Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Disability benefits, labour force participation, and health: Evaluating the effect of social protection policies (DLH)

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: Netherlands
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2020-09-01
End date: 2022-08-31
Duration (months): 24.0
Total project cost (EUR): 187572.48
EU funding (EUR): 187572.48
Participants: 1
Project status: CLOSED

In the last decade, financial crises and population ageing have led to the retrenchment of the welfare state. One area under financial pressure is the provision of disability benefits. In response, governments have reduced expenditures by tightening eligibility criteria or reducing the benefit amounts. The Netherlands has become an example of such a system as it has persistently reduced the number of new individuals receiving disability benefits. Even though the reforms seem to have achieved their objective, there is little understanding of how they impact labour force participation and individual level health. The literature shows that not receiving a disability benefit leads to higher probabilities of working. However, there is surprisingly little about whether the effect is persistent, whether it differs across education groups, and whether it impacts household members. By contrast, there is a dearth of knowledge on the causal effect on health. This is especially striking since the original aim is to protect health. This research will contribute to our understanding of disability benefits by estimating their causal effect on work and health. For that, I will use unique administrative data from the Netherlands and exploit the regulations that define eligibility by means of an innovative empirical approach. The combination of this approach and the Dutch data will allow me to estimate the effect of disability benefits on work and health, and more importantly, to evaluate its persistence, its heterogeneity by education, and its impact on household members. As many countries strive for the financial sustainability of social programs, the knowledge generated in this research will provide valuable evidence of how government benefits impact labour force participation and individual level health. This nuanced understanding is essential as policy makers seek to prioritize programs and lack evidence to guide them in avoiding costly problems for future generations.

Keywords: disability benefits,labour force participation,individual level health,netherlands
Deep Learning for Medical Imaging: Learning Clinically Useful Information from Images (Deep4MI)

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-2019-ADG, 2019)
Start date: 2021-01-01
End date: 2025-12-31
Duration (months): 60.0
Total project cost (EUR): 2499900.0
EU funding (EUR): 2499900.0
Participants: 1
Project status: SIGNED

Medical imaging has revolutionized medicine and healthcare like no other recent technology, and is now an integral part of diagnosis, treatment planning, treatment delivery and follow-up. It provides an unparalleled ability to image anatomy and function with high spatial (and temporal) resolution. Its success has led to a dramatic increase in the number of medical imaging examinations. Despite this success, medical imaging is often stressful for patients, requires patient cooperation and is difficult in the presence of motion (e.g. patient motion or breathing motion). Furthermore, even more than 100 years after the discovery of X-rays, the interpretation of medical images relies almost exclusively on human experts. All of the above mean that there is a strong need for increased automation and quantification in order to reduce costs, increase efficiency and patient-friendliness, and provide higher diagnostic and prognostic accuracy for clinical decision making. At the same time, machine learning and deep learning techniques have made significant advances and have started to make a large impact in many real-world applications. The aim of this proposal is to exploit these advances to address the above challenges and to achieve a paradigm shift in the way information is extracted from medical images for diagnostics, therapy and follow-up. We will do this by developing a transformative and synergistic approach to medical imaging in which acquisition, reconstruction, analysis and interpretation will be tightly coupled, with bidirectional feedback between the different stages, in order to optimize the overall objective of the imaging pipeline: Extracting clinically useful and actionable information. To achieve this step change, the project aims to develop novel deep learning approaches for image acquisition, reconstruction, analysis and interpretation that can be trained in an end-to-end fashion, allowing fast and more efficient imaging.

Keywords: deep learning,medical image computing
Structural pOweR CompositEs foR futurE civil aiRcraft (SORCERER)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Clean Sky 2
Action type: Research and Innovation actions
Partnership: CS2 (Art-187)
Countries involved: Spain,Sweden,Sweden,United Kingdom
Call: Structural energy storage and power generation functionalities in multifunctional composite structures (H2020-CS2-CFP03-2016-01, 2016)
Start date: 2017-02-01
End date: 2021-01-31
Duration (months): 48.0
Total project cost (EUR): 1650632.5
EU funding (EUR): 1650632.5
Participants: 4
Project status: CLOSED

