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In this paper we study the problem of estimating receiver and sender positions using time-difference-of-arrival measurements. For this, we use a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. We present new, efficient solvers for the minimal problems of this low-rank problem. These solvers are used in a hypothesis and test manne
The focus on recovery within psychiatric care is increasing, where peer support may play a pivotal role. Previous research shows both mixed and promising results in terms of beneficial outcomes for patients and peer support workers (PSW). The study’s aim was to investigate PSW’ experiences of their professional role and associated relationships with healthcare staff and patients. Semi-structured i
Dopamine (DA) neurons of the midbrain are at risk to become affected by mitochondrial damage over time and mitochondrial defects have been frequently reported in Parkinson's disease (PD) patients. However, the causal contribution of adult-onset mitochondrial dysfunction to PD remains uncertain. Here, we developed a mouse model lacking Mitofusin 2 (MFN2), a key regulator of mitochondrial network ho
Large intelligent surface (LIS) is a technology that extends massive MIMO by considering an even greater number of antennas distributed throughout vast areas. In order to be able to implement this technology, it is crucial to consider decentralized architectures so as to make the whole system scalable. We consider a LIS divided into several LIS panels of smaller size, which can be located far away
This piece is influenced by the Bénard instability, a puzzle of stability that occurs far from equilibrium. Regarded as a classic case of self-organization, Henri Bénard discovered that heating a thin layer of fluid may result in strangely ordered forms. When a liquid is uniformly heated from below, a constant circuit is set into motion moving from bottom to top. When the temperature difference be
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The Transformer architecture has been successful across many domains, including natural language processing, computer vision and speech recognition. In keyword spotting, self-attention has primarily been used on top of convolutional or recurrent encoders. We investigate a range of ways to adapt the Transformer architecture to keyword spotting and introduce the Keyword Transformer (KWT), a fully se
