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Hovedmålet med kreftbehandling er å eliminere kreftceller og dette er tradisjonelt oppnådd ved kirurgi, bruk av giftige medikamenter (cellegift) og stråling. En ny og betydningsfull tilnærming til kreftbehandling kalt immunterapi, har derimot fått mye oppmerksomhet det siste tiåret; Her forsøker leger og forskere å utnytte immunsystemet vårt for å målrettet  ødelegge kreftceller. En nøkkelaktør i denne banebrytende tilnærmingen er en gruppe «drapsmenn» i immunsystemet kjent som cytotoxiske T-lymfocytter (CTL-er). Disse cellene har en bemerkelsesverdig evne til å oppdage kreftceller ved å gjenkjenne unormale molekyler på overflaten av kreftcellene - molekyler som friske celler ikke har. Når CTL-er gjenkjenner kreftcellene ødelegger de dem ved å frigjøre giftige molekyler som initierer kreftcellenes selvdestruksjon. 
 
Selv om betydelige innsats har blitt dedikert til å forstå hvordan CTL-er aktiveres og hvordan de gjenkjenner kreftceller, vet vi mindre om de påfølgende hendelsene inne i kreftcellene som fører til deres død. Fra før vet vi at CTL-er kan initiere to forskjellige typer celledød i kreft: den første, kalt apoptose, er en stille og ordnet prosess der kreftcellene krymper og brytes opp uten å varsle immunsystemet; den andre, kalt pyroptose, er en mer dramatisk prosess som involverer dannelse av åpninger i cellemembranen, noe som fører til at cellene svulmer opp og sprekker. Under denne cellebristen blir innholdet inne i cellene frigitt i omgivelsene, og dette kan fungere som 'faretegn' som kan stimulere en sterkere immunrespons mot kreftcellene. Betydningen av denne cellebristen for å forsterke anti-tumorresponsene vil bli undersøkt i dette prosjektet. 
 
Videre er vi fascinert av muligheten for å avdekke ytterligere, ennå ukjente, former for celledød indusert av CTL-er. Utforsking av disse dødsrelaterte prosessene i kreftcellene kan potensielt øke effektiviteten av immunterapi og bidra betydelig i den pågående kampen mot kreft.

The primary goal of most cancer therapies is to induce cancer cell death. Immunotherapy relies on the cytotoxic activity of lymphocytes such as natural killer cells (NKs) and cytotoxic T lymphocytes (CTLs) to achieve this. While a significant amount of research in immunotherapy focuses on the events within cytotoxic lymphocytes or at the interface between cytotoxic lymphocytes and cancer cells, less is known about the molecular mechanisms that orchestrate cancer cell death, particularly in the case of CTL-mediated death.
CTLs are known to induce two types of cell death in cancer: non-inflammatory apoptosis and proinflammatory pyroptosis. Pyroptotic cancer cells release proinflammatory signals that attract immune cells to the tumor site, thereby enhancing the anti-tumor response. Cell lysis is a common outcome of pyroptotic cell death. It is unclear whether lysis can be decoupled from pyroptosis in cancer cells and whether the proinflammatory properties of pyroptotic cancer cell death depend on lysis. Moreover, it remains unknown whether CTLs can induce other forms of cell death in cancer, apart from apoptosis and pyroptosis.
Studying the mechanisms of CTL-mediated cancer cell death is challenging because CTLs selectively target cells expressing specific antigens. However, given the critical role of CTLs in immunotherapy, it is essential to deepen our understanding of CTL-induced cancer cell death.
This project aims to develop novel methodologies to investigate the death mechanisms that are initiated by CTLs. In addition, we will identify new pathways and mediators involved in CTL-induced cancer cell death. Furthermore, we will assess the contribution of proinflammatory cell death and lysis in promoting anti-tumor responses in vivo. Overall, this research will improve our knowledge of the molecular mechanisms of CTL-mediated cancer cell death and potentially reveal novel targets to enhance the efficacy of cancer immunotherapy.

T-cell-mediated proinflammatory cell death and lysis in cancer

En av de vanligste, men minst studerte, utfordringene med å bli eldre er problemer med å kommunisere. Mange eldre sliter spesielt med pragmatiske ferdigheter, som å forstå undertekst, eller tilpasse det de sier til personen de snakker med. 

La oss si at en lege må gi en alvorlig beskjed til en pasient. For å gjøre det litt lettere å takle, bruker legen vagere språk, som "kanskje" i stedet for "sannsynligvis". Mens yngre voksne ofte tar hensyn til høflighetsstrategier i måten de tolker det som blir sagt på, har eldre ofte vanskelig for å forstå når noen snakker indirekte. Mange eldre voksne har vanskelig for å forstå ikke-bokstavelig språk og kan misforstå alvorlighetsgraden av diagnosen. Dette kan påvirke beslutningen deres om behandling, noe som kan føre til utilsiktede konsekvenser. 

