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In an Arrow-Debreu world of unrestricted access to perfect and competitive financial markets, there is no need for accounting information about the financial situation of a firm. Because information is costless, share- and stakeholders are then indifferent in deposits and securities (e.g., Holthausen & Watts 2001; Freixas & Rochet 2008). How-ever, several reasons exist indicating a rejection of the assumptions for an Arrow-Debreu world, hence there is no perfect costless information. Moreover, the distribu-tion of information is asymmetric, causing follow-through multi-level agency prob-lems, which are the main reasoning for the variety of financial and non-financial ac-counting standards, regulatory and advisory entities and the auditing and rating agency profession. Likewise, these agency problems have been at the heart of the accounting literature and raised the question of whether and how accounting information can help resolve these problems. ...
The skeletal system forms the mechanical structure of the body and consists of bone, which is hard connective tissue. The tasks the skeleton and bones take over are of mechanical, metabolic and synthetic nature. Lastly, bones enable the production of blood cells by housing the bone marrow. Bone has a scarless self-healing capacity to a certain degree. Injuries exceeding this capacity caused by trauma, surgical removal of infected or tumoral bone or as a result from treatment-related osteonecrosis, will not heal. Critical size bone defects that will not heal by themselves are still object of comprehensive clinical investigation. The conventional treatments often result in therapies including burdening methods as for example the harvesting of autologous bone material. The aim of this thesis was the creation of a prevascularized bone implant employing minimally invasive methods in order to minimize inconvenience for patients and surgical site morbidity. The basis for the implant was a decellularized, naturally derived vascular scaffold (BioVaSc-TERM®) providing functional vessel structures after reseeding with autologous endothelial cells. The bone compartment was built by the combination of the aforementioned scaffold with synthetic β-tricalcium phosphate. In vitro culture for tissue maturation was performed using bioreactor technology before the testing of the regenerative potential of the implant in large animal experiments in sheep. A tibia defect was treated without the anastomosis of the implant’s innate vasculature to the host’s circulatory system and in a second study, with anastomosis of the vessel system in a mandibular defect. While the non-anastomosed implant revealed a mostly osteoconductive effect, the implants that were anastomosed achieved formation of bony islands evenly distributed over the defect.
In order to prepare preconditions for a rapid approval of an implant making use of this vascularization strategy, the manufacturing of the BioVaSc-TERM® as vascularizing scaffold was adjusted to GMP requirements.
This thesis describes the growth and characterization of both the all-oxide heterostructure
Fe3O4/ZnO and the spin-orbit coupling driven layered perovskite iridates.
As for Fe3O4/ZnO, the 100% spin-polarized Fe3O4 is a promising spin electrode candidate
for spintronic devices. However, the single crystalline ZnO substrates exhibit different polar surface termination which, together with substrate preparation method, can drastically affect the physical properties of Fe3O4/ZnO heterostructures. In this thesis two different methods of substrate preparation were investigated: a previously used in situ method involving sputtering and annealing treatments and a recent ex situ method containing only the annealing procedure. For the latter, the annealing treatment was performed in dry and humid O2 gas flow for the O- and Zn-terminated substrates, respectively, to produce atomically at surfaces as verified by atomic force microscopy(AFM). With these methods, four different ZnO substrates were fabricated and used further for Fe3O4 film growth. Fe3O4 films of 20 nm thickness were successfully grown by reactive molecular beam epitaxy. AFM measurements reveal a higher film surface roughness for the samples with in situ prepared substrates. Moreover, X-ray photoelectron spectroscopy (XPS) measurements indicate significant Zn substitution within the Fe3O4 film for these samples, whereas the samples with ex situ prepared substrates show stoichiometric Fe3O4 films. X-ray diffraction measurements confirm the observations from XPS, revealing additional peaks due to Zn substitution in Fe3O4 films grown on in situ prepared ZnO substrates. Conductivity, as well as magnetometry, measurements show the presence of Zn-doped ferrites in films grown on in situ prepared substrates. Such unintentionally intercalated Zn-doped ferrites dramatically change the electrical and magnetic properties of the films and, therefore, are not preferred in a high-quality heterostructure.
X-ray reflectivity (XRR) measurements show for the film grown on ex situ prepared Zn-terminated substrate a variation of film density close to the interface which is also confirmed by transmission electron microscopy (TEM). Using polarized neutron reflectometry, magnetic depth profiles of the films grown on ex situ prepared substrates clearly indicate Fe3O4 layers with reduced magnetization at the interfaces. This result is consistent with earlier observations made by resonant magnetic X-ray reflectometry (RMXR), but in contrast to the findings from XRR and TEM of this thesis. A detailed TEM study of all four samples shows that the sample with ex situ prepared O-terminated substrate has the sharpest interface, whereas those with ex situ prepared Zn-terminated as well as in situ prepared substrates indicate rougher interfaces. STEM-EELS composition profiles of the samples reveal the Zn substitution in the films with in situ prepared substrates and therefore confirm the presence of Zn-doped ferrites. Moreover, a change of the Fe oxidation state of the first Fe layer at the interface which was observed in previous studies done by RMXR, was not verified for the samples with in situ prepared substrates thus leaving the question of a possible presence of the magnetically dead layer open. Furthermore, density functional theory calculations were performed to determine the termination dependent layer sequences which are ...-Zn-O-(interface)-[Fe(octa)-O-Fe(tetra)-Fe(octa)-Fe(tetra)-O]-[...]-... and ...-O-Zn-(interface)-[O-Fe(octa)-O-Fe(tetra)-Fe(octa)-Fe(tetra)]-[...]-... for the samples with O- and Zn-terminated substrates, respectively. Spin density calculations show that in case of O-termination the topmost substrate layers imitate the spin polarization of film layers close to the interface. Here, the first O layer is affected much stronger than the first Zn layer. Due to the strong decrease of this effect toward deeper substrate layers, the substrate surface is supposed to be sensitive to the contiguous spin polarization of the film. Thus, the topmost O layer of the O-terminated substrate could play the most essential role for effective spin injection into ZnO.
