Dragon09/odtu_chatbot huggingface dataset:
microbesynthesised dna nanostructures for displaycontrolled storage cartridges

dna has a huge potential for the longterm storage of large amounts of data however writing editing and reading dnabased data is expensive and inefficient with current technologies our vision is to develop a lowcost energyefficient and fast data drive that is able to write edit store and retrieve dnabased data the data drive is based on simple and easily available hardware components plus bacterial cells the proposed technological solution enables the short medium and longterm storage of dnabased data to achieve this vision we will exploit bacterial genetic mechanisms that were evolutionarily optimized for billions of years such as coloursensitive genetic switches and dna exchange processes we have defined two specific objectives to achieve our goal as a proofofconcept we will store a large trajectory file of a molecular dynamics simulation encoded on dna our consortium has six partners from four european countries one research organisation two university and two smes will work together to achieve the outlined vision
minimisation of the offshore wind and tidal turbine acoustic footprint on marine life

for renewable energies to be sustainable in the future their impact and harmful effects on the environment should be minimum recent evidences suggest that offshore wind and tidal turbines can have an acoustic damaging impact on marine life due to the sustained generation of noise which propagates very efficiently underwateroffcoustics combines numerical simulations and experiments to provide insights into the physics governing the aerohydroacoustic generation and propagation for offshore wind and tidal farms control of these physics will enable the design of silent offshore farms enabling renewable energy with zero acoustic impact first i propose to develop a novel aerohydroacoustic solver blending advanced high order numerical techniques through machine learning and trained with experiments to simulate flowacoustic signatures for wind and tidal turbines in realistic offshore environments including bathymetry airwater surface etc second an experimental campaign will generate aerohydroacoustic data for scaled turbines and farms to help elucidate the physics governing offshore acoustics and to guidevalidate the flowacoustic simulator third simulations and experiments will be combined to characterise turbines in complex offshore environments and to develop physicinformed surrogate models fourth using the developed surrogate models and optimisation offcoustics will propose new designs of silent farms that minimise the acoustic impact while ensuring energy productionmajor advances in multidisciplinary aspects are expected including fluid mechanics numerical simulations optimisation experimental acoustics aerohydroacoustics and offshore wind and tidal turbine physics
conversas of muslim and jewish origin in the premodern crown of aragon parallels and contrasts

the project conversas explores the cultural identities of muslim and jewish cryptoreligious minorities within coerced monoconfessional premodern crown of aragon c 14001500 it will challenge traditional interpretations based on male centred historical documents and largely ignored within gender blind research by creating a novel concept of comparison especially between socioreligious characteristics of these groups female members converted to christianity moriscas christian women of muslim origin and judeoconversas christian women of jewish origin suspected of secret adherence to the religion of their ancestors the project aims to develop an adaptable multidimensional comparative and intersectional model to provide cultural historical and gender analysis of these religious groups as a sample of multidimensional methodology applied to the underutilized archival data most notably inquisitorial trial dossiers jewish and muslim religious and legal texts royal documents local legislations notarial and cadastral documents the applicant will write a research monograph accompanied by a database of selected manuscripts integrated into the hosts servers and coorganize a workshop the research will be conducted in a transdisciplinary research group at the universitat pompeu fabra upf in barcelona spain under the supervision of professor linda gale jones an international authority of comparative muslim and christian gender studies the applicant will bring philological historical and anthropological skills that will facilitate research in the group and the transfer of ideas since democratic managing of increasing cultural diversity represents one of the crucial challenges that europe is facing today the knowledge acquired from islamic and judaic intangible cultural heritage will prevent ethnic disintegration and promote understanding and reconciliation toward creating a plural tolerant and broadminded cohesive society
codesigning human centric pathways for future skills in manufacturing through augmented empowered inclusive and symbiotic complementarities between ai automation and human task

