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Kunstig lys om natten (ALAN) setter naturen ut av balanse. Mange dyr er avhengige av lengden på dagslyset (fotoperioden) som signal for å synkronisere reproduksjon med gunstige forhold. Forstyrrelser i dette naturlige signalet, enten gjennom lysforurensning fra urban belysning eller akvakultur, kan ha alvorlige konsekvenser for dyrs livssyklus og overlevelse. Prosjektet mitt tar sikte på å avdekke de biologiske mekanismene bak sesongmessig reproduksjon for bedre å forutsi og redusere disse påvirkningene. Jeg vil undersøke et nøkkelhormon, thyroidstimulerende hormon (TSH), og dets funksjon i reguleringen av sesongmessig reproduksjon hos dyr ved å bruke medaka (japansk risfisk) som modell.
Denne lille fisken er perfekt for genetiske studier, da det allerede finnes mange verktøy og protokoller for denne arten for å studere i detalj de cellulære og molekylære mekanismene som er involvert i essensielle kroppsfunksjoner, som for eksempel reproduksjon. For å undersøke dette vil jeg bruke avanserte genetiske verktøy og optogenetikk, en metode som bruker lys til å kontrollere celleaktivitet, for å avdekke mekanismen som regulerer det sesongmessige tidspunktet for reproduksjon. Ved å dekode hvordan dyr tilpasser sin sesongmessige reproduksjon til forstyrrelser i lyssignaler, vil dette prosjektet belyse hvordan vi kan ivareta biologisk mangfold og utvikle bærekraftig akvakulturpraksis.

Seasonal reproduction in vertebrates ensures offspring survival by aligning reproductive timing with photoperiod as the primary cue. However, artificial light at night (ALAN) disrupts these cues, posing a threat to species survival. Similarly, continuous light used in aquaculture to inhibit fish reproduction may have unintended physiological effects. OptoSeason seeks to decode the mechanisms underlying seasonal reproduction as a critical step toward predicting and mitigating the impact of these environmental disturbances.
Research in mammals and birds suggests that thyroid-stimulating hormone (TSH) in the pituitary pars tuberalis (PT-TSH) regulates seasonal reproduction. However, the role of PT-TSH remains controversial due to the challenges of knocking out the Tshb gene without affecting essential thyroid functions. Thanks to the teleost-specific whole-genome duplication (WGD), we can now study a TSH gene specifically involved in seasonal reproduction using teleost fish models. Our previous findings indicate that tshbb plays a crucial role in this process.
To unravel these mechanisms, OptoSeason will develop a next-gen optogenetic tool in Japanese medaka, a seasonally breeding teleost suitable for genetic manipulation and knockout studies. Considering its potential, this tool also has broader applications across various biological research areas. We will also employ advanced techniques such as CRISPR/Cas9-mediated knockout/knock-in, receptor assays, laser microdissection, transcriptomics, calcium imaging, and patch clamping to explore the tshbb pathway and its link to reproduction.
Understanding this pathway will help identify markers for out-of-season spawning risks due to ALAN and provide insights into environmental and genetic influences on reproduction. This research will address challenges like early puberty in aquaculture, advance scientific knowledge, and develop tools to tackle key environmental and industrial issues.

OptoSeason: decoding seasonal reproduction in vertebrates using a next-gen optogenetic tool

Mennesker påvirker marine økosystemer på mange måter, som gjennom klimaendringer, forurensning og overfiske. Kumulative effekter refererer til de samlede effektene av slike stressfaktorer. Disse utgjør en av de største truslene mot økosystemer og biologisk mangfold. Likevel vet vi lite om hvordan stressfaktorer virker sammen i komplekse økosystemer. Dette gjør det utfordrende å forvalte våre kyst- og havområder bærekraftig.

CLIMAX-prosjektet har som mål å bedre forstå kumulative påvirkninger gjennom datasimuleringer. Det introduserer innovative modellerings- og dataanalysemetoder som kombinerer dagens datakraft med kunnskapen som økologer har bygget i flere tiår gjennom felt- og laboratoriestudier.

CLIMAX vil vise potensialet til disse nye metodene med en casestudie: menneskelige påvirkninger i Skagerrak og Kattegat. Her tar prosjektet for seg to sentrale miljøspørsmål. For det første vet vi allerede mye om de enkelte stressfaktorenes effekter på individuelle arter – men hvordan samhandler disse stressorene ved å skape økosystemendringer som redusert biologisk mangfold og produktivitet? For det andre, hvordan påvirker langvarig stress økosystemets evne til å motstå og komme seg etter ekstreme hendelser som marine hetebølger?

Marine økosystemer er bemerkelsesverdig stabile, men kumulative påvirkninger kan overvelde deres evne til å motstå og komme seg etter forstyrrelser. Derfor kan CLIMAX sine resultater forbedre bærekraftig bruk og vern av marine økosystemer i Norge og andre steder.

