Dragon09/odtu_chatbot huggingface dataset:
an enhanced drug delivery system for brain cancer treatment which will be tested by human cellbased 3d in vitro microfluidic system

cancer treatment by current clinical methods has many side effects which result from the nonspecificity of these methods moreover treatment of some cancers such as brain tumors is extremely difficult because the brain barriers bloodbrain barrier bbb and blood tumor barrier btb prevents more than 98 of drugs from entering the brain the use of stimuliresponsive nanomaterials for cancer therapy is more efficient than conventional ones due to access to targeting tissues deep molecular targets lower side effects and controlled drug release mesoporous silica nanoparticles msns are widely used nanocarrier for drug delivery due to their unique physicochemical properties however the lack of consideration of the economic efficiency of msns synthesis their surface modification methods and the lack of use of physiologically relevant systems to test the efficacy and safety of msns have caused that an effective and definitive cancer treatment method by msns has not been provided so far in this project we aim to solve these problems and make the use of msns for therapeutic approaches realistic the goal of this project is to develop a biosourcederived stimuliresponsive msn for combined pdt chemotherapy of brain tumors to be evaluated in a physiologically relevant human cellbased 3d in vitro brain tumor microfluidic system this project will be the first to investigate a combination therapeutic agent based on natural products modified with advanced plasma technology and evaluated in a novel human cellbased 3d microfluidic in vitro system that includes the bbb outcomes of this project will enhance the existing knowledge and technologies for msns synthesis modification and their cancer treatment performance evaluation which will yield highimpact journal publications as well as potential commercial product in the long term
augmenting and evaluating the physical and digital infrastructure for ccam deployment

augmented ccam aims to understand harmonise and evaluate in an augmented manner adapted and novel support solutions of physical digital and communication pdi infrastructure to advance its readiness for large scale deployment of ccam solutions for all the project will elaborate extend and harmonise pdi classification and support levels mapping codetermined pdi priority requirements and adaptations based on this and by deploying an open sharing technology agnostic service operational framework and architecture for pdi enabled ccam addressing all ccam actors via multicooperation models the project will develop 11 pdi support solutions aiming at tlr 67 that will apply and evaluate in different configurations in seven 7 test sites across three 3 european countries france latvia spain encompassing a vast spectrum of physical living labs closed areas open traffic highway urban and periurbanrural environments and virtual dt av driving simulators test beds ai and big data advanced techniques and crowdsourced hd maps will leverage the whole transport system and its users situational awareness prediction and actuation the different test activities findings supported by micro and macroscopic traffic simulations will allow the assessment of different pdi support on functional safety of the whole transport infrastructure on traffic safety and efficiency driving behaviour environmental footprint service reliability trust security considering the socioeconomic benefits and costs of all actors and the issue of roadmap and recommendations proposing riskaversion decision making tools and methodologies for policy making and ccam ready infrastructure investments augmented ccam coordinated by fehrl consists of a multistakeholder consortium of 26 partners from 12 european countries and one associated partner from switzerland roughly 50 of them are firms 30 industries 50 of which road operators and 185 of them smes
cavity quantum electrodynamics control of magnetic phases in twisted van der waals heterostructures

to further increase performance and reduce energy consumption in technological devices a new paradigm is needed exploiting quantum mechanical phenomena an attractive route to enter this paradigm is by interfacing light and magnetic excitations in new optomagnetic devices which ensures processing frequencies comparable with electronics and hold great promise for future memory spintronics and quantum computing devices this however requires a deeper understanding of strongly coupled lightmatter systems and the interplay between magnetic electronic photonic and lattice excitations a promising platform to explore exotic magnetic phenomena is magnetic van der waals vdw materials since the competition of anisotropy quantum fluctuations and spinorbit coupling make these materials prime candidates to host such states and susceptible to material engineering techniques this can be exploited in cavity quantum electrodynamics cqed and moir engineering to control the magnetic state by combining cqed with moir engineering the goal of cavitymag is to construct schemes to control the magnetic state of vdw materials and to induce exotic magnetic phases this will be achieved by developing stateoftheart computational tools based on quantum electrodynamical density functional theory qeddft in combination with effective spinphoton models this computational framework will be used to perform a systematic study of lightinduced magnetic phases in twisted vdw materials to gain a deeper understanding of how microscopic magnetic interactions can be modified and to establish concrete protocols to control the macroscopic magnetic state it will also be used to guide experimental efforts by identifying candidate materials and parameter regimes likely to host exotic states of great promise for the construction of new high performance and energy efficient technological devices
european union contest for young scientists eucys 2024

