Dragon09/odtu_chatbot huggingface dataset:
hybrid dryhot extremes prediction and adaptation

half a million people die due to heat stress every year these numbers keep rising as climate continues to change heatwaves are becoming more frequent and severe and disproportionally synchronised with droughts droughts reduce the ability of the land surface to cool down via evaporation further enhancing heatwave temperatures nonetheless how these compound droughtheatwave events spatially propagate and their future lethality remains unclear counterintuitive findings now indicate that drought can even dampen heatwave deadliness by reducing air humidityconsequently our ability to forecast dryhot events and their impacts on human health remains limited subseasonal timescales between two weeks and two months have traditionally been a blind spot conventional weather forecast models are not tailored to these scales however the adoption of artificial intelligence ai may hold the key to fill this gap and reliably predict the upcoming occurrence of heat stress episodes weeks in advance this would bring enormous societal benefits by enabling emergency planning in this project we will explore an innovative way to generate subseasonal forecasts of droughts and heatwaves and their consequent human heat stress episodes a hybrid approach will be embraced ie an approach based on physicsbased models combined with ai algorithms building upon this approach we will deepen our understanding of the climatic drivers of human heat stress and explore the future benefits of landbased adaptation practices designed to attenuate these events including afforestation crop selection and largescale irrigation altogether heat will foster our preparedness and resilience to future heat stress episodes by improving their prediction investigating the mechanisms that trigger them globally and providing realistic and effective landadaptation strategies to mitigate them while heralding the adoption of hybrid approaches in climate science
circular valorisation of industrial algae waste streams into highvalue products to foster future sustainable blue biorefineries in europe

algae biomass is highly underexploited and its efficient utilization is one of the main challenges in current and future eu marine policies towards sustainability circalgae will boost the blue bioeconomy by applying an integrated biorefinery concept to valorise the massively produced over 36 mt of algae biomass annual world production and vastly underexploited algae industrial waste streams which can add up to 95 of the initial biomass from the main existing sources to date the phycolloid production from macroalgae and proteinlipid microalgae industries circalgaes simple waterbased technologies will transform these waste streams into valueadded ingredients to be used in specific texturized vegan foods healthpromoting food ingredients protein rich feed and cosmetic formulations incorporating texturizing or highly bioactive ingredients for topical use 3 blue biorefinery schemes upscaled to hundreds of kg will be demonstrated throughout circalgae project 12 demonstrator products will be developed by food feed and cosmetic industry partners validating the great potential of novel algae ingredients in these key sectors additionally 2 final products will be qualified for market including their studies in consumer acceptance assessments through cocreating and colearning circalgae will connect all algae crosssectional actors including industrial enduser partners rtos technological and consultancy smes for the validation of all healthpromoting effects and claims regulatory aspects and environmental economic and social impacts engaging all relevant stakeholders in the primary sector to reshape the current industrial network for a future thriving blue bioeconomy
recognition and acknowledgement of injustice to strengthen equality

recognition and acknowledgement of injustice to strengthen equality raisestructural racism exists because of social constructions of group demarcations such boundary making processes are at the root of both structural and individual xenophobia and racism this project therefore first aims to empirically map boundary making processes in peoples everyday life institutional contexts second the project aims to provide empirical evidence in what actions as a response of boundary making processes will support equality raise draws on the assumption that to reduce structural racism people and the institutions they operate in have to be aware of these underlying boundary making processes that reproduce structural racism and the role it has in lasting inequalities recognition and acknowledgment of these forms of injustice will contribute to social action for equality the project will be the first in europe to study the awareness of boundary making processes in reproducing structural racism and what collective actions contribute to break through such boundary making processes to reduce structural racismby taking an interdisciplinary approach from theologists big data scientists social psychologists geographers political scientists economists and sociologists and by creation of research in collaboration between ngos that address racism and xenophobia operating in precarious contexts ngos from hungary poland and turkey and academics this project is at the front of generating new insights on structural racism in europe
triboelectric nanogenerators printed from composite inks for energy harvesting

