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Institute
- Institut für Physik und Astronomie (28)
- Institut für Biochemie und Biologie (27)
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Be Creative, Now!
(2018)
Purpose – This thesis set out to explore, describe, and evaluate the reality behind the rhetoric of freedom and control in the context of creativity. The overarching subject is concerned with the relationship between creativity, freedom, and control, considering freedom is also seen as an element of control to manage creativity.
Design/methodology/approach – In-depth qualitative data gathered from at two innovative start-ups. Two ethnographic studies were conducted. The data are based on participatory observations, interviews, and secondary sources, each of which included a three months field study and a total of 41 interviews from both organizations.
Findings – The thesis provides explanations for the practice of freedom and the control of creativity within organizations and expands the existing theory of neo-normative control. The findings indicate that organizations use complex control systems that allow a high degree of freedom that paradoxically leads to more control. Freedom is a cover of control, which in turn leads to creativity. Covert control even results in the responsibility to be creative outside working hours.
Practical implications – Organizations, which rely on creativity might use the results of this thesis. Positive workplace control of creativity provides both freedom and structure for creative work. While freedom leads to organizational members being more motivated and committing themselves more strongly to their and the organization’s goals, and a specific structure also helps to provide the requirements for creativity.
Originality/value – The thesis provides an insight into an approach to workplace control, which has mostly neglected in creativity research and proposes a modified concept of neo-normative control. It serves to provide a further understanding of freedom for creativity and to challenge the liberal claims of new control forms.
The aim of this doctoral thesis was to establish a technique for the analysis of biomolecules with infrared matrix-assisted laser dispersion (IR-MALDI) ion mobility (IM) spectrometry. The main components of the work were the characterization of the IR-MALDI process, the development and characterization of different ion mobility spectrometers, the use of IR-MALDI-IM spectrometry as a robust, standalone spectrometer and the development of a collision cross-section estimation approach for peptides based on molecular dynamics and thermodynamic reweighting.
First, the IR-MALDI source was studied with atmospheric pressure ion mobility spectrometry and shadowgraphy. It consisted of a metal capillary, at the tip of which a self-renewing droplet of analyte solution was met by an IR laser beam. A relationship between peak shape, ion desolvation, diffusion and extraction pulse delay time (pulse delay) was established. First order desolvation kinetics were observed and related to peak broadening by diffusion, both influenced by the pulse delay. The transport mechanisms in IR-MALDI were then studied by relating different laser impact positions on the droplet surface to the corresponding ion mobility spectra. Two different transport mechanisms were determined: phase explosion due to the laser pulse and electrical transport due to delayed ion extraction. The velocity of the ions stemming from the phase explosion was then measured by ion mobility and shadowgraphy at different time scales and distances from the source capillary, showing an initially very high but rapidly decaying velocity. Finally, the anatomy of the dispersion plume was observed in detail with shadowgraphy and general conclusions over the process were drawn.
Understanding the IR-MALDI process enabled the optimization of the different IM spectrometers at atmospheric and reduced pressure (AP and RP, respectively). At reduced pressure, both an AP and an RP IR-MALDI source were used. The influence of the pulsed ion extraction parameters (pulse delay, width and amplitude) on peak shape, resolution and area was systematically studied in both AP and RP IM spectrometers and discussed in the context of the IR-MALDI process. Under RP conditions, the influence of the closing field and of the pressure was also examined for both AP and RP sources. For the AP ionization RP IM spectrometer, the influence of the inlet field (IF) in the source region was also examined. All of these studies led to the determination of the optimal analytical parameters as well as to a better understanding of the initial ion cloud anatomy.
The analytical performance of the spectrometer was then studied. Limits of detection (LOD) and linear ranges were determined under static and pulsed ion injection conditions and interpreted in the context of the IR-MALDI mechanism. Applications in the separation of simple mixtures were also illustrated, demonstrating good isomer separation capabilities and the advantages of singly charged peaks. The possibility to couple high performance liquid chromatography (HPLC) to IR-MALDI-IM spectrometry was also demonstrated. Finally, the reduced pressure spectrometer was used to study the effect of high reduced field strength on the mobility of polyatomic ions in polyatomic gases.
The last focus point was on the study of peptide ions. A dataset obtained with electrospray IM spectrometry was characterized and used for the calibration of a collision cross-section (CCS) determination method based on molecular dynamics (MD) simulations at high temperature. Instead of producing candidate structures which are evaluated one by one, this semi-automated method uses the simulation as a whole to determine a single average collision cross-section value by reweighting the CCS of a few representative structures. The method was compared to the intrinsic size parameter (ISP) method and to experimental results. Additional MD data obtained from the simulations was also used to further analyze the peptides and understand the experimental results, an advantage with regard to the ISP method. Finally, the CCS of peptide ions analyzed by IR-MALDI were also evaluated with both ISP and MD methods and the results compared to experiment, resulting in a first validation of the MD method. Thus, this thesis brings together the soft ionization technique that is IR-MALDI, which produces mostly singly charged peaks, with ion mobility spectrometry, which can distinguish between isomers, and a collision cross-section determination method which also provides structural information on the analyte at hand.
Systemic inflammation is a hallmark of cancer cachexia. Among tumor-host interactions, the white adipose tissue (WAT) is an important contributor to inflammation as it suffers morphological reorganization and lipolysis, releasing free fatty acids (FA), bioactive lipid mediators (LM) and pro-inflammatory cytokines, which accentuate the activation of pro-inflammatory signaling pathways and the recruitment of immune cells to the tissue. This project aimed to investigate which inflammatory factors are involved in the local adipose tissue inflammation and what is the influence of such factors upon enzymes involved in FA or LM metabolism in healthy individuals (Control), weight stable gastro-intestinal cancer patients (WSC) and cachectic cancer patients (CC). The results demonstrated that the inflammatory signature of systemic inflammation is different from local adipose tissue inflammation. The systemic inflammation of the cachectic cancer patients was characterized by higher levels of circulating saturated fatty acids (SFA), tumor-necrosis-factor-α (TNF-α), interleukins IL-6, IL-8 and CRP while levels of polyunsaturated fatty acids (PUFAs), especially n3-PUFAs, were lower in CC than in the other groups. In vitro and in adipose tissue explants, pro-inflammatory cytokines and SFAs were shown to increase the chemokines IL-8 and CXCL10 that were found to be augmented in adipose tissue inflammation in CC which was more profound in the visceral adipose tissue (VAT) than in subcutaneous adipose tissue (SAT). Systemic inflammation was negatively associated with the expression of PUFA synthesizing enzymes, though gene and protein expression did hardly differ between groups. The effects of inflammatory factors on enzymes in the whole tissue could have been masked by differentiated modulation of the diverse cell types in the same tissue. In vitro experiments showed that the expression of FA-modifying enzymes such as desaturases and elongases in adipocytes and macrophages was regulated into opposing directions by TNF-α, IL-6, LPS or palmitate. The higher plasma concentration of the pro-resolving LM resolvin D1 in CC cannot compensate the overall inflammatory status and the results indicate that inflammatory cytokines interfere with synthesis pathways of pro-resolving LM. In summary, the data revealed a complex inter-tissue and inter-cellular crosstalk mediated by pro-inflammatory cytokines and lipid compounds enhancing inflammation in cancer cachexia by feed-forward mechanisms.
The solar activity and its consequences affect space weather and Earth’s climate. The solar activity exhibits a cyclic behaviour with a period of about 11 years. The solar cycle properties are governed by the dynamo taking place in the interior of the Sun, and they are distinctive. Extending the knowledge about solar cycle properties into the past is essential for understanding the solar dynamo and forecasting space weather. It can be acquired through the analysis of historical sunspot drawings. Sunspots are the dark areas, which are associated with strong magnetic fields, on the solar surface. Sunspots are the oldest and longest available observed features of solar activity.
One of the longest available records of sunspot drawings is the collection by Samuel Heinrich Schwabe during 1825–1867. The sunspot sizes measured from digitized Schwabe drawings are not to scale and need to be converted into physical sunspot areas. We employed a statistical approach assuming that the area distribution of sunspots was the same in the 19th century as it was in the 20th century. Umbral areas for about 130 000 sunspots observed by Schwabe were obtained. The annually averaged sunspot areas correlate reasonably well with the sunspot number. Tilt angles and polarity separations of sunspot groups were calculated assuming them to be bipolar. There is, of course, no polarity information in the observations. We derived an average tilt angle by attempting to exclude unipolar groups with a minimum separation of the two surmised polarities and an outlier rejection method, which follows the evolution of each group and detects the moment, when it turns unipolar as it decays. As a result, the tilt angles, although displaying considerable natural scatter, are on average 5.85° ± 0.25°, with the leading
polarity located closer to the equator, in good agreement with tilt angles obtained from 20th century data sets. Sources of uncertainties in the tilt angle determination are discussed and need to be addressed whenever different data sets are combined.
Digital images of observations printed in the books Rosa Ursina and Prodromus pro sole mobili by Christoph Scheiner, as well as the drawings from Scheiner’s letters to Marcus Welser, are analyzed to obtain information on the positions and sizes of sunspots that appeared before the Maunder minimum. In most cases, the given orientation of the ecliptic is used to set up the heliographic coordinate system for the drawings. Positions and sizes are measured manually displaying the drawings on a computer screen. Very early drawings have no indication of the solar orientation. A rotational matching using common spots of adjacent days is used in some cases, while in other cases, the assumption that images were aligned with a zenith–horizon coordinate system appeared to be the most likely. In total, 8167 sunspots were measured. A distribution of sunspot latitudes versus time (butterfly diagram) is obtained for Scheiner’s observations. The observations of 1611 are very inaccurate, but the drawings of 1612 have at least an indication of the solar orientation, while the remaining part of the spot positions from 1618–1631 have good to very good accuracy. We also computed 697 tilt angles of apparent bipolar sunspot groups, which were observed in the period 1618–1631. We find that the average tilt angle of nearly 4° does not significantly differ from the 20th century values.
The solar cycle properties seem to be related to the tilt angles of sunspot groups, and it is an important parameter in the surface flux transport models. The tilt angles of bipolar sunspot groups from various historical sets of solar drawings including from Schwabe and Scheiner are analyzed. Data by Scheiner, Hevelius, Staudacher, Zucconi, Schwabe, and Spörer deliver a series of average tilt angles spanning a period of 270 years, in addition to previously found values for 20th-century data obtained by other authors. We find that the average tilt angles before the Maunder minimum were not significantly different from modern values. However, the average tilt angles of a period 50 years after the Maunder minimum, namely for cycles 0 and 1, were much lower and near zero. The typical tilt angles before the Maunder minimum suggest that abnormally low tilt angles were not responsible for driving the solar cycle into a grand minimum.
With the Schwabe (1826–1867) and Spörer (1866–1880) sunspot data, the butterfly diagram of sunspot groups extends back till 1826. A recently developed method, which separates the wings of the butterfly diagram based on the long gaps present in sunspot group occurrences at different latitudinal bands, is used to separate the wings of the butterfly diagram. The cycle-to-cycle variation in the start (F), end (L), and highest (H) latitudes of the wings with respect to the strength of the wings are analyzed. On the whole, the wings of the stronger cycles tend to start at higher latitudes and have a greater extent. The time spans of the wings and the time difference between the wings in the northern hemisphere display a quasi-periodicity of 5–6 cycles. The average wing overlap is zero in the southern hemisphere, whereas it is 2–3 months in the north. A marginally significant oscillation of about 10 solar cycles is found in the asymmetry of the L latitudes. This latest, extended database of butterfly wings provides new observational constraints, regarding the spatio-temporal distribution of sunspot occurrences over the solar cycle, to solar dynamo models.
This thesis investigates the comprehension of the passive voice in three distinct populations. First, the comprehension of passives by adult German speakers was studied, followed by an examination of how German-speaking children comprehend the structure. Finally, bilingual Mandarin-English speakers were tested on their comprehension of the passive voice in English, which is their L2. An integral part of testing the comprehension in all three populations is the use of structural priming. In each of the three distinct parts of the research, structural priming was used for a specific reason. In the study involving adult German speakers, productive and receptive structural priming was directly compared. The goal was to see the effect the two priming modalities have on language comprehension. In the study on German-acquiring children, structural priming was an important tool in answering the question regarding the delayed acquisition of the passive voice. Finally, in the study on the bilingual population, cross-linguistic priming was used to investigate the importance of word order in the priming effect, since Mandarin and English have different word orders in passive voice sentences.
Modeling and data analysis of large-scale atmosphere dynamics associated with extreme weather
(2018)
In the last decades the frequency and intensity of extreme weather events like heat waves and heavy rainfall have increased and are at least partly linked to global warming. These events can have a strong impact on agricultural and economic production and, thereby, on society. Thus, it is important to improve our understanding of the physical processes leading to those extreme events in order to provide accurate near-term and long-term forecasts. Thermodynamic drivers associated with global warming are well understood, but dynamical aspects of the atmosphere much less so. The dynamical aspects, while less important than the thermodynamic drivers in regards to large-scale and long-time averaged effects, play a critical role in the formation of extremes.