this proposal concerns the organization of the 35th european union contest for young scientists eucys which will be held in katowice poland in september 2024the european union eu contest for young scientists eucys is the most important student science fair in the eu showcasing the best of student scientific achievement in the eu and beyond each year the event brings together promising talented students bright young minds 1420 years old from all over europe and beyond to present their projects to a panel of international judgesthe competition helps promote science and research and draws attention to young talents in european and global countries during the competition young scientists have the opportunity to meet other participants with similar interests confront their project with other young scientists activities and talk with the judges the most prominent scientists in europe the eucys competition works to attract young people to careers in science and technology
novel antibiotics from antarctic microbes

microbial resistance to antimicrobial compounds has become one of the biggest threats to global health the inability to treat infectious diseases poses a severe threat to human health and the costs associated with antimicrobial resistance amr are immense the severity of amr is emphasized by implementing the fight against amr into major goals of the united nations european union or world health organization one of the major issues with amr is the longterm decline in the development of novel antibiotics thus new antibiotics are urgently needed microbes living in the harsh condition of antarctica represent a promising new source that is worth exploring for new antibiotics recent studies showed a significant genetic divergence of antarctic microbes from other microbes worldwide and suggested the enormous potential of these microbes to produce novel bioactive metabolites therefore the main goals of this project are devoted to the characterization of the overall biosynthetic potential hidden within different antarctic microbial communities through identification of a broad spectrum of the biosynthetic gene cluster bgc determination of their diversity phylogeny and environmental distribution followed by target genome mining for the discovery of bgc producing new antibiotics the acquired knowledge will then be used for the heterologous expression of antibiotic bgc in a suitable host followed by compounds isolation bioactivity verification and the elucidation of the structure to pursue the raised objectives interdisciplinary methods will be integrated such as bioinformatics molecularsynthetic biology and analytical chemistry such an interdisciplinary project will provide the applicant with excellent training in both scientific and transferable skills together with the applicants participation in the excellent national and international network of the supervisor prof ziemert will significantly enhance the applicants career perspectives
holistic unified certification approach for novel systems based on advanced automation

the hucan project addresses legal and regulatory challenges of an atm environment with higher levels of automation coherently with the sria that advocates the need for new methodologies for validation and certification of advanced automation that ensure transparency legal aspects robustness and stability under all conditions and take full consideration for a future atm environment built on multiple aialgorithms system of systems with a humancentric approach the hucan project proposes a novel approach for certification and approval of new atmrelated airborne and ground systems embedding higher levels of automation including those based on ai and ml the proposed approach is intended to support both the approvalcertification and the design phases of such technologies developing to this end two interconnected products 1 a new holistic and unified certification method for highly automated systems whose main target users are easa national aviation authorities qualified entities and ansps and 2 a set of suitable design guidelines and associated toolkit for streamlining the development of automation and aipowered technologies targeted to manufacturers for the design and development of such products the project will review the most prominent trends and challenges in automation and ai research and applications regarding atm systems also analysing possible approaches developed in other sociotechnical and safety critical domains and taking into account all possible impacts of higher levels of automation including those on atcos licence and training a parallel analysis of certification approaches legal and regulatory features and critical issues of such technologies will be carried out case studies specifically focused on capacity on demand and dynamic airspace will feed and validate the theoretical research and the design of both the approvalcertification approach and the guidelines for the design produced by the project
printed electronics for the circular economy

