Refine
Departments, institutes and facilities
- Graduierteninstitut (51)
- Fachbereich Informatik (20)
- Fachbereich Angewandte Naturwissenschaften (18)
- Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE) (5)
- Institut für Verbraucherinformatik (IVI) (5)
- Fachbereich Wirtschaftswissenschaften (4)
- Institut für Cyber Security & Privacy (ICSP) (4)
- Institute of Visual Computing (IVC) (4)
- Institut für Sicherheitsforschung (ISF) (3)
- Internationales Zentrum für Nachhaltige Entwicklung (IZNE) (2)
Document Type
- Doctoral Thesis (64) (remove)
Year of publication
Language
- English (64) (remove)
Has Fulltext
- no (64)
Keywords
- Robotics (3)
- Antioxidans (2)
- Evolutionary optimization (2)
- Human-Computer Interaction (2)
- Nachhaltigkeit (2)
- Quality diversity (2)
- Softwareentwicklung (2)
- Sustainability (2)
- Virtual Reality (2)
- API Gebrauchstauglichkeit (1)
During space missions astronauts suffer from cardiovascular deconditioning, when they are exposed to microgravity conditions. Until now, no specific drugs are available for effective countermeasures, since the underlying mechanism is not completely understood. Endothelial cells (ECs) and smooth muscle cells (SMCs) play crucial roles in a variety of cardiovascular functions, many of which are regulated via P2 receptors. However, their function in ECs and SMCs under microgravity condition is still unknown. In this study, ECs and SMCs were isolated from bovine aorta and differentiated from human mesenchymal stem cells (hMSCs), respectively. Subsequently, the cells were verified based on specific markers. An altered P2 receptor expression pattern was detected during the commitment of hMSC towards ECs and SMCs. The administration of natural and artificial P2 receptor agonists and antagonists directly affected the differentiation process. By using EC growth medium as conditioned medium, a vessel cell model was created to culture SMCs and vice versa. Within this study, we were able to show for the first time that the expression of some P2 receptors were altered in ECs and SMCs grown for 24h under simulated microgravity conditions. On the other hand, in some P2 receptor expressions such as P2X7 conditioned medium compensated this change.
In conclusion, our data show that P2 receptors play an important functional role in hMSC differentiation towards ECs and SMCs. Since some P2 receptor artificial ligands are already used as drugs for patients with cardiovascular diseases, it is reasonable to assume that in the future they might be promising candidates for treating cardiovascular deconditioning.
Risikobasierte Authentifizierung (RBA) ist ein adaptiver Ansatz zur Stärkung der Passwortauthentifizierung. Er überwacht eine Reihe von Merkmalen, die sich auf das Loginverhalten während der Passworteingabe beziehen. Wenn sich die beobachteten Merkmalswerte signifikant von denen früherer Logins unterscheiden, fordert RBA zusätzliche Identitätsnachweise an. Regierungsbehörden und ein Erlass des US-Präsidenten empfehlen RBA, um Onlineaccounts vor Angriffen mit gestohlenen Passwörtern zu schützen. Trotz dieser Tatsachen litt RBA unter einem Mangel an offenem Wissen. Es gab nur wenige bis keine Untersuchungen über die Usability, Sicherheit und Privatsphäre von RBA. Das Verständnis dieser Aspekte ist jedoch wichtig für eine breite Akzeptanz.
Diese Arbeit soll ein umfassendes Verständnis von RBA mit einer Reihe von Studien vermitteln. Die Ergebnisse ermöglichen es, datenschutzfreundliche RBA-Lösungen zu schaffen, die die Authentifizierung stärken bei gleichzeitig hoher Menschenakzeptanz.
Computer graphics research strives to synthesize images of a high visual realism that are indistinguishable from real visual experiences. While modern image synthesis approaches enable to create digital images of astonishing complexity and beauty, processing resources remain a limiting factor. Here, rendering efficiency is a central challenge involving a trade-off between visual fidelity and interactivity. For that reason, there is still a fundamental difference between the perception of the physical world and computer-generated imagery. At the same time, advances in display technologies drive the development of novel display devices. The dynamic range, the pixel densities, and refresh rates are constantly increasing. Display systems enable a larger visual field to be addressed by covering a wider field-of-view, due to either their size or in the form of head-mounted devices. Currently, research prototypes are ranging from stereo and multi-view systems, head-mounted devices with adaptable lenses, up to retinal projection, and lightfield/holographic displays. Computer graphics has to keep step with, as driving these devices presents us with immense challenges, most of which are currently unsolved. Fortunately, the human visual system has certain limitations, which means that providing the highest possible visual quality is not always necessary. Visual input passes through the eye’s optics, is filtered, and is processed at higher level structures in the brain. Knowledge of these processes helps to design novel rendering approaches that allow the creation of images at a higher quality and within a reduced time-frame. This thesis presents the state-of-the-art research and models that exploit the limitations of perception in order to increase visual quality but also to reduce workload alike - a concept we call perception-driven rendering. This research results in several practical rendering approaches that allow some of the fundamental challenges of computer graphics to be tackled. By using different tracking hardware, display systems, and head-mounted devices, we show the potential of each of the presented systems. The capturing of specific processes of the human visual system can be improved by combining multiple measurements using machine learning techniques. Different sampling, filtering, and reconstruction techniques aid the visual quality of the synthesized images. An in-depth evaluation of the presented systems including benchmarks, comparative examination with image metrics as well as user studies and experiments demonstrated that the methods introduced are visually superior or on the same qualitative level as ground truth, whilst having a significantly reduced computational complexity.
