Dragon09/odtu_chatbot huggingface dataset:
from sky to seafloor observation achieving excellence in oceanic surveillance and conservation through deep learning

technological areas such as artificial intelligence ai and ecosystems such as shipping maritime and space have been strategically prioritised by cyprus to improve its research and innovation ri performanceat their intersection lies the need to enhance marine conservation efforts and maritime surveillance by leveraging deep learning dl methodologies built on standardized and robust data sets indeed insitu sampling stands as a cornerstone in marine conservation offering a direct approach to monitoring marine biodiversity while remote sensing stands as a pivotal addition to maritime surveillance expanding the scope beyond traditional automatic identification system capabilities dl as a cuttingedge ai tool holds immense potential to enhance the analysis of insitu samples and remotely sensed dataaxolotl is proposed as a transformational international endeavour capable of enhancing the ri capacity of cmmi cyprus and europe in the interdisciplinary fields of dlenhanced insitu biodiversity assessment and dlenhanced remote sensing for maritime surveillance the project will contribute to closing the gap between a h2020 teaming centre of excellence and 2 strong innovators from france and belgium through capacitybuilding knowledge transfer networking and outreach activities at regional and international levels activities will go beyond the strictly scientific scope and support the mutual development consolidation and reinforcement of administrative dissemination and entrepreneurial competencies access to networks of excellence and the sustainable linkage between partners the projects ri component will develop new strategies for improving data quality standardization and synchronization issues devise novel interdisciplinary methodologies develop robust dl models from stateoftheart computer vision methods and validate its proposed solutions in 2 relevant realworld contexts biodiversity assessment and maritime surveillance
sustainable careers for researcher empowerment

the sustainable careers for researcher empowerment secure project will develop coordination and support measures to create trial implement and mainstream a common research career framework rcf that offers a suite of options to support organisations in the recruitment employment training development progression and mobility of researchers with the aim of improving research careers and reducing career precarity the rcf will recognise the research profession across sectors provide a career development and progression structure for research careers recognise both research and transferable skills and competences facilitate intersectoral collaboration and mobility and offer solutions to the precariousness of research careers in academia secure will test aspects of the rcf and ttl models in trials in four rpos one rfo and one recruitment agency the trial organisations will first conduct a scoping exercise to map the rcf onto their existing policies and activities for research careers before developing integration plans on how the rcf could be adopted into their existing policies and activities due to the short duration of the project and window for trials it is expected that only some aspects of the rcf and ttl models will be tested the trial organisations will thus develop actions plans selecting relevant aspects from the integration plans to test and implement during the trials secure will mainstream the rcf and ttl models through a series of policy briefs and a summit that explain key aspects of the rcf and ttl models to relevant organisations employing researchers the rcf and ttl models will be further promoted through key partner organisations in the project targeting researchers rpos and companies the rcf and ttl models will lastly be promoted in the euraxess network including the many euraxess service centres the newly established euraxess hubs and through the era talent platform being developed
technology for european independence in space image sensor

the objective of the technology for european independence in space image sensors tensis project is to develop manufacture and validate a scalable largearea highresolution radiation tolerant customizable and affordable 180nm cmos detector with the key technical characteristics of a 24k x 16k format matrix of 400mpixels the targeted pixel pitch is 35m to keep the overall matrix manufacturable with the proposed xfab 018m cmos image sensor process and with high full well capacityoverall pixel electrooptical performances including mtf and spectral features will be enhanced by the design and implementation of specific optical stack in back side illumination configuration combining rgbnir filters with flat microlenses as a by product of the design of the 24k x 16k detector a 4k x 4k detector will also be designed and manufactured by te2v in fsi then bsi configuration te2v will package produced dies in pcb package and deliver them to airbus defence and space in toulouse for detailed functional electrooptical characterization before this characterization test campaign airbus will develop dedicated test means including proximity boards both matching with the 24k x 16k and the 4k x 4k detectors in close cooperation with teva group of 4k x 4k bsi detectors initially electrooptically characterized by airbus will then be delivered to alter at sville to be submitted to dedicated environmental tests including tid tnid and heavy ions radiation campaigns as well as burnin and power onoff cycling tests thanks to this test campaign the 4k x 4k detector die will reach trl7 by the end of the project the project will further aim at creating a strategic competitive advantage for the european partners prime and equipment manufacturers and reduce the dependence on critical technologies and capabilities from outside eu it will rely on the xfab foundry which is key for the tensis project
firstinclass myc inhibitor the making of a breakthrough cancer therapy

