Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Understanding and Supporting Peer Feedback at Massive Learning Scale (WeLearnAtScale)

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: Information Science and Engineering
Countries involved: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-09-03
End date: 2020-10-28
Duration (months): 24.0
Total project cost (EUR): 158121.6
EU funding (EUR): 158121.6
Participants: 1
Project status: CLOSED

Massive Open Online Courses (MOOCs) offer high quality education from the worlds' top universities in a wide range of areas. MOOCs can be freely accessed by millions around the world via a valid Internet connection; however not every individual accessing MOOCs equally benefits from them. The dropout of learners with limited or no background is inevitable as instructors cannot monitor every student and provide timely formative feedback and guidance tailored to their unique needs. As a result, MOOC learners cannot receive feedback on their progress/work to improve and complete the course. Thus, feedback, which is imperative to learning, is troublesome in MOOCs. This project aims to advance the understanding of feedback phenomenon at massive learning scale and improve the current MOOC practice in this regard. This project comprises three research objectives. First one is to develop guidelines for enabling effective feedback exchange among MOOC learners and use these guidelines to design an intelligent peer feedback system called WL@S. Second objective is to advance current knowledge on MOOC learners’ engagement in feedback exchange by exploring their activities in and experiences of using WL@S, examining the impact of the guidelines (embodied in WL@S), and identifying the influential factors. Third objective is to support the MOOC students’ learning and performance through timely provision of feedback and to identify the role of students’ background and learning characteristics. To achieve the research objectives, framed as educational design research, this research involves two iterations of intervention in real MOOC contexts, involving close collaboration with instructors at the host (using focus group). The proposed research and training activities will enhance the career prospects of the researcher and offer significant value to the host. This project is in line with the EU strategy for supporting education and training in Europe and beyond.

Keywords: mooc,machine learning,data mining,peer feedback,intelligent learning systems,learning analytics,technology enhanced learning,formative feedback
Hyperconnected Architecture for High Cognitive Production Plants (HyperCOG)

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: Spain,Germany,Spain,Türkiye,Türkiye,Hungary,France,France,France,Denmark,United Kingdom
Call: Digital technologies for improved performance in cognitive production plants (IA) (H2020-NMBP-SPIRE-2019, 2019)
Start date: 2019-09-01
End date: 2023-08-31
Duration (months): 48.0
Total project cost (EUR): 7649262.5
EU funding (EUR): 6504312.5
Participants: 15
Project status: SIGNED

HyperCOG project “HYPERCONNECTED ARCHITECTURE FOR HIGH COGNITIVE PRODUCTION PLANTS” addresses the full digital transformation of the process industry and cognitive process production plants through an innovative Industrial Cyber-Physical System (ICPS). It is based on commercially available advanced technologies, that will enable the development of a hyper-connected network of digital nodes. The nodes can catch outstanding streams of data in real-time, which together with the high computing capabilities available nowadays, provide sensing, knowledge and cognitive reasoning to the industrial business. Furthermore, HyperCOG is deeply grounded in the last advances in Artificial Intelligence such as modelling for twin factories, decision-support systems for human-machine interaction and augmented reality for industrial processes visualization. It pursues self-learning from the process in order to deal with the typical dynamic fluctuations of the industrial processes and global optimization. The objective is to increase the production performance while reducing the environmental impact by reducing the energy consumption and the CO2 emissions thereof. Society will get profit of this project not only throughout the environmental impact, but through the lifelong learning of workers and vocational training for digitisation, and the available training modules for youth at schools such as ESTIA technological institute or U-PEC University. The breaking-edge system proposed in HyperCOG project will be validated on the productivity and environmental impacts, replicability and usability aspects on three use cases belonging to the SPIRE scope such us SIDENOR (steel making), CIMSA (cement), and SOLVAY (chemical) use cases.

