The chronically ill in the labour market – are they hierarchically sorted by education?

Background The chronically ill as a group has on average lower probability of employment compared to the general population, a situation that has persisted over time in many countries. Previous studies have shown that the prevalence of chronic diseases is higher among those with lower levels of education. We aim to quantify the double burden of low education and chronic illness comparing the differential probabilities of employment between the chronically ill with lower, medium, and high levels of education and how their employment rates develop over time. Methods Using merged Norwegian administrative data over a 11-year period (2008–2018), our estimations are based on multivariable regression with labour market and time fixed effects. To reduce bias due to patients’ heterogeneity, we included a series of covariates that may influence the association between labour market participation and level of education. To explicitly explore the ‘shielding effect’ of education over time, the models include the interaction effects between chronic illness and level of education and year. Results The employment probabilities are highest for the high educated and lowest for chronically ill individuals with lower education, as expected. The differences between educational groups are changing over time, though, driven by a revealing development among the lower-educated chronically ill. That group has a significant reduction in employment probabilities both in absolute terms and relative to the other groups. The mean predicted employment probabilities for the high educated chronic patient is not changing over time indicating that the high educated as a group is able to maintain labour market participation over time. Additionally, we find remarkable differences in employment probabilities depending on diagnoses. Conclusion For the chronically ill as a group, a high level of education seems to “shield” against labour market consequences. The magnitude of the shielding effect is increasing over time leaving chronically ill individuals with lower education behind. However, the shielding effect varies in size between types of chronic diseases. While musculoskeletal, cardiovascular and partly cancer patients are “sorted” hierarchically according to level of education, diabetes, respiratory and mental patients are not.publishedVersio

Gassmetning og biologiske effekter i Skibotnelva

Gassovermetning fra Skibotn kraftverk er dokumentert med verdier opp til 183 % TDG i periode 2021 – 2023. Historiske målinger av gassmetning i kraftverksutløpet viste maksnivåer mellom 106 og 184 % TDG i en periode mellom 2006 – 2011. Målinger i perioden 2021 – 2023 viste gassmetningsnivåer med risiko for akutt fiskedød både ved stasjon i kraftverksutløp, men også ved stasjoner 4,8 km og 8,2 km nedstrøms utløpet. Høye gassmetningsverdier inntraff i sammenheng med drift av Skibotn kraftverk og hovedårsak er sannsynligvis luftinndrag ved bekkeinntak. Resultater av ungfiskundersøkelser og bunndyr viste lavere tettheter nedstrøms enn oppstrøms kraftverksutløpet, noe som kan være en effekt av gassovermetning, men også av andre habitatforhold eller reguleringseffekter. Fortynning med ikke-overmettet vann fra restfeltet demper påvirkningen av gassovermetning fra Skibotn kraftverk, men det forblir usikkert hvor stor strekning som rammes før vannet er tilstrekkelig fortynnet eller utluftet. Det anbefales derfor å fortsette overvåking av gassmetning i Skibotnelva og å utvide stasjonsnett med målinger på begge sider av elv ca. 900 m nedstrøms kraftverksutløpet, ved tilløp av Kvitlielva. Dette vil også hjelpe å belyse biologiske effekter og årsakssammenheng mer detaljert. Følgende avbøtende tiltak vurderes som egnet til å redusere gassovermetning: Struping eller ombygging av bekkeinntak, fremskynding av fortynning og lufting ved økt turbulens i elva og tilpassing av driftsmønster. Også nye teknologier og metoder slik som utlufting ved ultralyd kan fungere, men her er det fortsatt forskningsbehov.publishedVersio

Hva forklarer kostnads- og tidsoverskridelser i bypakker? En undersøkelse av utvalgte samferdselstiltak i Bergen, i Trondheim og på Nord-Jæren

