Dragon09/odtu_chatbot huggingface dataset:
controlling the flow of attention transition dynamics of attention and distraction across external and internal domains

we often choose to distract our minds either externally eg looking at our phone or internally eg thinking about weekend plans it is currently not clear how when or why we choose to become distracted nor do we have a mechanistic understanding of flow states in which there is minimal distraction this is a pressing issue as distraction is omnipresent in our society obstructing our capacity to focus both on personal goals and the many challenges humanity faces to advance our understanding on how distraction occurs we must overcome the current practice in which different attentional states are studied in isolation i propose to capture the different research fields on attention in a single space defined by the dimensions direction external vs internal and locus ontask vs distracted distinguishing four attentional states ie ontaskexternal ontaskinternal external distraction and mind wandering the objective of the mindflow project is to map the dynamical transitions between these states and to causally influence the amount of time people spend in each of them i will use behavioral measures eyetracking and pupillometry to capture these states and quantify the dwelling times and a transition matrix through computational modeling inspired by recent empirical work on attention switching and neurobiological models of mind wandering i hypothesize i the existence of an offfocus state through which these dynamical transitions occur ii that internal bias and goal value determine which areas are visited most and iii that contextual manipulations can alter the relative times spent in each area i will test these predictions by a modelcomparison approach and withinsubject experimental manipulations of context volatility and task difficulty bridging these different fields of attentional research will increase crosstalk between them and provide building blocks for interventions targeting healthy attentional engagement
intelligent asset management platform for hydropower operation and maintenance

the iamphydro project will improve the digital operation of existing plants through the development of 6 expected results r which will collectively form iamp a novel intelligent asset management platform see result r5 in fig 1 encompassing secure open and transparent data sharing protocols r4 and three novel digital solutions r1 condition monitoring and predictive maintenance modelling r2 ecological status monitoring and water management r3 improved weather and flow forecasting the full package of digital solutions will be validated at a diverse set of five realworld existing hydropower plants producing evidence for policy making to support the green and digital transition of hydropower r6 the existing plants include differing power capacities electromechanical equipment type water enduse flow and head regimes climatic conditions and environmental sensitivities biodiversitythe project will increase the technology competitiveness of existing hydro by reducing om costs by 510 improving generation and revenues increasing flexibility and datadriven decision making in hydropower operations it will also increase the market penetration of renewables in the grid by 84 twh and getting closer to the eu 2030 climate and energy targets and eu green deal iamphydro will improve environmental and socioeconomic sustainability of the existing hydropower fleet by reducing operating costs by 1 billion per annum reducing co2 emissions by 1260 tonnes creating 10000 futureproof jobs and enabling environmentally sustainable flow regulation using digital solutions the project will advance the scientific basis for hydropower digitalization by developing validating and providing a roadmap for the further development of 5 new digital technologies we will produce 10 peer reviewed journal publications and 20 conference publications
biophysical genetic design automation technology

advances in our capabilities to program synthesize and modify dna has led to a surge in the field of synthetic biology various gene circuits have been proposed and designed in various organisms for application domains ranging from biomedicine over biotechnology to biomaterials our current bottleneck is not anymore our ability to program and synthesize custom dna but rather our ability to design regulatory circuit that realize the desired functionality and operate reliably in a specific target host cell or in vitro systems the largest hurdle that we identify is the contextdependency of synthetic circuits ie their perturbation by other molecular factors belonging to the host cell given the complexity of these molecular systems current design approaches that rely on trialanderror will not be able to produce meaningful designs in a reliable fast and systematic manner at the scale required for industrial applications although genetic design automation tools are available to overcome this unsatisfactory state of affairs their practical impact have been limited this is due to the fact that the used models are not accurate enough in particular they cannot predict reliably the performance of a circuit design when operating within a host cell the main reason for this limited predictive power is that models do not take into account the named contextdependency of circuits the current project plate takes on this challenge and leverages methods developed within the erc project consyn that allow for accurate modeling of contexteffects through the use of detailed biophysical models the aim of plate is to integrate all those computational methods into a coherent design environment for the synthetic biology researcher in academia and in industry the resulting plate software suite follows a modular approach where different analysis types and different design methods can be selected according to the specific need of a given academic or industrial project
optical and wireless sensors networks for 6g scenarios

