Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Challenging the KNDy Hypothesis Using CRISPR-Cas9 Genome Editing: Evaluation of the Role of Neurokinin B and Dynorphin in Kiss1 neurons in the Control of Fertility (CRISPR-KissCas9)

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: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2020-05-01
End date: 2022-04-30
Duration (months): 24.0
Total project cost (EUR): 160932.48
EU funding (EUR): 160932.48
Participants: 1
Project status: CLOSED

The function of the hypothalamic-pituitary-gonadal (HPG) axis is mastered by the hypothalamic neuronal population producing gonadotropin-releasing hormone (GnRH), which regulates LH and FSH secretion by the pituitary. Perturbations of fertility, e.g., in polycystic ovarian syndrome (PCOS) and hypogonadism associated with metabolic disorders, are related to functional alterations in the neuronal networks controlling pulsatile GnRH secretion. Recently, a neuronal population in the hypothalamic arcuate nucleus (ARC), which synthesizes kisspeptins (Kp; products of the Kiss1 gene), has been identified as an essential element in the regulation of pulsatile GnRH release. This ARC Kiss1 neuronal population co-expresses the neuropeptides, neurokinin B (NKB; encoded by Tac2) and dynorphin-A (Dyn; encoded by Pdyn); the term KNDy (for Kiss1, NKB & Dyn) has been coined to name this population. Different studies have pointed out the reciprocal stimulatory and inhibitory roles of NKB and Dyn, respectively, in the control of Kp output, which seemingly play a crucial role in the control of GnRH pulse generation. However, the relevance of such NKB/Dyn interplay in the dynamic control of GnRH release in different (patho)-physiological conditions, and whether this is fully dependent on Kp signaling, has not been fully clarified. We propose here to apply for the first time somatic genome editing of Tac2, Pdyn and Kiss1 loci in KNDy neurons, by using the CRISPR/Cas9 technology and virogenetic tools in suitable genetic mouse models, to address the physiological roles of NKB and Dyn in the dynamic control of GnRH neurosecretion, and their dependence on Kp signaling. The studies outlined in this proposal will substantially advance our understanding of basic neuroendocrine mechanisms for the control of fertility and will aid for the development of better strategies to treat reproductive abnormalities, such as polycystic ovarian syndrome and in/ subfertility related to metabolic disorders.

Keywords: health sciences,neuroendocrinology,reproduction,gnrh,kiss1,hypothalamus,metabolism,crispr,cas9
Quantification of mixing and dynamic uncertainty for transport in heterogeneous porous media (MixUQ)

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: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-12-01
End date: 2023-02-28
Duration (months): 24.0
Total project cost (EUR): 160932.48
EU funding (EUR): 160932.48
Participants: 1
Project status: CLOSED

Natural and engineered porous systems exhibit heterogeneity across several spatial scales leading to complex flow fields with strong fluctuations. The latter enhance the segregation and distortion of a transported scalar mixture, while diffusion promotes the local homogenization of it. In this context, spreading has been traditionally identified with the overall growth of the dissolved plume while mixing with the internal plume homogenization. Accurate quantification of mixing in heterogeneous media is one of the most relevant and still open challenges. Our current failure lay in the inability of capturing the interplay between flow fluctuations and local diffusion: the former promotes both the internal plume segregation (at early times, dominance of pure advection) and the subsequent homogenization (at late times; dominance of dispersion) by the sampling of flow fluctuations which trigger the internal folding and distortion of the plume enabling local homogenization by diffusion (coalescence mechanism). We here propose to predict mixing within a unified framework (Work package 1) which leverage on the Lamellar description of transport and capture the early (segregation) and late (coalescence) time impact of fluctuations by viewing spreading as a sub-plume scale process: the dispersion and interactions of Lamellae are captured through a continuous time random walk (CTRW) approach. At the same time, uncertainty about concentration distribution is a dynamic quantity ruled by the same physical mechanisms: plume segregation (uncertainty production) and homogenization (uncertainty reduction). We here take advantage of the insight from the novel transport model to close evolution equations (e.g., for the variance and the probability density function) apt to describe the dynamic uncertainty (Work package 2). We then explore the establishment of ergodicity for mixing under a variety of conditions (e.g., degree of heterogeneity, strength of diffusion and advection)

