Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Visual Search and Cognitive Control of the Speed-Accuracy Trade-off (VISSATO)

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-2017, 2017)
Start date: 2018-09-01
End date: 2021-08-31
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

The visual environment in our daily life contains many objects, yet only a few of them are relevant for our behavior. In recent decades, our understanding of how we are able to find relevant objects has made substantial progress, in terms of both behaviour and its underlying neural basis. This progress is mainly based on the visual search paradigm where participants are asked to find a target object among non-target objects on a computer screen. Despite this progress, an important aspect of visual search has been neglected, the cognitive control of the ubiquitous speed-accuracy trade-off (SAT, i.e. we are likely to miss targets if we aim for fast responses). We can exert this control depending on many factors (e.g. motivation, situational context, etc.) and its flexibility undoubtedly contributed to our survival as a species. Despite this importance, few studies have investigated cognitive control of SAT in visual search. VISSATO aims to close this gap by employing a set of highly interdisciplinary research lines with experimental and computational modeling techniques. VISSATO will also draw on recent progress on SAT in the related field of perceptual decision making. This field typically examines how we make decisions about perceptual characteristics of single objects (e.g. the motion direction of noisy motion patterns). VISSATO will develop a novel visual search task which allows us to tap into cognitive control of SAT and conduct EEG studies with this task. VISSATO will also develop novel biophysical models of these experiments, testing different hypotheses about the control mechanisms. Using the latest advances in Bayesian model evaluation (including EEG source reconstruction) VISSATO will determine which of these novel models best explains the empirical data, thereby providing strong evidence on how the cognitive control of SAT in the processing of visual scenes is implemented in the brain.

Keywords: selective visual attention,perceptual decision making,speed accuracy trade off,cognitive control,computational modeling,psychophysical experiments,bayesian model fitting,neural basis
Molecular Infection Biology Estonia - Research capacity building (MIBEst)

Framework: Horizon 2020 — Spreading excellence and widening participation
Programme: Widening participation and spreading excellence
Theme: Improved access to Excellence
Action type: Coordination and support actions
Countries involved: Estonia,Switzerland,Sweden
Call: Twinning (H2020-WIDESPREAD-2018-03, 2018)
Start date: 2019-09-01
End date: 2023-02-28
Duration (months): 42.0
Total project cost (EUR): 796550.0
EU funding (EUR): 796550.0
Participants: 3
Project status: CLOSED

Infectious diseases have been the leading cause of death for many centuries. The development of vaccination and antibiotic treatments combined with improved hygiene has decreased the number of deaths, but the mortality and morbidity associated with infections remain considerable, requiring constant societal awareness and scientific research. An increasing concern are the latent and chronic infections that are often refractory to treatments. As the frequency of latent infections increases with age, it is a major concern for aging societies. The great diversity of the infectious agents, and the multidisciplinary nature of the infectious biology research demand a convergence of various competencies: microbiology, cell biology, animal infection models, immunology etc, emphasizing the need for collaboration between research centres. Especially important are joint activities for smaller countries, e.g. Estonia, where establishment of full-scale stand-alone programs is not economically feasible. Despite the strong positions in basic molecular biology, virology and microbiology, Estonia often fails to capitalize on the excellence in basic research by transitioning to the development of therapeutics targeting medically relevant processes. The main objective of the MIBEst project is to strengthen the research capacity on latent and chronic infections of Institute of Technology at University of Tartu by creating long-lasting links with internationally-leading research institutions: Molecular Infection Medicine Sweden at Umeå University, Sweden, and Basel Biozentrum, University of Basel, Switzerland. As an outcome of MIBEst, Estonian scientists will have new knowledge in infection biology with particular focus on advancement in models for latent infections and high throughput screening for promising candidates for antiinfective compounds. Altogether, it enables development of new anti-infection strategies that will have major impact at the national, European and global scale.