Cumulative impacts refer to the combined effects of multiple stressors on an ecosystem, e.g., climate change, pollution, and fishing. They are one of the biggest threats to ecosystems and biodiversity, but understanding them better remains a grand challenge in marine ecology. Modeling is a crucial component of tackling this challenge. However, current modeling approaches contradict empirical studies, suffer from data limitations, or ignore the statistical possibilities arising when ecosystem simulations are run many times. New modeling and analysis approaches are therefore needed. CLIMAX aims to 1) make a leap in the modeling of cumulative impacts and 2) exploit this methodological progress to understand how cumulative impacts emerge at the ecosystem scale.

CLIMAX’s scientific potential comes from a novel combination of leading-edge computational methods and a strong foundation in the empirical literature. This integration of methods is based on three ideas. First, ecosystem models (here, Ecospace) can simulate how stressor effects identified in empirical studies might ripple through the food web. Second, ecosystem models can generate big data about the simulated ecosystem in computational experiments (running the model many times with changing inputs). Third, such big data allow for unprecedented statistical analyses of how ecosystem-scale changes might emerge in the model system. CLIMAX will develop these methods, make them available in free software, and show their scientific potential by addressing two critical research questions: 1) How might stressor interactions at the ecosystem scale emerge from known effects on individual species? 2) How do chronic stressors affect ecological resilience to short-term, extreme disturbances like marine heatwaves?

By combining the best computational methods and harnessing the unprecedented computing power available today, CLIMAX has the potential to set an ambitious agenda for modeling cumulative impacts for decades to come.

Understanding cumulative human impacts in a marine ecosystem with computational experiments

Chemosensation is a critical signalling process for sea cucumbers which relies on the interaction between their chemosensory receptors and various ligands for foraging and reproduction. Although there is a vast amount of research on the chemistry of secreted specialized metabolites of sea cucumbers, and some behavioural data evidencing chemoreception of these metabolites, the chemosensory receptors of these organisms have not yet been identified and nothing is known about the physiology behind sea cucumber chemosensation. This setback is in large part because the scientific approach behind studying chemosensation requires a vast array of techniques and expertise in ethology, chemistry, molecular biology, and biophysics.  Firstly, a behaviour associated with a chemical cue must be quantifiable, secondly, the precise chemical cue eliciting the behaviour response must be identified and isolated, thirdly, the chemosensory receptor of this specific cue needs to be identified on a tissue, cellular, and molecular level, and finally, the activation of this specific receptor by a specific chemical cue must elicit a measurable response on a molecular, cellular, tissue, and organismal level. Through this project, I will elucidate the physiology of chemical communication between sea cucumber by considering these sequential steps in chemosensation. With my previous experience in sea cucumber ethology and chemistry, SensHolo will enrich my skill base in molecular biology and biophysics so that the mechanisms behind intraspecific chemical communication between sea cucumbers may be determined from both the emitter and receiver perspective; from signal to receptor.  This holistic approach will be ground-breaking in chemosensation and sea cucumber research. It will enable future research to address the evolution of chemosensation in marine invertebrates and the chemical ecology of sea cucumbers both in the context of optimizing aquaculture and in their ecological conservation.

Chemosensation in Holothruoids

Lys spiller en avgjørende rolle for livet i havet. Lyset driver fotosyntesen, styrer hvordan dyr finner mat, hvordan de unngår rovdyr og hvordan de beveger seg gjennom vannet. Livet i havet er tilpasset naturlige svingninger i lysstyrke, og er derfor følsomt for endringer i både lysstyrke og døgnsykluser. Forurensning og algeoppblomstring hindrer for eksempel sollys i å trenge ned i havet, dette fører til mørkere kystvann (kystformørkning). Kunstig lys om natten (Artificial Light at Night, ALAN) fra byer og skip tilfører derimot lys om natten. Disse endringene kan forstyrre viktige atferdsmønstre, som for eksempel den daglige vertikale forflytningen hos dyreplankton, som søker tilflukt i dypere (mørkere) vann på dagtid og bruker nattemørket som kamuflasje når de svømmer mot overflaten for å spise. Endringer i denne adferdselen kan forstyrre viktige næringskjeder og økosystemer i havet.  I ALANIS-prosjektet vil vi undersøke hvordan kunstig lys om natten og kystformørking påvirker havmiljøet. Dette gjøres gjennom en tverrfaglig og regionalt bred forskningsinnsats som kombinerer avanserte lysmålinger, kontrollerte eksperimenter, feltstudier og økosystemmodellering. Ved å integrere fysiske og biologiske data med satellittobservasjoner og eksperimentelle funn, har ALANIS som mål å lage et risiko- og sårbarhetskart for europeiske farvann, som vil gi beslutningstakere et bedre grunnlag for å forstå og håndtere effektene av lysforurensning på viktige økosystemfunksjoner, som for eksempel karbontransport.

