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Transcending the conventional debate around efficiency in sustainable consumption, anti-consumption patterns leading to decreased levels of material consumption have been gaining importance. Change agents are crucial for the promotion of such patterns, so there may be lessons for governance interventions that can be learnt from the every-day experiences of those who actively implement and promote sustainability in the field of anti-consumption. Eighteen social innovation pioneers, who engage in and diffuse practices of voluntary simplicity and collaborative consumption as sustainable options of anti-consumption share their knowledge and personal insights in expert interviews for this research. Our qualitative content analysis reveals drivers, barriers, and governance strategies to strengthen anti-consumption patterns, which are negotiated between the market, the state, and civil society. Recommendations derived from the interviews concern entrepreneurship, municipal infrastructures in support of local grassroots projects, regulative policy measures, more positive communication to strengthen the visibility of initiatives and emphasize individual benefits, establishing a sense of community, anti-consumer activism, and education. We argue for complementary action between top-down strategies, bottom-up initiatives, corporate activities, and consumer behavior. The results are valuable to researchers, activists, marketers, and policymakers who seek to enhance their understanding of materially reduced consumption patterns based on the real-life experiences of active pioneers in the field.
Geometric electroelasticity
(2014)
In this work a diffential geometric formulation of the theory of electroelasticity is developed which also includes thermal and magnetic influences. We study the motion of bodies consisting of an elastic material that are deformed by the influence of mechanical forces, heat and an external electromagnetic field. To this end physical balance laws (conservation of mass, balance of momentum, angular momentum and energy) are established. These provide an equation that describes the motion of the body during the deformation. Here the body and the surrounding space are modeled as Riemannian manifolds, and we allow that the body has a lower dimension than the surrounding space. In this way one is not (as usual) restricted to the description of the deformation of three-dimensional bodies in a three-dimensional space, but one can also describe the deformation of membranes and the deformation in a curved space. Moreover, we formulate so-called constitutive relations that encode the properties of the used material. Balance of energy as a scalar law can easily be formulated on a Riemannian manifold. The remaining balance laws are then obtained by demanding that balance of energy is invariant under the action of arbitrary diffeomorphisms on the surrounding space. This generalizes a result by Marsden and Hughes that pertains to bodies that have the same dimension as the surrounding space and does not allow the presence of electromagnetic fields. Usually, in works on electroelasticity the entropy inequality is used to decide which otherwise allowed deformations are physically admissible and which are not. It is alsoemployed to derive restrictions to the possible forms of constitutive relations describing the material. Unfortunately, the opinions on the physically correct statement of the entropy inequality diverge when electromagnetic fields are present. Moreover, it is unclear how to formulate the entropy inequality in the case of a membrane that is subjected to an electromagnetic field. Thus, we show that one can replace the use of the entropy inequality by the demand that for a given process balance of energy is invariant under the action of arbitrary diffeomorphisms on the surrounding space and under linear rescalings of the temperature. On the one hand, this demand also yields the desired restrictions to the form of the constitutive relations. On the other hand, it needs much weaker assumptions than the arguments in physics literature that are employing the entropy inequality. Again, our result generalizes a theorem of Marsden and Hughes. This time, our result is, like theirs, only valid for bodies that have the same dimension as the surrounding space.
Current curricular trends require teachers in Baden-
Wuerttemberg (Germany) to integrate Computer Science (CS) into
traditional subjects, such as Physical Science. However, concrete guidelines
are missing. To fill this gap, we outline an approach where a
microcontroller is used to perform and evaluate measurements in the
Physical Science classroom.
Using the open-source Arduino platform, we expect students to acquire
and develop both CS and Physical Science competencies by using a
self-programmed microcontroller. In addition to this combined development
of competencies in Physical Science and CS, the subject matter
will be embedded in suitable contexts and learning environments,
such as weather and climate.
