Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
International impact of TALK©: a simple and practical approach to multi-professional structured feedback and debriefing, to be used after unplanned learning events in clinical environments. (TALK)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Spain,Norway,Morocco,United Kingdom
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2016, 2016)
Start date: 2017-06-01
End date: 2022-02-28
Duration (months): 57.0
Total project cost (EUR): 274500.0
EU funding (EUR): 274500.0
Participants: 7
Project status: CLOSED

TALK© is a communication tool which aims to guide multi-professional clinical teams learning and improving quality of patient care and patient safety together. It is a simple and practical approach to multi-professional structured feedback and debriefing, to be used after unplanned learning events in clinical environments. Debriefing is the process of an individual or team formally reflecting on their performance after a particular task, a shift or a critical event (World Health Organisation 2009). TALK proposes an easy way to guide a constructive conversation between team members whenever new insights might be learnt from clinical experience. This includes cases or sessions in which things went well but also near misses and untoward events. Patient safety is far too often threatened by unidentified system flaws, poor practices, weaknesses in team communication and lack of appropriate action after critical events. The relevance of a culture of safety and communication is emphasized by WHO advocating debriefing in its Human Factors review, 2009. This RISE project will consist of three phases; firstly secondees will contribute to parallel implementation processes in specified units across the 3 participating countries and will undertake research to better understand the benefits of structured debriefing, communication and organisational culture. Secondly, using the data generated from the research study, further training materials will be developed and translated to support the wider deployment of the TALK tool. Thirdly, the TALK tool will be widely disseminated as a structured debriefing tool and implemented across and beyond all participating partners and its impact will be assessed.

Keywords: debriefing,organisational culture,patient safety,staff well being,feedback,democratisation,learning,reflection
Feasibility Assessment of a Foot INflammation Detection Device (FIND)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Treating and managing disease
Action type: SME instrument
Countries involved: Netherlands
Call: Clinical research for the validation of biomarkers and/or diagnostic medical devices (H2020-SMEINST-1-2014, 2014)
Start date: 2014-11-01
End date: 2015-04-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Hemics is a medical device company focusing on monitoring solutions for inflammatory joint diseases. This proposal describes how Hemics (SME) will deliver a feasibility study on the development, validation and commercialization of an imaging device (FootScan) to monitor joint inflammation in the feet of patients with Rheumatoid Arthritis (RA). Current treatment of RA focuses on the reduction of disease activity to remission by use of drug therapy. Treatment of RA is guided by monitoring the disease activity. The latest scientific evidence shows that tight control strategies are recommended in the early stages of RA as the best way of preventing escalation of the disease. The DAS28 score is the most used monitoring method, although it is too subjective, time consuming and painful for the patient. Given the time constraints tight control is hardly possible through the DAS28 method. Other, more objective and sensitive, methods (eg. X-Ray, MRI) are time-consuming and too costly to use as a regular basis for monitoring. This proves the clinical need for an objective, sensitive and time saving method to monitor RA, enabling tight control and treatment of, now often undiagnosed, subclinical inflammation. The niche market of rheumatology consists of 16.000 rheumatologists worldwide. If every three rheumatologists would use a FootScan, the potential market would consist of approximately 5300 units. With a life expectancy of eight years and a pricing range between € 60.000 and € 80.000 this market represents a value of € 46.690.000 per annum. In 2015 Hemics plans to start the product engineering phase. To reach that milestone, Phase 1 feasibility assessment will cover a technical feasibility study as well as a business feasibility study. The objective of the feasibility assessment is to optimize the optical technology for the FootScan and to develop a business and implementation plan for successful commercialization.

Keywords: rheumatoid arthritis,optical detection technology,biomarkers,inflammation of joints
Comprehensive Mechanisms of Bacterial Antibiotic Tolerance in Mycobacterium Tuberculosis (COMBATTB)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Reintegration panel
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2019-04-01
End date: 2021-12-30
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 1
Project status: CLOSED

Mycobacterium tuberculosis (Mtb) is one of about a dozen bacterial species for which some clinical isolates are now resistant to most or all antibiotics (abx) approved for treatment of the infections they cause. Mechanisms of antimicrobial resistance (AMR) in Mtb deserve study for their potential relevance to AMR in other pathogens; because tuberculosis (TB) is now the leading cause of death from infectious disease; and because drug-resistant TB may be the most prevalent of all drug-resistant bacterial infections. Heritable AMR in Mtb emerges with interruption of treatment, and the long duration of TB treatment provides many opportunities for interruption. Prolonged treatment is necessary because of nonheritable resistance, also called phenotypic tolerance or persistence, defined as the transient tolerance of bacteria in an antibiotic-sensitive population to an antibiotic during exposure to an otherwise lethal concentration of that antibiotic. In contrast to “resisters”, whose AMR is genetically encoded, “persisters” are genetically sensitive bacteria whose phenotypic tolerance allows them to survive for prolonged periods during what would otherwise be rapidly curative treatment. In addition, phenotypic tolerance is likely a source of treatment failure and a major contributor to TB reactivation after apparently effective treatment. The specific aims of this application are to identify genetic determinants that foster phenotypic tolerance in Mtb and decipher at a molecular level the mechanisms by which Mtb enters and maintains a persistent state.

