Active learning and optimal climate policy

This paper develops a climate-economy model with uncertainty, irreversibility, and active learning. Whereas previous papers assume learning from one observation per period, or experiment with control variables to gain additional information, this paper considers active learning from investment in monitoring, specifically in improved observations of the global mean temperature. We find that the decision maker invests a significant amount of money in climate research, far more than the current level, in order to increase the rate of learning about climate change. This helps the decision maker make improved decisions. The level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations. As the uncertainty about climate change is smaller, active learning reduces the optimal carbon tax. The greater the risk, the larger is the effect of learning. The method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable, for instance, the precision at which we observe GDP, unemployment, or the quality of education

Life Cycle Management of Infrastructures

By definition, life cycle management (LCM) is a framework “of concepts, techniques, and procedures to address environmental, economic, technological, and social aspects of products and organizations in order to achieve continuous ‘sustainable’ improvement from a life cycle perspective” (Hunkeler et al.\ua02001). Thus, LCM theoretically integrates all sustainability dimensions, and strives to provide a holistic perspective. It also assists in the efficient and effective use of constrained natural and financial resources to reduce negative impacts on society (Sonnemann and Leeuw\ua02006; Adibi et al.\ua02015). The LCM of infrastructures is the adaptation of product life cycle management (PLM) as techniques to the design, construction, and management of infrastructures. Infrastructure life cycle management requires accurate and extensive information that might be generated through different kinds of intelligent and connected information workflows, such as building information modeling (BIM)

Chronic pain: a PET study of the central effects of percutaneous high cervical cordotomy

We have studied 5 patients with unilateral, severe chronic pain due to cancer before and after percutaneous, ventrolateral cervical cordotomy to investigate the central effects of the procedure. The aim was to identify the functional anatomical correlates of abolishing unilateral nociceptive input to the brain. Patients were investigated by positron emission tomography using C15O2 to evaluate cerebral blood flow. Comparisons were made between the patients with unilateral pain before cordotomy and normal volunteers. These demonstrated significantly less blood flow in 3 out of 4 of the individual quadrants of the hemithalamus contralateral to the side of pain (P < 0.01-0.05). These differences were abolished by cordotomy. Comparison of the patients before and after cordotomy showed a significant decrease in blood flow in the dorsal anterior quadrant of the thalamus contralateral to the side of pain (P < 0.05) which was normalised after cordotomy. There were no significant changes in the prefrontal or primary somatosensory cortex. We conclude that chronic pain results in a decrease of synaptic activity at thalamic level either from decreased activity in neurones projecting to that region and/or attenuated local neuronal firing. We have demonstrated no secondary remote effects in cortex, indicating the importance of subcortical mechanisms in central responses to chronic pain