Dragon09/odtu_chatbot huggingface dataset:
high energy density asymmetric hybrid supercapacitors for applications in consumer goods and electrification

supercapacitors are considered important energy storage devices that can complement batteries for various applications while currently the electric doublelayer capacitors edlcs still dominate the market their low energy density cannot satisfy the everincreasing demand the hedasupercap project aims at developing high energy density asymmetric hybrid supercapacitors consisting of two dissimilar edlctype and batterytype electrodes the improvement of energy density will be accomplished through the asymmetric cell design and developing novel materials and components including electrode materials ionic liquid electrolytes and current collectors sustainable environmentallyfriendly and costeffective synthetic approaches will be employed to ensure the elimination of critical raw materials crms usage and the minimisation of environmental impact during the components production supercapacitor cells and modules comprised of newly developed compoents along with innovative management system will be developed and demonstrated in electric scooters for lastmile mobility as well as in hand warming gloves for sport leisure comprehensive technoeconomic and value chain analyses will be carried out and a business case and exploitation strategy will be developed by the end of the project to roadmap future commercialisation of the hedasupercap technologythe hedasupercap consortium comprises three research technology organisations two universities and three leading companies in the automotive energy and engineering sectors this will allow the developed technology to be quickly taken up and adopted in the market the hedasupercap project will promote widespread deployment of high energy density hybrid supercapacitors in mobility and consumer goods sectors the project results will be disseminated to different stakeholders raising their awareness of the latest development of this new technology
quantum simulation of farfromequilibrium gauge theories

gauge theories gt are the staple of the standard model and their farfromequilibrium dynamics opens a window into the most fundamental questions of highenergy physics hep and the nature of equilibration in isolated quantum manybody systems however this dynamics is often highly nonperturbative and difficult to probe using classical methods due to entanglement buildup through quantum advantage and tunability quantum simulators qs emerge as a particularly suitable venue to solve this problemqusigauge hinges on developing an overarching framework composed of two main interconnected pillars a technological one focused on designing robust tunable experimentally feasible qs of gt and a phenomenological one concerned with a rigorous formulation of farfromequilibrium quantum criticality and equilibration in isolated manybody models the project will focus on the quantum simulation of nonabelian gt qudit quantum computing for hep nonergodic dynamics of gt and extracting farfromequilibrium quantum critical exponents from dynamical phase transitions in gt the approach is organized such that it provides both basic intuition and formal understanding while emphasizing quantitative predictions accessible to stateoftheart and nearterm qsqusigauge will pave at least two solid paths to uncover new physics 1 it will provide a toolbox for probing engineered exotic gt and gaugenoninvariant dynamics not easily accessible to particle colliders yielding tunable platforms for investigating the equilibration of controlled isolated manybody models 2 it will advance qs towards the holy grail of making them a reliable complementary venue for exploring colliderrelevant physics qusigauge will be of immediate impact to current coldatom and iontrap experiments which are approaching quantum advantage and will reach far beyond its immediate field eliciting strong connections between condensed matter hep and quantum simulationcomputing
regenerative resilient smart manufacturing networks

manufacturing and logistics companies are subject to unforeseen events that disrupt the supply chain causing production slowdowns reduced output and increased costs making it difficult to meet customer demand to mitigate these risks manufacturers must build resilience across entire value chains narrate will develop a sophisticated tool using ai digital twin and iot technologies allowing endtoend visibility and control over supply chain operations to monitor and predict potential disruptions enabling supply chains to achieve improved resilience the intelligent manufacturing custodian imc will leverage data from various production sources to enable proactive decisionmaking and act as a nerve centre for a supplychain network providing realtime monitoring and coordination of intelligent production processes and logistics integrating an imc into a supplychain will evolve its operations into smart manufacturing network smn a connected and selforchestrated ecosystem linked endtoend with programmable manufacturingasaservice capabilities that can withstand disruptionsa digital twin will provide a reliable model to represent production and operational data of an smn to unlock deeper imc intelligence collected data will train machine learning models to predict potential disruptions such as natural disasters or delayed shipments ai algorithms will analyse the data and provide realtime reporting and visualization on a dashboard the imc and digital twin interaction will generate powerful insights and selfadapting abilities that support an smn to evolve under human supervision by switching services between multiple external partners to respond to risks and disruptions and improve energy efficiency product circularity and environmental sustainability across the entire production processthe effectiveness of narrate will be evaluated by testing the imc in real production environments in quite diverse industry sectors
interplay between energy and metabolism in dictating growth constrain and setting final size

