Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
A Holistic System for Building Inspection and Energy Efficiency Management (ENGINENCY)

Framework: Horizon 2020 — Societal Challenges
Action type: Innovation actions
Countries involved: Spain,Germany,Spain,France,Netherlands
Call: Fast Track to Innovation Pilot (H2020-FTIPilot-2015-1, 2015)
Start date: 2016-07-01
End date: 2018-11-30
Duration (months): 29.0
Total project cost (EUR): 3038068.93
EU funding (EUR): 2376877.51
Participants: 5
Project status: CLOSED

Three industrial SMEs (ICM, QIVIVO and DEMO) and a public research institution (University of Vigo) from three EU countries are joining expertise in different building energy efficiency domains to develop and commercialize Enginency. Our approach will help to deliver, implement and optimize the energy efficiency of buildings, with technical, economic and societal potential to drastically reduce energy consumption and decrease CO2 emissions, addressing both new facilities and retrofitting and/or managing of existing ones. Enginency will support energy managers and expert´s decisions through the integration of energy audit with advanced technological solutions for automated measurement acquisition, simulation over automatically calibrated models and analysis engines to deliver a holistic tool to inspect building, and measure, manage, report and improve their energy efficiency. Enginency will be commercialized as Software as a Service, facilitating the implementation and acquisition of this powerful system while decreasing both costs of deployment and maintenance to the end user, without requiring the presence of IT experts. In particular, Enginency will allow the final user to reduce the energy consumption of buildings of above 50%, with a zero-risks formula, while allowing Energy Service Companies (ESCOs) a 94% reduction of the inspection costs and an 88% reduction of the inspection duration, obtaining 15% more accurate results, with a payback time of only 12.4 months. The Enginency consortium will take advantage of the substantial foreseen growth of the energy efficient market in Europe, as well as of the experience and current distribution network of its partners, to deliver its solution to ESCOs and final users generating 65 new jobs inside the consortium and a cumulative revenue of 20.4M€ over the first five years of commercialization, representing a unique opportunity of growth and market expansion for the members of the consortium.

Keywords: energy efficiency,buildings,inspection,software as a service,calibrated,holistic tool,automated measurement,building simulation,energy saving,esco,energy managers
Deconstructing Ageing: from molecular mechanisms to intervention strategies (DeAge)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Physiology in Health, Disease and Ageing
Panel description: Organ and tissue physiology, comparative physiology, physiology of ageing, pathophysiology, interorgan and tissue communication, endocrinology, nutrition, metabolism, interaction with the microbiome, non-communicable diseases including cancer (and except disorders of the nervous system and immunity-related diseases)
Countries involved: Spain
Call: ERC Advanced Grant (ERC-2016-ADG, 2016)
Start date: 2017-09-01
End date: 2023-08-31
Duration (months): 72.0
Total project cost (EUR): 2456250.0
EU funding (EUR): 2456250.0
Participants: 1
Project status: SIGNED

Over many years, our research group has explored the complex relationship between cancer and ageing. As part of this work, we have generated mouse models of protease deficiency which are protected from cancer but exhibit accelerated ageing. Further studies with these mice have allowed us to unveil novel mechanisms of both normal and pathological ageing, to discover two new human progeroid syndromes, and to develop therapies for the Hutchinson-Gilford progeria syndrome, now in clinical trials. We have also integrated data from many laboratories to first define The hallmarks of ageing and the current possibilities for Metabolic control of longevity. Now, we propose to leverage our extensive experience in this field to further explore the relative relevance of cell-intrinsic and -extrinsic mechanisms of ageing. Our central hypothesis is that ageing derives from the combination of both systemic and cell-autonomous deficiencies which lead to the characteristic loss of fitness associated with this process. Accordingly, it is necessary to integrate multiple approaches to understand the mechanisms underlying ageing. This integrative and multidisciplinary project is organized around three major aims: 1) to characterize critical cell-intrinsic alterations which drive ageing; 2) to investigate ageing as a systemic process; and 3) to design intervention strategies aimed at expanding longevity. To fully address these objectives, we will use both hypothesis-driven and unbiased approaches, including next-generation sequencing, genome editing, and cell reprogramming. We will also perform in vivo experiments with mouse models of premature ageing, genomic and metagenomic studies with short- and long-lived organisms, and functional analyses with human samples from both progeria patients and centenarians. The information derived from this project will provide new insights into the molecular mechanisms of ageing and may lead to discover new opportunities to extend human healthspan.