reform printed electronics for the circular economy sets out to address the environmental and sustainability challenges around conventional surface mounted and embedded functional electronics the project aims to accelerate and guide the development of a new european green functional electronics supply chain it seeks to use ecodesign principles to ensure that functional electronics can be produced that meet multiple application requirements for technological performance and compliance while also meeting societal and environmental needs for sustainabilityto achieve this reform will develop environmentally benign electronic building blocks focusing on green bioderived adhesives conductive inks and flexible substrates these will be integrated into industryled functional electronics systems and supported by innovations in conformance testing and material recovery methods taking a holistic approach to development across the supply chain positions this project is unique in not only achieving a stepchange in technology compatible with industrial reality but also producing prototype showcase systems with direct future impact on sustainabilityreform brings together a worldleading consortium of academics nonprofit rtos industrial associations private sme partners and large firms from eight countries across europe the project is femaleled and coordinated by cidetec a specialist rto in surface engineering and energy storage based in spain with a strong track record of leading large collaborative european projects by combining the consortiums unique and complementary expertise reform aims to give europe an innovation lead in green functional electronics enhancing european competitiveness and helping meet the ambitions for the european green dealthe immediate outcome of reform will be three demonstrators a green smart logistics tag a green embedded wireless sensor and a microsupercapacitor taking the project from trl 23 to trl 5
the many faces of prejudice the what the why and the how of inferences we make from membership in social groups

prejudice and discrimination have undeniable consequences for peoples lives and wellbeing our knowledge of stereotyping and prejudice is predominantly based on studies of simple dichotomies of us vs them whereas every person we interact with in real life will simultaneously belong to multiple social groups in this project i introduce the differential information processing dip model of intergroup attitudes to explain how we process information about others multiple group memberships to form impressions of them the key proposition of the model is that the mechanisms of impression formation depend on inferences we make from social categories categories that are seen as informative of beliefs eg religion give rise to ingroup bias whereas categories that are seen as informative of status eg education give rise to status bias i propose to comprehensively test this new model by addressing three essential questions what inferences do we make from peoples membership in different social groups why do we make them and how do we make them the proposed set of studies will utilize diverse methodological approaches including crosscultural survey experiments to capture variation in inferences people make and type and strength of biases they show across the globe text analysis of childrens literature and experimental work with children to understand how socialization experiences shape childrens beliefs about differential informativeness of social categories and neuroimaging work to understand if distinct neural processes can be linked to belief and status inferences and the corresponding biases if supported this new theoretical model will connect disparate strands of literature and bring a stepchange in how we study stereotyping and prejudice opening new avenues for more generalizable interventions for prejudice reduction
streamlining environmental impact assessment complex networks to integrate new eu environmental policies

in response to climate change the landmark paris agreement established a set of goals to achieve climate neutrality and limit global warming to help investors and companies contribute to these goals the eu adopted a taxonomy for sustainable activities and in line with it investments must not cause significant harm as indicated by the recovery and resilience facility regulation since its inception the environmental impact assessment eia procedure has aimed to minimize the impacts of projects that could significantly damage the environment certainly there are recognized weaknesses in the eia but its fitness to address complex environmental challenges such as climate change is unmatched considering the eia importance in ensuring the scaling up of sustainable energyrelated investments netdeal focuses on providing innovative and easytouse methods to improve eia worldwide and combines policy analysis and eia assessment data into complex networks first i will analyze models of impact assessment ia legislation that can make recommendations about how ia can change to fit the global effort to tackle the energy and resource crises second i will expose best practice models and investigate through networkrelated statistical analyses the collaboration links established in each eia stage which are behind successful projects from the perspective of productivity circular economy adaptation to climate change and reaching the goal of zero net emissions third using exponential random graph models i will explore the dynamic interaction between eia stakeholders to diagnose the organizational structures and factors that strongly influence these projects lastly i will create an integrated multilayer framework to improve the eias effectiveness the findings will be translated into the economic sector and provide new instruments to facilitate a streamlined eia procedure that facilitates the adoption of urgent measures to mitigate the current energy crisis
artificial intelligence and competition