The 5d transition metal oxides Ba2IrO4 (BIO) and Sr2IrO4 (SIO) are associated with the Ruddlesden-Popper iridate series with phase type "214" (RP{214), and due to the strong spin-orbit coupling belong to the class of Mott insulators. Moreover, they show many similarities of the isostructural high Tc-cuprate superconductors, e.g. crystal structure, magnetism and electronic band structure. Therefore, it is of great interest to activate a potential superconducting phase in (RP{214) iridates. However, only a small number of publications on PLD grown (RP{214) iridates in the literature exists. Furthermore, published data of soft X-ray angle resolved photoemission spectroscopy (SX-ARPES) experiments mainly originate from measurements which were performed on single crystals or MBE grown films of SIO and BIO. In this thesis La-doped SIO films (La0:2Sr1:8IrO4, further referred as LSIO) were used to pursue a potential superconducting phase.
A set of characterization methods was used to analyze the quality of the PLD grown BIO, SIO and LSIO films. AFM measurements demonstrate that thick PLD grown(RP{214) iridate films have rougher surfaces, indicating a transition from a 2D layer-bylayer growth (which is demonstrated by RHEED oscillations) to a 3D island-like growth mode. In addition, chemical depth profiling XPS measurements indicate an increase of the O and Ir relative concentrations in the topmost film layers. Constant energy k-space maps and energy distribution curves (EDCs) measured by SX-ARPES show for every grown film only weak energy band dispersions, which are in strong contrast to the results obtained on the MBE grown films and single crystals from the literature. In this thesis,
a subsequent TEM study reveals missing SrO layers within the grown films which occur mainly in the topmost layers, confirming the results and suggestions from XPS and SX-ARPES data: the PLD grown films have defects and, therefore, incoherently scatter photoelectrons. Nevertheless, the LSIO film shows small additional spectral weight between the highsymmetry M points close to the Fermi level which can be attributed to quasiparticle states which, in turn, indicates the formation of a Fermi-arc. However, neither conductivity measurements nor valence band analysis via XPS confirm an activation of a superconducting phase or presence of spectral weight of quasiparticle states at the Fermi level in this LSIO film.
It is possible that these discovered difficulties in growth are responsible for the low number of SX-ARPES publications on PLD grown (RP{214) iridate films. For further investigations of (RP{214) iridate films by SX-ARPES, their PLD growth recipes have to be improved to create high quality single crystalline films without imperfections.
The lability of B=B, B-P and B-halide bonds is combined in the syntheses of the first diiododiborenes. In a series of reactivity tests, these diiododiborenes demonstrate cleavage of all six of their central bonds in different ways, leading to products of B=B hydrogenation and dihalogenation as well as halide exchange.
Since Channelrhodopsins has been described first and introduced successfully in freely moving animals (Nagel et al., 2003 and 2005), tremendous impact has been made in this interesting field of neuroscience. Subsequently, many different optogenetic tools have been described and used to address long-lasting scientific issues. Furthermore, beside the ‘classical’ Channelrhodopsin-2 (ChR2), basically a cation-selective ion channel, also altered ChR2 descendants, anion selective channels and light-sensitive metabotropic proteins have expanded the optogenetic toolbox. However, in spite of this variety of different tools most researches still pick Channelrhodopsin-2 for their optogenetic approaches due to its well-known kinetics. In this thesis, an improved Channelrhodopsin, Channelrhodopsin2-XXM (ChR2XXM), is described, which might become an useful tool to provide ambitious neuroscientific approaches by dint of its characteristics. Here, ChR2XXM was chosen to investigate the functional consequences of Drosophila larvae lacking latrophilin in their chordotonal organs. Finally, the functionality of GtACR, was checked at the Drosophila NMJ. For a in-depth characterisation, electrophysiology along with behavioural setups was employed. In detail, ChR2XXM was found to have a better cellular expression pattern, high spatiotemporal precision, substantial increased light sensitivity and improved affinity to its chromophore retinal, as compared to ChR2. Employing ChR2XXM, effects of latrophilin (dCIRL) on signal transmission in the chordotonal organ could be clarified with a minimum of side effects, e.g. possible heat response of the chordotonal organ, due to high light sensitivity. Moreover, optogenetic activation of the chordotonal organ, in vivo, led to behavioural changes. Additionally, GtACR1 was found to be effective to inhibit motoneuronal excitation but is accompanied by unexpected side effects. These results demonstrate that further improvement and research of optogenetic tools is highly valuable and required to enable researchers to choose the best fitting optogenetic tool to address their scientific questions.
This dissertation consists of three contributions. Each addresses one specific aspect of intergenerational income mobility and is intended to be a stand-alone analysis. All chapters use comparable data for Germany and the United States to conduct country comparisons. As there are usually a large number of studies available for the United States, this approach is useful for comparing the empirical results to the existing literature.
The first part conducts a direct country comparison of the structure and extent of intergenerational income mobility in Germany and the United States. In line with existing results, the estimated intergenerational income mobility of 0.49 in the United States is significantly higher than that of 0.31 in Germany. While the results for the intergenerational rank mobility are relatively similar, the level of intergenerational income share mobility is higher in the United States than in Germany. There are no significant indications of a nonlinear run of intergenerational income elasticity. A final decomposition of intergenerational income inequality shows both greater income mobility and stronger progressive income growth for Germany compared to the United States. Overall, no clear ranking of the two countries can be identified. To conclude, several economic policy recommendations to increase intergenerational income mobility in Germany are discussed.
