Dragon09/odtu_chatbot huggingface dataset:
human collaboration with ai agents in national health governance organizational circumstances under which data analysts and medical experts follow or deviate from ai

this project will study a multisited ethnography of a currently evolving revolution in global health systems big dataaiinformed national health governance with health data being considered countries future oil public and scholarly concerns about algorithmic ethics rise research has long shown that datasets in ai reproduce social biases discriminate and limit personal autonomy this literature however has merely focused on ai design and institutional frameworks examining the subject through legal technocratic and philosophical perspectives whilst overlooking the sociocultural context in which big data and ai systems are embedded most particularly organizations in which human agents collaborate with ai this is problematic as frameworks for ethical ai currently consider human oversight crucial assuming that humans will correct or resist ai when needed while empirical evidence for this assumption is extremely thin very little is known about when and why people intervene or resist ai research done consists of single mostly western studies making it impossible to generalize findings the innovative force of our research is fourfold 1 to empirically analyze decisive moments in which dataanalysts follow or deviate ai moments deeply impacting national health policies and individual human lives 2 to do research in six national settings with various governmental frameworks and in different organizational contexts enabling us to contrast findings eventually leading to a theory on the contextual organizational factors underlying ethical ai 3 to use innovative anthropological methods of futurescenarioing which will enrich the anthropological discipline by developing and finetuning futurefocused research 4 the research connects anthropological insights with the expertise of aidevelopers and partners with relevant health decisionmakers and policyinstitutions allowing to both analyze and contribute to fair ai
detection of chronic toxicity of xenobiotes using pandoraseq of small nonconding rnas

the xenoseq project aims to develop tools for detecting epigenetic changes caused by chronic toxicity of chemicals by sequencing small noncoding rna sncrna profiles xenobiotics including herbicides like glyphosate have raised concerns regarding their possible effects on human and environmental health but chronic and especially transgenerational effects are often ignored due to limitations of time and resources this research project seeks to study whether the newly developed pandoraseq unveils subtle changes in sncrna profiles that may serve as early indicators of chronic toxicity pandoraseq utilizes two rna modifying enzymes t4 polynucleotide kinase and alkb demethylase to extend the repertoire of detected sncrnas to an unprecedented world comprehensive sequencing of sncrna profiles may reveal chronic toxicity associated with xenobiotic exposure here we aim to 1 characterize baseline sncrna profiles in healthy systems offering a reference point for comparison 2 expose biological systems to potentially toxic agents and track changes in sncrna expression using pandoraseq and 3 detect early indicators of chronic toxicity allowing the development of a complementary tool for the assessment of chemical toxicity pandoraseqs precision and sensitivity make it a promising tool for studying epigenetic regulation which may cause chronic and transgenerational diseases as this msca project is a first effort to use sncrna for chronic ecotoxicology we open the research field by using the fruit fly as a model organism but the technique can be easily adapted for studying other relevant organisms such as honey bees and mammals
researcher night bringing researchers into the light

with this project we want to bring the figure of the researcher and his work closer to the entire society for this reason we organize events in diferent areas of the country we carry out actions in educational centers and we will organize activities in rural areas disadvantaged neighborhoods activities for people with special needs and specific activities of interest for elderly people we want to include all areas and audiences of society to do this we present this project between 2 coordinators and an associated entity that complement each other we include an entity with great experience in this project and actions to disseminate and bring science closer to society in general and an entity with a national dimension which covers the field of culture research and education throughout the country all this is complemented by the participation of an associate the spanish association against cancer that combines research and dissemination at the national level
delox air continuous air biodecontamination compatible with human presence

we learned from the pandemic that air quality is essential for peoples health current technologies did not effectively manage infectious diseases propagated by aerosol suspensions of pathogens leading to the need for social distancing and dramatically impacting the economy and peoples mental health the challenge is not only cleaning the space but keeping people safe and free from microorganisms exposure without harming them with harsh chemicals delox air solution will change the paradigm of biodecontamination of airborne pathogens in occupied spaces a disruptive factor in the market based on our proprietary dryvhp delox air can kill microorganisms in the air with 9999 efficacy ensuring 100 human safety and consuming up to 20 less energy than current systems delox air can be readily integrated into any hvac systems for continuous air purificationdelox air is part of the air purification market we are targeting the commercial applications that capture the largest market 70 in 2021 accounting for 150 b by 2030 we will first target settings characterised by high occupancy density presence of vulnerable individuals and elevated risk of pathogen spread such as nursing homes and hospitals office spaces and educational and governmental buildingsour business model b2b is based on indirect sales through distributors already working in the sector that will easily reach hvac consultantscontractors customer designing and delivering a turnkey hvac system for the enduser we request eic funding to complete the development of our system and validate it in three different types of closed environments our solution addresses the eic challenge of aerosol decontamination for pandemic management satisfying the unmet need of facilitating social interaction and preventing disease spread
policy recommendations to maximise the beneficial impact of unexplored mobilities in and beyond the european union