I dette prosjektet har vi undersøkt hvile faktorer som fremmer og hemmer vellykket iverksetting av samferdselstiltak. Til sammen er iverksettingen av seks ulike infrastrukturtiltak undersøkt i hhv Bergen, Trondheim og på Nord-Jæren. Oppmerksomheten er rettet mot hvilke faktorer som kan belyse hvorfor budsjett og framdriftsplan holdes eller ikke. Undersøkelsen er gjennomført ved dokumentstudier og intervju. Undersøkelsen viser at tre av tiltakene har overskredet budsjettene, ett av tiltakene ligger innenfor budsjett, mens to av tiltakene ikke er ferdigstilt enda. For to av tiltakene er det flere års forsinkelser, mens det for de andre er mindre forsinkelser. En viktig årsak til budsjettoverskridelse i planleggingsfasen er at flere av prosjektene har vært mer komplisert enn antatt eller at man har mangler kunnskap om bygging av den spesifikke typen prosjekter i urbane områder. Manglende kontroll og dermed for sein iverksettelse av korrigerende tiltak er en annen årsak til budsjettoverskridelse. Generelt sett er også omorganisering samtidig med iverksetting uheldig. I anleggsfasen framstår manglende kunnskap om grunnforhold som en viktig årsak til budsjettoverskridelse. Dette kan medføre behov for ny prosjektering og kostnadssprekk i mange ledd i tillegg til forsinkelser. Økte priser på stål og betong grunnet eksterne forhold (Covid-19) og Ukraina-krigen har også bidratt til økte kostnader for flere av samferdselstiltakene.Hva forklarer kostnads- og tidsoverskridelser i bypakker? En undersøkelse av utvalgte samferdselstiltak i Bergen, i Trondheim og på Nord-JærenpublishedVersio

Likestillingsmonitor Agder for perioden 2017–2021

Dette er den tredje likestillingsmonitoren som lages for Agder basert på Statistisk sentralbyrås (SSBs) likestillingsindikatorer. Den første kom i 2011 og den forrige kom i 2015 og var utarbeidet av Agderforskning. Siden den gang er mange år gått, vi har hatt kommunesammenslåinger i Agder og vi er blitt ett Agder fra 2020. Denne rapporten har Senter for likestilling ved UiA og NORCE Norwegian Research Center i samarbeid planlagt, men det er NORCE som har ført i pennen denne oppdaterte monitoren med data for perioden 2017-2021. I tillegg blir tre dybdestudier utarbeidet i denne forbindelse og i denne andre versjonen av likestillingsmonitoren har vi tatt med et dybdestudie av kvinner i ledelse og uttak av deltid blant kvinner i Agder.Likestillingsmonitor Agder for perioden 2017–2021publishedVersio

Beyond the food on your plate: Investigating sources of microplastic contamination in home kitchens

Given that a substantial amount of time is spent in kitchens preparing food, the kitchen equipment used may be relevant in determining the composition and amount of microplastics ending up on our dinner plate. While previous research has predominantly focused on foodstuffs as a source of microplastics, we emphasise that micro- and nanoplastics are ubiquitous and likely originate from diverse sources. To address the existing knowledge gap regarding additional sources contributing to microplastics on our dinner plates, this review investigates various kitchen processes, utensils and equipment (excluding single-use items and foodstuffs) to get a better understanding of potential microplastic sources within a home kitchen. Conducting a narrative literature review using terms related to kitchenware and kitchen-affiliated equipment and processes, this study underscores that the selection of preparation tools, storage, serving, cooking, and cleaning procedures in our kitchens may have a significant impact on microplastic exposure. Mechanical, physical, and chemical processes occurring during food preparation contribute to the release of microplastic particles, challenging the assumption that exposure to microplastics in food is solely tied to food products or packaging. This review highlights diverse sources of microplastics in home kitchens, posing concerns for food safety and human health.publishedVersio

On the emission-path dependency of the efficiency of ocean alkalinity enhancement

Ocean alkalinity enhancement (OAE) deliberately modifies the chemistry of the surface ocean to enhance the uptake of atmospheric CO2. The chemical efficiency of OAE (the amount of CO2 sequestered per unit of alkalinity added) depends, among other factors, on the background state of the surface ocean, which will significantly change until the end of this century and beyond. Here, we investigate the consequences of such changes for the long-term efficiency of OAE. We show, using idealized and scenario simulations with an Earth system model, that under doubling (quadrupling) of pre-industrial atmospheric CO2 concentrations, the simulated mean efficiency of OAE increases by about 18% (29%) from 0.76 to 0.90 (0.98). We find that only half of this effect can be explained by changes in the sensitivity of CO2 sequestration to alkalinity addition itself. The remainder is due to the larger portion of anthropogenic emissions taken up by a high-alkalinity ocean. Importantly, both effects are reversed if atmospheric CO2 concentrations were to decline due to large-scale deployment of land-based (or alternative ocean-based) carbon dioxide removal (CDR) methods. By considering an overshoot pathway that relies on large amounts of land-based CDR, we demonstrate that OAE efficiency indeed shows a strong decline after atmospheric CO2 concentrations have peaked. Our results suggest that the assumption of a constant, present-day chemical efficiency of OAE in integrated assessment modeling and carbon credit assignments could lead to economically inefficient OAE implementation pathways.publishedVersio

Advances in understanding of air-sea exchange and cycling of greenhouse gases in the upper ocean