The second part examines the transmission channels of intergenerational income persistence in Germany and the United States. In principle, there are two ways in which well-off families may influence the adult incomes of their children: first through direct investments in their children's human capital (investment effect ), and second through the indirect transmission of human capital from parents to children (endowment effect ). In order to disentangle these two effects, a descriptive as well as a structural decomposition method are utilized. The results suggest that the investment effect and the endowment effect each account for approximately half of the estimated intergenerational income elasticity in Germany, while the investment effect is substantially more influential in the United States with a share of around 70 percent. With regard to economic policy, these results imply that equality of opportunity for children born to poor parents cannot be reached by the supply of financial means alone. Conversely, an efficient policy must additionally substitute for the missing direct transmission of human capital within socio-economically weak families.
The third part explicitly focuses on the intergenerational income mobility among daughters. The restriction to men is commonly made in the empirical literature due to women‘s lower labor market participation. While most men work full-time, the majority of (married) women still work only part-time or not at all. Especially with the occurrence of assortative mating, daughters from well-off families are likely to marry rich men and might decide to reduce their labor supply as a result. Thus, the individual labor income of a daughter might not be a good indicator for her actual economic status. The baseline regression analysis shows a higher intergenerational income elasticity in Germany and a lower intergenerational income elasticity in the United States for women as compared to men. However, a separation by marital status reveals that in both countries unmarried women exhibit a higher intergenerational income elasticity than unmarried men, while married women feature a lower intergenerational income elasticity than married men. The reason for the lower mobility of unmarried women turns out to be a stronger human capital transmission from fathers to daughters than to sons. The higher mobility of married women is driven by a weaker human capital transmission and a higher labor supply elasticity with respect to spousal income for women as compared to men. In order to further study the effects of assortative mating, the subsample of married children is analyzed by different types of income. It shows that the estimated intergenerational income elasticity of children's household incomes is even higher than that of their individual incomes. This can be seen as an indication for strong assortative mating. If household income is interpreted as a measure of children‘s actual economic welfare, there are barely any differences between sons and daughters. The intergenerational income elasticity of spousal income with respect to parental income is again relatively high, which in turn supports the hypothesis of strong assortative mating. The elasticity of the sons-in-law with respect to their fathers-in-law in Germany is even higher than that of the sons with respect to their own fathers.
The thesis provides insights in reconstruction and analysis pipelines for processing of
three-dimensional cell and vessel images of megakaryopoiesis in intact murine bone.
The images were captured in a Light Sheet Fluorescence Microscope. The work
presented here is part of Collaborative Research Centre (CRC) 688 (project B07) of
the University of Würzburg, performed at the Rudolf-Virchow Center. Despite ongoing
research within the field of megakaryopoiesis, its spatio-temporal pattern of
megakaryopoiesis is largely unknown. Deeper insight to this field is highly desirable to
promote development of new therapeutic strategies for conditions related to
thrombocytopathy as well as thrombocytopenia. The current concept of
megakaryopoiesis is largely based on data from cryosectioning or in vitro studies
indicating the existence of spatial niches within the bone marrow where specific stages
of megakaryopoiesis take place. Since classic imaging of bone sections is typically
limited to selective two-dimensional views and prone to cutting artefacts, imaging of
intact murine bone is highly desired. However, this has its own challenges to meet,
particularly in image reconstruction. Here, I worked on processing pipelines to account
for irregular specimen staining or attenuation as well as the extreme heterogeneity of
megakaryocyte morphology. Specific challenges for imaging and image reconstruction
are tackled and solution strategies as well as remaining limitations are presented and
discussed. Fortunately, modern image processing and segmentation strongly benefits
from continuous advances in hardware as well as software-development. This thesis
exemplifies how a combined effort in biomedicine, computer vision, data processing
and image technology leads to deeper understanding of megakaryopoiesis. Tailored
imaging pipelines significantly helped elucidating that the large megakaryocytes are
broadly distributed throughout the bone marrow facing a surprisingly dense vessel
network. No evidence was found for spatial niches in the bone marrow, eventually
resulting in a revised model of megakaryopoiesis.
Making machines understand natural language is a dream of mankind that existed
since a very long time. Early attempts at programming machines to converse with
humans in a supposedly intelligent way with humans relied on phrase lists and simple
keyword matching. However, such approaches cannot provide semantically adequate
answers, as they do not consider the specific meaning of the conversation. Thus, if we
want to enable machines to actually understand language, we need to be able to access
semantically relevant background knowledge. For this, it is possible to query so-called
ontologies, which are large networks containing knowledge about real-world entities
and their semantic relations. However, creating such ontologies is a tedious task, as often
extensive expert knowledge is required. Thus, we need to find ways to automatically
construct and update ontologies that fit human intuition of semantics and semantic
relations. More specifically, we need to determine semantic entities and find relations
between them. While this is usually done on large corpora of unstructured text, previous
work has shown that we can at least facilitate the first issue of extracting entities by
considering special data such as tagging data or human navigational paths. Here, we do
not need to detect the actual semantic entities, as they are already provided because of
the way those data are collected. Thus we can mainly focus on the problem of assessing
the degree of semantic relatedness between tags or web pages. However, there exist
several issues which need to be overcome, if we want to approximate human intuition of
semantic relatedness. For this, it is necessary to represent words and concepts in a way
that allows easy and highly precise semantic characterization. This also largely depends
on the quality of data from which these representations are constructed.