Keywords: high throughput screening,molecular microbiology,molecular virology,proteomics,imaging,mouse infection models,cell culture infection models,bioinformatics,structural biology
Design and NanoEngineering of Microporous Membranes for Energy Storage (NanoMMES)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Products and processes engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2019-11-01
End date: 2024-10-31
Duration (months): 60.0
Total project cost (EUR): 1499871.0
EU funding (EUR): 1499871.0
Participants: 1
Project status: SIGNED

With the rapid development of renewable energy such as solar and wind power, energy storage technologies are in urgent need to integrate the low carbon energy into the power grid. Redox flow batteries are promising for grid scale energy storage owing to their scalable storage capacity, decoupled power and energy, long-term cycle performance, and quick response time. Membrane separators play a crucial role in flow batteries by selectively transporting ions while preventing the crossover of redox-active materials. Commercial Nafion membranes are being widely used for flow batteries, however, their high costs limit the large-scale application of this promising technology. Next-generation low-cost membranes with high ionic conductivity and selectivity, and durability are desirable for flow battery energy storage. This proposal NanoMMES aims at designing and nanoengineering low-cost, high-performance, ion-selective microporous membranes for redox flow battery energy storage applications. The objectives of NanoMMES will be achieved through curiosity-driven research into (1) designing the structures of microporous polymers to precisely tune the pore size and ion-conducting functionality required for batteries with different redox chemistries; (2) processing and nanoengineering polymers into highly conductive and selective membranes, and understanding the mechanisms of transport of ions and redox materials; (3) combining the designer membranes with redox flow battery chemistries to achieve efficient and stable energy storage. NanoMMES will undertake interdisciplinary research combining the molecular design of microporous polymers, membrane science and engineering, and redox flow battery chemistry and technology. The ultimate goal of the project is to generate design principles for next-generation ion-selective membranes that will have broad implications on advanced batteries for energy storage, helping the EU develop renewable energy and reduce greenhouse gas emissions.
Improving Educational Outcomes by Transforming the Selection of Future Teachers (SELECTION)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Human Mind and Its Complexity
Panel description: Cognitive science, psychology, linguistics, theoretical philosophy
Countries involved: United Kingdom
Call: ERC Consolidator Grant (ERC-2014-CoG, 2014)
Start date: 2015-09-01
End date: 2021-02-28
Duration (months): 66.0
Total project cost (EUR): 1400214.0
EU funding (EUR): 1400214.0
Participants: 1
Project status: CLOSED

The most effective way of improving education systems is to improve the quality of teachers; a fundamental step to improve the quality of teachers is to select candidates for training who possess the 'soft skills' or non-cognitive traits and attributes that are related to effective teaching. Prof. Robert Klassen’s research will draw on interdisciplinary educational and occupational psychology frameworks to develop an evidence-based teacher training selection approach based on an innovative situational judgment test (SJT) methodology. This is ground-breaking research, as current selection procedures are ad hoc with little or no theory grounding or evidence of predictive validity. The project will dramatically improve the accuracy of the teacher candidate selection process, build understanding of the short- and long-term predictive validity of the non-cognitive attributes of prospective teachers, and provide system-wide educational improvements by increasing the quality of candidates entering teacher training programs. The ERC funding presents an opportunity for a novel high-rewards approach to applied educational psychology research that has the potential to markedly improve teacher quality and educational outcomes.

Keywords: teachers,teacher effectiveness,educational psychology,selection,hiring,retention
Future Freight Loco for Europe (FFL4E)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: European rail initiative
Action type: Research and Innovation actions
Partnership: Shift2Rail (Art-187)
Countries involved: Austria,Germany,Germany,Germany,Spain,Italy,Sweden,Sweden
Call: Freight Propulsion concepts (H2020-S2RJU-CFM-2015-01-1, 2015)
Start date: 2016-09-01
End date: 2019-07-31
Duration (months): 35.0
Total project cost (EUR): 1499857.5
EU funding (EUR): 1499857.5
Participants: 10
Project status: CLOSED