pancreatic ductal adenocarcinoma pdac is one of the most lethal cancers with very few and often ineffective therapeutic options despite recent advances cancer therapies remain ineffective andor highly toxic our approach is targeting myc a function essential to cancer cells that allows them to survive and develop resistance to therapy in contrast to standard drugs inhibiting myc selectively blocks tumor progression without causing important side effects myc has been considered undruggable for a long time and no clinical myc inhibitor is yet marketed peptomycs firstinclass drug omo103 is a cellpenetrating miniprotein that derives from omomyc the best myc inhibitor known to date omo103 recently completed a phase 1 clinical trial that confirmed its safety and clinical activity in allcomers solid tumor patients causing a 49 tumor shrinkage in a pdac patient and stabilizing the disease of 8 out of 12 evaluable patients moreover using ai we identified a predictive and a pharmacodynamic circulating biomarker signatures and generated companion diagnostic for stratification and realtime response monitoring tests for omo103 omo103 and its companion diagnostic tests offer a promising therapeutic option for a disease in great need and could apply to treat many other cancer indications the next steps and goals of this mycurex project consist of conducting a phase 1b trial in 1stline pdac patients combining omo103 with the standard of care to evaluate its safety and clinical activity refining the companion diagnostic prototypes and app securing the scaleup of the innovation by developing a commercialscale compatible manufacturing process and expand the applications of omo103 and peptomycs drug pipeline by completing mycurex peptomyc will consolidate the therapeutic potential of myc inhibition in cancer patients improving their survival and quality of life while establishing itself as a european leader biotech in myc targeting
design and implementation of an advanced nonlinear and nongaussian data assimilation algorithm for bounded variables in numerical weather prediciton models

hazardous weather events affecting populated coastal are among the most devastating natural disasters in terms of mortality and economical losses due to their low predictability currently the generation of useful predictions reliable and anticipated of hazardous weather events affecting populated coastal regions remains an ambitious challenge for the scientific community deficiencies in the accurate prediction of such events are tightly related with the initial value problem which states that better the state of the atmosphere is estimated the more accurate the forecasts this problem is addressed by using advanced data assimilation da techniques which play an important role in current numerical weather prediction and is currently at the forefront of atmospheric and oceanic sciences research however although using the most current sophisticated da algorithms the estimation of the atmosphere is not accurate enough to improve the predictability of hazardous weather events mainly because their linear and gaussian underlying assumptions the main aim of the present project is to go beyond the state of the art in da by developing and implementing a novel and advanced da technique that takes nonlinearities and nongaussianities into account enabling us to to improve highimpact weather forecasts the new da will be tested in real cases in combination with a highresolution atmospheric model to improve the predictability of several poorly forecasted mediterranean hurricanes this novel technique will significantly improve global regional and climate forecasts the applicants strong mathematical and theoretical skills in da together with his broad experience running numerical weather models using hpc facilities will facilitate the achievement of the key goals of this proposal this project will also expand the applicants experience research competencies and professional networks enhancing the development of his career as an independent researcher
rna processing for anticancer immunotherapy

in the past five years rna therapeutics have witnessed a true revolution several rnabased therapies have been approved for the treatment of genetic diseases with unprecedented successes as in spinal muscular atrophy moreover the past year showed the world that rnabased therapies namely mrna vaccines can be the answer to a worldwide pandemic and save the lives of millions rna therapies are however lagging behind in clinical oncology the overarching aim of this multiarmed project is to develop rnabased cancer treatmentsin parallel the development of immune checkpoint inhibitors has revolutionized cancer care but its success remains limited to a subset of patients altogether for 60 percent of the eight million new cancer patients diagnosed in europe each year including almost all children with solid tumors there is no ema or fdaapproved immunotherapy option and they are left out of the circle of hopein response cancerna aims to build on these two breakthroughs and apply rnabased therapeutics to overcome key barriers to unfold successful anticancer immune responses our two key objectives are on one hand harness the modulation of rna processing to enhance the accessibility and immune susceptibility of the tumour and its microenvironment while on the other hand enhance the activity of the immune system by retargeting immune effector cells modulating rna splicing of key immune receptors and developing personalized mrna vaccines the project will focus on two cancer types harboring splicing factor mutations and being generally refractory to immunotherapy acute myeloid leukemia relevant for pediatric cancer and uveal melanomathe collective knowledge of our consortium of rna scientists clinicians and biotechpharma experts in rna processing rna drug design and delivery biocomputing and immunooncology provides a unique opportunity to significantly advance novel rna technologies into successful cancer therapies
reconfigurable heterogeneous highly parallel processing platform for safe and secure ai

