Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Personalised Medicine in Diabetic Chronic Disease Management (PROMINENT)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Co-funding of regional, national and international programmes (COFUND)-Doctoral programmes
Action type: Marie Skłodowska-Curie actions
Countries involved: Netherlands
Call: Co-funding of regional, national and international programmes (H2020-MSCA-COFUND-2016, 2016)
Start date: 2017-09-01
End date: 2023-08-31
Duration (months): 72.0
Total project cost (EUR): 3348480.0
EU funding (EUR): 1674240.0
Participants: 1
Project status: SIGNED

Diabetes is increasing rapidly from 415 million patients in 2015 to 642 million patients by 2040. As a result, it will become the leading disease worldwide, affecting 1 out of 10 persons globally and 3 out of 4 in low and middle income countries. The World Health Organisation marked World Health Day 2016 as calling for action on diabetes. Despite successful treatment of the inadequate glucose handling, diabetic patients show long-term effects of the disease such as a progressive loss of multiple organ function, in particular in the cardiovascular and renal systems. About half of the diabetic patients are at risk for renal complications associated with a markedly increased disease burden and death rate, the latter even surpassing the death rate in all treated cancer patients. The major reason for the lack of treatment efficacy is the large variation in individual response to the treatment. Consequently, we are left with a huge unmet need in the treatment of this chronic disease. A huge step forward in chronic diabetes disease management is personalised medicine. The EC has recognized the importance of personalised medicine and has started initiatives in this regard in 2016. The COFUND PROMINENT programme of the Research Institute for Drug Exploration (GUIDE) brings these fields together and introduces personalised medicine for chronic diabetes disease management. PROMINENT is focussed at setting up a dedicated doctoral training programme for 16 Early Stage Researchers (ESRs) at the University Medical Center Groningen (UMCG) and the University of Groningen (RUG). PROMINENT aims to select the best students to become excellently trained researchers, who can perform high quality research, and who subsequently have a major impact on scientific breakthroughs that foster the European society and economy in this field.

Keywords: personalised medicine,diabetes mellitus,doctoral training,multidisciplinary
Feedback for Small Companies and Firsttimers (FeedS First) (FeedS First)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Austria
Call: Supporting experimentation in innovation agencies (H2020-INNOSUP-2018-06-two-stage, 2018)
Start date: 2019-10-01
End date: 2023-04-30
Duration (months): 43.0
Total project cost (EUR): 60000.0
EU funding (EUR): 60000.0
Participants: 1
Project status: SIGNED

The main objective of this project is to test the effects of feedback provided by FFG experts to R&D projects of small companies and first-timers funded in the “General Programme” of the FFG. The “General Programme” (https://www.ffg.at/en/general-programme-further-information) of the Austrian Research Promotion Agency (FFG) is the biggest and longest running R&D funding scheme in Austria. The focus is on providing feedback for small companies and first timers in the FFG, which are funded in the “General Programme”. These types of companies are selected in this experiment because it was pre-assessed that in these cases feedback would be necessary. The feedback will be offered on the technical concept, the business plan and/or the written application. The effects of this feedback should be measured by the quality of the project execution, quality of future proposals and the success of the project outcomes and company. So far feedback is only provided if the application is rejected. No feedback is given in case of a positive evaluation result. Only a contract is issued and sometimes there are conditions included in the contract (e.g. for financing statements). So, although these projects are classified as worth funding (à “good projects”) until now they do not receive any information on how to improve. This is what this INNOSUP-application intends to change: Give also feedback to the “good projects” in order to further improve the quality of the projects (e.g. in terms of technical issues or economic aspects) with the expectation that this feedback enhances business performance. With this experiment FFG wants to test, if giving feedback for small enterprises and enterprises who apply the first time have positive effects on the quality of the project execution, quality of future proposals and the success of the project outcomes and company performance.

Keywords: feedback,proposal check,first timers,quality improvement,randomised controlled trials rcts
European Union Contest for Young Scientists' 2018 (EUCYS2018)

Framework: Horizon 2020 — Science with and for Society
Programme: Make scientific and technological careers attractive to young students, and forster sustainable interaction between schools, research institutions, industry and civil society organisations
Action type: Coordination and support actions
Countries involved: Ireland
Call: European Union Contest for Young Scientists (EUCYS) 2018 (H2020-IBA-SWFS-EUCYS-2018, 2018)
Start date: 2018-01-01
End date: 2018-10-31
Duration (months): 10.0
Total project cost (EUR): 1251250.0
EU funding (EUR): 800000.0
Participants: 1
Project status: CLOSED

