Recent Submissions
Interagieren mit der Spiegelwelt
(2024) Avdic, Seval; Özver, Muhammed Enes
Diese Bachelorarbeit beschreibt die Entwicklung und Evaluation eines Prototyps für einen Smart Mirror, der drei verschiedene Interaktionsmethoden untersucht: Touch-, Spiegelbild- und Holografie-Interaktion. Die Touch-Interaktion nutzt den Ultraleap-Handtracker und das TouchFree-Plugin, um direkte Berührungen der Benutzeroberfläche zu ermöglichen. Die Spiegelbild-Interaktion verwendet ebenfalls den Ultraleap-Handtracker, jedoch wird die Interaktionsebene so verschoben, dass der Benutzer mit dem Spiegelbild interagiert, unterstützt durch visuelles Feedback in Form eines Schattens. Die Holografieinteraktion wird durch die Microsoft HoloLens 2 realisiert, wobei die Benutzeroberfläche holografisch vor dem Spiegel erscheint, während der Spiegel selbst nicht-interaktive Elemente darstellt.
Die Evaluation mit zwölf Teilnehmern zeigte, dass die Touch- und Spiegelbild-Interaktionen bezüglich Benutzerfreundlichkeit, Präzision und Eingabeerkennung bessere Ergebnisse erzielten als die Holografieinteraktion. Insbesondere die Touchinteraktion wurde als intuitiv empfunden, während die Spiegelbildinteraktion aufgrund der berührungslosen Handhabung als hygienisch und alltagstauglich bewertet wurde. Die Holografieinteraktion wies Herausforderungen hinsichtlich der räumlichen Tiefe und Synchronisation auf und wurde von den Teilnehmern als weniger präzise empfunden.
Die Studie identifizierte außerdem Limitierungen des Prototyps, darunter die Genauigkeit des Handtrackings und die ergonomische Belastung bei längerer Nutzung. Für die zukünftige Forschung wird eine Verbesserung der Hand- und Fingererkennung und die Entwicklung ergonomischerer Bedienmethoden vorgeschlagen. Zudem wäre eine größere Studie mit einer umfangreicheren Stichprobe wünschenswert, um die Ergebnisse zu validieren.
Quantum-assisted distortion-free audio signal sensing
(2022) Zhang, Chen; Dasari, Durga; Widmann, Matthias; Meinel, Jonas; Vorobyov, Vadim; Kapitanova, Polina; Nenasheva, Elizaveta; Nakamura, Kazuo; Sumiya, Hitoshi; Onoda, Shinobu; Isoya, Junichi; Wrachtrup, Jörg
Quantum sensors are known for their high sensitivity in sensing applications. However, this sensitivity often comes with severe restrictions on other parameters which are also important. Examples are that in measurements of arbitrary signals, limitation in linear dynamic range could introduce distortions in magnitude and phase of the signal. High frequency resolution is another important feature for reconstructing unknown signals. Here, we demonstrate a distortion-free quantum sensing protocol that combines a quantum phase-sensitive detection with heterodyne readout. We present theoretical and experimental investigations using nitrogen-vacancy centers in diamond, showing the capability of reconstructing audio frequency signals with an extended linear dynamic range and high frequency resolution. Melody and speech based signals are used for demonstrating the features. The methods could broaden the horizon for quantum sensors towards applications, e.g. telecommunication in challenging environment, where low-distortion measurements are required at multiple frequency bands within a limited volume.