Two-dimensional bouyancy-driven convection in a horizontal fluid layer with stress-free boundary conditions at top and bottom and periodic boundary conditions in the horizontal direction is investigated by means of numerical simulation and bifurcation-analysis techniques. As the bouyancy forces increase, the primary stationary and symmetric convection rolls undergo successive Hopf bifurcations, bifurcations to traveling waves, and phase lockings. We pay attention to symmetry breaking and its connection with the generation of large-scale horizontal flows. Calculations of Lyapunov exponents indicate that at a Rayleigh number of 2.3×105 no temporal chaos is reached yet, but the system moves nonchaotically on a 4-torus in phase space.
Distances affect economic decision-making in numerous situations. The time at which we make a decision about future consumption has an impact on our consumption behavior. The spatial distance to employer, school or university impacts the place where we live and vice versa. The emotional closeness to other individuals influences our willingness to give money to them. This cumulative thesis aims to enrich the literature on the role of distance for economic decision-making. Thereby, each of my research projects sheds light on the impact of one kind of distance for efficient decision-making.
Against the background of the increasingly discussed “Linguistic Saving Hypothesis” (Chen, 2013), I studied whether the targeted use of a present tense (close tense) and a future tense (distant tense) within the same language have an impact on intertemporal decision-making. In a monetarily incentivized laboratory experiment in Germany, I implemented two different treatments on intertemporal choices. The treatments differed in the tense in which I referred to future rewards. My results show that individuals prefer to a greater extent rewards which are associated with a present tense (close tense). This result is in line with my prediction and the first empirical support for the Linguistic Saving Hypothesis within one language. However, this result holds exclusively for males. Females seem to be unaffected by the linguistic manipulation. I discuss my findings in the context of “gender-as-culture” as well as their potential policy-implications.
Zuerst erschienen in:
Alexander von Humboldt-Stiftung. Mitteilungen, 5. Jg., Heft 38, Oktober 1980, S. 27–36.
This thesis is concerned with the solution of the blind source separation problem (BSS). The BSS problem occurs frequently in various scientific and technical applications. In essence, it consists in separating meaningful underlying components out of a mixture of a multitude of superimposed signals. In the recent research literature there are two related approaches to the BSS problem: The first is known as Independent Component Analysis (ICA), where the goal is to transform the data such that the components become as independent as possible. The second is based on the notion of diagonality of certain characteristic matrices derived from the data. Here the goal is to transform the matrices such that they become as diagonal as possible. In this thesis we study the latter method of approximate joint diagonalization (AJD) to achieve a solution of the BSS problem. After an introduction to the general setting, the thesis provides an overview on particular choices for the set of target matrices that can be used for BSS by joint diagonalization. As the main contribution of the thesis, new algorithms for approximate joint diagonalization of several matrices with non-orthogonal transformations are developed. These newly developed algorithms will be tested on synthetic benchmark datasets and compared to other previous diagonalization algorithms. Applications of the BSS methods to biomedical signal processing are discussed and exemplified with real-life data sets of multi-channel biomagnetic recordings.
The knowledge of the contemporary in situ stress state is a key issue for safe and sustainable subsurface engineering. However, information on the orientation and magnitudes of the stress state is limited and often not available for the areas of interest. Therefore 3-D geomechanical-numerical modelling is used to estimate the in situ stress state and the distance of faults from failure for application in subsurface engineering. The main challenge in this approach is to bridge the gap in scale between the widely scattered data used for calibration of the model and the high resolution in the target area required for the application. We present a multi-stage 3-D geomechanical-numerical approach which provides a state-of-the-art model of the stress field for a reservoir-scale area from widely scattered data records. Therefore, we first use a large-scale regional model which is calibrated by available stress data and provides the full 3-D stress tensor at discrete points in the entire model volume. The modelled stress state is used subsequently for the calibration of a smaller-scale model located within the large-scale model in an area without any observed stress data records. We exemplify this approach with two-stages for the area around Munich in the German Molasse Basin. As an example of application, we estimate the scalar values for slip tendency and fracture potential from the model results as measures for the criticality of fault reactivation in the reservoir-scale model. The modelling results show that variations due to uncertainties in the input data are mainly introduced by the uncertain material properties and missing S-Hmax magnitude estimates needed for a more reliable model calibration. This leads to the conclusion that at this stage the model's reliability depends only on the amount and quality of available stress information rather than on the modelling technique itself or on local details of the model geometry. Any improvements in modelling and increases in model reliability can only be achieved using more high-quality data for calibration.