In this thesis, we extract semantic information from both tagging data created by users
of social tagging systems and human navigation data in different semantic-driven social
web systems. Our main goal is to construct high quality and robust vector representations
of words which can the be used to measure the relatedness of semantic concepts.
First, we show that navigation in the social media systems Wikipedia and BibSonomy is
driven by a semantic component. After this, we discuss and extend methods to model
the semantic information in tagging data as low-dimensional vectors. Furthermore, we
show that tagging pragmatics influences different facets of tagging semantics. We then
investigate the usefulness of human navigational paths in several different settings on
Wikipedia and BibSonomy for measuring semantic relatedness. Finally, we propose
a metric-learning based algorithm in adapt pre-trained word embeddings to datasets
containing human judgment of semantic relatedness.
This work contributes to the field of studying semantic relatedness between words
by proposing methods to extract semantic relatedness from web navigation, learn highquality
and low-dimensional word representations from tagging data, and to learn
semantic relatedness from any kind of vector representation by exploiting human
feedback. Applications first and foremest lie in ontology learning for the Semantic Web,
but also semantic search or query expansion.
Development and proof of concept of a biological vascularized cell‐based drug delivery system
(2019)
A major therapeutic challenge is the increasing incidence of chronic disorders.
The persistent impairment or loss of tissue function requires constitutive on‐demand
drug availability optimally achieved by a drug delivery system ideally directly connected
to the blood circulation of the patient. However, despite the efforts and achievements in
cell‐based therapies and the generation of complex and customized cell‐specific
microenvironments, the generation of functional tissue is still unaccomplished.
This study demonstrates the capability to generate a vascularized platform technology to
potentially overcome the supply restraints for graft development and clinical application
with immediate anastomosis to the blood circulation.
The ability to decellularize segments of the rat intestine while preserving the ECM for
subsequent reendothelialization was proven. The reestablishment of a functional
arteriovenous perfusion circuit enabled the supply of co‐cultured cells capable to replace
the function of damaged tissue or to serve as a drug delivery system. During in vitro
studies, the applicability of the developed miniaturized biological vascularized scaffold
(mBioVaSc‐TERM®) was demonstrated. While indicating promising results in short term
in vivo studies, long term implantations revealed current limitations for the translation
into clinical application. The gained insights will impact further improvements of quality
and performance of this promising platform technology for future regenerative therapies.
We present a theoretical study on exciton–exciton annihilation (EEA) in a molecular dimer. This process is monitored using a fifth-order coherent two-dimensional (2D) spectroscopy as was recently proposed by Dostál et al. [Nat. Commun. 9, 2466 (2018)]. Using an electronic three-level system for each monomer, we analyze the different paths which contribute to the 2D spectrum. The spectrum is determined by two entangled relaxation processes, namely, the EEA and the direct relaxation of higher lying excited states. It is shown that the change of the spectrum as a function of a pulse delay can be linked directly to the presence of the EEA process.
Cataglyphis ants are famous for their navigational abilities. They live in hostile habitats where they forage as solitary scavengers covering distances of more than hundred thousand times their body lengths. To return to their nest with a prey item – mainly other dead insects that did not survive the heat – Cataglyphis ants constantly keep track of their directions and distances travelled. The navigational strategy is called path integration, and it enables an ant to return to the nest in a straight line using its home vector. Cataglyphis ants mainly rely on celestial compass cues, like the position of the sun or the UV polarization pattern, to determine directions, and they use an idiothetic step counter and optic flow to measure distances. In addition, they acquire information about visual, olfactory and tactile landmarks, and the wind direction to increase their chances of returning to the nest safe and sound. Cataglyphis’ navigational performance becomes even more impressive if one considers their life style. Most time of their lives, the ants stay underground and perform tasks within the colony. When they start their foraging careers outside the nest, they have to calibrate their compass systems and acquire all information necessary for navigation during subsequent foraging. This navigational toolkit is not instantaneously available, but has to be filled with experience. For that reason, Cataglyphis ants perform a striking behavior for up to three days before actually foraging. These so-called learning walks are crucial for the success as foragers later on. In the present thesis, both the ontogeny and the fine-structure of learning walks has been investigated. Here I show with displacement experiments that Cataglyphis ants need enough space and enough time to perform learning walks. Spatially restricted novices, i. e. naïve ants, could not find back to the nest when tested as foragers later on. Furthermore, ants have to perform several learning walks over 1-3 days to gain landmark information for successful homing as foragers. An increasing number of feeder visits also increases the importance of landmark information, whereas in the beginning ants fully rely on their path-integration vector. Learning walks are well-structured. High-speed video analysis revealed that Cataglyphis ants include species-specific rotational elements in their learning walks. Greek Cataglyphis ants (C. noda and C. aenescens) inhabiting a cluttered pine forest perform voltes, small walked circles, and pirouettes, tight turns about the body axis with frequent stopping phases. During the longest stopping phases, the ants gaze back to their nest entrance. The Tunisian Cataglyphis fortis ants inhabiting featureless saltpans only perform voltes without directed gazes. The function of voltes has not yet been revealed. In contrast, the fine structure of pirouettes suggests that the ants take snapshots of the panorama towards their homing direction to memorize the nest’s surroundings. The most likely hypothesis was that Cataglyphis ants align the gaze directions using their path integrator, which gets directional input from celestial cues during foraging. To test this hypothesis, a manipulation experiment was performed changing the celestial cues above the nest entrance (no sun, no natural polarization pattern, no UV light). The accurately directed gazes to the nest entrance offer an easily quantifiable readout suitable to ask the ants where they expect their nest entrance. Unexpectedly, all novices performing learning walks under artificial sky conditions looked back to the nest entrance. This was especially surprising, because neuronal changes in the mushroom bodies and the central complex receiving visual input could only be induced with the natural sky when comparing test animals with interior workers. The behavioral findings indicated that Cataglyphis ants use another directional reference system to align their gaze directions during the longest stopping phases of learning walk pirouettes. One possibility was the earth’s magnetic field. Indeed, already disarraying the geomagnetic field at the nest entrance with an electromagnetic flat coil indicated that the ants use magnetic information to align their looks back to the nest entrance. To investigate this finding further, ants were confronted with a controlled magnetic field using a Helmholtz coil. Elimination of the horizontal field component led to undirected gaze directions like the disarray did. Rotating the magnetic field about 90°, 180° or -90° shifted the ants’ gaze directions in a predictable manner. Therefore, the earth’s magnetic field is a necessary and sufficient reference system for aligning nest-centered gazes during learning-walk pirouettes. Whether it is additionally used for other navigational purposes, e. g. for calibrating the solar ephemeris, remains to be tested. Maybe the voltes performed by all Cataglyphis ant species investigated so far can help to answer this question..