The overall aim of this thesis is to improve our understanding of patterns, variability and trends in the global atmospheric circulation under a changing climate. In particular, in this dissertation I developed two new data-driven methods to quantitatively describe the dynamics of jet streams, Hadley cells and storm tracks. In addition, I introduce and validate a new statistical-dynamical atmosphere model that can be used to efficiently model the large-scale circulation.
First, I developed a scheme based on the Dijkstra ‘shortest-path’ algorithm to identify jet stream cores. Using reanalysis data, I found a significant change in jet stream strength and position over the last decades: Specifically, a decrease in wind speeds and a spatial shift toward the poles. This work also shows that the splitting or merging of the polar front jet stream and the subtropical jet stream depends on the season and longitudinal position. In a follow-up study, I analyzed trends in the latitudinal position of the poleward edge of the Hadley cell and subtropical jet stream core for all longitudes. These trends depend strongly on longitude and thus the impacts of tropical expansion might be pronounced in some regions and absent in others.
The second approach was to develop an empirical forecast method for European and Mediterranean winter precipitation. This prediction algorithm innovatively incorporates the spatial patterns of predictors in autumn using clustering analyses. I identified the most important precursors (snow cover in Eurasia, Barents and Kara sea ice concentrations as well as sea surface temperature in the Atlantic and Mediterranean region) for the precipitation prediction. This forecast algorithm had higher forecast skills than conventionally employed methods such as Canonical Correlation Analysis or operational systems using climate models.
The last approach was to examine the atmospheric circulation using the novel statisticaldynamical atmosphere model Aeolus. First, I validated the model’s depiction of the largescale circulation in terms of Hadley circulation, jet streams, storm tracks and planetary waves. To do so, I performed a parameter optimization using simulated annealing. Next, I investigated the sensitivity of the large-scale circulation to three different temperature components: global mean temperature, meridional temperature gradient and zonal temperature gradient. The model experiment showed that the strength of the Hadley cell, storm tracks and jet streams depend almost linearly on both the global mean temperature and the meridional temperature gradient, whereas the zonal temperature gradient is shown to have little or no influence. The magnitude of planetary waves is clearly affected by all three temperature components. Finally, the width of the Hadley cell behaves nonlinearly with respect to all three temperature components.
These findings might have profound consequences for climate modeling of the Mediterranean region. The latitudinal poleward trend of the Hadley cell edge position might become stronger under climate change according to the results with Aeolus. These changes would lead to a substantial reduction of the winter precipitation in the Mediterranean region. In this case seasonal empirical forecast methods, like the clustering-based prediction scheme, will play an important role for forecasting seasonal droughts in advance such that water managers and politicians can mitigate impacts.
The ongoing trend of miniaturizing multifunctional devices, especially for minimally-invasive medical or sensor applications demands new strategies for designing the required functional polymeric micro-components or micro-devices. Here, polymers, which are capable of active movement, when an external stimulus is applied (e.g. shape-memory polymers), are intensively discussed as promising material candidates for realization of multifunctional micro-components. In this context further research activities are needed to gain a better knowledge about the underlying working principles for functionalization of polymeric micro-scale objects with a shape-memory effect. First reports about electrospun solid microfiber scaffolds, demonstrated a much more pronounced shape-memory effect than their bulk counterparts, indicating the high potential of electrospun micro-objects.
Based on these initial findings this thesis was aimed at exploring whether the alteration of the geometry of micro-scale electrospun polymeric objects can serve as suitable parameter to tailor their shape-memory properties. The central hypothesis was that different geometries should result in different degrees of macromolecular chain orientation in the polymeric micro-scale objects, which will influence their mechanical properties as well as thermally-induced shape-memory function. As electrospun micro-scale objects, microfiber scaffolds composed of hollow microfibers with different wall thickness and electrosprayed microparticles as well as their magneto-sensitive nanocomposites all prepared from the same polymer exhibiting pronounced bulk shape-memory properties were investigated. For this work a thermoplastic multiblock copolymer, named PDC, with excellent bulk shape-memory properties, associated with crystallizable oligo(ε-caprolactone) (OCL) switching domains, was chosen for the preparation of electrospun micro-scale objects, while crystallizable oligo(p-dioxanone) (OPDO) segments serve as hard domains in PDC.
In the first part of the thesis microfiber scaffolds with different microfiber geometries (solid or hollow with different wall thickness) were discussed. Hollow microfiber based PDC scaffolds were prepared by coaxial electrospinning from a 1, 1, 1, 3, 3, 3 hexafluoro-2-propanol (HFP) solution with a polymer concentration of 13% w·v-1. Here as a first step core-shell fiber scaffolds consisting of microfibers with a PDC shell and sacrificial poly(ethylene glycol) (PEG) core are generated. The hollow PDC microfibers were achieved after dissolving the PEG core with water. The utilization of a fixed electrospinning setup and the same polymer concentration of the PDC spinning solution could ensure the fabrication of microfibers with almost identical outer diameters of 1.4 ± 0.3 µm as determined by scanning electron microscopy (SEM). Different hollow microfiber wall thicknesses of 0.5 ± 0.2 and 0.3 ± 0.2 µm (analyzed by SEM) have been realized by variation of the mass flow rate, while solid microfibers were obtained by coaxial electrospinning without supplying any core solution. Differential scanning calorimetry experiments and tensile tests at ambient temperature revealed an increase in degree of OCL crystallinity form χc,OCL = 34 ± 1% to 43 ± 1% and a decrease in elongation of break from 800 ± 40% to 200 ± 50% associated with an increase in Young´s modulus and failture stress for PDC hollow microfiber scaffolds when compared with soild fibers. The observed effects were enhanced with decreasing wall thickness of the single hollow fibers. The shape-memory properties of the electrospun PDC scaffolds were quantified by cyclic, thermomechanical tensile tests. Here, scaffolds comprising hollow microfibers exhibited lower shape fixity ratios around Rf = 82 ± 1% and higher shape recovery ratios of Rr = 67 ± 1% associated to more pronounced relaxation at constant strain during the first test cycle and a lower switching temperature of Tsw = 33 ± 1 °C than the fibrous meshes consisting of solid microfibers. These findings strongly support the central hypothesis that different fiber geometries (solid or hollow with different wall thickness) in electrospun scaffolds result in different degrees of macromolecular chain orientation in the polymeric micro-scale objects, which can be applied as design parameter for tailoring their mechanical and shape-memory properties.
The second part of the thesis deals with electrosprayed particulate PDC micro-scale objects. Almost spherical PDC microparticles with diameters of 3.9 ± 0.9 μm (as determined by SEM) were achieved by electrospraying of HFP solution with a polymer concentration of 2% w·v-1. In contrast, smaller particles with sizes of 400 ± 100 nm or 1.2 ± 0.3 μm were obtained for the magneto-sensitive composite PDC microparticles containing 23 ± 0.5 wt% superparamagnetic magnetite nanoparticles (mNPs). All prepared PDC microparticles exhibited a similar overall crystallinity like the PDC bulk material as analyzed by DSC. AFM nanoindentation results revealed no influence of the nanofiller incorporation on the local mechanical properties represented by the reduced modulus determined for pure PDC microparticles and magneto-sensitive composite PDC microparticles with similar diameters around 1.3 µm. It was found that the reduced modulus of the nanocomposite microparticles increased substantially with decreasing particles size from 2.4 ± 0.9 GPa (1.2 µm) to 11.9 ± 3.1 GPa (0.4 µm), which can be related to a higher orientation of the macromolecules at the surface of smaller sized microparticles. The magneto-sensitivity of such nanocomposite microparticles could be demonstrated in two aspects. One was by attracting/collecting the composite micro-objects with an external permanent magnet. The other one was by a inductive heating to 44 ± 1 °C, which is well above the melting transition of the OCL switching domains, when compacted to a 10 x 10 mm2 film with a thickness of 10 µm and exposed to an alternating magnet field with an magnetic field strength of 30 kA·m-1. Both functions are of great relevance for designing next generation drug delivery systems combining targeting and on demand release.
By a compression approach shape-memory functionalization of individual microparticles could be realized. Here different programming pressures and compression temperatures were applied. The shape-recovery capability of the programmed PDC microparticles was quantified by online and off-line heating experiments analyzed via microscopy measurement. The obtained shape-memory properties were found to be strongly depending on the applied programming pressure and temperature. The best shape-memory performance with a high shape recovery rate of about Rr = 80±1% was obtained when a low pressure of 0.2 MPa was applied at 55 °C. Finally, it was demonstrated that PDC microparticles can be utilized as micro building parts for preparation of a macroscopic film with temporary stability by compression of a densely packed array of PDC microparticles at 60 °C followed by subsequent cooling to ambient temperature. This film disintegrates into individual microparticles upon heating to 60 °C. Based on this technology the design of stable macroscopic release systems can be envisioned, which can be easily fixed at the site of treatment (i.e. by suturing) and disintegrate on demand to microparticles facilitating the drug release.
In summary, the results of this thesis could confirm the central hypothesis that the variation of the geometry of polymeric micro-objects is a suitable parameter to adjust their shape-memory performance by changing the degree of macromolecular chain orientation in the specimens or by enabling new functions like on demand disintegration. These fundamental findings might be relevant for designing novel miniaturized multifunctional polymer-based devices.
Synchrotron-based angle-resolved time-of-flight electron spectroscopy for dynamics in dichalogenides
(2018)
Samarium hexaboride
(2018)
On a small scale
(2018)
This study argues that micro relations matter in peacekeeping. Asking what makes the implementation of peacekeeping interventions complex and how complexity is resolved, I find that formal, contractual mechanisms only rarely effectively reduce complexity – and that micro relations fill this gap. Micro relations are personal relationships resulting from frequent face-to-face interaction in professional and – equally importantly – social contexts.
This study offers an explanation as to why micro relations are important for coping with complexity, in the form of a causal mechanism. For this purpose, I bring together theoretical and empirical knowledge: I draw upon the current debate on ‘institutional complexity’ (Greenwood et al. 2011) in organizational institutionalism as well as original empirical evidence from a within-case study of the peacekeeping intervention in Haiti, gained in ten weeks of field research. In this study, scholarship on institutional complexity serves to identify theoretical causal channels which guide empirical analysis. An additional, secondary aim is pursued with this mechanism-centered approach: testing the utility of Beach and Pedersen’s (2013) theory-testing process tracing.
Regarding the first research question – what makes the implementation of peacekeeping interventions complex –, the central finding is that complexity manifests itself in the dual role of organizations as cooperation partners and competitors for (scarce) resources, turf and influence. UN organizations, donor agencies and international NGOs implementing peacekeeping activities in post-conflict environments have chronic difficulty mastering both roles because they entail contradictory demands: effective cooperation requires information exchange, resource and responsibility-sharing as well as external scrutiny, whereas prevailing over competitors demands that organizations conceal information, guard resources, increase relative turf and influence, as well as shield themselves from scrutiny. Competition fuels organizational distrust and friction – and impedes cooperation.
How is this complexity resolved? The answer to this second research question is that deep-seated organizational competition is routinely mediated – and cooperation motivated – in micro relations and micro interaction. Regular, frequent face-to-face interaction between individual organizational members generates social resources that help to transcend organizational distrust and conflict, most importantly familiarity with each other, personal trust and belief in reciprocity. Furthermore, informal conflict mediation and control mechanisms – namely, open discussion, mutual monitoring in direct interaction and social exclusion – enhance solidarity and mutual support.
Nanoparticles (NPs) are particles between 1 and 100 nanometers in size. They have attracted enormous research interests owing to their remarkable physicochemical properties and potential applications in the optics, catalysis, sensing, electronics, or optical devices. The thesis investigates systems of NPs attached to planar substrates.
In the first part of the results section of the thesis a new method is presented to immobilize NPs. In many NP applications a strong, persistent adhesion to substrates is a key requirement. Up to now this has been achieved with various methods, which are not always the optimum regarding adhesion strength or applicability. We propose a new method which uses capillarity to enhance the binding agents in the contact area between NP and substrate. The adhesion strength resulting from the new approach is investigated in detail and it is shown that the new approach is superior to older methods in several ways.
The following section presents the optical visualization of nano-sized objects through a combination of thin film surface distortion and interference enhanced optical reflection microscopy. It is a new, fast and non-destructive technique. It not only reveals the location of NPs as small as 20nm attached to planar surfaces and embedded in a molecularly thin liquid film. It also allows the measurement of the geometry of the surface distortion of the liquid film. Even for small NPs the meniscus reaches out for micrometers, which is the reason why the NPs produce such a pronounced optical footprint.
