Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Multiparametric Microfluidic System for the Point-Of-Care detection of sepsis (MuMiPOC)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Society and Enterprise panel
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Netherlands
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-02-01
End date: 2023-01-31
Duration (months): 24.0
Total project cost (EUR): 175572.48
EU funding (EUR): 175572.48
Participants: 1
Project status: CLOSED

Sepsis is a life-threatening condition caused by a dysregulated response of the host’s immune system to infection. If not treated immediately, it can result in multiple organ failure and death. According to the World Health Organisation (WHO), sepsis affects approximately 30 million people worldwide every year, leading to potentially 6 million deaths. The main challenges associated with this condition are that it is, on the one hand, challenging to diagnose in its early stages when it is still potentially reversible, and, on the other hand, it is often confused with non-life-threatening diseases such as flu or gastroenteritis. Current clinical approaches to diagnose sepsis in low-complexity healthcare settings (where most patients are admitted at first) fail to provide the required sensitivity and specificity to overcome these challenges. Portable, fast and economical technologies that help to infer sepsis accurately are therefore vital to tackle these challenges. This project aims to develop a portable, low-cost microfluidic platform which has the capability to detect sepsis under 1 hour and has sensitivity and specificity levels above 90%. This platform is based on the quantification of several blood rheological parameters that are affected by this pathology. Previous research has shown that these parameters have clinical relevance for the early diagnosis of sepsis. The project will be executed in the company Micronit Microtechnologies BV (host institution) located in the Netherlands under the supervision of Dr. Maciej Skolimowski. This project also includes a secondment in the Department of Intensive Care at the Erasme Hospital – Université Libre de Bruxelles (secondment institution) located in Belgium under the supervision of Prof. Jean-Louis Vincent. The duration of the project is 24 months.

Keywords: microfluidics,lab on a chip,sepsis,blood rheology
Pledge Limits Evaluation for Decarbonization: Goals of the EU27 Strategy (PLEDGES)

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-2020, 2020)
Start date: 2022-03-01
End date: 2024-02-29
Duration (months): 24.0
Total project cost (EUR): 224933.76
EU funding (EUR): 224933.76
Participants: 1
Project status: SIGNED

This research aims to develop a new climate policy modelling tool - PLEDGES - which manages, for the first time, carbon budget targets for EU-27 countries. Each EU country has different barriers and opportunities for decarbonization. However, these potentialities are not exploited nor explored by the EU Green Deal or by the long-term mitigation targets established under the United Nations Conference of the Parties Agreements, which pledged to keep the temperature increase below 2°C. Current EU policies mainly focus on emission reduction targets and do not take into account cumulative emissions or the speed at which the transition to lower carbon can be achieved. Considering these factors is critical to the success of policies that can achieve the temperature goal. PLEDGES model will fill this gap, providing EU policy-makers with a tool able to downscale EU and world climate mitigation policy to national levels. It will set a European carbon budget and allocate an allowance of carbon emissions to each EU region, country, or even person according to a set of eligibility criteria based on an effort-sharing approach. Once a potential carbon budget for each member state is calculated, the PLEDGES tool will be able to simulate necessary deviations from the assumed national quotas and to evaluate how those deviations impact on the other member states. PLEDGES will help policy-makers evaluate accurately the shared effort needed to mitigate climate change; it configures as a high interdisciplinary tool, helping in designing mitigation actions under a holistic view that considers topics in scientific, economic and social spheres, including the role of gender.

Keywords: carbon budget,decarbonization,climate change,climate mitigation,eu policy,cop21,greenhouse,gases,emissions trade system,system dynamics
Opportunities and education in networked innovation for new graduates with PhDs using open online resources (OPENING DOORS)

Framework: Horizon 2020 — Science with and for Society
Programme: Make scientific and technological careers attractive to young students, and forster sustainable interaction between schools, research institutions, industry and civil society organisations
Action type: Coordination and support actions
Countries involved: Ireland,Ireland,Czechia,Denmark,Japan
Call: Research innovation needs & skills training in PhD programmes (H2020-SwafS-2020-1, 2020)
Start date: 2021-02-01
End date: 2022-06-30
Duration (months): 17.0
Total project cost (EUR): 304815.0
EU funding (EUR): 304815.0
Participants: 5
Project status: CLOSED

The purpose of OPENING DOORS is to co-develop an interdisciplinary, intersectoral, & international educational offering for post-graduate researchers. Our goal is to shape more innovative, socially aware, integrative and employable research graduates, ready to meet the challenges of the future. This will be accomplished through a challenge-based, open online educational course on open science. The focus of the course is on cultivating valued skills that can contribute meaningfully to the quadruple-helix model of open innovation. This model recognises four major actors in the innovation system: the scientific enterprise, policy, industry, and society. The Covid-19 pandemic has transformed technology-enabled university teaching overnight. An adaptation process that often takes years has been greatly accelerated, disrupting many cultural barriers to using digital learning environments. The OPENING DOORS virtual learning environment will be underpinned by connectivism as the pedagogical approach. Connectivism reflects the networked innovation environments of the future. The specific objectives of OPENING DOORS are to: 1) identify the graduate skills that are valued in open innovation systems through interviews with employers, PhD graduates and educators in those systems 2) co-design an educational course for PhD and postdoctoral researchers in collaboration with industry, government, community, university stakeholders including PhD students, that uses real-world challenges as the basis of collaborative learning opportunities 3) enable students to manage interdisciplinary, intersectoral and international connectivity through an open, online learning environment; reflexivity, interdisciplinary team communication processes, intercultural sensitivity, digital skills and career development will underpin the learning process This work is vital in an era where open science practices are becoming the currency in many intersectoral innovation networks