European Union Contest for Young Scientists (EUCYS) has been organised since 1989 with the aim of promoting science and research among Europe's youth and bringing together the talented young people across Europe. The young scientists also have the chance to meet others with similar abilities and interests and to be guided by some of the most prominent scientists in Europe. This way EUCYS seeks to strengthen the efforts made in each participating country to attract young people to careers in science and technology. EUCYS has been organised in countries across Europe with the aim of promoting science and research in different countries and bringing research and young talents into spotlight in these countries. Ireland will organise EUCYS for the second time in 2018, after hosting it for the first time in 2004. Ireland also has previous experience in organising an Irish National contest for young scientists for the last 54 years, the longest running competition of its kind in Europe. The host organiser of EUCYS 2018 will be Young Scientist & Technology Exhibition Limited in close cooperation with the Irish Department for Education and Skills. EUCYS brings together excellent young researchers from 40-69 countries. During 4 days the participating projects will be interviewed by jury members and decisions about European Union prizes, special prizes and host organisation prizes will be made.

Keywords: european union contest for young scientists 2018 dublin,ireland
Gameful approaches for Equity, Diversity and Inclusion education (GAMINCLUSIVE)

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: Finland
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-09-01
End date: 2024-08-31
Duration (months): 24.0
Total project cost (EUR): 190680.96
EU funding (EUR): 190680.96
Participants: 1
Project status: SIGNED

GamInclusive proposes a framework to guide professionals and enthusiasts in designing gameful Equity, Diversity and Inclusion (EDI) educational approaches that promote cognitive, behavioural, and attitudinal learning to mitigate implicit bias and empower individuals in reflecting, exercising and upholding each others’ rights. It aims to address the intersection between gameful approaches and EDI education and training areas, which is yet to mature on theoretical, empirical and practical levels, by: G1) systematically integrating research and applications while consolidating this interdisciplinary subject with ground theory; G2) quantitative and qualitatively analyse empirical outcomes of the designed gameful instructional materials, prototypes and web learning application with user testing and controlled experiment by comparing the interaction, pre/post-test and survey responses; and G3) defining a practical framework for gameful EDI educational strategies that raises awareness about social issues and engages behavioural and attitudinal changes, by triangulating theoretical and empirical evidence. The host institution and my skill sets are highly complementary and suit the needs of this ground-breaking research, in which I will transfer my software development knowledge (especially in gamified education settings), and the Tampere University will provide the experience on humanities, psychology, and sustainability. The innovative and career-building aspect of GamInclusive is a novel combination of humanities, psychology, education, and gameful technologies towards the betterment of social sustainability issues, as those from 2030 Sustainable Development Goals (e.g., #5: Gender equality, #10: Reduced inequalities, and #16: Peace, justice and strong institutions). Tackling inequalities and discrimination issues, GamInclusive potential for social change attracts the interest of academia, industries, NGO fighting discrimination and overall society.

Keywords: game based learning,gamification,sustainability,social issues,equality,inclusivity,awareness,implicit bias,discrimination,prejudice
iBILD: Imaging Biomarker for Intelligent Lung Cancer Detection (iBILD)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Treating and managing disease
Action type: SME instrument
Countries involved: United Kingdom
Call: Clinical research for the validation of biomarkers and/or diagnostic medical devices (H2020-SMEINST-1-2015, 2015)
Start date: 2016-04-01
End date: 2016-09-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Lung cancer is one of the most common cancers with the highest mortality rate both in Europe and Worldwide. In 2012, 449,000 new cases were diagnosed with 388,000 deaths recorded in Europe alone. The reason for the 86% mortality rate is that most lung cancers are detected only after clinical symptoms are prevalent, by which time the cancer is in a late stage. Early detection using Chest Computed Tomography (CT) can lead to markedly improved outcomes, as shown recently by the NLST lung cancer screening trial in USA which has achieved a ground-breaking, 20% mortality reduction. However there is currently no solution that allows screening and management of suspected lung cancer patients in an economically sustainable manner. Optellum has developed a novel technology, Deep Learnt Biomarker (DLB). It is a software application that will allow radiologist to make a more accurate diagnosis by providing additional information extracted from the same CT, already acquired anyway as standard of care. It is based on machine learning algorithms applied to large databases of CTs with known ground-truth diagnosis, which learns patterns not obvious to a human eye. Our product will a) improve early diagnosis of lung cancer, b) save EUR799M p.a. in unnecessary costs to EU health providers c) enable European Union to become the leader in lung cancer screening. Optellum was founded to commercialize machine learning technologies that will transform radiology by learning novel biomarkers from medical image databases. During this Phase 1 SME project, we will investigate the commercial feasibility of this first application and will develop a detailed business plan, with a focus on a roadmap to navigate the complex regulatory and health economics environment.