Quantum nonlinear spectroscopy of single nuclear spins
(2022) Meinel, Jonas; Vorobyov, Vadim; Wang, Ping; Yavkin, Boris; Pfender, Mathias; Sumiya, Hitoshi; Onoda, Shinobu; Isoya, Junichi; Liu, Ren-Bao; Wrachtrup, Jörg
Conventional nonlinear spectroscopy, which use classical probes, can only access a limited set of correlations in a quantum system. Here we demonstrate that quantum nonlinear spectroscopy, in which a quantum sensor and a quantum object are first entangled and the sensor is measured along a chosen basis, can extract arbitrary types and orders of correlations in a quantum system. We measured fourth-order correlations of single nuclear spins that cannot be measured in conventional nonlinear spectroscopy, using sequential weak measurement via a nitrogen-vacancy center in diamond. The quantum nonlinear spectroscopy provides fingerprint features to identify different types of objects, such as Gaussian noises, random-phased AC fields, and quantum spins, which would be indistinguishable in second-order correlations. This work constitutes an initial step toward the application of higher-order correlations to quantum sensing, to examining the quantum foundation (by, e.g., higher-order Leggett-Garg inequality), and to studying quantum many-body physics.
Printed temperature sensor array for high-resolution thermal mapping
(2022) Bücher, Tim; Huber, Robert; Eschenbaum, Carsten; Mertens, Adrian; Lemmer, Uli; Amrouch, Hussam
Fully-printed temperature sensor arrays - based on a flexible substrate and featuring a high spatial-temperature resolution - are immensely advantageous across a host of disciplines. These range from healthcare, quality and environmental monitoring to emerging technologies, such as artificial skins in soft robotics. Other noteworthy applications extend to the fields of power electronics and microelectronics, particularly thermal management for multi-core processor chips. However, the scope of temperature sensors is currently hindered by costly and complex manufacturing processes. Meanwhile, printed versions are rife with challenges pertaining to array size and sensor density. In this paper, we present a passive matrix sensor design consisting of two separate silver electrodes that sandwich one layer of sensing material, composed of poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS). This results in appreciably high sensor densities of 100 sensor pixels per cm 2for spatial-temperature readings, while a small array size is maintained. Thus, a major impediment to the expansive application of these sensors is efficiently resolved. To realize fast and accurate interpretation of the sensor data, a neural network (NN) is trained and employed for temperature predictions. This successfully accounts for potential crosstalk between adjacent sensors. The spatial-temperature resolution is investigated with a specially-printed silver micro-heater structure. Ultimately, a fairly high spatial temperature prediction accuracy of 1.22 °C is attained.
Development of a software framework for the generation of data sets with PFLOTRAN
(2025) Hausch, Max
This thesis presents the development of a software framework, VampireMan, designed to automate the generation of diverse and reproducible data sets for training surrogate machine learning models in groundwater flow simulations with heat pumps. Groundwater flow and heat transport simulations are important tools for applications like geothermal energy systems, requiring extensive high-quality data sets for accurate predictive modeling. Surrogate machine learning models have emerged as efficient alternatives to computationally expensive numerical simulations, enabling rapid predictions of subsurface temperature fields. The success of these models relies on the availability of diverse and reliable data sets, encompassing variations in physical and operational parameters. However, manual and semi-automated data set creation approaches are limited in scalability and prone to errors.
VampireMan addresses this challenge by automating the entire data generation workflow: systematically varying simulation parameters, generating simulation input files, running simulations with PFLOTRAN, and visualizing outputs. The framework adheres to Research Software Engineering (RSE) and FAIR4RS (Findable, Accessible, Interoperable, and Reusable for Research Software) principles, ensuring reproducibility, scalability, and extensibility.
Key features include reproducible data set generation using different parameter variation modes (fixed, constant, and spatial), modular pipeline stages, and integration with PFLOTRAN. VampireMan's effectiveness is demonstrated through preconfigured examples that showcase parameter variations and simulation workflows. By enabling efficient and reproducibility data set generation, VampireMan can help advancing machine learning applications in environmental engineering, facilitating resource-efficient and real-time decision-making for subsurface energy systems.
