Dragon09/odtu_chatbot huggingface dataset:
intelligent sensing and communication as training network for perceptive mobile networks in 6g

isacnewton addresses critical challenges within various 6g wireless application scenarios necessitating precise environmental information integrated sensing and communication isac emerges as a promising paradigm to harness the synergy between sensing and communication where perceptive mobile networks pmns have been proposed to enhance existing wireless networks by incorporating accurate sensing capabilities established cellular networks offer opportunities for sensing with extensive coverage robust computation communication power and networking sensing from multiple nodes for the same target however pmns encounter significant hurdles including inherent interference complex sensing environments and highspeed target tracking by cellular networks isacnewton aims to overcome these challenges through an exceptional research and training program the vision is a fully integrated system where sensing and communication coexist sharing resources across time frequency space and power domains alongside key elements like signal processing machine learning and hardware the project adopts a multidimensional information perception 1 of the physical layer by employing innovative metasurfaces to effectively address challenges in both lineofsight and nonlineofsight scenarios 2 for robust and reliable sensing by novel prediction and situational algorithms and optimised monostatic bistatic or multistatic design for adaptive locationtime aware scheduling and improved coverage 3 for intelligent wireless radio resource management by novel machine learning enabled radio access network mechanisms for realtime decision making and zerotrust security isacnewton will provide a unique advanced multidisciplinary training programme covering all aspects of intelligent communication and sensing science field modelling design development data analysis validation and translation to the application in an harmonious synergy that enconpasses future wireless networks
manufacturing as a service to increase resilience in value networks

maasivetraditional value chains are facing challenges due to the fastmoving markets customer demands and unpredictable manufacturing and logistics to address these challenges manufacturing as a service maas is introduced as a concept that utilizes existing resources in a value network by connecting manufacturers to service providers on demand through a connected network the maasive project aims to develop models of value networks that enable companies to recover from unforeseen external events by connecting to new services and reconfiguring value networks utilizing internal and external manufacturing services maasive will provide a toolkit for industry which will consist of a blend of existing methods and technology applied in the maas context and new models and technology developed as part of the project four distinct aspects are addressed in the maasive project to increase resilience in value networks network building impact assessment reorchestration of networks and value network operation the overall aim of maasive is to increase value network resilience by enabling manufacturers to rapidly respond to unforeseen external events or sudden changes in supply or demand utilizing manufacturing as a servicemaasive uses an iterative approach to develop technical solutions and identify potential technology risks early on the project is focused on creating a toolkit from a humancentered perspective and involving professionals and workers in requirement and scenario definition the iterative approach follows three loops focusing on 1 model foundations 2 impact simulation and scenarios and 3 network orchestration and operation the results of maasive will be developed in two use case demonstratorsthe results of maasive will contribute to companies being more resilient towards external unforeseen events by being able to utilize services in a value network better and faster while also increasing utilization of network resources
braininspired intelligence for semantic video compression

the braincode project proposes novel compression techniques for extended reality xr data which are energy efficient while ensuring a reconstruction quality that satisfies the human visual semantic perception there are several challenges concerning the complexity and the power consumption of the latest video compression standards which have not yet taken into account by the signal processing communitywe propose that these challenges can be addressed by machine learning based architectures in order to avoid the exhaustivecomparisons between sequential frames we aim at releasing a semantic video compression algorithm that uses convolutional neuralnetworks cnns and drives the bit allocation with respect to the content of the visual scene another goal of braincode is to mimicthe visual system as an intelligent mechanism that processes the visual stimulus this can be claimed as it consumes low power itdeals with high resolution dynamic signals and the dynamic way it transforms and encodes the visual stimulus is beyond the currentcompression standards during the last decades a lot of effort has been made to understand how the visual system works what is thestructure and role of each layer and individual cell that lies along the visual pathway and how the huge visual information ispropagated and compacted through the nerve cells before it reaches the visual cortex there are very interesting mathematicalmodels which approximate the neural behaviour and they have been widely used for image processing applications includingcompression the braincode project searches the latest neuroscience models for the design of a groundbreaking xr video compressionarchitecture the efficiency of the above approaches is expected to improve several image processing applications like computervision virtual reality and video compression among other where the realtime processing of the visual scene plays a substantial role
nonverbal multimodal social intention modelling