The nucleation and growth of individual bubbles is presented in chapter 5. Nucleation is a ubiquitous natural phenomenon and of great importance in numerous industrial processes. Typically it occurs on very small scales (nanometers) and it is of a random nature (thermodynamics of small systems). Up to now most experimental nucleation studies deal with a large number of individual nucleation processes to cope with its inherently statistical, spatio-temporal character. In contrast, in this thesis the individual O2-bubble formation from single localized platinum NP active site is studied experimentally. The bubble formation is initiated by the catalytic reaction of H2O2 on the Pt surface. It is studied how the bubble nucleation and growth depends on the NP size, the H2O2 concentration and the substrate surface properties. It is observed that in some cases the bubbles move laterally over the substrate surface, driven by the O2-production and the film ablation.
Neuroinflammatory and neurodegenerative diseases such as Parkinson's (PD) and multiple sclerosis (MS) often result in a severe impairment of the patient´s quality of life. Effective therapies for the treatment are currently not available, which results in a high socio-economic burden. Due to the heterogeneity of the disease subtypes, stratification is particularly difficult in the early phase of the disease and is mainly based on clinical parameters such as neurophysiological tests and central nervous imaging. Due to good accessibility and stability, blood and cerebrospinal fluid metabolite markers could serve as surrogates for neurodegenerative processes. This can lead to an improved mechanistic understanding of these diseases and further be used as "treatment response" biomarkers in preclinical and clinical development programs. Therefore, plasma and CSF metabolite profiles will be identified that allow differentiation of PD from healthy controls, association of PD with dementia (PDD) and differentiation of PD subtypes such as akinetic rigid and tremor dominant PD patients. In addition, plasma metabolites for the diagnosis of primary progressive MS (PPMS) should be investigated and tested for their specificity to relapsing-remitting MS (RRMS) and their development during PPMS progression.
By applying untargeted high-resolution metabolomics of PD patient samples and in using random forest and partial least square machine learning algorithms, this study identified 20 plasma metabolites and 14 CSF metabolite biomarkers. These differentiate against healthy individuals with an AUC of 0.8 and 0.9 in PD, respectively. We also identify ten PDD specific serum metabolites, which differentiate against healthy individuals and PD patients without dementia with an AUC of 1.0, respectively. Furthermore, 23 akinetic-rigid specific plasma markers were identified, which differentiate against tremor-dominant PD patients with an AUC of 0.94 and against healthy individuals with an AUC of 0.98. These findings also suggest more severe disease pathology in the akinetic-rigid PD than in tremor dominant PD. In the analysis of MS patient samples a partial least square analysis yielded predictive models for the classification of PPMS and resulted in 20 PPMS specific metabolites. In another MS study unknown changes in human metabolism were identified after administration of the multiple sclerosis drug dimethylfumarate, which is used for the treatment of RRMS. These results allow to describe and understand the hitherto completely unknown mechanism of action of this new drug and to use these findings for the further development of new drugs and targets against RRMS.
In conclusion, these results have the potential for improved diagnosis of these diseases and improvement of mechanistic understandings, as multiple deregulated pathways were identified. Moreover, novel Dimethylfumarate targets can be used to aid drug development and treatment efficiency. Overall, metabolite profiling in combination with machine learning identified as a promising approach for biomarker discovery and mode of action elucidation.
Reversible-deactivation radical polymerization (RDRP) is without any doubt one of the most prevalent and powerful strategies for polymer synthesis, by which well-defined living polymers with targeted molecular weight (MW), low molar dispersity (Ɖ) and diverse morphologies can be prepared in a controlled fashion. Atom transfer radical polymerization (ATRP) as one of the most extensive studied types of RDRP has been particularly emphasized due to the high accessibility to hybrid materials, multifunctional copolymers and diverse end group functionalities via commercially available precursors. However, due to catalyst-induced side reactions and chain-chain coupling termination in bulk environment, synthesis of high MW polymers with uniform chain length (low Ɖ) and highly-preserved chain-end fidelity is usually challenging. Besides, owing to the inherited radical nature, the control of microstructure, namely tacticity control, is another laborious task. Considering the applied catalysts, the utilization of large amounts of non-reusable transition metal ions which lead to cumbersome purification process, product contamination and complicated reaction procedures all delimit the scope ATRP techniques.
Metal-organic frameworks (MOFs) are an emerging type of porous materials combing the properties of both organic polymers and inorganic crystals, characterized with well-defined crystalline framework, high specific surface area, tunable porous structure and versatile nanochannel functionalities. These promising properties of MOFs have thoroughly revolutionized academic research and applications in tremendous aspects, including gas processing, sensing, photoluminescence, catalysis and compartmentalized polymerization. Through functionalization, the microenvironment of MOF nanochannel can be precisely devised and tailored with specified functional groups for individual host-guest interactions. Furthermore, properties of high transition metal density, accessible catalytic sites and crystalline particles all indicate MOFs as prominent heterogeneous catalysts which open a new avenue towards unprecedented catalytic performance. Although beneficial properties in catalysis, high agglomeration and poor dispersibility restrain the potential catalytic capacity to certain degree.
Due to thriving development of MOF sciences, fundamental polymer science is undergoing a significant transformation, and the advanced polymerization strategy can eventually refine the intrinsic drawbacks of MOF solids reversely. Therefore, in the present thesis, a combination of low-dimensional polymers with crystalline MOFs is demonstrated as a robust and comprehensive approach to gain the bilateral advantages from polymers (flexibility, dispersibility) and MOFs (stability, crystallinity). The utilization of MOFs for in-situ polymerizations and catalytic purposes can be realized to synthesize intriguing polymers in a facile and universal process to expand the applicability of conventional ATRP methodology. On the other hand, through the formation of MOF/polymer composites by surface functionalization, the MOF particles with environment-adjustable dispersibility and high catalytic property can be as-prepared.
In the present thesis, an approach via combination of confined porous textures from MOFs and controlled radical polymerization is proposed to advance synthetic polymer chemistry. Zn2(bdc)2(dabco) (Znbdc) and the initiator-functionalized Zn MOFs, ZnBrbdc, are utilized as a reaction environment for in-situ polymerization of various size-dependent methacrylate monomers (i.e. methyl, ethyl, benzyl and isobornyl methacrylate) through (surface-initiated) activators regenerated by electron transfer (ARGET/SI-ARGET) ATRP, resulting in polymers with control over dispersity, end functionalities and tacticity with respect to distinct molecular size. While the functionalized MOFs are applied, due to the strengthened compartmentalization effect, the accommodated polymers with molecular weight up to 392,000 can be achieved. Moreover, a significant improvement in end-group fidelity and stereocontrol can be observed. The results highlight a combination of MOFs and ATRP is a promising and universal methodology to synthesize versatile well-defined polymers with high molecular weight, increment in isotactic trial and the preserved chain-end functionality.
More than being a host only, MOFs can act as heterogeneous catalysts for metal-catalyzed polymerizations. A Cu(II)-based MOF, Cu2(bdc)2(dabco), is demonstrated as a heterogeneous, universal catalyst for both thermal or visible light-triggered ARGET ATRP with expanded monomer range. The accessible catalytic metal sites enable the Cu(II) MOF to polymerize various monomers, including benzyl methacrylate (BzMA), styrene, methyl methacrylate (MMA), 2-(dimethylamino)ethyl methacrylate (DMAEMA) in the fashion of ARGET ATRP. Furthermore, due to the robust frameworks, surpassing the conventional homogeneous catalyst, the Cu(II) MOF can tolerate strongly coordinating monomers and polymerize challenging monomers (i.e. 4-vinyl pyridine, 2-vinyl pyridine and isoprene), in a well-controlled fashion. Therefore, a synthetic procedure can be significantly simplified, and catalyst-resulted chelation can be avoided as well. Like other heterogeneous catalysts, the Cu(II) MOF catalytic complexes can be easily collected by centrifugation and recycled for an arbitrary amount of times.
The Cu(II) MOF, composed of photostimulable metal sites, is further used to catalyze controlled photopolymerization under visible light and requires no external photoinitiator, dye sensitizer or ligand. A simple light trigger allows the photoreduction of Cu(II) to the active Cu(I) state, enabling controlled polymerization in the form of ARGET ATRP. More than polymerization application, the synergic effect between MOF frameworks and incorporated nucleophilic monomers/molecules is also observed, where the formation of associating complexes is able to adjust the photochemical and electrochemical properties of the Cu(II) MOF, altering the band gap and light harvesting behavior. Owing to the tunable photoabsorption property resulting from the coordinating guests, photoinduced Reversible-deactivation radical polymerization (PRDRP) can be achieved to further simplify and fasten the polymerization.
More than the adjustable photoabsorption ability, the synergistic strategy via a combination of controlled/living polymerization technique and crystalline MOFs can be again evidenced as demonstrated in the MOF-based heterogeneous catalysts with enhanced dispersibility in solution. Through introducing hollow pollen pivots with surface immobilized environment-responsive polymer, PDMAEMA, highly dispersed MOF nanocrystals can be prepared after associating on polymer brushes via the intrinsic amine functionality in each DMAEMA monomer. Intriguingly, the pollen-PDMAEMA composite can serve as a “smart” anchor to trap nanoMOF particles with improved dispersibility, and thus to significantly enhance liquid-phase photocatalytic performance. Furthermore, the catalytic activity can be switched on and off via stimulable coil-to-globule transition of the PDMAEMA chains exposing or burying MOF catalytic sites, respectively.
Due to a challenging population growth and environmental changes, a need for new routes to provide required chemicals for human necessities arises. An effective solution discussed in this thesis is industrial heterogeneous catalysis. The development of an advanced industrial heterogeneous catalyst is investigated herein by considering porous carbon nano-material as supports and modifying their surface chemistry structure with heteroatoms. Such modifications showed a significant influence on the performance of the catalyst and provided a deeper insight regarding the interaction between the surface structure of the catalyst and the surrounding phase. This thesis contributes to the few present studies about heteroatoms effect on the catalyst performance and emphasizes on the importance of understanding surface structure functionalization in a catalyst in different phases (liquid and gaseous) and for different reactions (hydrogenolysis, oxidation, and hydrogenation/ polymerization). Herein, the heteroatoms utilized for the modifications are hydrogen (H), oxygen (O), and nitrogen (N). The heteroatoms effect on the metal particle size, on the polarity of the support/ the catalyst, on the catalytic performance (activity, selectivity, and stability), and on the interaction with the surrounding phase has been explored. First hierarchical porous carbon nanomaterials functionalized with heteroatoms (N) is synthesized and applied as supports for nickel nanoparticles for hydrogenolysis process of kraft lignin in liquid phase. This reaction has been performed in batch and flow reactors for three different catalysts, two of comparable hierarchical porosity, yet one is modified with N and the other is not, and a third is a prepared catalyst from a commercial carbon support. The reaction production and analyses show that the catalysts with hierarchical porosity perform catalytically much better than in presence of a commercial carbon support with lower surface area. Moreover, the modification with N-heteroatoms enhanced the catalytic performance because the heteroatom modified porous carbon material with nickel nanoparticles catalyst (Ni-NDC) performed highest among the other catalysts. In the flow reactor, Ni-NDC selectively degraded the ether bonds (β-O-4) in kraft lignin with an activity of 2.2 x10^-4 mg lignin mg Ni-1 s-1 for 50 h at 350°C and 3.5 mL min-1 flow, providing ~99 % conversion to shorter chained chemicals (mainly guaiacol derivatives). Then, the functionalization of carbon surface was further studied in selective oxidation of glucose to gluconic acid using < 1 wt. % of gold (Au) deposited on the previously-mentioned synthesized carbon (C) supports with different functionalities (Au-CGlucose, Au-CGlucose-H, Au-CGlucose-O, Au-CGlucoseamine). Except for Au-CGlucose-O, the other catalysts achieved full glucose conversion within 40-120 min and 100% selectivity towards gluconic acid with a maximum activity of 1.5 molGlucose molAu-1 s-1 in an aqueous phase at 45 °C and pH 9. Each heteroatom influenced the polarity of the carbon differently, affecting by that the deposition of Au on the support and thus the activity of the catalyst and its selectivity. The heteroatom effect was further investigated in a gas phase. The Fischer-Tropsch reaction was applied to convert synthetic gas (CO and H2) to short olefins and paraffins using surface-functionalized carbon nanotubes (CNTs) with heteroatoms as supports for ion (Fe) deposition in presence and absence of promoters (Na and S). The results showed the promoted Fe-CNT doped with nitrogen catalyst to be stable up to 180 h and selective to the formation of olefins (~ 47 %) and paraffins (~6 %) with a conversion of CO ~ 92 % at a maximum activity of 94 *10^-5 mol CO g Fe-1 s-1. The more information given regarding this topic can open wide range of applications not only in catalysis, but in other approaches as well. In conclusion, incorporation of heteroatoms can be the next approach for an advanced industrial heterogeneous catalyst, but also for other applications (e.g. electrocatalysis, gas adsorption, or supercapacitors).