Keywords: bacterial persistence,high persistence mutants,infectious disease,tuberculosis,antimicrobial resistance
Infrastructure for the European Network for Earth System modelling - Phase 3 (IS-ENES3)

Framework: Horizon 2020 — Excellent Science
Programme: Research Infrastructures
Theme: Research infrastructures
Destination: Integrating activities and infrastructures
Action type: Research and Innovation actions
Countries involved: Spain,Germany,Germany,Spain,Italy,Serbia,Sweden,Norway,Norway,Greece,France,France,France,Czechia,Netherlands,Netherlands,Netherlands,United Kingdom,United Kingdom,United Kingdom,United Kingdom
Call: Integrating Activities for Advanced Communities (H2020-INFRAIA-2018-1, 2018)
Start date: 2019-01-01
End date: 2023-03-31
Duration (months): 51.0
Total project cost (EUR): 9802612.5
EU funding (EUR): 9802612.5
Participants: 24
Project status: SIGNED

IS-ENES3 will deliver the third phase of the distributed e-infrastructure of the European Network for Earth System Modelling (ENES). IS-ENES3 will be initiated as the European climate modelling community faces the challenges of contributing to the next assessment report of the Intergovernmental Panel on Climate Change through the 6th phase of the Coupled Model Intercomparison Project. IS-ENES3 will address these challenges by developing, documenting and deploying new and advanced models and tools, standards and services to deal with unprecedented data volumes and model complexity. IS-ENES3 will stimulate collaboration, disseminate software and data, and further integrate the European climate science community. IS-ENES3 will support climate research, climate impact science, and the climate services industry. It will bring down barriers of access, and expand the community who can exploit the data and knowledge produced by state-of-the-art climate models. In doing so, it will find innovative ways of working with the Copernicus programme, other parts of the European data infrastructure, and with the high performance computing and data analytics industries. IS-ENES3 will be delivered by partners combining expertise in climate modelling, computational science, data management, climate impacts and climate services, with proven ability to increase the influence of European science internationally. It will deliver the European part of the Earth System Grid Federation and a central point of entry to services providing access to new data, software, models and tools. Joint research will support a new community sea ice model, promote efficient use of high-performance computing, improve the European common model evaluation framework, and develop and enhance services on data. Networking will grow the user base, increase the cohesion of the climate modelling community, promote innovation and prepare for a long term sustainable infrastructure in support of climate modelling.

Keywords: earth system modelling,climate change,model data repository,wcrp international experiments,high performance computing
GuestXR: A Machine Learning Agent for Social Harmony in eXtended Reality (GuestXR)

Framework: Horizon 2020 — Excellent Science
Programme: Future and Emerging Technologies (FET)
Theme: EIC Pathfinder
Destination: Emerging themes and communities
Action type: Research and Innovation actions
Countries involved: Spain,Israel,Austria,Poland,France,France,Netherlands
Call: FET Proactive: emerging paradigms and communities (H2020-FETPROACT-2020-2, 2020)
Start date: 2022-01-01
End date: 2025-12-31
Duration (months): 48.0
Total project cost (EUR): 4499519.76
EU funding (EUR): 4499519.75
Participants: 9
Project status: SIGNED