The air–sea exchange and oceanic cycling of greenhouse gases (GHG), including carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), carbon monoxide (CO), and nitrogen oxides (NOx = NO + NO2), are fundamental in controlling the evolution of the Earth’s atmospheric chemistry and climate. Significant advances have been made over the last 10 years in understanding, instrumentation and methods, as well as deciphering the production and consumption pathways of GHG in the upper ocean (including the surface and subsurface ocean down to approximately 1000 m). The global ocean under current conditions is now well established as a major sink for CO2, a major source for N2O and a minor source for both CH4 and CO. The importance of the ocean as a sink or source of NOx is largely unknown so far. There are still considerable uncertainties about the processes and their major drivers controlling the distributions of N2O, CH4, CO, and NOx in the upper ocean. Without having a fundamental understanding of oceanic GHG production and consumption pathways, our knowledge about the effects of ongoing major oceanic changes—warming, acidification, deoxygenation, and eutrophication—on the oceanic cycling and air–sea exchange of GHG remains rudimentary at best. We suggest that only through a comprehensive, coordinated, and interdisciplinary approach that includes data collection by global observation networks as well as joint process studies can the necessary data be generated to (1) identify the relevant microbial and phytoplankton communities, (2) quantify the rates of ocean GHG production and consumption pathways, (3) comprehend their major drivers, and (4) decipher economic and cultural implications of mitigation solutions.publishedVersio

Robust Optimization Using the Mean Model with Bias Correction

Optimization of the expected outcome for subsurface reservoir management when the properties of the subsurface model are uncertain can be costly, especially when the outcomes are predicted using a numerical reservoir flow simulator. The high cost is a consequence of the approximation of the expected outcome by the average of the outcomes from an ensemble of reservoir models, each of which may need to be numerically simulated. Instead of computing the sample average approximation of the objective function, some practitioners have computed the objective function evaluated on the “mean model,” that is, the model whose properties are the means of properties of an ensemble of model realizations. Straightforward use of the mean model without correction for bias is completely justified only when the objective function is a linear function of the uncertain properties. In this paper, we show that by choosing an appropriate transformation of the variables before computing the mean, the mean model can sometimes be used for optimization without bias correction. However, because choosing the appropriate transformation may be difficult, we develop a hierarchical bias correction method that is highly efficient for robust optimization. The bias correction method is coupled with an efficient derivative-free optimization algorithm to reduce the number of function evaluations required for optimization. The new approach is demonstrated on two numerical porous flow optimization problems. In the two-dimensional well location problem with 100 ensemble members, a good approximation of the optimal location is obtained in 10 function evaluations, and a slightly better (nearly optimal) solution using bias correction is obtained using 216 function evaluations.publishedVersio

Machine learning reveals regime shifts in future ocean carbon dioxide fluxes inter-annual variability

The inter-annual variability of global ocean air-sea CO2 fluxes are non-negligible, modulates the global warming signal, and yet it is poorly represented in Earth System Models (ESMs). ESMs are highly sophisticated and computationally demanding, making it challenging to perform dedicated experiments to investigate the key drivers of the CO2 flux variability across spatial and temporal scales. Machine learning methods can objectively and systematically explore large datasets, ensuring physically meaningful results. Here, we show that a kernel ridge regression can reconstruct the present and future CO2 flux variability in five ESMs. Surface concentration of dissolved inorganic carbon (DIC) and alkalinity emerge as the critical drivers, but the former is projected to play a lesser role in the future due to decreasing vertical gradient. Our results demonstrate a new approach to efficiently interpret the massive datasets produced by ESMs, and offer guidance into future model development to better constrain the CO2 flux.Machine learning reveals regime shifts in future ocean carbon dioxide fluxes inter-annual variabilitypublishedVersio

Autonomous UAV Exploration and Mapping in Uncharted Terrain Through Boundary-Driven Strategy

Unmanned Aerial Vehicles (UAVs) play a crucial role in exploring unpredictable terrains, such as accident sites and search zones. These robots require autonomous navigation and precise path planning to operate safely and efficiently in dynamic environments. UAVs must balance navigation accuracy and energy efficiency constraints during autonomous operations. This paper introduces an innovative boundary-driven mapping strategy for UAV exploration in unknown environments. The study proposes a novel approach for boundary extraction using deep learning and presents a decision-making methodology to enable the UAV to select the most optimal frontier for exploration based on deep learning-derived information. The primary objective is to efficiently expand the unknown map. The research demonstrates a significant reduction in exploration time within a simulated environment, achieving better performance compared to other methodologies documented in the literature. The results highlight the effectiveness and efficiency of the proposed strategy in terms of mapping exploration.publishedVersio