Sustainability assessments of energy scenarios : citizens’ preferences for and assessments of sustainability indicators
(2022) Schmidt-Scheele, Ricarda; Hauser, Wolfgang; Scheel, Oliver; Minn, Fabienne; Becker, Lisa; Buchgeister, Jens; Hottenroth, Heidi; Junne, Tobias; Lehr, Ulrike; Naegler, Tobias; Simon, Sonja; Sutardhio, Claudia; Tietze, Ingela; Ulrich, Philip; Viere, Tobias; Weidlich, Anke
Background: Given the multitude of scenarios on the future of our energy systems, multi-criteria assessments are increasingly called for to analyze and assess desired and undesired effects of possible pathways with regard to their environmental, economic and social sustainability. Existing studies apply elaborate lists of sustainability indicators, yet these indicators are defined and selected by experts and the relative importance of each indicator for the overall sustainability assessments is either determined by experts or is computed using mathematical functions. Target group-specific empirical data regarding citizens’ preferences for sustainability indicators as well as their reasoning behind their choices are not included in existing assessments.
Approach and results: We argue that citizens’ preferences and values need to be more systematically analyzed. Next to valid and reliable data regarding diverse sets of indicators, reflections and deliberations are needed regarding what different societal actors, including citizens, consider as justified and legitimate interventions in nature and society, and what considerations they include in their own assessments. For this purpose, we present results from a discrete choice experiment. The method originated in marketing and is currently becoming a popular means to systematically analyze individuals’ preference structures for energy technology assessments. As we show in our paper, it can be fruitfully applied to study citizens’ values and weightings with regard to sustainability issues. Additionally, we present findings from six focus groups that unveil the reasons behind citizens’ preferences and choices.
Conclusions: Our combined empirical methods provide main insights with strong implications for the future development and assessment of energy pathways: while environmental and climate-related effects significantly influenced citizens’ preferences for or against certain energy pathways, total systems and production costs were of far less importance to citizens than the public discourse suggests. Many scenario studies seek to optimize pathways according to total systems costs. In contrast, our findings show that the role of fairness and distributional justice in transition processes featured as a dominant theme for citizens. This adds central dimensions for future multi-criteria assessments that, so far, have been neglected by current energy systems models.
Approach and results: We argue that citizens’ preferences and values need to be more systematically analyzed. Next to valid and reliable data regarding diverse sets of indicators, reflections and deliberations are needed regarding what different societal actors, including citizens, consider as justified and legitimate interventions in nature and society, and what considerations they include in their own assessments. For this purpose, we present results from a discrete choice experiment. The method originated in marketing and is currently becoming a popular means to systematically analyze individuals’ preference structures for energy technology assessments. As we show in our paper, it can be fruitfully applied to study citizens’ values and weightings with regard to sustainability issues. Additionally, we present findings from six focus groups that unveil the reasons behind citizens’ preferences and choices.
Conclusions: Our combined empirical methods provide main insights with strong implications for the future development and assessment of energy pathways: while environmental and climate-related effects significantly influenced citizens’ preferences for or against certain energy pathways, total systems and production costs were of far less importance to citizens than the public discourse suggests. Many scenario studies seek to optimize pathways according to total systems costs. In contrast, our findings show that the role of fairness and distributional justice in transition processes featured as a dominant theme for citizens. This adds central dimensions for future multi-criteria assessments that, so far, have been neglected by current energy systems models.
Analysis of different preconditioners for kernel matrices based on the PLSSVM library using SYCL
(2025) Horstmann, Jonas
PLSSVM is a library that enables the efficient training and execution of Support Vector Machines, which can be used to classify data. It does so by utilizing various high performance computing frameworks to construct and solve a system of linear equations. The conjugate gradient algorithm is used to iteratively solve this linear system. Large datasets with many features, resulting in ill-conditioned kernel matrices have a negative impact on the convergence of the CG method.
To remedy this problem, the goal of this thesis is to analyze different preconditioners in the context of the preconditioned conjugate gradient algorithm, in order to reduce the condition number of the linear system, leading to better convergence and higher stability in regards to different hyperparameter sets.
