Dragon09/odtu_chatbot huggingface dataset:
radical improvement of cancer treatment without additional negative side effects

we have developed a device called hypercollar4d that significantly increases the effectiveness of radiotherapy for head and neck hn cancer the first results on 70 patients have proven that our technology yields 50 complete response with respect to radiotherapy alone the hypercollar4d is based on hyperthermia warming up the tumor to 43 c improves its sensitivity to radiotherapy hyperthermia yields no lasting toxicity unlike radiotherapy and chemotherapy the challenge with hyperthermia is delivering it effectively ie heating only the tumor and not the nearby tissues and costefficiently the hypercollar4d is the first device to achieve effective and costefficient hyperthermia treatments for hn cancer our technology called thermotherapy is protected by two patents one granted and one filed the hypercollar4d design is modular so it can be extended to add modules to treat other kinds of cancers sensius is a spinoff of the erasmus medical center
molecules as electronically open quantum systems

to control chemistry we must understand it and this requires a fundamental quantum mechanical description today we have a highly mature state of accurate quantum chemical modeling of molecules a central assumption in these models is that the molecules have a fixed number of electrons ie that they are electronically closed recent experiments show great promise for probing chemical understanding and inducing chemical reactivity by passing a current of electrons through the molecule hence quantum chemical models which can treat molecules as electronically open quantum systems are urgently needed the mission of openquantum is to establish the field of electronic wave function theory for electronically open systems i will establish highlevel models within the open quantum system formalism and develop it into a validated computational toolbox computationally efficient and versatile wave function implementations connected to multiscale environment models provide tools for investigating ground and excited state properties under open conditions i will provide a detailed theoretical and computational description of how molecules are modified through electric currents and explore possibilities that emerge in chemistry through fundamental knowledge of molecules as open quantum systems the new methodologies and insight that openquantum will bring are crucial to push the underlying understanding of excited states and redox stability of open molecules toward the use of electric current to catalyze and modify chemical reactions
timing the cosmic expansion with gravitationalwaves dark sirens from compact binaries to large scale structures

for 20 years measurements of the universe expansion rate from closeby and far sources are in tension hinting at the presence of new physics our struggle to study the universes expansion is due to the difficulty of observing cosmological sources for which the distance is known gravitational waves gws from compact binary coalescences cbcs are emergent cosmological probes that provide directly the distance of the source thus taking the name of standard sirens unfortunately they do not provide the other ingredient to measure the universe expansion the redshiftgravitysirens is an ambitious project aiming to measure the cosmic expansion with cbcs and exploit their link with the astrophysical environment to obtain implicit redshift information gravitysirens will focus on the population and astrophysical properties of gw sources that can allow a more precise measure of the cosmic expansion my team and i will exploit data delivered in the next 5 years from the gw detectors ligo virgo kagra the satellite euclid and arrays of radio telescopes such as hera meerkat and skao by using a mixture of population synthesis codes and semianalytical models we will jointly infer how fast the universe is expanding and how cbcs relate to galaxies and largescale structures lss we will use stateoftheart technologies such as machine learning and graphical process units to construct efficient algorithms for population analyses and use scientific data delivered in the upcoming years gravitysirens will provide the most accurate and precise gwbased measures of the universe expansion and measure the link between cbcs galaxies and lsss on one hand the cosmic expansion measures that gravitysirens will provide can potentially lead us to the discovery of new physics at cosmological scales on the other hand inferring the relationship between cbcs galaxies and lss tracers will point us to the processes acting for compact object formation
development of novel multimodal dextranbased theranostic tracers targeting fibroblast activation protein as proof of concept

