Data-Gouv-ML/pcri-actions-marie-curie-participations-et-projets-laureats huggingface dataset:
Projet BALSAM (Horizon Europe, appel à projets 2021)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

Additive manufacturing has attracted the attention of industries such as aerospace and automotive as well as the medical technology sectors in recent years. Laser additive manufacturing technology (LAM) has become a very promising alternative to high-value large metal components in many manufacturing industries. Although major progress has been made in process development, path slicing, programming, and material analysis, a comprehensive process monitoring, and control system are yet to be developed. BALSAM project (Boosting Accuracy of Laser Additive Manufacturing) aims to provide in-depth methods, models and tools of sensing and control design suitable for the LAM system, including technologies developed for a generic welding process using the candidate previous results on data-driven control methodology. Particular focus is given to the integration of sensor-based feedback control, and how they could be implemented into the LAM process to improve the surface quality and geometric accuracy of the final product. The project concludes with different simulation and experimental results to verify the system’s performance and robustness. The multidisciplinary nature of the BALSAM project is strong, involving a combination of well-developed control, robotics, laser-welding and manufacturing. This proposal includes both the transfer of knowledge to the host institution and the training of the candidate in new advanced techniques. Results have the potential capacity to increase the use of LAM in the European industries and provide room for further studies at the fundamental and applied levels. This project is in line with the EU industrial strategy that aims to make the EU industry more competitive globally.

Mots clés : laser additive manufacturing, control engineering, additive manufacturing technology, data driven control system, laser wire feed metal additive manufacturing, 3d printing, system identification

Participants :
- Université du Luxembourg (Luxembourg) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 191760.0 €
- Fraunhofer-Gesellschaft (Allemagne) — Partner, associated partner, Recherche, subvention : 0.0 €
Projet HiddenTipChains (Horizon Europe, appel à projets 2023)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : SIGNED

Consider a scenario in a financial market where investors privately share important insider information within their social circles. Although financial authorities could monitor investors' transactions, it remains challenging to identify which investors have received and are exploiting insider information. I term this scenario a hidden cascade problem, in which the true states of agents cannot be directly observed. This particular form of cascade modelling, involving the inference of agent states from indirect observations, has received limited attention in the existing literature.  This proposal, "HiddenTipChains", introduces approaches based on Topological Data Analysis, Machine Learning, and probabilistic modeling to reveal hidden information transfer through investors’ social connections and to detect suspicious trading based on insider information. This supports European Commission goals for financial stability and investor protection. In a broader context, the methods will enable us to analyse hidden cascade models when direct observations of agents' true states are not directly observable. I expect that in future research, these approaches can find application in addressing hidden cascade challenges across various fields, such as epidemiology, climate science, and information security.  The empirical part of the project is based on world-wide unique and exceptionally extensive datasets, providing us with full access to investors’ full market-wide trading history on all the securities they traded. Additionally, we have observable social connections among insider investors, allowing us to track how news tips about future events propagate within this network. The approached developed in this project will be verified with synthetic data with extensive Monte-Carlo experiments. The project contributes to the Computer Science literature by developing techniques for hidden cascade problems and within the Quantitative Finance domain for identifying market abuse.

Mots clés : information cascades, insider information, machine learning, topological data analysis

Participants :
- Université d'Aarhus (Danemark) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Institut indien de technologie Delhi (Inde) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université de Tampere (Finlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 199694.4 €
Projet InTime (Horizon Europe, appel à projets 2024)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Life Sciences
Statut du projet : SIGNED

