Recent advances in animal tracking technology have ushered in a new era in biologging. However, the considerable size of many sophisticated biologging devices restricts their application to larger animals, whereas older techniques often still represent the state-of-theart for studying small vertebrates. In industrial applications, low-power wireless sensor networks (WSNs) fulfill requirements similar to those needed to monitor animal behavior at high resolution and at low tag mass. We developed a wireless biologging network (WBN), which enables simultaneous direct proximity sensing, high-resolution tracking, and long-range remote data download at tag masses of 1 to 2 g. Deployments to study wild bats created social networks and flight trajectories of unprecedented quality. Our developments highlight the vast capabilities of WBNs and their potential to close an important gap in biologging: fully automated tracking and proximity sensing of small animals, even in closed habitats, at high spatial and temporal resolution.

In the current study, the potential of dry machining of the titanium alloy Ti-6Al-4V with uncoated tungsten carbide solid endmills was explored. It is demonstrated that tribo-oxidation is the dominant wear mechanism, which can be suppressed by milling in an extreme high vacuum adequate (XHV) environment. The latter was realized by using a silane-doped argon atmosphere. In the XHV environment, titanium adhesion on the tool was substantially less pronounced as compared to reference machining experiments conducted in air. This goes hand in hand with lower cutting forces in the XHV environment and corresponding changes in chip formation. The underlying mechanisms and the ramifications with respect to application of this approach to dry machining of other metals are discussed.

In this paper, the BATS project is presented, which aims to track the behavior of bats via an ultra-low power wireless sensor network. An overview about the whole project and its parts like sensor node design, tracking grid and software infrastructure is given and the evaluation of the project is shown. The BATS project includes a lightweight sensor node that is attached to bats and combines multiple features. Communication among sensor nodes allows tracking of bat encounters. Flight trajectories of individual tagged bats can be recorded at high spatial and temporal resolution by a ground node grid. To increase the communication range, the BATS project implemented a long-range telemetry system to still receive sensor data outside the standard ground node network. The whole system is designed with the common goal of ultra-low energy consumption while still maintaining optimal measurement results. To this end, the system is designed in a flexible way and is able to adapt its functionality according to the current situation. In this way, it uses the energy available on the sensor node as efficient as possible.

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The production of massive steel-aluminium hybrid components by means of massive (hot) forming following a joining operation requires advanced heat treatment strategies for the adjustment of local material properties with maximum joint strengths. For the given process-step sequence, the challenge is that the heat treatment of the hybrid component can only take place in the joined state and after (hot) forming. Consequently, suitable heat treatment strategies must enable both a T6 heat treatment of the aluminium component and a surface hardening of the steel component. It could be shown that the inductive surface hardening of a steel functional surface in the immediate vicinity of the aluminium component can take place without reducing the bond strength. To achieve the desired hardening result, the use of a field former is required. The bond strength could be increased by up to 20% compared to the friction-welded initial conditions by adjusting the parameters of the T6 heat treatment.

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Many interesting applications of continuous-query processing are concerned with pattern matching or complex temporal aggregation of events. Real-world queries that rely on these operations are difficult to implement in current streamprocessing systems. The reason seems to be a gap between two types of existing query languages: Some languages (e. g. CQL) offer a small set of simple operators that can be combined in order to create complex queries. While these languages provide sound and comprehensible semantics, they lack the expressiveness required for many real-world applications. Other approaches (e. g. Aurora) provide powerful operators but lack semantic strictness, which is required for reasoning about query results. Such reasoning is a prerequisite for safe query optimization.We try to bridge this gap by integrating operators for pattern matching and time-aware aggregates into a generalpurpose stream model featuring stream partitioning. These operators can answer several questions that we have found to be relevant in a real-world object-tracking scenario. Moreover, they are formally defined, allowing expressive and efficient queries to be written in CQL-like languages, while remaining understandable and easy to use.

By using electrically assisted forming the usually rather poor workability of magnesium can be improved. The processes taking place during these forming operations have a strong influence on the microstructure. However, the metallographic preparation of magnesium is challenging due to its low hardness and strong tendency to oxidize. Therefore, a reliable preparation method was developed that revealed the microstructural features caused by the electrically assisted forming. The different morphologies of twins caused by plastic deformation and of those caused by an electric impulse could clearly be distinguished.