Siden god kommunikasjon er viktig både i viktige medisinske samtaler og i hverdagen, er det viktig at vi finner ut hva som gjør at eldre kan ha vansker med å forstå og bli forstått. RESILIENCE skal hjelpe til med denne utfordringen ved å samle data om praktiske, kognitive og språklige ferdigheter hos voksne i alderen 18-90 år over tid. Dette vil gi oss en stor mengde data om pragmatiske, kognitive og språk ferdigheter og gjøre det tilgjengelig for forskning. Med denne dataen som grunnlag har vi følgende mål: 

• Forstå hvordan praktiske evner endrer seg generelt gjennom voksenlivet. 
• Finne ut hvilke mekanismer som påvirker pragmatiske evner på forskjellige tidspunkter i livet.
 • Utvikle en teoretisk modell som forklarer hvordan pragmatiske ferdigheter endrer seg med alderen.
 • Lage algoritmer som kan forutsi hvordan pragmatiske evner vil utvikle seg for enkeltpersoner i årene som kommer. 
• Utvikle og teste et verktøy som kan måle pragmatisk helse (både pragmatiske ferdigheter og deres underliggende mekanismer), noe som kan åpne  for å iverksette tiltak. 

Dette vil gi oss muligheten til å forstå bedre hvordan folk kan utvikle pragmatisk resiliens gjennom livsløpet.

A cornerstone of human communication is our reliance on pragmatic skills to guide linguistic interactions (e.g., reasoning about others' mental states to bridge the gap between what is said and intended in conversation). However these skills are highly sensitive to age-related decline, leading to miscommunication and uninformed decision making in the older adult population. This raises an important question, one which has puzzled linguistics and psychologists for decades: if pragmatic competence is fundamental to communication, why do individuals vary so much in this capacity? 

Traditionally, psychologists have approached pragmatic competence from a cognitive angle, reasoning that individual differences in executive functions (i.e., the cognitive skills associated with goal-directed actions) are what underlie effective pragmatic behavior. In a similar vein, language scientists have taken a linguistic approach, reasoning that one’s language background (e.g., the frequency with which individuals shift between languages) shapes pragmatic skills by enhancing sensitivity to the communicative context. This focus on either cognitive or linguistic influences has resulted in two expansive yet disparate areas of research.

RESILIENCE will unite these disciplines to pursue a longstanding debate on what underlies pragmatic resilience and decline using a large-scale, interdisciplinary and longitudinal approach. By gathering data on adults' (ages 18-90) pragmatic, cognitive and language skills over multiple time points, we will develop a comprehensive theoretical model that explains how cognitive and linguistic systems interact to shape pragmatic competence as we age, and create algorithms that predict the trajectory of an individual’s pragmatic abilities in upcoming years. Based on these results we will design a multidimensional tool that detects the earliest signs of pragmatic deficits, leading to future interventions, allowing us to uncover the paths to pragmatic resilience.

Uncovering the paths to pragmatic resilience

Noen av oss tåler stressende livshendelser godt. Andre derimot utvikler vedvarende fysiske og psykiske plager som følger av stress. Hvor godt vi håndterer stress avhenger av et komplekst samspill mellom miljøfaktorer, sosiale forhold, biologisk sårbarhet og indre motstandskraft. Forskning på stressreaksjonene til dyr og pasientgrupper som til vanlig lever under mye stress viser at en gruppe signalstoffer i kroppen som aktiverer det samme hjernesystemet som cannabis – endocannabinoidene – kan begrense styrken på stressreaksjoner og bidra til at man raskere kommer seg til hektene. I dette prosjektet skal vi undersøke hvordan mestring av stress på kort og lang sikt henger sammen med nivåer av endocannabinoider i kroppen for å forstå hvorfor noen personer er mer motstandsdyktige mot stress enn andre. I den ene studien følger vi pasienter som skal gjennomgå en stressende, men veldig vanlig, situasjon: kirurgi. Her måler vi pasientenes opplevelse av stress, samt mentale og fysiske helse, fra tiden før til to år etter operasjonen og undersøker hvordan dette henger sammen med nivåene deres av endocannabinoider og andre stresshormoner. I den andre studien bruker vi data fra et eksperiment hvor deltakerne har blitt utsatt for psykososialt stress til å undersøke om endocannabinoidnivået deres påvirker hvordan de reagerer på stress, og om stresset i seg selv kan påvirke kroppens produksjon av endocannabinoider. Til syvende og sist er målet med studien å vurdere hvorvidt målinger av endocannabinoidnivåer kan brukes til å forebygge helseplager og til å evaluere behovet for økt oppfølging etter alvorlig stressende påkjenninger i livet.

