO_MECH_COLL_MIGRA)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2016-02-02
End date: 2018-02-01
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

Directional cell migration is important in physiology and pathology. Molecular mechanisms regulating directional migration are largely studied; but the role of mechanical cues and their interplay with biochemical signals during directional migration is poorly understood. To address this we will use Neural Crest (NC) cells, a highly migratory embryonic cell population. Evidence about how chemical cues regulate NC migration has accumulated, but nothing is known about the biomechanics of NC migration. This proposal focuses on understanding how NC interacts with the mechanical cues from its environment during directional migration in vivo, as well as understanding the molecular nature of this interaction. Thus, our aims are: Aim 1) to study the role of mechanical cues in vivo and their interplay with chemical signals during in vivo NC migration. Aim 2) identify the molecular mechanism by which the mechanical properties of the substrate are sensed and translated as signals into the NC, and to test the role of Nedd9 as a key component of this process. (Nedd9 appears in a screening that I performed to identify potential NC mechanosensors). These studies will provide new tools and information on the role of mechanical cues during directional migration in vivo, how these cues interact with chemical guidance, how are they integrated as cellular signalling within cells? These questions are poorly studied aspects of cell migration, thus our results will be a real contribution to the state-of-the-art in cell migration. This multidisciplinary proposal is will be mutually beneficial, providing the host and me with new collaborations. A research line will be created in ERA with NC as a model to study biophysics of migration in vivo. I will complement my current skills with new knowledge in biophysics of cell migration and managerial skills; this will have a countless impact in the career that I project as an independent researcher in the cell migration field.

Keywords: directional collective migration,xenopus embryo,neural crest migration,biomechanics,afm mechanotransduction
Accelerating Autonomous Vehicle Development with Photorealistic, Virtual AI Training and Testing Simulation (aiSim)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Hungary
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2019-02-01
End date: 2019-04-30
Duration (months): 3.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Level 5 autonomous vehicles (AVs), i.e. completely self-driving cars, are now the foreseeable future of mobility. There are numerous ongoing developments globally: every significant automaker is pursuing the technology either in-house or in partnerships with specialist companies. This resulted in significant advances in all areas of autonomous driving technologies, bringing them closer to commercial readiness. However, the great challenge is to make sure that these technologies work safely and properly; i.e. testing and validation. Real road testing is not only expensive and time-consuming, but also inefficient, as it is not possible to create situations that characteristically lead to accidents without hazarding other road users. Founded in 2015, AImotive has grown to be one of the largest independent teams in the world working towards fully self-driving car technology. 190 colleagues work with us in our headquarters in Budapest, Hungary and offices in Helsinki, Finland; Mountain View, California and Tokyo, Japan. One of our key developments, aiSim is a simulator for self-driving technologies, created to accelerate the development of aiDrive, our self-driving solution. The ability to recreate real-world situations and create unique scenarios ensures the safe development of autonomous vehicle technology and enables to undertake testing of new developments about two orders of magnitude more cost efficiently and an order of magnitude faster than real road testing. Currently available to our partners as part of aiDrive projects. The proposed Phase 1 project explores the opportunity and requirements of commercialising aiSim as a stand-alone product.