Keywords: mixing spreading uncertainty quantification heterogeneity porous media,stochastic modeling lamellar mixing,non fickian transport,continuous time random walk,ergodicity
Re-evaluation of temperature correction in microbial biodegradation kinetics (ReArrhenius)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Environment and Geosciences
Countries involved: Switzerland,United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-GF) (H2020-MSCA-IF-2014, 2014)
Start date: 2016-04-01
End date: 2019-03-31
Duration (months): 36.0
Total project cost (EUR): 267147.0
EU funding (EUR): 267147.0
Participants: 2
Project status: CLOSED

The main objective of this project is to evaluate the validity of using temperature correction factors (e.g. Q10) to predict the rates of micropollutant biodegradation in natural communities. The Q10 correction factor is based on the Arrhenius equation, which gives degradation kinetic rate constants as a function of temperature, and it is widely adopted in modelling (such as numerical fate models) in environmental exposure assessments. Despite its popularity, the Q10 approach is still the object of great debate among scientists, as the Arrhenius relationship holds over a very small temperature range for biological systems, in which microorganisms can function, and it is based on the assumption of compositional and functional ubiquity of the microbial communities. However, a change in temperature does not only impact chemical kinetic rates, but also determines shift and adaptation of the microbial population towards degraders that survive and perform better at the altered temperature. This project will adopt a multidisciplinary approach where biotransformation assays, kinetic modelling and high-throughput microbiological assays will be integrated to provide a thorough understanding of temperature dependence of micropollutant biotransformation kinetics in aerobic biological systems, taking into account the strong relationship between taxon traits and the environment.

Keywords: temperature correction factor,biotransformation kinetic processes,microbial community,enzyme activity
9eGEN - Development of innovative lightweight HVDC 9-phase Brushless/Generator for Clean Sky Rotorcraft (9eGEN)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Clean Sky 2
Action type: Innovation actions
Partnership: CS2 (Art-187)
Countries involved: Italy
Call: HVDC Generator (H2020-CS2-CFP02-2015-01, 2015)
Start date: 2016-07-01
End date: 2021-10-31
Duration (months): 64.0
Total project cost (EUR): 1670550.0
EU funding (EUR): 1169385.0
Participants: 1
Project status: CLOSED

Scope of this project (referred to as 9eGEN in the Technical and Administrative Section) is to develop a High Voltage Direct Current (HVDC) Brushless/Generator up to TRL6 intended to be installed on Clean Sky Life Craft helicopter for demonstration in flight. ASE S.p.A., an medium-sized Italian company that has been working in the Aerospace & Defence Industry for over 60 years sharing the market with major International players, is the applicant and the only participant in this project. The company owns full capability to run 9EGEN in its whole activities and delivery needs, relying on robust know-how and experience in the development and manufacture of Electrical Power Generation Systems. Integration, Performance, Efficiency and Reliability are not only the key features of the HVDC Brushless/Generator ASE is strongly committed to giving shape to, but they also perfectly meet the requirement for a modern Life Craft helicopter able to meet Clean Sky standards and the challenging demand for a more innovative Brushless/Generator for next generation platforms.

Keywords: hvdc,9egen,brushless,generator,clean sky,innovation,270vdc,project,20kw
CRoss-sEcToral planning decisIoN-maKing platform to foster climate Action (RethinkAction)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Action type: Research and Innovation actions
Countries involved: Spain,Spain,Italy,Italy,Germany,Germany,Germany,Greece,Sweden,Hungary,France,Japan,Portugal
Call: Developing end-user products and services for all stakeholders and citizens supporting climate adaptation and mitigation (H2020-LC-GD-2020-2, 2020)
Start date: 2021-10-01
End date: 2025-09-30
Duration (months): 48.0
Total project cost (EUR): 4999817.5
EU funding (EUR): 4999817.5
Participants: 14
Project status: SIGNED

RethinkAction puts citizens and decision-makers at the core of the climate change action, by developing a cross-sectoral user-friendly decision-making platform tailored to the needs of different end-users for delivering clear and valuable information on climate change, increasing awareness and attractiveness of mitigation and adaptation solutions centred on land use as a key driver, even critical, to sustain life and to reach objectives in the context of climate change. RethinkAction moves beyond just informing them about the desirable future and what needs to be changed, but guiding them in the decision-making process by showing how to do it through practical land-use based solutions, while at the same time building awareness and attractiveness of new lifestyles and behavioural change, and how barriers can be overcome. By co-creating of the solutions through participatory processes, RethinkAction will unquestionably promote climate change action and acceptability of the measures. RethinkAction platform will allow users to assess land use-based adaptation and mitigation solutions, understand climate change impacts over time, linking local, EU and global scales based on 6 representative case studies, covering the main regional differences related to climate change.