what determines organ and organism size is a fundamental question that remains unanswered all through development organ size increases while being scaled to organism size until growth terminates this project addresses the question of how growth is regulated and arrests during development we propose that energy becomes limiting throughout development and thus sets final size indeed kleibers law postulates that the cellular metabolic power decreases with increasing organism mass limiting the energy assigned for growth using drosphila melanogaster as a model organism we aim to study growth directly as a 3d dynamic process in order to address the question of how organs and organisms form with consistent size and shape we will track organism growth in terms of mass and volume as well as organ growth during the larval period of development by correlating size increase to energy fluctuations we will uncover to what extent fly larvae follow kleibers law and whether individual organs also follow the same rule finally we will consider three pillars that restrict growth capacity of organs by constraining energy fractal transportation branching morphogenetic gradients and mechanics and demonstrate how growth arrests during development
stemsight curing blindness with stem cells

stemsight is developing offtheshelf stem cell therapies to cure blindness we aim to solve the global shortage of corneal donor tissue by producing highquality tissue products using allogeneic induced pluripotent stem cells ipscs and biomaterials our lead product is aimed at a rare but severe form of corneal blindness limbal stem cell deficiency lscd for which there are currently no valid treatment options the companys innovations have arisen from extensive academic research and the company has spun out from tampere university finland in 2021 stemsight is a rare kind of deeptech startup as all of its scientific founders are women
computational hardness of representation learning

rich internal representations of complex data are crucial to the predictive power of neural networks unfortunately current statistical analyses are restricted to oversimplified networks whose representations ie weight matrices are either random andor project the data in comparatively very large or very low dimensional spaces in many applications the situation is very different the modelisation of realistic data is another issue there is an urgent need to reconcile theory and practicebased on a synergy of the mathematical physics of spin glasses matrixmodels from physics and information and random matrix theory chorals statistical framework will delimit computational gaps in the learning from structured data of much more realistic models of neural networks these gaps will quantify the discrepancy betweeni the statistical cost of learning good representations ie the minimal amount of training data required to reach a satisfactory predictive performanceii the cost of efficiency ie the amount of data needed when learning using tractable algorithms such as approximate messagepassing and noisy gradient descentscomparing these costs will quantify when learning is computationally hard or notto achieve this choral will first focus on dictionary learning another essential task of representation learning and then move on to multilayer neural networks which can be thought of as concatenated dictionary learning problemschorals ambitious program by defining benchmarks for algorithms used in virtually all fields of science and technology will have a direct practical impact equally important will be its conceptual impact the study of information processing systems has become a major source of inspiration for mathematics
integrated femtosecond laser based frequency comb and photonic microwave oscillator

in femtoicomb we develop the first integrated femtosecond laserbased frequency comb that can serve as the basis for a wide variety of optical and radiofrequency rf technologies ranging from high resolution environmental and health sensing to lidar and radar femtoicomb is based on the successful eicpathfinder project femtochip where we demonstrate an integrated high power femtosecond laser enabling extremely low jitter on chip scale here we tam the free running comb from the integrated femtosecond laser with onchip continuum generation carrierenvelope and repetition rate locking to an optical reference to become a fully stabilized femtosecond laser frequency comb fslfc with extremely high frequency stability we use the femtoicomb to pursue photonic microwave oscillators for a variety of applications ranging from autonomous driving to ultralow phase noise oscillators for advanced signal generators and rftest and measurement equipment and demonstrate these devices in relevant industrial environments for each application these prototype field tests will validate the trl levels achieved for each application and together with surveys of potential customers will inform the business case to be made for each potential product line
sentencing architecture building a decisionmaking matrix