Information on the contemporary in-situ stress state of the earth’s crust is essential for geotechnical applications and physics-based seismic hazard assessment. Yet, stress data records for a data point are incomplete and their availability is usually not dense enough to allow conclusive statements. This demands a thorough examination of the in-situ stress field which is achieved by 3D geomechanicalnumerical models. However, the models spatial resolution is limited and the resulting local stress state is subject to large uncertainties that confine the significance of the findings. In addition, temporal variations of the in-situ stress field are naturally or anthropogenically induced. In my thesis I address these challenges in three manuscripts that investigate (1) the current crustal stress field orientation, (2) the 3D geomechanical-numerical modelling of the in-situ stress state, and (3) the phenomenon of injection induced temporal stress tensor rotations. In the first manuscript I present the first comprehensive stress data compilation of Iceland with 495 data records. Therefore, I analysed image logs from 57 boreholes in Iceland for indicators of the orientation of the maximum horizontal stress component. The study is the first stress survey from different kinds of stress indicators in a geologically very young and tectonically active area of an onshore spreading ridge. It reveals a distinct stress field with a depth independent stress orientation even very close to the spreading centre. In the second manuscript I present a calibrated 3D geomechanical-numerical modelling approach of the in-situ stress state of the Bavarian Molasse Basin that investigates the regional (70x70x10km³) and local (10x10x10km³) stress state. To link these two models I develop a multi-stage modelling approach that provides a reliable and efficient method to derive from the larger scale model initial and boundary conditions for the smaller scale model. Furthermore, I quantify the uncertainties in the models results which are inherent to geomechanical-numerical modelling in general and the multi-stage approach in particular. I show that the significance of the models results is mainly reduced due to the uncertainties in the material properties and the low number of available stress magnitude data records for calibration. In the third manuscript I investigate the phenomenon of injection induced temporal stress tensor rotation and its controlling factors. I conduct a sensitivity study with a 3D generic thermo-hydro-mechanical model. I show that the key control factors for the stress tensor rotation are the permeability as the decisive factor, the injection rate, and the initial differential stress. In particular for enhanced geothermal systems with a low permeability large rotations of the stress tensor are indicated. According to these findings the estimation of the initial differential stress in a reservoir is possible provided the permeability is known and the angle of stress rotation is observed. I propose that the stress tensor rotations can be a key factor in terms of the potential for induced seismicity on pre-existing faults due to the reorientation of the stress field that changes the optimal orientation of faults.
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against data privacy attacks. To the best of our knowledge, we are the first to directly compare the impact of differentially private training on two different neural network architectures, DenseNet121 and ResNet50. Extending the federated learning environments previously analyzed in terms of privacy, we simulated a heterogeneous and imbalanced federated setting by distributing images from the public CheXpert and Mendeley chest X-ray datasets unevenly among 36 clients. Both non-private baseline models achieved an area under the receiver operating characteristic curve (AUC) of 0.940.94 on the binary classification task of detecting the presence of a medical finding. We demonstrate that both model architectures are vulnerable to privacy violation by applying image reconstruction attacks to local model updates from individual clients. The attack was particularly successful during later training stages. To mitigate the risk of a privacy breach, we integrated Rényi differential privacy with a Gaussian noise mechanism into local model training. We evaluate model performance and attack vulnerability for privacy budgets ε∈{1,3,6,10}�∈{1,3,6,10}. The DenseNet121 achieved the best utility-privacy trade-off with an AUC of 0.940.94 for ε=6�=6. Model performance deteriorated slightly for individual clients compared to the non-private baseline. The ResNet50 only reached an AUC of 0.760.76 in the same privacy setting. Its performance was inferior to that of the DenseNet121 for all considered privacy constraints, suggesting that the DenseNet121 architecture is more robust to differentially private training.