In aquatic environments natural light not only determines the rate of photosynthesis as primordial energy source but also critically influences trophic interactions throughout the entire food web. Light modulates visual predation by many predators as well as predation avoidance strategies by the prey and thus structures the vertical organization of aquatic ecosystems. Alterations of light, a reduction of underwater light intensity due to coastal darkening (CD) or additional light at night from artificial light sources (ALAN) have the potential to strongly effect zooplankton diel migration patterns with consequences to whole marine ecosystems.
In ALANIS, we will investigate the proliferation of ALAN from coastal activities and shipping and its impact on organismic behaviour such as vertical migration and on key ecosystem functions, while also considering counteracting effects of CD. We will apply a cross-basin state-of-the-art research pipeline approach, linking spectrally resolved light measurements, single species lab and in situ mesocosm studies, with community-wide field experiments and ecosystem modelling. Experimental and observational study sites will cover different regions. The expected results will provide the necessary fundamental physical characterization of underwater ALAN and will deliver an assessment of zooplankton photo-responsiveness and -behavioural thresholds. Remote sensing data of ocean brightness at night and long-term observations of ocean colour will be used to establish an atlas of ALAN for European waters. This ALAN risk map together with the biological and physical knowledge leveraged at the study sites will be integrated into a mechanistic modelling approach for producing a sensitivity map of potential impacts of ALAN and CD on key ecosystem functions such as export flux. Collaborative communication, dissemination, and outreach of ALANIS results will efficiently inform decisions and actions of a diverse group of stakeholders.

Lightscapes ALANIS - ALANIS: Impacts of Artificial Light At Night on pelagIc ecosystems in European Seas

Mining Impact-prosjektet ble valgt ut som en del av den tredje fasen av den vellykkede JPI Oceans Joint Action om de økologiske aspektene ved dyphavsgruvedrift. Forskningskonsortiet samler eksperter fra Belgia, Danmark, Tyskland, Italia, Nederland, Norge, Polen, Portugal og Storbritannia. Med et totalbudsjett på ca. € 9 millioner (hvorav ca. € 5,7 millioner er finansiert av nasjonale finansiører gjennom JPI Oceans), vil prosjektet fylle kritiske kunnskapshull om dyphavsøkosystemer og den potensielle effekten av gruvedrift på dem. Forskning vil ikke bare fokusere på polymetalliske knutefelt, men også adressere massive sulfidavsetninger, og kombinere eksisterende data med nye ekspedisjoner for å fremme vår forståelse av disse unike miljøene. Dette prosjektet er ment å gi avgjørende vitenskapelig bevis for å støtte informert beslutningstaking om fremtiden for havbunnsmineralutvinning og dens styrende internasjonal og nasjonal lovgivning.

MiningImpact3 har som mål å:
· Vurdere den romlige og tidsmessige variasjonen til dyphavsmiljøet
· Forstå genetiske sammenhenger mellom dyphavspopulasjoner
· Studere effekten av gruve-indusert toksisitet og press på bunn- og pelagiske samfunn.
· Støtte utviklingen av indikatorer for økosystemhelse og terskler for alvorlig skade
· Avanserte styrings- og styringsverktøy, inkludert digital tvillingteknologi
· Sammenligne virkningene av dyphavs- og landbasert gruvedrift

Prosjektet vil dra nytte av tilgang til forskningsfartøyet Sonne levert av det tyske forbundsdepartementet for utdanning og forskning. En ekspedisjon vil undersøke steder av tidligere polymetalliske knutergruveprøver i Clarion-Clipperton-sonen i det nordøstlige ekvatoriale Stillehavet fem år etter nedslaget. Ytterligere ekspedisjoner vil studere økosystemet ved havbunnens massive sulfidforekomster langs den arktiske midthavsryggen, med forskningstokt planlagt til Mohnsryggen i norske farvann i løpet av 2026 og 2027.

MiningImpact is the leading international research project investigating the environmental impacts of
future deep-sea mining (DSM). Since its start in 2015, it has delivered independent scientific research
output and significantly improved our knowledge on polymetallic nodule ecosystems in the Clarion-
Clipperton Zone (CCZ) and the Peru Basin and their responses to anthropogenic disturbances as
documented by >100 peer-reviewed publications (see Section VI). MiningImpact experts have closely
interacted with stakeholder groups (national and international authorities, industry, NGOs, the public),
and in particular the International Seabed Authority (ISA). Noteworthy are contributions to the CCZ
regional environmental management plan (REMP) (ISA, 2021a), draft Guidelines of the Mining Code
(ISA, 2022a, 2022b), and the current Intersessional Expert Group developing binding environmental
threshold values (ISA, 2022c). While the first phase of MiningImpact focussed on decade-old benthic
impact experiments in the CCZ (cruise SO239) and the DISCOL experiment in the Peru Basin (cruise
SO242), during and after the second phase an independent monitoring programme of the first
industrial trials of the pre-prototype nodule collector vehicle Patania II by GSR in the CCZ was delivered
(cruises SO268, IP21, SO295).
In the third project phase (MiningImpact-3), proposed here, we will focus on addressing identified
knowledge gaps (e.g., Boetius & Haeckel, 2018; Amon et al., 2022; Hitchin et al., 2023; Pickens et al.,
2024; Singh, 2021; Weaver et al., 2022) and furthering the understanding of the ecosystems associated
with polymetallic nodules (PMN) and seafloor massive sulphides (SMS) and their vulnerability and
resilience to mining.

