Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
The composition and evolution of C. elegans behavioural genetic architectures (EvolBehavGenArch)

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: France
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-09-03
End date: 2020-09-02
Duration (months): 24.0
Total project cost (EUR): 185076.0
EU funding (EUR): 185076.0
Participants: 1
Project status: CLOSED

The maintenance of genetic diversity in the face of neutral and non-neutral processes that continually erode it is one of the longstanding puzzles of biology. Natural selection shapes the genetic variation provided by mutation, segregation and recombination to (generally) improve fitness, but it is often difficult to obtain measures of fitness and genetic variation in the interesting, but uncontrolled, natural environments in which we find organisms. A related question is the heritable basis of phenotypic variance. Knowing the genetic architectures of well-defined traits – the number and type of loci that contribute to phenotypic variance, and the distribution and conditionality of their effects – is central to our general understanding of evolutionary processes, and for our ability to predict phenotypes of interest in agriculture and medicine. In this context, the genetic basis of behavioural variation is particularly fascinating but poorly understood. Caenorhabditis elegans is an exceptional model system with which to tackle these problems, and experimental evolution provides exceptional power to dissect genetic architectures of well-defined behavioural traits and their dynamic properties under controlled conditions. The proposed research will advance our understanding of how trait correlations shape the distribution of genetic variance, and will reveal, in unprecedented detail, the composition and evolution of behavioural genetic architectures shaped by natural selection.

Keywords: evolution of correlated traits,behaviour,locomotion,epistasis,environmental interaction,genetic architecture
Cost competitive process for recycling Cobalt from end of life Li-ion batteries (CoReco)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Italy
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-06-01
End date: 2019-11-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The Black Mass is a residue of the Li-ion spent batteries (LIB) composed by Cobalt, Nickel, Manganese, Copper, Lithium, Iron and Carbonates, currently disposed as special waste for the lack of cost-competitive metals recovery technologies. The steep growth of electric vehicles (EV) and hybrid-electric vehicles (HEV) market, projected to reach respectively 25 million and 7.6 million units by 2025, is leading to an unparalleled increase of the Black Mass amount to be disposed (up to 4 million tons by 2025) with an unsustainable expense for the industrial players (100 €/ton). But the Black Mass is a potential source of Cobalt, a critical material for the battery manufacturing: today, more than 60% of the global Cobalt comes from the Democratic Republic of Congo, with a steeply growing trend of its price due to political instability and market demand increase. Cobalt price is highly fluctuating, but it is foreseen to reach >100 €/kg from 2022, with an extra cost of 600 M€/year for EV industry. Recycling the Cobalt contained in the spent batteries would allow to mitigate the price and reduce the dependence of European companies on imports. CoReco is an innovative and cost competitive process able to recover Cobalt, Nickel, Manganese and Copper contained in the Black Mass derived from the recycling of LIB with high purity. CoReco uses 2 innovative solutions: a Top Blown Rotary Converter for smelting, much more efficient and compact than competing solutions; a single reactor for all subsequent hydrometallurgical purification steps. CoReco is able to recover 98% of Ni, Co, Mn and Cu contained in the Black Mass and to reach > 99% purity of the Cobalt for reuse as secondary raw material for the LIB manufacturing. The compactness and low CAPEX of the plant makes CoReco the most competitive recycling solution on the market: the target Cost of Recovery (CoR) is < 1,200 €/ton (including CAPEX and OPEX), 30% less than competing solutions, making recycling industrially viable.

