Dragon09/odtu_chatbot huggingface dataset:
ssmart uupgraded assetvalues and quality of life ppublic private partnership eextended energy efficiency rrenewables triggered by the project shsocial housing iinvestment nnet zero eeuropean

the objectives and impacts of the supershine project will assist and support the european commission to implement the european green deal particular attention will be paid to the renovation of social housing to help households who struggle to pay their energy bills in addition supershine will also contribute to the decrease of energy poverty the supershine lighthouse districts will be characterised by energy efficient buildings low carbon mobility smart grids efficient water and waste management all underpinned by responsive technologies that optimise resources while promoting wellbeing and sustainable lifestyles more specifically supershine will adopt an integrated strategy with these key principles aenergy efficiency first b affordability c decarbonisation and integration of renewables d lifecycle thinking and circularity e high health and environmental standards by promoting sustainable energy behaviours f tackling the twin challenges of the green and digital transitions together g respect for aesthetics and architectural quality the main areas of intervention are a strengthening information and incentives for public and private owners and tenants to undertake renovations while improving community participation or inspiring new patterns of citizen behaviour bensuring adequate and welltargeted funding by supporting innovative bottom up financial solutions such as public private partnerships ppps and green public procurement gpp and collaborating with innovative local small and medium enterprises smes c promoting comprehensive and integrated renovation interventions d making the construction ecosystem fit to deliver sustainable renovation based on circular solutions use and reuse of sustainable materials and the integration of naturebased solutions while reducing whole lifecycle carbon emissions
dynamicsaware theory of deep learning

the recent advances in deep learning dl have transformed many scientific domains and have had major impacts on industry and society despite their success dl methods do not obey most of the wisdoms of statistical learning theory and the vast majority of the current dl techniques mainly stand as poorly understood blackbox algorithms even though dl theory has been a very active research field in the past few years there is a significant gap between the current theory and practice i the current theory often becomes vacuous for models with large number of parameters which is typical in dl and ii it cannot capture the interaction between data architecture training algorithm and its hyperparameters which can have drastic effects on the overall performance due to this lack of theoretical understanding designing new dl systems has been dominantly performed by adhoc trialanderror approachesthe main objective of this proposal is to develop a mathematically sound and practically relevant theory for dl which will ultimately serve as the basis of a software library that provides practical tools for dl practitioners in particular i we will develop error bounds that closely reflect the true empirical performance by explicitly incorporating the dynamics aspect of training ii we will develop new model selection training and compression algorithms with reduced timememorystorage complexity by exploiting the developed theoryto achieve the expected breakthroughs we will develop a novel theoretical framework which will enable tight analysis of learning algorithms in the lens of dynamical systems theory the outcomes will help relieve dl from being a blackbox system and avoid the heuristic design process we will produce comprehensive opensource software tools adapted to all popular dl libraries and test the developed algorithms on a wide range of real applications arising in computer vision audiomusicnatural language processing
untwist policy recommendations to regain losers of feminism as mainstream voters

untwist aims to promote gender equality as a core value of the eu defending it from the emerging threat that the oppositional gender rhetoric from extreme populist parties represents by developing policy recommendations that uphold gender equality as both a value and a way of life our project will contribute to shaping the global future thus fulfilling relevant objectives in the eus political agenda for the period 20192024 by understanding if extreme populist parties are acting as niche parties substantively representing but also twisting the needs and demands of citizens at the margins who feel abandoned or disempowered by current mainstream feminist discourses and policies it will cocreate alternative ways of addressing those citizens thus developing and implementing new policies that can counter genderequalityrepressive strategies and the policies of extreme populist parties representative democracies will consequently be reinvigorated and the citizenship empowered by a better safeguarding of gender equalityuntwists main working strategy toward that end will consist of empowering nonradicalpopulist parties in europe to improve their representation of the genderbased interests of the citizenry through the definition enhancement and transfer of a policy recommendation handbook with evidencebased policy recommendations that 1 help mainstream parties improve their substantive representation of sex and genderbased needs and demands in ways that diminish the appeal of extreme populist messages untwisting oppositional gender messages particularly from rightwing populism and 2 contributes to the widening horizon of gender expectations and overcomes current gender fatigue among citizens the improvement in substantive democratic representation by these parties will decrease citizens interest in the antifeminist messages of radical or populist parties
physicsinformed datadriven analysis for wind power hubs