the act of sentencing represents a critical juncture at which the power of the state to punish intersects with the personal freedoms of the individual it is governed by an intricate set of decisionmaking dynamics for which we lack a cohesive understanding this groundbreaking project seeks to fill this gap by introducing a fresh perspective rooted in choice architecture aiming to devise a comprehensive theoretical matrix that systematically captures the multidimensional nature of sentencing decisionsemploying the notion of the decisionmaking environment the project seeks to map out the sentencing environment a concept that includes both wellresearched elements like judicial discretion and less examined factors such as procedural nuances and habitual decisions the objective is to move beyond the dichotomy of legal vs nonlegal factors using choice architecture in a nontraditional way not to guide decisions but to understand the sentencing landscape and its mechanicsthe methodology encompasses a metanalysis of existing literature supplemented by workshops and testing the initial findings through courtroom observation interviews and experiments with practitioners to develop a typology of sentencing frameworks these will be tested against realworld practices and subjected to computer simulations using agentbased modeling providing a visual representation of the sentencing environmentthe project is pioneering for several reasons firstly it unites fragmented research into a holistic picture employing an interdisciplinary approach that promises greater transparency in sentencing secondly it uses visualization and simulation as tools for communication and strategic reform potentially influencing legal and policy directions lastly it offers insights into how various sentencing dimensions interact with human decisionmaking contributing to a fairer justice system and a deeper understanding of legal behaviour
a climate neutral sustainable and productive blue economy partnership

the sustainable blue economy partnership sbep aims to design steer and support a just and inclusive transition to a regenerative resilient and sustainable blue economy boosting the transformation needed towards a climateneutral sustainable productive and competitive eu by 2030the sbep will deliver solutions to strengthen eu and international sciencepolicy interfaces in marine and maritimerelated domains of the eu green deal and digital europe strategies through aligning national regional and eu ri priorities bringing together science industry policy and society it will also contribute to accelerate the postpandemic recovery and resiliencein line with the ec new approach for a sustainable blue economy in the eu the sbep rollsout impact pathways to catalyse the transformation of ocean economy value chains deliver ocean knowledge and impactdriven ri solutions cooperate to respond to international eu and national regulations recommendations and policy strategies contribute to the social and digital transition by developing innovative governance frameworks that benefit coastal communities including by reinforcing skills and enhance ocean observation capacity contributing to eoos and geoss59 partners from 25 countries ms and ac together with the ec will join an unprecedent effort to pool ri investments aligning programmes at paneuropean scale the ambition is to launch 6 cofunded calls over a sevenyear timeframe to support ri joint programming on thematic priority areas of interventions stemming from a codesigned sria the sbep will also identify additional mechanisms for alignment and look for further economic support of ri programs leveraging other funding and finance streams in parallel a longterm structuring ambition will support the creation of a community of practice fostering cocreation coordinating all relevant initiatives at seabasinsatlantic ocean level and further promoting the eu blue economy at global level
impact licensing initiative

technologies and data are still underused or suboptimally allocated to solve the societal challenges of today in europe and beyond moreover the covid pandemic and the recent war in ukraine has revealed that health environment energy chocks in our systems create new technology needs and gaps in our access to necessary technologies in europe itself impact licensing is a strategic instrument to optimize the valorization potential of technologies and data without losing sight of the economic dimension it is a timebounded voluntary permission granted by a technology holder to bring at preferred conditions an ip a technology a product or a service to a predefined market for a specified societal purpose which can be a societal or environmental unmet need or triggered by a crisis moreover the impact licensing mechanism creates for technology holders important incentives for market exploration reverse frugal innovation and access to real world data on technology performance and outcome impact indicatorsthis project aims to develop an integrated toolkit 6 instruments and 2 training modules and a network of intermediaries clearing houses across the eu to introduce impact licensing as an ip instrument a for societal value creation with focus on the un sdg goals b as an instrument for a resilient europe that guarantees access to technology and data during crisis c as a driver for innovation and research through performance data access and insight for technology improvement and d as a smart tool for emerging market exploration
subwavelength holographic lithography stepper for integrated circuit production