In SORCERER revolutionary lightweight electrical energy storing composite materials for future electric and hybrid-electric aircraft are to be developed. Building on previous research novel lightweight supercapacitor composites, structural battery and structural energy generating composite materials are to be realised for aeronautical application and demonstrated on the systems level. Such demonstration ranges from table-top demonstrators for structural batteries and energy harvesting materials to aircraft component demonstrators for structural supercapacitors. The SORCERER consortium consist of the world leading research groups on structural power composites. The team has an outstanding scientific track record in research covering all aspects of structural power composites development and manufacture namely: multifunctional matrices (SPE) and carbon fibres (i.e. constituents); separator materials and designs; structural electrodes; connectivity and power management and materials modelling and design. In SORCERER we will build on these experiences to adapt current structural power composites solutions for aeronautical applications as well as develop new materials and devices for the aircraft application. By the end of the project each technology, i.e. structural supercapacitor, battery and power generation device, will have matured and as a result been brought-up at least one step on the TRL scale. In particular, the developed devices will be demonstrated on the systems level. For all structural battery and power generation composite materials this will be the world’s first demonstration on that level of complexity.

Keywords: composites,batteries,supercapacitors,multufunctional
CAD WALK: Enabling Computer Aided Diagnosis of Foot Pathologies through the use of Metric Learning (CAD WALK)

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: Belgium
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-10-01
End date: 2019-09-30
Duration (months): 24.0
Total project cost (EUR): 160800.0
EU funding (EUR): 160800.0
Participants: 1
Project status: CLOSED

Dynamic plantar pressure imaging (PPI) refers to the measuring, across time, of pressure fields between the foot and the ground. PPI is used, in part, to diagnose foot problems such as metatarsalgia and plantar fasciitis. Despite the widespread clinical use of PPI, its diagnostic potential has not been fully exploited. PPI creates large and dynamic datasets that cannot be easily analysed and interpreted by the human brain. As a result, PPI images are subsampled before being clinically examined, which discards potentially valuable information. The objective for this action is to improve the diagnostic value of PPI through the introduction of a computer-aided diagnosis (CAD) system called CAD WALK. Using concepts from my previous CAD research (STEAM), CAD WALK will build a statistical model of PPI images from a healthy population. To test a new patient, their PPI image will be aligned to the model and compared to that healthy population using statistical tests. Outliers from these statistical tests will then be highlighted to help guide a clinician’s examination of the full PPI image. As a novel addition, metric learning will be introduced to create a statistical model that is more specific to the test subject. A key goal of this action is the deployment of CAD WALK as a supported software product. To do so, we propose a Triple ‘i’ (international, intersectoral, interdisciplinary) initiative that partners me with industry (rs scan®) and clinical end users (Sint Maartenskliniek, NL) to translate my CAD research into practical use. Through this process, and a secondment with industry partner rs scan®, I expect to deepen my knowledge of industrial product development (i.e. intellectual property rights, industry regulations, customer constraints) and improve my management skills. By addressing these two gaps in my career experience, I expect to move one step closer to fulfilling my ambition of leading my own research translation lab.

Keywords: voxel based analysis,kernel regression,atlas construction,statistical testing,medical imaging
Transcriptional control of plasma cell development and function (PlasmaCellControl)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced 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: Austria
Call: ERC Advanced Grant (ERC-2016-ADG, 2016)
Start date: 2018-01-01
End date: 2023-12-31
Duration (months): 72.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 1
Project status: SIGNED

Antibody-secreting cells consisting of short-lived proliferating plasmablasts and long-lived quiescent plasma cells are essential for the acute response to infection and long-term protection of the host against pathogens. Only a few regulators (Blimp1, IRF4, XBP1, Aiolos, Ikaros and E-proteins) have been implicated in the transcriptional control of antibody-secreting cells, and their target genes, with the exception of Blimp1 and E-proteins, are still unknown. This proposal aims to systematically identify key players in the development and function of antibody-secreting cells by using the CRISPR/Cas9 and Cre/loxP methods. For this, we improved existing protocols to extend the duration of in vitro plasmablast differentiation and showed that Rosa26(Cas9/+) B cells infected with Blimp1 or Xbp1 sgRNA-expressing retroviruses recapitulated the Blimp1 and Xbp1 mutant phenotypes in this proof-of-principle experiment. Moreover, Cre retrovirus-mediated deletion of Irf4, Ikaros and Aiolos strongly impaired plasmablast differentiation in this optimized system. To discover new regulators of plasma cell differentiation, CRISPR/Cas9-based screens will be performed with pooled sgRNA libraries targeting all known upregulated genes in plasmablasts and plasma cells, followed by individual validation of the best hits. Selected top-ranked genes will be analyzed in vivo by conditional mutagenesis with newly generated, plasma cell-specific Cre lines. Regulated target genes of IRF4, Ikaros, Aiolos, XBP1 and the XBP1-regulated transcription factor Bhlha15 will be identified in plasmablasts by ChIP- and RNA-seq analyses. Target genes with potentially interesting functions will be further characterized by CRISPR/Cas9- or Cre/loxP-mediated mutagenesis. These experiments will provide fundamentally new insight into the molecular mechanisms controlling the development and function of antibody-secreting cells, which are the essential effector cells of humoral immunity.

