Dragon09/odtu_chatbot huggingface dataset:
symbolic logic framework for situational awareness in mixed autonomy

symaware addresses the fundamental need for a new conceptual framework for awareness in multiagent systems mass that is compatible with the internal models and specifications of robotic agents and that enables safe simultaneous operation of collaborating autonomous agents and humans the goal of symaware is to provide a comprehensive framework for situational awareness to support sustainable autonomy via agents that actively perceive risks and collaborate with other robots and humans to improve their awareness and understanding while fulfilling complex and dynamically changing tasksthe symaware framework will use compositional logic symbolic computations formal reasoning and uncertainty quantification to characterise and support situational awareness of mas in its various dimensions sustaining awareness by learning in social contexts quantifying risks based on limited knowledge and formulating riskaware negotiation of task distributions these objectives will be achieved in symaware through a logical characterisation of awareness using symbolic methods b quantifying the symbolic reasoning for awareness with spatial and temporal ingredients for decision making c risk awareness via quantified knowledge d quantifying and communicating knowledge awareness e demonstrating awareness engineering in aviation and automotive use cases and f identifying requirements for ethical and trustworthy awareness in humanagent interactionthe objectives of symaware address the awareness inside challenge of eic by extending and formalising humanbased models of situational awareness and by providing a novel conceptual situational awareness framework for mass that encompasses logical characterisation and integrative formal reasoning of interdependent awareness dimensions including knowledge spatiotemporal risk and social dimensions this will support transitioning to safe mixed operation of autonomous agents and humans
the old the young and the uncertain future using highdimensional stochastic overlappinggenerations models to evaluate fiscal policies that shift risk and resources across generations

policy decisions about government borrowing taxation and spending have a differential impact on generations and thus imply substantial intergenerational transfers the costs and benefits of these policies occur over decades and come with large uncertainty for instance related to productivity growth global financial conditions and demographic trends therefore fiscal policies whether intentional or not transfer risk and resources across generations assessing their impact on welfare calls for simulating such policies in models that include the relevant demographics and risks yet also the related riskpremia the latter lower government borrowing costs relative to the expected return on investments and are thus particularly important for the welfare implications of fiscal policy solg for policy aims to build stochastic overlappinggenerations solg models that integrate all these elements and are thus able to quantitatively assess the welfare implications of fiscal policy choices involving intergenerational redistribution and risksharing to solve these models despite their highdimensional nature solg for policy leverages recent advances in computational economics based on adaptive sparse grids asgs and develops three extensions of this approach first using shapepreserving asgs to facilitate value function iteration second merging asgs with endogenous grids to avoid computeintensive optimization steps third parameterizing intergenerational distributions to further alleviate the curse of dimensionality policy questions that will be addressed include should the debt accumulated in the covid crisis be paid down through taxation or do low real interest rates make it desirable to leave the debt and its uncertain burden for future taxpayers to deal with is it feasible and desirable to make the pension system provide less redistribution yet more insurance across generations and how can this be achieved
unlocking cognition by pulsatile gnrh in alzheimers disease

cognitive decline associated with alzheimer disease ad and other agerelated dementias affects 55 million people worldwide and is a growing problem in aging european societies however most drugs fail at clinical trial and approved treatments aimed at controlling or reversing pathological changes in the brain do not improve cognition in patients besides having significant side effects it is thus essential to design and test alternative approaches to enhance cognitive performance and reduce the personal familial and societal burden of ad there is abundant circumstantial evidence pointing to a correlation between cognitive decline or ad progression with the agedependent loss or deregulation of gonadotropinreleasing hormone gnrh a neuropeptide better known for its role in the reproductive axis nevertheless a link between the two processes has not been seriously considered in a recent groundbreaking study we have shown that adlike cognitive deficits in down syndrome stem from progressive gnrh loss and restoring native gnrh in a physiologically relevant pulsatile pattern using implantable pumps safely and effectively improves cognition long after the onset of symptoms together with augmented brain connectivity additionally we have shown that tanycytes specialized hypothalamic glial cells that control gnrh secretion are fragmented in ad patient brains putting these two findings together we hypothesize that cognitive performance in ad patients can also be enhanced by administering pulsatile gnrh at normally occurring doses improving their quality of life the upgrade project will extend promising results we have obtained on the effectiveness of this strategy in a preclinical mouse model of ad analyze gnrh activity and pulsatility in an existing cohort of ad patients and finally draft a clinical trial protocol to test the safety and efficacy of pulsatile gnrh therapy to reactivate cognitive reserves in patients with mildmoderate ad
developing the supply chains for industrial hemp fibre and biobased resins towards high performance circular biobased composites