Keywords: cyber physical system,artificial intelligence,machine learning,iot data analytics,decision support algorithms,data collection,sensing technologies,cybersecurity,enviromenytal lca,training
A woman's reproductive experience: Long-term implications for chronic disease and death (HealthierWomen)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced 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: Norway
Call: ERC Advanced Grant (ERC-2018-ADG, 2018)
Start date: 2019-09-01
End date: 2024-08-31
Duration (months): 60.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 1
Project status: SIGNED

Pregnancy complications such as preeclampsia and preterm birth are known to affect infant health, but their influence on mothers’ long-term health is not well understood. Most previous studies are seriously limited by their reliance on information from the first pregnancy. Often they lack the data to study women’s complete reproductive histories. Without a complete reproductive history, the relationship between pregnancy complications and women’s long-term health cannot be reliably studied. The Medical Birth Registry of Norway, covering all births from 1967-, includes information on more than 3 million births and 1.5 million sibships. Linking this to population based death and cancer registries provides a worldwide unique source of population-based data which can be analysed to identify heterogeneities in risk by lifetime parity and the cumulative experience of pregnancy complications. Having worked in this field of research for many years, I see many erroneous conclusions in studies based on insufficient data. For instance, both after preeclampsia and after a stillbirth, the high risk of heart disease observed in one-child mothers is strongly attenuated in women with subsequent pregnancies. I will study different patterns of pregnancy complications that occur alone or in combination across pregnancies, and analyse their associations with cause specific maternal mortality. Using this unique methodology, I will challenge the idea that placental dysfunction is the origin of preeclampsia and test the hypothesis that pregnancy complications may cause direct long-term effects on maternal health. The findings of this research have the potential to advance our understanding of how pregnancy complications affect the long-term maternal health and help to develop more effective chronic disease prevention strategies.

Keywords: preterm birth,preeclampsia,gestational diabetes,perinatal death,materal cvd mortality,diabetes 2,foetal growth restriction,large for gestational age macrosomia
The first non-toxic bio-based polymer resin to revolutionize the wood panel industry (SWOP)

Framework: Horizon 2020 — Industrial Leadership
Action type: Innovation actions
Countries involved: Finland,Belgium,Netherlands,Netherlands
Call: Fast Track to Innovation (FTI) (H2020-EIC-FTI-2018-2020, 2019)
Start date: 2019-11-01
End date: 2023-04-30
Duration (months): 42.0
Total project cost (EUR): 3043857.52
EU funding (EUR): 2249687.0
Participants: 5
Project status: SIGNED

Across huge industries, like the construction and wood industry, formaldehyde-based polymer resins are used in large volumes as binders to keep together materials and components to produce stable and durable products. Such oil-based based resins, however, pose a large societal and environmental burden, as these are toxic, carcinogenic, non-recyclable, and have a large CO2 footprint. Due to increased problem recognition and recently introduced regulations, these industries actively seek for alternatives. However no safe, bio-based and cost-competitive resins are currently available that meet the functional requirements for a strong and durable material,.. until now. Plantics B.V. has developed Plantics-GX, a strong, 100% bio-based, recyclable and safe (no formaldehyde or other toxic components) alternative with a carbon footprint that is 5 to 7 times lower compared to existing resins. Plantics-GX is a biopolymer of which the raw materials are abundantly available, at low cost, making production of Plantics-GX cost-competitive to existing oil-based resins. It is ready to replace toxic and polluting resins, starting with binders in the wood industry. The SWOP consortium, consisting of 3 industrial parties and 1 NGO, has been established to realize and accelerate market entry of revolutionary GX-wood panels with Plantics-GX used as a binder. As a result of this project, these wood panels will be commercialized by Koskisen Oy, Finnish market leading wood manufacturer, and used by Triboo B.V., Dutch circular furniture manufacturer, to commercialize formaldehyde-free kitchens. WOOD.BE, a Belgian research and advice organisation in the wood industry, will perform studies to measure the health and environmental effects of a shift to using Plantics-GX. This two year project will accelerate market entry (2022), stimulate the European economy and while doing so address European health and environmental goals.