according to who cancer is a leading cause of death worldwide accounting for nearly 20 million new cases and 10 million deaths in 2020 this project addresses the development of a novel compound targeting the fibroblast activation protein overexpressed in more than 90 of human epithelial cancers it combines up to four imaging techniques singlephoton emission computed tomography positron emission tomography magnetic resonance and optical imaging and two therapeutic approaches radionuclide therapy and boron neutron capture therapy bnct the novel compound is based on a dextran scaffold which acts as a backbone for attachment of i a fapinhibitor based on a quinoline structure ii a macrocycle chelator for complexation with gadolinium technetium99m rhenium188 gallium68 and lutetium177 for imagining or radionuclide therapy iii carborane for bnct and iv fluorescent dye for optical imaging the aim is to achieve a tailormade combination of unique and versatile properties by adapting the multifunctional structure of the ligand compound throughout different imaging and therapeutic procedures using a simple and robust labeling protocol exploiting the outstanding properties of each moiety and conferring our compound with precisely designed functionalities the implementation and delivery of highimpact outcomes will be achieved following a welldefined route the longterm objective of this project is to determine whether vial kits for imaging and therapy can be developed the novel ligand will be synthesized following wellestablished methodologies and fully characterized by elemental analysis ir and nmr then the radiolabeling procedures of the ligand with the radionuclides will be optimized and a kit formulation will be developed at the same time the project will determine the inhibitory activities of the radiolabeled compounds and their applicability for in vivo imaging and radionuclide therapy in fappositive tumorbearing mice
infrared fiber analysis of battery electrolyte dynamic chemistry

as global energy demands escalate and the use of nonrenewable resources becomes untenable renewable resources and electric vehicles require far better batteries to stabilize the new energy landscape to maximize battery performance and lifetime understanding and monitoring the fundamental mechanisms that govern their operation throughout their lifetime is crucial unfortunately from the moment batteries are sealed until the end of their life they remain a black box and our understanding of the health status of commercial batteries is limited to measurements of current voltage temperature and impedance at the cell or even module level during use however the landscape has recently evolved with the integration of optical fiberbased sensors into batteries providing unprecedented insights into their thermal and mechanical properties a significant breakthrough in this trajectory is the successful integration of infrared fiber evanescent wave spectroscopy irfews into commercial naion cells this achievement enables realtime monitoring of battery chemistry dynamics during operation marking a paradigm shift in battery design with the potential for enhanced performance extended lifespan and enhanced reliabilityinfralytics aims to explore the myriad of opportunities opened by this advance the initiative kicks off by integrating chemical monitoring using irfews into battery cells delving into the evolution of electrolytes and the formation of parasitic productsbe they soluble solid or gaseous through a synergistic approach involving optical fiber design electrochemical data generation and datadriven modeling the project strives to develop a technology capable of bridging complex degradation phenomena with batteries longterm performance by addressing current knowledge gaps infralytics aims to position the eu research and industry to produce more efficient and durable batteries thereby contributing to a more sustainable future
in cellular conformations of microrna34a via magnetic resonance

microrna34a mir34a is misregulated in 75 of cancers and is considered a promising drug target in a recent clinical trial mir34a was used against terminal liver cancer showing promising result with remission of 3 patients however mortality remained high and was attributed to its ability to target multiple mrnas project economics will investigate this issue by elucidating the underlying structure and dynamics of multiple mir34amrna complexes using nmr spectroscopy and molecular dynamic simulations this will provide information about the conformation of mir34a which is mrna specific this can further be stabilized by mutations to increase target specificity of mir34a leading to an improvement in clinical trial results mir34a targets and binds the 3untranslatedregion 3utr of 100 mrnas via the rnainduced silencing complex resulting in downregulation of the associated genes recently it was discovered that mir34a attains a high energy excited state es conformation for mrna encoding gene sirt1 stabilizing this es resulted in a twofold increase in gene repression can mir34a have a similar es for other genes implicated in various cancers this will be studied by exploring the structure and dynamics of mir34a when complexed with 3utr of the mrna encoding the genes hnf4a notch1 notch2 dll1 and wnt1 cellular environment is proposed to affect the es of mir34a therefore a detailed conformational landscape of mir34amrna complexes will be mapped by comparing both in vitro and in live human cells cancerous and noncancerous this study will provide targeting rules for microrna within the cell and insight into its regulatory mechanism this information will improve the efficiency rna based drug development giving a competitive edge to eus pharmaceutical industry and ultimately realizing europes beating cancer plan to achieve longterm survival of 70 patients with cancer by 2035
virus inhibition by sirna optimized by nmr