In the face of major life stressors, some individuals cope well whereas others develop ill health and long-term adverse outcomes. Predicting who needs additional support in response to major life stressors is essential for targeted prevention and more efficient allocation of resources. The endocannabinoid system is emerging as a promising target for understanding vulnerability and resilience to stress. This system appears to buffer stress in two ways: by limiting the magnitude of the stress response, and by facilitating recovery after a stressful event. While the early findings are intriguing, they mainly stem from studies in rodents and small clinical groups with high stress burden. What role endocannabinoids have more globally for human resilience, health and well-being remains elusive. 

In this project we address this gap by leveraging comprehensive experimental and clinical data on two potent stress models: psychosocial stress and surgery. Drawing on these unique datasets, which combine experimental control with ecological validity, we will decipher how endocannabinoid levels influence people’s stress response and recovery across minutes, days, weeks and years. The project represents a novel directional shift for endocannabinoid research and will (i) determine the value of endocannabinoid levels as a biomarker to predict outcomes after surgery, (ii) quantify sex differences, (iii) assess endocannabinoid interplay with opioid analgesics, sex hormones and other stress markers (iv) spearhead open and reproducible science practices in endocannabinoid research, and (v) make this fine-grained and novel data available through an interactive web application. 

This project represents an ambitious effort to understand endocannabinoids’ role in stress resilience and will determine the value of endocannabinoids as a predictive biomarker and potential target for individualized treatment.

Deciphering endocannabinoid stress buffering in humans: 
Mechanistic and clinical investigations

BOLD MINDS aspires to enhance the understanding of vulnerability factors underlying the emergence of borderline personality disorder (BPD), with an ultimate aim of increasing the potential for young individuals to receive early, evidence-based help when their mental health is at risk. BOLD MINDS will achieve this by investigating whether disruptions in two aspects of autobiographical memory (AM), narrative identity (NI) and involuntary AM (IAM), are associated with BPD features and problem behaviours in adolescents concurrently and over time. In doing so, BOLD MINDS will strengthen the understanding of mechanisms underlying the emergence of BPD in adolescence and lay a groundwork for developing evidence-based early interventions for BPD. While currently limited, the study of AM in this field is essential for two reasons. Firstly, because the aspects of AM under investigation, NI and IAM, are known to be involved in identity formation and emotion regulation which represent two key psychological processes that are disrupted in adults with BPD and are linked to problem behaviours such as self-harm and suicidality. Secondly, because promising research is emerging on the use of AM targets in the treatment of emotional disorder in adults, and provides a strong model for future treatment development with vulnerable adolescents. In addition, this timely research program aligns with calls from international organizations to prioritize early interventions to promote adolescent mental health. BOLD MINDS will adopt and adapt state-of-the-art ecological momentary assessment and analytical techniques and work at the crossroads of clinical and cognitive psychological perspectives, allowing for a multidimensional approach to understanding BPD vulnerability. Training-through-research and formalized training of the experienced researcher will prepare her for a permanent academic position and the founding of her own research lab specializing in AM and early interventions for BPD.

Borderline Personality Disorder: Memory and Identity in Adolescence

The goal of the Bilingual Experiences, Cognitive Ageing and underlying Mechanisms (BECAME) project is to examine the functional neuroplastic mechanisms underlying mitigatory effects of bilingual experience on age-related cognitive decline. While evidence is available for structural brain changes supporting bilingualism-induced effects on cognitive aging (CA), functional mechanisms underlying such effects are not yet well understood. BECAME aims to fill this gap by investigating the trajectory of bilingualism-induced functional neuroplasticity across the adult lifespan (ages 18-85), crucially adopting an individual differences approach related to measurable degree of bilingual engagement. Importantly, although such benefits are thought to be rooted early in the lifespan, evidence for the timeframe and conditions of their early emergence is scarce. The choice of including the whole adult lifespan allows us to investigate these mechanisms and their emergence more directly from a lifespan perspective. I combine behavioral testing with brain recordings via electroencephalography (EEG). EEG is widely used in cognitive neuroscience to assess brain activity and the degree of communication between brain regions (functional connectivity) in response to stimuli and at rest. Combining behavioral and EEG modalities will allow me to test bilingualism’s effect on functional connectivity, as well as its consequences for functional efficiency, the minimum required neural activation to successfully perform a task. This will enable a detailed, evidence-based account of the protective effects observed in older-aged bilinguals, and how they are built from earlier life stages. By illuminating the relationship between multilingualism and resulting neurocognitive adaptations, BECAME will enable to capitalize on it as a health initiative, with manifold societal implications and the potential to be translated into actionable policies exploiting multilingualism to ameliorate effects of CA.

