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A Power Market Forward Curve with Hydrology Dependence - An Approach based on Artificial Neural Networks

This paper develops an hourly forward curve for power markets where the intra-day and intra-week shapes (profiles) depend on the level of the hydrological balance. The shaping model is based on a feed-forward Artificial Neural Network (ANN), which is trained on a historical data set of hourly electricity spot prices from the Nord Pool market and weekly measurements of the Nordic hydrological balan

Time-domain Green dyadics for temporally dispersive, simple media

Time-domain fundamental solutions and Green dyadics for temporally dispersive, simple media are introduced. Second forerunner approximations to the electromagnetic fields from an electric point dipole in unbounded dispersive materials are obtained. Numerical results for two frequently used material models are presented. Moreover, surface integral representations of the electromagnetic fields in di

Nanowires in Cell Biology

This thesis explores the interactions between cells and nanowires, to increase our understanding of how cells are affected and how they can be manipulated by these one-dimensional, semiconductor crystals (lengths 1-10 µm, diameters