the last two years profoundly marked by the covid19 sanitary crisis have demonstrated the difficulties to answer adequately to the emergence of novel pathogenic viruses today no broadspectrum antiviral exists similar to antibiotics targeting bacteria repositioning of existing molecules had limited success despite intense initial hopes vaccines have played a major role in fighting the pandemic and limiting the impact of the virus however it remains insufficient to end the pandemic due to many factors including their worldwide uneven accessibility their intrinsic efficiency towards different variants and the complex sociopolitical context related to mass vaccination there is therefore an urgent need of novel approaches to design molecules targeting viruses and in particular sarscov2 to answer this challenge we propose a novel strategy derived from fundamental research on small interfering rna sirna this project derives from the erc starting grant paramir in which novel structural biology approaches are proposed to understand the mechanism of recognition of a similar class of rna involved in numerous diseases especially cancer our approach combines the latest advances in sarscov2 virology and structural biology to propose efficient and specific molecules active towards a broad range of sarscov2 current and future variants if successful the project will lead to a class of sirna with optimized specificity and stability validated in vitro and exvivo in a reconstituted human airway epithelial model and ready for testing towards preclinical and clinical stage finally the strategy proposed here will be on a longer term applicable to multiple other pathogenic viruses
the sesar 3 knowledge transfer network

based on the experience of the previous engage knowledge transfer network ktn it will support the sesar 3 joint undertaking s3ju and contribute to the development and implementation of the sesar digital academy sda created by sesar 2020 joint undertaking in order to train and inspire the next generation aviation workforce in anticipation of the digital economy in particular the consortium will build on the platform of engage ktn engage taking forward the success story of its previous 45 years of work drawing on lessons learned and complementing the partnership with invaluable new partners engage 2 will build on the existing brand and awareness of the engage ktn to deliver excellence across the elements of the expected outcomes as delineated taskbytask through this proposal lean and efficient implementation from a tightly knit and highly effective consortium whilst ensuring experienced and competent delivery has enabled engage 2 to maximise its potential and outreach into the atm community and beyond both directly through maximised externalised budget eg through phd funding and catalyst funds and indirectly eg through continued development of the engage knowledge hub or wiki and its multiple resources engage 2 will deliver crossfertilisation of knowledge from other disciplines to stimulate inputs from innovative futurescoping and unconventional research into the domain of atm a focal point here is the atm concepts roadmap which will be developed further as a core element of the engage wiki the ktn will continue to forge strong links between research at the leading edge of apposite fields and establish alignment and synergies with the operational challenges facing sesarthis will be achieved across multiple activities and underpinned by the thematic challenges a key success story of the engage ktn
a coupled finite element framework for multiphysics environmental flows

hydrocouple proposes to develop 1 a new coupled finite element fe method for environmental flows 2 goaloriented adaptive mesh refinement strategies and 3 to apply the new techniques to physical watersheds for verification of its capabilities as well as to demonstrate these the project is a collaboration between three researchers the applicant eirik valseth currently at the university of texas at austin prof kentandre mardal the university of oslo and prof ethan kubatko the ohio state university many current approximation techniques for multiphysics phenomena where two or more models partial differential equations govern the physics focuses on the approximation of these as separate phenomena and prescribe appropriate interface conditions to exchange information between the models recent attention has been given to monolithically coupled methods kuchta et al 2021 where all models are approximated simultaneously thanks to careful algorithm design and numerical analysis hydrocouple will extend the theory of these monolithic coupling schemes to environmental flow problems and develop a fe framework for their corresponding numerical approximation this developed framework can subsequently be applied in flood prediction and hydropower production planning as the models in environmental flows govern both overland and riverine flows which are critical in both applications hydrocouple will also develop meshadaptive refinement techniques based on goaloriented error estimation to ensure the high fidelity of its numerical approximations finally the proposed framework will be verified against available data for existing watersheds to demonstrate its efficiency and accuracy to end users in industry and government working in the section of mechanics at the department of mathematics with a world renowned scientist will provide a perfect setting to integrate my knowledge and start my research career in europe
point of care diagnostic solution for definitive differentiation of true and false threatened preterm labour cases

threatened preterm labour tptl is the leading cause of preterm births and hospitalization during pregnancy with 45m cases annually treatments and resources are not being properly allocated towards the patients who need them efficient diagnosis of tptl is the key to optimizing treatments but current methods are ineffective at detecting true eventsinnitius has developed fine birth the first noninvasive poc diagnostic device that uses torsional waves and ai to directly measure a patients cervical tissue consistency to identify the risk of tptl in realtime it is objective accurate fast and can be operated by staff with minimal trainingwe have reached trl6 testing the prototype in a multicentre clinical study with 300 patients in 7 sites we need 25m to fully develop and validate our ai software do a multicentre pivotal clinical trial and obtain regulatory approval which we will be able to finalise with the support of the eic
science for global challenges

