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Das Deutsche Zentrum für Luft- und Raumfahrt (DLR) führt viele Forschungen und Studien im Bereich der Luft- und Raumfahrt durch. Dabei spielen die Studien für die Gesundheit und Medizin auch eine sehr wichtige Rolle bei der DLR. Zu diesem Zweck führt die DLR die Artificial Gravity bed rest study (AGBRESA) im Auftrag der European Space Agency (esa) und in Kooperation der NASA durch. In dieser Studie werden die negativen Auswirkungen der Schwerelosigkeit auf dem Menschen im Weltall simuliert. Dabei werden Experimente durchgeführt, um die negative Auswirkungen entgegenzuwirken. Die Ergebnisse der Experimente werden in der DLR digital, aber auch auf Papier dokumentiert. In diesem Master-Projekt habe ich nun die Aufgabe, die Papierprotokolle für den Bereich der Blutabnahme und der Labordokumentation in eine digitale Form zu ersetzen.
This work presents the preliminary research towards developing an adaptive tool for fault detection and diagnosis of distributed robotic systems, using explainable machine learning methods. Autonomous robots are complex systems that require high reliability in order to operate in different environments. Even more so, when considering distributed robotic systems, the task of fault detection and diagnosis becomes exponentially difficult.
To diagnose systems, models representing the behaviour under investigation need to be developed, and with distributed robotic systems generating large amount of data, machine learning becomes an attractive method of modelling especially because of its high performance. However, with current day methods such as artificial neural networks (ANNs), the issue of explainability arises where learnt models lack the ability to give explainable reasons behind their decisions.
This paper presents current trends in methods for data collection from distributed systems, inductive logic programming (ILP); an explainable machine learning method, and fault detection and diagnosis.
Healing of large bone defects requires implants or scaffolds that provide structural guidance for cell growth, differentiation, and vascularization. In the present work, an agarose-hydroxyapatite composite scaffold was developed that acts not only as a 3D matrix, but also as a release system. Hydroxyapatite (HA) was incorporated into the agarose gels in situ in various ratios by a simple procedure consisting of precipitation, cooling, washing, and drying. The resulting gels were characterized regarding composition, porosity, mechanical properties, and biocompatibility. A pure phase of carbonated HA was identified in the scaffolds, which had pore sizes of up to several hundred micrometers. Mechanical testing revealed elastic moduli of up to 2.8 MPa for lyophilized composites. MTT testing on Lw35human mesenchymal stem cells (hMSCs) and osteosarcoma MG-63 cells proved the biocompatibility of the scaffolds. Furthermore, scaffolds were loaded with model drug compounds for guided hMSC differentiation. Different release kinetic models were evaluated for adenosine 5′-triphosphate (ATP) and suramin, and data showed a sustained release behavior over four days.
Bone tissue engineering is an ever-changing, rapidly evolving, and highly interdisciplinary field of study, where scientists try to mimic natural bone structure as closely as possible in order to facilitate bone healing. New insights from cell biology, specifically from mesenchymal stem cell differentiation and signaling, lead to new approaches in bone regeneration. Novel scaffold and drug release materials based on polysaccharides gain increasing attention due to their wide availability and good biocompatibility to be used as hydrogels and/or hybrid components for drug release and tissue engineering. This article reviews the current state of the art, recent developments, and future perspectives in polysaccharide-based systems used for bone regeneration.
This work introduces a semi-Lagrangian lattice Boltzmann (SLLBM) solver for compressible flows (with or without discontinuities). It makes use of a cell-wise representation of the simulation domain and utilizes interpolation polynomials up to fourth order to conduct the streaming step. The SLLBM solver allows for an independent time step size due to the absence of a time integrator and for the use of unusual velocity sets, like a D2Q25, which is constructed by the roots of the fifth-order Hermite polynomial. The properties of the proposed model are shown in diverse example simulations of a Sod shock tube, a two-dimensional Riemann problem and a shock-vortex interaction. It is shown that the cell-based interpolation and the use of Gauss-Lobatto-Chebyshev support points allow for spatially high-order solutions and minimize the mass loss caused by the interpolation. Transformed grids in the shock-vortex interaction show the general applicability to non-uniform grids.