The utilization of lignin as renewable electrode material for electrochemical energy storage is a sustainable approach for future batteries and supercapacitors. The composite electrode was fabricated from Kraft lignin and conductive carbon and the charge storage contribution was determined in terms of electrical double layer (EDL) and redox reactions. The important factors at play for achieving high faradaic charge storage capacity contribute to high surface area, accessibility of redox sites in lignin and their interaction with conductive additives. A thinner layer of lignin covering the high surface area of carbon facilitates the electron transfer process with a shorter pathway from the active sites of nonconductive lignin to the current collector leading to the improvement of faradaic charge storage capacity.
Composite electrodes from lignin and carbon would be even more sustainable if the fluorinated binder can be omitted. A new route to fabricate a binder-free composite electrode from Kraft lignin and high surface area carbon has been proposed by crosslinking lignin with glyoxal. A high molecular weight of lignin is obtained to enhance both electroactivity and binder capability in composite electrodes. The order of the processing step of crosslinking lignin on the composite electrode plays a crucial role in achieving a stable electrode and high charge storage capacity. The crosslinked lignin based electrodes are promising since they allow for more stable, sustainable, halogen-free and environmentally benign devices for energy storage applications. Furthermore, improvement of the amount of redox active groups (quinone groups) in lignin is useful to enhance the capacity in lithium battery applications. Direct oxidative demethylation by cerium ammonium nitrate has been carried out under mild conditions. This proves that an increase of quinone groups is able to enhance the performance of lithium battery. Thus, lignin is a promising material and could be a good candidate for application in sustainable energy storage devices.
Photocatalysis is considered significant in this new energy era, because the inexhaustibly abundant, clean, and safe energy of the sun can be harnessed for sustainable, nonhazardous, and economically development of our society. In the research of photocatalysis, the current focus was held by the design and modification of photocatalyst.
As one of the most promising photocatalysts, g-C3N4 has gained considerable attention for its eye-catching properties. It has been extensively explored in photocatalysis applications, such as water splitting, organic pollutant degradation, and CO2 reduction. Even so, it also has its own drawbacks which inhibit its further application. Inspired by that, this thesis will mainly present and discuss the process and achievement on the preparation of some novel photocatalysts and their photocatalysis performance. These materials were all synthesized via the alteration of classic g-C3N4 preparation method, like using different pre-compositions for initial supramolecular complex and functional group post-modification. By taking place of cyanuric acid, 2,5-Dihydroxy-1,4-benzoquinone and chloranilic acid can form completely new supramolecular complex with melamine. After heating, the resulting products of the two complex shown 2D sheet-like and 1D fiber-like morphologies, respectively, which maintain at even up to high temperature of 800 °C. These materials cover crystals, polymers and N-doped carbons with the increase of synthesis temperature. Based on their different pre-compositions, they show different dye degradation performances. For CLA-M-250, it shows the highest photocatalytic activity and strong oxidation capacity. It shows not only great photo-performance in RhB degradation, but also oxygen production in water splitting. In the post-modification method, a novel photocatalysis solution was proposed to modify carbon nitride scaffold with cyano group, whose content can be well controlled by the input of sodium thiocyanate. The cyanation modification leads to narrowed band gap as well as improved photo-induced charges separation. Cyano group grafted carbon nitride thus shows dramatically enhanced performance in the photocatalytic coupling reaction between styrene and sodium benzenesulfinate under green light irradiation, which is in stark contrast with the inactivity of pristine g-C3N4.
Scalable data profiling
(2018)
Data profiling is the act of extracting structural metadata from datasets. Structural metadata, such as data dependencies and statistics, can support data management operations, such as data integration and data cleaning. Data management often is the most time-consuming activity in any data-related project. Its support is extremely valuable in our data-driven world, so that more time can be spent on the actual utilization of the data, e. g., building analytical models. In most scenarios, however, structural metadata is not given and must be extracted first. Therefore, efficient data profiling methods are highly desirable.
Data profiling is a computationally expensive problem; in fact, most dependency discovery problems entail search spaces that grow exponentially in the number of attributes. To this end, this thesis introduces novel discovery algorithms for various types of data dependencies – namely inclusion dependencies, conditional inclusion dependencies, partial functional dependencies, and partial unique column combinations – that considerably improve over state-of-the-art algorithms in terms of efficiency and that scale to datasets that cannot be processed by existing algorithms. The key to those improvements are not only algorithmic innovations, such as novel pruning rules or traversal strategies, but also algorithm designs tailored for distributed execution. While distributed data profiling has been mostly neglected by previous works, it is a logical consequence on the face of recent hardware trends and the computational hardness of dependency discovery.
To demonstrate the utility of data profiling for data management, this thesis furthermore presents Metacrate, a database for structural metadata. Its salient features are its flexible data model, the capability to integrate various kinds of structural metadata, and its rich metadata analytics library. We show how to perform a data anamnesis of unknown, complex datasets based on this technology. In particular, we describe in detail how to reconstruct the schemata and assess their quality as part of the data anamnesis.
The data profiling algorithms and Metacrate have been carefully implemented, integrated with the Metanome data profiling tool, and are available as free software. In that way, we intend to allow for easy repeatability of our research results and also provide them for actual usage in real-world data-related projects.
Nanophotonics is the field of science and engineering aimed at studying the light-matter interactions on the nanoscale. One of the key aspects in studying such optics at the nanoscale is the ability to assemble the material components in a spatially controlled manner. In this work, DNA origami nanostructures were used to self-assemble dye molecules and DNA coated plasmonic nanoparticles. Optical properties of dye nanoarrays, where the dyes were arranged at distances where they can interact by Förster resonance energy transfer (FRET), were systematically studied according to the size and arrangement of the dyes using fluorescein (FAM) as the donor and cyanine 3 (Cy 3) as the acceptor. The optimized design, based on steady-state and time-resolved fluorometry, was utilized in developing a ratiometric pH sensor with pH-inert coumarin 343 (C343) as the donor and pH-sensitive FAM as the acceptor. This design was further applied in developing a ratiometric toxin sensor, where the donor C343 is unresponsive and FAM is responsive to thioacetamide (TAA) which is a well-known hepatotoxin. The results indicate that the sensitivity of the ratiometric sensor can be improved by simply arranging the dyes into a well-defined array. The ability to assemble multiple fluorophores without dye-dye aggregation also provides a strategy to amplify the signal measured from a fluorescent reporter, and was utilized here to develop a reporter for sensing oligonucleotides. By incorporating target capturing sequences and multiple fluorophores (ATTO 647N dye molecules), a reporter for microbead-based assay for non-amplified target oligonucleotide sensing was developed. Analysis of the assay using VideoScan, a fluorescence microscope-based technology capable of conducting multiplex analysis, showed the DNA origami nanostructure based reporter to have a lower limit of detection than a single stranded DNA reporter. Lastly, plasmonic nanostructures were assembled on DNA origami nanostructures as substrates to study interesting optical behaviors of molecules in the near-field. Specifically, DNA coated gold nanoparticles, silver nanoparticles, and gold nanorods, were placed on the DNA origami nanostructure aiming to study surface-enhanced fluorescence (SEF) and surface-enhanced Raman scattering (SERS) of molecules placed in the hotspot of coupled plasmonic structures.
Deoxyribonucleic acid (DNA) is the carrier of human genetic information and is exposed to environmental influences such as the ultraviolet (UV) fraction of sunlight every day. The photostability of the DNA against UV light is astonishing. Even if the DNA bases have a strong absorption maximum at around 260 nm/4.77 eV, their quantum yield of photoproducts remains very low 1. If the photon energies exceed the ionization energy (IE) of the nucleobases ( ̴ 8-9 eV) 2, the DNA can be severely damaged. Photoexcitation and -ionization reactions occur, which can induce strand breaks in the DNA. The efficiency of the excitation and ionization induced strand breaks in the target DNA sequences are represented by cross sections. If Si as a substrate material is used in the VUV irradiation experiments, secondary electrons with an energy below 3.6 eV are generated from the substrate. This low energy electrons (LEE) are known to induce dissociative electron attachment (DEA) in DNA and with it DNA strand breakage very efficiently. LEEs play an important role in cancer radiation therapy, since they are generated secondarily along the radiation track of ionizing radiation.
In the framework of this thesis, different single stranded DNA sequences were irradiated with 8.44 eV vacuum UV (VUV) light and cross sections for single strand breaks (SSB) were determined. Several sequences were also exposed to secondary LEEs, which additionally contributed to the SSBs. First, the cross sections for SSBs depending on the type of nucleobases were determined. Both types of DNA sequences, mono-nucleobase and mixed sequences showed very similar results upon VUV radiation. The additional influence of secondarily generated LEEs resulted in contrast in a clear trend for the SSB cross sections. In this, the polythymine sequence had the highest cross section for SSBs, which can be explained by strong anionic resonances in this energy range. Furthermore, SSB cross sections were determined as a function of sequence length. This resulted in an increase in the strand breaks to the same extent as the increase in the geometrical cross section. The longest DNA sequence (20 nucleotides) investigated in this series, however, showed smaller cross section values for SSBs, which can be explained by conformational changes in the DNA. Moreover, several DNA sequences that included the radiosensitizers 5-Bromouracil (5BrU) and 8-Bromoadenine (8BrA) were investigated and the corresponding SSB cross sections were determined. It was shown that 5BrU reacts very strongly to VUV radiation leading to high strand break yields, which showed in turn a strong sequence-dependency. 8BrA, on the other hand, showed no sensitization to the applied VUV radiation, since almost no increase in strand breakage yield was observed in comparison to non-modified DNA sequences.
In order to be able to identify the mechanisms of radiation damage by photons, the IEs of certain DNA sequences were further explored using photoionization tandem mass spectrometry. By varying the DNA sequence, both the IEs depending on the type of nucleobase as well as on the DNA strand length could be identified and correlated to the SSB cross sections. The influence of the IE on the photoinduced reaction in the brominated DNA sequences could be excluded.
New bio-based polymers
(2018)
Redox-responsive polymers, such as poly(disulfide)s, are a versatile class of polymers with potential applications including gene- and drug-carrier systems. Their degradability under reductive conditions allows for a controlled response to the different redox states that are present throughout the body. Poly(disulfide)s are typically synthesized by step growth polymerizations. Step growth polymerizations, however, may suffer from low conversions and therefore low molar masses, limiting potential applications. The purpose of this thesis was therefore to find and investigate new synthetic routes towards the synthesis of amino acid-based poly(disulfide)s.
The different routes in this thesis include entropy-driven ring opening polymerizations of novel macrocyclic monomers, derived from cystine derivatives. These monomers were obtained with overall yields of up to 77% and were analyzed by mass spectrometry as well as by 1D and 2D NMR spectroscopy. The kinetics of the entropy-driven ring-opening metathesis polymerization (ED-ROMP) were thoroughly investigated in dependence of temperature, monomer concentration, and catalyst concentration. The polymerization was optimized to yield poly(disulfide)s with weight average molar masses of up to 80 kDa and conversions of ~80%, at the thermodynamic equilibrium. Additionally, an alternative metal free polymerization, namely the entropy-driven ring-opening disulfide metathesis polymerization (ED-RODiMP) was established for the polymerization of the macrocyclic monomers. The effect of different solvents, concentrations and catalyst loadings on the polymerization process and its kinetics were studied. Polymers with very high weight average molar masses of up to 177 kDa were obtained. Moreover, various post-polymerization reactions were successfully performed.
This work provides the first example of the homopolymerization of endo-cyclic disulfides by ED-ROMP and the first substantial study into the kinetics of the ED-RODiMP process.
Utilization of sunlight for energy harvesting has been foreseen as sustainable replacement for fossil fuels, which would also eliminate side effects arising from fossil fuel consumption such as drastic increase of CO2 in Earth atmosphere. Semiconductor materials can be implemented for energy harvesting, and design of ideal energy harvesting devices relies on effective semiconductor with low recombination rate, ease of processing, stability over long period, non-toxicity and synthesis from abundant sources. Aforementioned criteria have attracted broad interest for graphitic carbon nitride (g-CN) materials, metal-free semiconductor which can be synthesized from low cost and abundant precursors. Furthermore, physical properties such as band gap, surface area and absorption can be tuned. g-CN was investigated as heterogeneous catalyst, with diversified applications from water splitting to CO2 reduction and organic coupling reactions. However, low dispersibility of g-CN in water and organic solvents was an obstacle for future improvements.
Tissue engineering aims to mimic natural tissues mechanically and biologically, so that synthetic materials can replace natural ones in future. Hydrogels are crosslinked networks with high water content, therefore are prime candidates for tissue engineering. However, the first requirement is synthesis of hydrogels with mechanical properties that are matching to natural tissues. Among different approaches for reinforcement, nanocomposite reinforcement is highly promising.