Bilingual Experiences, Cognitive Ageing and underlying Mechanisms

WHeelchair Activity Monitoring project (WHAM)

Wheelchair users (WCU) are three to five times more inactive than the general population, leading to a high risk of developing preventable secondary conditions. Although physical activity (PA) guidelines have been specifically developed for WCU, we lack systematic approaches to implement them in practice, as well as valid algorithms to monitor PA change in WCU through sensor-based solutions. Accordingly, the overall scientific aim of the WHeelchair Activity Monitoring project (WHAM) is to advance PA research and practice in WCU by developing valid digital markers for monitoring of and providing feedback on PA, paving the way for implementation and intervention. I will accomplish this through combining the complementary research fields of 1) behavioural intervention studies focusing on increasing PA in WCU (core competence University of British Columbia, UBC; outgoing phase) and 2) sensor-based PA monitoring (core competence Norwegian University of Science and Technology, NTNU; returning phase – consolidated by non-academic placement at Maastricht Instruments, which develop research prototypes including PA monitors). WHAM’s scientific aim is achieved through three objectives: 1) Measure the effect of a pragmatic exercise intervention trial on self-reported physical activity levels and cardio-respiratory fitness, 2) Develop valid algorithms for tracking PA markers in WCU, and 3) Co-create a framework that outlines how PA can be conjointly monitored and provided feedback on in WCU. This fellowship will enable me to become established as an internationally recognized researcher in the field of “physical activity and disability”, while bringing together ongoing national disjointed research activities in this field. Altogether, my overall ambition is to contribute to reducing inequalities in daily-life participation among WCU compared to the rest of the population.

Per- og polyfluorerte stoffer (PFAS) er en stor gruppe menneskeskapte kjemikalier med høyt fluorinnhold som antas å ha negative helseeffekter. Kilder til PFAS kan være produksjon av vann-, varme- og flekkbestandige produkter og disse kjemikaliene er en del av hverdagen vår. PFAS påvirkning av biologiske systemer er ikke fullstendig forstått. Noen PFAS er antatt å øke risikoen for å utvikling av ikke-alkoholisk fettleversykdom (NAFLD) og øke risikoen for diabetes. 

For å forstå hvordan PFAS påvirker organene våre ønsker vi å bruke små laboratoriedyrkede organmodeller, kalt organoider. Disse miniatyrorganene kan dyrkes fra menneskelige stamceller og tilbyr et kontrollert miljø for å studere hvordan PFAS påvirker f.eks lever og bukspyttkjertelen vår, uten bruk av dyreforsøk.

For å studere helseeffekter må vi kunne måle nivået av biomolekyler som fettstoffer i leveren og hormoner i bukspyttkjertelen. Til dette trenger vi å utvikle analytiske verktøy for å måle effektene. Først vil vi bekrefte at når leverorganoidene eksponeres for enkelte PFAS-forbindelser utvikles det NAFLD-lignende sykdom ved å sammenligne den biokjemiske profilen (proteiner og metabolitter) til organoider av lever med PFAS-eksponerte organoider. Deretter vil vi utvide den analytiske verktøykassen for å undersøke hvilke metabolske veier som påvirkes, og om effekten er den samme i NAFLD-induserte og PFAS-eksponerte organoider. Vi vil også eksponere insulinproduserende bukspyttkjertelorganoider for PFAS for å undersøke effekten av PFAS på hormonproduksjon. Når effektene av PFAS-eksponering på lever- og bukspyttkjertel-organoider er etablert, vil organoidene bli samkultivert i en chip, og effektene av PFAS-eksponering vil bli undersøkt og sammenlignet med individuelle organoider.

Persistent organic pollutants (POPs) are believed to contribute to metabolic diseases, such as non-alcoholic fatty liver disease (NAFLD) and type 1 diabetes. HE-POP aims to investigate the effects of per- and polyfluoroalkyl compounds (PFAS), a type of POPs), on organ function in a controlled environment.

Organoids are multicellular laboratory-grown miniature organs, that are grown from stem cells. HE-POP will use organoids to examine how PFAS affects our organs and develop cutting-edge bioanalytical tools and methodology to measure these effects using liquid chromatography-mass spectrometry. HE-POP hypothesizes that PFAS negatively affects organ function, as evidenced by changes in hormone and lipid levels characteristic of NAFLD and type 1 diabetes. 

Organoids offer a controlled environment to study the effects of PFAS on the liver and pancreas, without the use of animal models. HE-POP aims to gain evidence of the negative effects of PFAS on organ function through controlled experiments on organoids and aid in understanding the biological mechanisms underlying NAFLD and type 1 diabetes.

HE-POP has fundaments in UN sustainable development goals, specifically #3, #12, and #14/15, seeking an understanding of diseases with worldwide prevalence, and understanding how POPs affect our life and surroundings and help enable the right regulatory actions and replacement chemicals.

