Cointegrated energy : can energy company shares be used to create error correction model forecasts for the oil price? : if so, are there certain sectors within the industry that produce better forecasts?

Oil company shares are closely related to the oil price. This paper examines if this relationship is strong enough to conclude that the historical spot prices for oil are cointegrated with individual oil company share price time series, arguing that investors, who buy shares in companies whose business is related to the exploration, production or marketing of oil and oil based products, are forward looking. In turn this implies that the share prices embody information about expected future oil prices, much like oil futures. The paper will also attempt to explore, if there are certain sectors within the oil industry that are more appropriate to use as forecasting tools for oil. The paper answers whether there is a cointegrated relationship between oil shares and the spot price for crude, but fails to answer the second part because no such cointegrated relationship seems to exist

Systemic inflammatory markers as predictors of longitudinal outcomes in COPD : Results from the Bergen COPD Cohort Study

Background: Chronic obstructive pulmonary disease (COPD) is major cause of morbidity and mortality worldwide. The prevalence is increasing worldwide, as a result of an increase in cigarette smoking the last decades. The main symptom of COPD is chronic and progressive dyspnea, often accompanied with cough and increased amounts of phlegm. A significant share of the patients suffers episodes with exacerbation of the disease, which may negatively impact quality of life, disease burden and survival. COPD pathophysiology is complex and consists of different disease mechanisms. Inflammation is a central component of COPD, and increased number of immune cells and cytokines are found both in the airways and in the systemic circulation. The COPD pathophysiology is incompletely understood, and there is comprehensive research on inflammatory biomarkers in order to improve diagnosis, identify patients with increased risk of adverse outcome, and to find targets for medical treatment. Aims: 1-Identify diagnostic biomarkers of stable COPD and acute exacerbation of COPD. 2 -Identify inflammatory biomarkers as predictors for longitudinal outcome using longitudinal data: a. as predictors for future exacerbations b. as predictors for change in lung function c. as predictors for mortality and cause of death d. as predictors for lung cancer Methods: The Bergen COPD cohort study (BCCS) included 433 COPD patients and 325 controls between 2006 and 2009. The COPD patients were aged between 40-76, all were former or current smokers. The COPD diagnosis was based on a clinical evaluation combined with an obstructive post-bronchodilator spirometry. Of the 433 COPD patients, 356 patients living in the vicinity of Haukeland University Hospital were also included in the Bergen COPD Exacerbation Study (BCES). All patients and controls went through an extensive examination at inclusion including medical history, physical examination, lung function testing, bioelectrical impedance measurements, HRCT, blood sampling, and microbiological testing. The patients and a selection of the controls were followed up during study visits each 6 months for 3 years, repeating lung function tests and blood sampling each 6 months, bioelectrical impedance each 12 months. In addition, patients were followed up to 9 years regarding mortality and cause of death as well as lung cancer development. Acute exacerbations of COPD (AECOPD) were registered both at each 6-month visit, in addition the patients in the BCES were telephoned each month and asked about symptoms regarding AECOPD. A selection of the patients was also examined at exacerbation where additional blood sampling was performed. The inflammatory biomarkers were evaluated at baseline and at AECOPD using both non-parametric and multiple regression models. For the analysis of the inflammatory biomarkers as predictors of future exacerbations, decline in lung function, mortality and lung cancer development, bi-level longitudinal regression models and cox-regression models were used. Results: Systemic inflammatory markers were measured in all 433 patients and 325 controls at inclusion, and in 149 patients at AECOPD. Macrophage migration inhibitory factor (MIF) was identified as potential biomarker both for stable COPD as well as AECOPD in Paper 2. Within the three years of the BCES, 350 of 403 COPD patients suffered 933 moderate and 370 severe COPD exacerbations. A history of exacerbations, female sex, chronic cough and a lower FEV1 were identified as predictors for future AECOPD in Paper 1. In Paper 3, high levels of GDF-15 were identified as a predictor for a higher future AECOPD count. The COPD patients experienced an average yearly FEV1 decline of 61 ml (1.31 %) in men and 36 ml (0.76 % women) in women. High levels of GDF-15 were identified as a predictor of a faster decline of both FEV1 and FVC in Paper 3. Other factors associated with a faster FEV1 decline were male sex and cachexia. Thirty-six COPD patients died with the first three years of follow up, 159 within 9 years. High levels of GDF-15 were identified as a predictor of a higher mortality in Paper 3. Other factors associated with a higher mortality were a low FEV1, cachexia, obesity and a high degree of comorbidity. Twenty-eight patients developed lung cancer within 9 years. COPD was significantly associated with a higher lung cancer risk. Within COPD patients, emphysema and obesity was associated with a higher lung cancer risk. Of 44 inflammatory biomarkers, only IP-10 was associated with a higher lung cancer risk, whereas systemic inflammation evaluated by a PCA-analysis did not show any correlation with lung cancer development. Conclusion: 1 Macrophage migration inhibitory factor (MIF) was identified as potential biomarker for both for stable COPD as well as AECOPD. 2 a. High levels of GDF-15 were identified as a predictor for a higher future AECOPD count in addition to several clinical characteristics. b. High levels of GDF-15 were identified as a predictor of a faster decline of both FEV1 and FVC. c. High levels of GDF-15 were identified as a predictor of all-cause mortality as well as mortality due to respiratory disease. d. IP-10 was significantly associated with a higher lung cancer risk, whereas systemic inflammation did not show any correlation with lung cancer development.Doktorgradsavhandlin

