Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Designing Human-centered Sustainable Cyber-physical Systems of the Future (Sustainable-CPS)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Sweden,Sweden,United States
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-09-01
End date: 2024-04-29
Duration (months): 24.0
Total project cost (EUR): 190559.04
EU funding (EUR): 190559.04
Participants: 3
Project status: SIGNED

This proposal presents the research idea of an experienced researcher (ER), Didem Gürdür Broo, which is called “Designing Human-centered Sustainable Cyber-physical Systems of the Future” (Sustainable-CPS). The project is designed as a research training fellowship between KTH, Royal Institute of Technology (beneficiary for m1-m12), Uppsala University (beneficiary for m13-m24) located in Sweden and Stanford University (partner organization) located in the United States of America. Didem Gürdür Broo invited to work in Professor Leifer’s designX research lab at Stanford University. ER wants to initially work with the research group at Stanford for a year to develop a framework through small case studies and observations and then come back to Sweden to introduce and evaluate the framework through workshops. Today, CPS exist everywhere in different sizes, with different functionalities and capabilities. Some examples can be listed as smart cities, industry 4.0 applications, internet of things, autonomous systems, intelligent transport systems and so on. Several characteristics of these systems are new and these new properties push the limits of traditional engineering practices. Some examples of these new characteristics are intelligence, autonomy, connectivity, and collaboration. Moreover, today’s engineering education and practices are preliminarily concentrating to solve technical problems related to these systems and, unfortunately, do not include sustainability and social implications perspective as default. Sustainable-CPS project aims to use interactive, collaborative, and innovative tools from design thinking, systems thinking and future studies to develop a framework and a toolkit to support the design of future CPS by primarily focusing on human needs, social implications and sustainability.

Keywords: human centered design,sustainability,future,cyber physical systems,engineering education
Unravelling the mechanisms of competence induction by antibiotic stress in Streptococcus pneumoniae (PneumoCompetence)

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: Netherlands
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-05-01
End date: 2017-04-30
Duration (months): 24.0
Total project cost (EUR): 165598.8
EU funding (EUR): 165598.8
Participants: 1
Project status: CLOSED

Despite the introduction of several vaccines, the human pathogen Streptococcus pneumoniae remains one of the leading bacterial causes of mortality worldwide, killing 1 million of children each year. In developed countries, the rise of multi-drug resistance in S. pneumoniae during last decade is a serious cause of concern, since the patient is more likely to require hospitalization consuming high health resources, and increasing the risk of death. The main mechanism by which S. pneumoniae acquire and spread antibiotic resistance is by activation of the competence state that allows the uptake of exogenous DNA. Strikingly, competence is induced by several antibiotics, but the molecular mechanisms driving competence development are poorly understood. Our approach integrates the use of promoter-luciferase fusions to competence genes, transposon-mutagenesis and -sequencing, total RNA sequencing, knockout strains constructions and time-lapse fluorescence microscopy, to identify clinical antimicrobials that induce competence and unravel its underlying molecular mechanisms. Data generated in this project will provide a better understanding of the mode of action of these antibiotics and give valuable molecular insights into the evolution of antibiotic resistance in S. pneumoniae. Finally, we will test thousands of pairwise drug combinations in a novel high-throughput screen to identify inhibitors of the competence process. This highly relevant project will provide new pre-clinical data for future novel treatment strategies against bacterial infections and the mitigation of the spread of antibiotic resistance.

Keywords: antibiotics,competence development,high throughput screening,streptococcus pneumoniae,bacterial stress response
Sparse Composite Likelihood Inference in Count Time Series (SCouT)

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: Italy
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-06-01
End date: 2018-05-31
Duration (months): 24.0
Total project cost (EUR): 168277.2
EU funding (EUR): 168277.2
Participants: 1
Project status: CLOSED