ssuchynext builds further where previous bbi ssuchy stopped in 2022 ambition is to bring different parts of the hemp fibre supply chain to trl 7 through production at scale of various fibre products covering the complete value chain from field to composite two value chains are further developed fibres are extracted by either scutching or by breaking rollercard linking into different geographical regions hackled and carded slivers are further processed into high quality preforms for composites woven and quasiud fabrics and purely ud hemp tape the appearance at industrial scale of high quality hemp fibres would give a boost to plant fibre composites in competition with glass fibre composites offering both an environmentally sound and cost effective alternative especially with less expensive medium length fibres with hemp fibres which are largely circular one of the major bottlenecks for a further breakthrough of biobased composites has been the lack of fully biobased environmentally sound and as well cost efficient polymer matrices hence our ambition in ssuchynext to work on 3 biobased resins biobased acrylic polymer elium with very high biocontent and fully biobased benzoxazine and bgepoxy building upon developments in ssuchy all systems developed to trl 6 or 7 to demonstrate the viability of the materials various inspiring applications are developed to trl7 we demonstrate the design production testing and certification of a 126 meter long wind turbine blade made from hemp and biobased acrylic woodbased products are developed based on infiltrated wood scaffolds in first instance with fluid acrylic also a hybrid woodbased product with hemp reinforcement is included to produce a leather replacement large scale building applications are demonstrated based on shorter fibres and benzoxazine for each developed product we demonstrate its recyclability all developments are monitored and adjusted by means of lca
disruption of mucin glycosylation and mucus barrier function in response to a westernstyle diet

in the healthy intestines mucus acts as a barrier that separates the host epithelium from the microbiota and intestinal contents as well as a habitat for commensal microbes the major component of intestinal mucus muc2 is heavily oglycosylated mucin oglycans are critical for mucus barrier function and hostmicrobe interactions alterations to mucin glycosylation have been associated with diseases such as inflammatory bowel disease and cancer and represent a novel target for therapeutic intervention however studies of the specific glycan structures altered during disease as well as the consequences of these alterations on mucus barrier function and the microbiota have been limited by a lack of tools to detect individual glycan epitopes mucus barrier dysfunction and microbiota dysbiosis specifically a shift towards expansion of mucindegrading bacteria have been observed in response to a high fatsugar low fiber westernstyle diet wsd my preliminary data indicates that a wsd can also alter specific mucin glycosylation patterns the identification of specific glycan alterations associated with a wsd creates the opportunity to study the role of individual glycan structures in mucus barrier dysfunction and microbiota composition this study aims to 1 develop novel probes to detect specific glycan epitopes and 2 use these probes to investigate the relationships linking mucus barrier dysfunction glycan alterations and dysbiosis in response to a wsd i will combine my previous experience characterizing glycan alterations in in vivo models of intestinal disease with host lab training in mucus physiology and bacterial enzyme characterization findings will advance our understanding of how glycosylation patterns are altered during disease and how these alterations contribute to disease pathogenesis this grant will allow me to enhance my skills as a researcher and give me the tools and experience necessary to establish my independent research group
reinventing the theory of machine learning on graphs

in many scientic domains graphs are the objects of choice to represent structured data from molecules to social networks power grids the internet and so on the exploitation of graph data represents a major scientic and industrial challenge graph machine learninggml is thus a fastgrowing eld with socalled graph neural networks gnn at the forefront however in sharp contrast with traditional ml the eld of gml has somewhat jumped from early methods to deep learning without the decadeslong development of well established notions to compare analyze and improve algorithms as a result 1 gnns all based on the socalled messagepassing paradigm have signicant limitations both practical and theoretical and it is not clear how to address them and 2 gnns do not take into account the specicities of graphs coming from domains as dierent as biology or the social sciences thus practical results may vary wildly from one case to the other with no guidelines on how to design reliable gnns in each case overall these are the symptoms of an overlooked major issue gml is hitting a glass ceiling due to its severe lack of a grand foundational theorythe ambition of project malaga is to develop such a theory solving the crucial limitations of the current theory is highly challenging current mathematical tools cannot analyze the learning capabilities of gml methods in a unied way existing statistical graph models donot faithfully represent the many characteristics of modern graph data computational complexity becomes problematic on large graphs malaga will develop a radically new understanding of gml problems and of the strengths and limitations of a large panel of algorithms our goal is to signicantly boost the performance reliability and adaptivity of gnns with a signicant impact on three types of graph data that exhibit very dierent but representative behaviors biological networks social networks and online recommender systems
building vascular networks and bloodbrainbarriers through a biomimetic manufacturing technology for the fabrication of human tissues and organs