HE-POP: Studying the Health Effects of Persistent Organic Pollutants, Using Mass Spectrometry, Organoids, and Organ-On-A-Chip

Rundt 7% av norske 4-åringer har så store psykiske vansker at de kvalifiserer for en diagnose, men det tar ofte lang tid fra vanskene oppstår, til de blir oppdaget og barna får rett hjelp. Myndighetene har derfor lagt tydelige føringer for at de som jobber med barn, må vite hva de skal se etter og hvordan de skal gå frem for at barna skal få den hjelpen de trenger. I Norge går over 95% av barna i barnehage hvor pedagogene blir godt kjent med barna over tid i deres naturlige miljø og har utviklingssamtaler med de foresatte 1-2 ganger i året. Barnehagen skulle derfor være en ideell arena for tidlig oppdagelse av psykiske vansker. Det har imidlertid ikke vært tilgjengelig noen tilpasset metode for de arbeidsformene og terminologi som er vanlig i barnehagene. Vi har derfor utviklet metoden Dialogbasert tidlig oppdagelse (DBTO) i nært samarbeid med pedagoger og foreldre i 8 ulike barnehager. Metoden går ut på å bruke utviklingssamtalen mer systematisk ved at både foreldre og barnehagelærer på forhånd fyller ut et spørreskjema om mulige bekymringer de har hatt for barnets utvikling og trivsel de siste månedene. I samtalen kan de så utforske og forsøke å enes om forståelsen av barnet og om det er behov for ytterligere vurdering eller andre tiltak. Tilbakemeldingene under utviklingen og tidlig utprøving tyder på at metoden fungerer godt og oppleves som et nyttig verktøy i foreldresamarbeidet. For å få tydeligere dokumentert kunnskap om hvordan DBTO fungerer i barnehagene, har vi utviklet forskningsprosjektet PRO-DIALOG. Vi ønsker med det å få kunnskap om (1) hvordan DBTO fungerer som et screening-instrument, (2) hvor brukervennlig den er, (3) hvordan den påvirker tidspunkt for igangsetting av tiltak og (4) hvordan den påvirker utviklingen av den psykiske helsen til barna over tid. 12 barnehager er plukket tilfeldig ut til å gjennomføre metoden, mens 11 skal fungere som kontroller. Foresatte til rundt 300 barn som har tre år igjen av barnehagen, vil bli spurt om å delta.

There is an unambiguous call for early interventions at the municipal level for children at risk of developing mental health problems. However, there is a surprisingly absence of socially valid methods for detecting children in need of early support.
        The aim of the project is to establish the properties of such a novel method; Dialogue Based Early Detection (DBED). We will study its properties as a mental health screener, how well it is adapted in an ordinary kindergarten context, and whether it affects activation of interventions for mental health concerns and children’s future mental health.
        The novel aspect of DBED is the systematic assessment of the child’s development and well-being by the kindergarten teacher and his/her parents, and the subsequent dialogue that aims to explore and converge their understanding of the child and conclude whether there is a need for further assessment or supportive actions.
        Parents of approximately 300 children in 23 different kindergartens aged 2-3 years will be invited to participate for the three last years before school start and follow-up the next two years. The kindergartens will be randomized to an implementation group or a control group. Parents’ socio-demographic characteristics and data from parent-teacher meetings, initiated interventions, user satisfaction, parental stress, and child mental health will be collected biannually, as well as tape recordings from interviews about user experiences of parents and teachers.
        The most critical challenges of the project will be participation rate of the invited parents in addition to attrition due to the time pressures in a busy workday in the kindergartens, and willingness of the control parents to complete the repeated questionnaires. Appropriate measures are made to take those risks into account.

Promoting mental health in young children – a sustainable dialogue based approach in kindergartens (PRO-DIALOG)

Dette prosjektet, kalt Hukommelse for musikk, fokuserer på det økende antallet mennesker over hele verden som lever med demens, spesielt Alzheimer's sykdom (AD). AD starter typisk med hukommelsesproblemer og påvirker etter hvert daglige aktiviteter. Aktive musikkintervensjoner, spesielt sang, har vist positive effekter på humør, atferd og livskvalitet for personer med demens, men deres innvirkning på kognisjon er ikke godt forstått. Prosjektet har som mål å fylle dette kunnskapsgapet ved å studere effektene av å lære nye sanger på kognitiv, atferdsmessig og hjernemessig funksjon.

Studien vil omfatte hjemmeboende voksne over 65 år med AD fra Argentina, Østerrike og Norge. Deltakerne vil gjennomgå 5 måneder med intensiv musikalsk opplæring (to ganger i uken) og 5 måneder med minimal opplæring (en gang i måneden) i tilfeldig rekkefølge, med en to måneders pause imellom. Intervensjonene inkluderer å lære nye sanger med en personlig musikklærer. Generell kognisjon vil bli målt ved bruk av Alzheimer's Disease Assessment Scale - Cognitive (ADAS-cog), og hukommelse for musikk vil bli vurdert gjennom ulike metoder, inkludert atferdsoppgaver og hjerneaktivitet (EEG). Humør vil også bli evaluert i hver økt.