This thesis aims to investigate aqueous and organic dispersions of g-CN materials. Aqueous g-CN dispersions were utilized for visible light induced hydrogel synthesis, where g-CN acts as reinforcer and photoinitiator. Varieties of methodologies were presented for enhancing g-CN dispersibility, from co-solvent method to prepolymer formation, and it was shown that hydrogels with diversified mechanical properties (from skin-like to cartilage-like) are accessible via g-CN utilization. One pot photografting method was introduced for functionalization of g-CN surface which provides functional groups towards enhanced dispersibility in aqueous and organic media. Grafting vinyl thiazole groups yields stable additive-free organodispersions of g-CN which are electrostatically stabilized with increased photophysical properties. Colloidal stability of organic systems provides transparent g-CN coatings and printing g-CN from commercial inkjet printers.
Overall, application of g-CN in dispersed media is highly promising, and variety of materials can be accessible via utilization of g-CN and visible light with simple chemicals and synthetic conditions. g-CN in dispersed media will bridge emerging research areas from tissue engineering to energy harvesting in near future.
Understanding how humans move their eyes is an important part for understanding the functioning of the visual system. Analyzing eye movements from observations of natural scenes on a computer screen is a step to understand human visual behavior in the real world. When analyzing eye-movement data from scene-viewing experiments, the impor- tant questions are where (fixation locations), how long (fixation durations) and when (ordering of fixations) participants fixate on an image. By answering these questions, computational models can be developed which predict human scanpaths. Models serve as a tool to understand the underlying cognitive processes while observing an image, especially the allocation of visual attention.
The goal of this thesis is to provide new contributions to characterize and model human scanpaths on natural scenes. The results from this thesis will help to understand and describe certain systematic eye-movement tendencies, which are mostly independent of the image. One eye-movement tendency I focus on throughout this thesis is the tendency to fixate more in the center of an image than on the outer parts, called the central fixation bias. Another tendency, which I will investigate thoroughly, is the characteristic distribution of angles between successive eye movements.
The results serve to evaluate and improve a previously published model of scanpath generation from our laboratory, the SceneWalk model. Overall, six experiments were conducted for this thesis which led to the following five core results:
i) A spatial inhibition of return can be found in scene-viewing data. This means that locations which have already been fixated are afterwards avoided for a certain time interval (Chapter 2).
ii) The initial fixation position when observing an image has a long-lasting influence of up to five seconds on further scanpath progression (Chapter 2 & 3).
iii) The often described central fixation bias on images depends strongly on the duration of the initial fixation. Long-lasting initial fixations lead to a weaker central fixation bias than short fixations (Chapter 2 & 3).
iv) Human observers adjust their basic eye-movement parameters, like fixation dura- tions and saccade amplitudes, to the visual properties of a target they look for in visual search (Chapter 4).
v) The angle between two adjacent saccades is an indicator for the selectivity of the upcoming saccade target (Chapter 4).
All results emphasize the importance of systematic behavioral eye-movement tenden- cies and dynamic aspects of human scanpaths in scene viewing.
Arctic warming has implications for the functioning of terrestrial Arctic ecosystems, global climate and socioeconomic systems of northern communities. A research gap exists in high spatial resolution monitoring and understanding of the seasonality of permafrost degradation, spring snowmelt and vegetation phenology. This thesis explores the diversity and utility of dense TerraSAR-X (TSX) X-Band time series for monitoring ice-rich riverbank erosion, snowmelt, and phenology of Arctic vegetation at long-term study sites in the central Lena Delta, Russia and on Qikiqtaruk (Herschel Island), Canada. In the thesis the following three research questions are addressed:
• Is TSX time series capable of monitoring the dynamics of rapid permafrost degradation in ice-rich permafrost on an intra-seasonal scale and can these datasets in combination with climate data identify the climatic drivers of permafrost degradation?
• Can multi-pass and multi-polarized TSX time series adequately monitor seasonal snow cover and snowmelt in small Arctic catchments and how does it perform compared to optical satellite data and field-based measurements?
• Do TSX time series reflect the phenology of Arctic vegetation and how does the recorded signal compare to in-situ greenness data from RGB time-lapse camera data and vegetation height from field surveys?
To answer the research questions three years of TSX backscatter data from 2013 to 2015 for the Lena Delta study site and from 2015 to 2017 for the Qikiqtaruk study site were used in quantitative and qualitative analysis complimentary with optical satellite data and in-situ time-lapse imagery.
The dynamics of intra-seasonal ice-rich riverbank erosion in the central Lena Delta, Russia were quantified using TSX backscatter data at 2.4 m spatial resolution in HH polarization and validated with 0.5 m spatial resolution optical satellite data and field-based time-lapse camera data. Cliff top lines were automatically extracted from TSX intensity images using threshold-based segmentation and vectorization and combined in a geoinformation system with manually digitized cliff top lines from the optical satellite data and rates of erosion extracted from time-lapse cameras. The results suggest that the cliff top eroded at a constant rate throughout the entire erosional season. Linear mixed models confirmed that erosion was coupled with air temperature and precipitation at an annual scale, seasonal fluctuations did not influence 22-day erosion rates. The results highlight the potential of HH polarized X-Band backscatter data for high temporal resolution monitoring of rapid permafrost degradation.
The distinct signature of wet snow in backscatter intensity images of TSX data was exploited to generate wet snow cover extent (SCE) maps on Qikiqtaruk at high temporal resolution. TSX SCE showed high similarity to Landsat 8-derived SCE when using cross-polarized VH data. Fractional snow cover (FSC) time series were extracted from TSX and optical SCE and compared to FSC estimations from in-situ time-lapse imagery. The TSX products showed strong agreement with the in-situ data and significantly improved the temporal resolution compared to the Landsat 8 time series. The final combined FSC time series revealed two topography-dependent snowmelt patterns that corresponded to in-situ measurements. Additionally TSX was able to detect snow patches longer in the season than Landsat 8, underlining the advantage of TSX for detection of old snow. The TSX-derived snow information provided valuable insights into snowmelt dynamics on Qikiqtaruk previously not available.
The sensitivity of TSX to vegetation structure associated with phenological changes was explored on Qikiqtaruk. Backscatter and coherence time series were compared to greenness data extracted from in-situ digital time-lapse cameras and detailed vegetation parameters on 30 areas of interest. Supporting previous results, vegetation height corresponded to backscatter intensity in co-polarized HH/VV at an incidence angle of 31°. The dry, tall shrub dominated ecological class showed increasing backscatter with increasing greenness when using the cross polarized VH/HH channel at 32° incidence angle. This is likely driven by volume scattering of emerging and expanding leaves. Ecological classes with more prostrate vegetation and higher bare ground contributions showed decreasing backscatter trends over the growing season in the co-polarized VV/HH channels likely a result of surface drying instead of a vegetation structure signal. The results from shrub dominated areas are promising and provide a complementary data source for high temporal monitoring of vegetation phenology.
Overall this thesis demonstrates that dense time series of TSX with optical remote sensing and in-situ time-lapse data are complementary and can be used to monitor rapid and seasonal processes in Arctic landscapes at high spatial and temporal resolution.
Fluvial terraces, floodplains, and alluvial fans are the main landforms to store sediments and to decouple hillslopes from eroding mountain rivers. Such low-relief landforms are also preferred locations for humans to settle in otherwise steep and poorly accessible terrain. Abundant water and sediment as essential sources for buildings and infrastructure make these areas amenable places to live at. Yet valley floors are also prone to rare and catastrophic sedimentation that can overload river systems by abruptly increasing the volume of sediment supply, thus causing massive floodplain aggradation, lateral channel instability, and increased flooding. Some valley-fill sediments should thus record these catastrophic sediment pulses, allowing insights into their timing, magnitude, and consequences.
This thesis pursues this theme and focuses on a prominent ~150 km2 valley fill in the Pokhara Valley just south of the Annapurna Massif in central Nepal. The Pokhara Valley is conspicuously broad and gentle compared to the surrounding dissected mountain terrain,
and is filled with locally more than 70 m of clastic debris. The area’s main river, Seti Khola, descends from the Annapurna Sabche Cirque at 3500-4500 m asl down to 900 m asl where it incises into this valley fill. Humans began to settle on this extensive
fan surface in the 1750’s when the Trans-Himalayan trade route connected the Higher Himalayas, passing Pokhara city, with the subtropical lowlands of the Terai. High and unstable river terraces and steep gorges undermined by fast flowing rivers with highly seasonal (monsoon-driven) discharge, a high earthquake risk, and a growing population make the Pokhara Valley an ideal place to study the recent geological and geomorphic history of its sediments and the implication for natural hazard appraisals.
The objective of this thesis is to quantify the timing, the sedimentologic and geomorphic processes as well as the fluvial response to a series of strong sediment pulses. I report
diagnostic sedimentary archives, lithofacies of the fan terraces, their geochemical provenance, radiocarbon-age dating and the stratigraphic relationship between them. All these various and independent lines of evidence show consistently that multiple sediment pulses filled the Pokhara Valley in medieval times, most likely in connection with, if not triggered by, strong seismic ground shaking. The geomorphic and sedimentary evidence is
consistent with catastrophic fluvial aggradation tied to the timing of three medieval Himalayan earthquakes in ~1100, 1255, and 1344 AD. Sediment provenance and calibrated radiocarbon-age data are the key to distinguish three individual sediment pulses, as these are not evident from their sedimentology alone. I explore various measures of adjustment and fluvial response of the river system following these massive aggradation pulses. By using proxies such as net volumetric erosion, incision and erosion rates, clast provenance on active river banks, geomorphic markers such as re-exhumed tree trunks in growth position, and knickpoint locations in tributary valleys, I estimate the response of the river network in the Pokhara Valley to earthquake disturbance over several centuries. Estimates of the removed volumes since catastrophic valley filling began, require average net sediment
yields of up to 4200 t km−2 yr−1 since, rates that are consistent with those reported for Himalayan rivers. The lithological composition of active channel-bed load differs from that of local bedrock material, confirming that rivers have adjusted 30-50% depending on data of different tributary catchments, locally incising with rates of 160-220 mm yr−1. In many tributaries to the Seti Khola, most of the contemporary river loads come from a Higher Himalayan source, thus excluding local hillslopes as sources. This imbalance in sediment provenance emphasizes how the medieval sediment pulses must have rapidly traversed up to 70 km downstream to invade the downstream reaches of the tributaries
up to 8 km upstream, thereby blocking the local drainage and thus reinforcing, or locally creating new, floodplain lakes still visible in the landscape today.
Understanding the formation, origin, mechanism and geomorphic processes of this valley fill is crucial to understand the landscape evolution and response to catastrophic sediment pulses. Several earthquake-triggered long-runout rock-ice avalanches or catastrophic dam burst in the Higher Himalayas are the only plausible mechanisms to explain both the geomorphic and sedimentary legacy that I document here. In any case, the Pokhara Valley was most likely hit by a cascade of extremely rare processes over some two centuries starting in the early 11th century. Nowhere in the Himalayas do we find valley fills of
comparable size and equally well documented depositional history, making the Pokhara Valley one of the most extensively dated valley fill in the Himalayas to date. Judging from the growing record of historic Himalayan earthquakes in Nepal that were traced and
dated in fault trenches, this thesis shows that sedimentary archives can be used to directly aid reconstructions and predictions of both earthquake triggers and impacts from a sedimentary-response perspective. The knowledge about the timing, evolution, and response of the Pokhara Valley and its river system to earthquake triggered sediment pulses is important to address the seismic and geomorphic risk for the city of Pokhara. This
thesis demonstrates how geomorphic evidence on catastrophic valley infill can help to independently verify paleoseismological fault-trench records and may initiate re-thinking on post-seismic hazard assessments in active mountain regions.
The formation and breaching of natural dammed lakes have formed the landscapes, especially in seismically active high-mountain regions. Dammed lakes pose both, potential water resources, and hazard in case of dam breaching. Central Asia has mostly arid and semi-arid climates. Rock glaciers already store more water than ice-glaciers in some semi-arid regions of the world, but their distribution and advance mechanisms are still under debate in recent research. Their impact on the water availability in Central Asia will likely increase as temperatures rise and glaciers diminish.
This thesis provides insight to the relative age distribution of selected Kyrgyz and Kazakh rock glaciers and their single lobes derived from lichenometric dating. The size of roughly 8000 different lichen specimens was used to approximate an exposure age of the underlying debris surface. We showed that rock-glacier movement differs signifcantly on small scales. This has several implications for climatic inferences from rock glaciers. First, reactivation of their lobes does not necessarily point to climatic changes, or at least at out-of-equilibrium conditions. Second, the elevations of rock-glacier toes can no longer be considered as general indicators of the limit of sporadic mountain permafrost as they have been used traditionally.