triboelectric nanogenerators have recently emerged as a very promising energy harvesting technique for transforming mechanical energy into electrical energy their emergence is especially timely as the world undergoes a sustainable energy revolution and these devices have successfully demonstrated energy harvesting from a vast range of applications from wind to wave to wearable textiles importantly they can also be fabricated from common materials such as paper polymers and graphite however as most highly triboelectric materials are polymeric they suffer from low currents and brittleness under friction with high performances usually only achieved using complex materials with a large number of processing stages these are major challenges that are preventing the widespread and longterm application of these devices this project will simultaneously address all of these issues by developing a printable polymeric composite containing 1d carbon nanotubes to improve both mechanical strength electrical conduction and 2d nanosheets of molybdenum disulphide to improve the charge retention operation lifetime which in combination with a paperbased tribopositive layer will form the basis of a lowcost high performance robust triboelectric nanogenerator crucially as this composite will be printable it will be compatible with scalable processes such as rolltoroll or flexographic printing success here will be achieved by combining the applicants expertise on printable nanomaterials with the supervisors knowledge and background on triboelectric generation and energystorage devices we will also demonstrate the practical utility of these devices by printing a device capable of harvesting energy from a bicycle tyre under cycling conditions the creation of an optimised ink in combination with additive manufacturing techniques means we will be easily able to print devices that can ultimately be integrated into a wide range of harvesting applications
sustainable decarbonised vanadium titanium and iron extraction from europes lowgrade vanadiumbearing titanomagnetite deposits

the ecs critical raw materials crm act sets multiple benchmarks for reducing europes dependency on a few unlikeminded third countries for strategiccritical raw materials through the domestic extraction of two crms vanadium v and titanium metal ti metal avantis addresses the first target of the act 10 domestic extraction for v ti avantis rationale lies in the fact that europe has a multitude of unexploited lowgrade vbearing titanomagnetite deposits in finland sweden greenland norway poland ukraine however these deposits have a complex spiderweblike mineral assemblage without selective blasting selective fragmentation and preconcentration technologies to separate the tirich ilmenite grains from the vbearing magnetite it is uneconomic to exploit these deposits supported by a bespoke forensic geometallurgy approach avantis develops a novel selective blasting approach that allows for rock excavation in view of increased mineral liberation at the blasting stage and reduced energy demand in the crushing grinding stages likewise avantis designs tailored waterfree and waterlean preconcentration technologies that allow to produce two distinct preconcentrates 1 ilmeniterich tipreconcentrate and 2 ilmenitefree vpreconcentrate the waterlean method is also tailored to process vtibearing mining wastes from historicalongoing operations the resulting flowsheets have a low net water consumption 70 water recycling and reduced ghg intensity of extraction reduction of 60700 g co2eq per t ore hauled to the crushing plant a preliminary analysis of the potential european reserves that are unlocked yields a total of 154 mt ti 35 mt v still excluding ukraine to be compared with current levels of eu consumption 15 mty ti 127 kty v avantis strengthens the responsible mining in europeparadigm increasing societys trust in domestic crm production
targeting kidney fibrosis by a novel myofibroblast specific small molecule inhibitor

chronic kidney disease ckd is a progressive disease that is prevalent in 10 of the developed world and develops as a result of diabetes mellitus hypertension glomerulonephritis or acute kidney injury over time ckd can progress to endstage renal disease esrd a condition that can only be treated through hemodialysis or kidney transplantation posing a severe medical societal and economic challenge fibrosis is recognized as a key pathological mechanism in ckd responsible for slowly destroying the tissue architecture of the kidney current therapies for ckd alleviate symptoms of the disease by controlling hypertension and hyperglycemia but while fibrosis is as a promising therapeutic target no antifibrotic therapy for the kidney have reached the clinic hence there is an urgent need for diseasemodifying and curative treatments that can halt fibrosis in fibrotarg we will assess the technical and commercial feasibility of fibrolisine a firstofitskind antifibrotic drug candidate for the treatment of ckd our preliminary data has confirmed a unique expression profile of our therapeutic target and reduced fibrosis onset in in vivo knockout models without sideeffects after kidney injury hence fibrolisine is expected to target the process of fibrogenesis and halt the progression to esrd in earlystage ckd patients through the activities in fibrotarg project we aim to demonstrate the antifibrotic potential of fibrolisine in advanced human kidney fibrosis organoid models and in vivo models of kidney injury concurrently we will investigate the commercial potential of fibrolisine by analyzing the commercial landscape and develop an initial commercialization strategy
formalizing verifying and applying isa security guarantees as universal contracts