Keywords: cobalt recycling,spent li ion batteries,black mass,pyrometallurgy,hydrometallurgy,secondary raw materials,high purity metals
Revolutionary Non-Disruptive DDoS Testing Technology that significantly strengthens resistance to DDoS attacks and provides ongoing visibility on identified DDoS mitigation vulnerabilities. (DDoS Analyser)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Israel
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-06-01
End date: 2018-11-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Distributed Denial of Service (DDoS) is a form of cyber attack that makes a machine or network resource unavailable to its genuine users resulting in (i) downtime and (ii) a smokescreen for the introduction of viruses or other malware or to steal customer data. The effective downtime created by DDoS attacks is devastating for organisations that require reliable, non-stop (24/7) online availability – including telecommunication, mass transport, government voting systems, health systems, banking & financial institutions and e-commerce businesses. In 2016, the average effective downtime from each DDoS attack was 17 hours with an estimated average cost to companies of $250,000 (~€213,000) per hour . DDoS attacks are becoming easier to launch and the frequency, size and complexity of these attacks are increasing. Although DDoS attacks can be blocked using DDoS mitigation solutions, these solutions currently have limited effectivity. Effective and well aligned attack mitigation, on the dynamic systems run by organizations, requires continual DDoS testing. The challenge is that currently all DDoS testing technologies are themselves disruptive to the test environment – meaning that they are restricted to isolated tests at specific time points and require costly dedicated maintenance windows that limit the number of tests which can be performed. MazeBolt Technologies has developed the first ever Non-Disruptive (ND) DDoS testing technology that continuously simulates a wide variety of DDoS attacks without disrupting the tested environments. This offers a step change in the level of information and visibility on companies’ DDoS mitigation vulnerabilities. Our revolutionary DDoS Analyser runs exponentially more tests, continuously 24/7, with real time analysis of identified vulnerabilities.

Keywords: ddos,analyser,ddos analyser,ddos attack,distributed denial of service,mitigation,ddos mitigation,ddos testing,threat assessment,threat analysis,non disruptive testing,network validation
Distributed Intelligence and Technology for Traffic and Mobility Management (DIT4TraM)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: Research and Innovation actions
Countries involved: Israel,Germany,Spain,Cyprus,Switzerland,Switzerland,Greece,Greece,Belgium,Greece,France,France,Netherlands,Netherlands,Netherlands,Netherlands
Call: Network and traffic management for future mobility (H2020-MG-2020-TwoStages, 2020)
Start date: 2021-09-01
End date: 2024-08-31
Duration (months): 36.0
Total project cost (EUR): 4997171.36
EU funding (EUR): 4997122.0
Participants: 21
Project status: SIGNED

The transport sector is expected to alter shape in the coming decades. This transition is driven by user-centred mobility services, integrated and intelligent transport networks, pricing and payments, automation, safety and security, as well as public and private innovation. Next to Big Data and Artificial Intelligence, these developments provide major opportunities, but also increase system complexity. The overarching aim of DIT4TraM is to develop, implement and test a generic distributed control paradigm, applicable at the level of traffic operations, mobility management, demand-supply synchronisation and shared mobility, including advanced monitoring, estimation and (machine learning) forecasting technology, and associated algorithms for a variety of novel multi-modal management and mobility concepts operating at all urban scales. A holistic approach to decentralisation, distribution and mechanism design for monitoring and control is proposed aiming to achieve social optimality, yet with only necessary information exchanges, which is further translated into four key application fields corresponding to four interlaced urban scales carefully selected to ensure that all relevant challenges are tackled. Pilots in several cities across Europe are organised to test DIT4TraM concepts and assess market potential and design business models. Our vision is to support the transition to seamless and sustainable connected and autonomous mobility by disentangling the system components to the highest extent possible, yet ensuring sufficient cooperation and emergent coordination by smart system design, leading to liveability, safety, resilience, efficiency, as well as privacy, participation, fairness and sustainability on a city scale. The DIT4TraM partnership (4 Universities, 5 Industrial partners, 2 RTOs, 3 stakeholders), has been formed to address the combination of technical, organisational, and implementation challenges to develop and successfully test the proposed solution.

Keywords: distributed control,mobility services,machine learning,demand management
Bayesian markets for unverifiable truths (BayesianMarkets)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Individuals, Markets and Organisations
Panel description: Economics, finance and management
Countries involved: Netherlands
Call: ERC Starting Grant (ERC-2014-STG, 2014)
Start date: 2016-01-01
End date: 2020-12-31
Duration (months): 60.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: CLOSED

Subjective data play an increasing role in modern economics. For instance, new welfare measurements are based on people’s subjective assessments of their happiness or their life satisfaction. A problem of such measurements is that people have no incentives to tell the truth. To solve this problem and make those measurements incentive compatible, I will introduce a new market institution, called Bayesian markets. Imagine we ask people whether they are happy with their life. On Bayesian markets, they will trade an asset whose value is the proportion of people answering Yes. Only those answering Yes will have the right to buy the asset and those answering No the right to sell it. Bayesian updating implies that “Yes” agents predict a higher value of the asset than “No” agents do and, consequently, “Yes” agents want to buy it while “No” agents want to sell it. I will show that truth-telling is then the optimal strategy. Bayesian markets reward truth-telling the same way as prediction markets (betting markets) reward people for reporting their true subjective probabilities about observable events. Yet, unlike prediction markets, they do not require events to be objectively observable. Bayesian markets apply to any type of unverifiable truths, from one’s own happiness to beliefs about events that will never be observed. The present research program will first establish the theoretical foundations of Bayesian markets. It will then develop the proper methodology to implement them. Finally, it will disseminate the use of Bayesian markets via applications. The first application will demonstrate how degrees of expertise can be measured and will apply it to risks related to climate change and nuclear power plants. It will contribute to the political debate by shedding new light on what true experts think about these risks. The second application will provide the first incentivized measures of life satisfaction and happiness.

