Kunnskapens betydning i tverretatlig samarbeid : et essay

Bachelor i politiutdannin

The Return of Death in Times of Uncertainty:A Sketchy Diagnosis of Death in the Contemporary ‘Corona Crisis’

For most parts of human history, death was an integral part of life, something that prehistoric and premodern man had no other option than to live with as best as possible. According to historians, death was familiar and tamed, it was at the center of social and cultural life. With the coming of modern secular society, death was increasingly sequestrated and tabooed, moved to the outskirts of society, made invisible and forbidden. Death became a stranger, and the prevalent attitude towards death was that of alienation. At the threshold of the 21st century, the topic of death again began to attract attention, becoming part of a revived death attitude described as ‘Spectacular Death’. In the article, the authors diagnose, analyze, and discuss the impact of the return of death during the current ‘Corona Crisis’, arguing that despite the fact that the concern with death is at the very core of the management of the crisis, death as such remains largely invisible. In order to provide such a diagnosis of the times, the authors initially revisit the prevailing death attitudes in the Western world from the Middle Ages to the present day

The implementation of Going Dynamic in Telenor from a management control perspective : why and how has Telenor gone Beyond Budgeting?

Today’s organization is striving in environments which frequently are characterized by uncertainties and rapid changes. The budget has been, and still is, a management tool most companies use to govern their activities. The critics of the budget have claimed that the budget has lost its relevance in today’s highly competitive environment. Beyond Budgeting is such a concept that claims that organizations needs to replace the budget due to its conflicting purposes. Telenor is one of the organizations which realized that the budget was inadequate for the company's needs because it did not always contribute in providing the optimal management information. Management realized that the budget was grasping for more than it could handle and introduced Going Dynamic – a management model inspired by the Beyond Budgeting philosophy. We have studied why and how Telenor introduced Going Dynamic by interviewing the project leader for Going Dynamic and employees in two market outlets. Telenor decided to introduce Going Dynamic in the Norwegian organization in 2006. The market outlets were separately responsible for introducing new designs that replaced the budget, which has resulted in some interesting similarities and differences. The study of how Going Dynamic has been introduced in the market outlets has been done from a management control perspective which includes targets, resource allocation and prognoses. The literature states that each organization’s journey to go Beyond Budgeting is unique, and our study confirms that this is the case even between divisions in a single organization. We found that the budget no longer provided management with the adequate information needed in Telenor’s rapid changing environment. The budget could no longer perform its multiple roles included target setting, resource allocation, and cost management in a way that enabled decision making and follow up. Telenor has separated the targets, resource allocation and prognoses as a result of this. The two market outlets have developed different mechanisms that allow a more dynamic resource allocation. The processes of making prognoses, which aim to reveal gaps towards the targets, are applied differently in the two market outlets. The prognoses have made processes more visible and the incentive structure has been changed. However, there are indications that the budget has not been fully deinstitutionalized yet and the budget-like fixed target setting process seems to hamper Telenor’s ability to allocate resources dynamically to a certain degree

Intragenomic Matching Reveals a Huge Potential for miRNA-Mediated Regulation in Plants

microRNAs (miRNAs) are important post-transcriptional regulators, but the extent of this regulation is uncertain, both with regard to the number of miRNA genes and their targets. Using an algorithm based on intragenomic matching of potential miRNAs and their targets coupled with support vector machine classification of miRNA precursors, we explore the potential for regulation by miRNAs in three plant genomes: Arabidopsis thaliana, Populus trichocarpa, and Oryza sativa. We find that the intragenomic matching in conjunction with a supervised learning approach contains enough information to allow reliable computational prediction of miRNA candidates without requiring conservation across species. Using this method, we identify ∼1,200, ∼2,500, and ∼2,100 miRNA candidate genes capable of extensive base-pairing to potential target mRNAs in A. thaliana, P. trichocarpa, and O. sativa, respectively. This is more than five times the number of currently annotated miRNAs in the plants. Many of these candidates are derived from repeat regions, yet they seem to contain the features necessary for correct processing by the miRNA machinery. Conservation analysis indicates that only a few of the candidates are conserved between the species. We conclude that there is a large potential for miRNA-mediated regulatory interactions encoded in the genomes of the investigated plants. We hypothesize that some of these interactions may be realized under special environmental conditions, while others can readily be recruited when organisms diverge and adapt to new niches

A Predictive Chance Constraint Rebalancing Approach to Mobility-on-Demand Services

This paper considers the problem of supply-demand imbalances in Autonomous Mobility-on-Demand systems (AMoD) where demand uncertainty compromises both the service provider's and the customer objectives. The key idea is to include estimated stochastic travel demand patterns into receding horizon AMoD optimization problems. More precisely, we first estimate passenger demand using Gaussian Process Regression (GPR). GPR provides demand uncertainty bounds for time pattern prediction. Second, we integrate demand predictions with uncertainty bounds into a receding horizon AMoD optimization. In order to guarantee constraint satisfaction in the above optimization under estimated stochastic demand prediction, we employ a probabilistic constraining method with user defined confidence interval. Receding horizon AMoD optimization with probabilistic constraints thereby calls for Chance Constrained Model Predictive Control (CCMPC). The benefit of the proposed method is twofold. First, travel demand uncertainty prediction from data can naturally be embedded into AMoD optimization. Second, CCMPC can further be relaxed into a Mixed-Integer-Linear-Program (MILP) that can efficiently be solved. We show, through high-fidelity transportation simulation, that by tuning the confidence bound on the chance constraint close to "optimal" oracle performance can be achieved. The median wait time is reduced by 4% compared to using only the mean prediction of the GP.Comment: 11 pages, 8 figure