Dragon09/odtu_chatbot huggingface dataset:
highly efficient super critical zero emission energy system

wind and sun will be central energy sources of a climate neutral europe 2050 bringing with them the need to balance weather dependent differences between supply and load conventional gas turbines can fulfill this task also for longer periods even well as they can stabilize the grid with their capability of quick startstop however their efficiency is limited and even if burning climate neutral hydrocarbons they still produce local emissions hermes overcomes these limitations and advances gas turbine technology to the futureproof level by creating a reliable flexible zeroemission solution for energy supply with long term impact at eu levelhermes develops and assesses the first highly efficient closedloop supercritical zero emission energy system it is based on directly fired supercritical gas turbine engine operating on locally synthesized renewable liquid and gaseous fuels eg methanol or hydrogen coupled with decentralized carbon capture utilization and storage ccus the carrier medium is highly dense supercritical carbon dioxide or xenon demanding less compression power therefore and because of operating at high pressure conditions above 150 bar the system achieves significantly higher efficiency above 65 than todays gas turbines by utilizing pure oxygen for fuel oxidation and by capturing bulky flow of exhaust products h2o andor co2 and reusing them for fuel synthesis the system produces virtually no pollutants a detailed assessment of the hermes approach will be done using experimental and computational approaches and dynamic simulation tools including digital twins and machine learning the 36month project will be realized by an 11partner consortium including 3 smes with expertise in renewable energy combustion technoeconomics and sociopolitical science hermes will pave the way to a major breakthrough in the understanding of fundamentals of combustion in supercritical fluids with zero emission of any pollutants
european startup nations alliance

the time is now to bring europe to the forefront of the global startup ecosystem in order to boost societal health and wealth and increase economic growth especially in this period of recovery following the covid19 global pandemic the world will not be the same again and europe has a fantastic opportunity to become a global leader in the world of tomorrow if it manages to convert its potential as a continent of innovators pioneers and entrepreneurs into a competitive well organized and coordinated ecosystem of startups for that europe must establish the best framework conditions that can help the most promising and strategic startups stay and flourish in europe and grow to compete globallythe signature of the eu startup nations standard declaration in march 2021 as a formal commitment of 27 european countries to enhance these framework conditions through the adoption of best practices and now the creation of the europe startup nations alliance esna as a new startup nations hub to coordinate support and monitor national progresses towards this process are the two key elements of this european policy the present proposal is focused on establishment of esna with the mission to accelerate the growth of european entrepreneurship by improving national policy frameworks of the esna member countries on the common standards agreed upon in the startup nations standard declaration and to continuously identify and develop best practices into deployable policies based on analysis of data gathered from members on a digital platform providing up to date key information of the
light on our dark past elucidating the deep archaeal roots of eukaryotic cellular complexity

the origin of the eukaryotic cell with its complex and compartmentalized features represents a prime hallmark in the evolution of life on earth yet important details underpinning the emergence of cellular complexity of eukaryotic cells remain thus far unresolved current views support evolutionary scenarios in which the first eukaryotic evolved via a merger between an archaeal host cell and one or more bacterial endosymbionts recent phylogenomic work from my lab has shown that the archaeal host cell evolved from within the asgard archaea an archaeal clade uniquely displaying several eukaryotelike features however key aspects regarding the nature and biology of the archaeal host cell remain elusive limiting our current understanding of the early stages of eukaryogenesis in darkroots my team will capitalize upon our unique position and foundational results and use complementary approaches to elucidate the emergence of complex cellular features during eukaryogenesis firstly building on encouraging preliminary results we will use an advanced anaerobic cultivation infrastructure to enrich diverse asgard archaeal lineages next we will use highresolution and live microscopy approaches to study their cellular ultrastructures and cell biological properties furthermore we will monetize on recent breakthroughs in structural biology and use aiguided structural genomics to uncover new eukaryotic signature proteins in asgard archaea finally we will trace the evolution of asgard archaeal proteins focusing on homologs of proteins that give stature to the complex and compartmentalized nature in eukaryotic cells altogether building on a rich foundation of preliminary results my group will bring new pieces of the enigmatic eukaryogenesis puzzle to the table by elucidating how intracellular complexity arose during the prokaryotetoeukaryote transition
building a comprehensive burden sharing framework to inform on an equitable implementation of the paris agreement