Keywords: expectations,subjective data,belief elicitation,subjective probabilities,prediction markets,scoring rules,bayesian truth serum,market design,experts
Investigation of interspecific pollen tube reception (INTERSPREC)

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: Switzerland
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-07-01
End date: 2020-06-30
Duration (months): 24.0
Total project cost (EUR): 175419.6
EU funding (EUR): 175419.6
Participants: 1
Project status: CLOSED

Cell-cell interaction mechanisms play a role in many fundamental biological processes from symbiotic interactions of fungi and bacteria with their host plants to fertilization both in animals and plants. In plant reproduction, pollen tube (PT) reception is a cell-cell communication process allowing the recognition of the male gametophyte (the PT) by the female gametophyte necessary for fertilization. To investigate this process, the host lab used interspecific crosses between certain Arabidopsis thaliana accessions and A.lyrata pollen, where most PTs are not recognized, causing a failure in sperm release and thus fertilization. In contrast, several other A.thaliana accessions almost perfectly recognize interspecific PTs. Preliminary results identified the gene At5g62150 as a key player for species-specific PT recognition. At5g62150 codes for a LysM-domain containing glycan-binding peptide, pointing at glycosylation patterns for the distinction of intra- and interspecific PTs, a mechanism already known to be important in symbiosis and immunity. It was found that differences in the regulation of At5g62150 in distinct species is responsible for recognition, as the amino acid sequence does not differ between A. thaliana other accessions. With this proposal, we will first attest and manipulate the expression profile of At5g62150 in different accessions to correlate its regulation with its function. Then, we propose to dissect the regulation of At5g62150 in different ways: identification and study of the essential cis-regulatory element for regulation and Y1H screening and Reverse ChIP to find trans-acting regulators. The output will not only pave the way for the understanding and manipulating crosses barriers in plants, which is highly relevant for plant breeding, and shed light on cell-cell communication processes in general, but also will establish a novel, powerful instrument (Reverse ChIP) to investigate DNA-protein interaction in complex organisms.
A New Adjuvant Nutraceutical from the North Atlantic Ocean for Breast, Lung and Pancreatic Cancer Patients (Simecos)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Iceland
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2018)
Start date: 2018-02-01
End date: 2020-07-31
Duration (months): 30.0
Total project cost (EUR): 2180387.5
EU funding (EUR): 1526271.25
Participants: 1
Project status: CLOSED

Genis is based in Siglufjördur, a village in the North Iceland traditionally focused on the fishing industry. After the fishery crisis worsen in 2008, Siglufjördur started to pay attention to the marine biotechnology, with Genis at the forefront. Hence, since 2002, we develop health products based in T-ChOS™ (Therapeutic Chitooligosaccharides), which are compounds obtained from chitin extracted from the North Atlantic shrimp exoskeleton. T-ChOS™ show a strong anti-inflammatory effect based in a novel biological pathway discovered by Genis: Inhibition of the YKL-40 chitinase enzyme, whose levels are very high in several diseases as cancer. Our in vitro, in vivo and human studies prove that T-ChOS™ can decrease inflammation and enhance tumour response to chemotherapy. During the Ph1 project, we confirmed the feasibility of developing a nutraceutical based on T-ChOS™ to use as an adjuvant to chemotherapy in cancer patients. In this Ph2 project, we aim to optimise manufacturing, validate through a clinical trial and bring to market SIMECOS: A nutraceutical for cancer patients derived from chitin purified T-ChOS™ molecules. SIMECOS targets lung, breast and pancreatic cancer patients, with survival rates after 5-year of 20%, 82.2% and 5.2%, respectively. SIMECOS is expected to increase their quality of life, thanks to its proven effects to decrease pain and fatigue. The high trends (30%-95%) among cancer patients to use complementary supplements entail a great business opportunity for SIMECOS as in Europe, there are more than 780,000 patients per year diagnosed with breast, pancreatic and lung cancer looking for solutions to decrease chemotherapy side effects and improve the effectiveness of their treatment. Clinically validated SIMECOS will help these patients. We expect SIMECOS to reach the market in 2020. By 2024, after our European expansion, SIMECOS will give a profit of €10.45M and considering a Phase 2 budget of €2.18M, the return-on-investment (ROI) will be 9.9