an underexplored problem in social signal processing ssp is human social intent detection ssp develops automated systems to interpret human social behaviour from sensors such as cameras microphones and wearables prior work estimating intent uses scenarios that are constrained enough so that the intent is determined by a congruent outcome in reality this is not true otherwise emergent leaders are never female because they do not speak up and black minorities are criminals because they are often seen interacting with police neon addresses intention detection in more openended contexts involving large unstructured social gatherings such as networking or mingling events during these events there are no prearranged conversations multiple conversations can occur at the same time and all conversation come about via coordination with multiple independent actors with their own possibly conflicting goals how do we train machines to perceive plausible intentions asking the individual to continuously report on their immediate intentions would contaminate their spontaneous social behaviour neon hypothesises that plausible social intentions are perceivable by external observers though the explanations of why based on the behaviours of the individual and the surround social context may vary depending on the perceivers own life experiences to this end neon will develop a novel framework to harvest and learn from social intentions and their relation to future outcomes using a novel multitask learning set up that clusters both on the traits of the perceivers as well as the observed individuals a unified theory that situates conversations in free standing groups in both space and time and a novel graphical neural network architecture to model it through multisensor cross modal learned neural representations aside from being a significant advance for ssp neon also benefits a range of other fields from humanrobot interaction to organisational psychology
molecular mechanisms of gpcr heteromers signaling

g protein coupled receptors gpcrs are key mediators of how cells sense and react to their outside environment traditionally these receptors have been thought to function as individual units at the cell surface over the past decade new evidence has shown they can assemble in larger complexes to form new signaling entities and vastly expand a cells capacity to respond to its environment thanks to their strong tissuespecificity these complexes termed heteromer also form important targets for the development of new drugs with less side effects still our understanding of the molecular mechanisms by which assembly of gpcrs in complexes transform their signaling properties remain extremely sparse my proposal investigates how heteromers interact and integrate changes in their environments to generate unique cellular responses i focus my research on the mglu25ht2a heteromer as its existence has been demonstrated in humans and is involved in schizophrenia a debilitating condition that urgently requires new treatments this proposal is organised in three objectives1 a too often overlooked component of a gpcr environment is the lipidic membrane it is inserted in using a multiscale biophysics approach i will characterise the essential role lipids play in the assembly and function of heteromers but also how receptors themselves change the membrane they are inserted in to transmit information2 i will use cryoelectron microscopy to solve the first structure of a heteromer bound to its signaling partners g proteins i will go even further and develop cuttingedge em tools to resolve a highresolution movie of a gpcr heteromer signaling cascade from receptor assembly to g protein activation3 finally using single particle cryoem and fluorescence i will investigate how heteromers recruit other partners which in turn modify receptors to form these new signaling units
tracing visual computations from the retina to behavior

every second millions of bits of information enter our eyes how does the brain identify taskrelevant information from this gigantic input stream this key challenge of the visual system is tackled by substantially processing the sensory input for behavioral relevance already in the retina the frontend of the visual system neuronal circuits extract multiple features from the environment and form up to 40 channels to the brain so far however one of the basic principles underlying vision namely how the brain processes these multiple channels from the eye remains fundamentally unclearin this proposal i will focus on the superior colliculus an evolutionary conserved retinorecipient brain area critically involved in visuomotor transformations and solve the following problem how do neuronal circuits in mouse superior colliculus integrate retinal signals to drive behavior i will implement an interdisciplinary approach that combines population imaging of neuronal activity in behaving mice with optogenetic manipulations deep neural network modeling and quantitative behavioral analysis by modeling a defined brain area all the way from the retinal input to its role in behavior in an ecological setting i will mechanistically dissect the behavioral relevance of retinal circuitsmy work will uncover general principles of how diverse retinal channels are represented in downstream targets identify elemental convergence rules of feedforward retinal signals in postsynaptic neurons and causally link retinal function to distinct behaviors if successful my proposal will reveal fundamental neuronal and computational mechanisms used by the visual system to convert a complex visual input into action my approach can be adapted to other sensory modalities guiding the design of innovative experiments and analyses the identified mechanisms of efficient information processing will also contribute to the development of robust neuroinspired artificial intelligence
photocatalytic methylations via direct methane functionalization

