Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Light-matter interaction with structured light (LIMAStruct)

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: Physics
Countries involved: France
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-09-01
End date: 2018-08-31
Duration (months): 24.0
Total project cost (EUR): 185076.0
EU funding (EUR): 185076.0
Participants: 2
Project status: CLOSED

The full structuration of light in the transverse plane, including intensity, phase and polarization, holds the promise of unprecedented capabilities for applications in classical optics as well as in quantum optics and information sciences. Harnessing special topologies can lead to enhanced focusing, data multiplexing or advanced sensing and metrology. In this context, the present project aims at interfacing atomic ensembles with structured light exhibiting high topological charges, beyond the two-dimensional case. Two directions will be investigated: the realization of highly multimode quantum memories at the single-photon level with applications to quantum networks, and the demonstration of highly-sensitive magnetometer based on photonic gears.

Keywords: orbital angular momentum,structured light,atomic ensemble,vortex beams
Advancing Econometric Methods for Analyzing Data from Regression Discontinuity Designs (RD-ADVANCE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Individuals, Markets and Organisations
Panel description: Economics, finance and management
Countries involved: Germany
Call: ERC Consolidator Grant (ERC-2017-COG, 2017)
Start date: 2018-09-01
End date: 2023-02-28
Duration (months): 54.0
Total project cost (EUR): 878970.0
EU funding (EUR): 878970.0
Participants: 1
Project status: SIGNED

Over the past two decades, regression discontinuity (RD) designs have become one of empirical economics' most popular strategies for estimating causal effects from observational data. In such designs, units are assigned to the treatment group if and only if a special covariate, or running variable, falls above a known cutoff value. Under mild conditions, those units close to the cutoff are as good as randomly assigned to receive the treatment, which provides a simple and transparent source of identification of the treatment's causal effect. This project extends the range of methodological tools available to applied researchers working with data from RD designs. It is divided into three parts. The first part develops methods for incorporating covariates and group structures into the analysis of RD designs by adapting modern machine learning methods and empirical Bayes approaches. The second part considers RD designs with a discrete running variable. It shows that current state-of-the-art inference procedures are likely to be misleading in such settings, and develops new confidence intervals for causal effects. The third part develops methods for estimation and inference that account for manipulation in RD designs. Here manipulation refers to any strategic action taken by the actors within the respective institutional context that leads to observational units on different sides of the cutoff being non-comparable. The part develops a general framework for manipulation with corresponding nonparametric methods for estimation and inference, and considers various extensions. Given the huge popularity of RD designs, and the proposal's focus on practical methods, this project has the potential to have a sizable impact on empirical economic research in a number of policy relevant areas, including education and public finance; but also on other branches of science where researchers commonly work with observational data, such as sociology or epidemiology.

Keywords: causal inference,nonparametric estimation,clustering
Efficient hydrogen sensing with atomically engineered materials (H2OXIDES)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Condensed matter physics
Panel description: Structure, electronic properties, fluids, nanosciences, biological physics
Countries involved: Netherlands
Call: ERC Proof of Concept Grant (ERC-2019-PoC, 2019)
Start date: 2019-09-01
End date: 2021-02-28
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Hydrogen will be a key element of our future decarbonised economy as a sustainable energy vector. In the future economy, efficient hydrogen sensors will be a critical element. The high flammability of air-hydrogen mixtures and the minimal input power required to trigger combustion pose serious safety concerns. The light nature of the hydrogen molecule and its high diffusivity makes detection and leakage-control particularly challenging. Leak detection in a distribution network requires the availability of sensing elements with demanding performance targets. The objective of this project is to harness recent results in fundamental research in oxide electronics to develop an innovative material platform for ultra-sensitive resistive hydrogen sensors.

