Open Access

Anhand der Ergebnisse einer Längsschnittstudie mit Schlaganfallbetroffenen und ihren Angehörigen wird untersucht, welche Faktoren Einfluss auf die Akzeptanz und die Nutzungsbereitschaft von Telepräsenzrobotik ausüben.

The use of quantum processing units (QPUs) promises speed-ups for solving computational problems, in particular for discrete optimisation. While a few groundbreaking algorithmic approaches are known that can provably outperform classical computers, we observe a scarcity of programming abstractions for constructing efficient quantum algorithms. A good fraction of the literature that addresses solving concrete problems related to database management concentrates on casting them as quadratic unconstrained binary optimisation problems (QUBOs), which can then, among others, be processed on gate-based machines (using the quantum approximate optimisation algorithm), or quantum annealers. A critical aspect that affects efficiency and scalability of either of these approaches is how classical data are loaded into qubits, respectively how problems are encoded into QUBO representation. The effectiveness of encodings is known to be of crucial importance for quantum computers, especially since the amount of available qubits is strongly limited in the era of noisy, intermediate-size quantum computers. In this paper, we present three encoding patterns, discuss their impact on scalability, and their ease of use. We consider the recreational (yet computationally challenging) Sudoku problem and its reduction to graph colouring as an illustrative example to discuss their individual benefits and disadvantages. Our aim is enable database researchers to choose an appropriate encoding scheme for their purpose without having to acquire in-depth knowledge on quantum peculiarities, thus easing the path towards applying quantum acceleration on data management systems.

Federated online social networks are an alternative to centralized and often profit-driven social networks. Instead of providing exactly one main platform, federated and decentralized approaches consist of multiple platforms, nodes or instances, leading to new challenges for guaranteeing confidentiality, integrity and availability. In addition, privacy is taken into close consideration due to the sensitive nature of processed personal data and the purpose of online social networks as well as the user behavior on social media. The recent popularity and broad use of the federated micro-blogging platform Mastodon issues the matter of security and privacy challenges for this type of architecture and the specific platform as well. Mastodon is part of a larger network called Fediverse with several platforms with different purposes. Communication and interoperability between Fediverse platforms is mostly achieved by ActivityPub protocol as standard for decentralized social networking, defined by W3C. We analyze Mastodon as the currently most prominent and largest example of a Fediverse platform. Therefore, we perform tests for typical types of software vulnerabilities as well as evaluate common security challenges built into its design. As a result, we identify trust as security principle as critical issue, leading to multiple weak points such as enabling attackers and malicious actors to spread misleading information as well as network availability impacts. We suggest possible solutions customized to our findings as well as general security recommendations when building a federated online social network such as the Fediverse