methane is one of the most abundant underutilized carbonbased chemical feedstocks on the planet moreover the simplest alkane is one of the most potent greenhouse gases in the atmosphere due to which united nations has lunched the global methane initiative for achieving a 30 reduction in its emission by 2030 the current methodologies for the utilization and disposal of methane gas suffer due to being cost intensive and nonsustainable as a result there is an urgent need to develop protocols which allow the transformation of this greenhouse gas into valuable products in a profitable manner on the other hand the selective substitution of ch bonds in drug candidates to cme bonds have often led to an average 100fold increase in their biological activity magic methyl effect as a result protocols which allow the selective incorporation of methyl groups into organic substrates have gained wide attentionthe proposed project aims at developing efficient catalytic processes that allow direct methane functionalization by using it as a methylating reagent in a variety of cme bond forming reactions through dual transition metal photoredox catalysis new pathways for the direct use of methane in reactions such as crosscouplings ch methylations and cascade cyclizations will be developed based on this novel bimetallic photocatalytic strategy it is envisioned that the proposed research will open new avenues for the utilization of methane as feedstock for the synthesis of drugs and biorelevant molecules thus contributing to the reduction in the emissions of this gas and helping to reach uns global methane initiative and to eus european green deal objective of achieving zero net greenhouse gas emission by 2050
understanding latin american challenges in the 21st century

social political and cultural transformation a fastchanging global economy geopolitical tensions and global uncertainties have created a markedly different context from the previous era of european union eu policies towards latin america and the caribbean lac the doctoral network laceu will establish a novel comprehensive and interdisciplinary framework to understand lac and its relationship with the eu fostering respectful noneurocentric research and engagement it will enable a better understanding of current challenges in latin american governance and support sustainable equitable and successful relations between the eu and laclaceu offers doctoral candidates an outstanding integrated fouryear phd programme and provides world class interdisciplinary research and training in social and political sciences law and the humanities as well as research exchanges and policyrelevant secondments at associated partners in the eu and lac research themes within laceu include the rise of populism democracy gender rights trade migration health global cities sustainability and green finance and cultural learning the laceu doctoral programme comprises an interdisciplinary multisectoral network composed of four leading european universities an outstanding lac higher education institution and key highly relevant civil society and policy partners from a range of european and lac countries it offers an exceptional combination of academic and researchrelated training and transferable skills to deliver scientific excellence occupational mobility and preparation for lifelong policyrelevant learning for a new generation of researchers furthermore it provides the eu with the vital inputs needed to design coherent sustainable equitable and comprehensive policies towards lac and to promote an effective and respectful interregional engagement that enhances the potential for mutually beneficial partnerships in global and multilateral fora
rural structural transformation in developing countries

a key feature of economic development is structural transformation characterized by spatial and sectoral labor reallocation out of agriculture despite clear evidence of ruralurban migration flows in developing countries recent contributions show persistently lower productivity in agriculture compared to other sectors and large disparity in agricultural productivity across space this points to the key question of this proposal why do so many workers remain in agriculture there is a pressing need for reliable answers to this question as rural areas host large shares of the population facing high agricultural risk and poverty incidence any effective poverty eradication policy such as those envisioned by the uns sustainable development goals must therefore necessarily focus on rural development rustdec will obtain novel answers to this key question by combining innovative micro panel data from subsaharan africa and southeast asia with an array of geospatial data on rural areas exogenous variation in agricultural productivity and quantitative theoretical models the project employs remotesensing and computer vision methods for generating community data as well as quasiexperimental and structural estimation techniques for rigorous causal estimation to pursue three major objectives i provide first evidence on the role of dynamic adjustments in agricultural production for explaining the agricultural productivity gap and the magnitude of factor misallocation ii dissect the microeconomic anatomy of spatial and sectoral labor reallocation and skill selectivity within and across rural communities and iii identify the historic and future impact of climate change on agricultural production adaptation and rural development and its implications for the productivity gap these objectives address three welldefined gaps in the literature each going beyond the specific stateoftheart and with the potential of generating groundbreaking impact
nutrient fluctuations and the integrative stress response as metabolic cell fate determinants in b cell lymphoma

