37115 research outputs found
Sort by
Internal Community Engagement and Impact Benefit Agreements: Pathways to Community-Driven Outcomes
No full textFull text not availableImpact benefit agreements (IBAs) between Indigenous communities and mining companies have become a key instrument through which these communities engage with mineral development on their traditional lands. IBAs offer the potential to generate substantial benefits and improve quality of life for signatory communities; however, research has demonstrated that outcomes vary widely. Strong internal community engagement mechanisms are associated with positive IBA outcomes, though the nature of this engagement and the specific ways it influences outcomes has not been explored in depth. This thesis examined this relationship through a review of the literature and a qualitative case study with the community of Pinehouse, Saskatchewan, a Métis community with a culture of community engagement and experience with multiple IBAs. The findings indicate that although framed in the IBA literature as single or episodic events in the IBA process, engagement is best viewed as a sustained practice throughout the IBA lifespan. In order to have the beneficial effects described in the IBA literature, such as clarification and prioritization of community values and increased community unity, the engagement must reflect core qualities of inclusion, empowerment, and open dialogue. At the same time, the trust and capacity within the community to convene and sustain this kind of meaningful engagement develops over time and requires deliberate attention and commitment. As such, community engagement should be understood as a core capacity of governance at the community level necessary for successful and locally meaningful IBA outcomes
The Impact of Political Narratives on Effective Policy Making: The case of German climate policies under the Ampelkoalition
Get PDFIn the context of ever-increasing gaps between climate targets and climate action, this thesis studies the role of narratives in political discourse on climate change and climate policy making. It uses the German government during the legislative period from 2021 - 2024, the so-called Ampelkoalition [traffic light coalition], and examines how politicians from the governing parties used narratives to position themselves and their political opponent vis-à-vis climate change and climate policy.
Incorporating textual evidence from parliamentary debates on climate-related topics and applying Political Discourse Analysis, the thesis unveils common narratives and demonstrates how these are employed by policymakers to legitimise and justify their own political agenda. At the same time, the narrative themes that emerge show that they further serve to undermine the legitimacy of political opponents.
Applying the concept of Narratology (Bal, 1999), this work argues that actors are discursively classified into positive or negative categories that allow politicians to claim credit and avoid blame. Thereby, parliamentary debates serve as a space for using narratives as political tool and communicative strategy, in order to advance one's political agenda. The main narratives that emerged are focused on the government as actively driving progress - titled We're doing our best and Reassurances and Responsiveness - and the opposition and hindering advancement of policies - labelled Devious Discursive Strategies and Inherited Problems.
The use of narratives in such strategic ways leads to concerns regarding their manipulative potential and the impact of this on democratic processes. Together with the negative impact on humans and the environment that climate change entails, the thesis discusses how neglecting appropriate means to tackle climate change endangers the peacekeeping abilities of a democracy
Constraining the environmental and biological controls on the geochemical composition of Neogloboquadrina pachyderma: Towards developing robust proxies for reconstructing polar surface ocean hydrography
Get PDFRapid ongoing climate change includes warmer sea surface temperatures, salinity changes, reduced sea ice cover, and melting ice sheets in the polar regions. This has consequences for climate and society regionally and globally. However, there are large knowledge gaps regarding the sensitivity of these systems. Records of past changes in polar climate and ocean-cryosphere interactions can provide invaluable insight to the impacts of ongoing warming. The planktic foraminifer, Neogloboquadrina pachyderma, is a key species in high latitude marine ecosystems and integral for palaeoceanographic reconstructions of the subpolar and polar oceans. The composition of their calcium carbonate shells broadly reflects the conditions they grew in, e.g., shell Mg/Ca increases with temperature. The species exhibits a thick outer crust with significantly different element/Ca (e.g., lower Mg/Ca) compared to the inner lamellar calcite. This large intrashell variability combined with a lack of culture-based low temperature calibrations result in large uncertainties in Mg/Ca-based temperature reconstructions in the polar regions. In addition, there are currently no robust trace element proxies for reconstructing salinity or carbonate chemistry.