High quality antenatal care (ANC) can significantly reduce global maternal and newborn mortality. The World Health Organization (WHO) currently monitors the implementation of its new ANC model using the indicator of four or more ANC visits, but this approach has limitations, notably its failure to consider the timing of ANC interventions. Timing is critical, as many interventions are most effective when started early in pregnancy, which is often not the case in low- and middle-income countries (LMIC) where women frequently initiate ANC late.  InTime addresses this challenge by developing an innovative model based on evidence synthesis of randomised controlled trials on the impact of timing of key antenatal interventions on their effectiveness. The model integrates this data in the coverage of the interventions in 81 “Countdown to 2030 priority countries”, and further links it with health system readiness to deliver the modelled service, estimated using existing data from nationally representative health facility assessments in LMICs.  For maximum impact, InTime implements the findings through a computational tool that has a world-wide coverage and is widely used by global organisations and governments to estimate the impact of scaling up maternal and child health interventions in LMICs. By quantifying the impact of untimely ANC on maternal and neonatal mortality in Countdown to 2030 priority countries, and making this data freely available globally, InTime will assist health policy makers and programme implementers in LMICs to analyse the quality and equity of ANC, locate ANC implementation bottlenecks, evaluate the effectiveness of new innovations for delivering ANC, and target valuable resources to where they are needed most, thus ultimately contributing to saving lives.  The results will be broadly communicated through open access and open peer reviewed articles, and targeted high-level consultations with health policy makers, including WHO and the World Bank.

Mots clés : antenatal care anc , global health, quality of care, impact estimation, computational modeling, low and middle income countries lmic , maternal mortality, neonatal mortality

Participants :
- Université Johns-Hopkins (Etats-Unis) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université de Tampere (Finlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 318564.3 €
Projet PCARE (Horizon Europe, appel à projets 2021)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : CLOSED

"After a homicide, suicide, malpractice, or death of a child, there can be terribly deep bitterness and anger at the perpetrator, making the grieving unable to move forward in life when death cannot be accepted" (Anna Liisa Aho, 2020). Among all events leading to bereavement, the death of a child is categorized as the most devastating event, leaving bereaved parents with effects on their health, psychology, and social relationships. To date, there is a lack of understanding regarding parental grief after the traumatic death of a child. A discussion on bereavement after a traumatic death may be taboo, and its need is underestimated due to culture and beliefs among people. The proposed study aims to investigate bereaved parents` meaning-making process after the traumatic death of their child, analyze the dynamic of formal and informal support received by the bereaved parents, analyze formal supports from bereavement experts` perspectives, and develop a web-enabled app-based intervention (PCARE app) that is derived from bereaved parents` and bereavement experts` perspectives to support bereaved parents. This study combines various qualitative research approaches, including in-depth interviews, Focused group discussion, and Participatory Action Research. The participants will be bereaved parents who experienced the traumatic death, bereavement experts, and IT professionals. Thematic analysis using ATLAS ti. software will be conducted to identify themes that emerge from the study. The themes will be translated into the innovation of the PCARE app. This study is vital to support the United Nations' sustainable goals and Horizon Europe's strategic planning to strengthen the health care systems and promote vulnerable families' health and well-being outcomes through the innovation of bereavement digital-based intervention.

Mots clés : parental grief, traumatic death, meaning making, support, participatory action research, qualitative studies, online bereavement support

Participants :
- Université de Tampere (Finlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 215534.4 €
Projet GERIATRIC (Horizon Europe, appel à projets 2023)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : SIGNED

One out of 5 Europeans is ≥ 65 years old, and 10% of Europeans struggle with performing Instrumental Activities of Daily Living like housekeeping, shopping, and managing finances. This everyday struggle is predominantly attributed to cognitive ageing. Early detection of cognitive decline is imperative to slow down the exacerbation of cognitive ageing, yet existing tools fall short in the timely identification of such decline. The proposed project attempts to bridge this gap, utilizing Immersive Virtual Reality (IVR) to create an innovative cognitive assessment system, simulating real-life conditions and providing an accurate representation of individuals' everyday functionality. The GERIATRIC project recognizes the barriers posed by the elderly population's often limited IT proficiency and compromised motor skills, which have historically obstructed the effective use of computerized cognitive assessment tools. GERIATRIC seeks to address these challenges by incorporating Eye-Tracking (ET) and Finger-Tracking (FT) technologies, thereby augmenting the usability, accessibility, and clinical relevance of IVR cognitive assessments. Hand-based (FT) and gaze-based (ET) interactions will be developed, evaluated, and compared in terms of usability, performance, and throughput. The validity and clinical utility of the IVR cognitive test will be examined, especially for the detection of cognitive decline in older adults. In collaboration with industry partners, the final stage transforms the IVR cognitive assessment into a potent cognitive training tool. To foster innovation in the field, GERIATRIC will promote the democratization of IVR for broader research and clinical applications by offering open-source access to IVR software, code, and assets to the broader scientific community. Through GERIATRIC, I will cultivate a diverse skill set and a robust track record, which may assist me in acquiring a tenure position at a prestigious European research institution or university.

