Dragon09/odtu_chatbot huggingface dataset:
active young healthy mind strategies for psychological wellbeing in university students

in recent years there has been an increase in mental health problems among university students university life is socially complex and stressful and young adults often exhibit low levels of physical activity this poses a significant threat to the students mental and physical health what is urgently needed is a strategy to boost mental and physical health that can be easily accessed and integrated into a students life the first objective is to evaluate the effectiveness of mindfulnessbased stress reduction mbsr tai chi chuang tcc and highintensity functional training hift on the cognitive and mental health of university students and uncover potential mediators and moderators this study intends to explore the effects of potential mediators on physical physical activity and fitness status mental mindful thinking sleep quality and fatigue and physiological stress heart rate variability levels it will also examine the potential moderator effects of demographic factors sexgender age and educational level and individual factors cognitive reserve intelligence quotient personality on interventioninduced changes in proposed outcomes to achieve this a threearm randomized controlled trial will be conducted considering that an immersive virtual reality vr environment can offer additional benefits and improve training adherence the second objective will focus on exploring the feasibility and effectiveness of mind and body interventions using vr mbsrvr tccvr hiftvr on the cognitive and mental health among university students to do so another randomized controlled trial will be undertaken the results are expected to facilitate the development of targeted wellbeing strategies for individual students youngfitt aims to contribute to nu 2030 sustainable development goal 3 good health and wellbeing through a multidisciplinary approach combining sports science computer science and neuropsychology
utilizing spectroscopy to quantify thermal transport in flame spread

uncontrolled fire in the built and wild environment remains a major societal issue climate change and an increasing elderly population suggest a worsening of fire damage within the following years the flame spread rate vf is the principal quantity to assess the danger of a fire accurately predicting thermal transport to the unburnt material is critical to predicting the vf improved quantification of the modes by which flames spread can aid in the prevention and control of nonstationary fires combined simultaneous multidimensional temperature distributions of the gas with the condensedphase are required to calculate heat flux to the surface utile is tailored to understand flame spread fs by measuring heat flux with multidimensional ultrafast laser diagnostics a canonical fs configuration flat plate with wellknown boundary conditions and optical access will be built fsps hybrid rotational coherent antistokes raman spectroscopy hrcars will be employed for the gasphase measurements phosphor thermometry will be used to measure the surface temperature no fire studies have used simultaneous multidimensional temperature measurements of the gas and condensedphase to calculate heat flux piv will measure the airflow boundary layer and ch or oh chemiluminescence will locate the reacting flame front utile is not limited to quantifying heat flux but is a platform to advance the stateoftheart in ultrafast laser diagnostics pushing limitations in 2d hrcars and ultrabroadband hcars will decrease experimental time and increase species sensitivity to the opposed and concurrent fs studies using multiphoton excitation for phosphor thermometry has the potential to improve multidimensional surface thermometry combining a modern experimental setup with tailored laser diagnostics will provide novel data quantifying heat flux leading to fs improving vf models will benefit fire safety and refine the predictability of cfds
brainwide criticality and information processing

the brain is an adaptive system that efficiently performs unique functions in complex and continuously changing environments nearly two decades of empirical observations suggest that the brain selforganizes to operate near criticality a state located at the border between order and disorder characterized by peculiar features such as longrange correlations and scale invariance of activity maximal variability of spatiotemporal patterns and wide response range to perturbations theoretical arguments and numerical models indicate that criticality could support optimal computational capabilities by providing a favorable tradeoff between reliability and flexibility needed to achieve collective neural behaviors that underlie complex brain functions despite signatures of criticality in brain dynamics across spatial scales and systems the alleged functional role of criticality in brain functions currently lacks direct in vivo empirical confirmation in this project we aim to investigate in vivo functional advantages of brain criticality elucidating the relation between emergent brainwide critical dynamics and brain functions in zebrafish larvae due to their small size and transparency zebrafish remain the only vertebrates permitting whole brain imaging of neural activity with cellular resolution during behavioral study to probe the functional role of brainwide criticality in vivo we will develop a combined theoreticalexperimental approach to follow and perturb in nearreal time collective neural dynamics during processing of sensory stimuliand associated behavioral response learning and memory retrieval while quantifying function identifying signatures of criticality and evaluate the relation with information processing this will consist of a criticality estimator for the online decoding of neural activity and a finely tunable closedloop optogenetic stimulation strategy to drive the system away from criticality and assess its functional role
machine learning and the internet of things for optimisation of the last mile delivery