Results presented in this thesis are based on culture experiments of N. pachyderma in controlled conditions including temperature, salinity, and carbonate chemistry, and high-resolution shell element composition was obtained using Laser Ablation Inductively Coupled Plasma Mass Spectrometry. The main outcomes of this study are: 1) N. pachyderma is a resilient species which utilise strategies such as dormancy and asexual reproduction to outlast unfavourable conditions; 2) A method was developed to geochemically distinguish the crust and lamellar calcite which revealed distinct differences in element/Ca between the two components; and 3) A cold water-tailored culture-based Mg/Ca-temperature calibration with separate regressions for the crust and lamellae, and refined understanding of environmental influences on shell composition. Overall, the methods presented in this thesis reduce uncertainties in high latitude palaeoenvironmental reconstructions towards better understanding of ocean-climate interactions.Nåtidens raske klimaendringer leder til varmere havtemperaturer, endringer i saltholdighet, mindre havis, og smeltende innlandsis i polområdene. Dette har konsekvenser for klima og samfunn regionalt og globalt. Fremdeles er kunnskap om hvor sensitive disse systemene er mangelfull. Studier om endringer i klima og hav-kryosfære sammenkoblinger i polområdene i fortiden kan gi verdifull forståelse for konsekvensene av klimaendringene som skjer i nåtiden. Det planktoniske poredyret (foraminifer), Neogloboquadrina pachyderma, er en nøkkelart i marine økosystem i høyere breddegrader og er avgjørende for å rekonstruere paleoseanografi i polare og subpolare områder. Den kjemiske sammensetningen av poredyrenes kalsium-karbonat skjell reflekterer miljøet de vokste i, f.eks., med økende temperatur øker forholdet Mg/Ca. Arten bygger et tykt lag bestående av idiomorf kalsitt med ulik sammensetning (f.eks., lavere Mg/Ca) enn det indre finkrystallede lamellære laget. Denne store intra-skjell variasjonen kombinert med manglende kultiveringsbaserte kalibreringer, spesielt for lave temperaturer, resulterer i store usikkerheter i Mg/Ca-baserte temperaturrekonstruksjoner i polarområdene. I tillegg finnes det foreløpig ingen robuste metoder basert på sporstoffer for å rekonstruere saltholdighet eller karbonatkjemi.
Resultatene presentert i denne doktorgradsavhandlingen er basert på kultiveringseksperiment på N. pachyderma under kontrollerte forhold, inkludert temperatur, saltholdighet, og karbonatkjemi, samt høy-oppløst sammensetning av sporstoffer i skjellene deres målt med Laserablasjons Induktivt Koblet Plasma Massespektrometer. Hovedfunnene av denne studien er: 1) N. pachyderma er en tilpasningsdyktig art og utnytter dvale og aseksuell reproduksjon til å overleve ugunstige forhold; 2) En geokjemisk metode for å skille det ytre kalsitt-laget fra det lamellære laget ble utviklet og brukt til å vise tydelige forskjeller i sporstoff/Ca forholdene mellom de to lagene; og 3) en kultiveringsbasert Mg/Ca-temperaturkalibrering tilpasset kaldt vann med egne regresjonslinjer for hvert av de to skjell-lagene, og forbedret forståelse for miljøpåvirkninger på skjellenes sammensetning. Metodene presentert i denne avhandlingen forbedrer presisjon og nøyaktighet i paleoseanografiske rekonstruksjoner i høyere breddegrader
Experimental Transformer System for Time Series Forecasting
Get PDFThe goal of the project is to use and suit a transformer based foundation model such as Lag-Llama (https://arxiv.org/abs/2310.08278) to forecast energy prices. Lag-Llama is pretrained on a large corpus of diverse time series data from several domains, and demonstrates strong zero-shot generalization capabilities compared to a wide range for forecasting models. The forecasting task should focus on general one-step (t+1) and multi-step predictions (t+n). Forecasts that can predict extremes (maximum prices and minimum prices ) are especially important. Both univariate and multivariate forecasting should be addressed in accordance with findings documented in https://m unin.uit.no/handle/10037/32757?show=full&locale-attribute=en
Coordinated Controller to Mitigate Voltage Violation in Smart Distribution Network
Get PDFThis thesis addresses the increasing challenges posedby highphotovoltaic(PV)
penetration in distribution networks, specifically focusing on voltage stability
issues caused by extreme seasonal generation variations. Current voltage con-
trol approaches fail to effectively manage these fluctuations- tests on the IEEE
37-bus system showed summer solar production is over 5 times higher than in
winter. This huge difference creates completely different operating conditions
as seasons change, requiring a new approach to voltage control.
The research aims to develop an adaptive control framework that can maintain
voltage stability across variable generation conditions while reducing system
lossesandextendingequipmentlifespan.ACoordinatedVoltageControllerwas
proposed and evaluated that dynamically adjusts responses based on violation
magnituderatherthanpredeterminedthresholds,coordinatingsmartinverters,
battery systems, and mechanical regulators across different timescales.
Results demonstrate significant improvements over traditional methods, in-
cluding a 59.1% reduction in voltage violations, 19.24% reduction in system
losses, and 40% reduction in mechanical switching operations. Notably, unex-
pectedbatteryutilizationpatternswereidentifiedandanon-linearrelationship
between PV penetration and voltage violations with distinct seasonal charac-
teristics was established.
This work advances distribution system theory by demonstrating that adapting
control sensitivity to violation severity significantly enhances voltage stability
across variable generation conditions. The findings provide practical guide-
lines for distribution network operators seeking to accommodate higher PV
penetration while maintaining power quality and reliability standards.
