"Spekk-finger" or Sealer's Finger

Contains an account of a severe local infection (cellulitis) common among sealers, especially those handling the blubber (spekk) or skins. Its occurrence and distribution, symptoms, cause (not as yet established, but probably Erysipelothrix rhusiopatiae), treatment, including latest experiment with antibiotics are discussed. Description of a case is given, and measures of prevention indicated. Bibliography (11 items)

Investigating the underlying components of long-term committed mating psychology

Menneskelig seksualitet er pluralistisk på den måten at folk både ønsker og opplever flere forskjellige forhold som varierer i forpliktelse og lengde i løpet av livet. Mens individuelle forskjeller i korttidsseksualitet er godt forstått, er de underliggende komponentene som forårsaker langtidsforhold mindre klare. I et snøballutvalg bestående av 183 menn og 423 kvinner fra en likestilt kultur etablerte vi et måleinstrument på langtidsseksualitet basert på de adaptive utfordringene ved langtidsforhold. Gjennom en prinsipiell faktoranalyse bekreftet vi de predikerte komponentene våre, og en konfirmerende faktoranalyse bekreftet at de tre komponentene passet dataen bedre enn en totalskåre. Inkluderingen av de nye komponentene forbedret forklaringsevnen til prediktive modeller for menneskelig langtidsatferd over effekten av to andre etablerte mål i fire av de fem regresjonsanalysene. Forpliktelseskomponenten og eksklusivitetskomponenten, men ikke intimitetskomponenten, forklarte variasjon i utfallsmålene når de var kontrollert for de andre variablene. Forpliktelseskomponenten forklarte variasjon i forholdsstatus, tid som singel, og antall forpliktede forhold. Eksklusivitets komponenten forklarte unik varians i utroskap, forholdsstatus, tid som singel og antall forpliktede forhold. Vi fant også at sosioseksualitet var et sentralt mål for å forstå variasjon i langtidsatferd. Funnene og implikasjonene er diskutert opp mot en multidimensjonal forståelse av menneskelig seksualitet.Human mating is pluralistic in that most people both desire and experience multiple relationships of varying degrees of commitment and duration throughout their life. While individual variation in short-term uncommitted mating is well understood, the underlying components of long-term committed mating psychology are less so. In a snowball sample of 183 men and 423 women from a high ranked gender-egalitarian culture, we successfully established a multi-component measurement based on the assumed adaptive functions of long-term committed relationships. Principal factor analysis extracted our predicted three-component structure, and a confirmatory analysis confirmed that the three-component structure fit the data better than an overall total score. The inclusion of our new components improved upon the explanatory power of predictive models of human sexuality over and above the effect of contemporary and established measurements of human mating (SOI-R and LTMO-MSOI) in four of our five behavioral outcome variables. The commitment component and the exclusivity component, but not the intimacy component, uniquely explained individual variation when controlled for the other predictors. The commitment component significantly explained variation in relationship status, time spent single, and history of committed relationships. However, it was unrelated to infidelity, which was better explained by the exclusivity component. The exclusivity component also explained unique variation in the probability of being partnered, time spent single, and the number of committed relationships. We also found that sociosexuality was an essential measurement of long-term behavioral outcomes. Findings and implications are discussed in light of the multidimensional conceptualization of sexual strategies