Keywords: lung cancer,patient stratification,pulmonary nodules,early detection,computed tomography,machine learning,big data
Age-dependent Regulation of Dendritic Cell Development and Function (Baby DCs)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Immunity, Infection and Immunotherapy
Panel description: The immune system, related disorders and their mechanisms, biology of infectious agents and infection, biological basis of prevention and treatment of infectious diseases, innovative immunological tools and approaches, including therapies
Countries involved: Germany
Call: ERC Starting Grant (ERC-2016-STG, 2016)
Start date: 2017-06-01
End date: 2024-12-31
Duration (months): 91.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: SIGNED

Early life immune balance is essential for survival and establishment of healthy immunity in later life. We aim to define how age-dependent regulation of dendritic cell (DC) development contributes to this crucial immune balance. DCs are versatile controllers of immunity that in neonates are qualitatively distinct from adults. Why such age-dependent differences exist is unclear but newborn DCs are considered underdeveloped and functionally immature. Using ontogenetic tracing of conventional DC precursors, I have found a previously unappreciated developmental heterogeneity of DCs that is particularly prominent in young mice. Preliminary data indicate that distinct waves of DC poiesis contribute to the functional differences between neonatal and adult DCs. I hypothesize that the neonatal DC compartment is not immature but rather that DC poiesis is developmentally regulated to create essential age-dependent immune balance. Further, I have identified a unique situation in early life to address a fundamental biological question, namely to what extent cellular function is pre-programmed by developmental origin (nature) versus environmental factors (nurture). In this proposal, we will first use novel models to fate map the origin of the DC compartment with age. We will then define to what extent cellular origin determines age-dependent functions of DCs in immunity. Using innovative comparative gene expression profiling and integrative epigenomic analysis the cell intrinsic mechanisms regulating the age-dependent functions of DCs will be characterized. Because environmental factors in utero and after birth critically influence immune balance, we will finally define the impact of maternal infection and metabolic disease, as well as early microbial encounter on DC poiesis. Characterizing how developmentally regulated DC poiesis shapes the unique features of early life immunity will provide novel insights into immune development that are vital to advance vaccine strategies.

Keywords: dendritic cell,neonatal immunity,immune development,fate mapping,obesity,schistosoma mansoni,epigenomic profiling,next generation sequencing,microbiome
Structure-activity relationship modelling of REACH-relevant endpoints to predict the toxicity of engineered nanomaterials (NanoQSAR)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Society and Enterprise panel
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-07-15
End date: 2023-07-14
Duration (months): 24.0
Total project cost (EUR): 172932.48
EU funding (EUR): 172932.48
Participants: 1
Project status: SIGNED

Nanotechnology is one of the fastest growing and most promising technologies in our society (Forster et al. 2011), promoting the development a new generation of smart and innovative products and processes that have created tremendous growth potential for a large number of industry sectors such as composites, colouring, ceramics, electronics, nutrition, cosmetics, energy, optics, automotive, as well as numerous other industrial sectors. Currently, there is a need of ensuring a safe and sustainable development of the nanotechnology, which implies a better understanding of the potential harmful effects that ENMs may have on human´s health or the environment. New paradigms are necessary to identify high concern ENMs and predict relevant endpoints for risk assessment, reducing the cost and timescale derived from the use of in vivo or in vitro assays. QSAR approaches have only recently been used to predict biological effects of ENMs, with only few Quantitative Nano- Structure Activity Relationships models described in the literature. The lack of available data explains why there is almost no literature reporting the use of computational modelling techniques applied to ENMs, especially in the area of nanotoxicology. On the other hand, current toxicological regulation, such as the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), strongly promotes the use of these predictive modelling. On the basis of the concept of the project, the main objective of the Nano-QSAR project is to develop new scientifically validated QSARs models to predict REACH relevant toxicological, ecotoxicological and environmental endpoints of a priority list of ENMs such as Metal Oxide Nanoparticles (MOx) and Quantum Dots (QD) on the basis of available literature and own experimental data.