Målet er å inkludere 113 deltakere for å sikre pålitelig påvisning av meningsfulle effekter. Studien vil utforske hvordan humør og hukommelse for musikk bidrar til endringer i kognitive evner, og om disse effektene varierer basert på faktorer som kjønn, alder, AD-stadium, eller tidligere musikalsk opplæring og generell utdanning. Prosjektet vektlegger samarbeid mellom forskere, tjenesteytere og brukere for å sikre studiens relevans og anvendelighet.

The number of people living with dementia is increasing and is high in low, middle, and high-income countries. Alzheimer’s disease (AD), the most common type of dementia, manifests itself initially with cognitive impairment in memory domains, and later affects all activities of daily living. Active music interventions, particularly singing, can help to improve mood, behaviour problems, and quality of life. Too little is known about their effects on cognition, although some promising studies exist. The M4M project aims to fill this gap by measuring effects of learning new songs on clinical, behavioural and brain functioning. Specifically, M4M aims to examine changes in general cognitive functioning and memory for music in non-musician adults with AD undergoing intensive individual musical training based on singing novel songs, compared to minimal training.
        Home-dwelling adults with AD, 65 years or older, in 3 countries (Argentina, Austria, Norway), will receive 5 months of intensive intervention (2x/week) and 5 months of minimal intervention (1x/month), in random order, with a 2-month break in between. Interventions will entail learning new songs with an individual music teacher. At the end of each intervention period, general cognition will be measured with the Alzheimer's Disease Assessment Scale – Cognitive (ADAS-cog) by a person who is unaware of the intervention received. Memory for music will be tested with observations, behavioural tasks, and brain responses (EEG). Mood will be assessed in each session. We aim to include 113 participants; this will help us to reliably detect clinically meaningful effects. We will also examine how mood and memory for music lead to changes in cognitive abilities, and whether effects depend on sex, age, AD stage, or previous musical training or general education. M4M will be conducted in close collaboration between academic researchers, service providers, and service users to ensure relevance and applicability.

Memory for Music: Effects of individual intensive musical training based on singing in non-musicians with Alzheimer’s disease

InterNASH - An intercellular-pathway therapeutic for non-alcoholic steatohepatitis

Utvikling av løsninger for den beregningsbaserte flaskehalsen i høyenergifysikk

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Professor

When particle physicists search for the basic building blocks of the universe, for example the elusive dark matter that keeps galaxies together, they are today faced with serious bottlenecks in computing. In order to test realistic new models against the plethora of data that exists today from anything from astrophysical observations to collider experiments at the Large Hadron Collider, the large parameter spaces of the models must be explored in detail. This means repeated numerical reevaluation of precision theoretical predictions for the model for different parameter values. Possibly millions to billions of evaluations are needed in total for a single model, depending on its number of parameters. These predictions are computationally very expensive, and today testing anything beyond the simplest models to high fidelity is infeasible, even with the use of supercomputing strategies.

This project aims to remove such computational bottlenecks by an interdisciplinary collaboration between particle physicists and statisticians. To achieve its goals the project will follow a number of research strategies: it will construct modern machine learning tools for performing precision calculations in quantum field theory and evaluating their uncertainties, and it will develop a software framework for their use in high-energy physics. To reduce the number of reevaluations needed in exploring new physics models the project will develop sophisticated new statistical techniques to reliably extract the best-fit parameter regions of models, and make model comparisons possible within today's computational limitations. Finally, the project will use these developments to explore five different new physics models that are particularly interesting as solutions to some of the major problems in high-energy physics today, for example the nature of dark matter.

When exploring the smallest fundamental constituents of the Universe physicists are faced with very serious calculational bottlenecks. To compare new physics models to data, for example from the Large Hadron Collider or astrophysical observations, we need to perform very computationally expensive calculations in quantum field theory (QFT); expensive due to the increasing complexity of higher-order quantum corrections. These are today too slow to perform at the necessary precision except for the simplest models. At the same time, the interpretation of the models given the available data, the best-fit regions of their parameter spaces, and the comparison of different models with each other through their goodness-of-fit, is made computationally intractable due to the size of the parameter spaces of the models and the complexity of the likelihood evaluation for each model.

The solution to these inherent problems can not be found in physics alone. This project builds on an interdisciplinary collaboration between physicists and statisticians focused on statistical learning and inference problems in high-energy physics. The project will develop machine learning based regression techniques to speed up QFT calculations with a proper probabilistic interpretation of uncertainties from higher-order contributions, it will develop a continual learning framework for faster emulation of the likelihood for model parameters, and it will investigate new improved statistical approaches to the problems of best-fit and goodness-of-fit using these emulations.