Daryoush Daniel Vaziri illustrates that the use of mixed methods designs may support the induction of more subtle and complete theories about older adults’ use of technologies for the support of active and healthy aging. The results show that older adults’ social contexts and environments considerably affect their perspectives, practices and attitudes with respect to health, quality of life, well-being and technology use for active and healthy aging support. Results were collected with older adults aged 60+ as well as relevant secondary stakeholders like caregivers, policy makers or health insurance companies.
The processing of employee personal data is dramatically increasing. To protect employees' fundamental right to privacy, the law provides for the implementation of privacy controls, including transparency and intervention. At present, however, the stakeholders responsible for putting these obligations into action, such as employers and software engineers, simply lack the fundamental knowledge needed to design and implement the necessary controls. Indeed, privacy research has so far focused mainly on consumer relations in the private context. In contrast, privacy in the employment context is less well studied. However, since privacy is highly context-dependent, existing knowledge and privacy controls from other contexts cannot simply be adopted to the employment context. In particular, privacy in employment is subject to different legal and social norms, which require a different conceptualization of the right to privacy than is usual in other contexts. To adequately address these aspects, there is broad consensus that privacy must be regarded as a socio-technical concept in which human factors must be considered alongside technical-legal factors. Today, however, there is a particular lack of knowledge about human factors in employee privacy. Disregarding the needs and concerns of individuals or lack of usability, though, are common reasons for the failure of privacy and security measures in practice. This dissertation addresses key knowledge gaps on human factors in employee privacy by presenting the results of a total of three in-depth studies with employees in Germany. The results provide insights into employees' perceptions of the right to privacy, as well as their perceptions and expectations regarding the processing of employee personal data. The insights gained provide a foundation for the human-centered design and implementation of employee-centric privacy controls, i.e., privacy controls that incorporate the views, expectations, and capabilities of employees. Specifically, this dissertation presents the first mental models of employees on the right to informational self-determination, the German equivalent of the right to privacy. The results provide insights into employees' (1) perceptions of categories of data, (2) familiarity and expectations of the right to privacy, and (3) perceptions of data processing, data flow, safeguards, and threat models. In addition, three major types of mental models are presented, each with a different conceptualization of the right to privacy and a different desire for control. Moreover, this dissertation provides multiple insights into employees' perceptions of data sensitivity and willingness to disclose personal data in employment. Specifically, it highlights the uniqueness of the employment context compared to other contexts and breaks down the multi-dimensionality of employees' perceptions of personal data. As a result, the dimensions in which employees perceive data are presented, and differences among employees are highlighted. This is complemented by identifying personal characteristics and attitudes toward employers, as well as toward the right to privacy, that influence these perceptions. Furthermore, this dissertation provides insights into practical aspects for the implementation of personal data management solutions to safeguard employee privacy. Specifically, it presents the results of a user-centered design study with employees who process personal data of other employees as part of their job. Based on the results obtained, a privacy pattern is presented that harmonizes privacy obligations with personal data processing activities. The pattern is useful for designing privacy controls that help these employees handle employee personal data in a privacy-compliant manner, taking into account their skills and knowledge, thus helping to protect employee privacy. The outcome of this dissertation benefits a wide range of stakeholders who are involved in the protection of employee privacy. For example, it highlights the challenges to be considered by employers and software engineers when conceptualizing and designing employee-centric privacy controls. Policymakers and researchers gain a better understanding of employees' perceptions of privacy and obtain fundamental knowledge for future research into theoretical and abstract concepts or practical issues of employee privacy. Employers, IT engineers, and researchers gain insights into ways to empower data processing employees to handle employee personal data in a privacy-compliant manner, enabling employers to improve and promote compliance. Since the basic principles underlying informational self-determination have been incorporated into European privacy legislation, we are confident that our results are also of relevance to stakeholders outside Germany.