Assessing the environmental impacts of deep-sea mining of polymetallic nodules and seafloor massive sulphides

SOLUME-prosjektet vil undersøke hvordan endringer i lys påvirker havene våre. Som svar på en utlysning fra JPI Oceans, har dette internasjonale initiativet som mål å forstå konsekvensene av formørkning av kystvannet og kunstig lys om natten (ALAN) for kystøkosystemer.
Prosjektet ledes av Leibniz Institute for Baltic Sea Research Warnemünde (IOW) og inkluderer fagmiljø fra Tyskland, Polen, Norge, Irland, Storbritannia og Malta. De vil  undersøke hvordan lysforholdene under vann langs den europeiske kysten har utviklet seg over tiår og århundrer, ved å bruke historiske data og avanserte modelleringsteknikker for å avdekke drivkrefter, kilder og konsekvenser av disse endringene.
Forskningen vil dekke store europeiske havbassenger og fokuserer på spesifikke regionale casestudier. Den vil utforske land-hav-forbindelser samt affekten av  temperatur- og salinitetsgradienter. ISOLUME er unikt i måten det undersøke fire dimensjoner av marine lysforhold: intensitet, plassering, timing og bølgelengde, med fokus på endringer de siste 25 årene og framskrivninger for 2050.
Prosjektet involverer eksterne partnere fra ulike europeiske land, industri, interessenter og samfunnet. Gjennom et vitenskapelig rådgivnings- og interessentpanel, har ISOLUME som mål å utvikle effektive overvåkings- og forvaltningsstrategier og etablere retningslinjer for å dempe konsekvensene av endrede marine lysforhold. Den vitenskapelige kunnskapen basert på forskningen i ISOLUME vil fremme effektive overvåkings- og forvaltningsstrategier og etablere retningslinjer for å moderere  endringen i marine lysforhold.

The ISOLUME project is a response to the JPI Oceans call on the “Consequences of Changing Marine Lightscapes”. This call identifies the urgent need to understand both the drivers and impacts of changes in marine lightscapes on the marine environment that result from both coastal darkening and marine artificial light at night (ALAN) pollution. Our international consortium, led by the Leibniz Institute for Baltic Sea Research Warnemünde (IOW), includes partners from Germany, Poland, Norway, Ireland, UK and Malta. ISOLUME will assess how marine lightscapes have changed across European sea basins over decadal to centennial timescales, and determine drivers, sources and impacts of these changes at both large and small scales. Our approach combines historical trend analyses of in situ and remotely sensed marine optics with statistical and mechanistic modelling. It covers both large, European sea basin scales and focussed smaller scale regional case studies addressing different aspects of drivers and impacts of changing marine lightscapes. The investigation includes marine, estuarine and freshwater systems, land-ocean connectivity and temperature and salinity gradients. The project uniquely investigates four dimensions of marine lightscapes: intensity, location, timing, and spectra, with a focus on changes in the recent 25 years and projections for 2050. The involvement of external partners from European countries, industry, stakeholders, and society is facilitated through a Science Advisory and Stakeholder Panel supported by a scoping activity and a call for expression of interest. The scientific evidence-based knowledge developed in ISOLUME will advance effective monitoring and management strategies and establish policy frameworks to mitigate changing marine lightscapes.

IndicatorS Of changing Lightscapes in Underwater Marine Ecosystems

I en tid med historisk og fremtidig oppvarming av kloden trenger vi modeller som kan predikere de fremtidige økologiske konsekvensene. For marine system består disse modellene ofte av en global klimamodell knyttet til ulike temperaturdrevne funksjoner som representerer biologiske og fysiologiske effekter. De fleste slike funksjoner er svært generelle og ofte basert på gjennomsnittsverdier på tvers av arter og system. Det er derfor sannsynlig at prediksjonene blir feil for en enkelt art eller region. Dessverre vet vi lite om hvor vanlige slike feil er, ettersom modellene nesten utelukkende brukes til å predikere fremtiden, og så godt som aldri fortiden.
I denne søknaden plukker vi ut sentrale modell-forventninger og skalerer dem ned til det regionale miljøet for ulike fiskebestander i norske farvann. Forventningene testes og analyseres ved hjelp av eksepsjonelt lange tidsserier, fysiologiske eksperiment og mekanistiske modeller for bioenergetikk og livshistorie.
Foreløpige resultater peker mot at flere fiskearter er mer fleksible, både fysiologisk og adferdsmessig, enn generelle modeller klarer å fange opp. Disse og fremtidige prosjektresultater vil bidra til å lage bedre prediksjoner, og forhåpentligvis også utvide forståelsen vår om hvordan temperatur virker og ikke virker på ulike biologiske prosesser.