Risk-based authentication (RBA) is an adaptive security measure to strengthen password-based authentication. RBA monitors additional implicit features during password entry such as device or geolocation information, and requests additional authentication factors if a certain risk level is detected. RBA is recommended by the NIST digital identity guidelines, is used by several large online services, and offers protection against security risks such as password database leaks, credential stuffing, insecure passwords and large-scale guessing attacks. Despite its relevance, the procedures used by RBA-instrumented online services are currently not disclosed. Consequently, there is little scientific research about RBA, slowing down progress and deeper understanding, making it harder for end users to understand the security provided by the services they use and trust, and hindering the widespread adoption of RBA.
In this paper, with a series of studies on eight popular online services, we (i) analyze which features and combinations/classifiers are used and are useful in practical instances, (ii) develop a framework and a methodology to measure RBA in the wild, and (iii) survey and discuss the differences in the user interface for RBA. Following this, our work provides a first deeper understanding of practical RBA deployments and helps fostering further research in this direction.
The limited sodium availability of freshwater and terrestrial environments was a major physiological challenge during vertebrate evolution. The epithelial sodium channel (ENaC) is present in the apical membrane of sodium-absorbing vertebrate epithelia and evolved as part of a machinery for efficient sodium conservation. ENaC belongs to the degenerin/ENaC protein family and is the only member that opens without an external stimulus. We hypothesized that ENaC evolved from a proton-activated sodium channel present in ionocytes of freshwater vertebrates and therefore investigated whether such ancestral traits are present in ENaC isoforms of the aquatic pipid frog Xenopus laevis. Using whole-cell and single-channel electrophysiology of Xenopus oocytes expressing ENaC isoforms assembled from alpha beta gamma- or delta beta gamma-subunit combinations, we demonstrate that Xenopus delta beta gamma-ENaC is profoundly activated by extracellular acidification within biologically relevant ranges (pH 8.0-6.0). This effect was not observed in Xenopus alpha beta gamma-ENaC or human ENaC orthologs. We show that protons interfere with allosteric ENaC inhibition by extracellular sodium ions, thereby increasing the probability of channel opening. Using homology modeling of ENaC structure and site-directed mutagenesis, we identified a cleft region within the extracellular loop of the delta-subunit that contains several acidic amino acid residues that confer proton-sensitivity and enable allosteric inhibition by extracellular sodium ions. We propose that Xenopus delta beta gamma-ENaC can serve as a model for investigating ENaC transformation from a proton-activated toward a constitutively-active ion channel. Such transformation might have occurred during the evolution of tetrapod vertebrates to enable bulk sodium absorption during the water-to-land transition.
Although work events can be regarded as pivotal elements of organizational life, only a few studies have examined how positive and negative events relate to and combine to affect work engagement over time. Theory suggests that to better understand how current events affect work engagement (WE), we have to account for recent events that have preceded these current events. We present competing theoretical views on how recent and current work events may affect employees (e.g., getting used to a high frequency of negative events or becoming more sensitive to negative events). Although the occurrence of events implies discrete changes in the experience of work, prior research has not considered whether work events actually accumulate to sustained mid-term changes in WE. To address these gaps in the literature, we conducted a week-level longitudinal study across a period of 15 consecutive weeks among 135 employees, which yielded 849 weekly observations. While positive events were associated with higher levels of WE within the same week, negative events were not. Our results support neither satiation nor sensitization processes. However, high frequencies of negative events in the preceding week amplified the beneficial effects of positive events on WE in the current week. Growth curve analyses show that the benefits of positive events accumulate to sustain high levels of WE. WE dissipates in the absence of continuous experience of positive events. Our study adds a temporal component and informs research that has taken a feature-oriented perspective on the dynamic interplay of job demands and resources.
