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Increasing Scots pine (Pinus sylvestris L.) mortality has been recently observed in the dry inner valleys of the European Alps. Besides drought, infection with pine mistletoe (Viscum album ssp. austriacum) seems to play an important role in the mortality dynamics of Scots pines, but how mistletoes promote pine decline remains unclear. To verify whether pine mistletoe infection weakens the host via crown degradation, as observed for dwarf mistletoes, we studied the negative effects of pine mistletoe infestation on the photosynthetic tissues and branch growth of pairs of infested and non-infested branches. Pine mistletoe infection leads to crown degradation in its host by reducing the length, the radial increment, the ramification, the needle length and the number of needle years of the infested branches. This massive loss in photosynthetic tissue results in a reduction in primary production and a subsequent decrease in carbohydrate availability. The significant reduction in needle length due to mistletoe infection is an indication for a lower water and nutrient availability in infested branches. Thus, mistletoe infection might lead to a decrease in the availability of water and carbohydrates, the two most important growth factors, which are already shortened due to the chronic drought situation in the area. Therefore, pine mistletoe increases the risk of drought-induced mortality of its host when growing in a xeric environment.
Chain scattering parameters or T-parameters are a useful tool for calculating cascaded two-ports. With the increasing importance of mixed-mode S-parameters, a need for converting the T-parameters from their unbalanced form into a balanced form emerges for suiting both common and differential mode waves, as well as the mode conversion. This paper presents the derivation of the equations for transformations between mixed-mode S- and T-parameters for a mixed-mode two-port. Although derived in a way very similar to monomode T-parameters, no simplifications were necessary. Measurement results exemplify the quality of the T-parameter transformation under real-life conditions.
Due to the Renewable Energy Act, in Germany it is planned to increase the amount of renewable energy carriers up to 60%. One of the main problems is the fluctuating supply of wind and solar energy. Here biogas plants provide a solution, because a demand-driven supply is possible. Before running such a plant, it is necessary to simulate and optimize the process. This paper provides a new model of a biogas plant, which is as accurate as the standard ADM1 model. The advantage compared to ADM1 is that it is based on only four parameters compared to 28. Applying this model, an optimization was installed, which allows a demand-driven supply by biogas plants. Finally the results are confirmed by several experiments and measurements with a real test plant.