Keywords: longevity,progeria,proteostasis,proteases,senescence
Connected cars for real time smart road maintenance and increased driving safety (Klimator-RSI)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Sweden
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2018)
Start date: 2018-06-01
End date: 2019-11-30
Duration (months): 18.0
Total project cost (EUR): 1412541.25
EU funding (EUR): 988778.88
Participants: 1
Project status: CLOSED

Correct road maintenance is crucial for ensuring good traffic flow and to maintain safety standards for road users. Safety is one of the most important factors in road maintenance with over 26,000 lives lost on EU roads alone with another 135,000 seriously injured with the total social cost estimated at €100 bn. Adverse weather conditions are the primary source of road accidents, with risk increased by 9 times on snowy roads and 20 times on icy roads. Current conventional methods for monitoring and forecasting road conditions have several disadvantages such as; cannot present real-time road surface data for an entire region at road level or are too costly to implement of whole road networks. These disadvantages mean that winter road maintenance is still undertaken using the experience and decision making of the staff without the use of real-time data to aid decision making. To address this need, KLIMATOR presents its Road Status Information Technology, which uses unique algorithms to interpret 3 key data sources to monitor and predict road surface conditions on an entire road network with a well-designed and clear user interface. Our algorithms then process this data which can be represented on a visual map of the whole road network. RSI allows contractors to decrease 20-30% of winter road maintenance costs while increase the safety and efficiency of the roads by keeping them open and decreasing costs (-5% vehicle wear, -20% fuel usage). The data produced using this system will also be sold to OEM car manufacturers as a friction mapping service, to give drivers and autonomous cars real-time information to increase safety. Our business opportunity relies on an estimated Total Available Market, within the EU alone, of €54M for our RSI system and another €4M for our initial friction mapping service. We estimate the RSI project will allow us to generate a cumulative net income of €27.8M in the period 2020-23 and a ROI of 13.97, achieving the breakeven during 2022.

Keywords: winter road maintenance,road status monitoring,climate model,road safety,surface,information,gritting,salt,de icing,winter,snow,efficient,mobility,smart,transport,weather,network
Climate economic policies: assessing values and costs of uncertainty in energy scenarios (MANET)

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: Italy
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-07-01
End date: 2024-06-30
Duration (months): 24.0
Total project cost (EUR): 171473.28
EU funding (EUR): 171473.28
Participants: 1
Project status: SIGNED

Curbing greenhouse gas emissions is a challenge of the utmost importance for our society future and requires urgent decisions on the implementation of clear-cut climate economic policies. Integrated Assessment Models (IAMs) allow to explore alternative energy scenarios in the next 30-70 years. They are key to support the design of climate policies as they highlight the nexus between climate modelling, social science, and energy systems. However, the use of IAMs to inform climate policies does not come free of controversial aspects. Primarily, the inherent uncertainty of IAMs long-term outputs has created several difficulties for the integration of the modelling insights in the policy design. Modelling outputs diverge across IAMs models quite dramatically when they are asked for example to quantify the uptake of key technologies for the decarbonisation, such as renewables and carbon capture and storage. Uncertainty in IAMs descends from lack of knowledge of the future and from IAMs incomplete representations of the future. Uncertainty cannot be removed, but reduced, understood, and conveyed appropriately to policy makers to avoid that different projections cause delayed actions. This project aims to fill this gap providing a methodology which defines the sources of uncertainty, either due to IAMs inputs or IAMs structure, and quantify their relative importance. The methodology will be embodied in an emulator of IAMs, MANET (the eMulAtor of iNtegratAd assEssmenT models) formulated using machine learning techniques to reproduce IAMs outputs. The project will provide a proof of concept of MANET focusing on the uptake of key decarbonisation technologies. The emulator will provide a simplified version of the IAM outputs as a response surface of the model to any variation of the inputs. MANET will be a flexible tool for policy makers and scientists for a direct comparison of IAMs with no limitation of the solution domain.
Interrogating Basolateral Amygdala Activity during Social Behaviour at Single-Cell and Population Levels (AMYGDALA-ELECTROPHYS)