Self-adaptive data quality
(2017)
Carrying out business processes successfully is closely linked to the quality of the data inventory in an organization. Lacks in data quality lead to problems: Incorrect address data prevents (timely) shipments to customers. Erroneous orders lead to returns and thus to unnecessary effort. Wrong pricing forces companies to miss out on revenues or to impair customer satisfaction. If orders or customer records cannot be retrieved, complaint management takes longer. Due to erroneous inventories, too few or too much supplies might be reordered.
A special problem with data quality and the reason for many of the issues mentioned above are duplicates in databases. Duplicates are different representations of same real-world objects in a dataset. However, these representations differ from each other and are for that reason hard to match by a computer. Moreover, the number of required comparisons to find those duplicates grows with the square of the dataset size. To cleanse the data, these duplicates must be detected and removed. Duplicate detection is a very laborious process. To achieve satisfactory results, appropriate software must be created and configured (similarity measures, partitioning keys, thresholds, etc.). Both requires much manual effort and experience.
This thesis addresses automation of parameter selection for duplicate detection and presents several novel approaches that eliminate the need for human experience in parts of the duplicate detection process.
A pre-processing step is introduced that analyzes the datasets in question and classifies their attributes semantically. Not only do these annotations help understanding the respective datasets, but they also facilitate subsequent steps, for example, by selecting appropriate similarity measures or normalizing the data upfront. This approach works without schema information.
Following that, we show a partitioning technique that strongly reduces the number of pair comparisons for the duplicate detection process. The approach automatically finds particularly suitable partitioning keys that simultaneously allow for effective and efficient duplicate retrieval. By means of a user study, we demonstrate that this technique finds partitioning keys that outperform expert suggestions and additionally does not need manual configuration. Furthermore, this approach can be applied independently of the attribute types.
To measure the success of a duplicate detection process and to execute the described partitioning approach, a gold standard is required that provides information about the actual duplicates in a training dataset. This thesis presents a technique that uses existing duplicate detection results and crowdsourcing to create a near gold standard that can be used for the purposes above. Another part of the thesis describes and evaluates strategies how to reduce these crowdsourcing costs and to achieve a consensus with less effort.
Biofilms are complex living materials that form as bacteria get embedded in a matrix of self-produced protein and polysaccharide fibres. The formation of a network of extracellular biopolymer fibres contributes to the cohesion of the biofilm by promoting cell-cell attachment and by mediating biofilm-substrate interactions. This sessile mode of bacteria growth has been well studied by microbiologists to prevent the detrimental effects of biofilms in medical and industrial settings. Indeed, biofilms are associated with increased antibiotic resistance in bacterial infections, and they can also cause clogging of pipelines or promote bio-corrosion. However, biofilms also gained interest from biophysics due to their ability to form complex morphological patterns during growth. Recently, the emerging field of engineered living materials investigates biofilm mechanical properties at multiple length scales and leverages the tools of synthetic biology to tune the functions of their constitutive biopolymers.
This doctoral thesis aims at clarifying how the morphogenesis of Escherichia coli (E. coli) biofilms is influenced by their growth dynamics and mechanical properties. To address this question, I used methods from cell mechanics and materials science. I first studied how biological activity in biofilms gives rise to non-uniform growth patterns. In a second study, I investigated how E. coli biofilm morphogenesis and its mechanical properties adapt to an environmental stimulus, namely the water content of their substrate. Finally, I estimated how the mechanical properties of E. coli biofilms are altered when the bacteria express different extracellular biopolymers.