Since 2008, the rail freight market has not yet recovered from the global recession and profit margins in the railway sector have been falling throughout Europe. Moreover, competition was able to increase their capacity due to innovations. Within the last 15 years, inland vessels have increased their transport capacity by 158%, truck transportation by up to 50% while rail freight transportation only by 3% thanks to increasing the length of trains to 740 metres. SHIFT²RAIL IP5 addresses this issue by fostering a vision for future rail freight operation offering increased quality and efficiency while simultaneously improving the overall cost structure. The target is to shift the road freight volumes for distances beyond 300 km to other modes in the range of 30% and 50% by the years 2030 and 2050 respectively. In this context, the FFL4E project (Future Freight Locomotive for Europe) aims at developing key technologies for future energy efficient freight locomotives, allowing highest operational flexibility and providing attractive and competitive rail freight services to the final customer. Focus is set on: • Extreme flexibility for operation in non-electrified and in electrified lines, allowing private and public operators to offer broaden rail freight services according to demand without the need of changing the locomotive. • Remote control for distributed power, thus, allowing the increase of the train length up to 1500 m and consequently improving the cost efficiency of rail transport. • Recuperation of braking energy as much as possible, store it onboard and reuse it whenever required, for traction purposes, for peak shaving or to supply auxiliaries and others. • Last mile propulsion capabilities, sourcing the energy from a powerful on-board Li-Ion battery • Reduction of wear and noise of freight operations by means of developing track-friendly, low-noise running gear for the future freight locomotive.

Keywords: last mile,li ion batteries,energy storage,hybrid propulsion,running gear,low wear,low noise,remote control for distributed power,long trains,radial steering,energy efficiency,peak shaving
Autonomous Vehicles to Evolve to a New Urban Experience (AVENUE)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: Innovation actions
Countries involved: Germany,Austria,Germany,Germany,Switzerland,Switzerland,Norway,Switzerland,Switzerland,Greece,Switzerland,France,France,France,Luxembourg,Denmark
Call: Full-scale demonstration of urban road transport automation (H2020-ART-2017-Two-Stages, 2017)
Start date: 2018-05-01
End date: 2022-10-31
Duration (months): 54.0
Total project cost (EUR): 20903392.66
EU funding (EUR): 15599780.0
Participants: 23
Project status: SIGNED

AVENUE aims to design and carry out full scale demonstrations of urban transport automation by deploying, for the first time worldwide, fleets of autonomous mini-buses in low to medium demand areas of 4 European demonstrator cities: Geneva, Lyon, Copenhagen and Luxembourg, and 3 replicator cities. AVENUE revisits the offered public transportation services, starting from the original problem, which is to allow passengers to move from one place to another. It takes into account their special needs and time constrains, instead of trying to accommodate autonomous vehicles to the existing solutions of pre-scheduled bus itineraries. In this context, AVENUE introduces disruptive public transportation paradigms led by SMEs on the basis of door2door services and the nascent concept of the ‘Mobility Cloud’ aiming in setting up a new model of public transportation. This model enables safe, efficient, on-demand and emission free personalised public transportation, available anytime and anywhere, blending conventional public transport with novel service models such these of the sharing economy. The project partners will apply cutting edge technologies and I2V, V2I & V2V communications that will allow a twofold increase of the average vehicle speed and a tenfold increase in the range served by autonomous vehicles. A set of corresponding in- and out-of-vehicle services that substantially enhance road safety, the overall quality of the service and the value added to the passenger will be introduced, targeting also elderly people, people with disabilities and vulnerable users. AVENUE draws and builds upon the accumulated experience from its consortium of 16 partners from 7 European countries, and the operation of Navya’s 65 mini-buses in 22 cities from 13 countries in 4 continents that already demonstrate reliable and safe operation at pilot sites by transporting over 180,000 passengers. The project activities are organised in 10 workpackages that are implemented within 4 years.

Keywords: autonomous v hicles,disruptive mobility services
Living with Others, Living with Diabetes: Relational Care among Diabetes Patients in Delhi, India (LIDIA)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-09-03
End date: 2021-08-30
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

The project examines relational care among diabetes patients from two social classes in Delhi: urban poor and the middle class. It will contribute to the existing ethnographic studies on diabetes and care by, first, providing an in-depth account of diabetes care in India, an underexplored case-country with a high incidence of the illness. Secondly, by providing a close ethnographic reading familial care, the study will break from earlier research on diabetes that largely focuses on self-care propagated by biomedical knowledge and institutions. Thirdly, the study will make theoretical contributions by developing a conceptual framework on relational care. It will do so by drawing on and bridging anthropological approaches that render care and and familial relatedness as forms of ongoing and habituated practices of the everyday, situated socioeconomically. The overall action will further researcher’s academic career, and create a platform of knowledge exchange between the researcher and the hosting Institution, Edinburgh Centre for Medical Anthropology (EdCMA). Through the implementation of research project, the action will also enhance researcher’s academic skills and facilitate her academic career. The project will enable researcher to enhance academic skills through a close work with the principal supervisor Ian Harper and through an active participation at the EdCMA and relevant research environment. The researcher’s project will create added value to the department’s organisation, research environment and networking activities. By focusing on chronic non-communicable illness, it will supplement the already strong EdCMA’s focus on infectious disease and mental health in the Global South. The work will feed directly into I. Harper’s on-going research into the ethics of global health; and the entanglement between health programmes, institutions and everyday life; and the relationships between chronic diseases and infectious disease.