rebecca a heavily smedriven project will democratize the development of novel edge ai systems towards this aim rebecca will develop a purely european complete hardwarehw and softwaresw stack around a riscv cpu which will provide significantly higher levels of a performance eg inferences per second b energypower efficiency eg inferences per joulewatt c safety and d security than the existing ones this will be achieved by utilizing stateoftheart technologies and by making significant scientific and technological advances in several key relevant domains including a processing units b hardware accelerators c reconfigurable hardware d tightly coupled interconnected chiplets e hwsw codesign and codevelopment tools f system software g middleware and h ai libraries and frameworks rebecca will significantly contribute to realizing business and societal opportunities by validating and demonstrating its approach on 4 realworld use cases and 2 benchmarks based on realworld applications from the smart appliances energy generation infrastructure inspection avionics automotive and health domains in terms of hw rebecca will develop a novel chip consisting of two tightly coupled chiplets which will incorporate a riscv multicore b neuromorphic ai accelerator c programmable array ai accelerator d ai accelerator utilizing a hierarchical processing architecture e dnn accelerator f reconfigurable hardware g nearmemoryprocessing h memory encryptionin terms of sw rebecca will implement optimized system sw middleware and ai libraries that will take full advantage of the underlying novel hw the rebecca platform will be complemented by a novel hwsw design space exploration tool which will allow the development of highly efficient rebeccabased systems rebecca will additionally provide the means for safety and security modeling and verification for the developed hw and sw from the very early design stages
humancentric artificial intelligence for sustainable future

for the eu to strengthen its role as the global leader in trustworthy ai experts on ethical humancentric and sustainable use of ai are urgently needed in public private and third sector organisations across member states this interdisciplinary expertise is not readily available through traditional doctoral training frameworks the fastevolving field will continue to create opportunities for individuals with resilience and futureproof skills humancentric artificial intelligence for sustainable future haif is a doctoral programme for 25 doctoral candidates dcs hosted by the university of turku utu finland and supported by 17 associated partners haif will establish a novel doctoral training scheme that connects utus faculties of technology social sciences law and humanities haifs research themes are societally relevant emphasizing humans as developers users and decisionsubjects affected by the technology in addition to individual and societal perspectives haif produces technological solutions for improved safety security interpretability and technical robustness of ai systems research on application areas such as health care autonomous systems and cybersecurity will be transferable to different sectors haifs academic collaboration network covers 7 eu countries and the us 6 nonacademic partners bring in business relevance and views of the public administration besides enhancing dcs academic skills and producing new interdisciplinary knowledge haif will train dcs on transferable skills such as communications and project management which are essential for widening their career prospects haif dcs will be selected through a transparent meritbased process with equity and inclusivity as crosscutting priorities by training the future professionals in the critical themes of humancentric and sustainable ai haif increases competitiveness jobs and growth from the regional to eu scale
bridging fundamental knowledge and novel technology to increase rice heat tolerance

seeds are the link between the end of the reproductive cycle of adult plants and the establishment of their next generation seeds are the means through which plants can adapt to climatic changes feeding the evergrowing population is a major challenge especially in light of rapidly changing climate conditions genome editing is set to transform plant breeding and help secure the global food supply advances in genome editing technologies provide new opportunities for crop improvement by employing precision genome engineering for targeted crop traits this proposal which addresses critical stages of the reproductive development integrates several approaches to comprehensively investigate sexual reproduction in rice under heat stress hs conditions with the aim of using the novel knowledge generated to improve rice production the model plant system arabidopsis thaliana will be used as proof of concept to generate quick knowledge that can be readily translated into concrete outcomes in rice specie of high importance to the european agricultural sectorcrispit main goal is to understand the mechanisms that regulate heat stress tolerance during the reproductive process in rice crispit will provide answers to the following questions how plant reproductive cells and tissues are affected by heat stress what are the molecular mechanisms underlying rice plants resilience to hs during reproduction to answer these crispit proposes to achieve three main objectives 1define hs features and marker genes in nagina22 rice variety 2 generate a new transcriptomic dataset 3 obtain and fully characterize mutants from the chosen genes in order to deliver rice hs lines produced by crispr technology
coordinating and piloting actions towards erahubs as inter and intraregional ecosystems for knowledge production