to achieve ever shrinking dimensions and higher resolutions of circuit elements projection lithography pl is growing in complexity and cost to manufacturers it is limited to producing 2d images on flat surfaces extension to 3d imaging is restricted by tradeoff between focus depth and resolution advanced costefficient solutions to fabricate waferscale 3d components are requiredholistep unleashes the potential of subwavelength holographic lithography hl as a powerful and enabling disruptive lithography hl will overcome limitations of pl and facilitate production of novel 3d topographies with high resolution while making the production of highresolution ic much more affordablean industrial prototype operating at 345nm with 200nm resolution will be produced and validated in an operational environment several advancements in holographic stepper subcomponents must be realised a uv fibrebased laser with 20w output power at 345nm and 15m coherence length an alignment system with 25nm overlay precision an adaptive optical system with correction precision of 120 and software modules for vector diffraction modelsenergy consumption of hl technology is drastically reduced compared to pl due to low powerconsumption of the laser and production of complex structures in one exposure hl images are not sensitive to mask defects eliminating frequent mask replacements and use of toxic materials moreover holographic masks act as projection optics eliminating the need for complex optical systemsthe hl prototype will be verified for 3d patterning for mems moems and microoptical components to show better resolution flexibility of 3d printing and reduced cost holistep will empower a positive transformative effect on environment economy and society by enabling a wider range of companies to produce novel highresolution 2d and 3d images at lower costs
improving surface and bulk properties of promising fusion material using deep cryogenic treatment

with progress and development of society the necessity of a more affordable reliable and sustainable energy is crucial to stability and prosperity of evergrowing population for this reason fusion power is being researched and developed to obtain high amounts of stable and greener energy compared to conventionally fossil fuelbased and fission processes materials which are being tested as possible candidates for fusion reactor components are mainly based on the previous selections designated for fission nuclear power however their implementation is not easily transmittable and has been proven to be considerably challenging consequently there is a high interest towards research of new development and processing such as heat treatment of selected materials applicable for fusion as well as materials that were not previously considered the proposal suggests to conduct fundamental research on selected material proposed alternative aisi 431 and its treatment which has the potential to be used as material for fusion reactor components the project tends to provide base understanding on how deep cryogenic treatment dct improves materials properties for fusion applications through their microstructural tailoring focus is placed on the role of modified microstructure as well as nanochemistry on the corrosion resistance which is up to now only superficially explored due to the unique influence of dct on microstructure the process can provide a novel greener way of material treatment that is both highly effective as well as economically feasible the proposal challenges promising alternative material for fusion and aims to show how dct can effectively improve microstructure corrosion and surface resistance of selected material furthermore the project will also develop new fundamental knowledge of dct effect on metallic materials in order to provide future possibilities and treatment combinations for materials used in fusion
marhab

the vast majority of marine habitats and species protected under the eu habitats directive still show an unfavourable conservation status this situation is particularly pressing in northern europe where the conservation status of marine habitats in the kattegatskagerrak region is consistently bad marhabs objective is to improve the conservation status of marine ecosystems by demonstrating an ecosystem dynamics approach to restoration and maintenance of protected habitats by employing cutting edge technology genomics tracking in situ observations machine learning in stateofart ecosystem research the project will provide the scientific underpinnings needed to bring about the long overdue reconciliation of fisheries management with biodiversity conservation moreover it will generate a leap in knowledge urgently needed to sustainably manage the productive but severely overexploited ecosystems harboured in the kattegatskagerrak seas and adjoining coastal waters marhab is urgent timely and innovative urgent because key habitats and species are in the worst environmental status of the european waters while european citizens rely on a healthy ocean for climate resilience and marine resources support livelihoods and food security timely because international agreements such as the 2030 european biodiversity strategy and the global biodiversity framework cop15 committed parties to reach important conservation targets in less than 7 years from now including effectively protecting 30 of the ocean and 10 with strict protection in eu and innovative because this is a highly understudied region in what concerns marine protection effectiveness marhab engages with the full range of relevant stakeholders at local regional national international eu and global level through a communication strategy tailored to target audiences marhab will contribute to increasing the public and politicians understanding of marine biodiversity conservation
ekkono synthesis federated learning for the industrial iot

ekkono is developing a unique product edge intelligence an edge machine learning framework that conducts learning on supersmall sensorsized devices enabling a transition from connected to smart it is based on over 7 years of university research and is materially different from other ai solutions that either run in the cloud or can only perform inference onboard of connected things iot our product trains an individual model on each unit it runs on learning how where and for what the unit is usedenabling perdevice maintenance performance optimizationwe are pioneering edge ai in the emerging industrial iot 20 specializing in the european industrial manufacturing automotive sectorsour ambition is to disrupt the market with our federated learning solution called synthesis where individual device models are collected compared correlated combined into supermodels enabling nextgen sustainability leap new servicecentric business models for product oems