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Mobility researchers acknowledge the multifaceted nature of individuals' trans-portation choices, influenced by personal attitudes, social norms, and transport infrastructure. However, the complexity of these factors often leads to incon-sistent findings in existing methodologies. Given the significant environmental impact of motorized private transportation, understanding the mechanisms of travel mode choice is imperative for fostering sustainable mobility behaviour. This paper introduces t...
Uncertainty quantification is an important task in machine learning - a task in which standard neural networks (NNs) have traditionally not excelled. This can be a limitation for safety-critical applications, where uncertainty-aware methods like Gaussian processes or Bayesian linear regression are often preferred. Bayesian neural networks are an approach to address this limitation. They assume probability distributions for all parameters and yield distributed predictions. However, training an...
Stochastic Model Predictive Control (SMPC) is a promising solution for controlling multivariable systems in the presence of uncertainty. However, a core challenge lies in obtaining a probabilistic system model. Recently, multi-step system identification has been proposed as a solution. Multi-step models simultaneously predict a finite sequence of future states, which traditionally involves recursive evaluation of a state-space model. Particularly in the stochastic context, the recursive evalu...
There are significant advances in GNSS-free cross-modality self-localization of self-driving vehicles. Recent methods focus on learnable features for both cross-modal global localization via place recognition (PR) and local pose tracking, however they lack means of combining them in a complete localization pipeline. That is, a pose retrieved from PR has to be validated if it actually represents the true pose. Performing this validation without GNSS measurements makes the localization problem ...
Mitigating outage regions is of particular interest for emerging millimeter-wave (mmWave) and future sub-terahertz frequency cellular networks. Whereas smart radio environments based on metasurfaces constitute a key concept for 6G research, current networks cannot be served as new control procedures are required. Although small prototypes are already emerging, costs will be higher for the dense deployment of reconfigurable intelligent surfaces (RISs) compared to passive reflectors. It is argu...
The ongoing changes in modern power systems towards increasingly decentralized systems render the coordination of generation assets and the corresponding dependency on Information and Communication Technology highly relevant. This work demonstrates the impact of three types of ICT errors, namely delayed data, data loss and data corruption, on the control of distributed energy resources in an active distribution network. The settling time of the active power response at the interconnection poi...
Nowadays, web applications are ubiquitous. Entire business models revolve around making their services available over the Internet, anytime, anywhere in the world. Due to today’s rapid development practices, software changes are released faster than ever before, creating the risk of losing control over the quality of the delivered products. To counter this, appropriate testing methodologies must be deeply integrated into each phase of the development cycle to identify potential defects as ear...
Aspartic proteases play a crucial role in human physiology and pathologyincluding as biomarkers for breast cancer and Alzheimer's disease, and as potential drug targets for infectious diseases. However, chemical probes for photoaffinity labeling (PAL) of these proteases are underdeveloped. We develop a full on-resin synthesis of clickable PAL probes based on the natural product inhibitor pepstatin, incorporating a minimal diazirine photo-reactive group. The positioning of this group in the i...
Silicon vacancies in silicon carbide (SiC) have been proposed as interesting candidates for quantum technology applications such as quantum sensing and quantum repeaters. SiC exists in many polytypes with different plane stacking sequences, and in each polytype, the vacancies can occupy a variety of different lattice sites. In this work, we focus on the three important charged silicon vacancies in the 6H-SiC polytype. We record the photoluminescence and continuous-wave optically detected magn...
Regarding the experimental observation that microtubule (MT) catastrophe can be described as a multistep process, we extend the Dogterom–Leibler model for dynamic instability in order to discuss the effect that such a multistep catastrophe mechanism has on the distribution of MT lengths in the two regimes of bounded and unbounded growth. We show that in the former case, the steady state length distribution is non-exponential and has a lighter tail if multiple steps are required to undergo a c...
This contribution analyzes the self-perception and political biases of OpenAI’s Large Language Model ChatGPT. Considering the first small-scale reports and studies that have emerged, claiming that ChatGPT is politically biased towards progressive and libertarian points of view, this contribution is aimed at providing further clarity on this subject. Although the concept of political bias and affiliation is hard to define, lacking an agreed-upon measure for its quantification, this contributio...
5-Methylcytosine (5mC) is the central epigenetic mark of mammalian DNA, and plays fundamental roles in chromatin regulation. 5mC is dynamically read and translated into regulatory outputs by methyl-CpG-binding domain (MBD) proteins. These multidomain readers recognize 5mC via an MBD domain, and undergo additional domain-dependent interactions with multiple additional chromatin components. However, studying this dynamic process is limited by a lack of methods to conditionally control the 5mC a...
The magnetic proximity effect provides a promising way to increase the low Curie temperature (TC) of europium monoxide (EuO) toward or even above room temperature, while keeping its stoichiometry and insulating properties. This work studies EuO/Co bilayers using static and time-resolved magneto-optical Kerr effect measurements, and explores the influence of magnetic proximity on TC and on the spin dynamics in EuO. Excitation above the EuO bandgap results in an ultrafast enhancement of the EuO...
Edge Artificial Intelligence is progressively pervading all aspects of our life. However, to perform complex tasks, a massive amount of matrix multiplications needs to be computed. At the same time, the available hardware resources for computation are highly limited. The pressing need for efficiency serves as the motivation for this dissertation. In this dissertation, we propose a vision for highly-resource constrained future intelligent systems that are comprised of robust Binarized Neur...
Many real life applications lead to optimal control problems whose control is given in form of a finite set of switches. These switches can be operated within a given continuous time horizon and admit only a finite number of states. Examples include gear-switches in automotive engineering or valves and compressors in gas networks. Solving optimal control problems with discrete control variables is challenging, and this thesis aims at developing a branch-and-bound algorithm to globally solve s...
In flood risk management awareness has been growing that the responsibility for coping with a flood cannot be assumed by the government alone. Homeowners need to be actively involved in flood risk management by taking responsibility; for this, they need empowerment and support to take adequate precautions. If homeowners implement precautionary measures, they can mitigate damage caused by floods and thus increase their resilience. This requires an appropriate risk communication strategy with t...
Precursor solubility is a crucial factor in industrial applications, dominating the outcome of reactions and purification steps. The outcome and success of thermodynamic modelling of this industrially important property with equations of states, such as Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT), vastly depends on the quality of the pure-component parameters. The pure-component parameters for low-volatile compounds such as ionic liquids (ILs) have been commonly estimated u...
Reservoir computing is a concept involving mapping signals onto a high-dimensional phase space of a dynamical system called “reservoir” for subsequent recognition by an artificial neural network. We implement this concept in a nanodevice consisting of a sandwich of a semiconductor phonon waveguide and a patterned ferromagnetic layer. A pulsed write-laser encodes input signals into propagating phonon wavepackets, interacting with ferromagnetic magnons. The second laser reads the output signal ...
Improving the quantum coherence of solid-state systems is a decisive factor in realizing solid-state quantum technologies. The key to optimize quantum coherence lies in reducing the detrimental influence of noise sources such as spin noise and charge noise. Here we demonstrate that we can utilize highly-excited Rydberg excitons to neutralize charged impurities in the semiconductor Cuprous Oxide - an effect we call purification. Purification reduces detrimental electrical stray fields drastica...
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- 74 Schweizer, Ben
- 74 Ufer, Stefan
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