to address the challenges of climate change and energy crisis the european union eu is accelerating the transition to carbon neutrality using wind power as the key driver to fully exploit eus offshore wind resources the strategy of constructing wind power hub has been devised recently and will be implemented in the north sea however integration of numerous power converters in wind power hub forms a sophisticated system making analysis difficult this project phydawn will tackle these challenges by developing physicsinformed datadriven modelling and stability assessment methodologies for wind power hub firstly effective impedance model of voltage source converters for varying operation points will be developed based on physicsinformed machine learning next a scalable aggregated model for wind power hub will be proposed using transfer learning improving modelling effectiveness under insufficient data then the stability of wind power hub will be assessed in a probabilistic manner realizing intensive stability analysis for internal converters a software toolbox will also be developed for fully exploitation of the research results in the industry the applicant has expertise in datadriven grid analysis during the project she will collaborate with the supervisor at aalborg university who has rich research experience on power converter modelling and analysis besides she will collaborate with the secondment supervisor at kth royal institute of technology who is an expert of control theory through these collaborations phydawn will create novel knowledge for wind power hubs and also strengthen the applicants career prospects the research results will be disseminated by publications in top journals and conferences producing a positive impact on raising the europe knowledge base moreover communication activities are planned to expand the impact of this project to the general public committing to eus carbon neutrality ambition
twinning for a european consortium of rectal cancer research institutions through stepping up scientific technological and innovation excellence of iors

neoadjuvant chemoradiotherapy crt is the gold standard in locally advanced rectal cancer larc but the response is not uniform among patients and improvements are currently being assessed profiling the response to crt in patients with larc would enable more adequate selection of patients who would benefit most from crt while minimizing adverse effects and toxicity patients with a favorable response to crt might be candidates for a less invasive surgical approach or for enrollment in a watch and wait approach in the case of a complete clinical response ccr this would increase their quality of life and contribute to the overall reduction of treatment cost identification of novel therapeutic targets might also benefit rectal cancer patients who do not respond well to neoadjuvant crtthe main aim of the stepupiors project is to establish a european consortium of research institutions dedicated to defining prognostic biomarkers in rectal cancer specific project objectives that would enable addressing this unmet clinical need are objective 1 determine the molecular profile of response to neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer through a newly formed rectal cancer consortium with complementary expertiseobjective 2 strengthen the research management and administrative abilities of the institute for oncology and radiology of serbia iors located in belgrade serbia along with the establishment of a rectal cancer biobankobjective 3 establish a longlasting knowledge personnel and sample exchange between participating institutions in the rectal cancer consortiumthe stepupiors project aligns with europes beating cancer plan and the horizon europe strategic plan 20212024 within the health cluster through setting up a research consortium that will enable improvement of rectal cancer prognosis monitoring and treatment and lead to better health outcomes
interrogating basal ganglia reinforcement with deep brain stimulation in parkinsons disease

dopamine and the basal ganglia have been conserved over more than 500 million years of evolution they are fundamental to animal and human behaviour parkinsons disease pd is associated with loss of dopaminergic innervation to the basal ganglia over 6 million people suffer from the debilitating symptoms of pd that span disturbance of emotion cognition and movement there is a pressing need to understand the pathogenesis of these symptoms but an integrated account of dopamine and basal ganglia function is lacking this constitutes a significant roadblock to scientific and therapeutic advances to overcome this roadblock reinforcebg poses the novel unconventional hypothesis that loss of dopamine in pd does not impair movement per se but leads to chronic negative reinforcement of neural population dynamics conversely in the healthy state transient dopamine signals may stabilize cortexbasal ganglia activity to facilitate reentry and refinement of cortical output to address this hypothesis reinforcebg will combine invasive electrocorticography and local field potential recordings with closedloop deep brain stimulation in pd patients aim 1 will investigate how basal ganglia pathways coordinate neuromuscular adaptation aim 2 will shed light on basal ganglia reinforcement in multiple behavioural domains including movement gait speech and spatial navigation in virtual reality aim 3 will develop a neuroprosthetic braincomputer interface that aims to modulate basal ganglia reinforcement reinforcebg deviates from outdated models on pro vs antikinetic go and nogo pathways and promises a holisticreinforcement centred view of basal ganglia function it will leverage the unprecedented spatiotemporal precision of neuromodulation for the development of an innovative brain circuit intervention that modulates neural reinforcement in real time this opens new horizons for the interdisciplinary treatment of brain disorders affecting the dopaminergic system
a design principle for predicting flexible metalorganic frameworks