In the mountainous and seismically active region of Central Asia, natural dams, besides rock glaciers, also play a key role in controlling water and sediment infux into river valleys. However, rock glaciers advancing into valleys seem to be capable of infuencing the stream network, to dam rivers, or to impound lakes. This influence has not previously been addressed. We quantitatively explored these controls using a new inventory of 1300 Central Asian rock glaciers. Elevation, potential incoming solar radiation, and the size of rock glaciers and their feeder basins played key roles in predicting dam appearance. Bayesian techniques were used to credibly distinguish between lichen sizes on rock glaciers and their lobes, and to find those parameters of a rock-glacier system that are most credibly expressing the potential to build natural dams.
To place these studies in the region's history of natural dams, a combination of dating of former lake levels and outburst flood modelling addresses the history and possible outburst flood hypotheses of the second largest mountain lake of the world, Issyk Kul in Kyrgyzstan. Megafoods from breached earthen or glacial dams were found to be a likely explanation for some of the lake's highly fluctuating water levels. However, our detailed analysis of candidate lake sediments and outburst-flood deposits also showed that more localised dam breaks to the west of Issyk Kul could have left similar geomorphic and sedimentary evidence in this Central Asian mountain landscape. We thus caution against readily invoking megafloods as the main cause of lake-level drops of Issyk Kul. In summary, this thesis addresses some new pathways for studying rock glaciers and natural dams with several practical implications for studies on mountain permafrost and natural hazards.
Landslides are frequent natural hazards in rugged terrain, when the resisting frictional force of the surface of rupture yields to the gravitational force. These forces are functions of geological and morphological factors, such as angle of internal friction, local slope gradient or curvature, which remain static over hundreds of years; whereas more dynamic triggering events, such as rainfall and earthquakes, compromise the force balance by temporarily reducing resisting forces or adding transient loads. This thesis investigates landslide distribution and orientation due to landslide triggers (e.g. rainfall) at different scales (6-4∙10^5 km^2) and aims to link rainfall movement with the landslide distribution. It additionally explores the local impacts of the extreme rainstorms on landsliding and the role of precursory stability conditions that could be induced by an earlier trigger, such as an earthquake.
Extreme rainfall is a common landslide trigger. Although several studies assessed rainfall intensity and duration to study the distribution of thus triggered landslides, only a few case studies quantified spatial rainfall patterns (i.e. orographic effect). Quantifying the regional trajectories of extreme rainfall could aid predicting landslide prone regions in Japan. To this end, I combined a non-linear correlation metric, namely event synchronization, and radial statistics to assess the general pattern of extreme rainfall tracks over distances of hundreds of kilometers using satellite based rainfall estimates. Results showed that, although the increase in rainfall intensity and duration positively correlates with landslide occurrence, the trajectories of typhoons and frontal storms were insufficient to explain landslide distribution in Japan. Extreme rainfall trajectories inclined northwestwards and were concentrated along some certain locations, such as coastlines of southern Japan, which was unnoticed in the landslide distribution of about 5000 rainfall-triggered landslides. These landslides seemed to respond to the mean annual rainfall rates.
Above mentioned findings suggest further investigation on a more local scale to better understand the mechanistic response of landscape to extreme rainfall in terms of landslides. On May 2016 intense rainfall struck southern Germany triggering high waters and landslides. The highest damage was reported at the Braunsbach, which is located on the tributary-mouth fan formed by the Orlacher Bach. Orlacher Bach is a ~3 km long creek that drains a catchment of about ~6 km^2. I visited this catchment in June 2016 and mapped 48 landslides along the creek. Such high landslide activity was not reported in the nearby catchments within ~3300 km^2, despite similar rainfall intensity and duration based on weather radar estimates. My hypothesis was that several landslides were triggered by rainfall-triggered flash floods that undercut hillslope toes along the Orlacher Bach. I found that morphometric features such as slope and curvature play an important role in landslide distribution on this micro scale study site (<10 km^2). In addition, the high number of landslides along the Orlacher Bach could also be boosted by accumulated damages on hillslopes due karst weathering over longer time scales.
Precursory damages on hillslopes could also be induced by past triggering events that effect landscape evolution, but this interaction is hard to assess independently from the latest trigger. For example, an earthquake might influence the evolution of a landscape decades long, besides its direct impacts, such as landslides that follow the earthquake. Here I studied the consequences of the 2016 Kumamoto Earthquake (MW 7.1) that triggered some 1500 landslides in an area of ~4000 km^2 in central Kyushu, Japan. Topography, i.e. local slope and curvature, both amplified and attenuated seismic waves, thus controlling the failure mechanism of those landslides (e.g. progressive). I found that topography fails in explaining the distribution and the preferred orientation of the landslides after the earthquake; instead the landslides were concentrated around the northeast of the rupture area and faced mostly normal to the rupture plane. This preferred location of the landslides was dominated mainly by the directivity effect of the strike-slip earthquake, which is the propagation of wave energy along the fault in the rupture direction; whereas amplitude variations of the seismic radiation altered the preferred orientation. I suspect that the earthquake directivity and the asymmetry of seismic radiation damaged hillslopes at those preferred locations increasing landslide susceptibility. Hence a future weak triggering event, e.g. scattered rainfall, could further trigger landslides at those damaged hillslopes.
The Sun is the nearest star to the Earth. It consists of an interior and an atmosphere. The convection zone is the outermost layer of the solar interior. A flux rope may emerge as a coherent structure from the convection zone into the solar atmosphere or be formed by magnetic reconnection in the atmosphere. A flux rope is a bundle of magnetic field lines twisting around an axis field line, creating a helical shape by which dense filament material can be supported against gravity. The flux rope is also considered as the key structure of the most energetic phenomena in the solar system, such as coronal mass ejections (CMEs) and flares. These magnetic flux ropes can produce severe geomagnetic storms. In particular, to improve the ability to forecast space weather, it is important to enrich our knowledge about the dynamic formation of flux ropes and the underlying physical mechanisms that initiate their eruption, such as a CME.
A confined eruption consists of a filament eruption and usually an associated are, but does not evolve into a CME; rather, the moving plasma is halted in the solar corona and usually seen to fall back. The first detailed observations of a confined filament eruption were obtained on 2002 May 27by the TRACE satellite in the 195 A band. So, in the Chapter 3, we focus on a flux rope instability model. A twisted flux rope can become unstable by entering the kink instability regime. We show that the kink instability, which occurs if the twist of a flux rope exceeds a critical value, is capable of initiating of an eruption. This model is tested against the well observed confined eruption on 2002 May 27 in a parametric magnetohydrodynamic (MHD) simulation study that comprises all phases of the event. Very good agreement with the essential observed properties is obtained, only except for a relatively poor matching of the initial filament height.
Therefore, in Chapter 4, we submerge the center point of the flux rope deeper below the photosphere to obtain a flatter coronal rope section and a better matching with the initial height profile of the erupting filament. This implies a more realistic inclusion of the photospheric line tying. All basic assumptions and the other parameter settings are kept the same as in Chapter 3. This complement of the parametric study shows that the flux rope instability model can yield an even better match with the observational data. We also focus in Chapters 3 and 4 on the magnetic reconnection during the confined eruption, demonstrating that it occurs in two distinct locations and phases that correspond to the observed brightenings and changes of topology, and consider the fate of the erupting flux, which can reform a (less twisted) flux rope.
The Sun also produces series of homologous eruptions, i.e. eruptions which occur repetitively in the same active region and are of similar morphology. Therefore, in Chapter 5, we employ the reformed flux rope as a new initial condition, to investigate the possibility of subsequent homologous eruptions. Free magnetic energy is built up by imposing motions in the bottom boundary, such as converging motions, leading to flux cancellation. We apply converging motions in the sunspot area, such that a small part of the flux from the sunspots with different polarities is transported toward the polarity inversion line (PIL) and cancels with each other. The reconnection associated with the cancellation process forms more helical magnetic flux around the reformed flux rope, which leads to a second and a third eruption. In this study, we obtain the first MHD simulation results of a homologous sequence of eruptions that show a transition from a confined to two ejective eruptions, based on the reformation of a flux rope after each eruption.
This research addressed the question, if it is possible to simplify current microcontact printing systems for the production of anisotropic building blocks or patchy particles, by using common chemicals while still maintaining reproducibility, high precision and tunability of the Janus-balance
Chapter 2 introduced the microcontact printing materials as well as their defined electrostatic interactions. In particular polydimethylsiloxane stamps, silica particles and high molecular weight polyethylenimine ink were mainly used in this research. All of these components are commercially available in large quantities and affordable, which gives this approach a huge potential for further up-scaling developments. The benefits of polymeric over molecular inks was described including its flexible influence on the printing pressure. With this alteration of the µCP concept, a new method of solvent assisted particle release mechanism enabled the switch from two-dimensional surface modification to three-dimensional structure printing on colloidal silica particles, without changing printing parameters or starting materials. This effect opened the way to use the internal volume of the achieved patches for incorporation of nano additives, introducing additional physical properties into the patches without alteration of the surface chemistry.
The success of this system and its achievable range was further investigated in chapter 3 by giving detailed information about patch geometry parameters including diameter, thickness and yield. For this purpose, silica particles in a size range between 1µm and 5µm were printed with different ink concentrations to change the Janus-balance of these single patched particles. A necessary intermediate step, consisting of air-plasma treatment, for the production of trivalent particles using "sandwich" printing was discovered and comparative studies concerning the patch geometry of single and double patched particles were conducted. Additionally, the usage of structured PDMS stamps during printing was described. These results demonstrate the excellent precision of this approach and opens the pathway for even greater accuracy as further parameters can be finely tuned and investigated, e.g. humidity and temperature during stamp loading.
The performance of these synthesized anisotropic colloids was further investigated in chapter 4, starting with behaviour studies in alcoholic and aqueous dispersions. Here, the stability of the applied patches was studied in a broad pH range, discovering a release mechanism by disabling the electrostatic bonding between particle surface and polyelectrolyte ink. Furthermore, the absence of strong attractive forces between divalent particles in water was investigated using XPS measurements. These results lead to the conclusion that the transfer of small PDMS oligomers onto the patch surface is shielding charges, preventing colloidal agglomeration. However, based on this knowledge, further patch modifications for particle self-assembly were introduced including physical approaches using magnetic nano additives, chemical patch functionalization with avidin-biotin or the light responsive cyclodextrin-arylazopyrazoles coupling as well as particle surface modification for the synthesis of highly amphiphilic colloids. The successful coupling, its efficiency, stability and behaviour in different solvents were evaluated to find a suitable coupling system for future assembly experiments. Based on these results the possibility of more sophisticated structures by colloidal self-assembly is given.
Certain findings needed further analysis to understand their underlying mechanics, including the relatively broad patch diameter distribution and the decreasing patch thickness for smaller silica particles. Mathematical assumptions for both effects are introduced in chapter 5. First, they demonstrate the connection between the naturally occurring particle size distribution and the broadening of the patch diameter, indicating an even higher precision for this µCP approach. Second, explaining the increase of contact area between particle and ink surface due to higher particle packaging, leading to a decrease in printing pressure for smaller particles.
These calculations ultimately lead to the development of a new mechanical microcontact printing approach, using centrifugal forces for high pressure control and excellent parallel alignment of printing substrates. First results with this device and the comparison with previously conducted by-hand experiments conclude this research. It furthermore displays the advantages of such a device for future applications using a mechanical printing approach, especially for accessing even smaller nano particles with great precision and excellent yield.
In conclusion, this work demonstrates the successful adjustment of the µCP approach using commercially available and affordable silica particles and polyelectrolytes for high flexibility, reduced costs and higher scale-up value. Furthermore, its was possible to increase the modification potential by introducing three-dimensional patches for additional functionalization volume. While keeping a high colloidal stability, different coupling systems showed the self-assembly capabilities of this toolbox for anisotropic particles.
This text is a contribution to the research on the worldwide success of evangelical Christianity and offers a new perspective on the relationship between late modern capitalism and evangelicalism. For this purpose, the utilization of affect and emotion in evangelicalism towards the mobilization of its members will be examined in order to find out what similarities to their employment in late modern capitalism can be found. Different examples from within the evangelical spectrum will be analyzed as affective economies in order to elaborate how affective mobilization is crucial for evangelicalism’s worldwide success. Pivotal point of this text is the exploration of how evangelicalism is able to activate the voluntary commitment of its members, financiers, and missionaries. Gathered here are examples where both spheres—evangelicalism and late modern capitalism—overlap and reciprocate, followed by a theoretical exploration of how the findings presented support a view of evangelicalism as an inner-worldly narcissism that contributes to an assumed re-enchantment of the world.
This doctoral dissertation aims at elucidating the development of hot and cool executive functions in middle childhood and at gaining insight about their role in childhood overweight. The dissertation is based on three empirical studies which have been published in peer-reviewed journals. Data from a large 3-year longitudinal study (the “PIER-study”) was used.
The findings presented in the dissertation demonstrated that both hot and cool EF abilities increase during middle childhood. They also supported the notion that hot and cool EF facets are distinguishable from each other in middle childhood, that they have distinct developmental trajectories, and different predictors.
