Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Single molecule imaging of herpes simplex virus type 1 DNA replication (HSV1_Single_Molecule)

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-2020, 2020)
Start date: 2022-09-01
End date: 2024-08-31
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 1
Project status: SIGNED

Herpes simplex virus type 1 (HSV-1) is a widespread and well-known pathogen. However, we still lack a complete understanding of the mechanism of HSV-1 genome replication. We propose to revisit long-standing questions of the HSV-1 genome replication mechanism using cutting-edge single molecule imaging techniques. This approach enables the detection of transient structures and heterogeneous behavior, leading to further crucial insights into this fundamental process. The current model for HSV-1 genome replication comprises an origin-dependent followed by an origin-independent stage. Whereas we do have evidence and a good understanding of the origin-dependent phase, we completely lack evidence for the proposed structures of the origin-independent phase. Thus, in the proposed project we want to study aspects of the origin-dependent replication phase. Specifically, we want to reveal the role of the HSV-1 origin binding protein UL9 during replication as this protein was proposed to act as a switch from the first to the second stage. It has been shown that UL9 is an essential protein during the origin-dependent stage but dispensable and even inhibitory during the second, origin-independent stage. We here propose to use single-molecule imaging techniques to reveal the inhibitory effect of UL9 on HSV-1 mediated replication and to further characterize the specific conditions of UL9 binding to the origins of replication.

Keywords: herpes simplex virus type 1,hsv 1,single molecule imaging,dna replication
All-steel external frame for the non-disruptive seismic retrofit of existing reinforced concrete buildings (AllSteel-SRetrofit)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Greece
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-04-10
End date: 2024-10-31
Duration (months): 24.0
Total project cost (EUR): 165085.44
EU funding (EUR): 165085.44
Participants: 1
Project status: SIGNED

The state-of-the-art review in seismic retrofit of existing reinforced-concrete (RC) buildings indicates that a technology that is non-disruptive and easy to implement, achieves simultaneous control of drifts and accelerations, and overcomes major issues related to low concrete strength, poor reinforcement details, and vulnerable RC columns, has never been described in the literature or in seismic design codes (e.g. Eurocode 8). The ambitious main objective against the background of the state-of-the-art of the project is to develop such a retrofit technology. In particular, the project will develop a non-disruptive retrofit scheme using an external, modular, steel frame as a facade close and in parallel connected to frames of the existing RC building. The external steel frame will have chevron braces to support energy dissipation devices, and, connectors to achieve horizontal coupling with the existing RC building. Strategically, the energy dissipation devices will be visco-plastic dampers, i.e. novel devices that will offer visco-elastic damping output under low-to-moderate earthquake intensities and friction damping output with a predefined limit on their peak force under high seismic intensities. The project will develop sophisticated yet practical structural details and a simplified seismic design procedure for the external steel frame. All these will be achieved through a carefully planned integrated experimental and numerical research program involving constitutive modelling, nonlinear finite element analysis, and shaking table tests. The proposed retrofit scheme constitutes a solid contribution to earthquake engineering that is expected to raise major international scientific and industrial interest.

Keywords: seismic,concrete,retrofit,steel frame
Experimental Analysis of Framing Effects via Observation of Decision-Making Processes to Improve the Real-World Applicability of Decision Research in Economics (FRAMING_EFFECTS)

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: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-10-01
End date: 2017-09-30
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

Fellowship objective is to explain influences of descriptive context on individual decisions, i.e. framing effects, by observing processes of making-sense (of representation/interpretation/rationalization). Experimental Economics ignores effects of framing on this “black-box” of decision-making processes, and instead theorizes framing by observing only choices & using fixed preference structures. This not only limits our understanding of these effects but weakens real-world applicability of experimental results & leads to inefficient use of public funds; e.g., it is well-established that descriptions used in policy tools, e.g. contingent valuation (CV) & nudging, significantly affect results, yet it is unknown why or how. To unpack this box, fellowship at U. of Nottingham’s Centre for Decision Research & Experimental Economics (CeDEx) will combine Dr.Isler’s background in methodology research with training/research on framing to develop 2 new experiment designs. Secondment at Leeds U. Centre for Decision Research will enable training on Process Tracing Methods (PTMs) & Mouselab software to provide capacity for process observations. Using PTMs/Mouselab in experiments at CeDEx, 1st design will isolate framing effects that choice/preference-based conventional theories cannot explain; 2nd design will analyse these effects in CV-like public good setting to develop probabilistic/structural model to forecast & PTM-based nonconventional theory to explain the effects. To allow sector/policy applications of lab results (e.g., to CV), designs will be used in field experiments at health/fundraising SME secondments, where training on patient/donor interaction & gender/ethics issues will prepare proper implementation. Fellowship’s training-through-research will thus launch a career in PTM-based framing research leading to innovations in Horizon 2020 health/efficiency/gender priorities that save public/private funds via appropriate reframing of customer relations & policy tools.