Keywords: open innovation networks,connectivism,learning ecologies,the third space,employability,interdisciplinary,quadruple helix model of innovation,smart cities,socioecological transition
ANALYSIS OF RC STRUCTURES EMPLOYING NEURAL NETWORKS (ARCSENN)

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: 2015-09-01
End date: 2017-08-31
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

The primary objective of the proposed project is to develop a radically new structural analysis procedure capable of accurately predicting the nonlinear behaviour of reinforced concrete structures. The proposed approach will be developed within the Soft Computing framework and as a result will require significantly less computational resources than those of more traditional methods of structural analysis. The proposed procedure will simulate each RC element, the beam-column joints included, with a single neural network, which has first to be appropriately trained. The training process will be based on the combined use of published test data, numerical predictions obtained from nonlinear finite-element analyses and the predicted behaviour of published physical models of RC structural elements at their ultimate limit state. In order to model intricate structures, the individual Neural Networks will be combined through a new solution strategy so as to provide a representative model of the structure considered. The stability and robustness of the proposed structural analysis method, as well as the validity and objectivity of its predictions, will be ensured through a comparative study of the predicted behaviour of RC frames with its counterparts established experimentally and numerically via nonlinear finite element analysis. Throughout these studies, attention will be focussed on identifying parameters affecting the overall structural response of RC frames (such as the effect of crack-formation within the joint regions) as well as their implications on practical structural analysis and design. Overall, the proposed work will lead to a stable, robust and computationally efficient numerical procedure capable of realistically and objectively predicting the nonlinear response of RC structures and suitable, not only for research and practical applications, but also for solving design optimization and reliability problems which require extensive parametric investigations.

Keywords: neural networks,soft computing,reinforced concrete structures,nonlinear structural analysis,nonlinear behaviour,beams,columns,joints,frames,numerical analysis,structures
Examining the Causes and Consequences of Criminal Behavior (CRIME)

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: Sweden
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-09-01
End date: 2024-12-01
Duration (months): 24.0
Total project cost (EUR): 191852.16
EU funding (EUR): 191852.16
Participants: 1
Project status: SIGNED

Criminal behavior presents a significant public health problem that involves heavy economic and social burdens, including the costs of criminal justice adjudication, compensation for victims and their families, and collateral impacts on communities. While there have been attempts to address this important topic, there are a number of limitations in other studies. Within the field of criminology, sociological perspectives have been the dominant explanation for criminal behavior for while biological factors have been largely ignored. Additionally, most of the criminological research has been based in the U.S., and criminological researchers who examine biological factors often need to rely on small, non-representative samples due to the lack of national U.S. databases containing relevant information. There have been attempts in Europe, mainly by psychiatrists and other medical professionals, to address crime-related questions by using available European registries; however, these projects examine familial transmission of genetic risks for psychiatric conditions, focus on specific subtypes of criminal offending, or utilized techniques that are considered outdated or rudimentary today. Lastly, much of the research has focused on male offenders and on offenders who engage in “street” crime (e.g., violent crime), with little attention paid to female offenders or less conventional forms of offending (e.g., white-collar crime). To overcome these limitations, this project will utilize Sweden’s national registries that allow for population-wide analyses and state-of-the-art statistical techniques to deepen the understanding of the role of biological (i.e., genetic) and social (i.e., environmental) influences in the development of criminal behavior (in general and by subtype), and how gender and socioeconomic status alter these biological and social influences. The proposed study will also examine the consequences of criminal behavior on subsequent life outcomes.

Keywords: crime,criminal behavior,heritability,genetics,population based,national registry,big data
Environmental fate of double stranded RNA (dsRNA) from RNA interference crop protection technology in agricultural systems: A systematic assessment of dsRNA hydrolysis, adsorption, and photolysis (dsRNAEnvFate)

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: Environment and Geosciences
Countries involved: Switzerland
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-07-01
End date: 2018-06-30
Duration (months): 24.0
Total project cost (EUR): 187419.6
EU funding (EUR): 187419.6
Participants: 1
Project status: CLOSED