premiumeu will develop a regional policy dashboard rpd for policy makers in vulnerable regions to help them formulate policies to use the potential of mobility to enhance regional inclusive growth and wellbeing it is an evidence based tool where policy makers are offered tailormade selections of policies that reflect the mobility and regional development profiles of their region the dashboard contains three modules that contain state of the art euwide regional qualitative and quantitative information a mobility module mm a regional development effects module rdem and a policy module pm the mm covers both past current and future trends forecastsscenarios in constructing past and current patterns and trends innovative methodologies will be used that combines traditional migration statistics with novel geocoded data from social media usage moreover mobility flows will tae into account the human capital dimension which allows to study brain drain and brain gain processes and mismatches on the labour market such as evidenced in labour exploitation of migrant workers filling the lowest sports of the labour marketa typology of regions based on the mix of different types of mobility will be developed the rdem uses a multidimensional definition of development covering not only economic but also social and cultural aspects a typology of regions based on the multidimensional set of regional development indicators will also be developed causal modeling of mobility and regional development will point at the key drivers of mobility relevant for development and the reverse relation of the key regional determinants of inward and outward moves the pm will choose a palette of relevant policies for the user based on the regional profile in the mobilityregional development typology users will also be given the opportunity to feed their experiences into the rpd
unveiling atomicscale elemental distribution of electrodeelectrolyte interfaces and interphase in batteries

developing highenergydensity rechargeable battery technologies is essential to solve energy and environmental problems however its development is currently impeded by a poor understanding of elementary processes occurring at electrodeelectrolyte interfaces several longstanding issues such as short cycle life low coulombic efficiency and hazardous dendrite formation in batteries cannot be fundamentally solved due to the knowledge gap the bottleneck is that interfacial chemistry on the atomicscale is as yet unresolved owing to the lack of sufficiently suitable analytical capabilities i will address this gap using atom probe tomography coupled with a highly innovative cryogenic sample preparation and transfer platform to provide atomicscale insights into solid electrolyte interphase sei formed at the electrodeelectrolyte interface the key open questions to answer are i what is the composition and elemental distribution in a stable sei ii how do ions in the electrolytes affect sei formation iii how does stable sei inhibit dendrite formation my goal is to advance fundamental understanding of sei formation establish its structureproperty relationships and elucidate its interplay with other elementary processes occurring at electrodeelectrolyte interfaces in a lithium metal battery model system i will i reveal elemental distribution and compositional details of sei inunder different electrolytes and working conditions ii unveil compositional evolution of sei and the electrolytes during charging and discharging and iii interrogate their roles in dendrite formation in a half and full battery cell respectively these unique data will shed atomistic insights into how to tailor sei and electrodeelectrolyte interfaces to mitigate longstanding issues furthermore the novel cryogenic platform is not systemspecific and will be applicable for studying other liquid or solidstateelectrolyte battery technologies
green technologies for 56g servicebased architectures

the 6green project aims to conceive design and realize an innovative servicebased and holistic ecosystem able to extend the communication infrastructure into a sustainable interconnected greener endtoend intercompute system and promote energy efficiency across the whole 56g valuechainthe ultimate objective is to enable and to foster 56g networks and vertical applications reducing their carbon footprint by a factor of 10 or moreto achieve this objective the project will exploit and extend stateoftheart cloudnative technologies and the b5g servicebased architecture with new crossdomain enablers to1 boost the global ecosystem flexibility scalability and sustainability and 2 enable all the 56g stakeholders from the ones acting at the infrastructure and network platform to vertical industries reducing their carbon footprint by becoming integral parts of a winwin greeneconomy business and meeting a decarbonization service agreementthe 6green intentbased crossdomain interactions among stakeholders will allow achieving a tight proportionality between the timevarying and geographically distributed mobile workload produced by vertical applications and network slices and the energycarbon footprint induced to the 56g network and computing infrastructure continuum 6green will provide stakeholders with flexible and green artificial intelligence mechanisms that will allow propagating the environment impact to any players acting on virtual domains and triggering zerotouch operations according to customizable energy and carbonaware policies allowing to optimally use renewable energy sourcesthe project will also deliver three futureproof usecase applications that will provide a diverse awareness of the green capabilities of the 6green platform and that will demonstrate the potential 56g impact in enabling other vertical industry sectors to reach the carbon neutrality targeted by the european green deal
digital twinning for personalized atrial fibrillation care