scientific advances in recent years have brought to light a series of potentially disruptive technologies in the ict landscape they are becoming and will increasingly become key enabling technologies for the development of applications and services designed to improve the quality of life of citizens and make processes more efficient among these we can identify some which research has recently focused on with particular attention machine learning and internet of things in this project we propose a combined use of these two technological enablers to solve one of the main issues which all logistics experts have to face the problem of optimising the last mile delivery lmd lmd is a crucial step of the entire delivery process as it causes bottlenecks and is typically the most costly problematic and inefficient part improving the lmd process in terms of route optimisation using classic approaches is difficult static algorithms are not suitable and even heuristic algorithms do not find highquality solutions as they do not consider several factors such as unpredictable realtime events which may occur to address these challenges a novel hardwaresoftware architecture which exploits realtime vehicles positions to continuously improve performances of the routing algorithms is proposed together with a new iotbased methodology to automaticallydynamically assign routes to drivers based on the values of a defined sixth senseparameter a ml module will predict the best among a chosen portfolio of different heuristicsmetaheuristics algorithms to optimise the route
window to the brain a game changer in the discovery of human neuronal circuitry cellular heterogenicity and biomarker profile indicative of early alzheimers disease related pathology

the molecular mechanisms leading to alzheimers disease ad are poorly understood this is due to lack of human tissue samples for research representing early changes of ad pathology the accumulating pathology including betaamyloid and tau proteins are manifested by concomitant neuroinflammatory reactions geared by malfunctional microglia microglia in the human and mouse ad brain exist in various subpopulations from which a specific diseaseassociated microglia population is thought to be involved in ad pathogenesis however there is no evidence on whether and how these specific microglial subpopulations actually impair neuronal functions in human ad brain i will now assess neuronglia network activities and functions indicative of early ad pathology in humans i hypothesize that early ad pathology selectively impairs neuronal circuits and that glial cells especially specific microglia subpopulations contribute to neuronal dysfunction and cognitive decline these events contribute to a detectable vesiclebased biomarker profile in cerebrospinal fluid and blood prior the clinical disease due to early ad pathology present in a subpopulation of idiopathic normal pressure hydrocephalus inph patients the brains of the inph patients offer a unique window to evaluate cellular and molecular events occurring during early ad i combine a series of stateofthe art techniques to answer how and what glial cell subpopulations are associated with altered neuronal network activities at subcellular and spatial resolution in human brain impacted by early adrelated pathology novel methodologies established in my lab knowhow and access to unique brain samples make me uniquely positioned to form a holistic view on how early adpathology impacts cellular functions at multiple levels this will pinpoint novel molecular targets for further validation and new fluid biomarkers
valorization of agroindustrial waste through fungi fermentation supported by digital modeling

the worlds evergrowing population demands an increasing amount of protein which cannot be sustainably met through traditional sources innovative approaches are key to procure highquality protein both efficiently and sustainably zest plans to harness technologies that can exert a global impact by producing close to user thus minimizing the carbon footprint associated with logistics from farm to table fungibased protein presents a promising solution to this challenge given its versatility in utilizing a variety of raw materials and its potential for global production zests strategy focuses on devising an enhanced fermentation production system capable of generating a diverse array of biobased protein products our primary objectives include 1 developing an efficient zerowaste automatic production system 2 designing a multipurpose bioreactor adaptable to substrates with varying viscosities and dry matter content 3assessing the entire value chains to ascertain their economic viability market potential environmental impact and sustainability of fungalbased productswith the advent of advanced technologies such as artificial intelligence ai we can embed process knowledge into control systems this ensures accessibility across both geographical and educational barriers thus equipping these solutions to deliver maximal impact on the climate crisis through their truly global applications our strategy incorporates an efficient zerowaste automatic production system that integrates feedstock screening fermentation condition monitoring and control along with downstream processing control we will employ a variety of agricultural waste streams as feedstock also zest aims to assess a range of compounds for their potential applications across various industries zests approach is geared towards driving the stateofart in protein production efficiency yield and quality with broad applications in the burgeoning biobased industry worldwide
european innovation partnership network promoting operational groups dedicated to forestry and agroforestry