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-2018, 2018)
Start date: 2019-05-01
End date: 2021-04-30
Duration (months): 24.0
Total project cost (EUR): 224933.76
EU funding (EUR): 224933.76
Participants: 1
Project status: CLOSED

The accurate perception and interpretation of social stimuli is crucial for survival in social species including rodents, primates and humans. Before deciding whether to mate, fight or avoid, an animal must process multisensory cues to activate an internal representation of the social environment that answers key questions (Sex? Age? Friend? Foe? Previously encountered?). Little is known about how the brain develops and activates this representation. We will focus on the role of neuronal firing in the basolateral amygdala complex (BLA) in processing and integrating social cues. In the first stage of this research, we will use neuropixel silicon probes to conduct large-scale recordings of the BLA in rats during social interaction with conspecifics (juvenile rats, male rats and female rats). We can record from large populations of neurons across weeks in freely-moving rats during social interaction. Second, by analysing the activity of single neurons in the BLA, we can characterize the specificity and responsivity of single neurons to social interaction and understand the mitigating factors (gender of conspecific, sexual receptivity, age, previous history). Third, we can decode the population activity of the BLA during social activity to understand how BLA connectivity changes during social interaction and with experience. Finally, we will use optical tagging of anatomically-defined ensembles of BLA neurons to understand how BLA projections code for specific properties of social activity. Success in this project will provide an understanding of how neural computation occurs within the BLA.
COMPutationally empowered Electromagnetic industrial TalEnts (COMPETE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Innovative Training Networks (ITN)-European Industrial Doctorates
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Italy,France
Call: Innovative Training Networks (H2020-MSCA-ITN-2020, 2020)
Start date: 2021-03-01
End date: 2025-02-28
Duration (months): 48.0
Total project cost (EUR): 1334103.12
EU funding (EUR): 1334103.12
Participants: 2
Project status: SIGNED

The aim of COMPETE (COMPutationally empowered Electromagnetic industrial TalEnts) is to bridge the gap between the mindset and needs of advanced electromagnetics industry and the academic doctoral programs forming electromagnetic modelers designers and innovators. Standard doctoral programs in computational electromagnetics provide solid theoretical and algorithmic background, but are often abstract and far from the on-the field industrial needs. Several key elements of the industrial processes related to sensitivity of key devices, associated costs, relaiability and benchmarking of results are often discovered much later by the PhD student, and often European doctoral curricula in this field results less competitive than those of PhD awarded candidates from other systems like the North American one. This training, will instead provide since the very beginning a very pragmatic prospective on the current industrial needs in modelling and will form and educate a cohort of young scientists and innovators in the field of industrial computational electromagnetics.

Keywords: computational electromagnetics,electromagnetic engineering,antenna analysis
A seamless multi-scale model for contact, friction, and solid lubrication (FricLess)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator 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: Italy,Netherlands
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2016-06-01
End date: 2023-11-30
Duration (months): 90.0
Total project cost (EUR): 1999985.0
EU funding (EUR): 1819985.0
Participants: 2
Project status: SIGNED

Friction and wear are liable for enormous losses in terms of energy and resources in modern society. Costs related to unwanted friction in industrialised countries are estimated to be about 3% of the gross domestic product. Urgency is even greater nowadays as friction between micro-components has become the bottleneck of several applications for which miniaturisation is critical. Lubrication is a commonly adopted solution to reduce friction. Graphite is a broadly used solid lubricant for large scale applications, while the lubricating properties of a few-layers graphene hold great promise especially for smaller scale applications. At present, our knowledge of the friction and lubrication of rough surfaces is essentially phenomenological. This is because friction is only deceivingly a simple mechanisms, which instead requires understanding of physical phenomena simultaneously acting at different length scales. The change in contact size, which controls the friction stress, depends on nano-scale phenomena such as atomic de-adhesion, sliding, dislocation nucleation in metals, but also on micro- and macro-scale phenomena as (size-dependent) plastic deformation. The objective of this proposal is to reach an unprecedented understanding of metal friction and lubrication by accounting, for the first time, for all relevant phenomena occurring from the atomic to the macro-scale, and their interplay. To this end, a seamless concurrent multi-scale model will be developed. The power of this new model lies in its capability of describing three-dimensional bodies with realistic roughness in sliding lubricated contact, with the accuracy of an atomistic simulation. This research builds towards a complete picture of metal friction and lubrication. The materials chosen for the proposed research are copper and multi-layer graphene. However, the model that will be developed is general and can be used to study different materials, lubricants and environmental conditions.