Energy efficiency of computing systems has become an increasingly important issue over the last decades. In 2015, data centers were responsible for 2% of the world's greenhouse gas emissions, which is roughly the same as the amount produced by air travel.
In addition to these environmental concerns, power consumption of servers in data centers results in significant operating costs, which increase by at least 10% each year.
To address this challenge, the U.S. EPA and other government agencies are considering the use of novel measurement methods in order to label the energy efficiency of servers.
The energy efficiency and power consumption of a server is subject to a great number of factors, including, but not limited to, hardware, software stack, workload, and load level.
This huge number of influencing factors makes measuring and rating of energy efficiency challenging. It also makes it difficult to find an energy-efficient server for a specific use-case. Among others, server provisioners, operators, and regulators would profit from information on the servers in question and on the factors that affect those servers' power consumption and efficiency. However, we see a lack of measurement methods and metrics for energy efficiency of the systems under consideration.
Even assuming that a measurement methodology existed, making decisions based on its results would be challenging. Power prediction methods that make use of these results would aid in decision making. They would enable potential server customers to make better purchasing decisions and help operators predict the effects of potential reconfigurations.
Existing energy efficiency benchmarks cannot fully address these challenges, as they only measure single applications at limited sets of load levels. In addition, existing efficiency metrics are not helpful in this context, as they are usually a variation of the simple performance per power ratio, which is only applicable to single workloads at a single load level. Existing data center efficiency metrics, on the other hand, express the efficiency of the data center space and power infrastructure, not focusing on the efficiency of the servers themselves. Power prediction methods for not-yet-available systems that could make use of the results provided by a comprehensive power rating methodology are also lacking. Existing power prediction models for hardware designers have a very fine level of granularity and detail that would not be useful for data center operators.
This thesis presents a measurement and rating methodology for energy efficiency of servers and an energy efficiency metric to be applied to the results of this methodology. We also design workloads, load intensity and distribution models, and mechanisms that can be used for energy efficiency testing. Based on this, we present power prediction mechanisms and models that utilize our measurement methodology and its results for power prediction.
Specifically, the six major contributions of this thesis are:
We present a measurement methodology and metrics for energy efficiency rating of servers that use multiple, specifically chosen workloads at different load levels for a full system characterization.
We evaluate the methodology and metric with regard to their reproducibility, fairness, and relevance. We investigate the power and performance variations of test results and show fairness of the metric through a mathematical proof and a correlation analysis on a set of 385 servers. We evaluate the metric's relevance by showing the relationships that can be established between metric results and third-party applications.
We create models and extraction mechanisms for load profiles that vary over time, as well as load distribution mechanisms and policies. The models are designed to be used to define arbitrary dynamic load intensity profiles that can be leveraged for benchmarking purposes. The load distribution mechanisms place workloads on computing resources in a hierarchical manner.
Our load intensity models can be extracted in less than 0.2 seconds and our resulting models feature a median modeling error of 12.7% on average. In addition, our new load distribution strategy can save up to 10.7% of power consumption on a single server node.
We introduce an approach to create small-scale workloads that emulate the power consumption-relevant behavior of large-scale workloads by approximating their CPU performance counter profile, and we introduce TeaStore, a distributed, micro-service-based reference application. TeaStore can be used to evaluate power and performance model accuracy, elasticity of cloud auto-scalers, and the effectiveness of power saving mechanisms for distributed systems.
We show that we are capable of emulating the power consumption behavior of realistic workloads with a mean deviation less than 10% and down to 0.2 watts (1%). We demonstrate the use of TeaStore in the context of performance model extraction and cloud auto-scaling also showing that it may generate workloads with different effects on the power consumption of the system under consideration.
We present a method for automated selection of interpolation strategies for performance and power characterization. We also introduce a configuration approach for polynomial interpolation functions of varying degrees that improves prediction accuracy for system power consumption for a given system utilization.
We show that, in comparison to regression, our automated interpolation method selection and configuration approach improves modeling accuracy by 43.6% if additional reference data is available and by 31.4% if it is not.
We present an approach for explicit modeling of the impact a virtualized environment has on power consumption and a method to predict the power consumption of a software application. Both methods use results produced by our measurement methodology to predict the respective power consumption for servers that are otherwise not available to the person making the prediction.
Our methods are able to predict power consumption reliably for multiple hypervisor configurations and for the target application workloads. Application workload power prediction features a mean average absolute percentage error of 9.5%.
Finally, we propose an end-to-end modeling approach for predicting the power consumption of component placements at run-time. The model can also be used to predict the power consumption at load levels that have not yet been observed on the running system.