Keywords: land use,local dynamic models,behavioural change,cross sectoral evaluation,integrated assessment platform
High performing batteries for accelerated uptake of hybrid and electric vehicles (BATTERY PLUS)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2019)
Start date: 2019-12-01
End date: 2022-05-31
Duration (months): 30.0
Total project cost (EUR): 1737500.0
EU funding (EUR): 1198225.0
Participants: 1
Project status: CLOSED

Boosted by the threat posed by climate change and high dependency on fossil fuels, electric/hybrid vehicles are keys of the mobility of tomorrow. So far, e-mobility still presents many customer paint points, the main ones reliant on optimal battery technologies. Electric vehicles may stall without a battery revolution and LEVs (e.g. motorcycles)/HDEVs (e.g. buses) cannot be left behind. BATTERY+ brings into the market unique fast charging high performing battery solutions for Light (LEV) and Heavy Duty (HDEV) Electric Vehicles that go beyond the state-of-the art: higher energy density (leading to more range), the most accurate battery State of Charge(SoC) monitoring system (reducing range anxiety/ enlarging the battery life) and light weight construction (improving manoeuvrability/weight capacity). The revolutionary Fast Maintenance Safety Box together with the accurate SoC system radically reduce the batteries Total Cost of Ownership. MILLOR batteries are designed for 2nd life applications and the use of an App for the remote battery health monitoring, diagnostics, & predictive maintenance, which is new in the HDEVs and LEVs application area, enhances market uptake. Our target customers are HD&LEV manufacturers. An investment of 1.7M€ will finance the latest developments before its full launch in 2022. BATTERY+ will accelerate our growth phase: generating 129M€ in accum. revenues in 3 years; reinforcing our HR structure (from 17 to 84 employees after 3 years of the project end); and accessing new geographical markets, primarily in EU and later on international markets (USA, Canada and LATAM). The company behind is MILLOR, SME specialised in the design, development and manufacturing of high added value battery solutions. In just a few years of existence, MILLOR managed to position as a key innovator in battery technology in Spain and has also tied links with key partners in Europe and abroad. The project will position EU at the forefront of the battery sector.

Keywords: sustainability,city transport,inner city transports,batteries,e mobility,electric vehicles,light electric vehicles,heavy duty electric vehicles,motorcycles,li ion battery,truck
Molecular Bose Einstein Condensate (MOLBEC)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Physical and analytical chemical sciences
Panel description: Analytical chemistry, chemical theory, physical chemistry/chemical physics
Countries involved: Germany,Israel
Call: ERC Advanced Grant (ERC-2019-ADG, 2019)
Start date: 2020-08-01
End date: 2025-07-31
Duration (months): 60.0
Total project cost (EUR): 2499990.0
EU funding (EUR): 2069909.71
Participants: 2
Project status: SIGNED

Generating a Bose Einstein Condensate (BEC) or Fermi gas of molecules is a long-standing goal of modern molecular science. Molecular BEC is a macroscopic millimeter-size quantum object with a large number of molecules occupying the lowest center-of-mass quantum state. In stark contrast to atoms, molecules possess internal degrees of freedom and stronger interactions that lead to the emergence of new phenomena. Strong dipole-dipole interactions give rise to new ordered states of matter, quantum crystals. Many-body effects start dominating collision dynamics where even molecular rotational excitations are dissipated as angular-momenta-carrying quasiparticles within the condensate. Despite intense experimental efforts, these fascinating ideas remain in the realm of theory. The main difficulty in turning theory into reality has been the absence of general molecular cooling methods. Recently, we have demonstrated the first experiment where collisions between cold molecules trapped in a 1 K deep superconducting magnetic trap are achieved without laser cooling [Segev et al. Nature, 572 (2019)], opening a clear path to molecular evaporation. We here propose to cool molecules by removing the fastest ones from the trap and letting the rest thermalize to lower temperatures via collisions. This method has been used to produce atomic BECs and we are the first group reaching identical initial conditions that are necessary for the successful application of the evaporative cooling. Generality of our approach is the key to successful search for a suitable molecular candidate. As an alternative to evaporation we suggest applying direct laser cooling on magnetically stopped NH radicals. We are confident that one of our approaches will lead to the long-sought generation of molecular quantum degenerate gas. Our proposal opens new fields and will find applications in areas ranging from quantum chemistry to quantum information science.