Lifetime Based Health Indicator for Bearings using Convolitional Neural Networks

Master's thesis Renewable Energy ENE500 - University of Agder 2019Out of all the components in rotating electrical machinery, bearings have the highest failure rate. Bearingdegradation is a seemingly random process which is hard to both model and predict. Countless of con-dition based methods and algorithms have been proposed in order to accurately diagnose incipient faultsand estimate the remaining useful lifetime of bearings. These methods are often complex and hard to im-plement. In this thesis, a data-driven method of estimating a linear lifetime based health indicator (HI)using convolutional neural networks (CNNs) is proposed. The idea behind the method is to train a CNNmodel to recognize the shapes and distributions of vibration data in order to predict a HI with minimalpre-processing. Two models are presented: A CNN that takes time-series vibration data as input and aCNN that takes vibration frequency spectrum data as input. Finally, HIs are predicted on unique datasetsand their respective remaining useful lifetimes (RULs) are estimated as part of the model validation process.The results show that the models are able to recognize relevant fault features to a certain degree. However, accurate predictions have proven difficult in many cases

Simulations of acoustic transmission loss of Fin whale calls reaching the LoVe Ocean Observatory

Equinor has plans to develop a whale monitoring station using acoustic animal destiny estimation at their cabled ocean observatory, the LoVe Observatory, in Lofoten-Vesterålen basin. The fauna of this area is of remarkable importance to the Norwegian economy due to its unique fishing banks and its newly discovered petroleum reserves. This makes it important to monitor the Fin whale population in the area, especially if human interference in the region is to be increased due to new petroleum related interventions. Moreover, the observatory will hopefully bring about new knowledge of the habitat and migratory routes of the Fin whale, which are currently poorly understood. In order to implement an animal density estimation algorithm at the LoVe Observatory it is necessary to know how the transmission loss experienced by sounds reaching the observatory varies as a function of position around the receiver. This study has developed a set of model tools fit to simulate the transmission loss at any position in the Lofoten-Vesterålen basin, by using environmental data available at various databases as input parameters to the parabolic equation model Range-dependent Acoustic Model (RAM). The study has utilized these tools to produce simulations of the transmission loss at a number of example transects, in order to present some conclusions about how the transmission loss is affected by the environmental parameters bathymetry, sound speed profiles and sedimentary geoacoustic properties. Furthermore, the simulations have been repeated for each of the four seasons, to look at how the transmission loss varies across the year. Generally, the study will show that the variation of transmission loss with position is complex and that the inclusion of environmental parameters in the simulations is necessary. It will be shown that the observatory is capable of detecting Fin whales at 190 km in low noise conditions, but that this range is limited by the angular direction of the propagation path and by increases in the noise level. Seasonal variability in the transmission loss will be shown, but it has not been possible connect this variation to the observed yearly variation in Fin whale detections.Masteroppgave i fysikkMAMN-PHYSPHYS39