We show that we can predict the power consumption of two different distributed web applications with a mean absolute percentage error of 2.2%. In addition, we can predict the power consumption of a system at a previously unobserved load level and component distribution with an error of 1.2%.
The contributions of this thesis already show a significant impact in science and industry. The presented efficiency rating methodology, including its metric, have been adopted by the U.S. EPA in the latest version of the ENERGY STAR Computer Server program. They are also being considered by additional regulatory agencies, including the EU Commission and the China National Institute of Standardization. In addition, the methodology's implementation and the underlying methodology itself have already found use in several research publications.
Regarding future work, we see a need for new workloads targeting specialized server hardware. At the moment, we are witnessing a shift in execution hardware to specialized machine learning chips, general purpose GPU computing, FPGAs being embedded into compute servers, etc. To ensure that our measurement methodology remains relevant, workloads covering these areas are required. Similarly, power prediction models must be extended to cover these new scenarios.
The attitude and orbit control system of pico- and nano-satellites to date is one of the bottle necks for future scientific and commercial applications. A performance increase while keeping with the satellites’ restrictions will enable new space missions especially for the smallest of the CubeSat classes. This work addresses methods to measure and improve the satellite’s attitude pointing and orbit control performance based on advanced sensor data analysis and optimized on-board software concepts. These methods are applied to spaceborne satellites and future CubeSat missions to demonstrate their validity. An in-orbit calibration procedure for a typical CubeSat attitude sensor suite is developed and applied to the UWE-3 satellite in space. Subsequently, a method to estimate the attitude determination accuracy without the help of an external reference sensor is developed. Using this method, it is shown that the UWE-3 satellite achieves an in-orbit attitude determination accuracy of about 2°.
An advanced data analysis of the attitude motion of a miniature satellite is used in order to estimate the main attitude disturbance torque in orbit. It is shown, that the magnetic disturbance is by far the most significant contribution for miniature satellites and a method to estimate the residual magnetic dipole moment of a satellite is developed. Its application to three CubeSats currently in orbit reveals that magnetic disturbances are a common issue for this class of satellites. The dipole moments measured are between 23.1mAm² and 137.2mAm². In order to autonomously estimate and counteract this disturbance in future missions an on-board magnetic dipole estimation algorithm is developed.
The autonomous neutralization of such disturbance torques together with the simplification of attitude control for the satellite operator is the focus of a novel on-board attitude control software architecture. It incorporates disturbance torques acting on the satellite and automatically optimizes the control output. Its application is demonstrated in space on board of the UWE-3 satellite through various attitude control experiments of which the results are presented here.
The integration of a miniaturized electric propulsion system will enable CubeSats to perform orbit control and, thus, open up new application scenarios. The in-orbit characterization, however, poses the problem of precisely measuring very low thrust levels in the order of µN. A method to measure this thrust based on the attitude dynamics of the satellite is developed and evaluated in simulation. It is shown, that the demonstrator mission UWE-4 will be able to measure these thrust levels with a high accuracy of 1% for thrust levels higher than 1µN.
The orbit control capabilities of UWE-4 using its electric propulsion system are evaluated and a hybrid attitude control system making use of the satellite’s magnetorquers and the electric propulsion system is developed. It is based on the flexible attitude control architecture mentioned before and thrust vector pointing accuracies of better than 2° can be achieved. This results in a thrust delivery of more than 99% of the desired acceleration in the target direction.
The aim of this thesis was the application of the functional prepolymer NCO-sP(EO-stat-PO) for the development of new biomaterials. First, the influence of the star-shaped polymers on the mechanical properties of biocements and bone adhesives was investigated. 3-armed star-shaped macromers were used as an additive for a mineral bone cement, and the influence on the mechanical properties was studied. Additionally, a previously developed bone adhesive was examined regarding cytocompatibility. The second topic was the examination of novel functionalization steps which were performed on the surface of electrospun fibers modified with NCO-sP(EO-stat-PO). This established method of functionalizing electrospun meshes was advanced regarding the modification with proteins which was then demonstrated in a biological application. Two different kinds of antibodies were immobilized on the fiber surface in a consecutive manner and the influence of these proteins on the cell behavior was investigated. The final topic involved the quantification of surface-bound peptide sequences. By functionalization of the peptides with the UV-reactive molecule 2-mercaptopyridine it was possible to quantify this compound via UV measurements by cleavage of disulfide bridges and indirectly draw conclusions about the number of immobilized peptides.
In the field of mineral biocements and bone adhesives, NCO-sP(EO-stat-PO) was able to influence the setting behavior and mechanical performance of mineral bone cements based on calcium phosphate chemistry. The addition of NCO-sP(EO-stat-PO) resulted in a pseudo-ductile fracture behavior due to the formation of a hydrogel network in the cement, which was then mineralized by nanosized hydroxyapatite crystals following cement setting. Accordingly, a commercially available aluminum silicate cement from civil engineering could be modified.
In addition, it could be shown that the use of NCO-sP(EO-stat-PO) is beneficial for adjusting specific material properties of bone adhesives. Here, the crosslinking behavior of the prepolymer in an aqueous medium was exploited to form an interpenetrating network (IPN) together with a photochemically curing poly(ethylene glycol) dimethacrylate (PEGDMA) matrix. This could be used for the development of a bone adhesive with an improved adhesion to bone in a wet environment. The developed bone adhesive was further investigated in terms of possible influences of the initiator systems. In addition, the material system was tested for cytocompatibility by using different cell lines.