metalorganic frameworks mofs are porous organicinorganic hybrid materials that hold the potential for developing newtechnologies to tackle some of the pressing global challenges such as pollution climate change and energy crisis their typical lowmass densities high internal surface area large pore volumes and facile chemistry makes them suitable for application in gas storagefiltration extraction catalysis and so on some mofs are known to show a substantial degree of structural flexibility wherein theframework reversibly expandscontracts when subjected to external stimuli like pressureheatlight or during absorptiondesorptionthis structural flexibility if fully understood can be used to enable the technological development of mofbased recyclable filtersswitchable catalysts threshold sensors stimulusinduced drug delivery systems with integrated keylock functionality compressiblegas tanks and so on however the origin of this flexibility has not yet been sufficiently understood to enable the rational design offlexible mofs this research project aims to provide a conceptual understanding on the origin of this flexibility at the atomic regimeby analysing all unique building units topologies and frameworks of all published mofs to design a universally robust metric forpredicting flexibility and mechanical properties of mofs with the overarching goal of providing a theoretical methodology for thecrystal engineering of flexible mofs
enhanced biomass valorisation by engineering of polyoxometalate catalysts

this project builds on a recent and groundbreaking discovery of the pi in the field of homogeneously catalysed selective biomass valorisation materials technologies that promise improved catalytic performance are of utmost interest for a more sustainable chemical industry manipulating molecular catalysts like polyoxometalates pom in solution by tuning the solvent properties and gas atmospheres introduces a new paradigm in homogeneouscatalysed biomass valorisation technologiesit has been found that by using methanol as a cosolvent pom catalysts can completely suppress undesired total oxidation to co2 under oxidative conditions this drastically enhances the carbon efficiency from biomass to close to 100 yield remarkably this manipulating effect could be explained with the formation of a new vanadylmethanolatecomplex in methanolaqueous solutions having a methanol content of at least 10the proposed biovalcat project aims for developing this potentially disruptive technology towards an industrial viable biomass valorisation process by laying the foundations for a scalable safe and economic process for the oxidation of biomass to valuable carboxylic acid esters the project is structured according to the key challenges that have to be mastered in order to achieve this ambitious goal a investigations to identify the nature of the pomsolvent interactions b understanding and revealing the key organic mechanisms in solution c development of novel pom catalysts specifically optimised to perform in aqueousalcoholic solvent mixtures d extension of the substrate and product scope to industrially viable biomass feedstock e process development with special emphasis on safety aspects process intensification as well as product isolation and catalyst recoverywith the proposed project the pi aims for paving the scientific route to novel lowcost biomass utilisation technologies with great promise for decentralised valorisation of biogenic waste
relatedness and the evolutionary pathway to worker sterility in ants

the sterile worker castes found in the colonies of social insects are often cited as archetypal examples of altruism in nature the challenge is to explain why losing the ability to reproduce has evolved as a superior strategy for transmitting genes into future generations the leading explanation for the evolution of worker sterility is the monogamy hypothesis the idea is that workers dont need to reproduce because they can transmit their genes indirectly by improving the reproductive success of the queen who carries the same genes for this to work the queen should be monogamously mated ensuring workers are raising full siblings the genetic equivalent of their own young r 05 there has been no appropriate test of this hypothesis however and an alternative hypothesis that worker sterility evolved via the enforcement of cooperation by policing has not been ruled out according to the policing hypothesis workers suppress each others reproduction by eating each others eggs or through aggression leading to sterility through evolutionary time crucially policing is predicted to evolve when relatedness is low in contrast to the monogamy hypothesishere i propose an interdisciplinary approach that combines a cuttingedge phylogenetic comparative analysis across 500 ant species with novel labbased experiments on the socially polymorphic ant formica exsecta to test between the low and high relatedness evolutionary pathways to worker sterility contrary to common belief workers in most ant species can lay eggs due to their haplodiploid sex determination system making them an ideal system for answering this question this project will fill a crucial gap in our knowledge of how complex life on earth evolved and potentially overturn the longheld hypothesis that high relatedness is the only route to cooperation
searching for oil spills on sea surfaces