in the optical and wireless sensors networks for 6g scenarios owin6g project key industry and academic stakeholders are brought together with the aim of developing a structured european training programme tp in optical technologies to facilitate disruptive wireless sensor applications within sixthgeneration 6g networks owin6g will be the first doctoral network dedicated to training new generation of earlystage researchers ie doctoral candidates dcs in the field of wireless sensor networks wsns for the internet of thingsinternet of everything as part of the 6g and beyond focusing on novel sensors solarcells for energy harvesting and optical detection and hybrid rfoptical wireless technologies and the application of machine learning to improve adoption optimization and security aspects in sensor networks owin6g will contribute significantly to the fundamental scientific understanding technical knowhows and innovation of the future hybrid rfoptical wsn through the collaborative research involving ten individual dcs projects addressing specific challenges and applications owin6g will make significant contributions to the fundamental scientific understanding technical knowhow and innovation of the future hybrid opticalrf sensor network in addition to technical tp through phd courses dedicated tutorials and workshops organized by the doctoral network dcs will be offered complementary nontechnical training activities including entrepreneurship authoring scientific paperspatents dissemination etc having industrial partners participate will further enhance dcs technological progress by focusing on standardization commercialization and handling of realworld projects in a realworld environment
reinforcement learning to improve proofautomation in theorem proving

developing generic proof automation methods for interactive theorem provers itps is challenging but valuable applications range from performance improvements in the verification of safetycritical systems to the certification of famous long and hardtoprove theorems we propose using recently successful reinforcement learning rl algorithms to learn proof strategies employed in vast itp libraries and use them as generic methods to automate the itp proving process specifically the project aims to create a tactic for one of the most popular and automated itps isabellehol and train the rl algorithms with theorems from the two largest isabelle libraries hollibrary and the archive of formal proofs afp we identify three gaps in the state of the art that such an rlandisabelle approach would close and describe the work packages that will achieve the corresponding three research objectives the project will be done under the guidance of dr josef urban who holds a distinguished researcher position at the czech institute of informatics robotics and cybernetics ciirc within the czech technical university ctu in prague dr urban and the ciirc group are experts in integrating machine learning ml and interactive theorem proving their infrastructure and expertise targeted to ml and itps provide the best research environment for this project jonathan julin huerta y munive the researcher carrying out the project complements this expertise with his isabellehol experience and knowledge of itp applications
the stress granule machinery controls metabolic signalling through mtor at steadystate

mtor kinase is an oncogenic master regulator of metabolism and cell growth and is known to reside in two multiprotein complexes upon stress mtor is inhibited by stress granules sgs which recruit mrnas and signaling factors to promote survival current work largely addresses the functions of sg proteins under stress focusing on their rna binding properties and sg assembly however nonstress functions are emerging i propose that sg proteins have prime functions in mtor signaling at metabolic steadystate in the absence of sgs our preliminary data show that core sg proteins bind mtor at steadystate and suggest that they are key controllers of mtor in beyond stress we will investigate sg proteins as a novel class of mtor regulators at steadystateby means of deep proteomics proteometaboflux rnaseq systems modelling mechanistic and cell biological studies we will identify and functionally characterize the sg interactome of the mtor complexes we will delineate the steadystate inputs that signal through sg proteins to mtor and we will unravel the mechanistic interplay through which sg assembly impinges on metabolic signaling upon stress as levels of core sg proteins correlate with cancer outcome we will explore their linkage with metabolic signaling prognosis and drug response in breast cancer beyond stress is groundbreaking as i it links sg protein research in stress to steadystate mtor signaling ii a unifying paradigm of mtor regulation at steadystate and stress will open new horizons for research on metabolic signaling and iii sg proteins are emerging as markers and targets for oncogenic signaling through mtor while focusing on mtor and breast cancer beyond stress will likely translate to further networks and tumor entities opening new avenues to signaling and cancer research
greenrubber sustainable production of natural rubber using yeast