Keywords: cold molecules,many body effects in chemistry
MAchinE Learning for Scalable meTeoROlogy and cliMate (MAELSTROM)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Theme: Public-private partnerships
Destination: European High Performance Computing
Action type: Research and Innovation actions
Partnership: EuroHPC (Art-187)
Countries involved: Germany,Germany,Italy,Switzerland,Norway,Luxembourg,United Kingdom
Call: Extreme scale computing and data driven technologies (H2020-JTI-EuroHPC-2019-1, 2019)
Start date: 2021-04-01
End date: 2024-03-31
Duration (months): 36.0
Total project cost (EUR): 4312412.5
EU funding (EUR): 2156206.25
Participants: 7
Project status: SIGNED

To develop Europe’s computer architecture of the future, MAELSTROM will co-design bespoke compute system designs for optimal application performance and energy efficiency, a software framework to optimise usability and training efficiency for machine learning at scale, and large-scale machine learning applications for the domain of weather and climate science. The MAELSTROM compute system designs will benchmark the applications across a range of computing systems regarding energy consumption, time-to-solution, numerical precision and solution accuracy. Customised compute systems will be designed that are optimised for application needs to strengthen Europe’s high-performance computing portfolio and to pull recent hardware developments, driven by general machine learning applications, toward needs of weather and climate applications. The MAELSTROM software framework will enable scientists to apply and compare machine learning tools and libraries efficiently across a wide range of computer systems. A user interface will link application developers with compute system designers, and automated benchmarking and error detection of machine learning solutions will be performed during the development phase. Tools will be published as open source. The MAELSTROM machine learning applications will cover all important components of the workflow of weather and climate predictions including the processing of observations, the assimilation of observations to generate initial and reference conditions, model simulations, as well as post-processing of model data and the development of forecast products. For each application, benchmark datasets with up to 10 terabytes of data will be published online for training and machine learning tool-developments at the scale of the fastest supercomputers in the world. MAELSTROM machine learning solutions will serve as blueprint for a wide range of machine learning applications on supercomputers in the future.

Keywords: scalable machine learning,hardware,software co design,compute system design
Modified Internal Gate image sensor for low light optimised Out-door Security surveillance Applications (MIGOSA)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Finland
Call: Open Disruptive Innovation Scheme (implemented through the SME instrument) (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

In today’s cameras the photographic film has been replaced by image sensors, which are silicon chip transforming light into digital images. The image sensors have large amount of pixels measuring locally the amount of light impinging on the pixel and jointly forming the digital image. The image sensors are manufactured like any other silicon chips in foundries having clean rooms and sophisticated silicon processing tools. So far there have been two different ways to readout the pixel specific signal, namely, External Gate (EG) configuration utilized e.g. in present Charge Coupled Device (CCD) and Complementary Metal Oxide Semiconductor (CMOS) image sensors as well as Internal Gate (IG) readout configuration that is prone to manufacturing issues and consequently its use is extremely limited. The EG was invented in the sixties and the IG in the seventies. The problem with both of them is that they suffer from non-optimal low light performance. Pixpolar has invented, developed, and patented (more than 20 patents are already granted) a third fundamentally new image sensor pixel readout configuration called the Modified Internal Gate (MIG) that provides superior low light performance when compared to the two other older technologies. The MIGOSA project comprises three different tasks. The first one is business plan development work comprising meetings with potential customers in order to ensure that there is sufficient need for the MIG technology and that the development work fulfills customer needs. The second one is an Intellectual Property Right (IPR) study to be performed in order to investigate whether there are any IPR obstacles for MIG image sensor manufacturing. The third one is a manufacturability study performed by the chosen foundry in order to find out whether our pixel design complies with the foundry’s manufacturing process.

Keywords: mig image sensors,high end low light black and white security and surveillance cameras,manufacturability study,freedom to operate study,business plan development