Prediction of power, energy and hydrogen demand in a zero-emission port

Norge har som mål å oppnå en utslippsfri maritim flåte innen 2050. For å nå dette målet må ny teknologi og alternative drivstoff bli implementert i den maritime sektoren. Noen av de foreslåtte teknologiene er batteri til full elektrisk og hybride skip, samt benytte seg av de utslippsfrie drivstoffene hydrogen, ammonium og metanol. Om hydrogen, ammonium og metanol skal kunne regnes som 100 \% utslippsfrie må de produseres ved bruk av strøm fra fornybare kilder gjennom elektrolyse. Disse alternativene vil kreve mye strøm og det er viktig å gjennomføre gode analyser som kan forutse hvordan det økende behovet vil påvirke kraftnettet slik det er i dag. På grunn av mye usikkerhet i den maritime sektor finnes det ingen gode analyseverktøy for å beregne det kommende kraftbehovet til sektoren. Derfor er det i denne masteroppgaven utviklet en modell som kan beregne fremtidige energi-, effekt- og hydrogenbehov for en valgfri havn som implementerer en eller flere av de nevnte teknologiene og nullutslippsdrivstoffene. Modellen består av tre deler: "Lastmodell", "Strømprismodell" og "Optimaliseringsmodell", og er laget slik at den kan brukes på alle havner i Norge. Lastmodellen beregner timesbehovet for hydrogen, landstrøm og ladestrøm for de ulike skipstypene som er i havn. I tillegg er produksjonen fra lokale solcellepaneler inkludert. Optimeringsmodellen består av to optimeringsproblemer som begge benytter de beregnede lastbehovene i tillegg til strømpriser og nettleie, for å finne en optimal hydrogenproduksjon basert på å minimere de årlige driftskostnadene. "Driftsoptimalisering" optimaliserer driftskostnadene i en havn der kapasiteten til elektrolyse, transformator og hydrogenlager er begrenset, mens "Drifts- og investeringsoptimalisering" inkluderer å finne de gunstige størrelsene på elektrolyse, transformator og hydrogenlager for en havn ved å minimere investeringskostnadene i tillegg til driftskostnadene. I denne masteroppgaven brukes Oslo Havn som eksempel for å vise bruksområdene til den utviklede modellen i tillegg til å beregne fremtidig kraft-, energi- og hydrogenbehov for havnen. Det er simulert for seks ulike scenarier med ulik bruk av nullutslipps drivstoff og teknologier. I tillegg er det gjennomført en sensitivitetsanalyse for å teste effekten av de ulike systemparameterne inkludert i modellen. En oppsummering av resultatene viser at implementeringen av landstrøm for alle tilkoblede skip anslås å kreve ca. 7 GWh i løpet av et år, med en effekttopp på 3 MW. Denne implementeringen kan redusere CO2-utslippene i havnene med omtrent 4505 tonn. I et scenario der alle skipene enten er "grønn hybrid" eller bruker hydrogen som drivstoff, er det totale hydrogenbehovet beregnet til 18260 tonn per år med et totalt energibehov på 923 GWh og en effekttopp på 170 MW. Denne implementeringen kan redusere CO2-utslippene i havnene med ca. 215422 tonn. Det beregnede effektbehovet (170 MW) er 4,7 ganger større enn den eksisterende transformatorkapasiteten som befinner seg på Oslo havn. Dette indikerer at kapasiteten i både transformatoren og kabler må fornyes for å kunne håndtere et høyere effektbehov i fremtiden. Videre viser sensitivitetsanalysen i denne masteroppgaven at simuleringer med spotpriser fra tidligere år, samt en større investeringskostnad for elektrolysøren reduserer de simulerte effekttoppene. Resultatene fra denne studien bidrar til å gi en oversikt over den omtrentlige totale energi-, effekt- og hydrogenetterspørselen som kan oppstå i fremtiden. Hovedformålet med denne studien er derfor å øke bevisstheten blant nettplanleggere og bransjeaktører om den forventede etterspørselen, slik at de kan planlegge og tilpasse infrastrukturen og kapasiteten deretter.Norway aims to achieve a zero-emission maritime fleet by 2050. To reach this goal it is predicted that shore power and green alternatives such as full-electric, plug-in hybrid electric, hydrogen, ammonia and methanol are implemented. All the mentioned options require electricity from renewable sources to be considered emission-free. However, a detailed power analysis regarding a zero-emission port is still not developed for the maritime sector. Therefore in this master thesis, a model is developed which considers the use of different green alternatives to compute the future energy, power, and hydrogen demand at a zero-emission port. The developed model consists of three parts ”Load Model”, ”Electricity Price Model”, and ”Optimization Model” and is designed in a generalized manner so that it can be applied to all ports in Norway. The ”Load Model” determines the total loads included in a zero-emission port, considering hydrogen, shore power, and charge power to full-electric and plug-in hybrid ships per hour throughout the year. In addition, the energy production from local solar panels is included. The ”Optimization Model” consists of two optimization problems, which utilize the calculated loads, in addition to the electricity prices and grid tariffs to estimate an optimal production of hydrogen based on minimizing annual costs of operation. The ”Optimal operation” optimizes the operation cost in a port where the capacities of electrolysis, transformer and hydrogen storage are limited, while ”Operation and investment optimization” includes finding the optimal sizes of electrolysis, transformer and hydrogen storage for a port by minimizing the investment cost in addition to the operation cost. In this master thesis, the port of Oslo is utilized as a case study to analyze the future power, energy and hydrogen demand for six different fuel mix scenarios. Furthermore, a sensitivity analysis is conducted to test the impact of the different system parameters. Summarizing the results, the implementation of shore power for all ships is estimated to require approximately 7 GWh for a year with a power peak reaching 3 MW. This implementation has the potential to reduce CO2 emissions in ports by approximately 4505 tons per year. Furthermore, in a scenario where all ships are either ”Green hybrids” or fueled with hydrogen, the total hydrogen demand for a year is calculated to be 18260 tons with a total energy demand of 923 GWh and a power peak reaching 170 MW. This implementation has the potential to reduce CO2 emissions in ports by approximately 215422 tons of CO2 per year. However, the predicted power demand is 4.7 times greater than the existing transformer capacity in the port of Oslo. This indicates that the capacity in both the transformers and cables needs to be renewed to handle a higher power demand in the future. Furthermore, the sensitivity analysis of this master thesis presents that the day-ahead prices of former years as well as a higher investment cost of electrolysis can reduce the simulated power peaks. The results obtained from this study contribute to providing an overview of the approximate total energy, power, and hydrogen demand that may emerge in the future. The primary purpose of this study is to raise awareness among stakeholders and industry participants regarding the projected demand, enabling them to plan and adapt their infrastructure and capacities accordingly. By doing so, they can better prepare for the anticipated changes and requirements in the maritime sector