Finally, the project will investigate a number of promising new physics models that can answer questions such as: What is dark matter? Are the properties of the Higgs boson indicating that the Universe is fundamentally unstable? Why is there more matter than anti-matter in the Universe?  If funded, this project will increase the reach of large and costly experiments in answering these questions for a relatively small extra cost.

Developing solvents for unclogging the calculational bottleneck in high-energy physics

The conference will provide an excellent opportunity for the presentation and discussion of research results and development in the areas of sensing and control of autonomous vehicles. This includes autonomous ships, airborne drones and underwater vehicles. The participants are from leading universities and research institutes worldwide including:
- Brigham Young University, USA
- École Polytechnique Fédérale de Lausanne, Switzerland
- ETH, Switzerland
- INRIA, France
- Instituto Superior Técnico, Portugal
- Johns Hopkins University, USA
- KTH Royal Inst. of Techn., Sweden
- Linköping University, Sweden
- Northeastern University, USA
- NTNU, Norway
- TuE, The Netherlands
- Tokyo Metropolitan University, Japan
- University of Colorado, USA
- University of Genova, Italy
- University of Girona, Spain
- University of Lecce, Italy
- University of Michigan, USA
- University of Nice Sophia Antipolis, France
- University of Porto, Portugal
- University of Stuttgart, Germany
- University of Washington, USA
- Virginia Tech, USA
- Woods Hole Oceanographic Institute, USA

The objectives of the workshop is to bring together PhD students from several research projects at NTNU (SFF, MAROFF, FRINATEK) and let them meet the leading researchers in the field of autonomous systems. 

The subject of the conference is sensing and control with applications to autonomous vehicles. Guidance, navigation and motion control systems for autonomous vehicles are increasingly important in land-based, marine and aerial operations. Autonomous underwater vehicles may be used for pipeline inspection, light-intervention work, underwater survey and collection of oceanographic/biological data. Autonomous aerial and ground vehicles can be used in many applications such as inspection, monitoring, data collection, surveillance, etc.

Event support for an International Conference on "Sensing and Control for Autonomous Vehicles" to be arranged by NTNU AMOS

Prosjektet har utviklet autopilotalgoritmer for vingeformede ubemannede fly (droner). Autopilotsystemene har utviklet seg signifikant over tid, fra tidlige systemer som så vidt kunne holde en konstant orientering til moderne systemer for automatisk landing og komplekse manøvrer. Imidlertid, konvensjonelle autopiloter opererer innenfor et lite arbeidsområde og den dynamiske oppførselen av farkosten er begrenset slik at lineære designmetoder kan brukes.  Dette legger unødvendige begrensinger på dronens operasjonelle kapasitet så vell som krav til hvilken vind det er trygt å fly i. Droner kan også opereres i autonome modi, hvilket krever at autopiloten er feiltolerang, rekonfigurerbar og intelligent for å takle uforutsette hendelser. Som en konsekvens av dette har vi utviklet autopilotalgoritmer hvor hovedmålet var å øke dronens arbeidsområde slik at dronen kan utføre mer avanserte manøvrer samt operere i ekstremt vær. Denne funksjonaliteten er viktig for mange kommersielle anvendelser.

I løpet av de første årene av prosjektet har flere nye resultater blitt publisert. Dette inkluderer en ikke-lineær modellpredikitv regulator for vingeformede ubemannede fly. Deep reinforcement learning har blitt brukt til å lage algoritmer for attituderegulering ved hjelp av optimaliseringsmetoder. En komplett aerodynamisk model har blitt utviklet og testet for Skywalker X8  UAV. De aerodynamiske koeffisientene i modellen har blitt kalibrert ved hjelp av vindtunneltester. Modellen kan brukes av forskere til å simulerer aggressive manøvre og teste ikke-lineære styresystemer.

The main motivation for the proposal is summarized below:
- The main goal is to increase the flight envelop of fixed-wing UAVs such that they can perform more advanced maneuvers and operate in harsh weather conditions. This functionality is needed in many commercial applications.
- Mathematically prove global asymptotic/exponential stability of the closed-loop system using nonlinear control theory.
- Achieve fault tolerance and robustness of the nonlinear autopilot system.
- Experimentally verify and demonstrate the nonlinear autopilot algorithms and their real-time implementation in challenging applications and case studies at NTNU's UAV Lab in cooperation with NTNU AMOS (NTNU Center of Excellence).

Demonstrate the following UAV operations and maneuvers:
1. Agile flight: Track a path with large curvature (course- and climb-rates) using nonlinear control. 
2. Operation in turbulent wind conditions: In strongly turbulent winds, the autopilot must be designed to handle large roll and pitch angles that could result from these disturbances also when not attempting any high-curvature maneuvers. 
3. Autonomous precision landing using large angles of attack (AOA): We intend to land an aircraft autonomously at a given landing target using deep stall to reduce the impact speed. 
4. Stabilization of camera: The goal is to operate a small UAV with camera without using a gimbal to stabilize the camera. The aircraft autopilot should stabilize the camera to avoid large bank angles during turning.