metabolic reprogramming enables cells to adopt different phenotypes providing flexibility in response to environmental stress of particular relevance during tumour development i recently demonstrated that the transcription factor mitf known regulator of cell transitions in melanoma controls the expression of the fatty acid fa desaturase scd1 the mitfscd1 axis maintains cell differentiation while its suppression by starvationinduced integrative stress response isr originates dedifferentiation and melanoma progression our findings support that metabolic rewiring and phenotype switching are interconnected events that govern tumour progressionas in melanoma bcell differentiation depends on mitf activity fa metabolism and a dynamic modulation of isr but weather an interplay among these factors dictates bcell fate is still unknown importantly mitf is regulated by mtorc1raggtpase signalling pathway frequently mutated in bcell lymphomas i hypothesize that the isrmitf axis and fa metabolism enable normal and pathological b cells to adapt to stress and critically licenses switches in phenotypic identity and bcell behaviour thus i will establish if and how mitf and fa composition control bcell transitions and impact lymphomagenesis along with its regulation by the isr we propose that abnormal isr and mitfscd1 deregulation corrupts bcell differentiation process contributing to lymphomagenesis this proposal aims at shedding light on the interplay between nutritional signals and stressrelated cellular responses that precipitate cancer cell transitions through the regulation of specific transcriptional programs controlling metabolic rewiring
running in the family understanding and predicting the intergenerational transmission of mental illness

mental illness runs in families the family consortium aims to improve the life of mentallyill persons with novel prediction models that are based on better understanding the mechanisms of intergenerational transmission of mental illness the objectives are to improve causal understanding and gain prediction power from the family context by the innovative combination of statistical modelling of genetically informed designs causal inference multimodal and multilevel normative prediction and molecular mapping brought by worldleading neuroscientific expertise of the consortium and address key bioethical and social issues raised by the concept of intergenerational risk transmission and risk prediction family will bring together the largest existing human epigenetic and neuroimaging datasets from both withinfamily population cohorts and familial highrisk offspring studies as well as utilise innovative animal models to shed light on pathways underlying intergenerational risk transmission family will focus specifically on risk for mood and psychosis symptoms and diagnoses indepth causal analyses of how and when risk for mental illness occurs will help identify early risk and resilience factors and predict who is likely to be diagnosed or develop symptoms of mental illness advanced insights can uncover new targets for the development of preventive strategies to break the intergenerational cycle of mental illness and to support strengths and resource building an immediate benefit will be to open direct translational perspectives to mental health care professionals by providing new familybased risk prediction tools for the early identification of adults and children at risk and to deliver ethical guidelines to guide its implementation this will accelerate preventive and treatment intervention in vulnerable families and help target resilience strategies to prevent the transition from health to disease despite high familial risk
indirect optical geometry measurement

optical metrology is driving our society forward and has strong impacts on manufacturing mobility medicine and fundamental science this is highlighted by the si revision in 2019 and the nobel prize winning microscopy with visible light in the nanometre range in 2014 optical techniques allow fast and precise geometry measurements but only if sufficient light energy is reflected from the objects surface to the photo detection unit for this reason specific measurement approaches for each surface type had to be developed such as deflectometry for highly reflective surfacesto provide one single measurement approach applicable to any surface and with the potential of submicrometre resolution inogem will initiate a paradigm shift instead of measuring the objects surface the geometry of the surrounding gas is measured the surrounding gas is detected optically by using tiny wellcontrolled fluorescent particles or molecules a confocal microscope and a modelbased signal processing which enables submicrometre resolution this will break new grounds for assessing additively manufactured parts and lightweight components made of fibrereinforced composites because the indirect measurement is less sensitive regarding the varying optical properties of the measurement objects surface and materialfurthermore indirect optical geometry measurements are possible at strongly curved or translucent objects even through a limited access which is currently considered impossible such challenging conditions occur eg for gears and additively manufactured parts so that inogem has a large potential for lownoise gears emobility and fuel cells hydrogenas a result fast geometry measurements with a today unachievable precision below classical limits are achieved in the nanometre range for a wide range of applications by developing the framework of a new class of measuring instruments inogem takes the field of optical geometry measurements to the next level