A Julia Implementation of the Differentiable Neural Computer

I differensierbar programmering-paradigmet modelleres programmer som parametriserte løsninger på et problem som deretter trenes med gradientbaserte optimeringsmetoder. DeepMinds Differentiable Neural Computer (DNC) er et eksempel på overgangen fra tradisjonell dyp læring til differensierbar programmering. I denne oppgaven argumenteres det for at Julias maskinlæringsrammeverk, med Flux i sentrum og med Zygote som algoritmisk differensiator, er et mer passende verktøy for implementasjon av programmer som DNC enn TensorFlow. Implementasjonen settes i kontekst av algoritmisk differensiering sin rolle i differensierbar programmering. DNC reimplementers i Julia og dens interne metoder måles opp mot den originale TensorFlow-implementasjonen, der den oppnår lik treningstid med enkelte interne metoder som kjører opp mot syv ganger så raskt.In the paradigm of differentiable programming, programs are modeled as a parameterized solution prototype, which is trained by gradient-based optimization. DeepMind's Differential Neural Computer (DNC) is an example of the transition from traditional deep learning models to differential programs. In this thesis, a Julia implementation of the DNC is presented. An argument is made for the applicability of the Julia programming language and its machine learning ecosystem, with Flux at its core and Zygote as the algorithmic differentiation engine, on differentiable programs. The focus of the thesis is on the role of algorithmic differentiation in machine learning toolkits. The reimplementation is benchmarked, achieving 10\% speedup on a simple training task with a simpler implementation, with some internal methods running up to seven times faster

Annexin-A5 assembled into two-dimensional arrays promotes cell membrane repair

Eukaryotic cells possess a universal repair machinery that ensures rapid resealing of plasma membrane disruptions. Before resealing, the torn membrane is submitted to considerable tension, which functions to expand the disruption. Here we show that annexin-A5 (AnxA5), a protein that self-assembles into two-dimensional (2D) arrays on membranes upon Ca2+ activation, promotes membrane repair. Compared with wild-type mouse perivascular cells, AnxA5-null cells exhibit a severe membrane repair defect. Membrane repair in AnxA5-null cells is rescued by addition of AnxA5, which binds exclusively to disrupted membrane areas. In contrast, an AnxA5 mutant that lacks the ability of forming 2D arrays is unable to promote membrane repair. We propose that AnxA5 participates in a previously unrecognized step of the membrane repair process: triggered by the local influx of Ca2+, AnxA5 proteins bind to torn membrane edges and form a 2D array, which prevents wound expansion and promotes membrane resealing