innovation is a key priority for the private forestryf and agroforestry af sector and nationallylocally funded eipagri operational groups ogs can play a key role in driving innovation at the eu level however the results of the ogs in f and af have not been disseminated to all eu countries because the various localnational ogs have not been linked to the experiences of other countries and the knowledge generated has only been shared locally in order to disseminate the knowledge generated by the ogs in f and af to all eu regions forest4eu will set up multiactor innovation interregional transversal hubs dealing with 5 innovation topics wood mobilisation forest adaptation to climate change improving approaches models and tools for sustainable forest management and ecosystem service provision to improve economic environmental and social benefits for rural areas nonwood forest products agroforestry to facilitate interregional transfer of knowledge generated by the ogs forest4eu will collect share and disseminate knowledge related to innovations from f and af ogs this will be done by providing tailored and understandable dissemination materials accessible through existing platforms as well as capacity building materials developed according to identified regional needs and transferred to where the innovation can be applied forest4eu will also discuss and present the benefits of ogs relevant to the green deal to eu policy makers in addition forest4eu will establish connections with policy makers working with cap and innovation at the local level particularly in countries where ogs dealing with f and af are not funded to promote new initiatives and a greater geographic balance between different eu regions
waste avoidance strategies for environmental sustainability

aligned with the priorities of the european green deal and the farmto fork strategy combating food waste stands as a cornerstone for fostering a fair healthy and environmentally friendly food system wastewise has been conceived to design realistic pathways of food waste prevention and reduction to deliver cobenefits for climate change mitigation biodiversity and circularity wastewise employs a holistic multiactor approach across the food supply chain to measure environmental impact of food waste prevention and reduction propose evidentbased measures and drive systemic shifts for sustainable food consumption poverty alleviation and environmental sustainability in prioritized supply chainsthe ambition of wastewise is to deepen the existing knowledge concerning the real extent of environmental impacts that can be achieved through food waste prevention and reduction efforts and how they can accelerate the progress towards eus climate targets in doing so wastewise will analyse food waste data develop reliable methods to assess environmental impacts and conduct policy analysis to inform evidencebased and realistic scenarios for food waste prevention and reduction by these evidencebased insights and pragmatic scenarios wastewise equips policy makers with key information and recommendation and the instruments to accelerate progress towards climate targets the wastewise consortium comprises all relevant scientific and technical expertise spanning fw quantification environmental impact assessment innovation and policy advice supported by stakeholders through multiactors platforms ministries companies associations ngos it ensures inclusive engagement and dissemination of results fostering broad uptake across cultural and socioeconomic contexts
oncolipidomics why is lipidomic dysregulation pattern in blood similar for various cancers

lipids are involved in numerous pathways of human metabolism that are related to pathological states alterations of lipid concentrations in the blood of cancer patients have been reported but the biological origin is still unknown deciphering the mechanisms of the lipid dysregulation mechanism could dramatically change oncology because it can open new avenues for cancer detection with subsequent effective treatment and drug development targeting dysregulated pathways early cancer diagnosis is one of the main unmet needs in medicine which can improve the unfavorable prognosis of patients the potential of lipidomics has not been fully explored yet because analytical workflows have limitations in terms of accurate molar quantitation and insufficient coverage of the lipidome biologists predict up to 100000 lipid species in nature but current methods typically report less than 1 of this number here we will develop novel approaches for quantitation of more than 2000 lipids from 80 classes using 13c stable isotope labeled internal standards and ultrahighresolution methods in liquid or supercritical fluid chromatography mass spectrometry and ion mobility the comprehensive characterization of lipidome will allow us to construct cancer lipidome atlas wp1 we will develop new bayesian software for automated data processing and statistical evaluation applicable to the main lipidomic and metabolomic workflows wp2 we will correlate lipidomics data with metabolomics proteomics and transcriptomics data to unravel why lipidomic dysregulation in blood has a similar pattern for various cancers wp3 this strategy will be applied for the comparison of ten types of cancer with control samples in cell lines animal models mice and pigs human samples tissues and plasma and extracellular vesicles our initial hypothesis is that the lower activity of cers2 triggered by cancer cells can downregulate very long fatty acyl ceramides and other sphingolipids
storming immune monogenic conditions through multiomic and gene editing approaches