Evidence was found for associations of hot and cool EF with body weight in middle childhood, which is in line with the notion that they might play a role in the self-regulation of eating and the multifactorial etiology of childhood overweight.
In this thesis we provide a construction of the operator framework starting from the functional formulation of group field theory (GFT). We define operator algebras on Hilbert spaces whose expectation values in specific states provide correlation functions of the functional formulation. Our construction allows us to give a direct relation between the ingredients of the functional GFT and its operator formulation in a perturbative regime. Using this construction we provide an example of GFT states that can not be formulated as states in a Fock space and lead to math- ematically inequivalent representations of the operator algebra. We show that such inequivalent representations can be grouped together by their symmetry properties and sometimes break the left translation symmetry of the GFT action. We interpret these groups of inequivalent representations as phases of GFT, similar to the classification of phases that we use in QFT’s on space-time.
Three Essays on EFRAG
(2018)
This cumulative doctoral thesis consists of three papers that deal with the role of one specific European accounting player in the international accounting standard-setting, namely the European Financial Reporting Advisory Group (EFRAG). The first paper examines whether and how EFRAG generally fulfills its role in articulating Europe’s interests toward the International Accounting Standards Board (IASB). The qualitative data from the conducted interviews reveal that EFRAG influences the IASB’s decision making at a very early stage, long before other constituents are officially asked to comment on the IASB’s proposals. The second paper uses quantitative data and investigates the formal participation behavior of European constituents that seek to determine EFRAG’s voice. More precisely, this paper analyzes the nature of the constituents’ participation in EFRAG’s due process in terms of representation (constituent groups and geographical distribution) and the drivers of their participation behavior. EFRAG’s official decision making process is dominated by some specific constituent groups (such as preparers and the accounting profession) and by constituents from some specific countries (e.g. those with effective enforcement regimes). The third paper investigates in a first step who of the European constituents choose which lobbying channel (participation only at IASB, only at EFRAG, or at both institutions) and unveils in a second step possible reasons for their lobbying choices. The paper comprises quantitative and qualitative data. It reveals that English skills, time issues, the size of the constituent, and the country of origin are factors that can explain why the majority participates only in the IASB’s due process.
Amorphous calcium carbonate(ACC) is a wide spread biological material found in many organisms, such as sea Urchins and mollusks, where it serves as either a precursor phase for the crystalline biominerals or is stabilized and used in the amorphous state. As ACC readily crystallizes, stabilizers such as anions, cations or macromolecules are often present to avoid or delay unwanted crystallization. Furthermore, additives often control the properties of the materials to suit the specific function needed for the organism. E.g. cystoliths in leaves that scatter light to optimize energy uptake from the sun or calcite/aragonite crystals used in protective shells in mussels and gastropods. Lifetime of the amorphous phase is controlled by the kinetic stability against crystallization. This has often been linked to water which plays a role in the mobility of ions and hence the probability of forming crystalline nuclei to initiate crystallization. However, it is unclear how the water molecules are incorporated within the amorphous phase, either as liquid confined in pores, as structural water binding to the ions or as a mixture of both. It is also unclear how this is perturbed when additives are added, especially Mg2+, one the most common additives found in biogenic samples. Mg2+ are expected to have a strong influence on the water incorporated into ACC, given the high energy barrier to dehydration of magnesium ions compared to calcium ions in solution.
During the last 10-15 years, there has been a large effort to understand the local environment of the ions/molecules and how this affects the properties of the amorphous phase. But only a few aspects of the structure have so far been well-described in literature. The reason for this is partly caused by the low stability of ACC if exposed to air, where it tends to crystallize within minutes and by the limited quantities of ACC produced in traditional synthesis routes. A further obstacle has been the difficulty in modeling the local structure based on experimental data. To solve the problem of stability and sample size, a few studies have used stabilizers such as Mg2+ or OH- and severely dehydrated samples so as to stabilize the amorphous state, allowing for combined neutron and x-ray analysis to be performed. However, so far, a clear description of the local environments of water present in the structure has not been reported.
In this study we show that ACC can be synthesized without any stabilizing additives in quantities necessary for neutron measurements and that accurate models can be derived with the help of empirical-potential structural refinement. These analyses have shown that there is a wide range of local environments for all of the components in the system suggesting that the amorphous phase is highly inhomogeneous, without any phase separation between ions and water. We also showed that the water in ACC is mainly structural and that there is no confined or liquid-like water present in the system. Analysis of amorphous magnesium carbonate also showed that there is a large difference in the local structure of the two cations and that Mg2+ surprisingly interacts with significantly less water molecules then Ca2+ despite the higher dehydration energy. All in all, this shows that the role of water molecules as a structural component of ACC, with a strong binding to cat- and anions probably retard or prevents the crystallization of the amorphous phase.
This dissertation consists of four self-contained papers that deal with the implications of financial market imperfections and heterogeneity. The analysis mainly relates to the class of incomplete-markets models but covers different research topics.
The first paper deals with the distributional effects of financial integration for developing countries. Based on a simple heterogeneous-agent approach, it is shown that capital owners experience large welfare losses while only workers moderately gain due to higher wages. The large welfare losses for capital owners contrast with the small average welfare gains from representative-agent economies and indicate that a strong opposition against capital market opening has to be expected.
The second paper considers the puzzling observation of capital flows from poor to rich countries and the accompanying changes in domestic economic development. Motivated by the mixed results from the literature, we employ an incomplete-markets model with different types of idiosyncratic risk and borrowing constraints. Based on different scenarios, we analyze under what conditions the presence of financial market imperfections contributes to explain the empirical findings and how the conditions may change with different model assumptions.
The third paper deals with the interplay of incomplete information and financial market imperfections in an incomplete-markets economy. In particular, it analyzes the impact of incomplete information about idiosyncratic income shocks on aggregate saving. The results show that the effect of incomplete information is not only quantitatively substantial but also qualitatively ambiguous and varies with the influence of the income risk and the borrowing constraint.
Finally, the fourth paper analyzes the influence of different types of fiscal rules on the response of key macroeconomic variables to a government spending shock. We find that a strong temporary increase in public debt contributes to stabilizing consumption and leisure in the first periods following the change in government spending, whereas a non-debt-intensive fiscal rule leads to a faster recovery of consumption, leisure, capital and output in later periods. Regarding optimal debt policy, we find that a debt-intensive fiscal rule leads to the largest aggregate welfare benefit and that the individual welfare gain is particularly high for wealth-poor agents.
There are numerous situations in which people ask for something or make a request, e.g. asking a favor, asking for help or requesting compliance with specific norms. For this reason, how to ask for something in order to increase people’s willingness to fulfill such requests is one of the most important question for many people working in various different fields of responsibility such as charitable giving, marketing, management or policy making.
This dissertation consists of four chapters that deal with the effects of small changes in the decision-making environment on altruistic decision-making and compliance behavior. Most notably, written communication as an influencing factor is the focus of the first three chapters. The starting point was the question how to devise a request in order to maximize its chance of success (Chapter 1). The results of the first chapter originate the ideas for the second and third chapter. Chapter 2 analyzes how communication by a neutral third-party, i.e. a text from the experimenters that either reminds potential benefactors of their responsibility or highlights their freedom of choice, affects altruistic decision-making. Chapter 3 elaborates on the effect of thanking people in advance when asking them for help. While being not as closely related to the other chapters as the three first ones are, the fourth chapter deals as well with the question how compliance (here: compliance with norms and rules) is affected by subtle manipulations of the environment in which decisions are made. This chapter analyzes the effect of default settings in a tax return on tax compliance.
In order to study the research questions outlined above, controlled experiments were conducted. Chapter 1, which analyzes the effect of text messages on the decision to give something to another person, employs a mini-dictator game. The recipient sends a free-form text message to the dictator before the latter makes a binary decision whether or not to give part of her or his endowment to the recipient. We find that putting effort into the message by writing a long note without spelling mistakes increases dictators’ willingness to give. Moreover, writing in a humorous way and mentioning reasons why the money is needed pays off. Furthermore, men and women seem to react differently to some message categories. Only men react positively to efficiency arguments, while only women react to messages that emphasize the dictator’s power and responsibility.
Building on this last result, Chapter 2 attempts to disentangle the effect of reminding potential benefactors of their responsibility for the potential beneficiary and the effect of highlighting their decision power and freedom of choice on altruistic decision-making by studying the effects of two different texts on giving in a dictator game. We find that only men react positively to a text that stresses their responsibility for the recipient by giving more to her or him, whereas only women seem to react positively to a text that emphasizes their decision power and freedom of choice.
Chapter 3 focuses on the compliance with a request. In the experiment, participants are asked to provide a detailed answer to an open question. Compliance is measured by the effort participants spend on answering the question. The treatment variable is whether or not they see the text “thanks in advance.” We find that participants react negatively by putting less effort into complying with the request in response to the phrase “thanks in advance.”
Chapter 4 studies the effect of prefilled tax returns with mostly inaccurate default values on tax compliance. In a laboratory experiment, participants earn income by performing a real-effort task and must subsequently file a tax return for three consecutive rounds. In the main treatment, the tax return is prefilled with a default value, resulting from participants’ own performance in previous rounds, which varies in its relative size. The results suggest that there is no lasting effect of a default value on tax honesty, neither for relatively low nor relatively high defaults. However, participants who face a default that is lower than their true income in the first round evade significantly and substantially more taxes in this round than participants in the control treatment without a default.
Spatio-temporal data denotes a category of data that contains spatial as well as temporal components. For example, time-series of geo-data, thematic maps that change over time, or tracking data of moving entities can be interpreted as spatio-temporal data.
In today's automated world, an increasing number of data sources exist, which constantly generate spatio-temporal data. This includes for example traffic surveillance systems, which gather movement data about human or vehicle movements, remote-sensing systems, which frequently scan our surroundings and produce digital representations of cities and landscapes, as well as sensor networks in different domains, such as logistics, animal behavior study, or climate research.
For the analysis of spatio-temporal data, in addition to automatic statistical and data mining methods, exploratory analysis methods are employed, which are based on interactive visualization. These analysis methods let users explore a data set by interactively manipulating a visualization, thereby employing the human cognitive system and knowledge of the users to find patterns and gain insight into the data.
This thesis describes a software framework for the visualization of spatio-temporal data, which consists of GPU-based techniques to enable the interactive visualization and exploration of large spatio-temporal data sets. The developed techniques include data management, processing, and rendering, facilitating real-time processing and visualization of large geo-temporal data sets. It includes three main contributions:
- Concept and Implementation of a GPU-Based Visualization Pipeline.
The developed visualization methods are based on the concept of a GPU-based visualization pipeline, in which all steps -- processing, mapping, and rendering -- are implemented on the GPU. With this concept, spatio-temporal data is represented directly in GPU memory, using shader programs to process and filter the data, apply mappings to visual properties, and finally generate the geometric representations for a visualization during the rendering process. Data processing, filtering, and mapping are thereby executed in real-time, enabling dynamic control over the mapping and a visualization process which can be controlled interactively by a user.
- Attributed 3D Trajectory Visualization.
A visualization method has been developed for the interactive exploration of large numbers of 3D movement trajectories. The trajectories are visualized in a virtual geographic environment, supporting basic geometries such as lines, ribbons, spheres, or tubes. Interactive mapping can be applied to visualize the values of per-node or per-trajectory attributes, supporting shape, height, size, color, texturing, and animation as visual properties. Using the dynamic mapping system, several kind of visualization methods have been implemented, such as focus+context visualization of trajectories using interactive density maps, and space-time cube visualization to focus on the temporal aspects of individual movements.
- Geographic Network Visualization.
A method for the interactive exploration of geo-referenced networks has been developed, which enables the visualization of large numbers of nodes and edges in a geographic context. Several geographic environments are supported, such as a 3D globe, as well as 2D maps using different map projections, to enable the analysis of networks in different contexts and scales. Interactive filtering, mapping, and selection can be applied to analyze these geographic networks, and visualization methods for specific types of networks, such as coupled 3D networks or temporal networks have been implemented.
As a demonstration of the developed visualization concepts, interactive visualization tools for two distinct use cases have been developed. The first contains the visualization of attributed 3D movement trajectories of airplanes around an airport. It allows users to explore and analyze the trajectories of approaching and departing aircrafts, which have been recorded over the period of a month. By applying the interactive visualization methods for trajectory visualization and interactive density maps, analysts can derive insight from the data, such as common flight paths, regular and irregular patterns, or uncommon incidents such as missed approaches on the airport.
The second use case involves the visualization of climate networks, which are geographic networks in the climate research domain. They represent the dynamics of the climate system using a network structure that expresses statistical interrelationships between different regions. The interactive tool allows climate analysts to explore these large networks, analyzing the network's structure and relating it to the geographic background. Interactive filtering and selection enables them to find patterns in the climate data and identify e.g. clusters in the networks or flow patterns.