In the face of global warming, state-of-the-art eco-physiological theories and their implementation in global models make sweeping predictions that high-latitude fish populations are imperilled from unavoidable physical-physiological mechanisms. These are often rooted in reproductive constraints, and at the base we find two main theories: 

1) The theory of thermal tolerance windows, predicting that spawning fish (with narrow tolerance) will encounter unavoidable thermal bottlenecks in a warming ocean. 
2) The theory of temperature-dependent physiological rates, predicting an unfavourable advancement of fish spawning time, causing offspring to fall out of sync with their zooplankton food – known as trophic asynchrony 

These are predictions, often drawn from controlled laboratory experiments, and in turn extrapolated to global models. But just as downscaling to regional specificities and higher resolution was necessary to improve predictive ability of earth system models, so a similar biological downscaling to particular ecosystems and species is required to assess predictions at the scale relevant for population processes and ecosystem dymanics.

In this project we will downscale these predictive theories for two test species - Atlantic cod and herring, among the best documented fish stocks in the world. Our previous publications and preliminary findings suggest that these species have remarkable plasticity in the timing of spawning, often opposite to that dictated by temperature, and in surprising synchrony with each other and with lower trophic levels.

Here, we pick key expectations from the high-profile literature on biological effects of ocean change and attempt to downscale these to local conditions for key high-latitude fish species using particularly long and detailed timeseries of biological data, remote sensing, high-resolution water column processes, individual behavioural observations, and biological models of bioenergetics and life histories.

Regional downscaling of eco-physiological theory. 
Confronting global predictions with local observations.

«Torsion»-prosjektet har som mål å gjøre det enklere å overvåke tilstanden til roterende maskineri i marine miljøer ved å bruke avanserte, kontaktløse sensorer. Ved å analysere dataene kan vi oppdage endringer i systemet for å diagnostisere og forutsi feil. Tidligere tester har vist at måling av torsjons-moment og vinkelhastighet er effektive for å oppdage feil tidlig. Systemet kan enkelt kobles til eksisterende plattformer som SCADA og fanger opp feil som tradisjonelle systemer ikke klarer. Med kontaktløse sensorer fra Kongsberg Maritime blir systemet enda mer pålitelig og holdbart i tøffe offshore-forhold. To doktorgrads-studenter ved NTNU avdeling for Marinteknikk deltar i dette prosjektet.

The Torsion project aims to develop advanced methods for condition monitoring of critical components i.e. electro-mechanical rotating machinery in marine and maritime applications using high-resolution, high-accuracy torsional measurements via contactless sensors. The modal analysis will then be employed to post process the data extracting the system properties changes trend for diagnosis and prognosis. Earlier works through extensive simulations have shown that the torque estimation and angular velocity measurements can be a reliable, yet cost-effect approach for early fault detection of electro-mechanical systems. The main advantage of such system compared with traditional vibration measurement is that the system can easily be integrated with existing data acquisition platform, for example Supervisory Control and Data Acquisition (SCADA) system which is commonly installed for operational monitoring. In addition, the torsional measurement can capture the failures in torsional direction particularly due load variations which are not possible by the traditional system. The novelty of adding contactless angular velocity sensor, a technology offered by Kongsberg Maritime, will even further improve the condition monitoring system life and reliability in harsh offshore conditions enabling to implement other advanced methods for system identifications.

Advanced Prognostic Condition Monitoring System for Rotating Machinery using Contactless Sensors Integrated with Operational Modal Analysis

Kunstig intelligens endrer hvordan vi jobber på sjøen, og norsk maritim sektor må følge med i utviklingen for å beholde sin sterke posisjon. DNV Maritime, som sertifiserer og klassifiserer skip over hele verden, har allerede tatt flere skritt inn i KI-alderen. De har utviklet systemer som kan forutsi slitasje på skipstanker, finne fram i tekniske tegninger på sekunder, og identifisere skipskomponenter fra bilder.
Men fremtidens utfordring ligger i å få ulike KI-systemer til å samarbeide, både med hverandre og med mennesker. I Prosjektet AI-Mar skal DNV, Raa Labs, Crayon Consulting og SINTEF utvikle en plattform der KI-agenter – selvstendige KI-programmer – kan jobbe sammen for å løse komplekse oppgaver. Tenk deg et team av digitale eksperter som sammen med menneskelige fagfolk vurderer et skips tilstand, hver med sin spesialkompetanse. En KI-agent analyserer værdata og driftshistorikk, en annen gjennomgår tekniske tegninger, mens en tredje vurderer sensordata fra skipets komponenter.
En stor utfordring er å få mennesker til å stole på KI-systemenes anbefalinger. Siden KI ofte fungerer som en "svart boks" der det er vanskelig å forstå hvordan den kommer frem til sine konklusjoner, vil prosjektet studere metoder som skaper forståelse og tillit. Dette er spesielt viktig i skipsfarten, der data kommer fra mange forskjellige kilder og sensorer med varierende kvalitet.
Prosjektet vil også utvikle nye metoder for hvordan team av programvareutviklere, KI-eksperter og fagfolk kan jobbe sammen for å skape og forbedre KI-tjenester. Dette er viktig fordi KI-systemer, i motsetning til tradisjonell programvare, kontinuerlig lærer og utvikler seg basert på nye data og erfaringer.
En velfungerende KI-plattform vil være avgjørende for å kunne sertifisere og overvåke skip der kunstig intelligens styrer viktige funksjoner om bord. Hvis prosjektet lykkes, vil vi bane vei for fremtidens autonome skip.