In forensic DNA profiling, the occurrence of complex mixed profiles is currently a common issue. Cases involving intimate swabs or skin flake tape liftings are prone to mixed profiles, because of more than one donor contributing to a DNA sample. By DNA profiling of single spermatozoa and skin flakes, problems associated with mixed profile could ideally be overcome. However, PCR is not a sensitive enough method to generate DNA profiles by STRs on single cells. Moreover, high quality intact DNA is required, but is not always available in skin flakes due to degradation. Additionally, single skin flakes are difficult to discriminate from other similar looking particles on tape liftings used to secure DNA samples from evidence. The main purpose of this study was to develop a method that enables DNA profiling of single sperm cells and skin flakes. After studying multiple whole genome amplification (WGA) protocols, REPLI-g Single Cell WGA was selected due to its suitability in the pre-amplification step of template DNA. Micromanipulation was used to isolate single spermatozoa. Furthermore, micromanipulation in combination with REPLI-g Single Cell WGA resulted in successful DNA profiling of single spermatozoa by using autosomal STRs as well as X- and Y-chromosomal STRs. The single spermatozoa DNA profiling method described in this thesis was successfully used to identify male contributors from mock intimate swabs with a mixture of semen from multiple male contributors. Different dyes were analysed to develop a staining method to discriminate skin flakes from other particles including particles such as those from hair cosmetic products. From all dyes tested, Orange G was the only dye which successfully discriminated skin flakes from hair product particles. Also, an alkaline based lysis protocol was developed that allowed PCR to be carried out directly on the lysates of single skin flakes. Furthermore, REPLI-g Single Cell WGA was tested on single skin flakes. In contrast to the single spermatozoa, REPLI-g Single Cell WGA was not successful in DNA profiling of single skin flakes. The single skin flake DNA profiling method described in this thesis was successfully used in correctly identifying contributors from mock mixed DNA evidence. Additionally, a small amplicon-based NGS method was tested on single skin flakes. Compared to the PCR and CE approach, the small amplicon-based NGS method improved DNA profiling of single skin flakes, giving a significant increase in allele recovery. In conclusion, this study shows circumventing mixtures is possible by DNA profiling of single spermatozoa, using micromanipulation and WGA. Furthermore, DNA profiling of single skin flakes has been improved by the staining of tape liftings methodology with Orange G, alkaline lysis, direct-PCR and a small amplicon-based NGS approach. Nonetheless, future work is required to assess the performance of the single spermatozoa method on mock swabs with more diluted semen. Also, commercially available NGS kits should be tested with single skin flakes and compared with the in-house NGS method.
Remineralizing soils? The agricultural usage of silicate rock powders in the context of One Health
(2022)
The concept of soil health describes the capacity of soil to fulfill essential functions and ecosystem services. Healthy soils are inextricably linked to sustainable agriculture and are crucial for the interconnected health of plants, animals, humans, and their environment ("One Health"). However, soil health is threatened through unprecedented rates of soil degradation. A major form of soil degradation is nutrient depletion, which has been seriously underestimated for potassium (K) and several micronutrients. One way to replenish K and micronutrients are multi-nutrient silicate rock powders (SRPs). Their agronomic suitability has long been questioned due to slow weathering rates, although recent studies found significant soil health improvements and challenge past objections which insufficiently addressed the factorial complexity of the weathering process. Furthermore, environmental co-benefits might arise through their mixture with livestock slurry, which could reduce the slurry’s ammonia (NH3) emissions and improve its biophysicochemical properties. However, neither SRPs effects on soil health, nor the biophysicochemical effects of mixing SRPs with livestock slurry have hitherto been comprehensively analyzed. The overall aim of this dissertation is thus to review the agricultural usage of SRPs in the context of One Health. The first part of this thesis starts with an elaboration of the health concept in general and then explores the interlinkages between soil health and One Health. Subsequently, the potentials and oftentimes bypassed problems of operationalizing soil health will be outlined, and feasible ways for its future usage are proposed. In the second part of the thesis, it is reviewed how and under which circumstances SRPs can ameliorate soil health. This is done by presenting a new framework with the most relevant factors for the usage of SRPs through which several contradictory outcomes of prior studies can be explained. A subsequent analysis of 48 crop trials reveals the potential of SRPs as K and multi-nutrient soil amendment for tropical soils, whereas the benefits for temperate soils are inconclusive. The review revealed various co-benefits that could substantially increase SRPs overall agronomic efficiency. The last part of the thesis reports about the effects of mixing two rock powders with cattle slurry. SRPs significantly increased the slurry´s CH4 emission rates, whereas the effects on NH3, CO2, and N2O emission rates were mostly insignificant. The rock powders increased the nutrient content of the slurry and altered its microbiology. In conclusion, the concept of soil health must be operationalized in more specific, practical, and context-dependent ways. Particularly in humid tropical environments, SRPs could advance low-cost soil health ameliorations, and its usage could have additional co-benefits regarding One Health. Mixing SRPs with organic materials like livestock slurry could overcome the major obstacle of their low solubility, although the effects on NH3 and greenhouse gas emissions must be further evaluated.