Keywords: india,diabetes,relatedness,care,everyday life,ethnography
Predicting Outcome of Rate or Rhythm Control in Patients with Atrial Fibrillation and Heart Failure (PREDICT-HF)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Prevention, Diagnosis and Treatment of Human Diseases
Panel description: Medical technologies and tools for prevention, diagnosis and treatment of human diseases, therapeutic approaches and interventions, pharmacology, preventative medicine, epidemiology and public health, digital medicine
Countries involved: United Kingdom
Call: ERC Consolidator Grant (ERC-2019-COG, 2019)
Start date: 2020-09-01
End date: 2025-08-31
Duration (months): 60.0
Total project cost (EUR): 1998927.0
EU funding (EUR): 1998927.0
Participants: 1
Project status: SIGNED

Heart failure (HF) and atrial fibrillation (AF) are common co-morbidities (AF-HF). AF-HF is prevalent in Europe with high rates of hospitalisation and death. AF-HF patients have two treatment options: rate control, where AF is not treated but drugs are used to slow the heart rate, or rhythm control, where AF is treated to restore sinus rhythm. Rate control is the first-line treatment, yet specific patient groups do much better under rhythm control. Identifying patients that will do best under rhythm control remains a significant clinical challenge. Potential responders to rhythm control can be identified by their disease history, however, this is often unknown, or their response to treatment, which can only be observed once the therapy has been delivered. We propose to address these challenges by developing patient specific biophysical cardiac models to infer patient history and predict patient response to treatment to inform optimal therapy selection for individual patients. A model for simulating AF-HF in human hearts, representing all four cardiac chambers, will be created. Bayesian uncertainty quantification techniques will be used to combine physical laws, physiology, population data and measurements from individual patients into cardiac models that account for data uncertainty in model parameters and simulation predictions. Patient specific cardiac models will be used to answer three critical clinical questions in prospective studies. Models will be used to predict: if AF led to HF, or HF led to AF in AF-HF patients where the index disease is unknown, response to rhythm control therapy in AF-HF patients and in which AF-HF patient’s rate or rhythm control is best. This proposal outlines an ambitious high risk/return program to address key technical challenges in bringing predictive patient specific models into clinical studies and will apply these innovative techniques to address important clinical questions on the treatment of patients suffering AF-HF.

Keywords: cardiac physiome,virtual physiological human
Automated Preparation of Ultra-Precise Chemical Solutions. (Cal-Mate)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Ireland
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-05-01
End date: 2019-10-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

There is a need in the lifesciences and industry to create very precise dilution concentrations of chemicals. In general, such dilutions are prepared manually by skilled technicians and scientists and this process of preparing dilution concentrations can consume many hours per week. Furthermore, as with many manual process requiring a high level of skill and concentration, the creation of dilution concentrations is prone to human error and it can be difficult to reliably determine the degree of such errors. Laboratory instrumentation does exist, which may assist in the creation of such dilutions, however the level of precision and accuracy, which is achievable with existing commercial solutions, is somewhat limited. This limitation is primarily due to the fundamental constraints of the underlying methodology used, which is generally positive displacement. Current automated solutions generally employ pipetting robots, which have a precision, at best, in the region of 500nl. Many applications require a level of precision, accuracy and repeatability, which is well beyond the capabilities of existing pipette based methodologies. Often multiple dilutions are used to achieve the required dilution concentration, which can waste the original stock chemicals, in addition to valuable time. PolyPico Technologies unique microdrop dispensing technology can dispense reagents with ultrahigh levels of precision and accuracy in the picolitlre volume range. To serve this unmet need PolyPico will offer a fully integrated automated system to prepare dilution concentrations for a broad range of applications. The instrument will incorporate PolyPico’s patented picolitre micro-drop dispensing technology.

Keywords: mass spectometry,calibration,picolitre dispensing,liquid dispensing technology