Immersive online social spaces will soon become ubiquitous. However, there is also a warning that we need to heed from social media. User content is the ‘lifeblood of social media’. However, it often stimulates antisocial interaction and abuse, ultimately posing a danger to vulnerable adults, teenagers, and children. In the VR space this is backed up by the experience of current virtual shared spaces. While they have many positive aspects, they have also become a space full of abuse. Our vision is to develop GuestXR, a socially interactive multisensory platform system that uses eXtended Reality (virtual and augmented reality) as the medium to bring people together for immersive, synchronous face-to-face interaction with positive social outcomes. The critical innovation is the intervention of artificial agents that learn over time to help the virtual social gathering realise its aims. This is an agent that we refer to as “The Guest” that exploits Machine Learning to learn how to facilitate the meeting towards specific outcomes. Underpinning this is neuroscience and social psychology research on group behaviour, which will deliver rules to Agent Based Models (ABM). The combination of AI with immersive systems (including haptics and immersive audio), virtual and augmented reality will be a hugely challenging research task, given the vagaries of social meetings and individual behaviour. Several proof of concept applications will be developed during the project, including a conflict resolution application in collaboration with the UN. A strong User Group made up of a diverse range of stakeholders from industry, academia, government and broader society will provide continuous feedback. An Open Call will be held to bring in artistic support and additional use cases from wider society. Significant work is dedicated to ethics “by design”, to identify problems and look eventually towards an appropriate regulatory framework for such socially interactive systems.

Keywords: extended reality,augmented reality,virtual reality,social psychology,neuroscience,haptics,immersive audio,social interaction,affective computing,agent based models,reinforcement learning
Time Sensitive Networking (TSN) technologies for Next Generation Ethernet (TSNet)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Denmark
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-12-01
End date: 2018-05-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Comcores aims to pursue a major opportunity through maturation and demonstration of a disruptive set of Silicon Intellectual Property (SIP) cores which can offer Time Sensitive Networking (TSN) on Ethernet networks. TSN is a set of standards developed by the TSN task group of the IEEE 802.1 working group to solve the emerging need for real time data transmission in one standardized solution rather than proprietary solutions. TSN over Ethernet is being requested in multiple fields: automotive, automation 5G communications. The current solutions in the market are expensive and not capable to efficiently support TSN and high bandwidth simultaneously. The unique algorithms and IP architectures developed by Comcores allow real time transmission of high volumes of data in high speed networks. Comcores aims to supply SIP cores integrating IEEE 802-1 standards, to be easily applied in integrated circuits and other sub-systems which in turn will be used by networking equipment’s manufacturers, automotive, avionic or in other industrial applications. The end-users will be 5G communications operators, transport, airline, energy companies among others. The primary benefits for customers and end-users are stemming from significant savings in networks infrastructures and improved efficiency in time critical tasks where massive amounts of data need to be handled. The global urgency in cost-effective technologies to provide time synchronization, high priority, low latency and high bandwidth represents a huge business opportunity and with TSNet project Comcores aims to establish itself as a strong player in the global semiconductor IP market. Comcores wishes, in Phase 1, to assess the technical and financial feasibility of the concept as well as the real market potential of the technology. Subsequently in Phase 2, Comcores aims to demonstrate the technology in real key applications and mature the technology according to the feedback of the customers/end-users.

Keywords: networks,ip cores,ethernet,time sensitive networking,semiconductors
Emotional Machines: The Technological Transformation of Intimacy in Japan (EMTECH)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Cultures and cultural production
Panel description: Literary studies, cultural studies, study of the arts, philosophy
Countries involved: Germany
Call: ERC Starting Grant (ERC-2016-STG, 2016)
Start date: 2017-08-01
End date: 2024-07-31
Duration (months): 84.0
Total project cost (EUR): 1489919.0
EU funding (EUR): 1489919.0
Participants: 1
Project status: SIGNED

EMTECH analyzes the relationship between aesthetic works on human-robot interaction in Japan and cutting-edge advances in robotics and artificial intelligence. Its central hypothesis argues that a tradition of literary, artistic, and other media forms of cultural production on human-robot relationships particular to Japan is currently being built into emotionally-intelligent companion robots with the ability to understand, record, and elicit emotions in its users, consequently expanding the capacities for humans to create affective bonds with machines and transforming structures of intimacy that sustain traditional social institutions. In its most ambitious claim, EMTECH argues that this cultural tradition has played a primary role in inspiring the recently-emerging mass production of domestic robots with technology that can register and record facial expressions, heart rate, skin conductance, and other signs of affect not consciously recognized by humans, thus generating new kinds of scientific data on human affect that fundamentally challenges previous understandings of emotion. Through the textual analysis of literary work on robot imaginaries and ethnographic fieldwork on human-robot interaction in homes, palliative care centers, and engineering laboratories, EMTECH’s purpose is to collect qualitative data on new technologies of emotion management in order to advance literary and cultural theory’s contributions to the affective sciences, as well as to inform public discussions on issues of data collection, privacy, and other ethical concerns raised by the adoption of emotionally-intelligent robots in the home. Leveraging research in the humanities to critique emotional models employed by robotics engineers and designers, and implementing novel research methods such as the use of robots in both literary critique and ethnographic fieldwork, EMTECH promises to yield groundbreaking data of both theoretical and methodological application across the human sciences.
A NOVEL AND INTEGRATED APPROACH TO INCREASE MULTIPLE AND COMBINED STRESS TOLERANCE IN PLANTS USING TOMATO AS A MODEL (TomRes)