In this doctoral thesis the curing process of visible light-curing (VLC) dental composites and 3D printing rapid prototyping (RP) materials are investigated with the focus on dielectric analysis (DEA). This method is able to monitor the curing of resins in an alternating electric fringe field with adjustable frequencies and is often used for cure control of composites manufacturing in the aviation and automotive industry but hardly established in dental science or RP method development. It is capable of investigating very fast initiation and primary curing processes using high frequencies in the kHz-range. The aim of the Thesis is a better understanding of the curing processes with respect to curing parameters such as resin composition, viscosity, temperature, and for light-curing composites also light intensity and irradiation depth. Due to the nature of both dental and RP systems an application of specific experimental set-up had to be designed allowing for the generation of reproducible and valid results. Subsequently, different evaluation methods were developed to characterize the curing behavior of both material types. A special focus was paid to the determination of kinetic parameters from DEA measurements. Reaction rates of the curing of the corresponding thermosets were calculated and applied to the ion viscosity curves measured by DEA to evaluate reaction kinetic parameters. For the dental composites it could be clearly shown that the initial curing rate is directly proportional to light intensity and not to its square root as proposed by many others authors. A good description of the curing behaviour of 3DP RP materials was also achieved assuming a reaction order smaller than one. This data provides the base for the kinetic modeling of polymerization and curing processes proposed within the Thesis.
The detection of human skin in images is a very desirable feature for applications such as biometric face recognition, which is becoming more frequently used for, e.g., automated border or access control. However, distinguishing real skin from other materials based on imagery captured in the visual spectrum alone and in spite of varying skin types and lighting conditions can be dicult and unreliable. Therefore, spoofing attacks with facial disguises or masks are still a serious problem for state of the art face recognition algorithms. This dissertation presents a novel approach for reliable skin detection based on spectral remission properties in the short-wave infrared (SWIR) spectrum and proposes a cross-modal method that enhances existing solutions for face verification to ensure the authenticity of a face even in the presence of partial disguises or masks. Furthermore, it presents a reference design and the necessary building blocks for an active multispectral camera system that implements this approach, as well as an in-depth evaluation. The system acquires four-band multispectral images within T = 50ms. Using a machine-learning-based classifier, it achieves unprecedented skin detection accuracy, even in the presence of skin-like materials used for spoofing attacks. Paired with a commercial face recognition software, the system successfully rejected all evaluated attempts to counterfeit a foreign face.
Collaboration among multiple users on large screens leads to complicated behavior patterns and group dynamics. To gain a deeper understanding of collaboration on vertical, large, high-resolution screens, this dissertation builds on previous research and gains novel insights through new observational studies. Among other things, the collected results reveal new patterns of collaborative coupling, suggest that territorial behavior is less critical than shown in previous research, and demonstrate that workspace awareness can also negatively affect the effectiveness of individual users.
Over the last 50 years, the controlled motion of robots has become a very mature domain of expertise. It can deal with all sorts of topologies and types of joints and actuators, with kinematic as well as dynamic models of devices, and with one or several tools or sensors attached to the mechanical structure. Nevertheless, the domain has not succeeded in standardizing the modelling of robot devices (including such fundamental entities as “reference frames”!), let alone the semantics of their motion specification and control. This thesis aims to solve this long-standing problem, from three different sides: semantic models for robot kinematics and dynamics, semantic models of all possible motion specification and control problems, and software that can support the latter while being configured by a systematic use of the former.
Intelligent virtual agents provide a framework for simulating more life-like behavior and increasing plausibility in virtual training environments. They can improve the learning process if they portray believable behavior that can also be controlled to support the training objectives. In the context of this thesis, cognitive agents are considered a subset of intelligent virtual agents (IVA) with the focus on emulating cognitive processes to achieve believable behavior. The complexity of employed algorithms, however, is often limited since multiple agents need to be simulated in real-time. Available solutions focus on a subset of the indicated aspects: plausibility, controllability, or real-time capability (scalability). Within this thesis project, an agent architecture for attentive cognitive agents is developed that considers all three aspects at once. The result is a lightweight cognitive agent architecture that is customizable to application-specific requirements. A generic trait-based personality model influences all cognitive processes, facilitating the generation of consistent and individual behavior. An additional mapping process provides a formalized mechanism to transfer results of psychological studies to the architecture. Personality profiles are combined with an emotion model to achieve situational behavior adaptation. Which action an agent selects in a situation also influences plausibility. An integral element of this selection process is an agent's knowledge about its world. Therefore, synthetic perception is modeled and integrated into the architecture to provide a credible knowledge base. The developed perception module includes a unified sensor interface, a memory hierarchy, and an attention process. With the presented realization of the architecture (CAARVE), it is possible for the first time to simulate cognitive agents, whose behaviors are simultaneously computable in real-time and controllable. The architecture's applicability is demonstrated by integrating an agent-based traffic simulation built with CAARVE into a bicycle simulator for road-safety education. The developed ideas and their realization are evaluated within this work using different strategies and scenarios. For example, it is shown how CAARVE agents utilize personality profiles and emotions to plausibly resolve deadlocks in traffic simulations. Controllability and adaptability are demonstrated in additional scenarios. Using the realization, 200 agents can be simulated in real-time (50 FPS), illustrating scalability. The achieved results verify that the developed architecture can generate plausible and controllable agent behavior in real-time. The presented concepts and realizations provide sound fundamentals to everyone interested in simulating IVA in real-time environments.
