Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Saving millions of lives by enabling an effective treatment for Heart Failure patients; V-LAP, a revolutionary, miniaturized implant and its dedicated wearable device. (V-LAP)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Israel
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-05-01
End date: 2017-09-30
Duration (months): 5.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Heart failure (HF) is a chronic condition affecting 1 in 5 people aged over 65 worldwide: heart is unable to pump enough blood flow to meet the body needs. The resulting excess of fluids in body and organs causes dyspnea, edema, leg swelling and tiredness, decreasing patients’ life quality. The sudden worsening of symptoms is called Acute Decompensate Heart Failure: a life-threatening condition with 30% mortality within 12 weeks. HF costs are high: 28 B€/year to EU NHS, 2% of total healthcare expenditure, the major part due to hospitalization. There is today a global call to increase awareness in HF, whose management is still highly ineffective. The transition from HF to the acute condition takes weeks but its earliest indicator, an increase in left ventricular filling pressure (LV), can only be measured invasively, in a hospital. Vectorious’ disruptive device is a miniaturized, battery-free, implantable hemodynamic monitor capable of detecting the rise in LV during patient’s daily life. The implantable, completely covered by Vectorious’ patents portfolio, is deployed trough a minimally invasive, catheter-based procedure. A belt-like external device is worn by the patient over the clothes 3 min/day: via inductive AC coupling, the implantable is powered so pressure data can be collected and sent back to the external unit which synchronize with the patient’s mobile device and with a dedicated website for the healthcare provider. A green/yellow/ red color code widely known among HF patients allows them to promptly adjust their medications, according with their clinicians’ prescription. V-LAP will be able to predict at least 98% ADHF events, HF management will become as simple as manage glucose levels in diabetes. During Phase 1 project the Company will assess scale-up industrialization plan, product development and clinical trials to be deployed in Europe to show the system efficacy on patient outcome and public healthcare costs.

Keywords: heart failure,hemodynamic monitor,implantable device,personalised medicine,wellbeing,silver age,medical device,atrial pressure
Empowered control of drugs’ dosage in chronic diseases (INSULCLOCK)

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: Spain
Call: Accelerating market introduction of ICT solutions for Health, Well-Being and Ageing Well (H2020-SMEINST-2-2016-2017, 2016)
Start date: 2016-11-01
End date: 2018-07-31
Duration (months): 21.0
Total project cost (EUR): 1482087.5
EU funding (EUR): 1037461.25
Participants: 1
Project status: CLOSED

INSULCLOCK addresses the opportunity of providing a new product Within the growing market for diabetes care, a very serious and painful disease with an expected global patient pool of 380 million by 2025. More specifically, INSULCLOCK approaches the insulin pens market which totaled above 8 billion € in 2013, with a 9% CAGR for the next years. More than 25% of diabetics depend on insulin injections daily, and it is estimated that 2/3 of insulin volume is injected via injection pens. If treatment fails, there is high risk of complications related to vascular and nerve affection and even death. The goal of our project is to launch market uptake of INCULCLOCK, a solution to really help diabetics and their caregivers in self-managing their disease. Thanks to the unique integration of smart electronic devices and wearable technologies, we create new demand both from patients already using insulin pens and those not doing so because of reliability issues. Also, around their caregivers, not involved today in business, creating an uncontested market space. In the current market there are smart insulin pen devices, although several reasons make INSULCLOCK unique: 1. It automatically records all critical information related to insulin in-taking for diabetes treatment, without interfering activities of daily living. 2. It stores data taking full advantage of possibilities offered by the Cloud and mobile technologies, assuring security, assistance and privacy. 3. It is universal and reusable. During Phase 1, further business opportunities have been detected, with pharmaceutical and health insurance companies, and relevant leads have been open. Additionally, market barriers and dynamics are fully understood now, allowing us for the definition of the work plan proposed in this Phase 2 application, which will last 15 months with a total budget of 1.48M€. Finally, we created the team, alliances and resources for international high growth. Now is our moment.