methodologies for assessing the ambition of national climate pledges are in theory guiding international negotiations processes under the un to this end pledges are compared to national emissions scenarios that represent an equitable share of the global scenarios and of the effort they require to achieve the paris agreement goals these equitable national emissions scenarios do not yet inform how they can be achieved through a combination domestic action and international cooperation though transfers of mitigation outcomes as discussions move beyond pledges into action informing subnational emissions objectives and international finance in line with the paris agreement and its equity principle can help implement mitigation globallyinternationally global socioeconomic scenarios inform the costoptimal geographic distribution of mitigation effort hypothesising sufficient finance equitybased scenarios provide the total effort that each actor should provide possibly through international support the difference between the scenario sets represents international finance that developed countries can use to fund part of their fair share in developing countries subnationally state and city governments often aspire to deliver mitigation beyond their fair shares of the national targets and align with the paris agreement goal a multilevel quantitative ambition assessment framework can serve as a basis to discuss the respective roles and efforts of subnational governments as part of a country or of subnational alliancesthis project seeks to quantify 1 subnational emissions trajectories consistent with the paris agreement goals and 2 the international emissions mitigation support that each country can receive or provide to fulfil its equitable emissions scenario costoptimally the goal is to provide the most comprehensive and unified peerreviewed climate ambition assessment framework to inform climate negotiations and ipcc reports
unveiling the functional outcome of single nucleotide polymorphisms and variants in oligodendroglia in multiple sclerosis

multiple sclerosis ms is a neurological disease characterized by autoimmune attack targeting oligodendroglia olg in the central nervous system cns and in particular their myelin which ensheaths neuronal axons genomewide association studies gwas have led to the identification of hundreds of singlenucleotide polymorphisms snps and variants that are associated with ms risk many of these are located near genes associated with immune cells indicating a key role for these cells in ms using singlecell omics approaches we recently found that olg present chromatin accessibility or express genes associated with some of these snpsvariants both in health and disease here we hypothesize that olg have a more active role in ms than previously anticipated and therefore we will determine the function of ms snpsvariants in olg in the context of ms using humanized mouse models patient samples and new singlecell omics techniques recently developed in my group we will 1 characterize indepth the transcriptomic and epigenomic landscape of human and mouse olg in the context of ms to identify putative genes affected by the snpsvariants 2 perform crisprguided editing of a cohort of the identified snpsvariants in human olg and determine the consequences of the editing at a an epigenomic and transcriptional level linking specific snpsvariants to their bonafide target genes and b a functional level by performing an array of functional assays targeting myelination cell survival and immune function both in vitro and in humanized mouse chimeras in which engineered human olg have been transplanted we will use singlecell and spatial omics technologies such as nanocuttag and spatial cuttag among others which we have recently developed in my research group the results of this project will yield unique insights into the role of olg and the identified snpsvariants in ms and thereby pave the way to novel therapeutic avenues for this disease
exsolutionbased nanoparticles for lowest cost green hydrogen via electrolysis

todays alkaline electrolysers favour current densities over efficiency to achieve commercially relevant current densities these systems typically operate at voltages exceeding 2 vcell corresponding to electrolyser power consumption of 54 kwhkg there are four reasons for employing high voltages 1 electrodes insufficient electrochemical activity 2 the relatively high gas permeability of commonly employed diaphragms means that improved hydrogen purity can be achieved at high current operation points 3 the stack designs are not optimised for lowcurrent operation due to very simple flow fields and 4 high currents are required to achieve attractive electrolyser capex costs eurkw yet there is a growing consensus that the wider adoption of green h2 is not hindered by electrolyser capex the costs of green h2 are in most cases vastly dominated by opex which in turn is a direct function of electrolyser efficiency thus to achieve lowest possible levelised cost of h2 efficiency should be prioritised over current densityexsothyc will optimise electrolyser operation towards lower voltages and higher efficiencies the innovation is threefold and addressing all four abovementioned reasonsalternative pathways to the o2 and h2 evolution reactions by new anode and cathode approachesnovel concepts of membrane electrode assemblies with integrated components novel cell design to enhance overall cell efficiency by integrating disruptive conceptsin the project we adopt an approach combining computer simulations rapid prototyping and thorough experimental validation on single cell sru and short stack level in a nutshell we will combine electrodes made using powder metallurgy with ceramic nanoparticles fabricated by exsolution leveraging on the synergy that both methods require reducing atmospheres also membraneelectrode assemblies based on zirfon will be developed the cellstack will be backed by computer modelling
trusted ai for transparent public governance fostering democratic values