The use of manually fed machines (e.g. table saws) bares risks of injury that are clearly above the average level of other high risk workplaces.
The wide use of such machines causes severe problems for occupational safety and implies high costs for medical treatments and accident annuities.
This thesis presents a new concept of a multispectral sensor to monitor an area in front of a danger zone to detect the user’s limbs and trigger safeguarding measures to prevent an accident in time.
The sensor concept realizes a contact-free material classification, which comprises the development of a system design and specific safety requirements with respect to international safety standards.
Furthermore, a prototypical implementation using four wavebands, which were determined for skin detection through an analysis of reflectance spectra acquired specifically for this purpose, was built.
The human enzymes GLYAT (glycine N-acyltransferase), GLYATL1 (glutamine N-phenylacetyltransferase) and GLYATL2 (glycine N-acyltransferase-like protein 2) are not only important in the detoxification of xenobiotics via the human liver, but are also involved in the elimination of acyl residues that accumulate in the form of their coenzyme A (coA) esters in some rare inborn errors of metabolism. This concerns, for example, disorders in the degradation of branched-chain amino acids, such as isovaleric acidemia or propionic acidemia. In addition, they also assist in the elimination of ammonium, which is produced during the transamination of amino acids and accumulates in urea cycle defects. Sequence variants of the enzymes have also been investigated, which may provide evidence of impaired enzyme activities, from which therapy adjustments can potentially be derived. A modified Escherichia coli strain was chosen for the overexpression and partial biochemical characterization of the enzymes, which may allow solubility and proper folding. Since post-translational protein modifications are very limited in bacteria, we also attempted to overexpress the enzymes in HEK293 cells (human-derived). In addition to characterization via immunoblots and activity assays, intracellular localization of the enzymes was also performed using GFP coupling and confocal laser scanning microscopy in transfected HEK293 cells. The GLYATL2 enzyme may have tasks beyond detoxification and metabolic defects and the preliminary molecular biology work has been performed as part of this project - the enzyme activity determinations were outsourced to a co-supervised bachelor thesis. The enzyme activity determinations with purified recombinant human enzyme from Escherichia coli provided a threefold higher activity of the sequence variant p.(Asn156Ser) for GLYAT, which should be considered as the probably authentic wild type of the enzyme. In addition, a reduced activity of the GLYAT variant p.(Gln61Leu), which is very common in South Africa, was shown, which could be of particular importance in the treatment of isovaleric acidemia, which is also common in South Africa. Intracellularly, GLYAT and GLYATL1 could be localized mitochondrially. As the analyses have shown, sequence variations of GLYAT and GLYATL1 influence their enzyme activity. As an example, the GLYAT variant p.(Gln61Leu) is frequently found in South Africa. In the case of reduced GLYAT activity, patients could be increasingly treated with L-carnitine in the sense of an individualized therapy, since the conjugation of the toxic isovaleryl-coA with glycine is restricted by the GLYAT sequence variation. Activity-reducing variants identified in this project are of particular interest, as they may influence the treatment of certain metabolic defects.
The generation and maintenance of intricate spatiotemporal patterns of gene expression in multicellular organisms requires the establishment of complex mechanisms of transcriptional regulation. Estimations that up to one million enhancers exist in the human genome accentuates the utmost importance of this type of cis-regulatory element for gene regulation. However, surprisingly little is known about the mechanisms used to temporarily or permanently activate or inactivate enhancers during cellular differentiation. The current work addresses the question how enhancer regulation can be achieved.
Using the chemokine (C-C motif) ligand gene Ccl22 as a model, the first example is based on the question how the activation of an enhancer can be prevented in a physiological context. Ccl22 is expressed by myeloid cells, such as dendritic cells, upon exposure to inflammatory stimuli. The expression in other cell types, such as fibroblasts, is prevented by the strong accumulation of H3K9me3 at the enhancer's proximal region. This accumulation is attenuated in myeloid cells through activity of the stimulus-induced demethylase Jmjd2d. To tease out which genomic fragment or fragments in the Ccl22 locus could be responsible for the maintenance of enhancer inactivity, potentially through the recruitment of H3K9 methyltransferases, the enhancer repressing capacity of 1 kb fragments of the gene locus was analysed in retroviral reporter assays. It was found that a fragment adjacent to the Ccl22 enhancer that overlaps with a member of a subfamily of long interspersed nuclear elements (LINEs) showed strong repressive potential on a model enhancer. Subsequent retroviral reporter assays with LINEs from loci of other stimulus-dependent genes identified additional LINE fragments that exhibit strong enhancer repressive capacity. These findings suggest a mechanism for enhancer silencing involving LINEs.