the modern manufacturing landscape is undergoing a transformative twin transition integrating green and digital technologies to bolster value chain resilience and explore reshoring options amidst this paradigm shift concerns about job displacement by machines particularly through the rise of artificial intelligence ai and machine learning ml have become more pronounced this proposal delves into the challenges posed by the pursuit of excellence in the industry 50 framework focusing on the potential impact of digital technologies on job nature and the ensuing need for humantechnology complementarity the potential for ai to exacerbate social disparities and inequalities especially for vulnerable groups is also a significant concern additionally the manufacturing sector faces labor shortages impacting innovation capacity and economic competitiveness the mission of skillaibility is to address these challenges emphasizing the need for a humancentric approach to assess digital technologies and enhance workers employabilitythe proposal also outlines the short medium and longterm contributions of skillaibility towards a resilient inclusive digital transition in the manufacturing industry this initiative provides tools and methodologies to understand and respond to the impacts of emerging digital technology advancements on human tasks skills training and policymaking skillaibilitys holistic impact spans various societal industrial academic and regulatory dimensions affecting citizens people with disabilities workers trade unions industry players research institutions and governmental bodies through upskilling and reskilling initiatives skillaibility aims to empower citizens and workers mitigate the risk of task automatization and increase employability within the advanced manufacturing sector furthermore the proposal contributes to the manufacturing industrys growth by filling skills gaps increasing performance and pro
strategic synergies cluster xkic bp 2325 proposal

the mission of the eit community strategic synergies eit css is to facilitate and foster collaboration across eit community in key thematic areas identified in the eit sia 2021207 and eu policy priorities by bringing together and promoting cooperation across the different kics involved the eit scc elevates the eit communitys visibility and impact in key areas to drive a systemic change in europe by gathering eit communitys answers to strategic challenges in one cluster the eit css creates links between programs that would otherwise never meet it increases scalability of actions and results it improves efficiency in terms of management and implementation of processes and attract new sources of fundings the eit css builds on the diverse expertise and knowledge of the kics involved and inspired by the holocaracy management framework yet aligned with eits recommendations it positions itself as unique community to address some of todays most pressing challenges for europe in four areas 1artificial intelligence by providing solutions for a humancentric implementation of ai that can best address its societal business environmental and regulatory challenges but also contributing to the ambitious deep tech talent initiative dtti initiave2new european bauhaus nebby supporting communitybased capacity building initiatives and startups to accelerate the shift towards a more sustainable inclusive and beautiful europe and contributing therefore to the green deal3women entrepreneurship by promoting a more inclusive entrepreneurial ecosystem mainstreaming business opportunities and increased the share of womenled innovation in the market4circular economy facilitating the shift from a linear to a circular economy model by connecting and engaging the different stakeholders of the innovation ecosystem
rrrxai right for the right reason explainable artificial intelligence

deep deep learning dl is a form of machine learning ml that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts this hierarchy allows a dl model to learn complicated concepts by building them out of simpler ones a graph of these hierarchies would be many layers deep and thus its name a deep neural network dnn is based on an artificial neural network model and its core strength is that there is no need for human assistance to formally specify all the knowledge that the model needs this makes dnns represent the state of the art in artificial intelligence ai despite their top performance and ubiquity of applications from healthcare to autonomous cars dnns suffer serious shortcomings first dnns are considered black box models ie with complex and opaque algorithms hard to interpret and diagnose second they suffer from bias and the testing protocols for automatic recognition are not fair as they learn patterns in the data that are not correlated to the output eg they may focus on areas outside the lung in x ray images to predict the presence of covid19 although dnns outperform many other methods they often are not right for the right reasons rrr rrrxai tackles this mismatch and bridges this gap through a tight integration of dl and symbolic ai with the principal objective of making dl explainable to achieve this i will follow the rationale behind xai under the rrr philosophy and perform analyses to understand two types of phenomena that cause trouble in dnns second i will use 1 domain knowledge expertise as supporting evidence to explain a particular model output 2 neuralsymbolic computation to communicate the explanation of such phenomena in natural language i will study two practical use cases where supporting explanations of the model output are critical a covid19 prediction from chest xray images and b weapon detection in alarm systems and crowds from images
sweepics swept lasers for noninvasive diagnostics