In the literature on occupational stress and recovery from work, several facets of thinking about work during off-job time have been conceptualized. However, research on the focal concepts is currently rather diffuse. In this study we take a closer look at the five most well-established concepts: (1) psychological detachment, (2) affective rumination, (3) problem-solving pondering, (4) positive work reflection, and (5) negative work reflection. More specifically, we scrutinized (1) whether the five facets of work-related rumination are empirically distinct, (2) whether they yield differential associations with different facets of employee well-being (burnout, work engagement, thriving, satisfaction with life, and flourishing), and (3) to what extent the five facets can be distinguished from and relate to conceptually similar constructs, such as irritation, worry, and neuroticism. We applied structural equation modeling techniques to cross-sectional survey data from 474 employees. Our results provide evidence for (1) five correlated, yet empirically distinct facets of work-related rumination. (2) Each facet yields a unique pattern of association with the eight aspects of employee well-being. For instance, detachment is strongly linked to satisfaction with life and flourishing. Affective rumination is linked particularly to burnout. Problem-solving pondering and positive work reflection yield the strongest links to work engagement. (3) The five facets of work-related rumination are distinct from related concepts, although there is a high overlap between (lower levels of) psychological detachment and cognitive irritation. Our study contributes to clarifying the structure of work-related rumination and extends the nomological network around different types of thinking about work during off-job time and employee well-being.
In the literature on occupational stress and recovery from work several facets of thinking about work in off-job time have been conceptualized. However, research on the focal concepts is currently rather disintegrated. In this study we take a closer look at the five most established concepts, namely (1) psychological detachment, (2) affective rumination, (3) problem-solving pondering, (4) positive work reflection, and (5) negative work reflection. More specifically, we scrutinized (1) whether the five facets of work-related rumination are empirically distinct, (2) whether they yield differential associations with different facets of employee well-being (burnout, work engagement, thriving, satisfaction with life, and flourishing), and (3) to what extent the five facets can be distinguished from and relate to conceptually similar constructs, such as irritation, worry, and neuroticism. We applied structural equation modeling techniques to cross-sectional survey data from 474 employees. Our results provide evidence that (1) the five facets of work-related rumination are highly related, yet empirically distinct, (2) that each facet contributes uniquely to explain variance in certain aspects of employee well-being, and (3) that they are distinct from related concepts, albeit there is a high overlap between (lower levels of) psychological detachment and cognitive irritation. Our study contributes to clarify the structure of work-related rumination and extends the nomological network around different types of thinking about work in off-job time and employee well-being.
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.
Kenya, like all other developing countries in the world, is faced with the task of working strategically towards the achievement of the Sustained Development Goals (SDGs) 2030. These goals whose due date of accomplishment coincides with those of the national development blueprint, namely, the Kenya Vision 2030, have become a major focus of attention in the country. Conferences, workshops, and seminars are organized throughout the country on regular bases by joint multiplicity of organizations to address modalities of ensuring a timely achievement of SDGs in the country. Universities either individually or jointly are working towards this same target. More specifically, there are great areas of concern or priority areas that the country is focusing on as a strategic focus towards the achievement of the Kenya Vision 2030 and SDGs 2030. These strategic areas of focus have been isolated and declared by the President of the Republic of Kenya, His Excellency Uhuru Kenyatta, as the country’s “big four priority areas”, namely, affordable housing, affordable health care, food security, and manufacturing as a grandiose effort towards achievement of the SDGs, Kenya Vision 2030 as well as job and wealth creation. Similarly, Mount Kenya University’s top management established the Graduate Enterprise Academy (GEA) in 2013 under the direct Patronage of the university’s Founder with the primary aim of assisting graduates to be job and wealth creators rather than being job seekers. So far, over twenty start-ups are running throughout the country under Graduate Enterprise Academy (GEA). Incidentally, although the Graduate Enterprise Academy’s diverse areas of focus extend beyond the President of Kenya’s “Big Four” to include ICT and creative arts, among others, there are justifiable cases to indicate that GEA’s activities are also in support of the national “Big Four” agenda. This paper gives an exposition of different start-ups under MKU’s Graduate Enterprise Academy and are show-cased as evidence of MKU’s support towards the achievement of the national “Big Four” agenda. The paper covers a part of an ongoing program through desk-top analyses of reports, with an objective of show-casing MKU’s contribution to the national agenda through the Graduate Enterprise Academy for possible scale - up.