We report transmission of tick-borne encephalitis virus (TBEV) in July 2008 through nonpasteurized goat milk to 6 humans and 4 domestic pigs in an alpine pasture 1,500 m above sea level. This outbreak indicates the emergence of ticks and TBEV at increasing altitudes in central Europe and the efficiency of oral transmission of TBEV.

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Intelligent IoT functions for increased availability, productivity and component quality offer significant added value to the industry. Unfortunately, many old machines and systems are characterized by insufficient, inconsistent IoT connectivity and heterogeneous parameter naming. Furthermore, the data is only available in unstructured form. In the following, a new approach for standardizing information models from existing plants with machine learning methods is described and an offline-online pattern recognition system for enabling anomaly detection under varying machine conditions is introduced. The system can enable the local calculation of signal thresholds that allow more granular anomaly detection than using only single indexing and aims to improve the detection of anomalous machine behaviour especially in finish machining.