swept lasers have enabled paradigmshifts in biomedical imaging and diagnostics the sweepics project will research and develop the next generation of swept source lasers with flexible pulse modulation capability high power output multiwavelength coherent output and multiapplication potential sweepics will develop new laserbased systems a highspeed high resolution multiphoton high content screening system a multimodal noninvasive imaging system based on highspeed photoacoustics and multiphoton microscopy and a smart microscope for accelerated acquisitiondiagnostics the interdisciplinary consortium of european partners will showcase the sweepics technology in cuttingedge use cases based on novel vascular organoids for animalfree drugtesting and infection studies this disruptive sweepics technology will rapidly generate highresolution diagnostic imaging in threedimension where the high imaging depth permits penetrating millimeter deep into tissuelike organoids and imaging at high temporal and spatial resolution in order to allow for a drastic reduction of animal testing and increased speed of diagnostic results it will allow the study of dynamic processes in realtime and at multiple length scales enabling researchers to observe how cells and tissues respond to viral infections or pathogeninduced inflammation while also permitting a highthroughput enabled discovery of novel diagnostic biomarkersoverall this technology represents a major breakthrough in capable laser technology for high accuracy and throughput medical diagnostics and is poised to make significant contributions to the european laser and biomedical technology landscape
generative idleness and gestures of reparation the resurgence and promises of intentional fallowing practices in european regenerative agriculture

this project proposes to investigate the resurgence of intentional fallowing as a practice for soil regeneration and as a tool for sustainability policies in europe it will deploy an interdisciplinary approach grounded in philosophy and multispecies ethnography to analyse the contemporary resurgence and mutations of intentional fallowing practices in european agriculture and policies as well as the cultural social and scientific consequences of this shift it combines qualitative research on european farms conducting experimental intentional fallowing a genealogical analysis of the historical and political context in which these practices are reemerging and an exploration of the adjacent spaces in which fallowing and fallowness are studied such as microbiology conservation biology and bioengineering by combining these three lines of inquiry the project demonstrates that fallowing is a marginalised practice currently under reevaluation and potential reintegration into projects and policies that go beyond agricultural concerns it will analyse the biopolitical and cosmopolitical dimensions of this renewed interest in alternatives to synthetic fertilisers and intensive agriculture by showing that fallowed soils are a site where a variety of interests and projects converge and by tracing how these practices take up replay and extend questions of productivity and idleness growth and alternatives to economic expansion this project will combine qualitative methods in particular indepth interviews with practitioners in the field with an extensive engagement with literature in agricultural science microbiology conservation biology and ecology producing an analysis of fallowing that cuts across what is usually deemed cultural and biological domains and studies the role promises and implications of fallowing practices in times of mass extinction and soil depletion
integrating galileo and copernicus downstream applications to support dynamic use of public spaces

space4cities will dynamise the uptake of spacebased solutions for dynamic use and management of public space this is an area of smart city development which is currently lagging behind in digital transformation when compared to parallel domains of similar economic and social importance cities are at the forefront of fighting todays grand societal challenges as they consume 75 of the natural resources 78 of the worlds energy produce 50 of the global waste and emit 6080 of the greenhouse gases yet they account for less than 2 of the earths surface therefore space4cities project predominantly targets cities and densely populated regionscities face increasing pressure to tackle their climate challenges and to utilise their existing assets more efficiently while at the same time be more agile in reacting to constant change from climate events and other factors in effect cities need to be more dynamic and more resilient however currently cities are not able to manage their public space on ground and in air in an agile manner that would adequately support the increasing amount of different types of needs if the management of areas is to become dynamic it has to be based on dynamic data assetsthis project strives for better more dynamic management of public spaces answering a concrete need for cities and regions to be able to adapt to fastchanging requirements for transport infrastructure open spaces and city maintenance and to increase their resilience to cope with extreme and disruptive events via smart exploitation of space data the space4cities project aims to build replicable solutions for the dynamic management of public areas and a clear roadmap for europewide implementation of such space databased solutions
a methodology for integrating community acceptance of wind energy into energy system modelling esm

decarbonisation of the energy system is key to achieving the paris agreement goal of limiting global temperature rise to below 2c which can be achieved by electrified and interconnected systems with a high share of variable renewables this transition is shaped by uncertain factors which include technology innovation resource availability and socioeconomic variables energy system modelling esm has been a key policy tool to study decarbonisation pathways esm provides stakeholders in the energy sector with knowledgebased and systematic methods to reach decisions about which technologies to support however present day esm mainly integrates technoeconomical input parameters whereas social factors such as local responses to new installations are largely neglected esm might therefore produce solutions that are not accepted by communities and as a result could jeopardize energy transition goals the main goal of windaccept is to develop an innovative and highly interdisciplinary mixedmethods approach to represent community acceptance stakeholder interests and wellbeing variables in esm this new methodology will be developed and applied to the case of norway a country with excellent wind resources but high local opposition towards their development the methodology will contribute to elucidate the impacts of community barriers and value the costs and benefits of alternative options on the net zero energy system design in norway and the effects on long term whole system decarbonisation in an interconnected europe this project will be made possible by combining the applicants experience in social acceptance of renewable technologies and the supervisors and hosts university of oslo expertise in esm the methodological and interdisciplinary trainingthroughresearch and unique set of skills gained from windaccept will position the researcher at the forefront of sociotechnical energy transitions modelling
precise global temperature data for a growing planet