ai4gov is a joint effort of policy makers public institutions organizations legal social science and humanities and big dataai experts to unveil the potentials of artificial intelligence ai and big data technologies for developing evidencebased innovations policies and policy recommendations to harness the public sphere political power and economic power for democratic purposes the project will also uphold fundamental rights and values standards of individuals when using ai and big data technologies hence the project aims to contribute to the promising research landscape that seeks to address ethical trust discrimination and bias issues by providing an indepth analysis and solutions addressing the challenges that various stakeholders in modern democracies are faced with when attempts are made to mitigate the negative implications of big data and ai in this direction the project will introduce solutions and frameworks towards a twofold sense to facilitate policymakers on the development of automated educated and evidencebased decisions and to increase the trust of citizens in the democratic processes and institutions moreover the project will leverage the capabilities of stateoftheart tools for providing unbias discriminationfree fair and trusted ai these tools will be validated in terms of their ability to provide technical andor organisational measures causal models for bias and discrimination and standardized methodologies for achieving fairness in ai
fastml efficient and costeffective distributed machine learning

deep learning is an area of massive progress with myriad applications and significant industry adoption a key enabler of its progress is the ability to train large highlyaccurate deep neural networks dnns in a distributed fashion across tens to thousands of different computational nodes yet dnn training at scale poses severe challenges to standard paradigms in distributed computing existing distributed training approaches and their practical implementations via training libraries such as pytorch or tensorflow often suffer from major distribution bottlenecks which can significantly reduce computational efficiency leading to wasted time money and energythe fastml proofofconcept poc project will tackle this efficiency challenge headon by introducing a distributed training framework that will significantly reduce or even eliminate the overheads of parallelization for practical distributed training workloads in common usage scenarios fastmls distinctive feature is leveraging the algorithmic and software techniques developed by our erc starting grant in order to reduce distribution overheads at scale without impacting training convergence or model accuracy fastml stands in contrast to current distribution techniques which rely on hardware overprovisioningessentially providing very fast but also very expensive interconnects between the computing nodes as such fastml can bring significant infrastructure and running cost improvements to its users as well as lowering the cost and hardware entry barrier to training accurate machine learning models the poc will design and develop the fastml software library to target industryrelevant workloads via pilot projects jointly with our industrial partners in addition we will perform an indepth market study devise intellectual property and gotomarket strategies and produce a minimallyviable product mvp which will be demonstrated to potential customers and investors
overcoming barriers and efficiency limitations in secure computation

over the past few decades our use of networks such as the internet underwent a complete transformation the data that we send over the network is now routinely used in computations by third parties this creates a considerable threat to our privacy as we witness countless data breaches and companies selling our private datathe aim of secure computation is to solve this problem it studies the design of methods for computing on sensitive data without compromising confidentiality secure computation has been firmly established as one of the most promising approaches to reconcile the use of datadriven algorithms with the necessity of protecting our privacy it has spurred a considerable research effort in the past decade which has witnessed the emergence of new models such as the models of secure computation with silent preprocessing introduced by the pi and of noninteractive secure computationwhile these silent and noninteractive features are fundamental for the deployment of secure computation over large networks current protocols suffer from important downsides which make them entirely impractical in realworld scenarios they scale poorly with the number of participants and cannot be used over mid to largesize networks they either require many rounds of interaction hence are impractical over highlatency networks or trade noninteractivity for huge computational costs they induce a large communication overhead compared to executing the computation on the clear data they are often based on exotic cryptographic assumptions whose security is not yet wellunderstoodthe aim of the project obelisc is to explore the current limits of silent and noninteractive protocols and to introduce new methods for overcoming the remaining barriers the longterm vision of the project is to enable the deployment of a largescale network that further protects our sensitive data whenever it is used in distributed computation
computational imaging through scattering materials using speckle correlation