science for global challenges is the motto to engage general public especially young students with research activities and scientific knowledge that may answer to major world and european challenges related to environmental economical and social sustainability this proposal intends to directly respond to responsible research and innovation rri goals of the eu framework program by raising public awareness also among school communities about the relevance of science to assure resources preservation green economy decarbonization social equity and inclusion while bridging the gap between scientists and society giving researchers the opportunity to perceive the main concerns of citizens and how those understand their work schools and their students will be involved in activities during the whole project in order to ensure scholar impact icluding the younger by increasing public and students outreach sciglo will contribute simultaneously for two main objectives i improving the understanding of the importance of scientific careers development and science investments ii increasing researchers understanding of the role of society as a whole for sustainable science policies developmentthe consortium of this project is coordinated by the university of lisbon through the national museum of natural history and science and combines efforts between researchers of major universities in portugal including four urban areas from north to south the university of minho the international iberian nanotechnology laboratory the university of vora the university of coimbra and the lisbon university institute for the impact assessment nova university in lisbon will coordinate a special program targeting school communities and the superior school for tourism in estoril will contribute to disseminate food security practices the lisbon municipality is a central partner for the engagement of diverse audiences and civil society stakeholders
enabling one health coastal management through advanced ai over marine copernicus and citizen science data

coastal zones comprise just 20 of the earths surface yet this transitional area between land and sea is of major environmental economic and social importance however they are also home to 45 of the entire human population given their exposure to anthropogenic and climate change pressures they are currently one of the most threatened environments on earth enhance will leverage copernicus marine service to monitor marine biodiversity and coastal water preserving atrisk ecosystems the project will adopt an one health approach encompassing services for the impact assessment of water quality in biodiversity public health and the environment more specifically enhance will engage all relevant stakeholders affecting and being affected by the degradation and evolution of coastal marine ecosystems to identify and analyze the stakeholder needs to support effective decision making for sustainable climate resilient coastal areas additionally a robust data collection and fusion infrastructure will be built for enhance to allow realtime data communication from a variety of information sources including copernicus data egnss services citizen science etc the project will enable the development of new products integrating copernicus and citizen science data services to provide more dynamic information both pressures and impacts and support policy makers and businesses in sustainable coastal management more specifically enhance will deliver 3 new products to analyse the urban agricultural and climate extremes pressures in coastal areas as well as their impacts following the one health framework enhance will be validated in 2 case studies in the mediterranean on barcelonas urban beach and pagasitikos gulf these two areas were chosen because of the touristic and anthropogenic pressures of barcelonas ecosystem and the latter because of the high climate change pressures resulting from the recent floods in the region of thessaly
extreme food risk analytics

efra will explore how extreme data mining aggregation and analytics may address major scientific economic and societal challenges associated with the safety and quality of the food that european consumers eat efras goals are i develop and test solutions to discover and distil food risk data from heterogeneous and dispersedscarce data sources with minimal delay and appropriate format ii design relevant human aspects interactions with users to measure usefulness for human risk prevention actions in realworld usecases iii demonstrate how solutions enable the development of trustworthy accurate green and fair ai systems for food risk prevention iv achieve groundbreaking advances in performance and effectiveness of food risk data discovery collection mining filtering and processing v integrate relevant technologies big data iot ai to foster links to food data innovator communities vi position its contributions into the overall ecosystem of public private stakeholders that share data technology and infrastructure to ensure the safety and quality of food in europe to achieve these goals efra will design test and deploy tools and undertake appropriate initiatives to facilitate their uptake elicit feedback and engage stakeholders the efra tools are i efra data hub offering intelligent crawlers and data annotation linking modules to search mine process annotate and link dispersed multilingual heterogeneous and deephidden food safety data sources ii efra analytics powerhouse offering modules running over a green cloud hpc that distil useful insights signals from the efra data hub to train privacypreserving explainable green food risk prediction ai models iii efra data analytics marketplace a frontfacing userfriendly web app that allows interested users to discover purchaseuse and contribute data ai models and analytics modules creating an economy where data holders and data consumers engage and trade