tenths of millions of people with organ failures or suffering from degenerative diseases are waiting for a novel cellular therapy or for a transplant of a donor compatible organ and the immense majority of these patients will die before receiving the tissue or organ they need despite the significant advances in tissue engineering not a single artificial tissue has been used to replace a part of an organ with the exception of simple or avascular tissues like skin or cartilage thor proposes the development of a revolutionary tissue engineering technology capable to produce any type of human tissue for organ repair or replacement in case of illness trauma or degenerative diseases patienttailored tissues will be fabricated by pools of bioinspired minirobots in fully automated production plants using the breakthrough incremental technologies of the thor project selfassembling molecules inspired to the extracellular matrix selfassembling solid and hollow polymeric fibers materials functionalization using photoactivable crosslinkers cuttingedge mini robots to wave 3d selfassembling structures with factors and cells with micrometric precision thor tissue arises from highresolution 3d spatial positioning of selfassembling structures angiogenic factors and relevant cell lineages reprogrammed and expanded in a dedicated bioreactor under controlled conditions our longterm vision encompasses 1 the establishment of a tissue engineering industry for personalized organ repair producing any type of well vascularized and fully functioning tissues and 2 the maintenance of such tissues alive for long periods of time for an easy transportation to hospitals and clinics even far from the big cities thor will foster the rise of a new industry and of a new biomedical field while cadaveric donors transplants will not be necessary
spacetime quantum metasurfaces with twodimensional layered materials

many disruptive information technologies such as quantum technologies and 6g communication have been emerging as critical enablers to significantly promote human wellbeing such as ultrafast computers and mobile internet however due to civilized development and growing volumes of data it has aroused higher requirements of dataprocessing power and wireless communication efficiency exploring new approaches to improve the performance in advanced information technology is a destination that scientists have been constantly pursuing one promising technology for achieving such goals in a spatially and temporally controllable manner utilizes an artificially engineered array of active elements known as spacetime metasurfaces this project will use one of twodimensional 2d materials graphene to design and fabricate spacetime metasurface addressing a key question in the fields of quantum information and photonics how to dynamically manipulate the quantum states of entangled photons or nonlinear light based on different degree of freedom such as frequency and polarization the key objective of the project is to build a practical prototype of spacetime quantum metasurfaces based on graphene for the first time this project will focus on three different objectives theoretical design of timemodulated algorithm and optimized space distribution fabrication of spacetime metasurfaces with gatedtuned graphene nanopatterns and quantum imaging applications of spacetime metasurfaces the multidisciplinary nature of the project is strong involving a combination of well developed optics information science quantum technology 2d materials and nanofabrication this proposal includes both the transfer of knowledge to the host institution and the training of the candidate in new advanced techniques results have the potential capacity to increase the competitiveness of quantum technology and nanophotonics
design and synthesis of mxenebased 3d porous heterostructure composites for enhanced photocatalytic ammonia production under ambient conditions for sustainable hydrogen energy storage

while hydrogen is an excellent green energy carrier which holds tremendous potential as a sustainable environmentally friendly efficient and clean energy alternative its storage remains costly energyintensive and hazardous recently the possibility of chemical storage of h2 in the form of ammonia nh3 is receiving increasing attention however despite the potential of nh3 for hydrogen storage the existing fossil fuelbased nh3 production technology is highly energy intensive and costly photocatalytic nh3 synthesis is gaining familiarity as it is environmentally benign and sustainable however the conventional photocatalysts suffer from low nh3 yield poor photocatalyst operational stability and low solartochemical conversion efficiencies thus it is the current scientific challenge to design an efficient photocatalyst to convert atmospheric n2 to nh3 hence the design and construction of novel hybrid photocatalysts with enhanced photocatalytic performance is vital for efficient synthesis of ammonia as a hydrogen energy storage medium in recent years the twodimensional transition metal carbides carbonitrides and nitrides mxenes are gaining popularity for photocatalytic n2 reduction owing to their diverse elemental compositions large surface area lightharvesting ability and capability to host a broad range of intercalants besides heterojunction formation by combination of mxenes with 3d reduced graphene oxide rgo and other novel photocatalysts such as metalorganic frameworks zscheme photocatalysts would significantly increase photocatalytic performance of the hybrid by combining the merits of each component besides the interconnected structure of 3d rgo framework possesses a macroscopic porous structure for efficient incorporation of semiconductor nanoparticles in the 3d structure thus the current studydesigns and fabricates innovative 3d mxenebased hybrid photocatalyst for efficient photocatalytic synthesis of nh3
artificial intelligence tool for environmental impact assessment of biobased products