Keywords: plasma cell development and function,crispr,cas9 screen for key regulators,conditional cre mediated mutagenesis,target genes of plasma cell specific transcription factors,transcriptional networks
Coordinated control and spectrum management for 5G heterogeneous radio access networks (COHERENT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Theme: Future Internet: Software, hardware, Infrastructures, technologies and services
Action type: Research and Innovation actions
Countries involved: Germany,Italy,Germany,Germany,Israel,Finland,Poland,Greece,Sweden,France,France,United Kingdom
Call: Advanced 5G Network Infrastructure for the Future Internet (H2020-ICT-2014-2, 2014)
Start date: 2015-07-01
End date: 2018-03-31
Duration (months): 33.0
Total project cost (EUR): 6024299.0
EU funding (EUR): 6024299.0
Participants: 16
Project status: CLOSED

The exponential growth of mobile traffic, drastically increasing of network complexity, and the strong need for inter-network coordination of wireless network resources call for breakthroughs in control, coordination and flexible spectrum management in 5G heterogeneous radio access networks. The COHERENT project aims to address these problems by researching, developing and validating a novel control framework for future mobile networks. The key innovation of COHERENT is to develop a unified programmable control framework to coordinate the underlying heterogeneous mobile networks as a whole. The COHERENT control framework has two unique features to deal with the insufficiency of current control solutions for inter-network coordination. First, theories and methods to abstract the low layer network states and behaviors of different underlying mobile networks are developed, which provides a simplified but sufficient abstracted network view for network-wide control and resource coordination. Network abstraction will significantly reduce the signaling overhead, making scalable network-wide control solutions feasible, and enable more flexible spectrum management, which are key for the success of 5G networks. Second, based on the abstracted network view, common interfaces and software-development kits will be developed to enable programmability in controlling and coordinating heterogeneous mobile networks. The programmable control will provide operators a flexible and cost efficient way to implement new control functions and thus to support new services. The innovative impact of the COHERENT project is in enabling a unified control and coordination framework for heterogeneous mobile networks by combining innovative approaches on abstraction of low layers in underlying mobile networks, software defined networking, and flexible spectrum management. COHERENT will build a true proof-of-concept prototype to demonstrate the applicability and benefits of its approach.

Keywords: heterogeneous radio access networks,programmability,radio resource management,network abstraction,spectrum management,traffic steering,energy efficiency
Performance Improvement for Vehicles on Track 2 (PIVOT2)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: European rail initiative
Action type: Innovation actions
Partnership: Shift2Rail (Art-187)
Countries involved: Spain,Austria,Austria,Germany,Germany,Germany,Germany,Germany,Germany,Spain,Spain,Spain,Italy,Italy,Austria,Sweden,Hungary,Sweden,France,France,France,France,United Kingdom,United Kingdom,Portugal
Call: Development of new technological concepts towards the next generation of rolling stock, applied to major subsystems such as Car body, Running Gear, Brakes, Doors, Modular interiors and HVAC (H2020-S2RJU-CFM-2019, 2019)
Start date: 2019-10-01
End date: 2023-06-30
Duration (months): 45.0
Total project cost (EUR): 24568171.76
EU funding (EUR): 17845062.0
Participants: 40
Project status: SIGNED

PIVOT2 is a continuation of the PIVOT project which was scheduled to finish in September 2019. PIVOT2 will build on the work and concepts of PIVOT and move all of these concepts to higher TRL levels. The overall ambition of PIVOT2 is to develop technologies that are lighter, more energy efficient, more comfortable for passengers and with a lower impact on the track, thereby reducing the life cycle cost not only of the vehicle itself, but of the entire railway system. Technologies that increase the operational reliability of trains, causing less travel disruptions, ensuring that passengers get to destination on time and delivering a better service are also objectives. It is expected that technologies developed should automatically promote the increase of the transport capacity of railway lines. The ambitions of Shift2Rail, which are inherited by PIVOT2, require substantial ground-breaking improvements in the six key technology areas addressed by the project. Indeed, current vehicle solutions are getting closer to their enhancement limits and new radical proposals must be envisaged to accomplish the goals. PIVOT2 will be dealing with the same five key technical demonstrator (TD) areas that were advanced in PIVOT, these are Car body shell, Running gear, Brakes, Accessibility and Doors and Modular Interiors. Within these areas the results are expected to achieve a TRL 7. A new TD for Heating, Ventilation and Air Conditioning (HVAC) has been added which should achieve a TRL 4.