Staff distress improves by treating pain in nursing home patients with dementia: results from a cluster-randomized controlled trial

Context. Most people with dementia develop neuropsychiatric symptoms (NPSs), which are distressing for their carers. Untreated pain may increase the prevalence and severity of NPSs and thereby staff burden. Objectives. We investigated the association between NPSs and the impact of individual pain treatment on distress in nursing home staff. Methods. Nursing home (NH) units were cluster-randomized to an intervention group (33 NH units; n ¼ 175) or control group (27 NH units; n ¼ 177). Patients in the intervention group received individual pain treatment for eight weeks, followed by a four-week washout period; control groups received care as usual. Staff informants (n ¼ 138) used the Neuropsychiatric InventoryeNH version (including caregiver distress) as primary outcome to assess their own distress. Other outcomes were pain (Mobilization-Observation-Behavior-Intensity-Dementia-2 Pain Scale) and cognitive functioning (MinieMental State Examination). Results. Using hierarchical regression analysis, all NPS items at baseline were associated with staff distress (P < 0.01) apart from euphoria; agitation had the largest contribution (b ¼ 0.24). Using mixed models, we found significantly lower staff distress in the intervention group compared to the control group. Moreover, we also found significantly reduced distress in the control group, and there were still effects in both groups throughout the washout period. Conclusion. Individual pain treatment reduced staff distress in the intervention group compared to control group especially in regard to agitation-related symptoms and apathy. Furthermore, our results indicated a multifactorial model of staff distress, in which enhanced knowledge and understanding of NPSs and pain in people with advanced dementia may play an important role.publishedVersio

What is the willingness to pay for green electricity in Norway? A perspective on Guarantees of Origin.

Norway is one of the only countries in the world producing its electricity from almost only renewable resources. The Renewable Energy Directive 2001/77/EC (2001) introduced a system of Guarantees of Origin (GOs) as an incentive system for power producers and a tracking system of the renewable electricity consumption in Europe. It is mandatory to purchase GOs to be able to claim any renewable electricity consumption. A low demand for GOs results in only 18 percent (2019) of the renewable electricity being purchased in Norway and the remainings being exported in Europe making Norway the largest exporter of GOs. Consequently, the electricity consumed by Norwegians is not as renewable as believed. Thus, in this thesis we tried to figure out if the low demand has roots in low knowledge about GOs or not. Furtheremore, we aimed to estimate their maximum willingness to pay and factors affecting it. In order to achieve these aims, we used contingent valuation method survey. The survey introduces GOs through a scenario and simplified example, followed by a payment card as the elicitation method. The data is further analyzed by Logistic Regression, Ordinal Logistic Regression, and Interval Regression to gain more in-depth insight about factors affecting willingness to buy (WTB) and willingness to pay (WTP). The results show that most respondents are neither aware of Norway’s green electricity production nor GOs. Nevertheless, after being informed about GOs, most of the respondents without prior knowledge were willing to buy these with an average WTP of 5 to 9 percent of their electricity bill. The most critical factors affecting respondents’ WTB are gender, age, heating source, social media behavior, beliefs and behaviors towards the environment, car type, and prior knowledge about GOs. The models regarding WTP indicate that the most vital factors are education, heating source, employment status, beliefs and behavior toward the environment, social media behavior, and satisfaction with the electricity provider

A methodological framework for capturing relative eyetracking coordinate data to determine gaze patterns and fixations from two or more observers