To achieve this goal three different preconditioners were implemented with SYCL and tested, showing that the usage of a preconditioners can indeed help to improve the mentioned aspects, resulting in fewer iterations (up to 78%) to converge and enabling the usage of hyperparameter combinations that were not possible before.
Mechanistic basis of the increased methylation activity of the SETD2 protein lysine methyltransferase towards a designed super-substrate peptide
(2022) Schnee, Philipp; Choudalakis, Michel; Weirich, Sara; Khella, Mina S.; Carvalho, Henrique; Pleiss, Jürgen; Jeltsch, Albert
Protein lysine methyltransferases have important regulatory functions in cells, but mechanisms determining their activity and specificity are incompletely understood. Naturally, SETD2 introduces H3K36me3, but previously an artificial super-substrate (ssK36) was identified, which is methylated >100-fold faster. The ssK36-SETD2 complex structure cannot fully explain this effect. We applied molecular dynamics (MD) simulations and biochemical experiments to unravel the mechanistic basis of the increased methylation of ssK36, considering peptide conformations in solution, association of peptide and enzyme, and formation of transition-state (TS) like conformations of the enzyme-peptide complex. We observed in MD and FRET experiments that ssK36 adopts a hairpin conformation in solution with V35 and K36 placed in the loop. The hairpin conformation has easier access into the active site of SETD2 and it unfolds during the association process. Peptide methylation experiments revealed that introducing a stable hairpin conformation in the H3K36 peptide increased its methylation by SETD2. In MD simulations of enzyme-peptide complexes, the ssK36 peptide approached TS-like structures more frequently than H3K36 and distinct, substrate-specific TS-like structures were observed. Hairpin association, hairpin unfolding during association, and substrate-specific catalytically competent conformations may also be relevant for other PKMTs and hairpins could represent a promising starting point for SETD2 inhibitor development.
AR driving assistant for wheelchairs
(2024) Halach, Tim
Wheelchairs are an important mobility aid for many people, but our built environment presents them with many challenges. To help those people better navigate our cities, we explore the viability of an informational driving assistant for wheelchairs. Driving assistants have already become commonplace in cars to help drivers control their cars. In this thesis, we present a prototype of a driving assistant for wheelchairs and evaluate it in a user study. To find what information the driving assistant should show to its users, we performed a requirements analysis on what information wheelchair and other mobility aid users might need from such a system and based our prototype on those findings. The results of our user study are inconclusive, because we had too few participants, but the concept itself seems promising.
Position-dependent effects of RNA-binding proteins in the context of co-transcriptional splicing
(2023) Horn, Timur; Gosliga, Alison; Li, Congxin; Enculescu, Mihaela; Legewie, Stefan
Alternative splicing is an important step in eukaryotic mRNA pre-processing which increases the complexity of gene expression programs, but is frequently altered in disease. Previous work on the regulation of alternative splicing has demonstrated that splicing is controlled by RNA-binding proteins (RBPs) and by epigenetic DNA/histone modifications which affect splicing by changing the speed of polymerase-mediated pre-mRNA transcription. The interplay of these different layers of splicing regulation is poorly understood. In this paper, we derived mathematical models describing how splicing decisions in a three-exon gene are made by combinatorial spliceosome binding to splice sites during ongoing transcription. We additionally take into account the effect of a regulatory RBP and find that the RBP binding position within the sequence is a key determinant of how RNA polymerase velocity affects splicing. Based on these results, we explain paradoxical observations in the experimental literature and further derive rules explaining why the same RBP can act as inhibitor or activator of cassette exon inclusion depending on its binding position. Finally, we derive a stochastic description of co-transcriptional splicing regulation at the single-cell level and show that splicing outcomes show little noise and follow a binomial distribution despite complex regulation by a multitude of factors. Taken together, our simulations demonstrate the robustness of splicing outcomes and reveal that quantitative insights into kinetic competition of co-transcriptional events are required to fully understand this important mechanism of gene expression diversity.