the main objective of argonaut is to develop an effective and easily accessible ai digital tool that accurately calculates the environmental and climate impact from biobased products across the entire value chain from cradle to grave using language models from global literature based on lca principles and allows for easy and secure tracking through a digital passport based on blockchain technology this tool will also include a decision support tool that uses this data to map out different alternatives for the value chain and their environmental impact thereby facilitating better and more sustainable decision making argonaut will contribute to the integration of key emerging digital technologies ai and blockchain and an environmental assessment methodology lca to create a reliable tool able to assist small and mediumsized producers to navigate the complex bioproduct landscape with enough relevant information security guarantees regarding the privacy of their data and in a userfriendly way capable of closing knowledge gaps and thereby of reaching to a wider range of producers argonaut will contribute to the implementation of the eus ecodesign for sustainable products regulation and allow for an accurate depiction of the environmental impact of such biobased products thereby supporting the development of more sustainable value chains and the transition to a circular bioeconomy across the eu
decoding calcium pathway activated by plant intracellular immune receptors

plant diseases have been causing global issues to agriculture economy and humanity understanding how plant disease resistance works is vital to finding durable and sustainable solutions to protect our crops one key molecular hallmark of plant immune activation is mediated by calcium signalling which is a commonly shared and wellknown second messenger in all cellular organisms however it has been overlooked how calcium signalling is activated by plant intracellular nucleotidebinding and leucinerich repeat immune receptors nlrs which are often one of the main genetic resources of plant breeding for disease resistance in addition upon activation it is not known how the immune receptors activate a large scale of defence genes via calcium signalling to answer these questions i will be addressing three objectives 1 decoding compartmentalized calcium dynamics activated by intracellular immune receptors nlrs 2 characterizing the role of helper nlrs in producing calcium signatures and transcriptional reprogramming 3 identifying calmodulins calciumbinding proteins that interact with key transcription factors to decode the calcium signature during effectortriggered immunity mediated by nlrs i will use an interdisciplinary approach combining cell biology genetics and multiomics the outcome of this study will expand our understanding of plant immunity and provide novel insights for crop breeding specifically tailored to counter hazardous pathogens i aim to 1 broaden my expertise in plant signalling research 2 expand my toolbox of cellular biology and genetics 3 develop the leadership skills required for managing a research group furthermore i will strengthen my scientific track record and network this decaeti project will be performed at the institute of biology leiden leiden university implementation of the project will support me to run this project successfully and advance my career to become an independent future leader
phytomanagement as a sustainable feedstock source of lignocellulosicbased highvalue biobased products for textile applications

phybi is a 48month action that will combine the soil phytoremediation concept with lignocellulosic biomass valorisation in an integrated phytomanagement circular economy approach the phybi concept will focus its efforts across different levels of development 1 test optimisation and validation of 4 phytomanagement case studies 2 optimisation of biomass fractionation into lignocellulosic components based on organosolv techniques and 3 characterisation and application of lignocellulosic fractions to create a wellplanned market route for the potential endapplications in the textile industryfurthermore the project will develop a virtual replication tool where phytomanagement valorisation process and endproducts will be integrated resulting in guidelines recommendations and thresholds for the replication of phybis case studies along other areas to finalise the proposal concept social innovation activities will strongly connect the process with the market and society with the aim to deliver high quality products with high level of acceptanceto achieve its goals phybi brings together a multidisciplinary team integrating experts in plant and soil science ubfc ubu uniovi phy chemical engineering and biorefineries cetim computational science ide textile materials and products ntt agroindustry particula phy dihleaf and market analysis knowledge exchange and social innovation sez