The availability of many interesting datasets consisting of count time series has motivated a steadily increasing research activity towards the development of appropriate statistical models. Nowadays, a variety of time series models constructed on the basis of the integer-valued property of count data is available. However, their practical usefulness is often limited because of difficulties to implement efficient estimation procedures. These difficulties grow significantly when higher-order autoregressive and moving average terms are included in the model or when multivariate time series data are considered. The SCouT project aims to enhance the flexibility of time series models for counts and facilitate their application to data characterized by complex dependence structures. To this end, the SCouT project proposes an innovative methodological approach that integrates two powerful statistical tools, that is sparsity techniques and composite likelihood methods. The project will provide a unified framework for simultaneous order selection and estimation of autoregressive and moving average terms in count time series models, reducing considerably the computational burden of traditional model selection approaches and improving the predictive performance of the fitted model. The potential of the suggested methodology will be further highlighted by investigating its extensions to spatial and spatio-temporal data that are usually characterized by complex dependence structures. Such data are often met in the field of temporal and spatial analysis of public health surveillance data that will be the main application field of the project. The simultaneous order selection and estimation procedure established by the SCouT project will offer great support to statistical methods for public health surveillance and significantly contribute to the achievement of the effective and timely detection of disease outbreaks.

Keywords: composite likelihood,count time series,public health surveillance,sparse penalty
Trucks as a part of the grid, energy storage made easy (ALELION)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Sweden
Call: Stimulating the innovation potential of SMEs for a low carbon and efficient energy system (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-06-01
End date: 2017-11-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Alelion is a leading actor within innovative energy solutions for lifttrucks and goods management vehicles, and a strong force in the development of the lifttrucks of tomorrow. The company cooperates with a number of leading suppliers (Samsung), manufacturers (Toyota, Jungheinrich) and end users (IKEA). Alelion’s innovation capacity has led to a unique solution that makes existing battery storages within the goods management sector avaliable for use as grid-connected battery storages. The Alelion concept is an effective tool to balance demand and supply in the new, sustainable energy landscape, while creating new business advantages for the users such as increased dependability, lowered costs and increased availability of trucks in end-user fleets Through a ground-breaking solution, Alelion makes new and existing battery storage in lifttruck fleets avaliable for use as power-grid balancing units. This contributes to bridging fluctuations from renewable energy, such as wind and photovoltaic sources. Meanwhile Alelion’s lithium-ion battery solutions supported by fleet- and energy management systems increase dependability, serviceability and overall operational economy for end users with a proven ROI in less than a year. Alelion will, trough already proven collaboration with partners in the value chain, provide great sustainability benefits to society as well as to end users in the lifttruck sector. The overall objectives are yearly reduction of energy use corresponding to one mid-size nuclear reactor, Alelion’s staff increased by 350% during the project period, demonstrators running in 4 EU countries and an increased exposure (through EU project participation) by at least 15 times.

Keywords: energy storage,lifttrucks of tomorrow,battery storage
High volume production facility for high accuracy nanocapsules (NANOHIGH)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Nanotechnologies
Action type: SME instrument
Countries involved: Spain
Call: Accelerating the uptake of nanotechnologies, advanced materials or advanced manufacturing and processing technologies by SMEs (H2020-SMEINST-1-2015, 2015)
Start date: 2015-12-01
End date: 2016-05-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The overall objective of NANOHIGH is the deployment in the market of an innovative technology for the production of high accuracy fibered/spherical-shaped nanocapsules based on principles of ElectroHydroDynamics (EHD). This technology, known as Coaxial EHD, enables the cost-effective manufacture of high accuracy capsules with special configurations and functionalities, which can be used for the controlled delivery of active compounds in multiple applications. The performance of this patent protected technology has been demonstrated in a lab scale pilot; however, its derivative products have not fully entered the market due to the lack of industrial scale equipment, required for the market deployment.