food security is an urgent global challenge to feed a population of 10bn by 2050 we must produce 50 more food despite water scarcity loss of arable land climate change lack of water water stress severely reduces crop yields the inability to measure water stress accurately leads to unpredictable and lowyielding harvests impacting the entire food supply chain from farm viability to food prices current crop health data is not fit for purpose leading to ineffective irrigation consuming 70 of global freshwater constellr will provide the first highprecision temperature data at field level daily globally from a uniquely scalable constellation of microsatellites hive enabling water stress detection in time to prevent yield loss the eic project will develop launch an mvp constellation generating the data required to increase global food production by up to 4 reduce agricultural water waste by up to 180 gigatons avoid up to 94m tons of co2 emissions
hydrogen pem fuel cell system to retrofit ships in the marine transport industry

the hyekotank project will develop costeffective technology for retrofitting seagoing and inland waterway vessels with hydrogen pem fuel cell systems for emissionfree operations retrofit solutions are urgently needed to transform the waterborne transport and reach the reduction of green house gas emissions established by eu and imo by 2050 hyekotank project proposes the design development approval and demonstration of a 16 mw hydrogen fuel cell system the technology will be developed by a consortium of 13 partners who are experts in the field and demonstrated by retrofitting a container ship kvitnos under operation at fix round trip from rotterdam to the northern norway in the north seathe main challenges that need to be resolved concern the development of a costefficient fuel cell system specifically designed for maritime applications and suitable to retrofit existing vessels as well as the assessment and creation of hydrogen infrastructure and logistics for vessel refueling in ports as well as safe hydrogen storage and handling we aim at approving the hyekotank technology to deploy it for any type of vessel and operation while demonstrating the expected environmental impacts 50 ghg reduction during voyage 100 reduction in port and 50 total reduction yearly the project will take the technology from trl 45 to trl 8the hyekotank consortium is mostly composed by companies with industrialcommercial interest in the project results teco 2030 as no shell international exploration production bv nl shell international trading shipping company limited uk samskip is navtech bv nl tarbit shipping ab se teco 2030 innovation center as no fartygskonstruktioner ab se blom maritime as no teco solutions as no umoe advanced composites as no they are all experienced in providing services and commercializing products in the hydrogen andor maritime fields the consortium also counts with the participation of an academic partner universitetet i troms norges arktiske universitet no
optimize risk prediction after myocardial infarction through artificial intelligence and multidimensional evaluation

myocardial infarction mi is a leading cause of death worldwide after mi longterm antithrombotic therapy is crucial to prevent recurrent events but increases bleeding that also impacts morbidity and mortality giving these competing risks prediction tools to forecast ischemic and bleeding are of paramount importance to inform clinical decisions but their current precision is limited improve events prediction by discovering novel and innovative markers of risk would have a tremendous impact on therapeutic decisions and patients outcome i hypothesize that using innovative multidimensional information from wearable devices biomarkers behavioral patterns and noninvasive imaging integrated through artificial intelligence computation we may discover novel computational biomarkers of risk and improve current standards of risk prediction in this project i will enroll a large cohort of mi patients whereby prospective collection of consolidated and innovative potential risk predictors will take place in order to generate a comprehensive and multidimensional dataset i will collect data from stateoftheart noninvasive imaging blood biomarkers wearable medical devices of continuous heart electrical activity sweat mobility and behavioral patterns to create a large physiological time series allowing patients deep phenotyping we will therefore analyze data leveraging artificial intelligence computation to find relevant associations with clinical outcomes and compare new algorithms with current risk prediction tools this research will increase our knowledge on bleeding and ischemic risk factors enabling enhanced capability predictions models in the near future we hypothesize that our clinicallyguided artificial intelligence algorithm might be integrated in clinical practice helping clinicians to inform treatment decisions patients to better understand their risk profile finally setting a common ground for shared patientphysician decisions