Keywords: thermoset biopolymer resin,wood panel industry,circular kitchen,binders,plywood,chipboard,bio economy,toxic formaldehyde,climate change,co2 reduction,occupational health
Geometric study of Wasserstein spaces and free probability (GWFP)

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: Austria
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2019-10-01
End date: 2021-09-30
Duration (months): 24.0
Total project cost (EUR): 186167.04
EU funding (EUR): 186167.04
Participants: 1
Project status: CLOSED

The proposed research is divided into two main work packages. The first one is the study of spaces of measures equipped with the optimal transport distance (Wasserstein distance) with a special emphasis on the structure of isometries (surjective distance-preserving maps) and isometric embeddings (not necessarily surjective transformations that preserve the distance) of these spaces. The second work package is devoted to the investigation of measures from the viewpoint of free probability theory. This work package covers three subtopics: the qualitative behaviour of the free convolution, new random matrix ensembles arising from tensor networks, and the study of free Wasserstein spaces.

Keywords: optimal transport,isometry group,free convolution,tensor networks,free wasserstein spaces
Abstractions for Safe and Secure HW-SW Systems (SafeSecS)

Framework: Horizon 2020 — 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 GRANT (ERC-2020-ADG, 2020)
Start date: 2021-10-01
End date: 2026-09-30
Duration (months): 60.0
Total project cost (EUR): 2445125.0
EU funding (EUR): 2445125.0
Participants: 1
Project status: SIGNED

Trains, planes, and other safety- and security-critical systems that our society relies on are controlled by computer systems, as is much of our critical infrastructure, including the power grid and cellular networks. But can we trust in the safety and security of these systems? The starting point of SafeSecS is the observation that today’s hardware-software abstractions, instruction set architectures (ISAs), are fundamentally inadequate for the development of safe or secure systems. Indeed, ISAs abstract from timing, making it impossible to develop safety-critical systems that have to satisfy real-time constraints on top of them. Neither do ISAs provide sufficient security guarantees, making it impossible to develop secure systems on top of them. As a consequence, engineers are forced to rely on brittle timing and security models that are proven wrong time and again, as evidenced e.g. by the recent Spectre attacks; putting our society at risk. SafeSecS will attack the problem at its root by introducing a framework centered around hardware-software contracts that extend the guarantees provided by ISAs to capture key non-functional properties. Hardware-software contracts formally capture the expectations on correct hardware implementations and they lay the foundation for achieving safety and security guarantees as the software level. Below the hardware-software interface, SafeSecS will contribute modular design principles and tools to construct microarchitectures that provably satisfy a given hardware-software contract. Above the hardware-software interface, SafeSecS will develop rigorous, precise, and scalable techniques to guarantee key safety and security properties at the software level on top of hardware-software contracts. As a whole, SafeSecS will enable the systematic engineering of safe and secure hardware-software systems we can trust in.

Keywords: hardware software systems,real time systems
Exploring the human gut microbiome at strain resolution (MicrobioS)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Integrative Biology: from Genes and Genomes to Systems
Panel description: Genetics, epigenetics, genomics and other ‘omics studies, bioinformatics, systems biology, genetic diseases, gene editing, innovative methods and modelling, ‘omics for personalised medicine
Countries involved: Germany
Call: ERC Advanced Grant (ERC-2014-ADG, 2014)
Start date: 2016-07-01
End date: 2021-12-31
Duration (months): 66.0
Total project cost (EUR): 2184432.5
EU funding (EUR): 2184432.5
Participants: 1
Project status: SIGNED

With the genome sequencing of hundreds of bacterial isolates per day and a vast and growing number of metagenomic sequencing projects on gut microbiomes in healthy and diseased people all over the world, it becomes feasible to explore the microbial diversity in us not only at the level of genera and species, but at strains. As two different strains of a prokaryotic species might only share 40% of the genes and can also have vastly differ in single nucleotide polymorphism (SNP) many aspects of a proper understanding of the microbial communities we host in the gut might only be revealed at this high resolution level. This proposal aims (i) to develop a robust methodology to characterize the SNP and gene content landscape from metagenomic shotgun data (ii) to explore patterns of variation in the human population to stratify geographically, but also in subpopulations such as families and to understand spreading patterns and the evolution of microbial strains as well as iii) to work towards medical applications, for example by monitoring fecal microbiota transplantation (FMT) at strain resolution or monitoring particular strain of interest in the population