natural rubber is a very important and widely used industrial raw material which cannot be replaced by other equivalents because of its unique properties eg durability and insulation synthetic rubber produced by petrochemicals is not only detrimental to the environment but also cannot replace natural rubber due to its lower quality therefore for many industrial applications eg in car tires humankind still heavily relies on rubber extracted from the rubber tree hevea brasiliensis however the demand of natural rubber is continuously increasing due to the fast pace of motorization in asian countries like china or india while production is sensitive to disease outbreaks or weather conditions for these reasons to become selfsufficient in natural rubber is within the european strategic priorities thus because both natural and synthetic rubber production is no longer sustainable there is an urgent need to establish environmentally friendly methods for the synthesis of natural rubber in alignment with the united nations sustainable development goals sdg 9 11 12 13 and 15 to meet this demand i will apply an interdisciplinary approach to develop a yeastbased cell factory to produce highquality natural rubber from cheap and readily renewable materials like sugar my research expertise in molecular biology polymer bioproduction and biochemistry make me the ideal candidate to implement this project combining my current knowledge with the systematic education on metabolic engineering and pathway elucidation that will be provided by the host lab i will build a unique profile as an expert in polymer bioproduction using microbial hosts greenrubber will help me develop and establish an independent international career on harnessing industrial microorganisms eg yeast to bioproduce polymers for highend applications such as medical consumables
european doctoral programme for smart urban coastal sustainability

the eudocs for smucs programme is a european doctoral programme designed to train 17 phd students based on cotutelles between la rochelle universit lruniv and its partners from the euconexus european alliance and beyond based on a challengedriven approach of research and education it addresses the societal challenges related to smart urban coastal sustainability smucs while strengthening cooperation within our alliance in order to enhance human resources for research and innovation in that area with 60 of the worlds population living within 100 kilometers of the coast and the landsea interface threatened by climate change and the sea level rise lruniv has been leading a consistent strategy of combining its forces in research and education in order to define understand and address the related challenges these challenges threaten local economies and quality of life of populations and may take very different forms from risks related to the artificialization of shorelines destruction and pollution of wetlands and biodiversity vulnerability of coastal towns massive migratory flows the impacts of unregulated mass tourism or energy losses related to ageing constructions and lack of urban policies and risk governance such complex and interdependent challenges require interdisciplinary approaches at an international level getting academic and nonacademic actors to work together on sustainable and resilient solutions building on the combined strengths of its partners our programme will train a generation of highly skilled researchers through 36months thesis able to tackle these issues with comprehensive approaches a strong international network and a solid training on researchrelated and transversal skills leading to their increased employability within academia and beyond after graduation this programme is anchored in three fundamental principles phd cotutelles excellence and interdisciplinarity and transversal skills
utility and unique chemistry of homoallylic amines with a difluoromethyl and fluoro substituted stereogenic carbon

organofluorine compounds are scarce in natural products but they are central to therapeutic science agrochemical development and materials research incorporation of fluorine atoms within an organic molecule can have profound effects on pharmacokinetic and pharmacodynamic properties enantiomerically enriched fluoro amino acids possess physiochemical and biological properties that distinguish them from canonical amino acids and are key to advances in biological sciences including peptide and protein engineering on another front many azasugars that have high pharmacological potential suffer from weak binding affinities and inferior pharmacokinetic properties this problem may be addressed through glycomimetics a promising strategy in glycomimetics entails htof and ohtocf2h exchange a compelling objective in modern chemistry therefore is the development of efficient and practical strategies for diastereo and enantioselective synthesis of readily modifiable organofluorine fragments that have a cf2h moiety however while enantioselective methods that can be used to form a csp3cf2h stereocenter are available none apply to the formation of products bearing a fully substituted carbon stereogenic center that has a cf2h and a f substituent to address this problem we will develop a robust practical and scalable catalytic strategy for practical efficient diastereo and enantioselective conversion of nitriles to homoallylic amines with a cf2h and fsubstituted allylic carbon our investigations will focus on an important but severely underdeveloped class of transformations namely catalytic diastereo and enanantioselective addition of a carbonbased nucleophile to nitriles we plan to utilize the new catalytic approach as the key design element in highly efficient diastereo and enantioselective syntheses of polyfluoro amino acids and azasugars bearing a fully substituted carbon stereogenic center that has a cf2h and a f substituent
kinetic exponent network analysis

significant efforts are underway in europe to reshore the synthesis of active chemical ingredients apis to ensure the safety and availability of medicine for its citizens this goes hand in hand with innovations and process intensification for example doing multiple chemical reaction steps in one go andor by using continuous flow reactors that are more energy and solvent efficient with a smaller footprint scalable by numberingup and cheaper to build and maintain a key issue however of doing multiple reactions at once is that different reactants and products can react thus forming a chemical reaction network crn while crns are ubiquitous in biological systems they are mostly avoided in industry due to their complex behavior and effort needed to understand and quantify them in this project i propose a new method to analyse experimental kinetic data in order to directly determine the structure of the crn to this end i will develop kinetic exponent network analysis kena to study crns that are of high interest for academia as well as industry the change in concentration at early times can be described with power laws from which the network connectivity of species population and thus the crn structure can be deduced kena could then optimize the chemical conversion and selectivity of the desired products in crns contributing to efficient api reimplementation in europe
citynaturebased solutions integration to local urban infrastructure protection for a climate resilient society