On nutritive hydrogels, micron-sized E. coli cells can build centimetre-large biofilms. During this process, bacterial proliferation and matrix production introduce mechanical stresses in the biofilm, which release through the formation of macroscopic wrinkles and delaminated buckles. To relate these biological and mechanical phenomena, I used time-lapse fluorescence imaging to track cell and matrix surface densities through the early and late stages of E. coli biofilm growth. Colocalization of high cell and matrix densities at the periphery precede the onset of mechanical instabilities at this annular region. Early growth is detected at this outer annulus, which was analysed by adding fluorescent microspheres to the bacterial inoculum. But only when high rates of matrix production are present in the biofilm centre, does overall biofilm spreading initiate along the solid-air interface. By tracking larger fluorescent particles for a long time, I could distinguish several kinematic stages of E. coli biofilm expansion and observed a transition from non-linear to linear velocity profiles, which precedes the emergence of wrinkles at the biofilm periphery. Decomposing particle velocities to their radial and circumferential components revealed a last kinematic stage, where biofilm movement is mostly directed towards the radial delaminated buckles, which verticalize. The resulting compressive strains computed in these regions were observed to substantially deform the underlying agar substrates. The co-localization of higher cell and matrix densities towards an annular region and the succession of several kinematic stages are thus expected to promote the emergence of mechanical instabilities at the biofilm periphery. These experimental findings are predicted to advance future modelling approaches of biofilm morphogenesis.
E. coli biofilm morphogenesis is further anticipated to depend on external stimuli from the environment. To clarify how the water could be used to tune biofilm material properties, we quantified E. coli biofilm growth, wrinkling dynamics and rigidity as a function of the water content of the nutritive substrates. Time-lapse microscopy and computational image analysis revealed that substrates with high water content promote biofilm spreading kinetics, while substrates with low water content promote biofilm wrinkling. The wrinkles observed on biofilm cross-sections appeared more bent on substrates with high water content, while they tended to be more vertical on substrates with low water content. Both wet and dry biomass, accumulated over 4 days of culture, were larger in biofilms cultured on substrates with high water content, despite extra porosity within the matrix layer. Finally, the micro-indentation analysis revealed that substrates with low water content supported the formation of stiffer biofilms. This study shows that E. coli biofilms respond to the water content of their substrate, which might be used for tuning their material properties in view of further applications.
Biofilm material properties further depend on the composition and structure of the matrix of extracellular proteins and polysaccharides. In particular, E. coli biofilms were suggested to present tissue-like elasticity due to a dense fibre network consisting of amyloid curli and phosphoethanolamine-modified cellulose. To understand the contribution of these components to the emergent mechanical properties of E. coli biofilms, we performed micro-indentation on biofilms grown from bacteria of several strains. Besides showing higher dry masses, larger spreading diameters and slightly reduced water contents, biofilms expressing both main matrix components also presented high rigidities in the range of several hundred kPa, similar to biofilms containing only curli fibres. In contrast, a lack of amyloid curli fibres provides much higher adhesive energies and more viscoelastic fluid-like material behaviour. Therefore, the combination of amyloid curli and phosphoethanolamine-modified cellulose fibres implies the formation of a composite material whereby the amyloid curli fibres provide rigidity to E. coli biofilms, whereas the phosphoethanolamine-modified cellulose rather acts as a glue. These findings motivate further studies involving purified versions of these protein and polysaccharide components to better understand how their interactions benefit biofilm functions.
All three studies depict different aspects of biofilm morphogenesis, which are interrelated. The first work reveals the correlation between non-uniform biological activities and the emergence of mechanical instabilities in the biofilm. The second work acknowledges the adaptive nature of E. coli biofilm morphogenesis and its mechanical properties to an environmental stimulus, namely water. Finally, the last study reveals the complementary role of the individual matrix components in the formation of a stable biofilm material, which not only forms complex morphologies but also functions as a protective shield for the bacteria it contains. Our experimental findings on E. coli biofilm morphogenesis and their mechanical properties can have further implications for fundamental and applied biofilm research fields.