The second example concentrates on the inactivation of an enhancer during colorectal cancer (CRC) progression. The adenoma to carcinoma transition during CRC progression often is accompanied by a downregulation of the tumour suppressor gene EPHB2. The EMT inducing factor SNAIL1 strongly downregulated EPHB2 expression in a CRC cell model. To gain insights into the transcriptional regulation of EPHB2, potential cis-regulatory elements in the EPHB2 upstream region were analysed using reporter assays. A cell-type-specific enhancer was identified and subsequent chromatin analyses revealed a correlation between enhancer chromatin conformation and EPHB2 expression in different CRC cell lines. Additionally, the overexpression of the murine Snail1 induced chromatin changes at the EPHB2 enhancer towards a poised, transcriptionally silent chromatin conformation. Mutational analyses of the minimal enhancer region pinpointed three transcription factor binding motifs to be essential for full enhancer activity. Different binding patterns between CRC cell lines at the TCF/LEF motif were subsequently identified. Furthermore, a switch from TCF7L2 to LEF1 occupancy was found upon overexpression of Snail1 in vitro and in vivo. The generation of LS174T CRC cells overexpressing LEF1 confirmed the involvement of LEF1 in the downregulation of EPHB2 and the competitive displacement of TCF7L2. This part of the work demonstrated that the SNAIL1 induced downregulation of EPHB2 is dependent on the decommissioning of a transcriptional enhancer and led to a hypothetical model involving LEF1 and ZEB1.
In summary, this work highlighted two distinct mechanisms for enhancer regulation. One mechanism is based on enhancer repressive LINE fragments that might prevent stimulus-dependent enhancer activation. In the second, enhancer silencing was shown to be based on a competitive transcription factor binding mechanism.
Despite their age, ray-based rendering methods are still a very active field of research with many challenges when it comes to interactive visualization. In this thesis, we present our work on Guided High-Quality Rendering, Foveated Ray Tracing for Head Mounted Displays and Hash-based Hierarchical Caching and Layered Filtering. Our system for Guided High-Quality Rendering allows for guiding the sampling rate of ray-based rendering methods by a user-specified Region of Interest (RoI). We propose two interaction methods for setting such an RoI when using a large display system and a desktop display, respectively. This makes it possible to compute images with a heterogeneous sample distribution across the image plane. Using such a non-uniform sample distribution, the rendering performance inside the RoI can be significantly improved in order to judge specific image features. However, a modified scheduling method is required to achieve sufficient performance. To solve this issue, we developed a scheduling method based on sparse matrix compression, which has shown significant improvements in our benchmarks. By filtering the sparsely sampled image appropriately, large brightness variations in areas outside the RoI are avoided and the overall image brightness is similar to the ground truth early in the rendering process. When using ray-based methods in a VR environment on head-mounted display de vices, it is crucial to provide sufficient frame rates in order to reduce motion sickness. This is a challenging task when moving through highly complex environments and the full image has to be rendered for each frame. With our foveated rendering sys tem, we provide a perception-based method for adjusting the sample density to the user’s gaze, measured with an eye tracker integrated into the HMD. In order to avoid disturbances through visual artifacts from low sampling rates, we introduce a reprojection-based rendering pipeline that allows for fast rendering and temporal accumulation of the sparsely placed samples. In our user study, we analyse the im pact our system has on visual quality. We then take a closer look at the recorded eye tracking data in order to determine tracking accuracy and connections between different fixation modes and perceived quality, leading to surprising insights. For previewing global illumination of a scene interactively by allowing for free scene exploration, we present a hash-based caching system. Building upon the concept of linkless octrees, which allow for constant-time queries of spatial data, our frame work is suited for rendering such previews of static scenes. Non-diffuse surfaces are supported by our hybrid reconstruction approach that allows for the visualization of view-dependent effects. In addition to our caching and reconstruction technique, we introduce a novel layered filtering framework, acting as a hybrid method between path space and image space filtering, that allows for the high-quality denoising of non-diffuse materials. Also, being designed as a framework instead of a concrete filtering method, it is possible to adapt most available denoising methods to our layered approach instead of relying only on the filtering of primary hitpoints.
Process-dependent thermo-mechanical viscoelastic properties and the corresponding morphology of HDPE extrusion blow molded (EBM) parts were investigated. Evaluation of bulk data showed that flow direction, draw ratio, and mold temperature influence the viscoelastic behavior significantly in certain temperature ranges. Flow induced orientations due to higher draw ratio and higher mold temperature lead to higher crystallinities. To determine the local viscoelastic properties, a new microindentation system was developed by merging indentation with dynamic mechanical analysis. The local process-structure-property relationship of EBM parts showed that the cross-sectional temperature distribution is clearly reflected by local crystallinities and local complex moduli. Additionally, a model to calculate three-dimensional anisotropic coefficients of thermal expansion as a function of the process dependent crystallinity was developed based on an elementary volume unit cell with stacked layers of amorphous phase and crystalline lamellae. Good agreement of the predicted thermal expansion coefficients with measured ones was found up to a temperature of 70 °C.
Evaluation and Optimization of IEEE802.11 multi-hop Backhaul Networks with Directional Antennas
(2020)
A major problem for rural areas is the inaccessibility to affordable broadband Internet connections. In these areas distances are large, and digging a cable into the ground is extremely expensive, considering the small number of potential customers at the end of that cable. This leads to a digital divide, where urban areas enjoy a high-quality service at low cost, while rural areas suffer from the reverse.