Moreover, the preparation of electrospun fiber meshes via solution electrospinning consisting of poly(lactide-co-glycolide) (PLGA) as a backbone polymer and NCO-sP(EO-stat-PO) as functional additive is an established method for the application of the meshes as a replacement of the native extracellular matrix (ECM). In general, these fibers reveal diameters in the nanometer range, are protein and cell repellent due to the hydrophilic properties of the prepolymer and show a specific biofunctionalization by immobilization of peptide sequences. Here, the isocyanate groups presented on the fiber surface after electrospinning were used to carry out various functionalization steps, while retaining the properties of protein and cell repellency. The modification of the electrospun fibers involved the immobilization of analogs or antagonists of tumor necrosis factor (TNF) and the indirect detection of these by interaction with a light-producing enzyme. Here, a multimodal modification of the fiber surface with RGD to mediate cell adhesion and two different antibodies could be achieved. After culturing the cell line HT1080, the pro- or anti-inflammatory response of cells could be detected by IL-8 specific ELISA measurements.
Furthermore, the quantification of molecules on the surface of electrospun fibers was investigated. It was tested whether the detection by means of super-resolution microscopy would be possible. Therefore, experiments were performed with short amino acid sequences such as RGD for quantification by fluorescence microscopy. Based on earlier results, in which a UV-spectrometrically active molecule was used to detect the quantification of RGD, it was shown that short peptides can also be quantified in a small scale on flat functional substrates (2D) such as NCO-sP(EO-stat-PO) hydrogel coatings, and modified electrospun fibers produced from PLGA and NCO-sP(EO-stat-PO) (3D). In addition, a collagen sequence was used to prove that a successful quantification can be carried out as well for longer peptide chains.
These studies have revealed that NCO-sP(EO-stat-PO) can serve as a functional additive for many applications and should be considered for further studies on the development of novel biomaterials. The rapid crosslinking reaction, the resulting hydrogel formation and the biocompatibility are to be mentioned as positive properties, which makes the prepolymer interesting for future applications.
The present thesis describes the development of a strategy to create discrete finite-sized supramolecular stacks of merocyanine dyes. Thus, bichromophoric stacks of two identical or different chromophores could be realized by folding of bis(merocyanine) dyes and their optical properties were discussed in terms of exciton theory. Quantum chemical calculations revealed strong exciton coupling between the chromophores within the homo- and hetero-π-stacks and the increase of the J-band of the hetero-dimers with increasing energy difference between the excited states of the chromophores could be attributed not only to the different magnitudes of transition dipole moments of the chromophores but also to the increased localization of the excitation in the respective exciton state. Furthermore, careful selection of the length of the spacer unit that defines the interplanar distance between the tethered chromophores directed the self-assembly of the respective bis(merocyanines) into dimers, trimers and tetramers comprising large, structurally precise π-stacks of four, six or eight merocyanine chromophores. It could be demonstrated that the structure of such large supramolecular architectures can be adequately elucidated by commonly accessible analysis tools, in particular NMR techniques in combination with UV/vis measurements and mass spectrometry. Supported by TDDFT calculations, the absorption spectra of the herein investigated aggregates could be explained and a relationship between the absorption properties and the number of stacking chromophores could be established based on exciton theory.
Mechanistic Insights into the Inhibition of Cathepsin B and Rhodesain with Low-Molecular Inhibitors
(2019)
Cysteine proteases play a crucial role in medical chemistry concerning various fields reaching from more common ailments like cancer and hepatitis to less noted tropical diseases, namely the so-called African Sleeping Sickness (Human Arfican Trypanosomiasis). Detailed knowledge about the catalytic function of these systems is highly desirable for drug research in the respective areas. In this work, the inhibition mechanisms of the two cysteine proteases cathepsin B and rhodesain with respectively one low-molecular inhibitor class were investigated in detail, using computational methods. In order to sufficiently describe macromolecular systems, molecular mechanics based methods (MM) and quantum mechanical based method (QM), as well as hybrid methods (QM/MM) combining those two approaches, were applied.
For Cathespin B, carbamate-based molecules were investigated as potential inhibitors for the cysteine protease. The results indicate, that water-bridged proton-transfer reactions play a crucial role for the inhibition. The energetically most favoured pathway (according to the calculations) includes an elimination reaction following an E1cB mechanism with a subsequent carbamylation of the active site amino acid cysteine.
Nitroalkene derivatives were investigated as inhibitors for rhodesain. The investigation of structurally similar inhibitors showed, that even small steric differences can crucially influence the inhibition potential of the components. Furthermore, the impact of a fluorination of the nitroalkene inhibitors on the inhibition mechanism was investigated. According to experimental data measured from the working group of professor Schirmeister in Mainz, fluorinated nitroalkenes show – in contrast to the unfluorinated compounds – a time dependent inhibition efficiency. The calculations of the systems indicate, that the fluorination impacts the non-covalent interactions of the inhibitors with the enzymatic environment of the enzyme which results in a different inhibition behaviour.
The measurement of the mass of the $W$ boson is currently one of the most promising precision analyses of the Standard Model, that could ultimately reveal a hint for new physics.
The mass of the $W$ boson is determined by comparing the $W$ boson, which cannot be reconstructed directly, to the $Z$ boson, where the full decay signature is available. With the help of Monte Carlo simulations one can extrapolate from the $Z$ boson to the $W$ boson.
Technically speaking, the measurement of the $W$ boson mass is performed by comparing data taken by the ATLAS experiment to a set of calibrated Monte Carlo simulations, which reflect different mass hypotheses.\
A dedicated calibration of the reconstructed objects in the simulations is crucial for a high precision of the measured value.
The comparison of simulated $Z$ boson events to reconstructed $Z$ boson candidates in data allows to derive event weights and scale factors for the calibration.