ai algorithms are increasingly being used in markets it is generally agreed that they create a wealth of value by facilitating economic interactions however there are also concerns that when applied to market environments they could lessen competition and harm consumers this proposal sets forth an important first step of an articulated research program on ai and competition the proposal is structured as three organic projects focusing on two important classes of ai algorithms the first class pricesetting algorithms are tools that are used by online merchants to set retail prices as the algorithms of each merchant interact in a common market they can mutually learn to defeat competition we plan to study how these collusive conducts are learned to propose a direction for potential regulation the second class recommender systems rs are ubiquitous online algorithms that suggest products and content to consumers that are based on their current and past behaviour for example amazoncom uses recommender systems to rank products on search result pages or to suggest other products that the user may be interested in the aim of the proposed research project is to assess whether rss are procompetitive or anticompetitive by studying how firms endogenously react to rss in terms of price product design and entryexit decisions methodologically these projects rigorously combine ingredients from economics and computer science cs departing from the stylized modelling approach of the literature and instead are aimed at analysing stateof theart algorithms developed in the cs literaturealgorithms and their impact on market outcomes naturally require an interdisciplinary approach dealing with actual algorithms calls for new tools to supplement the economists traditional analytical toolbox for this reason an essential part of this research proposal is the creation of a joint research agenda via a research pod with an associated scientific program
empower citizens to join forces with public authorities in protecting the environment

assuring environmental compliance requires a strong network of stakeholders from citizens and researchers to governments and environmental organisations through creative toolkits and protocols enforce aims to tackle the frequent mismatch between the environmental data gathered by citizens and what authorities require for enforcement purposes the project will address the challenges in data reporting coming from both the citizens side and the authorities side in order for the obtained data to be usable for environmental enforcement in this line enforce introduces the concept of data readiness level drl to assess the maturity of data to be used as evidence in environmental compliance cases in addition the project will capitalize on the use of geospatial intelligence and aienhanced tools strengthening their capacities promoting good practices and preparing an inventory on geospatial intelligence and ai use the proposed solution will ensure alignment with the green deal data space to ensure trustworthy data exchange among the relevant stakeholders the project encompasses 8 case studies that involve all relevant actors including grassroots organizations local and regional authorities and a diverse group of experienced researchers forming a scientifically robust interdisciplinary team the lessons learnt and evaluation results from the case studies will feed the replication guidelines that will be promoted through the enforce capacity building programme and associated policy recommendations to create a multiplier effect for the adoption of citizen science data to support environmental compliance
realtime hydrogenstorage monitoring via energyefficient deep learning

the use of renewable hydrogen as green fuel and energy storage was deemed key to achieve the european green deal however its largescale storage is still facing significant challenges measurement inversion via deep learning dl is a stateoftheart approach used for underground storagesite detection and monitoring however 1 it requires a huge amount of training data 2 dl training is expensive and 3 there are no efficient and reliable dl techniques for multiscale electromagnetic measurement inversionthe goal of geolearn is to guide hydrogen storage technologies by inverting subsurface multiscale electromagnetic measurements in real time using energyefficient dl methods for this purpose geolearn will leverage mixedprecision mp computations to maximise energy and costefficiency and ensure scalability geolearn proposes to address the above challenges as follows 1 develop mp finite element methods fems that can rapidly generate large training data 2 design mp dl algorithms that can efficiently process huge databases during training and invert measurements in real time and 3 apply the new techniques to invert multiscale geophysical electromagnetic measurements and guide hydrogen storagewe will collaborate with industry to disseminate the project results and maximise exploitation and the new methods will lead to high impacts in and outside academiathe host has extensive experience in dl methods for inverse problems in geophysics and fems and already collaborates with relevant companies the secondment host is expert in highperformance computing and fems and the applicant is expert in mp methods for scientific computing this multidisciplinary research team is essential for the success of geolearn and will enhance the applicants knowledge network and skills promoting his future career in research in europe the hosts and applicant will mutually benefit from the project outcomes and the industrial and academic collaborations