Keywords: nanomaterials,quantitative structure activity relationships qsar,computational chemistry,toxicology,numerical descriptors,reach
The momentum polytopes of nonholonomic systems (ROBOTTOPES)

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: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-09-16
End date: 2022-09-15
Duration (months): 24.0
Total project cost (EUR): 160932.48
EU funding (EUR): 160932.48
Participants: 1
Project status: CLOSED

The plan of the project is to extend momentum polytope theory for the standard momentum mapping three different scenarios: (1) the case of contact hamiltonian systems; (2) the mathematical description of nonholonomic (robotic) systems and (3) multisymplectic field theories. The state of the art of research on momentum polytopes has been primarily focussed on the theoretical aspects rather than interdisciplinary research and applications, so this work will open up new grounds of research. The study of general multisymplectic manifolds is not only crucial to understand dynamics but is also of great independent interest e.g. for the quantisation of mechanics or field theories.

Keywords: symplectic geometry,motion,robotics,wheel movement,mathematical modelling
Predictive Maintenance for railway switches. Smart sensor networks on a machine learning analytics platform (Andromeda)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: SME instrument
Countries involved: Germany
Call: Small business innovation research for Transport and Smart Cities Mobility (H2020-SMEINST-2-2016-2017, 2017)
Start date: 2017-12-01
End date: 2019-11-30
Duration (months): 24.0
Total project cost (EUR): 2155000.0
EU funding (EUR): 1508500.0
Participants: 1
Project status: CLOSED

92.000.000 minutes, or 180 years. These are the, potentially avoidable, train delays caused by problems due to rail switches – every year, in Europe alone. The rail switch is a critical component of the rail-infrastructure. It is responsible for actively changing the route of trains, and must therefore endure higher levels of stress and mechanical fatigue than other elements of the rail infrastructure. Failures at track switches can result in expensive delays, or even dangerous derailments. In fact, track switches account for 19% of the delays, and have been linked to 110 derailments since 2010. It is therefore unacceptable that most of the monitoring of critical switches is solely dependent on manual inspections, since they are prone to measurement error and lack of global oversight. The outcome is generally an inaccurate estimation of the State-of-Health of each switch and re-active – not preventive – maintenance, with financial losses due to delays or additional investment in infrastructure maintenance. European spending on railway switches is currently over 4B€ (30B€ worldwide). Furthermore, passenger and freight volumes are expected to increase respectively by 34% and 40% by 2030, which means shorter infrastructure access time for maintenance and monitoring. KONUX has developed the ANDROMEDA system, which promises to revolutionize the maintenance procedures for rail infrastructure. The system pulls data from sensors deployed permanently at the rail switch, which means no more expensive and manual data acquisition. Through self-calibrating smart sensors and machine learning analytics, the result is a holistic overview of the whole rail switch network, with current - and predicted - State-of-Health for each switch. With a total of 600.000 switches in Europe and 2.510.000 switches worldwide, the ANDROMEDA project represents a 12,4B€ business opportunity.

Keywords: railway,predictive maintenance,soh prediction,soh estimation
Securing the Internet of Things with a unique microchip fingerprinting technology (INSTET)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Netherlands
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2018)
Start date: 2018-06-01
End date: 2020-05-31
Duration (months): 24.0
Total project cost (EUR): 2496362.5
EU funding (EUR): 1747453.75
Participants: 1
Project status: CLOSED

Intrinsic ID is a Dutch SME, a spin-off from Philips Research, a world leader in security solutions for chips, with 25+ patents. Intrinsic ID has created a technology to uniquely identify & authenticate chips based on the inherent characteristics of their memory component (SRAM). This technology called Physical Unclonable Function (PUF) is a digital equivalent of a fingerprint. Intrinsic ID is working on INSTET—a fully-fledged security solution on top of PUF that will protect low-end chips that are omnipresent in IoT devices everywhere by making them physically & cryptographically secure and very resilient to advanced attacks. INSTET will work as a Root of Trust—a set of core software components that are always trusted by the chip, and provide a trust foundation for the IoT device & distributed IoT systems. INSTET addresses the core problem of semiconductor vendors and OEMs—lack of security. INSTET can be deployed on almost any chip, including the ones that are already in the field, without costly redesigns or additional hardware, generating savings of up to 90% per chip. Intrinsic ID has successfully completed an SME Instrument Phase 1 feasibility study & validated business opportunities in wearables, medical electronics & critical infrastructure verticals. In this 2-year Phase 2 project Intrinsic ID will complete industrialization of INSTET, validate it in 3 trial cases & start commercialization. The total requested EC contribution is €1,75m. Intrinsic ID is the sole benefactor & the party responsible for implementation of this Phase 2 project.

Keywords: physical unclonable function,chip,fingerprinting