The project targets education of two PhD and eight MSc candidates as well as training of one postdoctoral researcher through Working Packages 1-3 dealing with:

WP1: Nonlinear control allocation and attitude control
WP2: Nonlinear speed and path-following control 
WP3: System integration, testing and case studies

The results will be published at conferences and in the top ranked journals in the field.

Nonlinear Autopilot Design for Extended Flight Envelopes and Operation of Fixed-Wing UAVs in Extreme Conditions

The main motivation for the proposal is summarized below:
- Develop low-cost integrated navigation using MEMS components with lower computational footprint than the Kalman filter and develop explicit stability guarantees for the nonlinear observers. 
- De monstrate how nonlinear observers can be implemented on light-weight embedded computers with limited processing capacity.
- Nonlinear observer theory, MEMS technology and embedded systems are changing the rules of the game and opens for the development of  low-cost compact position, velocity and attitude (PVA) estimation. The project will focus on methods which can be used in as low-cost consumer electronics, cars, navigation systems for autonomous underwater vehicles (AUVs), ships, unmanned aerial vehicle s (UAVs) etc.
- Demonstrate that it is possible to develop effective computer algorithms that can be implementation using only a fraction of the source code when compared to a standard EKF implementation. This will simplify implementation, maintenance and  software documentation. 
- Compare and verify the the performance to commercial EKF-based systems in cooperation with Maritime Robotics and FFI.
- The project targets education of three PhD and eight MSc candidates (Working Packages 1-3) dealing with:
   WP1: Integrated observer design with a North-seeking strapdown MEMS-based gyrocompass 
  WP2: Nonlinear tightly integrated filters for attitude, velocity and position 
  WP3: Model-based nonlinear integration filters for INS and position measurements 
- T he results will be published at conferences and in the top ranked journals in the field.

Low-Cost Integrated Navigation Systems Using Nonlinear Observer Theory

This project is driven by a need to improve fault-tolerance, safety and performance of vessel control, monitoring and advisory systems. Taking advantage of recent developments in low-cost Micro-electromechanical system (MEMS) based sensors, the approach i s sensor fusion that combines redundant inertial sensors with other redundant vessel state, motion and position sensors in order to achieve more accurate and reliable motion and position estimates.  Meeting these objectives are essential for reaching perf ormance and availability targets, and is challenging on existing technologies, in particular at a cost level that can enable a wider usage of high quality position reference systems and motion sensors.

Our vision is to develop novel architecture and algo rithms for integrating sensor data from various position reference systems and inertial sensors, to be able to provide motion and position measurements with better accuracy and reliability with less stringent requirements to each of the sensors. The solut ions will improve redundancy and failure handling, and use software algorithms to gain high quality information from data from lower grade sensors.

These objectives will be met through research centered around the following 3 work packages:

WP1: Optimal  sensor fusion for marine vessels using redundant inertial and position sensors
WP2: Fault-tolerant sensor fusion by exploiting redundant inertial measurements
WP3: Full-scale validation, pilot installations, technology qualification, and demonstrations

 The project targets mainly MAROFF theme 2: Challenging safe maritime operations, although the technology also has benefits towards fuel efficiency, emissions and cost.

0 projects

MAROFF-2-Maritim virksomhet og offsh-2

Event support for an International Conference on "Sensing and Control for Autonomous Vehicles" to be arranged by NTNU AMOS

Awarded: NOK 0.15 mill.

Project Period: 2017-2017

Location: Trøndelag - Trööndelage

IKTPLUSS-IKT og digital innovasjon

Nonlinear Autopilot Design for Extended Flight Envelopes and Operation of Fixed-Wing UAVs in Extreme Conditions

Awarded: NOK 9.9 mill.

Project Period: 2017-2021

Location: Trøndelag - Trööndelage

FRINATEK-Fri prosj.st. mat.,naturv.,tek

Low-Cost Integrated Navigation Systems Using Nonlinear Observer Theory

Awarded: NOK 9.4 mill.

Project Period: 2013-2016

Location: Trøndelag - Trööndelage

MAROFF-2-Maritim virksomhet og offsh-2

Fault-Tolerant Inertial Sensor Fusion for Marine Vessels

Awarded: NOK 5.1 mill.

Project Period: 2013-2016

Location: Trøndelag - Trööndelage

F-INF-Naturvitenskap, informatikk

Nonlinear observer design for tight integration of carrier differential GPS (CDGPS) and INS

Awarded: NOK 1.8 mill.

Project Period: 2003-2007

Location: Trøndelag - Trööndelage