Keywords: medical device,wearable,ehealth
Embedded learning and optimization for the next generation of smart industrial control systems (ELO-X)

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: Information Science and Engineering
Countries involved: Italy,Germany,Italy,Germany,Switzerland,Switzerland,Belgium,Romania,Belgium,Switzerland
Call: Innovative Training Networks (H2020-MSCA-ITN-2020, 2020)
Start date: 2021-01-01
End date: 2024-12-31
Duration (months): 48.0
Total project cost (EUR): 3884353.92
EU funding (EUR): 3884353.92
Participants: 11
Project status: SIGNED

Thanks to the increasing capabilities of digital technologies, the next generation of industrial control systems are expected to learn from streams of data and to take optimal decisions in real-time, leading to increased performance, safety, energy efficiency, and ultimately value creation. Numerical optimization is at the very core of both learning and decision-making, and machine learning algorithms and artificial intelligence raise huge worldwide research interest, often using cloud computing and large data centers for their optimization computations. However, in order to bring learning- and optimization-based automated decision-making into smart industrial control systems (SICS), two important bottlenecks have to be overcome: (1) computational resources on industrial control systems are locally embedded and limited, and (2) industrial control applications require reliable algorithms, with interpretable and verifiable behavior. Both requirements partially stem from safety aspects, which are crucial in applications where a single computation error can cause high economic and environmental cost or even damage to people. Pushing the performance boundary of SICS to leverage advanced digital technologies will therefore involve both fundamental new research questions and technological solutions, calling for a new set of advanced methods for embedded learning- and optimization-based control algorithms. Through its 15 PhD students hosted and seconded at 11 top European research centers (6 academic, 5 industrial) and 4 partner organizations in the US, Japan and China, ELO-X will address the timely and pressing need for highly qualified and competent researchers who will develop embedded learning- and optimization-based control methodologies for SICS, thus enabling new and possibly game-changing digital technologies for important EU industries.

Keywords: model learning,model predictive control,embedded optimization
Parental Engagement and Relationships (PEAR) in Early Childhood (EC) (PEAR_EC)

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: Social Sciences and Humanities
Countries involved: Ireland
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-05-04
End date: 2022-05-03
Duration (months): 24.0
Total project cost (EUR): 196590.72
EU funding (EUR): 196590.72
Participants: 1
Project status: CLOSED

In Ireland, 29% of children under six are at risk of poverty, compared to 26% in Europe. Poverty negatively affects children's early development and parental engagement in children’s education, with long-term effects. Ending poverty and ensuring quality education for all from early childhood are interrelated UN 2030 Sustainable Development Goals. Quality early childhood education and care (ECEC) can drive development and combat poverty through its multiplier effects, while providing parental support (PS) to engage with children’s education can further extend these effects. Commitments to ECEC and PS are reflected in emerging EU and Irish policy. However, coherent guidance on ECEC PS modalities is lacking and the effectiveness of practice rarely evaluated. Also, despite evidence of beneficial outcomes, the interaction between PS and poverty is neglected, as well as engagement with fathers/coparents. CDI is testing a model to improve children’s outcomes by integrating PS within ECEC services in Tallaght, a disadvantagd area in Ireland. The researcher, Dr. Catarina Leitão, will carry out a fellowship to study this model under the intersectoral supervision of Marian Quinn, CDI’s CEO and Professor Noirin Hayes of Trinity College Dublin. This fellowship will make a timely contribution to ECEC research and policy-practice gaps, particularly in the context of Ireland's recent (2019) commitment to PS through ECEC services. It will advance understanding of the characteristics and conditions related to positive child, parent and service outcomes by examining service quality, family background and gender effects. It will combine a quasi-experimental matching design and standardised tools that allow internal and external comparability, with innovative qualitative methods (e.g. Photovoice) that empower child and family voice. Lastly, it will optimise intersectoral collaboration to widely communicate and disseminate findings, enhancing potential for social impact.

Keywords: early learning and care services,parental support,engaging fathers,quasi experimental evaluation,children and families voice
Prefrontal Cortex Circuit Dynamics underlying Working Memory and its Serotonin Modulation (PIANISM)

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,United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-08-01
End date: 2022-12-08
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 2
Project status: CLOSED