Keywords: chitin derived olygosacharides,inflammation,cancer coadyuvant,ykl 40
ENHANCing Human Performance in Complex Socio-Technical SystEms (ENHANCE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Germany,Italy,Germany,China,Norway,Malaysia,Norway,United Kingdom,Pakistan
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2018, 2018)
Start date: 2019-02-01
End date: 2024-11-30
Duration (months): 70.0
Total project cost (EUR): 1099400.0
EU funding (EUR): 961400.0
Participants: 10
Project status: SIGNED

Rapid technological development within the maritime industry has improved efficiency, productivity and safety. However, this advancement is creating increasingly complex socio-technical systems, for which training has left human operators ill-prepared. Over 75% of all maritime accidents are attributed to human error, and smaller crew are handling more complex tasks. If safety is to be maintained or improved, it is vital to equip crew with the skills needed to manage them effectively. ENHANCE specifically investigates these issues for maritime applications by utilizing knowledge sharing between process and maritime industries. We will bring together the expertise of engineers, psychologists, human factors specialists and operators to generate solutions to cope with technological development. The project has two main objectives: a) to better understand the human role in complex socio-technical systems through close collaborations between the academic and non-academic sectors; and b) to develop new training and performance assessment methodologies designed to enhance the human performance. To ensure knowledge transfer, ENHANCE will connect academics and industry through an extensive secondment programme. This will bring together expert academic knowledge of advanced training techniques with the needs of the maritime industry and the best practice of the process industry. We will share knowledge across academia and industry, across sectors and across continents. Ultimately, this research will enable the maritime sector to improve the performance of humans within their complex socio-technical systems. This, in turn, will reduce the frequency and severity of incidents, reducing the negative social, economic and environmental impact of the sector. In addressing the needs of the maritime industry, we will also generate new cross disciplinary research initiatives, new career paths for researchers and new opportunities for long-term industry-academia collaboration.

Keywords: operator,seafarer training,performance assessment,system safety,training simulators,performance improvement
Ligand Directed NIR-based Theranostic Prodrugs for Prostate Cancer (ClickandTreatCancer)

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: Chemistry
Countries involved: Portugal
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-04-01
End date: 2022-03-31
Duration (months): 24.0
Total project cost (EUR): 159815.04
EU funding (EUR): 159815.04
Participants: 1
Project status: CLOSED

Cancer remains one of the leading causes of mortality worldwide. Prostate cancer (PC) is currently the most common male malignancy and remains the leading cause of death. Despite advances in chemotherapy, current strategies still carry severe side effects and offer limited benefit to the patient. Two main reasons behind these limitations include 1) non-specific delivery of anticancer drug to the target tissue and 2) poor diagnosis at an early stage of the disease. Thus, there is an urgent need for a novel and modular theranostic platform to deliver drugs selectively to cancer tissues and simultaneously follow therapeutic efficacy through non-invasive imaging techniques. Herein we propose a DT-diaphorase activated, DUPA guided NIR-based theranostic strategy to deliver anticancer drug selectively to prostate cancer cells while monitoring in real-time drug release and efficacy in vivo. The developing tool is novel and modular, enabling the use of various triggers, drugs and targeting agents. The fluorophore signal is expected to fall in the NIR region (>600 nm) and the scaffold with enable as real-time monitoring of drug release in vivo, as well as the introduction of targeting groups in order to improve the specificity of the theranostic agents towards cancer cells. The development of this technology can provide an invaluable platform that can be easily adapted for the treatment of different cancer types. It is likely that the directness and modularity of this novel approach will have a strong impact in the field of targeted drug-delivery for treating and monitoring in real-time drug effectiveness.

Keywords: theranostic prodrugs,targeted therapeutics,nir probe,prostate cancer,pmsa,dupa,dt diaphorase