Keywords: framing effects,experimental economics,cognitive psychology,experimental methodology,process tracing methods,field experiments,external validity,cv analysis,gender equality
Vision Inspired Driver Assistance Systems (VI-DAS)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: Research and Innovation actions
Countries involved: Germany,Ireland,Ireland,Germany,Germany,Germany,Ireland,Spain,France,France,France,France,Netherlands,Netherlands,United Kingdom
Call: Safe and connected automation in road transport (H2020-MG-2015_TwoStages, 2015)
Start date: 2016-09-01
End date: 2019-08-31
Duration (months): 36.0
Total project cost (EUR): 6225246.25
EU funding (EUR): 6225246.25
Participants: 20
Project status: CLOSED

Road accidents continue to be a major public safety concern. Human error is the main cause of accidents. Intelligent driver systems that can monitor the driver’s state and behaviour show promise for our collective safety. VI-DAS will progress the design of next-gen 720° connected ADAS (scene analysis, driver status). Advances in sensors, data fusion, machine learning and user feedback provide the capability to better understand driver, vehicle and scene context, facilitating a significant step along the road towards truly semi-autonomous vehicles. On this path there is a need to design vehicle automation that can gracefully hand-over and back to the driver. VI-DAS advances in computer vision and machine learning will introduce non-invasive, vision-based sensing capabilities to vehicles and enable contextual driver behaviour modelling. The technologies will be based on inexpensive and ubiquitous sensors, primarily cameras. Predictions on outcomes in a scene will be created to determine the best reaction to feed to a personalised HMI component that proposes optimal behaviour for safety, efficiency and comfort. VI-DAS will employ a cloud platform to improve ADAS sensor and algorithm design and to store and analyse data at a large scale, thus enabling the exploitation of vehicle connectivity and cooperative systems. VI-DAS will address human error analysis by the study of real accidents in order to understand patterns and consequences as an input to the technologies. VI-DAS will also address legal, liability and emerging ethical aspects because with such technology comes new risks, and justifiable public concern. The insurance industry will be key in the adoption of next generation ADAS and Autonomous Vehicles and a stakeholder in reaching L3. VI-DAS is positioned ideally at the point in the automotive value chain where Europe is both dominant and in which value can be added. The project will contribute to reducing accidents, economic growth and continued innovation.

Keywords: driver behaviour modelling,risk quantification,adas,scene understanding,advanced mapping cartography,connectivity,cooperative its,accident analysis,cloud infrastructure
RECOVERING LIFE WELLBEING THROUGH PAIN SELF-MANAGEMENT TECHNIQUES INVOLVING ICTs (RELIEF)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Active ageing and self-management of health
Action type: COFUND actions
Countries involved: Spain,Spain,Spain,Sweden,France
Call: Self-management of health and disease and patient empowerment supported by ICT (H2020-PHC-2015-single-stage, 2015)
Start date: 2016-02-01
End date: 2021-03-31
Duration (months): 62.0
Total project cost (EUR): 2698612.5
EU funding (EUR): 1889028.75
Participants: 6
Project status: CLOSED