This thesis presents a new approach to reweight the hadronic recoil in the simulations. The focus of the calibration is on the average hadronic activity visible in the mean of the scalar sum of the hadronic recoil $\Sigma E_T$ as a function of pileup. In contrast to the standard method, which directly reweights the scalar sum, the dependency to the transverse boson momentum is less strongly affected here.
The $\Sigma E_T$ distribution is modeled first by means of its pileup dependency. Then, the remaining differences in the resolution of the vector sum of the hadronic recoil are scaled. This is done separately for the parallel and the pterpendicular component of the hadronic recoil with respect to the reconstructed boson.
This calibration was developed for the dataset taken by the ATLAS experiment at a center of mass energy of $8\,\textrm{TeV}$ in 2012. In addition, the same reweighting procedure is applied to the recent dataset with a low pileup contribution, the \textit{lowMu} runs at $5\,\textrm{TeV}$ and at $13\,\textrm{TeV}$, taken by ATLAS in November 2017. The dedicated aspects of the reweighting procedure are presented in this thesis. It can be shown that this reweighting approach improves the agreement between data and the simulations effectively for all datasets.
The uncertainties of this reweighting approach as well as the statistical errors are evaluated for a $W$ mass measurement by a template fit to pseudodata for the \textit{lowMu} dataset. A first estimate of these uncertainties is given here. For the pfoEM algorithm a statistical uncertainty of $17\,\text{MeV}$ for the $5\,\textrm{TeV}$ dataset and of $18\,\text{MeV}$ for the $13\,\textrm{TeV}$ are found for the $W \rightarrow \mu \nu$ analysis. The systematic uncertainty introduced by the resolution scaling has the largest effect, a value of $15\,\text{MeV}$ is estimated for the $13\,\textrm{TeV}$ dataset in the muon channel.
The present dissertation investigates the management of RFID implementations in retail trade. Our work contributes to this by investigating important aspects that have so far received little attention in scientific literature. We therefore perform three studies about three important aspects of managing RFID implementations. We evaluate in our first study customer acceptance of pervasive retail systems using privacy calculus theory. The results of our study reveal the most important aspects a retailer has to consider when implementing pervasive retail systems. In our second study we analyze RFID-enabled robotic inventory taking with the help of a simulation model. The results show that retailers should implement robotic inventory taking if the accuracy rates of the robots are as high as the robots’ manufacturers claim. In our third and last study we evaluate the potentials of RFID data for supporting managerial decision making. We propose three novel methods in order to extract useful information from RFID data and propose a generic information extraction process. Our work is geared towards practitioners who want to improve their RFID-enabled processes and towards scientists conducting RFID-based research.
Sensitivity and selectivity remain the central technical requirement for analytical devices, detectors and sensors. Especially in the gas phase, concentrations of threat substances can be very low (e.g. explosives) or have severe effects on health even at low concentrations (e.g. benzene) while it contains many potential interferents. Preconcentration, facilitated by active or passive sampling of air by an adsorbent, followed by thermal desorption, results in these substances being released in a smaller volume, effectively increasing their concentration.
Traditionally, a wide range of adsorbents, such as active carbons or porous polymers, are used for preconcentration. However, many adsorbents either show chemical reactions due to active surfaces, serious water retention or high background emission due to thermal instability. Metal-organic frameworks (MOFs) are a hybrid substance class, composed inorganic and organic building blocks, being a special case of coordination polymers containing pores. They can be tailored for specific applications such as gas storage, separation, catalysis, sensors or drug delivery.
This thesis is focused on investigating MOFs for their use in thermal preconcentration for airborne detection systems. A pre-screening method for MOF-adsorbate interactions was developed and applied, namely inverse gas chromatography (iGC). Using this pulse chromatographic method, the interaction of MOFs and molecules from the class of explosives and volatile organic compounds was studied at different temperatures and compared to thermal desorption results.
In the first part, it is shown that archetype MOFs (HKUST-1, MIL-53 and Fe-BTC) outperformed the state-of-the-art polymeric adsorbent Tenax® TA in nitromethane preconcentration for a 1000 (later 1) ppm nitromethane source. For HKUST-1, a factor of more than 2000 per g of adsorbent was achieved, about 100 times higher than for Tenax. Thereby, a nitromethane concentration of 1 ppb could be increased to 2 ppm. High enrichment is addressed to the specific interaction of the nitro group as by iGC, which was determined by comparing nitromethane’s free enthalpy of adsorption with the respective saturated alkane. Also, HKUST-1 shows a similar mode of sorption (enthalpy-entropy compensation) for nitro and saturated alkanes.
In the second part, benzene of 1 ppm of concentration was enriched with a similar setup, using 2nd generation MOFs, primarily UiO-66 and UiO-67, under dry and humid (50 %rH) conditions using constant sampling times. Not any MOF within the study did surpass the polymeric Tenax in benzene preconcentration. This is most certainly due to low sampling times – while Tenax may be highly saturated after 600 s, MOFs are not. For regular UiO-66, four differently synthesized samples showed a strongly varying behavior for dry and humid enrichment which cannot be completely explained. iGC investigations with regular alkanes and BTEX compounds revealed that confinement factors and dispersive surface energy were different for all UiO-66 samples. Using physicochemical parameters from iGC, no unified hypothesis explaining all variances could be developed.
Altogether, it was shown that MOFs can replace or add to state-of-the-art adsorbents for the enrichment of specific analytes with preconcentration being a universal sensitivity-boosting concept for detectors and sensors. Especially with iGC as a powerful screening tool, most suitable MOFs for the respective target analyte can be evaluated. iGC can be used for determining “single point” retention volumes, which translate into partition coefficients for a specific MOF × analyte × temperature combination.