Keywords: human microbiome,gut metagenomics,microbiomics
Identifying Clinical, Demographic, and Genomic Risk Factors for Treatment-Resistant Psychiatric Disorders (ClinGen-PsychTx)

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: Sweden
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-04-01
End date: 2020-03-31
Duration (months): 24.0
Total project cost (EUR): 185857.2
EU funding (EUR): 185857.2
Participants: 1
Project status: CLOSED

Identifying factors contributing to treatment-resistance in psychiatric disorders could uncover shared aetiology or used to develop predictive tests to identify patients at risk of poor outcomes. Severe psychiatric disorders–here schizophrenia, bipolar disorder, major depressive disorder, and anorexia nervosa–have an enormous impact on morbidity. Up to 60% have poor outcomes despite adequate treatment. Those with treatment-resistant psychiatric disorders have high rates of mortality, higher health care costs, and are hospitalized longer. Further knowledge on how clinical, demographic, and genomic factors effect treatment-resistance in psychiatry is urgently needed. To date, I am unaware of any systematic assessment of genetic, clinical, and demographic factors associated with treatment-resistance across the 4 previously mentioned disorders simultaneously. Previous genomic studies investigating these disorders evaluated treatment-resistance for one disorder, were limited by small sample sizes, and did not consider a range of risk factors. First, I will investigate whether clinical and demographic factors are associated with treatment-resistant psychiatric disorders using Swedish National register data and whether they differ between disorders (N=20K). Second, I will examine whether different forms of genetic variation are associated with treatment-resistance, using existing samples (N=20K) with genome-wide genotyping, copy number variant, and exome data. Here, I will uncover knowledge about how genetic variation effects treatment-resistance, including shared genetic correlation. Third, I will examine the confounding effects of genetics on clinical and demographic factors for treatment-resistance. Completion of the proposed work could highly impact our understanding of treatment-resistance in psychiatry, and has the potential to reduce morbidity, mortality, and suffering in individuals with these disorders.

Keywords: psychiatry,genetics,genomics,epidemiology
Helping Empower Youth Brought up in Adversity with their Babies and Young children (HEY BABY)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Social World and Its Diversity
Panel description: Sociology, social psychology, social anthropology, education sciences, communication studies
Countries involved: United Kingdom
Call: ERC Consolidator Grant (ERC-2017-COG, 2017)
Start date: 2019-05-01
End date: 2025-04-30
Duration (months): 72.0
Total project cost (EUR): 1999960.0
EU funding (EUR): 1999960.0
Participants: 1
Project status: SIGNED

Society’s greatest problems are our most compelling social science challenges. This project will develop the first known theoretical framework of resilience for adolescent parents and their children in Africa. In doing so, we will achieve three major advances in prevention science: We will synthesise quasi-experimental, data pooling and qualitative methods to identify protective pathways. We will create the global South’s first multi-country study of parenting support. And we will combine pioneering research with embedded stakeholder engagement, thus directly impacting international policy. Globally, adolescent parenthood is a marker of intergenerational disadvantage. Africa has 11.4 million adolescent mothers and fathers, often arising from adversities such as abuse, poverty, HIV and orphanhood. In turn, their children are at risk for non-optimum development and poor health. Existing research has focused on pregnancy prevention, with little success. Whilst these efforts are important, no known studies investigate predictors of resilience for adolescent-parent families in African contexts. This marks a major evidence gap, and a compelling need. We will use three linked methodologies. First, we will build a longitudinal study of 450 parent-child dyads living in severe adversity in South Africa. Through this, we can examine protective socio-economic, education and healthcare pathways. Second, we will create a six-country pooled dataset of parenting program studies, and test effectiveness across 8,000 participants regionally. Third, we will integrate citizen social science: participatory research with young families in adversity. A final policy-inclusive synthesis stage will ensure impact and benefit-sharing. This is an ambitious research agenda, with theoretical and methodological innovation. It requires the elucidation of complex behaviours in precarious environments. It presents risks, but with the potential for groundbreaking scientific and societal impact.

Keywords: youth,parenting,children,families,adversity,aids,abuse,poverty,resilience,protective pathways,prevention science,evidence based policies,africa