The use of RNA interference (RNAi) to combat pest insects is anticipated to become an integral component of crop protection technology in the US and Europe by 2020. Protection against pests is conferred via double stranded RNA (dsRNA) as the active ingredient that is either externally applied to the crop or internally expressed in genetically modified crops. Following ingestion by the pest, the dsRNA is cleaved to produce small interfering RNA (siRNA), which interfere with the translation of specific mRNA into proteins. While concern has been raised that the release of dsRNA into agricultural soils and adjacent water bodies may have detrimental ecological effects, risk assessment of RNAi crop protection technology has been impaired due to the lack of information on the fate and stability of dsRNA in the environment. The objective of the proposed project is to advance a detailed understanding of dsRNA fate in agricultural soils and adjacent water bodies. To this end, three environmental processes impacting dsRNA persistence will be studied on a mechanistic level: abiotic and enzymatic dsRNA hydrolysis, adsorption of dsRNA to mineral and organic particle surfaces, and direct and indirect photolysis of dsRNA. These processes will be studied using state-of-the art dsRNA quantification methods, experimental approaches, and analytical techniques employed in the environmental sciences, material sciences, and molecular biology. The project aims at unraveling the mechanisms and main reaction pathways that control dsRNA hydrolysis, adsorption and photolysis. Through the generation of a fundamental understanding of these processes, the proposed project will lay the foundation to predict the fate and stability of dsRNA in agricultural systems. As such, the results of this proposal will allow regulatory agencies to develop dsRNA exposure scenarios in agricultural systems and thus help advance risk assessment of RNAi crop protection technology prior to its implementation.

Keywords: rnai,dsrna,crop protection,insecticide,exposure,risk assessment,environmental persistence,degradation,product characterization,hydrolysis,adsorption,desorption,photochemical transformation
AQANAT® biowater: Advanced sustainable residue free sanitation system for post-harvest food processing resulting in a 70% reduction in water usage and a 50% reduction in post-harvest losses (biowater)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Action type: SME instrument
Countries involved: United Kingdom
Call: Boosting the potential of small businesses in the areas of climate action, environment, resource efficiency and raw materials (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2016-06-01
End date: 2016-08-31
Duration (months): 3.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The food processing industry is a large water user worldwide. In particular, water is used as a cleaning source, conveyor of raw materials and cooling agent for quickly perishable commodities. Recently, the food industry is facing increasing pressure to ensure company activities follow environmentally sound protocols, but there is also pressure to increase profitability against competition. A primary concern of the food-industry is consumer safety. The use of alternative control means other than chemicals to reduce water microbial contamination and postharvest decay of fruit and vegetables is becoming increasingly important to enhance food safety and minimise residue levels in fresh produce while preserving water. Although water will always be an integral part of food processing, environmentally sound technologies for pollution prevention and water preservation have potential for cost-effective resource reduction practices. We have developed an innovative technology, biowater, for sustainable food processing and sanitation. The patented biowater process combines environmentally sound technologies for treatment, sanitation and recycling of wash water for postharvest fruit and vegetable processing. AQANAT’s innovative water treatment technology allows efficient sanitation of process waters in a closed system (zero discharge) allowing for substantial water savings. Following successful product development and commercial launch in the citrus packinghouse market, AQANAT LTD objectives include the development of further product prototypes for pilot commercial testing and commercial launch in other postharvest applications. In particular, a feasibility study will be carried out on large volume water users such as Hydro- Coolers of fruit and vegetable (e.g. salads, cherries, apples, carrots and other fruits and vegetables) produce with the objective to increase profitability while reducing produce postharvest losses and wastewater volume

Keywords: water filtration,disinfection,zero discharge,wash water,sanitation,produce,commodities
The Spatial Dynamics of Room Acoustics (SONORA)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Systems and communication engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: Belgium
Call: ERC Consolidator Grant (ERC-2017-COG, 2017)
Start date: 2018-05-01
End date: 2023-10-31
Duration (months): 66.0
Total project cost (EUR): 1999825.0
EU funding (EUR): 1999825.0
Participants: 1
Project status: SIGNED

The SONORA project aims to increase the general understanding of how complex sound scenes are impacted by the spatial dynamics of room acoustics. This knowledge is crucial in the design of signal processing algorithms for audio acquisition and reproduction problems in real-life situations, where moving sound sources and observers interact with room acoustics in a complicated manner. A major part of the project will be devoted to the development of novel room acoustics models and to the unification of existing models. The room acoustics models developed in this project will be data-driven models with a physically motivated structure, and are expected to fill the existing gap between geometric and wave-based models. This will be achieved by formulating existing and novel models in a dictionary-based mathematical framework and introducing a new concept coined as the equivalent boundary model, aimed at relaxing the prior knowledge required on the physical room boundary. A second part of the project will focus on the development of a protocol for measuring spatiotemporal sound fields. This protocol will be rooted in a novel sound field sampling theory which exploits the spatial sparsity of sound sources by invoking the compressed sensing paradigm. Thirdly, novel signal processing algorithms capable of handling spatiotemporal sound fields will be designed. By employing recent advances in large-scale optimization and multidimensional scaling, fast and matrix-free algorithms will be obtained that do not require prior knowledge of the sound scene geometry. The SONORA research results are anticipated to have a notable impact in various audio acquisition and reproduction problems, including acoustic signal enhancement, audio analysis, room inference, virtual acoustics, and spatial audio reproduction. These problems have many applications in speech, audio, and hearing technology, hence a significant benefit for industry and for technology end users is expected in the long run.

Keywords: room acoustics,audio signal processing,acoustic signal enhancement,audio analysis,room inference,virtual acoustics,spatial audio reproduction