cooperate overall objective is to develop and pilot the era hub concept based on the vision and success stories developed within the eurotech universities alliance and their ri ecosystems the overall approach revolves around cocreation arenas in which ecosystems and a broader community of quadruple helix actors can interact the piloting phases of the projects implementation are expected to test the approach and pave the way for its consolidation and replication phase the approach follows a mechanism in which leverage is sought to engage a broad range of stakeholders activate crossfertilization facilitate mutual understanding create intertwining cooperation and jointly develop innovative ideas for shaping the era hub framework model for further piloting and validation the intended era hub model builds on lines of action eg access to knowledge and talents which gather a set of initiativesprojects to animate the actors and stakeholders and operate the ecosystem around common priorities ie strategic multiannual roadmap which reflect the missionbased approach in this framework the key exploitable results include 1 the era hub model and associated playbook toolbox and platform with compliance criteria to develop the era hubs network 2 the policy recommendations and content from cocreation activitiesthe consortium is aware that the outcome of the project is supporting the ec roadmap towards the launch of era hubs as flagship initiative in europe to boost the era beyond the scope of the project tailor made communication dissemination and exploitation actions will therefore create awareness and engagement within regional ecosystems in eu building consensus in a close dialogue with eu and nationalregional institutions in particular two large events will be organised in brussels at midterm and at the end of the project for consensus building on the project findings and policy recommendations
noncommutative ergodic theory of higher rank lattices

noncommutative ergodic theory of higher rank lattices is a current topic that has seen several exciting developments in the last five years among these recent advancements in joint work with rmi boutonnet 2019 we proved a noncommutative analogue of nevozimmers structure theorem for actions of higher rank lattices on von neumann algebras first of all we derived several novel applications to ergodic theory topological dynamics unitary representation theory and operator algebras associated with higher rank lattices then we obtained a noncommutative analogue of margulis factor theorem that provides strong evidence towards connes rigidity conjecture for the group von neumann algebra of higher rank lattices these results revealed deep and unexpected interactions between the field of discrete subgroups of semisimple lie groups and the field of operator algebras in this research project i plan to build upon these recent achievements to develop new directions in noncommutative ergodic theory of higher rank lattices this research proposal is centered around two main interconnected themesfirstly i plan to work on several problems and conjectures around the dynamics of the space of positive definite functions and character rigidity for higher rank lattices these include the classification of characters for higher rank lattices of product type and more general lattices with dense projections in product groups as well as stiffness results for stationary positive definite functionssecondly drawing inspiration from margulis superrigidity theorem i plan to tackle connes rigidity conjecture for higher rank lattices by developing a novel strategy combining techniques from boundary theory calgebras and von neumann algebras these methods will lead to new rigidity phenomena for operator algebras arising from irreducible lattices in higher rank semisimple connected lie groups
synchronised neuromemristive architecture for reinforced learning technology

rapid progress in the regime of artificial intelligence and internetofthings has enthused the development of fast and energyefficient hardware to support future computing needs one of the most prominent solutions is the deployment of crossdisciplinary resources for mimicking the performance of a human brain also known as neuromorphic computing it relies on electronic components that could replicate the functioning of neurons and synapses designing such novel electronics needs the development of costeffective fast and reliable materials with tunable functionality a fundamental understanding of these materials will pave the foundation of innovative device designs and strategies for their largescale integration for neuromorphic architectures in this context the proposed project intends to deliver artificial neurons by developing thinfilms of a novel material tbmno3 that is capable of demonstrating a negative differential resistance ndr the idea is to utilise the fundamental understanding of multidimensional electrical optical mechanical and magnetic control of ndr which is not explored yet and is possible in tbmno3 ndr enables a twoterminal device to display selfoscillations due to applied electrical spikes the spiking electrical currents could be used to govern the behaviour of these oscillations and emulating the leaky integrate and fire behaviour of biological neurons once such a performance is achieved the device will further be integrated into oscillatory neural networks array for demonstration of complex computing tasks such as image recognition and imitating human behaviour the project will unite the applicants expertise in synaptic devices and materials engineering with the extensive experience of the hostlabs in thinfilm and neuromorphic devices importantly the project will warranty catapulting the applicants international recognition as an independent researcher and will improve his career prospects