The recently developed technique of Cyclotron Radiation Emission Spectroscopy (CRES) uses frequency information from the cyclotron motion of an electron in a magnetic bottle to infer its kinetic energy. Here we derive the expected radio frequency signal from an electron in a waveguide CRES apparatus from first principles. We demonstrate that the frequency-domain signal is rich in information about the electron's kinematic parameters, and extract a set of measurables that in a suitably designed system are sufficient for disentangling the electron's kinetic energy from the rest of its kinematic features. This lays the groundwork for high-resolution energy measurements in future CRES experiments, such as the Project 8 neutrino mass measurement.

After the spinal cord injury, inflammation and cytotoxicity cause further damage to neural cells. The progression of this secondary injury might be reduced by the administration of anti-inflammatory drugs. To allow the local delivery of such drugs while minimizing dural opening, we have created a polypyrrole (PPy)-coated microneedle array using a microscale three-dimensional (3D) printing technology that facilitates electronically controlled encapsulation and the transdural release of drugs. PPy microneedles demonstrated an electronically controlled release of steroid dexamethasone (Dexa) in a novel in vitro transdural model and in vivo. The biological activity of the device was then tested by the electronic release of Dexa into an in vitro model of neuroinflammation, using activated microglia. Following electrically activated Dexa release, inflammation was reduced, as demonstrated by a decrease in nitric oxide and proinflammatory cytokines Il-6 and MCP-1. These results demonstrate the feasibility of PPy-coated microneedles for the transdural delivery of anti-inflammatory drugs to the central nervous system.

Industry 4.0 tries to digitalize the production process further. The digitalization is achieved by connecting different entities (machines, worker) to data-exchange, which needs to be dynamic and to adapt to different changing situations and members in the process. However, just exchanging data might lead to confidentiality issues. The data-exchange needs to be protected to secure the confidentiality and trust in the system. Therefore, security rules need to adapt to these dynamic situations. One part of a possible solution might be dynamic access control rules. However in many cases, existing "legacy" systems are reused, which can in not handle dynamic access control rules. Due to this gap between the required and provided functionality, we propose an approach, which integrates dynamic access control based on the system-context into legacy systems. Our approach uses a security adaption controller, which dynamically adapts the access control rules to a new situation and integrates them into an existing legacy system. We discussed our approach with industrial practitioners and related our approach to their existing legacy system. In addition, we performed a scalability analysis to demonstrate the applicability of our approach in a realistic environment. CCS CONCEPTS• Security and privacy → Domain-specific security and privacy architectures; • Computer systems organization → Self-organizing autonomic computing.

The Locust simulation package is a new C++ software tool developed to simulate the measurement of time-varying electromagnetic fields using RF detection techniques. Modularity and flexibility allow for arbitrary input signals, while concurrently supporting tight integration with physics-based simulations as input. External signals driven by the Kassiopeia particle tracking package are discussed, demonstrating conditional feedback between Locust and Kassiopeia during software execution. An application of the simulation to the Project8 experiment is described. Locust is publicly available at https://github.com/project8/locust_mc.

Due to their close relation to physical and virtual entities (humans, machines, processes, etc.) including their changing state and context, modern cyber-physical and IoT systems exhibit a high degree of architectural dynamicity. While sharing of data among all the entities of the system is the key driver to the efficiency of the system, it is at the same time necessary to effectively control which data are shared, with whom, and in which context so as to prevent potential misuse. The problem however is that traditional methods to security and privacy, which typically rely on rigid hierarchies, cannot easily cope with the high degree of architectural dynamicity. In this paper, we outline an approach to ensure security and privacy on the architectural level in systems with dynamic architectures.In particular, we focus on a) data tracking using data flows and data processing described in system architectures, b) descriptions of dynamic sharing scenarios including decision derivation based on the current situation, and c) a runtime analysis platform that regulates data exchange. We ground the approach and illustrate it in the Industry 4.0 setting, as this is the domain in which we apply our approach as part of our project Trust 4.0, but we believe it can be used in other applications domains as well. CCS CONCEPTS• Applied computing → Supply chain management; • Security and privacy → Domain-specific security and privacy architectures;