The prefrontal cortex (PFC) is essential for higher cognitive tasks such as learning, decision making and, in particular, working memory (WM). To fulfill these tasks, PFC neurons express several serotonin (5HT) receptor subtypes that are modulated by a high density of serotonergic axons projected from the raphe nuclei. Alterations of the neuronal mechanisms within PFC lead to an impaired top-down regulation, causing cognitive dysfunctions in mental disorders such as schizophrenia. A key cellular mechanism related to WM formation and maintenance in the PFC is sustained action potential firing of neurons that outlasts the initial excitatory drive. Persistent firing is likely enabled by synaptic networks and intracellular ionic mechanisms, including voltage sensitive sodium and calcium inward currents or G-Protein-coupled receptor mediated TRPC/ CAN currents. Moreover, experimental data supports a link between dysfunctional serotonergic modulation in the PFC and WM deficits, but yet, the underlying mechanisms are poorly understood. Here, I plan to gain a mechanistic understanding of the serotonergic modulation of WM at the cellular level including the link between 5HT receptor activity and prefrontal cellular circuits dependent WM formation and the role of 5HT in WM-related persistent firing. I will perform patch-clamp electrophysiology and optical voltage imaging (genetically encoded voltage indicators) of prefrontal pyramidal and GABAergic cells (PV-, SST-, VIP-subtypes) in acute slices from naïve and WM deficient mice (chronic ketamine model of schizophrenia), and examine how the activity of these cell types are modulated by optogenetically and pharmacologically controlled 5HT signalling. These experiments aim to understand the serotonergic transmission and intrinsic properties within the PFC involved in WM formation, maintenance and deficiency. Better understanding of these mechanisms will help to develop new and specific therapeutic targets for WM deficiencies.
Digitalization of prosthetic socket personalization workflows trough artificial intelligence (DigiSocket)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Norway
Call: European SME innovation Associate - pilot (H2020-INNOSUP-2020-02, 2020)
Start date: 2020-10-01
End date: 2022-05-31
Duration (months): 20.0
Total project cost (EUR): 168712.5
EU funding (EUR): 118098.75
Participants: 1
Project status: CLOSED

Hy5 is a young and vibrant company, working towards the development of cost effective, accessible and high-quality prosthetic solutions. We have CE-marked, FDA-registered and Canada approved our first product, a disruptive myoelectrical prosthetic hand using a unique hydraulic-based actuation principle developed in-house – capitalizing our expertise in mechanics as a central technological enabler to develop a unique prosthetic hand offering an optimal balance between gripping functionality and overall cost. However, Hy5 aims to go one step further being a product-based company and we envision improve the existing value chain by empowering a digital revolution –providing more effective alternatives to several activities in the prosthetic workflows that use decade-old technologies. However, we do not possess in-house expertise in machine learning and advanced ICT concepts such as computer vision, that are essential for this project and therefore looking to recruit an Innovation Associate with the required skill set, in order to complement. The SME Innovation Associate programme project is thus necessary for Hy5 to initiate R&D activities with a view to expand its portfolio and ultimately positioning Hy5 as a key player up and downstream to the acquisition of a prosthetic hand. Acquiring these skills is thus fundamental for Hy5 to keep competitive advantage over the coming years – but more importantly, will allow for Hy5 to outgrow into a forefront innovation player at global scale.

Keywords: hand prosthetic,socket design,automation,artificial intelligence,3d computer vision,modelling
Global Lagrangian Cloud Dynamics (GLAD)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Earth system science
Panel description: Physical geography, geology, geophysics, atmospheric sciences, oceanography, climatology, cryology, ecology, global environmental change, biogeochemical cycles, natural resources management
Countries involved: Switzerland
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-01-01
End date: 2024-12-31
Duration (months): 60.0
Total project cost (EUR): 1493343.0
EU funding (EUR): 1493343.0
Participants: 1
Project status: SIGNED

This project will address fundamental gaps in our understanding of how clouds form, how they interact with the atmospheric flow and how they need to be simulated in weather and climate models. Our inability to improve the representation of clouds and their interactions with the atmospheric flow is the leading cause of the high level of uncertainty associated with projections of future changes in storm tracks, precipitation bands and weather extremes. The representation of clouds in models is poor, largely because clouds are unresolved. Given the potentially significant impacts of projected global warming and the significant benefits of improved weather predictions, it is imperative to improve the representation of cloud-circulation interactions in models. However, how do we acquire the necessary process understanding to close existing knowledge gaps? I propose a fundamentally new perspective on clouds and their control of the large-scale flow leading ultimately to a unique cloud classification system. Instead of studying clouds based on the traditional Eulerian perspective, I suggest analysing cloud-circulation couplings based on the history of air parcels (Lagrangian perspective). A systematic Lagrangian-based investigation of cloud-circulation couplings in ultra-high-resolution simulations is a true novelty and has never been attempted. Based on convection-permitting simulations over a climatological period, which exploit recent advances in supercomputing architectures, the cloud parcels are classified according to their circulation impact and feed into a machine learning algorithm that is trained using the physical processes acting along their pathways. This approach has the potential to drastically improve our mechanistic understanding of how to represent clouds in models and to identify the leading cloud-related processes that control regional to large-scale flow variability, which is one of the Grand Challenges defined by the World Climate Research Programme.