Keywords: oxide electronics,transition metal oxides,oxide interface engineering
Big Data EEG Recording and Analysis platform (WhiteBox EEG)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Active ageing and self-management of health
Action type: SME instrument
Countries involved: Slovenia
Call: Accelerating market introduction of ICT solutions for Health, Well-Being and Ageing Well (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2016-07-01
End date: 2016-12-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The main objective of our project is to develop and commercialise a world`s first scalable, multipurpose, high-throughput, Big Data EEG Platform that connects and controls large number of individual EEG amplifiers at the same location. With this innovative solution, we are meeting increasing demands of researchers, doctors and other EEG practitioners for more efficient EEG recording, that has become a bottleneck in modern neuroscience, and for larger samples in EEG reseach. Thus with the increased recording capacity of 10+ subjects simultaneously, up to 10 times faster recording output and up to 40% in cost savings compared to the existing EEG recording solutions, our innovative solution will disrupt the market for EEG research & medical diagnostics, EEG equipment and recording platforms and applied neuroscience. Furthermore, the high-throughput capabilities and the scalability of the WhiteBox platform provide an answer to a lack of larger databases of standardised and consistent EEG recordings, that enable Big Data approaches and which are crucial for the clinical validation of biomarkers. Our disruptive innovation not only makes the existing EEG recording and analysis faster and cheaper but through its scalability also represents a big opportunity to bring the benefits of EEG brain-imaging technology to new areas of use ranging from medical & research field (such as EEG based predictive disease diagnostics, personalised medicine, big data EEG analysis) to the emerging field of applied neuroscience (such as NeuroEducation, Neuromarketing/Consumer Neuroscience, Neuro-HR and Change Management, User Centred Neurodesign and EEG performance optimization in Professional Sports). The purpose of the Phase 1 is to outline the full scope of further development potential of our innovative solution, involving the technical and business viability issues, also regarding the analysis of associated risks and the exploitation of the project`s commercial potential to the fullest.

Keywords: big data,brain imaging,scalability,high throughput eeg recording and analysis,screening,clinical validation of biomarkers,disease prediction and diagnostics,ageing population
The effect of pro-aging and pro-youthful blood factors in normal ageing and Alzheimer’s disease: a multimodal approach (BioALFA)

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: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2018-01-01
End date: 2020-01-14
Duration (months): 24.0
Total project cost (EUR): 158121.6
EU funding (EUR): 158121.6
Participants: 1
Project status: CLOSED

The overall aim of the planned research is to test whether pro-aging and pro-youthful blood factors are associated with cognitive performance and neuroimaging outcomes in normal ageing and in individuals at risk of Alzheimer’s disease (AD), and whether this association is modified by lifestyle habits (e.g. exercise or diet) or genetic factors. Ageing is the most important risk factor for AD. However, the exact mechanism that link ageing and AD is still unknown and, up to now, potential therapies for AD by targeting ageing have been poorly explored. Thus, in the present project we aim to provide a better understanding of the link between ageing and AD by measuring in human blood those factors that have been found to be ‘pro-youthful’ (GDF-11) or ‘pro-aging’ (CCL2, CCL11 and CCL19) in experimental animal models, but have not been comprehensively studied in humans. For these purposes, we will first develop novel and highly specific and sensitive assays based on the state-of-the-art Simoa platform. Next, we will measure these factors in the participants of the ALFA (Alzheimer and Families) study, which is currently taking place in the Barcelonaβeta Brain Research Centre (BBRC), the host institution of this project. The ALFA cohort is composed of 2743 cognitively healthy individuals (45 to 75 years old) from which comprehensive clinical, neuropsychological, neuroimaging, genetic and environmental and lifestyle factors data are already available. Measurements will be performed in two steps: a training cohort and a validation cohort. Finally, we will investigate the association of the levels of the pro-aging/pro-youthful blood factors with features known to be related to AD such as clinical and life-style variables, neuroimaging outcomes and signatures and genetic variables. Altogether, the results of this project will clarify whether those blood pro-aging or pro-youthful factors may become potential therapeutic targets in AD.