when viewed under coherent imaging conditions eg laser illumination scattering materials such as biological tissues create noiselike images known as speckle despite their seemingly random nature speckle patterns have strong statistical correlation properties that are highly informative of the material producing them these can be used to enable remarkable imaging capabilities not possible with current state of the art for example seeing through highly scattering layersunfortunately realizing these in practical settings tissue imaging fluorescence microscopy remains a challenge research efforts are hindered by a lack of modeling tools resulting in an incomplete understanding of speckle propertiesthis project aims to use computational techniques from computer vision and computer graphics to greatly enhance our understanding of speckle statistics and significantly expand the scope of their applicationsto this end the project will explore algorithmic tools newlydeveloped by the pi that can accurately and efficiently simulate speckle patterns to formulate better models of speckle formationwe will exploit our new understanding to develop new types of computational imaging systems that can directly measure speckle correlation rather than the traditional pipeline where one captures speckle images and estimates their correlations algorithmically in postprocessingfinally we will exploit these tools in multiple computational imaging applications including i acquiring material parameters estimating the type size and density of particles composing a material of interest ii imaging fluorescent sources deep inside scattering tissue iii adaptive optics imagingpotential impact is anticipated in numerous areas where specklebased imaging techniques hold promise including medicine increased depth penetration of tissue imaging techniques and material fabrication and analysis accurate characterization of scattering materials
revolutionizing mirror technology to discover the dark universe

the first detection of gravitational waves and in particular the observation of merging black holes which otherwise appear dark has been one of the most exciting scientific achievements of the last decades with the next generation of even more sensitive detectors we plan to be able to see gravitational waves from objects as far away as the edge of the observable universe however a major limitation to the sensitivity of these detectors is the thermal noise of their core components the highlyreflective coated interferometer mirrorsthe use of cryogenic temperatures will be a major step forward in thermalnoise reduction however with current coating technology the sensitivity goals of next generation detectors cannot be met not to mention further upgrades or future detector generations a all amorphous coating materials identified so far with low thermal noise at low temperatures show too high optical absorption b singlecrystalline coatings can show both low thermal noise and low absorption but come with different obstacles such as limitations on the size and material combinations or different noise mechanisms eg from bonding the coating to the mirror i plan to explore a completely new path to realize coatingfree mirrors the use of ion implantation to create a highlyreflective multilayer structure directly inside the silicon mirror substrate my main hypothesis is that the implantation procedure preserves the excellent optical and thermalnoise properties of crystalline materials which cannot be met by amorphous coatings while not imposing the limitations of singlecrystalline coatings a successful realization of such mirrors will solve the coating thermal noise issue in gravitationalwave detection entirely allowing for an unhindered view into the universe
xray spectroscopy of molecular chirality in solutions

the purpose of this proposal is to implement xray circular and helical dichroism to investigate the structure and chemical dynamics of molecular systems in solution the proposal entails first establishing the concepts and observables of xray dichroism in steadystate studies both in the soft and hard xray ranges and then implementing timeresolved xray circular and helical dichroism spectroscopies as probes of the chemical dynamics
interplay of structures in conformal and universal random geometry

my overall goal is to provide novel conceptual understanding of persistent challenges in mathematical physics in light of recent discoveries of myself and others the emphasis is especially in finding connections between different areas making use of my expertise at their crossroads the first two aims concern statistical mechanics sm and mathematical formulations of logarithmic conformal field theory cft on the one hand algebraically and on the other hand probabilistically the last two aims focus on connections and interplay of structures arising in sm such as schrammloewner evolutions sle with algebrogeometric formulations of cft gaining conceptual understanding is fundamental for progress towards deep results specifically in aim 1 i focus on cft correlation functions and plan to reveal nonsemisimple and logarithmic behavior poorly understood even in the physics literature for this eg hidden symmetries from my earlier work will be exploited aim 2 combines this with probability theory investigations of nonlocal quantities in critical sm models relating to specific cft correlation functions and to sle in aim 3 i investigate the interplay of sle cft and teichmueller theory in terms of generalizations of socalled loewner energy of curves the main objective is to shed light on the hidden geometric interpretation of loewner energy from the point of view of formulations of cft in terms of riemann surfaces and eventually also to find its role within geometric quantization to elaborate the latter goal aim 4 combines these ideas with related structures in the theory of isomonodromic deformations my starting point is the observation that loewner energy minima and semiclassical limits of certain cft correlations are both described by isomonodromic systems i plan to make these connections explicit and implement them in order to discover intrinsic features of the interplay of the aforementioned structures