Maritim sektor står overfor store utfordringer i det 21. århundre, med økende krav til bærekraft, sikkerhet og effektivitet. For å opprettholde Norges posisjon som en ledende maritim nasjon, må næringen utnytte potensialet i kunstig intelligens (KI). AI-Mar-prosjektet har som mål å utvikle en banebrytende KI-plattform som vil muliggjøre samhandling mellom autonome KI-agenter og fageksperter, med fokus på å levere skreddersydde tjenester til både individuelle fartøy og flåter. For For eksempel vil man i større grad kunne automatisk verifisere tilstanden til skip, som kan gi mindre avbrudd i seile-tid (off-hire) og smartere arbeidsprosesser for mannskap ombord. AI-Mar skal levere tre innovasjoner:

KI-plattform for autonom samhandling: Prosjektet vil etablere en KI-plattform hvor KI-agenter kan operere autonomt og kommunisere både med andre agenter og med mennesker. Denne plattformen vil støtte automatisering av arbeidsprosesser og gjøre det mulig å tilby nye tjenester til kundene. 

Metode for utvikling av KI-tjenester: AI-Mar vil utvikle en metode som sikrer at KI-tjenester utvikles i tett samarbeid med brukere, samtidig som det tas hensyn til den kontinuerlige læringen og utviklingen av KI-modellene. Metoden vil adressere hvordan team (KI-utviklere, dataingeniører og fageksperter) best kan samarbeide for å utvikle og forvalte KI-tjenester.

Teknologi for å bygge tillit til KI-tjenester: Tillit er en avgjørende faktor for å ta i bruk KI-teknologi. AI-Mar vil utvikle teknologi som visualiserer og dokumenterer datakvaliteten som brukes i KI-modeller, noe som vil styrke fageksperters tillit til systemene. 

Med partnere DNV Maritime, Inmeta og Raa Labs og SINTEF vil prosjektet bygge på eksisterende forskning og erfaringer innen KI-teknologi. Gjennom utviklingen av en robust KI-plattform, vil AI-Mar styrke konkurransekraften til norske maritime aktører, samtidig som prosjektet posisjonerer DNV Maritime som en global leder innen KI-drevet innovasjon og sertifisering.

Plattform for autonome KI-agenter i maritim næring

De første ukene i en fiskelarves liv setter premissene for videre vekst og utvikling. Yngelproduksjon er den største flaskehalsen i oppdrett av marin fisk, og oppdrettere mangler verktøy for å kontrollere denne sårbare fasen av verdikjeden. Dette skal vi løse dette med vårt innovative verktøy for landbaserte oppdrettsmiljø kalt "Smart Yngelovervåking (SLRS)". 

Akvakultur er den raskest voksende sektoren for matproduksjon, og FN anslår at to tredjedeler av all sjømat vil komme fra oppdrett i 2030. For de fleste marine fiskearter er yngelproduksjonen preget av høy og uforutsigbar dødelighet. Fordi fisken er så liten, og det samtidig kan være millioner i ett eneste kar, er det veldig tidkrevende å følge opp for eksempel hvor mye fisken vokser eller hvor mange fisk man har i karet. Her mangler det gode verktøy, og det er bakgrunnen for dette prosjektet. SINTEF Ocean har utviklet patentert teknologi som automatisk logger og analyserer utviklingen hos fiskelarver, kalt Smart Yngelovervåking. Teknologien har som mål å gi oppdrettere informasjon om fiskelarvenes vekst og utvikling uten at det er behov for manuelle operasjoner og målinger. Kombinert med registrering av andre miljøforhold skal teknologien gi oppdretterne et beslutningsstøtteverktøy som gir økt kontroll, forutsigbarhet og lønnsomhet i produksjonen.

I dette verifiseringsprosjektet skal vi verifisere funksjonaliteten av hardware- og softwareløsninger for den patenterte prototypen ved å gjennomføre tester ute i industrien hos utvalgte pilotkunder. Disse testene vil danne grunnlaget for den nødvendige markedsinnsikten som trengs for å etablere en tilpasset forretnings- og kommersialiseringsplan.

Smart Larval Rearing System (SLRS) for healthy marine aquaculture production

Klinisk utprøvning av en ny diagnostisk test for veiledet legemiddelbehandling av kolorektalcancer med spredning.