Master Slag Production for the Recovery of Rare Earth Elements

The Rare Earth Elements (REEs) is a term describing a group of 17 elements which are critical components in many technological applications due to their magnetic or optical properties. In contrast to the name, these elements are relatively abundant, but distributed in low concentration throughout the Earth's crust. Recovery of these elements is currently focused mainly in China, but the strategic importance of these elements within the EU motivates innovation in local resource extraction. The development of a pyrometallurgical approach for the recovery of REEs from iron mine tailings containing apatite has been the main focus of the present work. This was realized through the production of a Master Slag, i.e. a slag of uniform relative composition of Nd2O3-SiO2-CaO made from an Apatite Concentrate produced by LKAB in Kiruna, Sweden, which is a Swedish iron mining company. An experimental investigation into the Nd2O3-SiO2-B2O3 phase diagram was also performed for the intention of developing fundamental thermodynamic data for the Nd-Fe-B system - commercially known as the system used in permanent magnets. The developed thermal process of producing the Master Slag includes two main steps, i.e. (1) removal of phosphorus, which was achieved with a 99.7% reduction, and (2) melting of the remaining material at 1873 K for 60 min in an induction furnace; followed by rapid cooling. Scanning Electron Microscope - Energy Dispersive X-ray Spectrometry (SEM-EDS), X-Ray Diffraction (XRD) and Inductively Coupled Plasma - Mass Spectrometry (ICP-MS) were used for the chemical analysis of the obtained material. The produced Master Slag proved to consist of three phase regions, these differed mainly by their neodymium concentration. The Nd-rich phase contained the compounds Ca2Nd3(SiO4)3F and variations of Ca2Nd3(SiO4)2(PO4)O with an overall Nd-concentration of 20-48% by weight. However, sampling at a lower temperature seems to indicate a higher Nd-concentration in the Nd-rich phase. The evaluation of the Nd2O3-SiO2-B2O3 phase diagram proved to offer several critical issues. A method for equilibriation of samples at high temperature (1673 K) without vaporization of B, as well as the optimization of the equilibriation time to secure reproducible results were the focus in the present work

Applying the consumer ethnocentrism model to norwegian consumers.

Bacheloroppgave i Markedsføring fra Handelshøyskolen BI, 2020This thesis explores Norwegian consumers perceptions towards foreign products. It specifically investigates consumers ethnocentric tendencies, which influences purchase intentions and preferences to domestic versus foreign products. The purpose of this thesis has been to establish Norwegian consumers’ level of ethnocentrism and look at variables affecting this. The following research question was therefore developed; What level of presence does consumer ethnocentrism have within Norwegian consumers, what factors affect this, and ultimately how does this affect the perception of foreign commodities? The conceptual framework of this study was inspired by numerous studies building on Shimp and Sharma’s theory of consumer ethnocentrism, consumer ethnocentric tendencies, and the CETSCALE. From this we also decided on the study’s independent socio-psychological variables: perceived product necessity, cultural openness, perceived economic threat, and environmental concern. We also researched the demographic variables age and ethnic identity. The paper is sectioned in four parts: firstly, a theoretical opening to introduce the topic and its relevance to contemporary society. Secondly, a methodology part where the responses were analysed and interpreted. Thirdly, discussion and conclusion where the results from methodology are defined and elaborated. Lastly, a reflective ending highlighting the limitations of the study, self-reflection and where to go with future research. A descriptive, quantitative design was used to increase the generalisability; the survey gave a total of 169 usable responses to analyse. Primarily the analyses used were ANOVA and regression to test the six hypotheses formulated for the study. Prior to analysing the hypotheses, several validity analyses were done to uncover which questions belonged under the different variables. Of the six formulated hypotheses four were supported. For the demographic variable, there is a significant difference in the level of consumer ethnocentric tendencies concerning age. As for the socio-psychological variables perceived economic threat, cultural openness, and environmental concern all have a significant effect on the level of CET. The level of CET was evaluated as high, however as perceived economic threat was proven to have an effect, the current COVID-19 pandemic has in all likeliness affected the level to be higher than normal. Ethnic identity and perceived product necessity was not supported. However, certain findings in the analyses gives an indication that it needs to be further researched