Keywords: carbody shell,running gear,brakes,entrance systems,doors,modular interiors,hvac
TRansport Innovation for vulnerable-to-exclusion People needs Satisfaction (TRIPS)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: Research and Innovation actions
Countries involved: Austria,Italy,Italy,Italy,Germany,Ireland,Belgium,Sweden,Croatia,Bulgaria,Netherlands,Portugal
Call: An inclusive digitally interconnected transport system meeting citizens' needs (H2020-MG-2019-SingleStage-INEA, 2019)
Start date: 2020-02-01
End date: 2023-01-31
Duration (months): 36.0
Total project cost (EUR): 2831175.0
EU funding (EUR): 2831175.0
Participants: 14
Project status: SIGNED

Eighty million European citizens face long-term physical, mental, intellectual or sensory impairment. The goal of TRIPS is to design, describe and demonstrate practical steps to empower people with disabilities to play a central role in the design of inclusive digital mobility solutions. The consortium brings together pan-European networks of users (ENIL), transport organisations (UITP), assistive technology experts (AAATE) and municipalities to engage in open innovation on mobility. Supported by design methodology experts (TUE), systems integration experts (TB) and privacy experts (TRI) TRIPS will deliver and deploy a Co-design-for-All methodology (WP5) in 7 pilot cities - Lisbon, Zagreb, Bologna, Cagliari, Brussels, Sofia, Stockholm (WP6). TRIPS will conduct research on needs and attitudes towards future mobility solutions (WP2); review the state-of-the-art on accessibility, mobility and related digital and assistive technologies and policies (WP3) and devise an index to measure mobility. We will bring together users and transport experts to discuss institutional barriers to adoption, agree innovation priorities and policy changes (WP4) and co-develop an innovation roadmap and research priorities (WP7). The consortium utilises its international reach to validate outcomes with a wider range of vulnerable-to-exclusion users to ensure that outcomes are relevant to the wider population and transport ecosystem. To achieve this, we reach out to senior citizens and migrant organisations, transport operators, municipalities, assistive technology providers as well as academics and students in design, transport management, and public administration. In doing so, we will address the expected impacts of the call to help (a) regional authorities and businesses in designing digital transport solutions that cater for individual needs and (b) support policy-makers in designing appropriate regulatory frameworks and social and educational strategies.

Keywords: co design,methodology,future urban mobility systems,participation,design research,assistive technologies,inclusive transport,user studies,policy recommendations
Self-Powered Skin Patch for Cystic Fibrosis Diagnosis (POWER-PATCH)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Products and processes engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: Spain
Call: ERC Proof of Concept Grant (ERC-2019-PoC, 2019)
Start date: 2020-01-01
End date: 2021-12-31
Duration (months): 24.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Cystic fibrosis (CF) is a genetic autosomal recessive disease, which induces mutations on a conductance transmembrane regulator protein (CFTR) that controls the exocrine system responsible or producing saliva, sweat, tears and mucus. The protein malfunction affects severely the lungs and digestive system. Patients with CF present also higher chloride contents in sweat than healthy subjects, so chloride testing in sweat has become the gold standard test for CF confirmation after new-born screening blood tests. However, tests on new-borns are not 100% sensitive and not universally stablished along European territory, which leads to patients with a late diagnostic that decreases their life quality and expectancy. The ‘sweat test’ requires either sophisticated analytical procedures or costly commercial analyzers and consumables that restrict the availability of the test to few specialized units scattered along the European territory. POWER-PATCH aims to evolve and promote the value of a novel, market disruptive patch that enables an affordable and easy-to-use sweat test for the screening of cystic fibrosis. The patch has been conceived to be applied on the forearm of the patient and yield a “positive” result in case of an abnormal conductivity level of sweat is detected. It combines the low cost and easy handling of paper that is associated with the filter paper-based diagnosis technique and at the same time allows obtaining a digital response with no further handling or treatment of the sample. Moreover, as it already contains a “battery sensor”, sweat collection and testing does not require additional equipment and can be easily taken to any clinical environment. Within this ERC PoC project, we aim to achieve (i) Technical validation and Clinical testing in a specialized CF unit and (ii) a business proposition in the form of a Business Plan containing strategies for commercialization, fundraising, IP management and future product development.

Keywords: diagnostic devices,paper batteries,cystic fibrosis,medical device,self powered sensor,conductivity sensor