nbsinfra supports the enhancement of the local urban critical infrastructures protection against natural and manmade hazards through the naturebased solutions nbs codesign and cocreation for a climate change resilient society nbsinfra will demonstrate that the naturebased solutions are a technically viable for the protection of critical infrastructures against hazards b socially acceptable and costeffective at the local scale and c efficiently capable to increase the empowerment of communities through the increase of their ecological social and economic resilience to achieve those goals nbsinfra will establish five 5 representative european regions with an equal number of city labs nbsinfra city labs shall assess the costeffectiveness of nbs in the protection of local infrastructure and shall maximize their impact based on solutions which will be citizen owned and cocreated by endusers and managers and civil society nbsinfra will provide a toolkit that the different stakeholders and society can use to compare and choose the most effective nbs for local critical infrastructure protection being the main goal the support for the enhancement of the local urban critical infrastructure protection against hazards through nbs codesign comonitoring and cocreation for a sustainable and resilient society
preclinical validation of a novel gene therapy for a rare disease in nonhuman primates integrative approach to the cmc scaleup process validation of a gene therapy product for friedreich ataxia

founded in 2018 biointaxis is an academic spinoff company established by a team of researchers lead by a woman scientist from the research institute germans trias i pujol igtp benefiting from extensive knowhow in the identification of genes biomarkers and translational mechanisms underlying neurodegenerative disorders our leading candidate btx101 is currently the bestinclass product for the treatment of friedreichs ataxia frda a rare devastating inherited progressive neurodegenerative disease typically affecting teenagers and young adults for whom there are no treatments our product proves treatment efficacy being able to reestablish the neurological and cardiac functions in two frda mice models the product is patented wo2019076973a1 becoming the first preclinical product ever to show lifelong disease modifying activity both for neurological and cardiac symptoms in frda biointaxis has a unique knowhow based on years of fundamental research which has resulted in strong collaborations from important research centers including the research institute germans trias i pujol igtp affiliated to the universitat autnoma de barcelona top university in spain reference public hospitals university hospital germans trias i pujol in badalona the virgen del roco university hospital in seville valdecilla university hospital in cantabria public administration biocat la fundaci bioregi de catalunya and foundations la caixa federacin de ataxias de espaa euroataxia stopfriedreich ataxia etc btx101 has already been capable of attracting investment to biointaxis with a 1m seed round in 2022 after sound preclinical and clinical validation completed in the next three years btx101 will become also capable of attracting more interest from pharma customers for further validation and commercialization ultimately biointaxis aims to change the paradigm in friedreichs ataxia and to defeat rare diseases to restore patients health
mitigating diversity biases of ai in the labor market

artificial intelligence ai is increasingly used in the employment sector to manage and control individual workers one type of ai is natural language processing nlp based tools that can analyze text to make inferences or decisions a recent sage study found that 24 of companies used ai for hiring purposes in an employment context this can involve analyzing text created by an employee or recruitment candidate in order to assist management in deciding to invite a candidate for an interview to training and employee engagement or to monitor for infractions that could lead to disciplinary proceedings however the models that nlpbased systems are based on are biased additionally it has been shown that bias in an underlying ai model is reproduced in applications based on that model this can lead to biased decisions that run contrary to the goals of the european pillar of social rights in relationship to work and employment specifically pillar 2 gender equality pillar 3 equal opportunity pillar 5 secure and adaptable employment and the united nations un sustainable development goals sdgs specifically sdg 5 gender equality sdg 8 decent work and economic growth it is therefore necessary to identify and mitigate biases that occur in applications used in a human resources management hrm context addressing such concerns in an employment context is especially relevant as most existing european studies on employment discrimination have indeed found that discrimination exists both when considering individual diversity criteria and multiple criteria in intersectional analyses in order to investigate and mitigate these biases we apply this biasproject for mitigating diversity biases of ai in the labor market the chief technical objective of bias is the development of a proofofconcept for an innovative technology based on natural language processing nlp and case based reasoning cbr for use in an hr recruitment use case