This work is dedicated to an alternative technical approach aiming to reduce the cost for Internet Service Provider in rural areas: WiFi-based Long Distance networks. A set of significant contributions of technology related aspects of WiFi-based Long Distance networks is described in three different fields: Propagation on long distance Wi-Fi links, MAC-layer scheduling and Interference modeling and Channel Assignment with directional antennas.
For each field, the author composes and discusses the state-of-the-art. Afterwards, the author derives research questions and tackles several open issues to develop these kinds of networks further towards a suitable technology for the backhaul segment.
Since its advent, the sustainability effects of the modern sharing economy have been the subject of controversial debate. While its potential was initially discussed in terms of post-ownership development with a view to decentralizing value creation and increasing social capital and environmental relief through better utilization of material goods, critics have become increasingly loud in recent years. Many people hoped that carsharing could lead to development away from ownership towards flexible use and thus more resource-efficient mobility. However, carsharing remains niche, and while many people like the idea in general, they appear to consider carsharing to not be advantageous as a means of transport in terms of cost, flexibility, and comfort. A key innovation that could elevate carsharing from its niche existence in the future is autonomous driving. This technology could help shared mobility gain a new boost by allowing it to overcome the weaknesses of the present carsharing business model. Flexibility and comfort could be greatly enhanced with shared autonomous vehicles (SAVs), which could simultaneously offer benefits in terms of low cost, and better use of time without the burden of vehicle ownership. However, it is not the technology itself that is sustainable; rather, sustainability depends on the way in which this technology is used. Hence, it is necessary to make a prospective assessment of the direct and indirect (un)sustainable effects before or during the development of a technology in order to incorporate these findings into the design and decision-making process. Transport research has been intensively analyzing the possible economic, social, and ecological consequences of autonomous driving for several years. However, research lacks knowledge about the consequences to be expected from shared autonomous vehicles. Moreover, previous findings are mostly based on the knowledge of experts, while potential users are rarely included in the research. To address this gap, this thesis contributes to answering the questions of what the ecological and social impacts of the expected concept of SAVs will be. In my thesis, I study in particular the ecological consequences of SAVs in terms of the potential modal shifts they can induce as well as their social consequences in terms of potential job losses in the taxi industry. Regarding this, I apply a user-oriented, mixed-method technology assessment approach that complements existing, expert-oriented technology assessment studies on autonomous driving that have so far been dominated by scenario analyses and simulations. To answer the two questions, I triangulated the method of scenario analysis and qualitative and quantitative user studies. The empirical studies provide evidence that the automation of mobility services such as carsharing may to a small extent foster a shift from the private vehicle towards mobility on demand. However, findings also indicate that rebound effects are to be expected: Significantly more users are expected to move away from the more sustainable public transportation, leading to an overcompensation of the positive modal shift effects by the negative modal shift effects. The results show that a large proportion of the taxi trips carried out can be re-placed by SAVs, making the profession of taxi driver somewhat obsolete. However, interviews with taxi drivers themselves revealed that the services provided by the drivers go beyond mere transport, so that even in the age of SAVs, the need for human assistance will continue – though to a smaller extent. Given these findings, I see action potential at different levels: users, mobility service providers, and policymakers. Regarding environmental and social impacts resulting from the use of SAVs, there is a strong conflict of objectives among users, potential SAV operators, and sustainable environmental and social policies. In order to strengthen the positive effects and counteract the negative effects, such as unintended modal shifts, policies may soon have to regulate the design of SAVs and their introduction. A key starting point for transport policy is to promote the use of more environmentally friendly means of transport, in particular by making public transportation attractive and, if necessary, by making the use of individual motorized mobility less attractive. The taxi industry must face the challenges of automation by opening up to these developments and focusing on service orientation – to strengthen the drivers’ main unique selling point compared to automated technology. Assessing the impacts of the not-yet-existing generally involves great uncertainty. With the results of my work, however, I would like to argue that a user-oriented technology assessment can usefully complement the findings of classic methods of technology assessment and can iteratively inform the development process regarding technology and regulation.
With the digital transformation, software systems have become an integral part of our society and economy. In every part of our life, software systems are increasingly utilized to, e.g., simplify housework or to optimize business processes. All these applications are connected to the Internet, which already includes millions of software services consumed by billions of people. Applications which process such a magnitude of users and data traffic requires to be highly scalable and are therefore denoted as Ultra Large Scale (ULS) systems. Roy Fielding has defined one of the first approaches which allows designing modern ULS software systems. In his doctoral thesis, Fielding introduced the architectural style Representational State Transfer (REST) which builds the theoretical foundation of the web. At present, the web is considered as the world's largest ULS system. Due to a large number of users and the significance of software for society and the economy, the security of ULS systems is another crucial quality factor besides high scalability.