oil spills rapidly spread on sea surfaces covering wide areas assuming different appearances and thicknesses the faster the actions to detect stop and contain the released oil from spreading the higher the oil spill response osr success rate since cleanup effectiveness is higher over thicker layers of oil referred to as actionable oil detecting these regions is crucial to enhance oil recovery efficiency thus minimizing environmental and socioeconomic impacts the objective of searching for oil spills on sea surfaces soseas project is to develop an artificial intelligencebased system to extract relative oil thicknesses by using multifrequency and multiresolution synthetic aperture radars sar aerial reconnaissance is currently the most common method to estimate the extent thickness and volume of oil spills however it is subjective biased and imprecise demanding welltrained experts to visually estimate the extent of an oil slick and distinguish different oil appearances conversely sar are keyoperational sensors for oil pollution monitoring offering a synoptic view over affected sites acquiring images during day and night regardless of weather conditions the use of sar data to detect the location and extent of oil pollution as well as to discriminate it from false alarms has been wellresearched however oil slicks characterization is underexplored but a promising new and highly innovative research area owing to the increasing availability of free sar data the development of powerful learning algorithms combined with highperformance computing advances an automatic system welltrained to recognize patterns related to qualitative thickness ranging will indicate the actionable oil regions these outputs can offer a less subjective and more precise oil pollution assessment than that of visual reconnaissance improving situational awareness in time to guide trustworthy decisionmaking during cleanup operations
challenges in competitive online optimisation

online decisionmaking characterized by the need to make decisions without knowledge of the future lies at the heart of numerous applications despite its prevalence our grasp of effective strategies for handling the associated uncertainty remains poor through the lens of the established framework of online algorithms as well as the emerging field of learningaugmented algorithms this project aims to address central challenges in decision making under uncertaintywhile there has been extensive research on online algorithms many of the fields core challenges remain unresolved however several recent discoveries of new algorithmic design and analysis techniques have opened up novel avenues for overcoming previous obstaclesalongside these technical advancements the rise of machine learning is now significantly enriching our toolset for dealing with uncertainty this has motivated the recent emergence of the field of learningaugmented algorithms here an algorithms input is augmented with predictions aiming for nearoptimal performance if predictions are reasonably good while still retaining classical worstcase guarantees even for highly erroneous predictionsinspired by these recent developments this project aims to substantially elevate our understanding of decisionmaking under uncertainty the main objectives are 1 to explore new directions around the concept of work functions 2 to elevate the mirror descent technique into a generic tool for online algorithm design 3 to develop universal techniques for designing learningaugmented algorithms and 4 to expand the scope of learningaugmented algorithms to new domainsthe project addresses questions at the forefront of theoretical computer science building on the pis recent success in resolving several longstanding problems and strives for foundational contributions to the timely issue of leveraging machinelearned predictions for improved algorithm design
experiencing access with interactive technologies

how is access experienced in interaction with modern technologies humancomputer interaction hci has a tradition of asking questions around functionality in the context of assistive and accessible technologies however the additional aspects of lived experiences with disabilities are often secondary to the questions and interests driven by nondisabled researchers this approach risks producing artefacts that might be functionally accessible but are deemed as undesirable unwanted or even harmful by disabled communities themselves with an increased move towards digitising aspects of our everyday lives there is an urgent need to understand the fundamentals of how access can be conceptualised implemented and flexible to situated engagements accesstech investigates the deeper theories behind access as a component affecting interaction with technologies for disabled people through participatory research through design drawing on the pis outstanding track record in critical analysis and participatory design practices within hci including 14 awardwinning papers we approach experiences of access along four paths of inquiry 1 we identify the needed research and design parameters enabling us to produce knowledges about accessenabling technologies 2 we establish which methods are required to design and develop critical technologies that are rooted in disability cultures as well as accepted and desired by disabled people 3 we explore a range of different technologies to understand how they afford different kinds of access experiences 4 we conceptualise and articulate access experiences as a distinct aspect shaping the interactive characteristics of modern technologies on a theoretical level each of these paths informs disability centred practices and theories in hci though collectively accesstech represents a fundamental paradigm shift in the ways we encounter disabilities and technologies