Keywords: nanomcapsules,high accuracy,materials
A hands-free remote monitoring solution for continuous and accurate medical grade assessment of heart health (wellwatch)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: United Kingdom
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2017-02-01
End date: 2017-04-30
Duration (months): 3.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Cardiovascular disease (CVD) is the leading cause of death in the EU with over 4m deaths annually. Although up to 80% of premature deaths are preventable through early prognosis and treatment the associated costs are significant with global estimates of €41tn in the next 25 years. There is an increasing focus on making care more patient-centric which could save €99bn in healthcare costs in the EU annually. Currently the only medically acceptable method of monitoring a CVD condition includes a trip to the hospital, a complete 12 lead ‘wet’ electrocardiogram (ECG) and a follow-up with a doctor. This process is time-consuming, costly to hospitals and provides only a snapshot of a patient’s heart health. At Smartlife, we have developed wellwatch; a wearable technology garment with our patented textile sensors built in and our unique contactless electronics hub that transmits signals to a mobile application for remote monitoring by patient and clinician. Our technology can be truly disruptive – assisting in the diagnosis of early onset or predictive heart conditions. To gain first mover advantage in the challenging medical market we must secure our supply chain, fully develop the care pathway and present an attractive value proposition to licensees and suppliers. We expect our initial route to market will be through private healthcare, as historically they have a faster uptake of novel solutions. The primary aim of our overall innovation project is to develop a clinically and economically validated wellwatch platform for self-monitoring of CVD. The objective of this feasibility study is to develop our business model for successful commercialisation of wellwatch. The market size of smart textiles in medical applications is forecast to be worth €0.9bn by 2021; our growth projections for wellwatch are to achieve a 5-year ROI of 250% for Smartlife following market entry in 2019, based on our estimated project costs this equates to an ROI of 770% to the EC.

Keywords: sensor,biometric,contactless,cardiovascular,algorithm,smart textile,remote monitoring
Molecular logic lab-on-a-vesicle for intracellular diagnostics (LOGIC LAB)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Innovative Training Networks (ITN)-European Training Networks
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: Germany,Ireland,Germany,Poland,Poland,Slovakia,Netherlands,Netherlands
Call: Innovative Training Networks (H2020-MSCA-ITN-2018, 2018)
Start date: 2018-11-01
End date: 2023-10-31
Duration (months): 60.0
Total project cost (EUR): 3538684.44
EU funding (EUR): 3538684.44
Participants: 15
Project status: SIGNED

A dysfunction of cells lining the inner walls of blood vessels, i.e. the endothelium, is the primary cause of many lifestyle related diseases. According to the WHO, those diseases accounted for 60% of all deaths worldwide in 2005. Tailor-made diagnostic tools for early and reliable identification of endothelial dysfunction are urgently needed both in fundamental research and clinical routine, respectively. The Marie Skłodowska-Curie action LOGIC LAB objects to develop and characterize innovative molecular logic gates that can be applied as advanced diagnostic tools for parallel analyte sensing in live mammalian cells. Thereby, providing a unique method to discover endothelial dysfunction and the onset of diseases much easier and earlier than so far. LOGIC LAB creates a multi-faceted and multi-sectoral research environment for the next generation of scientists in order to establish a novel type of molecular logic sensors that reliably operate in biological media – a crucial requirement for their application i.e. as rapid and easy-to-handle tools for intracellular diagnostics. With excellent cross-disciplinary scientific and complementary training provided in the network, we aim to educate highly-skilled young scientists in the fields of chemistry, physics and biology, who will significantly strengthen the international research community in the domain of molecular logic sensing. Thus, in the long term, LOGIC LAB aims to finally bridge the gap between lab bench and biological or medical practice. It is this gap, that so far prevents a wide-ranging use of existing molecular logic gates e.g. for the diagnosis of lifestyle-associated diseases.

Keywords: molecular logic gates,biological sensing,molecular spectroscopy,microfluidics,metabolomics
Nano-optics on flatland: from quantum nanotechnology to nano-bio-photonics (2DNANOPTICA)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Condensed matter physics
Panel description: Structure, electronic properties, fluids, nanosciences, biological physics
Countries involved: Spain
Call: ERC Starting Grant (ERC-2016-STG, 2016)
Start date: 2017-01-01
End date: 2021-12-31
Duration (months): 60.0
Total project cost (EUR): 1459219.0
EU funding (EUR): 1459219.0
Participants: 1
Project status: CLOSED