The European rabbit (Oryctolagus cuniculus) is declining in large parts of Europe but populations in some German cities remained so far unaffected by this decline. The question arises of how urbanization affects patterns of population genetic variation and differentiation in German rabbit populations, as urban habitat fragmentation may result in altered meta-population dynamics. To address this question, we used microsatellite markers to genotype rabbit populations occurring along a rural-to-urban gradient in and around the city of Frankfurt, Germany. We found no effect of urbanization on allelic richness. However, the observed heterozygosity was significantly higher in urban than rural populations and also the inbreeding coefficients were lower, most likely reflecting the small population sizes and possibly on-going loss of genetic diversity in structurally impoverished rural areas. Global FST and G'ST-values suggest moderate but significant differentiation between populations. Multiple matrix regression with randomization ascribed this differentiation to isolation-by-environment rather than isolation-by-distance. Analyses of migration rates revealed asymmetrical gene flow, which was higher from rural into urban populations than vice versa and may again reflect intensified agricultural land-use practices in rural areas. We discuss that populations inhabiting urban areas will likely play an important role in the future distribution of European rabbits.
Background: Multidirectional interactions in social networks can have a profound effect on mate choice behavior; e.g., Poecilia mexicana males show weaker expression of mating preferences when being observed by a rival. This may be an adaptation to reduce sperm competition risk, which arises because commonly preferred female phenotypes will receive attention also from surrounding males, and/or because other males can copy the focal male's mate choice. Do P. mexicana males indeed respond to perceived sperm competition risk? We gave males a choice between two females and repeated the tests under one of the following conditions: (1) an empty transparent cylinder was presented (control); (2) another ("audience") male inside the cylinder observed the focal male throughout the 2nd part, or (3) the audience male was presented only before the tests, but could not eavesdrop during the actual choice tests (non-specific sperm competition risk treatments); (4) the focal male could see a rival male interact sexually with the previously preferred, or (5) with the non-preferred female before the 2nd part of the tests (specific sperm competition risk treatments). Results: The strength of individual male preferences declined slightly also during the control treatment (1). However, this decrease was more than two-fold stronger in audience treatment (2), i.e., with non-specific sperm competition risk including the possibility for visual eavesdropping by the audience male. No audience effect was found in treatments (3) and (5), but a weak effect was also observed when the focal male had seen the previously preferred female sexually interact with a rival male (treatment 4; specific sperm competition risk). Conclusion: When comparing the two 'non-specific sperm competition risk' treatments, a very strong effect was found only when the audience male could actually observe the focal male during mate choice [treatment (2)]. This suggests that focal males indeed attempt to conceal their mating preferences so as to prevent surrounding males from copying their mate choice. When there is no potential for eavesdropping [treatment (3)], non-specific specific sperm competition risk seems to play a minor or no role. Our results also show that P. mexicana males tend to share their mating effort more equally among females when the resource value of their previously preferred mate decreases after mating with a rival male (perceived specific sperm competition risk), but this effect is comparatively weak.