Mots clés : usability, accessibility, elderly, ageing

Participants :
- Université nationale et capodistrienne d'Athènes (Grèce) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 211658.4 €
- Athena Research and Innovation Center In Information Communication & Knowledge Technologies (Grèce) — Partner, associated partner, Recherche, subvention : 0.0 €
- Neo auvra dijital saglik ve biyonikteknolojileri ve hizmetleri sanayive ticaret anonim serketi (Turquie) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
Projet BioCoatCorr (Horizon Europe, appel à projets 2024)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Chemistry
Statut du projet : SIGNED

316LVM stainless steel sternal wires (SW) are widely used in cardiothoracic surgery for chest closure. However, in the aggressive environment of the human body, SWs are likely to corrode without a protective coating. This can lead to the release of harmful chromium and nickel in the surrounding tissues or, worse, SW rupture with potentially life-threatening complications, such as heart lacerations. SW degradation is caused by several factors, like chloride attack promoted by the creation of confined areas (e.g., at the chest bone/SW interface), plastic deformation due to the placement of SW around the bone, and tensile stress. Moreover, after implantation, the patient’s immune system unavoidably triggers an acute inflammation episode during which leukocytes generate reactive oxygen species (ROS), such as H2O2 and radicals (notably via the Fenton reactions), that also contribute to the SW deterioration. BioCoatCorr aims to investigate in-depth in vitro degradation of 316LVM SW in phosphate buffer saline involving simultaneously multiple degradation factors (plastic deformation, H2O2, confined areas…). For that purpose, electrochemical measurements (corrosion potential monitoring coupled with impedance spectroscopy) will be carried out at various levels of wire deformation. Furthermore, a novel zein-bioglass-cerium protective coating capable of withstanding the harsh SW operative conditions will be prepared using electrophoretic deposition (EPD). The zein biopolymer has been selected for its ductile properties required for matching the significant SW deformation. The cerium will have the functionality of ROS scavenger, limiting the polymer degradation. The anti-corrosion behaviour and mechanical properties of the coatings will be assessed as a function of the synthesis parameters. The results of BioCoatCorr will contribute to developing the next-generation SW with enhanced durability and thus improve patient life quality postoperatively.

Mots clés : electrophoretic deposition, biomedical implants, inflammation, plastic deformation

Participants :
- Institut de la corrosion (France) — Coordinator, beneficiary, Recherche, subvention : 242260.56 €
Projet DataABM (Horizon Europe, appel à projets 2021)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : SIGNED

Image recognition or self-driving cars are just a few among many applications of machine learning (ML) methods. Given that we can train a cobot to mimic human behaviour, why not train a computer to mimic and simulate investor behaviour in stock markets? This would not only improve understanding about investor decision making and their interaction, but provide effective tools to predict investor behaviour on the microscopic level and simulate stock markets on the macroscopic level. The main objective is to create a data-driven Agent-Based Model (ABM), where agents' behaviour is governed by ML. Such models need appropriate data to be trained, which is possible thanks to a unique, big data set on investor level data accessible through the host. The objectives are: i) framework for data-driven ABM, ii) interpretable ML for ABM, iii) verification of the interpretability of data-driven ABMs using synthetic data, iv) training the data-driven ABMs using actual shareholder registration data, and finally v) analysis of investors’ decision-making mechanism. The objectives will be reached by using ML methods that achieve intrinsic interpretability with and without deep supervised learning. This research requires: a) strong numerical skills and experience with simulations, b) computer infrastructure allowing to carry out largescale numerical analysis for which the fellow and the host have complementary experience. The results will bring us closer to understanding the behavioural mechanism of market participants. The project does not just gain understanding, but introduces a data-driven approach to more realistic agent-based modelling, which is completely new. The outcome should focus the attention of regulators and policy makers, who are often unable to realistically predict the effects of considered economic measures. Finally, the project contributes to the ML literature on verification of interpretable methods with extensive data sets.