the instruction set architecture isa is the interface that processor hardware offers to software developers current isas do not explicitly specify the security properties guaranteed by that interface so that for example recent severe microarchitectural sidechannel vulnerabilities like spectre did not even violate the specifications this project proposes a fundamentally new approach to specify isa security properties by using what we call universal contracts these are formal contracts in a compositional program logic that automatically hold for arbitrary code such contracts capture isaenforced upper bounds on the effects of arbitrary even attackercontrolled software while this approach is widely different from traditional specifications the approach looks extremely promising universal contracts can be applied to general security primitives mechanically verified against the isas operational semantics and they make it possible to obtain fullsystem security proofs by manually verifying only the trusted code of a sytemin this project we will contribute reusable techniques and tools for applying universal contracts in realistic isas to this end we will 1 design prove and evaluate universal contracts for isas with stateofpractice security primitives 2 develop semiautomation machinery for verifying universal contracts of isas 3 extend universal contracts to deal with semantic complications like concurrency or microarchitectural sidechannels and 4 design implement and evaluate techniques which facilitate the construction of trusted software that relies on universal contracts particularly assemblylevel reasoning support and secure compilers if successful the project has the potential to fundamentally improve the security foundations of all softwarebased systems by 1 clearly dividing the security responsibilities between hardware and software developers and 2 enabling scalable rigorous fullsystem security proofs
aipowered early warning and surveillance system to identify the risks within the food supply chain

a product recall is the process of retrieving defective andor potentially unsafe goods from consumers it is the result of safety concerns over a manufacturing defect in a product that may harm its user it can tarnish a companys reputation leading to multibillion euros in losses for small companies it may lead to the end of their operation because they operate without robust cash flow and brand recognitionin the fb category mycotoxins pathogen contamination and pesticide residues are the most common reasons alone in 2021 there has been a yoy increase of 19 in the global recallsicomplai helps companies assess monitor and predict product risks worldwide for consumer goods with a focus on food icomplai provides services in the area of product benchmarking and virtual testing helping companies better assess the risks and opportunities for their products as well as what the customers like and dislikeicomplai solution differentiates itself through deep analysis on product features helping companies understand the preferences of the consumers for instance in regard to sensorik packaging specifications or microbiological quality of the products this platform helps manufacturers assess monitor and predict the risks of their products and supply chain it is currently focused on foodicomplai platform is intended as an early warning system to help food manufacturers bring safe products to the market the platform is updated daily with new information which is fed into the machine learning algorithm the results are then sent to the users based on their customisation the daily alerts include both the current as well as the future potential risks
intelligent and selfadaptive decision support system for optimization considering sustainable value creation and lifecycle approaches in shipping

despite its growth the shipping sectors sustainability transition lags compared to other sectors if left unchecked a 90130 increase in emissions by 2050 is forecasted with significant socioeconomic impacts though regulatory changes are emerging many criticize them for their narrow scope and lack of ambition lacking a clear approach that embodies ocean air and marine ecology preservation nereusshipping aims to develop a comprehensive and selflearning decision support system dss based on sustainability circularity and risk metrics following a lifecycle approach to highlight how shortterm operational decisions can affect the longterm sustainability of the vessel using the proposed tool stakeholders will be able to obtain vesselspecific suggestions for risk reduction considering environmental social and commercial goals nereusshipping stands out for its novel approach of integrating tools that were up till now employed in silos within a novel dynamic framework to offer a practical and costefficient solution that combines lifecycle assessment data analytics risk mapping and realtime data this tool will become an effective dss for identifying sustainability and circularity opportunities while its dynamic nature will allow updating of the metrics using vessel performance and supply chain dataunder this msca program the fellow will join one of europes most advanced teams on environmental engineering and circular economy national technical university of athens with further complimentary training in two other eu academic institutes technical university of crete and technical university of denmark and collaborate with industrial partners during the project the fellow will gain knowledge on sustainability risk modelling decision making cyberphysical systems and digital tools while also expanding his collaboration network the results will make educational and social impact through engagement with academic institutions and the public
order at the mesoscale connecting supercomputing of compressible convection to classical and quantum machine learning