Concerns have been raised that anthropogenic climate change could lead to large-scale singular climate events, i.e., abrupt nonlinear climate changes with repercussions on regional to global scales. One central goal of this thesis is the development of models of two representative components of the climate system that could exhibit singular behavior: the Atlantic thermohaline circulation (THC) and the Indian monsoon. These models are conceived so as to fulfill the main requirements of integrated assessment modeling, i.e., reliability, computational efficiency, transparency and flexibility. The model of the THC is an interhemispheric four-box model calibrated against data generated with a coupled climate model of intermediate complexity. It is designed to be driven by global mean temperature change which is translated into regional fluxes of heat and freshwater through a linear down-scaling procedure. Results of a large number of transient climate change simulations indicate that the reduced-form THC model is able to emulate key features of the behavior of comprehensive climate models such as the sensitivity of the THC to the amount, regional distribution and rate of change in the heat and freshwater fluxes. The Indian monsoon is described by a novel one-dimensional box model of the tropical atmosphere. It includes representations of the radiative and surface fluxes, the hydrological cycle and surface hydrology. Despite its high degree of idealization, the model satisfactorily captures relevant aspects of the observed monsoon dynamics, such as the annual course of precipitation and the onset and withdrawal of the summer monsoon. Also, the model exhibits the sensitivity to changes in greenhouse gas and sulfate aerosol concentrations that are known from comprehensive models. A simplified version of the monsoon model is employed for the identification of changes in the qualitative system behavior against changes in boundary conditions. The most notable result is that under summer conditions a saddle-node bifurcation occurs at critical values of the planetary albedo or insolation. Furthermore, the system exhibits two stable equilibria: besides the wet summer monsoon, a stable state exists which is characterized by a weak hydrological cycle. These results are remarkable insofar, as they indicate that anthropogenic perturbations of the planetary albedo such as sulfur emissions and/or land-use changes could destabilize the Indian summer monsoon. The reduced-form THC model is employed in an exemplary integrated assessment application. Drawing on the conceptual and methodological framework of the tolerable windows approach, emissions corridors (i.e., admissible ranges of CO2- emissions) are derived that limit the risk of a THC collapse while considering expectations about the socio-economically acceptable pace of emissions reductions. Results indicate, for example, a large dependency of the width of the emissions corridor on climate and hydrological sensitivity: for low values of climate and/or hydrological sensitivity, the corridor boundaries are far from being transgressed by any plausible emissions scenario for the 21st century. In contrast, for high values of both quantities low non-intervention scenarios leave the corridor already in the early decades of the 21st century. This implies that if the risk of a THC collapse is to be kept low, business-as-usual paths would need to be abandoned within the next two decades. All in all, this thesis highlights the value of reduced-form modeling by presenting a number of applications of this class of models, ranging from sensitivity and bifurcation analysis to integrated assessment. The results achieved and conclusions drawn provide a useful contribution to the scientific and policy debate about the consequences of anthropogenic climate change and the long-term goals of climate protection. --- Anmerkung: Die Autorin ist Trägerin des von der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Potsdam vergebenen Michelson-Preises für die beste Promotion des Jahres 2003/2004.
Mosses are a major component of the arctic vegetation, particularly in wetlands. We present C / N atomic ratio, delta C-13 and delta N-15 data of 400 brown-moss samples belonging to 10 species that were collected along hydrological gradients within polygonal mires located on the southern Taymyr Peninsula and the Lena River delta in northern Siberia. Additionally, n-alkane patterns of six of these species (16 samples) were investigated. The aim of the study is to see whether the inter-and intraspecific differences in C / N, isotopic compositions and n-alkanes are indicative of habitat, particularly with respect to water level. Overall, we find high variability in all investigated parameters for two different moisture-related groups of moss species. The C / N ratios range between 11 and 53 (median: 32) and show large variations at the intraspecific level. However, species preferring a dry habitat (xero-mesophilic mosses) show higher C / N ratios than those preferring a wet habitat (meso-hygrophilic mosses). The delta C-13 values range between 37.0 and 22.5% (median D 27.8 %). The delta N-15 values range between 6.6 and C 1.7%(median D 2.2 %). We find differences in delta C-13 and delta N-15 compositions between both habitat types. For some species of the meso-hygrophilic group, we suggest that a relationship between the individ-ual habitat water level and isotopic composition can be inferred as a function of microbial symbiosis. The n-alkane distribution also shows differences primarily between xeromesophilic and meso-hygrophilic mosses, i. e. having a dominance of n-alkanes with long (n-C29, n-C31 /and intermediate (n-C25 /chain lengths, respectively. Overall, our results reveal that C / N ratios, isotopic signals and n-alkanes of studied brown-moss taxa from polygonal wetlands are characteristic of their habitat.