Mots clés : agent based modelling, machine learning, behavioural finance

Participants :
- Université d'Aarhus (Danemark) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université de Tampere (Finlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 215534.4 €
Projet MeFMAB (Horizon Europe, appel à projets 2022)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Chemistry
Statut du projet : SIGNED

Current diagnosis of individuals suffering from disorders on the autism spectrum is based on behavioural and developmental observations, usually in their early life. Even so, there is a significant amount of people having to live with these life-long disorders that remain undetected and no treatment is provided to them. However, it is already established that such disorders are associated with metabolic changes. There is now a growing amount of evidence suggesting that such metabolic alterations can be detected in samples such as blood or urine taken from children early in their life. These routines however can cause significant discomfort to the child. The primary aim of the proposal will involve the use of less invasive sampling techniques such as exhaled breath and exhaled breath condensate for the early diagnosis of metabolic hallmarks of autism spectrum disorders. These samples will be analysed using already established chemical analysis techniques for the detection of small metabolic changes in the obtained samples. Tandem mass spectrometry techniques will be used for the unambiguous identification of these metabolites. Data analysis tools such as principal component analysis (PCA) and hierarchical clustering will be used, to associate these metabolic changes with existing medical records obtained from the patients, to establish a potential diagnostic tool. The potential for the rapid detection of these metabolites will be examined through the integration of novel ambient mass spectrometric ionisation methods such as plasma ionisation. The ability to selectively ionise specific metabolites associated with autism will be investigated with the aim of generating an early prototype of a rapid screening method for routine use. Data generated during the initial stage of the work will be used to create a database that will be used for near real-time characterisation of the exhaled breath through the analysis of metabolites and volatile organic compounds (VOCs).

Mots clés : ambient ionisation mass spectrometry, breath analysis, vocs, volatolomics, autism spectrum disorders

Participants :
- Université de Jaén (Espagne) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université de Chypre (Chypre) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 148488.0 €
Projet COLD-WAR-EURASIA (Horizon Europe, appel à projets 2024)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Social Sciences and Humanities
Statut du projet : SIGNED

Eurasianism is an ideological and political movement that emerged in interwar Europe in the 1920s among Russian émigrés who left their country after the WWI and Bolshevik revolution. In the broader context of Russian intellectual thought, Eurasianism represents one of the most visible and important ideological movements that underwent a series of transformations during the 20th century and, especially since the early 1990s, has regularly resonated in Russian foreign policy and academic research. Until now, research on Eurasianism mostly focused on two main topics: interwar Eurasianism of the 1920s and 1930s and post-Soviet neo-Eurasianism of the 1990s. Although the research on both topics produced significant findings, the Cold War period remained without sought-after academic attention.  In the current project, I aim to fill the blind spot in the study of Eurasianism by involving advanced digital analysis of unpublished archival documents from Prague, Saint Petersburg, and New York related to the development of Eurasianism in the US Cold War academia. Specifically, I will focus on Russian historian G. V. Vernadsky – one of the prominent members of the interwar Eurasianist movement who emigrated to the US in the late 1920s and pioneered Slavic studies at Yale. Throughout his outstanding academic career, Vernadsky remained in contact with numerous Russian emigrants, including Eurasianists N. S. Trubetzkoy and P. N. Savitsky and Soviet scholars, namely historian and ethnologist L. N. Gumilev, who became involved with Eurasianism in the late 1950s.  In a broader context, the project will help to understand the transformation of Eurasianist concepts within the field of Russian, Eurasian, and Slavic Studies, and will comment on the roots of exploitation of Eurasianist concepts in contemporary Russian anti-Western propaganda. The main output of the project will be the first-ever monograph focused on the development of Eurasianism in the US Cold War Slavic Studies.

Mots clés : cold war, eurasianism, slavic studies, us academia, russian emigration, historiography, digital humanities

Participants :
- Université Columbia (Etats-Unis) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université Masaryk (Rép. Tchèque) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 419888.52 €