Ubiquitous in nature, light-matter interactions are of fundamental importance in science and all optical technologies. Understanding and controlling them has been a long-pursued objective in modern physics. However, so far, related experiments have relied on traditional optical schemes where, owing to the classical diffraction limit, control of optical fields to length scales below the wavelength of light is prevented. Importantly, this limitation impedes to exploit the extraordinary fundamental and scaling potentials of nanoscience and nanotechnology. A solution to concentrate optical fields into sub-diffracting volumes is the excitation of surface polaritons –coupled excitations of photons and mobile/bound charges in metals/polar materials (plasmons/phonons)-. However, their initial promises have been hindered by either strong optical losses or lack of electrical control in metals, and difficulties to fabricate high optical quality nanostructures in polar materials. With the advent of two-dimensional (2D) materials and their extraordinary optical properties, during the last 2-3 years the visualization of both low-loss and electrically tunable (active) plasmons in graphene and high optical quality phonons in monolayer and multilayer h-BN nanostructures have been demonstrated in the mid-infrared spectral range, thus introducing a very encouraging arena for scientifically ground-breaking discoveries in nano-optics. Inspired by these extraordinary prospects, this ERC project aims to make use of our knowledge and unique expertise in 2D nanoplasmonics, and the recent advances in nanophononics, to establish a technological platform that, including coherent sources, waveguides, routers, and efficient detectors, permits an unprecedented active control and manipulation (at room temperature) of light and light-matter interactions on the nanoscale, thus laying experimentally the foundations of a 2D nano-optics field.

Keywords: graphene,2d materials,nano optics,plasmonics,near field optics
Production line of battery packs for telecommunications application (AURORA 4.0)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Spain
Call: Stimulating the innovation potential of SMEs for a low carbon and efficient energy system (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-08-01
End date: 2018-01-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

European battery manufacturing capability currently lags behind the Far East and the U.S.A, with most large players in this sector residing in Asia. A step change improvement in Security of supply, cost effectiveness and technical knowhow of cell level manufacture in Europe is essential for a sustainable European battery market going forward. The aim of Albufera Cells is to introduce a new rechargeable Aluminum-Air (Al-Air) battery technology based on sustainable materials and “lego” cell design enabling easy assembly of battery pack particularly in telecommunication market that is expected to double between 2020 and 2030 with the development of the 5G. Albufera Cells, a SME establish in January 2016 but composed of people who sum up more than 25 years of experience in energy storage industries (mainly Exide Technologies and SAFT) aims to become in the first factory at international level in Al-Air battery cells production for direct sale to telecommunication operators.

Keywords: battery manufacturing,technical knowhow,international factory,battery pack,telecomunication,aluminum air,sustainable materials
Unpacking Skills at the Cradle: A Machine Learning Approach to Construct Infant Skill Measures (SKILLS)

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: Economic Sciences
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2019-10-01
End date: 2021-10-15
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 1
Project status: CLOSED

A growing body of cross-disciplinary research highlights the importance of a child’s environment in the first years of life for skill development and outcomes over the life course. This period is thought to be important for human capital accumulation both because very young children are sensitive to their environment and because deprivation during this period can have long-term consequences. Long-term follow-up studies of early childhood development (ECD) interventions to improve nutrition and create stimulating environments have found large and wide-ranging effects into adulthood: increased college attendance, employment, and earnings and reductions in teen pregnancy and criminal activity. These promising long-term effects of ECD interventions have led to calls from policy-makers and academics to develop large-scale programs that integrate ECD interventions into existing public service infrastructure. Despite this recent call to action, evidence of medium-term impacts of more recent integrated ECD intervention shows that there is substantial fade-out of short-term treatment effects. The puzzling persistence and fade-out patterns of ECD interventions requires more evidence on follow-up studies of existing ECD interventions. Of equal importance is a more detailed analysis of which early skills interventions should target to achieve medium-and long-term improvements in human capital. The proposed research agenda aims to address those concerns in two ways. First, by providing new evidence of medium-term effects on a wide range of child development outcomes of a clustered randomized controlled ECD intervention. Secondly, by developing a new methodology to measure infant skills using innovative tools from the field of machine learning. Both research projects would bring more clarity to the academic literature and policy-makers on which type of infant skills are worth investing in.

Keywords: early childhood education,human capital,skill formation,impact evaluation,measurement