the goal of the twincareaf project is to develop innovative core methodologies for accurate and realtime calibration of cardiovascular electrophysiological models and to support medical decisions in the context of atrial fibrillation and catheter ablation therapy planning the proposed approach will focus on the generation of digital twins of patient hearts calibrated through robust and efficient machine learning techniques and able to replicate measured clinical data such as electrocardiogram and electrogram recordings specifically physicsinformed andor deeplearning techniques will be extended and implemented within the context of anatomicallyaccurate and biophysicallydetailed cardiac electrophysiology to accelerate the solution of classical forward electrophysiological model and to solve inverse problems for identifying patientspecific physical and tissue properties of the heart additionally a robust methodology for verification validation and uncertainty quantification will be adopted to showcase the agreement between model predictions and empirical observations and to provide reliable estimates of confidence in the model predictions the developed approach will be used to predict atrial fibrillation progression and determine potential ablation sets for individual patients the predictions of the developed model will undergo testing through in vivo intraoperative clinical measurements to enhance easy flow robust analysis and interpretation of patientspecific data the novel realtime mathematical workflow for atrial fibrillation simulations will be integrated into a clinically viable platform these tasks will leverage leadingedge mathematical methodologies improve the observationtodiagnosis clinical process by efficiently handling patientspecific data and support therapy planning ultimately enabling a scalable translation to large population cohorts
fullfield experimental and numerical investigation of novel fire resistant fibre reinforced concrete for tunnel lining

the problem of tunnel fires is one of the most complex areas of fire research under fire concrete linings spall resulting in the collapse of the tunnel structure causing a significant scourge in the economy society and the environment in summary the design of tunnel concrete linings is based on thermal calculations which ignore spalling based on such calculations new types of more durable strong and hence denser concrete have been introduced on the market recently that are much more probable to spall due to their lower permeability to increase the permeability of the concrete and ultimately its fire resistance it is commonly suggested to add polypropylene fibres however these tend to decrease the strength of the concrete and potentially its durability in fire2c i propose a new type of fire resistant fibre reinforced concrete to improve on the tunnel linings performance and ultimately the postfire structural stability of the tunnel to enhance our understanding of the performance of the concrete on a multiscale level i will employ a holistic approach between stateoftheart numerical discrete element method and fullfield experimental methods advanced material and fire testing xray computed tomography pushing the existing boundaries of our scientific knowledge specifically i will study experimentally the effect of size distribution and orientation of the fibres on the strength and fireresistance of concrete linings by employing fullfield imaging techniques pre and postfire which has not been done before and finally i will create a novel dem model to predict the thermomechanical response of fibrereinforced concrete utilising for the first time quantitative 3d experimental measurements at different lengthscales to validate accurately the material response
using deep learning to understand computations in neural circuits with connectomeconstrained mechanistic models

advances in experimental techniques yield detailed wiring diagrams of neural circuits in modelsystems such as the drosophila melanogaster how can we leverage these complex connectomes together with targeted recordings and perturbations of neural activity to understand how neuronal populations perform computations underlying behavior achieving a mechanistic understanding will require models that are consistent with connectomes and biophysical mechanisms while also being capable of performing behaviorally relevant computations current models fail to address this need mechanistic models satisfy anatomical and biophysical constraints by design but we lack methods for optimizing them to perform tasks conversely deep learning models can be optimized to perform challenging tasks but fall short on mechanistic interpretabilityto address this challenge we will provide a machine learning framework that unifies mechanistic modeling and deep learning and will make it possible to algorithmically identify models that link biophysical mechanisms neural data and behavior we will use our approach to study two key neural computations in d melanogaster we will build largescale mechanistic models of the optic lobe and motor control circuits which are constrained by connectomes and physiological measurements and optimize them to solve specific computational tasks extracting behaviorally relevant information from the visual input and coordinating leg movements to achieve robust locomotion our methodology for building interpreting and updating these deep mechanistic models will be applicable to a wide range of neural circuits and behaviors it will serve as a powerful hypothesis generator for predicting neural tuning and optimizing experimental perturbations and will yield unprecedented insights into how connectivity shapes efficient neural computations in biological and artificial networks
decision making methodologies for optimal design and operation of energy systems