For a sustainable development the electricity sector needs to be decarbonized. In 2017 only 54% of the West African households had access to the electrical grid. Thus, renewable sources should play a major role for the development of the power sector in West Africa. Above all, solar power shows highest potential of renewable energy sources. However, it is highly variable, depending on the atmospheric conditions. This study addresses the challenges for a solar based power system in West Africa by analyzing the atmospheric variability of solar power. For this purpose, two aspects are investigated. In the first part, the daily power reduction due to atmospheric aerosols is quantified for different solar power technologies. Meteorological data at six ground-based stations is used to model photovoltaic and parabolic trough power during all mostly clear-sky days in 2006. A radiative transfer model is combined with solar power model. The results show, that the reduction due to aerosols can be up to 79% for photovoltaic and up to 100% for parabolic trough power plants during a major dust outbreak. Frequent dust outbreaks occurring in West Africa would cause frequent blackouts if sufficient storage capacities are not available. On average, aerosols reduce the daily power yields by 13% to 22% for photovoltaic and by 22% to 37% for parabolic troughs. For the second part, long-term atmospheric variability and trends of solar irradiance are analyzed and their impact on photovoltaic yields is examined for West Africa. Based on a 35-year satellite data record (1983 - 2017) the temporal and spatial variability and general trend are depicted for global and direct horizontal irradiances. Furthermore, photovoltaic yields are calculated on a daily basis. They show a strong meridional gradient with highest values of 5 kWh/kWp in the Sahara and Sahel zone and lowest values in southern West Africa (around 4 kWh/kWp). Thereby, the temporal variability is highest in southern West Africa (up to around 18%) and lowest in the Sahara (around 4.5%). This implies the need of a North-South grid development, to feed the increasing demand on the highly populated coast by solar power from the northern parts of West Africa. Additionally, global irradiances show a long-term positive trend (up to +5 W/m²/decade) in the Sahara and a negative trend (up to -5 W/m²/decade) in southern West Africa. If this trend is continuing, the spatial differences in solar power potential will increase in the future. This thesis provides a better understanding of the impact of atmospheric variability on solar power in a challenging environment like West Africa, characterized by the strong influence of the African monsoon. Thereby, the importance of aerosols is pointed out. Furthermore, long-term changes of irradiance are characterized concerning their implications for photovoltaic power.
User Modeling and Machine Learning for User Modeling have both become important research topics and key techniques in recent adaptive systems. One of the most intriguing problems in the `information age´ is how to filter relevant information from the huge amount of available data. This problem is tackled by using models of the user´s interest in order to increase precision and discriminate interesting information from un-interesting data. However, any user modeling approach suffers from several major drawbacks: User models built by the system need to be inspectable and understandable by the user himself. Secondly, users in general are not willing to give feedback concerning user satisfaction by the delivered results.
Skill generalisation and experience acquisition for predicting and avoiding execution failures
(2023)
For performing tasks in their target environments, autonomous robots usually execute and combine skills. Robot skills in general and learning-based skills in particular are usually designed so that flexible skill acquisition is possible, but without an explicit consideration of execution failures, the impact that failure analysis can have on the skill learning process, or the benefits of introspection for effective coexistence with humans. Particularly in human-centered environments, the ability to understand, explain, and appropriately react to failures can affect a robot's trustworthiness and, consequently, its overall acceptability. Thus, in this dissertation, we study the questions of how parameterised skills can be designed so that execution-level decisions are associated with semantic knowledge about the execution process, and how such knowledge can be utilised for avoiding and analysing execution failures. The first major segment of this work is dedicated to developing a representation for skill parameterisation whose objective is to improve the transparency of the skill parameterisation process and enable a semantic analysis of execution failures. We particularly develop a hybrid learning-based representation for parameterising skills, called an execution model, which combines qualitative success preconditions with a function that maps parameters to predicted execution success. The second major part of this work focuses on applications of the execution model representation to address different types of execution failures. We first present a diagnosis algorithm that, given parameters that have resulted in a failure, finds a failure hypothesis by searching for violations of the qualitative model, as well as an experience correction algorithm that uses the found hypothesis to identify parameters that are likely to correct the failure. Furthermore, we present an extension of execution models that allows multiple qualitative execution contexts to be considered so that context-specific execution failures can be avoided. Finally, to enable the avoidance of model generalisation failures, we propose an adaptive ontology-assisted strategy for execution model generalisation between object categories that aims to combine the benefits of model-based and data-driven methods; for this, information about category similarities as encoded in an ontology is integrated with outcomes of model generalisation attempts performed by a robot. The proposed methods are exemplified in terms of various use cases - object and handle grasping, object stowing, pulling, and hand-over - and evaluated in multiple experiments performed with a physical robot. The main contributions of this work include a formalisation of the skill parameterisation problem by considering execution failures as an integral part of the skill design and learning process, a demonstration of how a hybrid representation for parameterising skills can contribute towards improving the introspective properties of robot skills, as well as an extensive evaluation of the proposed methods in various experiments. We believe that this work constitutes a small first step towards more failure-aware robots that are suitable to be used in human-centered environments.