Keywords: alzheimer s disease,ageing,blood biomarkers,preclinical alzheimer s disease
Integrated Design of Engineering Structures (InDEStruct)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Innovative Training Networks (ITN)-European Industrial Doctorates
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Denmark,United Kingdom,United Kingdom,Denmark
Call: Innovative Training Networks (H2020-MSCA-ITN-2017, 2017)
Start date: 2018-04-01
End date: 2022-09-30
Duration (months): 54.0
Total project cost (EUR): 1093151.52
EU funding (EUR): 1093151.52
Participants: 8
Project status: CLOSED

This collaborative doctoral training programme provides a model for the development of technology leaders, enabling them to apply scientific methods from academia to interdisciplinary industrial design. The project is driven by the need for more efficient & lower emission engine systems. Heat exchangers in engines has been identified as a key enabling technology for low-emission power systems that is vital to the EU economy and is of great societal concern. Development of high-performance heat exchangers is a complex engineering challenge requiring academic contributions at the forefront of engineering science, which will enhance the EU’s competitiveness by delivering economically and environmentally improved products. Having identified charge air cooling as a key enabling technology for low-emission power systems, here we propose an integrated approach to doctoral training in the area of engineering design leading to four doctorates covering diverse aspects of their mechanical engineering: structural vibration, stress & thermal analysis, additive manufacturing (AM), multifunctional metamaterials, fatigue & materials development. This project brings together a consortium of industrial and academic partners in a novel and bespoke doctoral training programme that is multi-disciplinary in its content and inter-sectoral with regards to the employability of the technology leaders of tomorrow. The programme provides a coherent training platform that inherently nurtures technical, creative and entrepreneurial skills. The central theme of Engineering Design within the programme enables us to build a training structure which is technically broad yet scientifically rigorous, while having the academic depth expected of a doctoral programme. The programme provides mobility, industrial experience and academic foundations in an integrated manner that will uniquely equip our future technology leaders to contribute to high-value innovation within EU industry.

Keywords: charge air cooler design,structural vibration,stress and thermal analysis,fatigue life,prediction and materials development,engineering design,exhaust gas recirculation,technology
Identification and characterisation of new class of PI3K modulators in oncology (PI3K MODULATORS)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2019-05-01
End date: 2021-04-30
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 1
Project status: CLOSED

PI3K signalling is a critical regulator of many cellular functions including cell growth and survival, and is deregulated in cancer and auto-immunity. This proposal is based on the concept to cause cell death by hyperactivating signalling in cancer cells above a tolerable threshold. This idea has been previously proposed for other kinases, but no small-molecule activators were available to formally test the idea. This proposal focuses on activators of the leukocyte-enriched PI3Kd, an isoform of PI3K that is involved in immune regulation and haematological malignancies. The 3 key objectives and their approaches are: 1. To discover and characterise small-molecule PI3Kd activators. This will be achieved using a combination of virtual screening and high throughput screening. 2. To understand the mechanism of PI3Kd activation. This enables understanding of how these activators function, and provides structural data that can be used for structure-based design and compound improvement. This will be achieved using structural biology (HDX-MS and crystallography), biochemical (lipid kinase) and biophysical (binding) assays. 3. To determine the activity of PI3Kd activators in haematopoietic malignancies. In order to use PI3Kd activators in cancer therapy, it is critical to determine the conditions under which hyperactivation of PI3Kd results in cancer cell death. This will be achieved with a panel of B and T-cell lymphoma cell lines using cell viability assays under different conditions. These objectives integrate my expertise in compound screening, molecular modelling and compound design with the world-leading expertise of the Host Lab in PI3K signalling, cancer biology and drug development. This proposal aims to make breakthroughs in understanding PI3K signalling, its exploitation in drug development and in cancer-therapy. This will be a key turning point in my scientific career and facilitate PI3K drug development collaborations of the Host Lab with the pharmaceutica.
A new standard for food safety and quality (ImpactVision)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: United Kingdom
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2019-01-01
End date: 2019-06-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