Together with the gradual change of mean values, ongoing climate change is projected to increase frequency and amplitude of temperature and precipitation extremes in many regions of Europe. The impacts of such in most cases short term extraordinary climate situations on terrestrial ecosystems are a matter of central interest of recent climate change research, because it can not per se be assumed that known dependencies between climate variables and ecosystems are linearly scalable. So far, yet, there is a high demand for a method to quantify such impacts in terms of simultaneities of event time series.
In the course of this manuscript the new statistical approach of Event Coincidence Analysis (ECA) as well as it's R implementation is introduced, a methodology that allows assessing whether or not two types of event time series exhibit similar sequences of occurrences. Applications of the method are presented, analyzing climate impacts on different temporal and spacial scales: the impact of extraordinary expressions of various climatic variables on tree stem variations (subdaily and local scale), the impact of extreme temperature and precipitation events on the owering time of European shrub species (weekly and country scale), the impact of extreme temperature events on ecosystem health in terms of NDVI (weekly and continental scale) and the impact of El Niño and La Niña events on precipitation anomalies (seasonal and global scale).
The applications presented in this thesis refine already known relationships based on classical methods and also deliver substantial new findings to the scientific community: the widely known positive correlation between flowering time and temperature for example is confirmed to be valid for the tails of the distributions while the widely assumed positive dependency between stem diameter variation and temperature is shown to be not valid for very warm and very cold days. The larger scale investigations underline the sensitivity of anthrogenically shaped landscapes towards temperature extremes in Europe and provide a comprehensive global ENSO impact map for strong precipitation events.
Finally, by publishing the R implementation of the method, this thesis shall enable other researcher to further investigate on similar research questions by using Event Coincidence Analysis.
Answer Set Programming (ASP) is a declarative problem solving approach, combining a rich yet simple modeling language with high-performance solving capabilities. Although this has already resulted in various applications, certain aspects of such applications are more naturally modeled using variables over finite domains, for accounting for resources, fine timings, coordinates, or functions. Our goal is thus to extend ASP with constraints over integers while preserving its declarative nature. This allows for fast prototyping and elaboration tolerant problem descriptions of resource related applications. The resulting paradigm is called Constraint Answer Set Programming (CASP).
We present three different approaches for solving CASP problems. The first one, a lazy, modular approach combines an ASP solver with an external system for handling constraints. This approach has the advantage that two state of the art technologies work hand in hand to solve the problem, each concentrating on its part of the problem. The drawback is that inter-constraint dependencies cannot be communicated back to the ASP solver, impeding its learning algorithm. The second approach translates all constraints to ASP. Using the appropriate encoding techniques, this results in a very fast, monolithic system. Unfortunately, due to the large, explicit representation of constraints and variables, translation techniques are restricted to small and mid-sized domains. The third approach merges the lazy and the translational approach, combining the strength of both while removing their weaknesses. To this end, we enhance the dedicated learning techniques of an ASP solver with the inferences of the translating approach in a lazy way. That is, the important knowledge is only made explicit when needed.
By using state of the art techniques from neighboring fields, we provide ways to tackle real world, industrial size problems. By extending CASP to reactive solving, we open up new application areas such as online planning with continuous domains and durations.
The development of self-adaptive software requires the engineering of an adaptation engine that controls the underlying adaptable software by a feedback loop. State-of-the-art approaches prescribe the feedback loop in terms of numbers, how the activities (e.g., monitor, analyze, plan, and execute (MAPE)) and the knowledge are structured to a feedback loop, and the type of knowledge. Moreover, the feedback loop is usually hidden in the implementation or framework and therefore not visible in the architectural design. Additionally, an adaptation engine often employs runtime models that either represent the adaptable software or capture strategic knowledge such as reconfiguration strategies. State-of-the-art approaches do not systematically address the interplay of such runtime models, which would otherwise allow developers to freely design the entire feedback loop.
This thesis presents ExecUtable RuntimE MegAmodels (EUREMA), an integrated model-driven engineering (MDE) solution that rigorously uses models for engineering feedback loops. EUREMA provides a domain-specific modeling language to specify and an interpreter to execute feedback loops. The language allows developers to freely design a feedback loop concerning the activities and runtime models (knowledge) as well as the number of feedback loops. It further supports structuring the feedback loops in the adaptation engine that follows a layered architectural style. Thus, EUREMA makes the feedback loops explicit in the design and enables developers to reason about design decisions.
To address the interplay of runtime models, we propose the concept of a runtime megamodel, which is a runtime model that contains other runtime models as well as activities (e.g., MAPE) working on the contained models. This concept is the underlying principle of EUREMA. The resulting EUREMA (mega)models are kept alive at runtime and they are directly executed by the EUREMA interpreter to run the feedback loops. Interpretation provides the flexibility to dynamically adapt a feedback loop. In this context, EUREMA supports engineering self-adaptive software in which feedback loops run independently or in a coordinated fashion within the same layer as well as on top of each other in different layers of the adaptation engine. Moreover, we consider preliminary means to evolve self-adaptive software by providing a maintenance interface to the adaptation engine.
This thesis discusses in detail EUREMA by applying it to different scenarios such as single, multiple, and stacked feedback loops for self-repairing and self-optimizing the mRUBiS application. Moreover, it investigates the design and expressiveness of EUREMA, reports on experiments with a running system (mRUBiS) and with alternative solutions, and assesses EUREMA with respect to quality attributes such as performance and scalability.
The conducted evaluation provides evidence that EUREMA as an integrated and open MDE approach for engineering self-adaptive software seamlessly integrates the development and runtime environments using the same formalism to specify and execute feedback loops, supports the dynamic adaptation of feedback loops in layered architectures, and achieves an efficient execution of feedback loops by leveraging incrementality.
The sequencing of the human genome in the early 2000s led to an increased interest in cheap and fast sequencing technologies. This interest culminated in the advent of next generation sequencing (NGS). A number of different NGS platforms have arisen since then all promising to do the same thing, i.e. produce large amounts of genetic information for relatively low costs compared to more traditional methods such as Sanger sequencing. The capabilities of NGS meant that researchers were no longer bound to species for which a lot of previous work had already been done (e.g. model organisms and humans) enabling a shift in research towards more novel and diverse species of interest. This capability has greatly benefitted many fields within the biological sciences, one of which being the field of evolutionary biology. Researchers have begun to move away from the study of laboratory model organisms to wild, natural populations and species which has greatly expanded our knowledge of evolution. NGS boasts a number of benefits over more traditional sequencing approaches. The main benefit comes from the capability to generate information for drastically more loci for a fraction of the cost. This is hugely beneficial to the study of wild animals as, even when large numbers of individuals are unobtainable, the amount of data produced still allows for accurate, reliable population and species level results from a small selection of individuals.
The use of NGS to study species for which little to no previous research has been carried out on and the production of novel evolutionary information and reference datasets for the greater scientific community were the focuses of this thesis. Two studies in this thesis focused on producing novel mitochondrial genomes from shotgun sequencing data through iterative mapping, bypassing the need for a close relative to serve as a reference sequence. These mitochondrial genomes were then used to infer species level relationships through phylogenetic analyses. The first of these studies involved reconstructing a complete mitochondrial genome of the bat eared fox (Otocyon megalotis). Phylogenetic analyses of the mitochondrial genome confidently placed the bat eared fox as sister to the clade consisting of the raccoon dog and true foxes within the canidae family. The next study also involved reconstructing a mitochondrial genome but in this case from the extinct Macrauchenia of South America. As this study utilised ancient DNA, it involved a lot of parameter testing, quality controls and strict thresholds to obtain a near complete mitochondrial genome devoid of contamination known to plague ancient DNA studies. Phylogenetic analyses confidently placed Macrauchenia as sister to all living representatives of Perissodactyla with a divergence time of ~66 million years ago. The third and final study of this thesis involved de novo assemblies of both nuclear and mitochondrial genomes from brown and striped hyena and focussed on demographic, genetic diversity and population genomic analyses within the brown hyena. Previous studies of the brown hyena hinted at very low levels of genomic diversity and, perhaps due to this, were unable to find any notable population structure across its range. By incorporating a large number of genetic loci, in the form of complete nuclear genomes, population structure within the brown hyena was uncovered. On top of this, genomic diversity levels were compared to a number of other species. Results showed the brown hyena to have the lowest genomic diversity out of all species included in the study which was perhaps caused by a continuous and ongoing decline in effective population size that started about one million years ago and dramatically accelerated towards the end of the Pleistocene.
The studies within this thesis show the power NGS sequencing has and its utility within evolutionary biology. The most notable capabilities outlined in this thesis involve the study of species for which no reference data is available and in the production of large amounts of data, providing evolutionary answers at the species and population level that data produced using more traditional techniques simply could not.
Business process management is an acknowledged asset for running an organization in a productive and sustainable way. One of the most important aspects of business process management, occurring on a daily basis at all levels, is decision making. In recent years, a number of decision management frameworks have appeared in addition to existing business process management systems. More recently, Decision Model and Notation (DMN) was developed by the OMG consortium with the aim of complementing the widely used Business Process Model and Notation (BPMN). One of the reasons for the emergence of DMN is the increasing interest in the evolving paradigm known as the separation of concerns. This paradigm states that modeling decisions complementary to processes reduces process complexity by externalizing decision logic from process models and importing it into a dedicated decision model. Such an approach increases the agility of model design and execution. This provides organizations with the flexibility to adapt to the ever increasing rapid and dynamic changes in the business ecosystem. The research gap, identified by us, is that the separation of concerns, recommended by DMN, prescribes the externalization of the decision logic of process models in one or more separate decision models, but it does not specify this can be achieved.
The goal of this thesis is to overcome the presented gap by developing a framework for discovering decision models in a semi-automated way from information about existing process decision making. Thus, in this thesis we develop methodologies to extract decision models from: (1) control flow and data of process models that exist in enterprises; and (2) from event logs recorded by enterprise information systems, encapsulating day-to-day operations. Furthermore, we provide an extension of the methodologies to discover decision models from event logs enriched with fuzziness, a tool dealing with partial knowledge of the process execution information. All the proposed techniques are implemented and evaluated in case studies using real-life and synthetic process models and event logs. The evaluation of these case studies shows that the proposed methodologies provide valid and accurate output decision models that can serve as blueprints for executing decisions complementary to process models. Thus, these methodologies have applicability in the real world and they can be used, for example, for compliance checks, among other uses, which could improve the organization's decision making and hence it's overall performance.
Active and passive source data from two seismic experiments within the interdisciplinary project TIPTEQ (from The Incoming Plate to mega Thrust EarthQuake processes) were used to image and identify the structural and petrophysical properties (such as P- and S-velocities, Poisson's ratios, pore pressure, density and amount of fluids) within the Chilean seismogenic coupling zone at 38.25°S, where in 1960 the largest earthquake ever recorded (Mw 9.5) occurred. Two S-wave velocity models calculated using traveltime and noise tomography techniques were merged with an existing velocity model to obtain a 2D S-wave velocity model, which gathered the advantages of each individual model. In a following step, P- and S-reflectivity images of the subduction zone were obtained using different pre stack and post-stack depth migration techniques. Among them, the recent prestack line-drawing depth migration scheme yielded revealing results. Next, synthetic seismograms modelled using the reflectivity method allowed, through their input 1D synthetic P- and S-velocities, to infer the composition and rocks within the subduction zone. Finally, an image of the subduction zone is given, jointly interpreting the results from this work with results from other studies. The Chilean seismogenic coupling zone at 38.25°S shows a continental crust with highly reflective horizontal, as well as (steep) dipping events. Among them, the Lanalhue Fault Zone (LFZ), which is interpreted to be east-dipping, is imaged to very shallow depths. Some steep reflectors are observed for the first time, for example one near the coast, related to high seismicity and another one near the LFZ. Steep shallow reflectivity towards the volcanic arc could be related to a steep west-dipping reflector interpreted as fluids and/or melts, migrating upwards due to material recycling in the continental mantle wedge. The high resolution of the S-velocity model in the first kilometres allowed to identify several sedimentary basins, characterized by very low P- and S-velocities, high Poisson's ratios and possible steep reflectivity. Such high Poisson's ratios are also observed within the oceanic crust, which reaches the seismogenic zone hydrated due to bending-related faulting. It is interpreted to release water until reaching the coast and under the continental mantle wedge. In terms of seismic velocities, the inferred composition and rocks in the continental crust is in agreement with field geology observations at the surface along the proflle. Furthermore, there is no requirement to call on the existence of measurable amounts of present-day fluids above the plate interface in the continental crust of the Coastal Cordillera and the Central Valley in this part of the Chilean convergent margin. A large-scale anisotropy in the continental crust and upper mantle, previously proposed from magnetotelluric studies, is proposed from seismic velocities. However, quantitative studies on this topic in the continental crust of the Chilean seismogenic zone at 38.25°S do not exist to date.