Midlene fra INNO-NAERING-INNO-NAERING fordelt på år

Midlene fra INNO-NAERING-INNO-NAERING fordelt på fylker

Midlene fra INNO-NAERING-INNO-NAERING fordelt på fagområde

The innovation is a new in vitro diagnostic test platform for selecting the most effective drug treatment for individual cancer patients. The test is based on drug screening of the patient’s own living cancer cells and performs a unique analysis of the cells’ response to a range of clinically relevant drugs and drug combinations. The results are fed into a nomination algorithm that generates a personalized diagnostic report. The treating physician uses the report to tailor subsequent drug regimens. This approach has the potential to dramatically increase the number of patients benefiting from anti-cancer drug therapies and reduce the costs from unnecessary side effects. 

Early studies show that the technology has a predictive accuracy above 80% for metastatic colorectal cancer, but the clinical feasibility and utility is uncertain. Several promising retrospective and prospective clinical trials have been performed, but sample sizes are small and randomized trials are lacking. In this project, Oncosyne and partners will generate initial data on clinical performance by conducting an exploratory, interventional, open-label, randomized control trial. Here, the in vitro diagnostic test will be used to guide drug treatment for patients with metastatic colorectal cancer refractory to standard-of-care therapy. The study will employ end-to-end standardized and scalable assay conditions to facilitate transfer into clinical routine if successful.

The innovation is a new in vitro diagnostic (IVD) platform for selecting the most effective drug treatment for individual cancer patients. The IVD is based on drug screening of the patient’s own living cancer cells and performs a unique analysis of the cells’ response to a range of clinically relevant drugs and drug combinations. The results are fed into a nomination algorithm that generates a personalized diagnostic report. The treating physician uses the report to tailor subsequent drug regimens. This approach has the potential to dramatically increase the number of patients benefiting from anti-cancer drug therapies and reduce the costs from unnecessary side effects. 

Early studies show that the technology has a predictive accuracy above 80% for metastatic colorectal cancer, but the clinical feasibility and utility is uncertain. Several promising retrospective and prospective clinical trials have been performed, but sample sizes are small and randomized trials are lacking. Hence, there is a clear need for further industrial research activities to show that this diagnostic approach is feasible and has clinical utility. In this project Oncosyne and partners will address feasibility and generate initial data on clinical performance by conducting an exploratory interventional, open-label, randomized control trial. Here, the IVD test will be used to guide drug treatment for patients with metastatic colorectal cancer refractory to 1st and 2nd line standard-of-care therapy. The study will employ end-to-end standardized and scalable assay conditions to facilitate transfer into clinical routine if successful.

E!2584: Clinical validation of a new diagnostic test for Drug SEnsitivity Evaluation in ColoRectal Cancer (DSEE-CRC)

Crowdsourcing is the process of getting ideas, data or services from a large group of people, and especially from an online community and through information and communication technologies (ICTs). The iResponse project followed a case-based approach to address societal-environmental challenges in urban sustainability through the use crowdsourcing. The cases are on 1) Sustainable water drainage; 2) Improved air quality; and 3) Effective urban planning. Crowdsourcing is a powerful tool to obtain detailed spatio-temporal information. However, challenges and social concerns need to be taken into account in the design of methods. One of the objectives was to develop two ICT-based tools to address urban environmental challenges based on citizen participation; 1) co-design inclusive urban stormwater solutions, and 2) to retrieve data to better estimate emissions from residential wood combustion. 

Methods based on citizen participation were tested in the cases by the use of existing tools. Participation was found to be one of the biggest challenges both regarding stakeholders and citizens. The cases have allowed us to drive some conclusions; 1) the communication strategy is one the most crucial steps in a participatory process; 2) A dissemination based on a broad spectrum of methods may be more successful that a plan around one unique media; 3) Success participation needs to be defined for each project. 

In the air quality case, a prototype tool for collecting data and ideas regarding wood combustion was designed and tested. We highlight as lessons learned; 1) feedbacks in designing processes contribute to the improvement of the original idea, 2) testing is a crucial step in making a prototype operational; 3) having a crowdsourcing tool does not mean that you have crowdsourcing, neither participation. Following stakeholder feedbacks, we developed a webcrawling method, defined as the process of extracting and combining in a systematic way contents of interest from the Web. We implemented the webcrawler and retrieved the geographical position of the dwellings being sold or rented out in a classified advertisements website. We have gathered data during one year and classified them based on the type of dwelling and residential heating installation. The data is treated and combined with existing information to provide a comprehensive spatial distribution of wood burning potential. This work allowed us to develop an emission model for Norway to obtain high-resolution emissions from residential wood combustion. 

In the stormwater case, we explored and developed crowdsourcing approaches that could enable an improved urban stormwater management. This contributed to better understand of data sources, and how crowdsourcing can be relevant to develop multi-functional nature-based solutions. Location-based crowdsourcing through Public Participation GIS at city and neighborhood scales ware carried out. We also developed, involving multiple actors, a prototype platform to co-create multi-functional blue green solutions by enabling peoples inputs into different phases of the project design. It builds on findings on crowdsourcing approaches used in water management, their prospects and potential challenges. This will be further used in real-life cases.