Keywords: diabatic processes,storm tracks,jet stream,clouds,lagrangian perspective,potential vorticity
The Problem of European Misperceptions in Politics, Health, and Science: Causes, Consequences, and the Search for Solutions (DEBUNKER)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Institutions, Governance and Legal Systems
Panel description: Political science, international relations, law
Countries involved: United Kingdom
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2016-09-01
End date: 2023-02-28
Duration (months): 78.0
Total project cost (EUR): 1931730.0
EU funding (EUR): 1931730.0
Participants: 1
Project status: SIGNED

While some people may simply lack relevant factual knowledge, others may actively hold incorrect beliefs. These factual beliefs that are not supported by clear evidence and expert opinion are what scholars call misperceptions (Nyhan and Reifler 2010). This project is principally about misperceptions—the “facts” that people believe that simply are not true. What misperceptions do Europeans hold on issues like immigration, vaccines, and climate change? Who holds these misperceptions? What demographic and attitudinal variables are correlated with holding misperceptions? And ultimately, what can be done to help reduce misperceptions? Misperceptions are an important topic for study because they distort public preferences and outcomes. This research program investigating misperceptions is currently at the state of the art in political science. To date, only a handful of published studies by political scientists have examined how corrective information changes underlying factual beliefs. The results of these studies are uniformly troubling—among those vulnerable to holding a given misperception, corrective efforts often make misperceptions worse or decrease the likelihood to engage in desired behaviors. This ambitious project has three primary objectives. First, the project will assess levels of misperceptions in Europe on three specific issues (immigration, vaccines, and climate change) that represent three different substantive domains of knowledge (politics, health, and science). Second, the project will examine a variety of approaches and techniques for combatting misperceptions and generating effective corrections. Third, the project will take what is learned from the first two stages and transmit the findings back to relevant academic and policy-maker audiences in order to aid policy design and communication efforts on important policy issues.

Keywords: knowledge,misperceptions,public opinion
Cervical cancer detection platform based on novel laser processing (CANCER-TECH)

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: Ireland
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2016-01-01
End date: 2017-12-31
Duration (months): 24.0
Total project cost (EUR): 175866.0
EU funding (EUR): 175866.0
Participants: 1
Project status: CLOSED

About 10% of all cancers diagnosed in women worldwide, are cancers of the cervix, the organ that connects the uterus and the vagina. Alone in the European Union over 16,000 deaths are reported annually due to cervical cancer effecting women mainly between the ages of 25 and 50. Within the scope of this fellowship, hosted by Dublin City University (Ireland) in collaboration with Arrows Biomedical GMBH (Germany), a highly sensitive platform to detect Human Papillomavirus (HPV), causative agent of about 99.7% of cervical cancer, will be developed. The proposed diagnostic platform will be based on a laser textured biopolymer as device substrate, functionalized with nanoparticles produced via the Pulsed Laser Ablation in Liquid (PLAL) technique. This on-chip immunoassay will allow rapid detection of the HPV. The novelty of this project lies in the high-quality bio-nanostructures as nano-labels via PLAL designed for ultrasensitive detection of HPV. Two major aspects of this project are: (1) the development of complex nano-labels specifically targeting high risk HPV; and (2) improvement in the performance of the developed assay increasing their sensitivity and specificity, relative to current start of the art. Ultrapure HPV-specific nano-labels will be prepared using pulsed laser ablation in liquid, a green synthesis route independent of any chemical processing. The proposed technique is advantageous due to the enhanced surface activity of laser-generated nanoparticles, which will reduce the amount of sample molecules needed for the successful detection by improving the limit of detection and overall detection time. This project aims at making substantial contribution to the advancement of cancer immunosensing based on a novel on-chip immunoassay design for medical applications. Through this project, the applicant aims to develop intellectual property related to the manufacturing of biomedical devices via laser processed surfaces.

Keywords: laser processing of polymer,pulsed laser ablation in liquids plal,bio functionalised nanoparticles,cancer detection,biomedical device