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Identifying diatom regulatory long noncoding (lnc)RNAs for increased biomass production for biorefinery applications – DiaLincs
Diatoms are very promising organisms for biofuel production since they can produce high quantities of lipids when nutrient depleted. We hypothesize that diatom lncRNAs expressed under nutrient stress are likely to be major players in the pathways regulating energy and biomass production which is supported by preliminary data.
Multi-principal-element Alloys as Solid Stores for HYdrogen – MASSHY
Multi-principal-element Alloys as Solid Stores for HYdrogen
Hydrogen molecular ions for precision physics – HYMPE
Molecular hydrogen ions H2+ or HD+ are sufficiently simple quantum systems to allow comparisons between theory and experiment at an extraordinary level of accuracy. This makes possible a better determination of some fundamental constants, but also the search for new effects beyond the standard model of particle physics.
Multi-redox porous crystalline hybrid chalcogenides – THIOMOFS
Advanced synthesis and characterization of new organic-inorganic chalcogenides, combining porosity, electronic conductivity and multiple redox activity
Photon-Atom Cooperative Effects at Interfaces – PACE-IN
The overall objective of this proposal is to meet the critical challenge of studying, implementing and optimizing ground-breaking, dynamically-controlled interfaces between matter and light.
Decentralized Knowledge Graphs – DeKaloG
Knowledge Graphs (KGs) penetrate our everyday life, telling us what to buy, what to learn, etc. Major companies maintain Knowledge Graphs to power voice assistants and search engines. However, access to these KGs is restricted and the way they are built and maintained is not transparent. This restricted access and the lack of transparency do not allow to build new KGs or to build on top of them. DeKaloG encourages the growth of a public and decentralized web of Knowledge Graphs.
Modulating the gene networks underlying phenotypic robustness in plant quantitative immunity – PRobIty
Quantitative disease resistance (QDR) is a form of plant immunity involving complex molecular bases poorly characterized. It is widespread in nature and the only form of effective immunity against necrotrophic pathogens such as the white mold fungus Sclerotinia sclerotiorum. Empirical studies highlighted that QDR is often broad spectrum and durable. The architecture of genetic networks underlying the robustness of the QDR phenotype is currently unknown.
Planning and Learning to Act in Systems of Multiple Agents – plasma
The main idea presented in this proposal is that it is possible to reduce a multi-agent decision-making problem (such as a partially observable stochastic game) to a fully observable stochastic game, which is solved using generic algorithms based on recent advances in Artificial Intelligence. We focus on generic methods with theoretical guarantees since they are of particular interest in safety-critical systems that can affect human lives.
Genetic traits required by bacterial phytopathogens for plant infection and fitness in non agricultural habitats using high-throughput transposon sequencing (Tn-seq) – TNPHYTO
Bacteria of plant pathogenic species can be isolated from various environments such as soil, water or healthy wild plants. We propose to work on strains of phytopathogenic bacteria isolated from the environment to identify the genetic determinants enabling their growth and survival in plants but also in an environmental substrate, river water, a major vector of dissemination.
Cavity-enhanced optical frequency comb spectroscopy for astrophysics – CECoSA
The aim of the CECoSA project is to combine cavity-enhanced spectroscopy based on optical frequency combs with uniform supersonic flows and time-resolved detection to detect the spectral signatures of molecules and radicals at low temperatures