the central challenge in energy systems is to balance costefficiency environmental responsibility and living standards multiobjective optimization in such systems is critical for striking compromises among stakeholders and ensuring competitiveness and sustainability as energy systems face uncertainty volatility and environmental regulations holistic optimization becomes more criticalhowever three main challenges currently hinder energy system optimization complex models demanding substantial computational power a lack of holistic and robust approaches and the use of realtime data for proper operation and analysis although each of these challenges has been addressed individually no contribution was able to bring them all together in a consistent methodological framework this is the main objective of this fellowshipthis fellowship will be conducted at istuniversity of lisbon under the supervision of prof henrique matos and aims to bridge these gaps by integrating machine learning systems optimization uncertainty analysis and realtime operation it seeks to develop advanced surrogate generation techniques emphasize system integration and holistic analysis optimization under uncertainty and the use of realtime data for operation these methods will be applied to real industrial challenges in an industrial secondment this research project will develop methods and tools to address such challenges and contribute to a sustainable profitable and responsible european economy
japan and europe network for neutrino and intensity frontier experimental research 3

jennifer3 aims to continue further develop and finalize the research and communication activities started in 2015 within the jennifer project and currently being carried on by the jennifer2 mscarise project which will conclude in may 2025 the community forming the jennifer3 consortium is putting together three research programs at experimental facilities located in japan where very rare processes can be observed accelerator produced neutrinos t2k and hyperk collaborations cosmic neutrinos detection hyperk collaboration and a high luminosity electronpositron collider belle ii experiment at superkekb such programs use different approaches are sensitive to different messengers of the new physics world and are essential to complement the so called energy frontier investigation which is carried on at the lhc sinergy and knowledge sharing among them is the drive force of the jennifer3 project which on one hand fosters the collaboration of european scientists with the japanese research community while on the other hand promotes close collaboration among different european research groups around key technologies such as cloud computing and data network developments machine learning applications for data filtering and reconstruction photon detection solid state detectors particle beam monitors collaboration with private sector technology providers is also essential to reach the scientific objectives of the project all project members are also committed to disseminate and communicate their work to the scientific community and to the european society through various initiatives aiming to different targetscross fertilization between different research communities and approaches is the real added value to boost the project impact both in terms of scientific results and of researchers careers
expanding immune cells and their tumor antigens during checkpoint immunotherapy

cancer immunotherapy using immune checkpoint blockade icb has revolutionized the treatment of advancedstage cancers one of the major limitations of icb is that durable responses are observed only in a subset of patients and in some specific cancer types we recently analyzed tumor biopsies from breast cancer patients collected during icb and indeed observed only in a subset of patients that tumorinfiltrating tcells undergo rapid expansion when exposed to icb we characterized the gene expression programs underlying this expansion at singlecell level and realized that although these expanding tcells are the main executors of therapeutic response to icb several key questions regarding their function remain unanswered first we lack accurate knowledge about where in the heterogeneous tumor microenvironment tme and in which metabolic niches tcell expansion occurs secondly based on their tcr sequence we cannot predict upfront which tcells will expand or rather act as bystander tcells nor can we say to which tumor antigens these expanding tcells are directed thirdly it is not known which molecular events underlie the generation of the tumor antigens regulating tcell expansion fourthly we also observed an expansion of the bcell repertoire and were left with similar questions as for expanding tcells for instance where are expanding bcells located how do they interact with expanding tcells and do they perhaps even recognize the same tumor antigens in expand it we will use several innovative singlecell technologies to provide answers to these questions these insights will much better characterize the mechanisms driving response to icb but will also provide important answers on how to sensitize patients not responding to icb our findings could also contribute to the discovery of highavidity antitumor tcrs that can be used in novel tcrbased cellular therapies