the human immune system controls the efficiency to respond to infections and eliminate aberrant cells such as cancer cells immune function depends on the balanced contribution of many genes encoding for receptors cytokines cell signalling molecules and transcription factors and are modulated by a wide range of environmental and epigenetic factors monogenic mutations for immunerelated genes also known as inborn errors of immunity iei provide unique examples for understanding immune fitness iei individually considered as rare diseases constitute a group of 400 immune disorders with a combined prevalence similar to leukemias 1100015000 for a given mutated gene iei patients can display a wide range of phenotypic expressivity from asymptomatic to severely impaired and different responses to treatments therefore there is an unmet need to address the wide underlying impact of iei previous eu consortia have not addressed these questions in full it is therefore needed a new generation of researchers equipped with a complete set of scientific technological and strategic skills and a wide vision to face the outstanding challenges in the iei field to this end the immerge msca dn combines the talent of leaders from different clinical and basic research and biotech environments to train 11 doctoral candidates through our research activity and training activities we will address key challenges in the field 1 to assess the functional impact of iei in different immune cell types through single cell and bulk multiomics 2 to develop computational tools for dissecting the altered cellular pathways underlying specific iei 3 to genetically correct or model iei and develop preclinical models with our strategy immerge will generate an outstanding network of professionals able to develop impactful studies that will change the field generate tools for personalised medicine and generate awareness in the society and influence policy makers
reducing bycatch of threatened megafauna in the east central atlantic

reduce will unify stakeholder efforts and utilize an interdisciplinary scientific approach to reduce bycatch of marine megafauna and inform sustainable fishery management in the eastern central atlantic ocean the diagnosis and integration of bycatch data across all industrial european fleets in the region linked with fishing effort and the spatiotemporal distribution of the species will provide a systematic approach to jointly assess and tackle policy challenges the expansion and improvement of the observer programmes and the advances in electronic monitoring and automated machine learning systems will enable speciesspecific and highresolution data of marine megafauna bycatch finescale gps tracking of selected species combined with ais fishery data in concurrent time will allow understanding key drivers of interactions and infer political responsibilities new finescale tracking data of carefully selected species in the region will allow for a better understanding of their abundance and distribution and postrelease mortality sightings fishery catches and tracking data on marine megafauna will be combined to provide a stepchanges in predictive habitat mapping approaches to understand overlap and bycatch risk from local to basinscales the combination of timeseries of sightings fishery catches gps and gls tracking and capturemarkrecapture studies will provide an unprecedented view on megafauna hotspots and the risks and impacts of bycatch boosting marine spatial planning or pelagic waters assessment and testing of mitigation measures will identify key approaches to significantly reduce bycatch in the region innovative and efficient data handling sharing and publishing will establish an integrated approach to the bycatch data community capacity and cooperation between science fishery industry and policymakers bordering eastern central atlantic ocean will be boosted by joint multidisciplinary workshops scientific training and monitoring events
mesoscopic lightmatter entanglement in hybrid solidstate networks

hybrid quantum systems couple together multiple distinct physical degrees of freedom they are essential to the quantum technological revolution as for instance the lightmatter coupling provides a way to transfer information from electronic to optical systems or vice versa they also allow studying fundamental physics of quantum informationi propose a theoretical project involving hybrid quantum networks consisting of coupled photonic and electronic systems it will lead to a stateoftheart blueprint for a quantum simulator and a set of new tools for understanding quantum mechanical entanglement in practicecurrently there are efforts to build quantum computers and simulators these systems are often based on superconducting circuits or trapped ions with one type of a system a qubit which is a twolevel system however simulating modes with multiple levels optical or vibrational systems for example is inefficient with qubits this project aims to provide novel theoretical tools for a hybrid quantum network that would fare better because it already contains optical modes the theoretical tools developed combine condensed matter physics and quantum optics including phasespace methodsi tackle the scientific objective in the following way first i focus on specific lightmatter interactions of quantum dots and microwave cavities i look into the smallest possible network of a quantum dot coupled to two cavities in this simple network i characterize the nonclassical and nonlocal correlations of the two cavities their entanglement by studying the crosscorrelations of the photons emitted by the cavities second i expand the network by connecting quantum dots to the two cavities this allows seeing the propagation of entanglement from the cavities to the terminating quantum dots finally i extend the investigations to large hybrid networks which i will use for quantum simulation and to find new effective descriptions of entanglement propagation