The social concerns with crowdsourcing was assessed during the project along with reflections on solutions to overcome them. Representative samples from five Norwegian cities were selected to map citizens? knowledge and concerns on the use of digital media, crowdsourcing and participation. 35% reported to have heard of crowdsourcing, 25% had tried to influence spatial planning where 40% believed that their participation had some impact. Considering that the Norwegian government aims at increasing the amount of digital communication with citizens, it is notable that 69% report to communicate seldom or never digitally with authorities, and 40% expected that they would communicate more or less as often as today in the future. 

We developed recommendations, applying the RRI framework, for the use of crowdsourcing for urban environmental research in a socially responsible way. The recommendations can be summarized as; 1) Fit-for-purpose, consider carefully if the crowdsourcing method is adequate for the aim of your study; 2) Collaborate and include co-creation, involve diverse stakeholders for input, managing expectations; 3) Communicate, be transparent, responsive towards the crowd, and flexible to implement ideas; 4) Value increase by combining data from different sources and methods; 5) Responsible process, reflect on data privacy, security and open data standards; 6) Impact across borders and long the way, short to long-term, knowledge transfer, awareness, from social to scientific impact. The iResponse project has broadly disseminated along the way and the most relevant material is available on www.iresponse-rri.com/results.

The iResponse project will develop and study social responsible ICT-based crowdsourcing tools for environmental research and decision-making processes based on citizen participation and engagement (crowdsourcing). Two crowdsourcing tools will be developed in the project following the principles of responsible research and innovation (RRI); 1) an interactive platform to assess citizen acceptance and involve them in co-creation of water drainage solutions and 2) an application (mobile app/web) to collect data about wood consumption for house heating for estimating emissions. Three main case studies in urban environment will be carried out to test and evaluate the two developed crowdsourcing tools and an existing one, a public participatory map based questionnaire for urban planning (Mapita). The case studies will address different research questions and learning cases regarding the urban environment and citizen participation; 1) sustainable water drainage, 2) air pollution and 3) effective urban planning. The ITC crowdsourcing tools will enable citizens to influence urban planning by expressing their preferences, providing observations or user information. Different participatory ways are therefore foreseen with the use of the different crowdsourcing tools, involving different concerns and challenges. Social concerns will be mapped out and addressed, and possible solutions to overcome them will be proposed based on implementation and testing processes. The project aims at designing tools in a liable way towards responsibility, transparency and openness to the public, without compromising the quality of the research and user needs. In the last phase of the project, recommendations for the development and use of crowdsourcing as tools for environmental research and decision-making (including urban planning) will be elaborated as good practices within the ICT sector.

Social Responsible Crowdsourcing for Environmental Research and Decision-Making

The implementation of climate change policies as mitigation measures against greenhouse gas (GHG) emissions may create complex changes in the atmosphere. Particular sectors such as transport have been affected by abatement actions, and the measures have i ncluded moving from fossil based energy to increased use of bio-fuels. This, however, may create new environmental challenges. While the GHG emissions will be reduced, emissions of other compounds may increase. An example is the use of bio-ethanol for tra nsportation which is increasing worldwide. However, further research in needed as high emissions of harmful organic compounds such as acetaldehyde and formaldehyde have been suggested in several studies.
Oslo constitutes an interesting case-study to evalu ate the effects of emissions from vehicles running on alternative fuels as several buses are currently running with bio-ethanol. The strong smell of acetic acid has already been noted as a negative side effect, and indicates possible implications of bio-f uel combustion on urban air quality. In order to add light and contribute to the understanding of emissions from bio-ethanol, an innovative measurement campaign will be carried out in Oslo as case-study and specific organic and inorganic compounds will be  measured. In addition, the improvement of the current air dispersion modelling tools and the development of new innovative modelling techniques will be performed in the BieBus project. As well as concentrations, the dispersion models will be adapted to p rovide estimates of odour annoyance levels associated with the bio-ethanol combustion.
BieBus project will evaluate the implementation of an integrated assessment tool for the evaluation of alternative fuels in transport via air pollution measurements, di spersion modelling and cost analysis. The use of a model framework will be assessed as a strategic tool and the limitations will be evaluated, as will the opportunities for enhancing the model.

0 projects

SAMANSVAR-Ansvarlig innovasjon og bedriftenes samfunnsansvar

Social Responsible Crowdsourcing for Environmental Research and Decision-Making

Awarded: NOK 12.1 mill.

Project Period: 2015-2018

Location: Akershus

SIS-MILJO-Strategiske instituttsatsninge

Bio-Ethanol in public transport: an integrated approach to evaluate the impact of climate change policies in urban areas

Awarded: NOK 5.4 mill.

Project Period: 2011-2014

Location: Akershus

PES-INST-Prosjektetablererstøtte EU (FoU)

Transfer Reserach to End-Users for Improving Conservation and Preservation of Cultural Heritage

Awarded: NOK 99,999

Project Period: 2008-2008

Location: Akershus