RELIEF aims to link European health procurers in order to create the innovative and sustainable solutions that will improve chronic pain control/relieve through ITC self-management techniques. Chronic pain diseases is costing to healthcare systems annually over €300bn in Europe; 1.5%-3% of GDP (gross domestic product). Chronic pain entails a significant direct cost to healthcare systems. Consultations with healthcare professionals confirm that Chronic pain associated costs are the largest share in healthcare system costs. Inappropriate and ineffective management and treatment generates repetitive visits to primary care physicians, and referrals to specialists. This has been identified as important drivers of avoidable healthcare costs. However, while direct costs are high, it has been estimated that nine-tenths of the burden of pain may fall on the broader society. Even small increases in the effectiveness of pain management reap large economic rewards. More than half of patients with acute or chronic pain are not well treated even though the existing therapeutic options have confirmed effective results. There is a clear heterogeneity in the treatments and also in the results. eHealth solutions must achieve greater comparability between systems, patients and protocols, so as to reach more effective and efficient procedures. At present, there is a wide range of high-tech devices aimed at treating pain in its many facets and complexity. But it is still necessary to cover the gap between Research and Commercialization of new products and devices, as outlined during the Pain Technology Transfer Forum, held in Madrid in July 2014. RELIEF will foster and accelerate the access to market for innovative solutions, while respecting the public procurement directives. The project will contribute to boost innovative tools that empower the patient to self-manage current and future pains.

Keywords: chronic pain,health,icts,wellbeing,medicine,patient,ehealth
Bio-Inspired Tools for Glycoscience (GLYCO-TOOLS)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Synthetic Chemistry and Materials
Panel description: New materials and new synthetic approaches, structure-properties relations, solid state chemistry, molecular architecture, organic chemistry
Countries involved: United Kingdom
Call: ERC Consolidator Grant (ERC-2014-CoG, 2014)
Start date: 2015-07-01
End date: 2020-12-31
Duration (months): 66.0
Total project cost (EUR): 1986356.0
EU funding (EUR): 1986356.0
Participants: 1
Project status: CLOSED

Cell surface carbohydrates play key roles in cell recognition mechanisms. O-glycosylation is a ubiquitous post-translational modification that is highly dynamic and responsive to cellular stimuli through the action of cycling enzymes. Expression of specific O-glycans is linked to changes in gene expression in, for example, inflammatory bowel disease, cystic fibrosis and several types of cancer. Protein-carbohydrate interactions typically exhibit high specificity and weak affinities toward their carbohydrate ligand. This low affinity is compensated in nature by the architecture of the protein, the host presenting the carbohydrate ligands in a multivalent manner or as clusters on the cell or mucosal surface. This effect is known as the multivalency or “cluster–glycoside effect” and has been well documented for lectin–carbohydrate interactions as increasing ligand affinity and selectivity. The fundamental understanding of these glycosylation patterns at molecular and functional levels will allow mechanisms associated with bacterial-host interactions, bowel disease and several cancers to be defined, which will facilitate the identification of effective treatments and diagnostics for these conditions in due course. This is a multidisciplinary project involving synthetic organic and inorganic chemistry, enzymology and glycobiology. The proposal centres on the development of expedient synthetic and chemo-enzymatic methodologies for the preparation of novel multivalent O-glycan probes that will be used in the screening of O-glycosylation-linked interactions in health and in disease. These studies will help us understand the parameters controlling the combinatorial diversity of O-glycans and the implications of such diversity on receptor binding and subsequent intracellular signalling, which in turn will lead us to the development of new glycan-based diagnostic tools and therapeutics.

Keywords: oligosaccharide synthesis,stereoselective glycosylations,chemo enzymatic synthesis,glycosyltransferases,fluorescent glyco nanoparticles
Mid-IR ultrabroadbaNd thulium-doped Fiber Laser sYstems (MINDFLY)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2016-03-01
End date: 2018-02-28
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

The aim of the proposed project is to develop novel configurations of the stable ultra-fast high power thulium-doped fibre laser systems mode-locked with carbon nanomaterials operating at ~2μm offering unique tool for micromachining. The Tm-doped fibre laser, with remarkable output parameters, will be used to obtain the ultra-broad supercontinuum generation in Mid-IR wavelength band extending beyond 3-9 μm. The MINDFLY project outputs will be relevant to the EU photonics industry through offering new cost-efficient technologies for stable, low-noise, ultra-high-speed, high-power ultrabroadband sources of light at Mid-IR with lower power consumption (~50%). The products transformed from the MINDFLY outputs will contribute to the enhancement of EU scientific excellence. In particular, the success of the project will lead to a number of disruptive innovations in photonics with potential application in medicine (including cancer diagnostics and optical coherence tomography), environmental sensing, optical frequency standards, and laser location services. The Fellow – Dr. Maria Chernysheva – will be trained in the fast growing field of science, technology and industrial applications of fibre lasers and nonlinear optics, receiving access to a unique training experience at the host and secondment organizations to become a rare asset to European research.

