Virkningsberegninger på KVARTS

Statistisk sentralbyrås makroøkonometriske kvartalsmodell KVARTS er konstruert med tanke på å fange opp de sentrale mekanismer i norsk økonomi som er viktige for konjunktur- og politikkanalyser på kort og mellomlang sikt. I denne rapporten belyses viktige trekk ved norsk økonomi gjennom virkningsberegninger på KVARTS. Modellens adferdsrelasjoner er tallfestet på bakgrunn av historiske observasjoner av de relevante økonomiske størrelsene gjennom de siste 15-25 årene, og rapporten dokumenterer hovedstrukturen i modellen slik den forelå sommeren 2004 - og dermed vår oppfatning av hvordan norsk økonomi fungerte på samme tidspunkt. Fokuset i denne rapporten er lagt på både sentrale aggregerte størrelser og på et relativt detaljert næringsnivå. Det rapporteres resultater på opptil 16 års sikt, og dette forholdsvis langsiktige perspektivet har medført at selve kvartalsdimensjonen har blitt undertrykt. Et av målene med arbeidet bak denne rapporten har vært å undersøke hvordan valutakursen påvirker norsk økonomi. Vår viktigste erfaring med denne er at nominelle sjokk forsterkes gjennom en pris-lønnsvalutakurs- spiral, som via realrenten forplanter seg videre i realøkonomien. Og at denne spiralen kan dempes, eventuelt motvirkes ved passende renteresponser

OXR1A, a Coactivator of PRMT5 Regulating Histone Arginine Methylation

Oxidation resistance gene 1 (OXR1) protects cells against oxidative stress. We find that male mice with brain-specific isoform A knockout (Oxr1A−/−) develop fatty liver. RNA sequencing of male Oxr1A−/− liver indicates decreased growth hormone (GH) signaling, which is known to affect liver metabolism. Indeed, Gh expression is reduced in male mice Oxr1A−/− pituitary gland and in rat Oxr1A−/− pituitary adenoma cell-line GH3. Oxr1A−/− male mice show reduced fasting-blood GH levels. Pull-down and proximity ligation assays reveal that OXR1A is associated with arginine methyl transferase PRMT5. OXR1A-depleted GH3 cells show reduced symmetrical dimethylation of histone H3 arginine 2 (H3R2me2s), a product of PRMT5 catalyzed methylation, and chromatin immunoprecipitation (ChIP) of H3R2me2s shows reduced Gh promoter enrichment. Finally, we demonstrate with purified proteins that OXR1A stimulates PRMT5/MEP50-catalyzed H3R2me2s. Our data suggest that OXR1A is a coactivator of PRMT5, regulating histone arginine methylation and thereby GH production within the pituitary gland.publishedVersio

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Sjokktesting av satelittkomponenter

Oppgaven omfatter en innføring til sjokk og sjokktesting av primært kubesatellittkomponenter. Utvikling og evaluering av en innretning til bruk av studenter for sjokktesting av satellittkomponenter ved NTNU Gløshaugen

Quantitative interpretation using inverse rock-physics modeling on AVO data

Quantitative seismic interpretation has become an important and critical technology for improved hydrocarbon exploration and production. However, this is typically a resource-demanding process that requires information from several well logs, building a representative velocity model, and, of course, high-quality seismic data. Therefore, it is very challenging to perform in an exploration or appraisal phase with limited well control. Conventional seismic interpretation and qualitative analysis of amplitude variations with offset (AVO) are more common tools in these phases. Here, we demonstrate a method for predicting quantitative reservoir properties and facies using AVO data and a rock-physics model calibrated with well-log data. This is achieved using a probabilistic inversion method that combines stochastic inversion with Bayes' theorem. The method honors the nonuniqueness of the problem and calculates probabilities for the various solutions. To evaluate the performance of the method and the quality of the results, we compare them with similar reservoir property predictions obtained using the same method on seismic-inversion data. Even though both approaches use the same method, the input data have some fundamental differences, and some of the modeling assumptions are not the same. Considering these differences, the two approaches produce comparable predictions. This opens up the possibility to perform quantitative interpretation in earlier phases than what is common today, and it might provide the analyst with better control of the various assumptions that are introduced in the work process

Seismic reservoir and source-rock analysis using inverse rock-physics modeling: A Norwegian Sea demonstration

Identifying type of rocks and fluids from seismic-amplitude anomalies can be challenging because of seismic nonuniqueness and rock-physics ambiguities. Lithology and fluid predictions based on seismic properties therefore are often associated with uncertainties. On the Norwegian Shelf, clay-rich source rocks and hydrocarbon-filled sandstones often show similar AVO responses. A seismic screening method based on rock physics enables one to better discriminate between these different facies. This technique is demonstrated on seismic AVO data (i.e., acoustic impedance [AI] and VP/VS) from the Norwegian Sea. Rock-physics models for organic-rich shales and gas sandstones are calibrated using nearby well data. Then these models are used for predictions of rock parameters away from well locations. From these predictions, the likelihood of presence of organic-rich shales versus gas sandstones can be evaluated, based on a rock-physics approach. However, there are many uncertainties in the accuracy of the calibrated models and the seismic image of the target area. Hence, predictions should be evaluated along with other geologic and geophysical information before firm conclusions about these anomalies are made

Rock-physics modeling guided by depositional and burial history in low-to-intermediate-porosity sandstones

ABSTRACT We present a new rock-physics modeling approach to describe the elastic properties of low-to-intermediate-porosity sandstones that incorporates the depositional and burial history of the rock. The studied rocks have been exposed to complex burial and diagenetic history and show great variability in rock texture and reservoir properties. Our approach combines granular medium contact theory with inclusionbased models to build rock-physics templates that take into account the complex burial history of the rock. These models are used to describe well log data from tight gas sandstone reservoirs in Saudi Arabia, and successfully explain the pore fluid, rock porosity, and pore shape trends in these complex reservoirs