Framework: Horizon 2020 — Societal Challenges
Programme: Food security, sustainable agriculture and forestry, marine and maritime and inland water research and the bioeconomy
Theme: Sustainable agriculture and forestry
Action type: Research and Innovation actions
Countries involved: Italy,Germany,Spain,Italy,Italy,Israel,Germany,Spain,Italy,Italy,Italy,Italy,Belgium,Greece,Greece,Romania,Slovenia,France,France,United Kingdom,United Kingdom,United Kingdom
Call: Solutions to multiple and combined stresses in crop production (H2020-SFS-2016-2, 2016)
Start date: 2017-06-01
End date: 2021-05-31
Duration (months): 48.0
Total project cost (EUR): 5996175.0
EU funding (EUR): 5996175.0
Participants: 26
Project status: CLOSED

Tomato is a main EU agricultural commodity, cultivated all over Europe in open and protected field and in glasshouses, representing a biological and agronomical model crop. Combined water and nutrient stress is a major problem for tomato farmers and solutions are needed to safeguard yields, while preserving the environment. TOMRES will select, among over 10,000 available accessions, rootstocks and scions tolerating combined stress, while retaining fruit quality and yield, taking advantage of innovative screening approaches. Novel traits, in particular belowground, to be exploited in breeding, will be identified. The role of selected hormones (strigolactones and brassinosteroids) will be studied to identify further resilience traits. TOMRES will test and optimize sustainable crop management strategies such as legume intercropping, precision fertilization and irrigation techniques, manipulation of symbiotic microorganisms, and the use of rootstocks more suited to water and nutrient uptake from the soil. Novel genotypes X management strategies will be developed with the goal of reducing N and P application by at least 20%, water input by 40%, while granting environmental sustainability and economic viability of the solutions proposed. Testing will be integrated with analysis of environmental (greenhouse emissions, water quality), and of socio-economic impact. Agronomical, environmental, and economical data will be processed to construction of models and of a Decision Support System. Demonstration and dissemination activities will follow the whole course of the project, and will transfer the results to different environments and other cropping systems, thus ensuring the widest impact of the gained knowledge on the EU economy. Trans-disciplinary knowledge transfer among farmers, breeders, industries, associations and scientists will be granted by a solid multi-actor approach since the planning stage.

Keywords: genotype screening,plant hormones,plant phenotyping,biostimulants,open ended co innovation
Ultra-Fast Silicon Detectors: Enabling Discoveries (UFSD)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Fundamental constituents of matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: Italy,Italy
Call: ERC Advanced Grant (ERC-2014-ADG, 2014)
Start date: 2015-09-01
End date: 2021-08-31
Duration (months): 72.0
Total project cost (EUR): 1793312.5
EU funding (EUR): 1743312.5
Participants: 2
Project status: CLOSED

The goal of our project is to empower a broad range of research fields with a completely new particle detector, able to concurrently deliver time resolutions of the order of ~10 picoseconds and position resolutions of ~30 microns. In so doing, we will remove the constrains that many applications such as particle tracking, medical PET, mass spectroscopy, and beam monitoring have due to the lack of precise information on all 4 dimensions. Our analysis of state-of-the-art particle detectors has shown a dichotomy: specialized sensors measure very accurately either time or position, but not both: the ambitious goal of UFSD is to create a new family of detectors, based on controlled charge multiplication in silicon, which will remove this limitation. We will have to tackle significant challenges along this research path, but our simulations and prototypes indicate that this approach has the potentiality to radically transform present detectors and to enable many applications to reach their peak performances. Our ultimate goal -- a highly segmented detector with a space resolution of ~30 microns and a time resolution of ~10 picoseconds -- can be achieved only by developing full custom Very Large Scale Integrated chips that, matching the size of the read-out to the area of each pixel sensor, will deliver unprecedented timing resolution at the pixel level. The PI, N. Cartiglia, is well known in the field of particle physics and detector development. He is currently in charge of several projects involving both new directions in physics, among which the LPCC forward physics group and the CT-PPS project at CERN, as well as new developments in instrumentation. He will lead the project leveraging on his past experience in detector development and group/grant management, his knowledge of the silicon research foundries and laboratories, and the expertise available in his home institution (INFN, Torino, Italy).

Keywords: ultra fast particle tracking,4dimensional tracking,silicon sensor,quartic gauge coupling