While physical activity during cancer treatment is found beneficial for breast cancer patients, evidence indicates ambiguous findings concerning effects of scheduled exercise programs on treatment-related symptoms. This study investigated effects of a scheduled home-based exercise intervention in breast cancer patients during adjuvant chemotherapy, on cancer-related fatigue, physical fitness, and activity level. Sixty-seven women were randomized to an exercise intervention group (n=33, performed strength training 3x/week and 30 minutes brisk walking/day) and a control group (n=34, performed their regular physical activity level). Data collection was performed at baseline, at completion of chemotherapy (Post1), and 6-month postchemotherapy (Post2). Exercise levels were slightly higher in the scheduled exercise group than in the control group. In both groups, cancer-related fatigue increased at Post1 but returned to baseline at Post2. Physical fitness and activity levels decreased at Post1 but were significantly improved at Post2. Significant differences between intervention and control groups were not found. The findings suggest that generally recommended physical activity levels are enough to relief cancer-related fatigue and restore physical capacity in breast cancer patients during adjuvant chemotherapy, although one cannot rule out that results reflect diminishing treatment side effects over time

Gamle – og pasienter med demens – Omsorg ved livets slutt

I livets siste leveår vil det store flertall gamle og pasienter med demens trenge kompetent omsorg, pleie, vurdering og behandling, med respekt for deres livsprosjekt og verdighet. Alle vil i de siste måneder, uker, dager og timer før de dør trenge kompetent omsorg ved livets slutt (palliative care), uavhengig av diagnose eller oppholdssted – til alle døgnets tider. Artikkelen drøfter utfordringer og muligheter, grunnlaget for nødvendig kompetanse: etikk, forberedende samtaler, organisering og samhandling

Actual clinical leadership: a shadowing study of charge nurses and doctors on-call in the emergency department

Background: The provision of safe, high quality healthcare in the Emergency Department (ED) requires frontline healthcare personnel with sufficient competence in clinical leadership. However, healthcare education curriculum infrequently features learning about clinical leadership, and there is an absence of experienced doctors and nurses as role models in EDs for younger and less experienced doctors and nurses. The purpose of this study was to explore the activities performed by clinical leaders and to identify similarities and differences between the activities performed by charge nurses and those performed by doctors on-call in the Emergency Department after completion of a Clinical Leadership course. Methods: A qualitative exploratory design was chosen. Nine clinical leaders in the ED were shadowed. The data were analyzed using a thematic analysis. Results: The analysis revealed seven themes: receiving an overview of the team and patients and planning the shift; ensuring resources; monitoring and ensuring appropriate patient flow; monitoring and securing information flow; securing patient care and treatment; securing and assuring the quality of diagnosis and treatment of patient; and securing the prioritization of patients. The last two themes were exclusive to doctors on-call, while the theme “securing patient care and treatment” was exclusive to charge nurses. Conclusions: Charge nurses and doctors on-call perform multitasking and complement each other as clinical leaders in the ED. The findings in this study provide new insights into how clinical leadership is performed by charge nurses and doctors on-call in the ED, but also the similarities and differences that exist in clinical leadership performance between the two professions. Clinical leadership is necessary to the provision of safe, high quality care and treatment for patients with acute health needs, as well as the coordination of healthcare services in the ED. More evaluation studies of this Clinical Leadership course would be valuable.publishedVersio

Listening to students for tomorrow, today: engaging students to define the future of higher education

This article examines the voices of students at a symposium organized by the European Consortium of Innovative Universities (ECIU) in 2018: ‘Learning for Tomorrow, Today: Future Fit Universities for 2040’. Twenty students from 11 universities attended with university leaders and policy makers. A dataset of field notes, written comments, post-event evaluations, and over 3 hours of video-material was accumulated, and has been analysed through video-hermeneutics and content-analysis. Five students chose to become co-authors after critically reading and validating the text and analysis. The research question asks how students perceive teaching and learning in a future fit university in 2040. Using an ‘engagement through partnership’ model, we argue that combining the voices of current andfuture stakeholders moves the sector a step closer to ‘future fit’ higher education. Our main finding is that students are eager to contribute to policy, strategy and practice. Furthermore, they express a view that universities must play a significant role in securing core societal values and in developing future citizens able to participate in democracy. At no point did students question the existence of universities in 2040. We argue that the students express a wish to assume the role of co-drivers and agents of change, not only in university management, but also in pedagogy and co-creation of new knowledge. Positioning themselves thus, they challenge our practice as academic staff, signalling that to develop full partnerships, we must position ourselvesas learners too, and embrace co-creation.publishedVersio