Keywords: computational mechanics,friction,lubrication,plasticity,graphene
Novel etiology of autoimmune disorders: the role of acquired somatic mutations in lymphoid cells (M-Imm)

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: Finland
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): 2047337.0
EU funding (EUR): 2047337.0
Participants: 1
Project status: CLOSED

Molecular pathogenesis of most immune-mediated disorders, such as of autoimmune diseases, is poorly understood. These common maladies carry a heavy burden both on patients and on society. Current therapy is non-targeted and results in significant short- and long-term adverse effects. Large granular lymphocyte (LGL) leukemia is characterized by expansion of cytotoxic T- or NK-cells and represents an intriguing clinical continuum between a neoplastic and an autoimmune disorder. Patients suffer from autoimmune cytopenias and rheumatoid arthritis (RA), which are thought to be mediated by LGL cells targeting host tissues. My group recently discovered that 40-50% of LGL leukemia patients carry in their lymphoid cells acquired, activating mutations in the STAT3 gene – a key regulator of immune and oncogenic processes (Koskela et al, N Engl J Med, 2012). This breakthrough discovery gives insight to the pathogenesis of autoimmune disorders at large. I present here a hypothesis that a strong antigen-induced proliferation is a mutational driver, which causes somatic mutations in lymphoid cells. When mutations hit key activating pathways, autoreactive cells acquire functional advantage and expand. The target antigen of the expanded clone determines the clinical characteristics of the autoimmune disease induced. To prove this hypothesis, we will separate small lymphocyte clones from patients with autoimmune diseases and use sensitive next-generation sequencing methods to characterize the spectrum of somatic mutations in lymphoid cells. Further, we will study the function of mutated lymphocytes and examine the mechanisms of autocytotoxicity and end-organ/tissue damage. Finally, we aim to understand factors, which induce somatic mutations in lymphoid cells, such as the role of viral infections. The results will transform our understanding of molecular pathogenesis of autoimmune diseases and lead to accurate diagnostics and discovery of novel drug targets.

Keywords: etiology,somatic mutations,virus,leukemia,aplastic anemia,rheumatoid arthritis
Differential Inclusions and Fluid Mechanics (DIFFINCL)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: Germany
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-04-01
End date: 2022-09-30
Duration (months): 66.0
Total project cost (EUR): 1860875.0
EU funding (EUR): 1860875.0
Participants: 1
Project status: CLOSED

Important problems in science often involve structures on several distinct length scales. Two typical examples are fine phase mixtures in solid-solid phase transitions and the complex mixing patterns in turbulent or multiphase flows. The microstructures in such situations influence in a crucial way the macroscopic behavior of the system, and understanding the formation, interaction and overall effect of these structures is a great scientific challenge. Although there is a large variety of models and descriptions for such phenomena, a recurring issue in the mathematical analysis is that one has to deal with very complex and highly non-smooth structures in solutions of the associated partial differential equations. A common ground is provided by the analysis of differential inclusions, a theory whose development was strongly influenced by the influx of ideas from the work of Gromov on partial differential relations, building on celebrated constructions of Nash for isometric immersions, and the work of Tartar in the study of oscillation phenomena in nonlinear partial differential equations. A recent success of this approach is provided by my work on the h-principle in fluid mechanics and Onsager's conjecture. Against this background my aim in this project is to go significantly beyond the state of the art, both in terms of the methods and in terms of applications of differential inclusions. One part of the project is to continue my work on fluid mechanics with the ultimate goal to address important challenges in the field: providing an analytic foundation for the K41 statistical theory of turbulence and for the behavior of turbulent flows near instabilities and boundaries. A further aim is to explore rigidity phenomena and to attack several outstanding open problems in the context of differential inclusions, most prominently Morrey's conjecture on quasiconvexity and rank-one convexity.

Keywords: fluid mechanics,turbulence,compensated compactness,h principle,differential inclusions