ImpactVision is a machine learning company, applying advanced imaging technology to food supply chains in order to improve food quality, generate consistent products and reduce waste. Our software provides insights about the quality of foods and is aimed at food processors, manufacturers, distributors and retailers. For example, our system is able to determine the freshness of fish, the ripeness of avocados or the presence of foreign objects rapidly, non-invasively and at production grade speeds. Hyperspectral imaging technology captures information our eyes cannot, in other parts of the electromagnetic spectrum. Our goal is to provide objective, real-time food quality data to the 30,000+ food processing facilities across the USA and improve efficiency of the global food supply chain. Currently, a third of all food produced is wasted. To illustrate the environmental impact at scale, managing food waste sustainably could reduce greenhouse gas emissions by over 500 million tonnes - the equivalent of taking all the cars off the road in the European Union. By digitizing food quality control, we improve yields and prevent waste, whilst increasing food companies’ revenues, which is particularly prescient considering the industry has razor thin profit margins. ImpactVision combines a hyperspectral sensor installed above a conveyor belt with software that analyzes images and provides real time insights about quality. By pursuing the present feasibility study, the management team aims to improve its understanding of international market conditions and the associated risks that need to be considered as the company develops a deeper business plan for rolling out, and scaling up ImpactVision as a marketable innovative solution. SME Instrument Phase-1 and Phase-2 will be extremely beneficial in helping the company to accelerate development and market penetration of the solution in target segments, boosting the company’s growth to 94 employees and $109M revenues by 2024.

Keywords: food quality,food preservation,food safety,decision making,real time assessment,secure food system,insights
The search for new physics through precision measurements of the CKM angle gamma (ONEDEGGAM)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Fundamental constituents of matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2017-STG, 2017)
Start date: 2018-06-01
End date: 2025-05-31
Duration (months): 84.0
Total project cost (EUR): 1499955.0
EU funding (EUR): 1499955.0
Participants: 1
Project status: SIGNED

There is a strong conviction that the Standard Model of particle physics is only a low energy approximation to a higher energy theory containing new fundamental particles. For example, it is not possible to explain the large asymmetry between the properties of matter and anti-matter that must exist to create the universe within we live, with the Standard Model that can only accommodate asymmetries orders of magnitude smaller. The theoretical framework that describes these asymmetries is the Cabibbo-Maskawa-Kobayashi (CKM) matrix. Through study the of the differences between the decay of certain types of hadrons containing a beauty quark, and the corresponding anti-particle decays, this project will lead to a precision measurement of a phase commonly called “gamma” which is related to some of the elements of the CKM matrix. The beauty hadron decay chain involves subsequent decay of charm hadrons, which are not well understood. By understanding this part of the process, in a larger range of decay modes and with significantly enhanced sensitivity than previously possible, the overall understanding of the beauty hadron decay chain is improved. Using the distinctive data collected by the BESIII in China, it is possible to make a number of new measurements that relate to the decay of charm hadrons. With this knowledge it becomes possible to gain considerably more sensitivity from the copious amounts of beauty hadron decays that will be collected by the LHCb experiment at CERN and the Belle II experiment in Japan over the timescale of this project. This new strategy to exploit the synergy between the different experiments means that a global precision of 1° is within reach. This precision has excellent potential to uncover significant discrepancies within the CKM matrix that can only be explained by physics beyond the standard model. This would launch particle physics into the next era of discovery.
Multi-scale computational hemodynamics in obese children and adolescents: enabling personalised prediction of cardiovascular disease (CALLIRHEO)

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: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2018-03-01
End date: 2020-02-29
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

Childhood obesity is currently at epidemic rates, with serious risks for cardiovascular disease in adulthood and premature death. Obesity is known to accelerate the initiation of endothelial dysfunction and alter the hemodynamics in young arteries. In alignment with urgent EU and worldwide policies on understanding childhood adiposity, we propose to develop a novel and safe computational tool to study numerically, for the first time, the obesity-altered hemodynamics in children and adolescents. The project aims to transfer the non-invasive computational fluid dynamic technology to the paediatric practice and enable personalised prediction of cardiovascular disease and effective decision-making. Within a multi-scale modeling framework, the proposed study seeks to utilise high-fidelity state-of-the-art numerical methods and develop new ones, for the implementation and coupling of the 3D flow in anatomically realistic arterial geometries with macroscopic and microscopic information, ensuring high stability and accuracy of results. In conjunction with clinicians, the study will perform patient-specific numerical simulations, correlated with medical data, and help towards individualized treatment planning, with a significant impact on the quality of life of the young patient. This multidisciplinary perspective is fundamental in elucidating early vascular changes induced by obesity and predict cardiovascular disease risks, while protecting the young population.

Keywords: childhood obesity,cardiovascular hemodynamics,numerical modelling