turbulent convection flows in nature display prominent patterns in the mesoscale range whose characteristic length in the horizontal directions exceeds the system scale height known as the turbulent superstructure of convection they are absent on both larger and smaller scales and evolve in ways not yet understood but they are an essential link in the heat and momentum transport to larger scales an important driver of intermittent fluid motion at submesoscales and one major source of uncertainty in the prognosis of climate change and space weather in mesocomp i will investigate the formation of superstructures in massively parallel simulations of compressible turbulent convection in horizontally extended domains aiming for a deeper understanding of their dynamical origin and role in the transport of heat and momentum i will then use these highfidelity simulations to build recurrent machine learning models to predict the evolution and statistics of the superstructure and thus quantify the transport fluxes beyond the mesoscale i will also analyse the impact of the mesoscale structures on the highly intermittent statistics at the smallscale of the flow and reveal the resulting feedback in the form of improved subgrid parametrizations by means of generative machine learning mesocomp opens additional doors to the application of quantum algorithms in machine learning which significantly improve the statistical sampling and data compression properties compared to their classical counterparts from a longerterm perspective my research results in a quantum advantage for the numerical analysis of classical turbulence which accelerates the parametrizations of mesoscale convection and increases their fidelity this work will finally lead to more precise predictions of the ongoing climate change and global warming the results will also improve solar activity models and thus solar storm prognoses with impacts on satellite communication and electrical grids
biogenic co2 capture into sustainable energy carriers a novel photosynthetic and hydrogenotrophic co2 fixation combined with waste nutrient upcycling for production of carbon negative energy carriers

this research project endeavours to pioneer a biological solution for mitigating carbon dioxide co2 emissions from effluent gases produced by bioenergy combustion systems the primary focus is on converting the captured co2 into carbonnegative energy carriers specifically emphasizing the photosynthetic conversion of biogenic co2 into energyrich biomass the transformation of this biomass into widely used renewable energy carriers such as biocrude and biogas is targeted with an additional emphasis on enriching these carriers with renewable hydrogen to achieve carbon circularitythe project is structured to address key aspects including efficient biogenic co2 capture from effluent systems development of resilient microalgae strains to enhance resistance to flue gas toxicity novel biomass pretreatment methods for cell disruption and nitrogen removal concurrent production of biostimulants and improvements in the efficiency and sustainability of hydrothermal liquefaction biocrude anaerobic digestion biogas and hydrogenotropic conversion of co2 to biomethane the ultimate goal is to validate the viability of the developed direct co2 fixation methods through integration with effluent systems at a pilot scale reaching trl5this multifaceted approach underscores the projects commitment to advancing sustainable and efficient methods for biogenic co2 fixation and subsequent conversion into renewable energy carriers to assess the economic viability a detailed technoeconomic analysis of the proposed carbon capture and use solution will be conducted furthermore sustainability and social impact assessments will be performed taking into account circular economy principles and addressing social economic and environmental aspects in alignment with the priorities outlined in the european green deal
increasing transmission distance of wireless power links for active implantable medical devices

cardiovascular diseases neuronal conditions and metabolic disorders together cause 22 million deaths each year worldwide fortunately those conditions can often be addressed through local sensing and treatments using for example active implantable medical systems aimds or transcutaneous bioelectronic devices to be invisible to the patients those devices should have the smallest volume possible which means they pack only limited data and energy storage relying on a wireless link to get recharged and to transfer data improvement in this link is urgently needed as todays poor transfer distance few centimeters leads to discomfort cognitive overload induces stress reduces quality of life and is associated with several suboptimal treatment outcomes because of this drawback many medical solutions already validated in the lab cannot be implemented on patientsmy aim is to achieve a major advance in the way energy and data are transferred and to gain an order of magnitude in the wireless transfer distance over existing technologies through the development of a novel timemodulated magnetic coupling strategythe approach will consist of wp1 developing a smart qmodulation which operates in a manner similar to regenerative braking systems where energy is temporary saved when the quality factor of the resonator has to be reduced for data transmission and later reused to increase the quality factor for power transmission wp2 maintaining the system in energyefficient operation against the body changing environment and wp3 guaranteeing a safe operation of the power transfer linkby enabling new wireless scenarios this project will enable a whole set of new medical devices to reach the market providing autonomously and imperceptibly operation to the user thus alleviating their cognitive burden the technology will also be transferable to many other applications such as industrial sensing reinforcing the european leadership on the field