Keywords: Voltage Control, Photovoltaic Integration, Battery Energy Storage
System, Distribution Networks, Adaptive Control, Seasonal Variability, Smart
Inverters, Power Qualit
Reliable reduction of manual workload for oil spill detection in SAR images using uncertainty estimation and deep learning
Get PDFMarine oil spills require constant monitoring as they can cause severe environmental damage. Synthetic Aperture Radar (SAR) images are often used for oil spill detection, but they are complex and the analysis is a time-consuming process as there are a lot of areas to monitor. Therefore, the manual analysis of the images will inevitably lead to some errors. Deep learning models can be deployed for automatic classification of these images, but they fail to provide reliable confidence estimation, which can have major consequences in the case of misclassification. This thesis explores how uncertainty estimation can be used for filtering of uncertain images for manual review by an operator, while high-confidence images are automatically classified by a ResNet-50 model. For uncertainty estimation, Test-Time Augmentation (TTA) is used with dropout on the images, Pixel-Value Shift (PVS) and elastic transformation as data augmentations. The elastic transformation has the best performance, with PVS performing nearly as well. The results show that to achieve a total error of 5%, operators only need to manually analyze 41% of the dataset. Since operators regularly process numerous images, the proposed uncertainty-filtering could provide a significant reduction in manual workload. The findings in this thesis are believed to pave the way for a new and more efficient way to process SAR images of marine oil spills
Felles rådighet ved erverv av eiendomsrett under rettskartleggingen i Finnmark
No full textFull text not availableTemaet for avhandlingen er erverv av kollektiv eiendomsrett basert på langvarig tradisjonell samisk bruk av land og vann i Finnmark. Hensikten med avhandlingen er å undersøke betydningen av felles rådighet ved erverv av kollektiv eiendomsrett. For å belyse problemstillingen fokuseres det både på de nasjonale reglene om alders tids bruk og Norges folkerettslige forpliktelser i form av ILO nr. 169, sett i lys av HR-2024-982-S (Karasjok). Herunder vil også forholdet til samiske sedvaner og rettsoppfatninger være sentralt
Desentrale lærings- og mestringstilbud- Effekten av et digitalt artrosekurs for pasienter på Helgeland
Get PDFSAMMENDRAG
Bakgrunn
Artrose er en vanlig kronisk leddsykdom og ofte årsak til smerte, funksjonsnedsettelse og redusert livskvalitet. Tilstanden rammer særlig eldre, og behovet for helse- og omsorgstjenester øker med alderen. I distriktsområder som Helgeland kan de geografiske forholdene gi utfordringer med å oppnå lik tilgang til helsetjenester og helsefaglig kompetanse. Desentrale lærings- og mestringskurs kan bidra til å møte dette behovet, og styrke pasientenes funksjon og egenmestring.
Metode
Studien er gjennomført som en kvasieksperimentell studie, som inkluderer pasienter med mild til moderat artrose i hofter eller knær. Målingene ble gjort ved bruk av de validerte spørreskjemaene KOOS og HOOS. Data ble samlet inn før og seks måneder etter intervensjonen «Artroseskole». Disse var på ordinalnivå og ikke-normalfordelte, og ble derfor analysert ved hjelp av Wilcoxon Signed-Rank Test. Det er også gjennomført estimert sesongkorrigering av data, basert på tidligere studier av sesongvariasjoner. Det ble i tillegg gjennomført strukturert litteratursøk for å innblikk i tidligere studier på lærings- og mestringskurs til artrosepasienter.
Resultat
Av 26 inviterte, svarte 19 pasienter både før og etter intervensjonen. Resultatene viste tendenser til positiv effekt for pasienter med kneartrose, hvor noen av funnene også var statistisk signifikant (p≤ 0,05). Resultatene for sesongkorrigering forsterket effekten for dimensjonen Smerte ytterligere. Hos pasientene med hofteartrose ble det ikke funnet statistisk signifikante endringer, men de rapporterte endringer i HOOS-skår som oversteg terskelen for minste klinisk relevante endring. Litteraturgjennomgangen støttet funn som viste at digitale tilbud kan ha positiv effekt på egenmestring, fysisk funksjon og symptomreduksjon, samt bidra til redusert behov for kirurgisk behandling og mindre bruk av smertestillende.
Konklusjon
Desentrale lærings- og mestringskurs kan være en nyttig og relevant tilnærming til oppfølging av personer med artrose i distriktene. De kan være et viktig supplement til eksisterende helsetjenester og bidra til bedre tilgjengelighet, økt bærekraft og bedre utnyttelse av fagkompetanse. I fremtidige studier anbefales det å gjennomføre randomisert kontrollert studie med et større utvalg for å oppnå høyrere statistisk styrke.ABSTRACT
Background
Osteoarthritis is a common chronic joint disease and a frequent cause of pain, functional impairment, and reduced quality of life. The condition primarily affects older adults, and the demand for healthcare services increases with age. In rural areas such as Helgeland, geographic factors can pose challenges to achieving equal access to healthcare services and professional expertise. Decentralized education and self-management courses may help address these challenges by enhancing patients' function and self-efficacy.