Keywords: supercontinuum generation,mid ir wavelength band,thulium doped mode locked fiber laser
Global Firms and Global Value Chains: Measurement and Mechanisms (GLOBALFIRMS)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Individuals, Markets and Organisations
Panel description: Economics, finance and management
Countries involved: United Kingdom,United Kingdom
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2018-01-01
End date: 2023-12-31
Duration (months): 72.0
Total project cost (EUR): 1462304.0
EU funding (EUR): 1462304.0
Participants: 2
Project status: SIGNED

The growing fragmentation of production across firms and countries has revolutionized international trade in recent decades. Firms today choose which production stages to conduct themselves and which to outsource to other parties, which to complete at home and which to offshore abroad. Known as global value chains (GVCs), this phenomenon creates new challenges and opportunities for individual firms and aggregate economies. Of primary policy interest are the implications of GVCs for growth, the transmission of shocks across firms and borders, and the design of economic policies. Yet academic research has faced two major challenges: poor measurement and poorly understood mechanisms. I propose an ambitious research program that will use exceptional new data and novel GVC measures for path-breaking GVC analysis. First, I will exploit unique panel data on firm production, management practices, export and import transactions for the world’s two largest export economies, China and the US; and unique panel data on firm production, export and import transactions, and the network of domestic firm-to-firm transactions for one of the most open economies, Belgium. Second, I will develop measures that comprehensively characterize three dimensions of firms’ GVC activity: value added (total/domestic/foreign), production line position (upstreamness), and network position (centrality). Third, I will empirically and theoretically examine the impact of GVCs on firm growth, shock transmission, and export-finance policy through six synergistic projects. Each project will make a distinct contribution by investigating new economic mechanisms, establishing new empirical facts, and combining theory and data for informative welfare calculations. The novelty of the data and the complex mechanisms driving GVCs make this research program highly ambitious. At the same time, the importance of understanding GVCs for economic policy and academic research make this agenda extraordinarily high-return.

Keywords: firms,global value chains,production networks
Knowledge Discovery in Data as Collaboration of Human and Software Actors (KDD-CHASER)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Ireland
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2018-02-01
End date: 2020-01-31
Duration (months): 24.0
Total project cost (EUR): 175866.0
EU funding (EUR): 175866.0
Participants: 1
Project status: CLOSED

The KDD-CHASER project aims to develop a process model and software platform for collaborative knowledge discovery in data (KDD). Traditionally, KDD has been an expert-driven process, but more recently, special types of KDD processes have begun to emerge that involve non-expert individuals in various roles. With sufficiently intelligent software tools, it is even possible for such individuals to take charge of the process and use KDD to extract useful knowledge from their own personal data, but this possibility is not adequately covered by the established process model of KDD. The project addresses this problem by exploring the requirements of incorporating autonomous software and non-expert humans as actors in the KDD process and distilling these into a new process model, consisting of a data model and a workflow model, that satisfies the requirements. The data model aims to provide a representation of the fundamental concepts of the KDD process, most importantly knowledge itself. The model forms an essential part of the foundation of new, more autonomous KDD software tools that are capable of carrying out tasks that currently require a human expert. The workflow model represents the actors of the KDD process - experts, non-experts and software - and the interactions through which they collaborate in different incarnations of the process. Once the models have been validated against their requirements, they will in turn be used to define requirements for a collaborative KDD software platform that can be used by diverse actors to establish teams and design solutions to KDD problems. Finally, the software platform will be implemented and validated by executing a test scenario involving knowledge discovery from personal lifelogs.

Keywords: knowledge discovery in data,process models,lifelogging,quantified self,knowledge representation