Method
The study was conducted as a quasi-experimental study, including patients with mild to moderate osteoarthritis in the hips or knees. Measurements were taken using the validated KOOS and HOOS questionnaires. Data were collected before and six months after the intervention "Osteoarthritis School." The Wilcoxon Signed-Rank Test was used for analysis, as the responses were ordinal and non-normally distributed. An estimated seasonal adjustment of the data was also performed, based on previous studies of seasonal variation. In addition, a structured literature review was conducted to gain insight into prior research on patient education and self-management programs for individuals with osteoarthritis.
Results
Of the 26 invited participants, 19 completed the questionnaires both before and after the intervention. The results indicated a tendency toward a positive effect for patients with knee osteoarthritis, with some findings also reaching statistical significance (p ≤ 0.05). Seasonal adjustment further strengthened the effect for the Pain subscale. Among patients with hip osteoarthritis, no statistically significant changes were found, but they reported changes in HOOS scores that exceeded the threshold for minimal clinically important difference. The literature review supported findings indicating that digital interventions may have a positive impact on self-management, physical function, and symptom reduction, as well as contribute to reduced need for surgical treatment and decreased use of pain medication.
Conclusion
Decentralized education and self-management courses may be a useful and relevant approach for the follow-up of individuals with osteoarthritis in rural areas. These programs can serve as an important supplement to existing healthcare services and contribute to improved accessibility, increased sustainability, and more effective use of healthcare expertise. Future studies are recommended to employ a randomized controlled trial design with a larger sample size to achieve greater statistical power
Governing with Knowledge: User Knowledge, Epistemic Justice, and Marine Mammal Management in the Arctic
Get PDFThis thesis investigates how user knowledge—place-based insights from hunters and local actors—is integrated into environmental governance, using the North Atlantic Marine Mammal Commission (NAMMCO) as a case study. Drawing on Tengö et al.’s (2017) five-task framework for knowledge integration (mobilize, translate, negotiate, synthesize, and apply), the study analyzes NAMMCO documents and reports from 2017 to 2024, with a focus on the narwhal management conflict in East Greenland. The research adopts a qualitative, document-based methodology and situates its analysis within broader debates on co-production, epistemic justice, and institutional legitimacy. Findings indicate that while NAMMCO has made significant strides in recognizing and institutionalizing user knowledge, structural and epistemological barriers persist. The case of East Greenland reveals both tensions and possibilities in co-production, showing how user knowledge can reshape management practices if meaningfully engaged. The study contributes to understanding how knowledge pluralism operates in Arctic governance and emphasizes the need for ethical, inclusive frameworks that value diverse ways of knowing.
Keywords: User knowledge, marine mammal management, knowledge co-production, epistemic justice, arctic governanc
Fragmentation and Volatile Depletion in Meteor Head Echo Measurements
Get PDFThe main source of mass influx to Earth is thought to come from microgram sized meteoroids. These micro-meteoroids are indirectly detectable by high powered large aperture radars through the plasma they generate while ablating. A subset of meteor head echoes is known to contain abrupt drops in radar cross section (RCS). These drops can indicate meteor fragmentation, depletion of volatile elements, and the pyrolysis of organic material. Relatively few such detections have been studied in depth, as they must be manually identified among all other meteor detections without sudden decreases in signal strength. This study uses deep learning methodology to systematically classify the MAARSY meteor head echo catalogue, which contains meteor head echo detections between 2016-2024. The deep learning method achieved an accuracy of 86% and a precision of 91% in the task of identifying drops in RCS. Of the 1.6 million catalogued meteors 12% contain a distinct drop in RCS. Through subsequent analysis of the classified meteoroids, it was found that sporadic meteoroids originating from the narrow Apex source—associated with comet 55P/Tempel-Tuttle—are overrepresented by 50% among the group of meteoroids with distinct drops in RCS. In contrast, Helion and anti-Helion meteors—associated with comet 2P/Encke—are less likely to exhibit a drop in RCS. A statistical analysis indicates that meteors with a drop in RCS appear to be low in volatiles, leading to the hypothesis that this could be a result of space weathering. This depletion would leave the meteoroids more porous and fragile, making them more susceptible to destructive fragmentation, detected by MAARSY as a distinct drop in the received signal power. The results show that there are significant differences in how different populations of micro-meteoroids ablate in the atmosphere, which can be linked to the origin of the meteoroids. This information can grant further insight into the composition and structure of micro-meteoroids, as well as the effect of space weathering processes on meteoroids in the solar system