A doppelalgebra is an algebra defined on a vector space with two binary linear associative operations. Doppelalgebras play a prominent role in algebraic K-theory. We consider doppelsemigroups, that is, sets with two binary associative operations satisfying the axioms of a doppelalgebra. Doppelsemigroups are a generalization of semigroups and they have relationships with such algebraic structures as interassociative semigroups, restrictive bisemigroups, dimonoids, and trioids.
In the lecture notes numerous examples of doppelsemigroups and of strong doppelsemigroups are given. The independence of axioms of a strong doppelsemigroup is established. A free product in the variety of doppelsemigroups is presented. We also construct a free (strong) doppelsemigroup, a free commutative (strong) doppelsemigroup, a free n-nilpotent (strong) doppelsemigroup, a free n-dinilpotent (strong) doppelsemigroup, and a free left n-dinilpotent doppelsemigroup. Moreover, the least commutative congruence, the least n-nilpotent congruence, the least n-dinilpotent congruence on a free (strong) doppelsemigroup and the least left n-dinilpotent congruence on a free doppelsemigroup are characterized.
The book addresses graduate students, post-graduate students, researchers in algebra and interested readers.
The all-female Amazon molly (Poecilia formosa) originated from a single hybridization of two bisexual ancestors, Atlantic molly (Poecilia mexicana) and sailfin molly (Poecilia latipinna). As a gynogenetic species, the Amazon molly needs to copulate with a heterospecific male, but the genetic information of the sperm-donor does not contribute to the next generation, as the sperm only acts as the trigger for the diploid eggs’ embryogenesis. Here, we study the sequence evolution and gene expression of the duplicated genes coding for androgen receptors (ars) and other pathway-related genes, i.e., the estrogen receptors (ers) and cytochrome P450, family19, subfamily A, aromatase genes (cyp19as), in the Amazon molly, in comparison to its bisexual ancestors. Mollies possess–as most other teleost fish—two copies of the ar, er, and cyp19a genes, i.e., arα/arβ, erα/erβ1, and cyp19a1 (also referred as cyp19a1a)/cyp19a2 (also referred to as cyp19a1b), respectively. Non-synonymous single nucleotide polymorphisms (SNPs) among the ancestral bisexual species were generally predicted not to alter protein function. Some derived substitutions in the P. mexicana and one in P. formosa are predicted to impact protein function. We also describe the gene expression pattern of the ars and pathway-related genes in various tissues (i.e., brain, gill, and ovary) and provide SNP markers for allele specific expression research. As a general tendency, the levels of gene expression were lowest in gill and highest in ovarian tissues, while expression levels in the brain were intermediate in most cases. Expression levels in P. formosa were conserved where expression did not differ between the two bisexual ancestors. In those cases where gene expression levels significantly differed between the bisexual species, P. formosa expression was always comparable to the higher expression level among the two ancestors. Interestingly, erβ1 was expressed neither in brain nor in gill in the analyzed three molly species, which implies a more important role of erα in the estradiol synthesis pathway in these tissues. Furthermore, our data suggest that interactions of steroid-signaling pathway genes differ across tissues, in particular the interactions of ars and cyp19as.
The all-female Amazon molly (Poecilia formosa) is the result of a hybridization of the Atlantic molly (P. mexicana) and the sailfin molly (P. latipinna) approximately 120,000 years ago. As a gynogenetic species, P. formosa needs to copulate with heterospecific males including males from one of its bisexual ancestral species. However, the sperm only triggers embryogenesis of the diploid eggs. The genetic information of the sperm donor typically will not contribute to the next generation of P. formosa. Hence, P. formosa possesses generally one allele from each of its ancestral species at any genetic locus. This raises the question whether both ancestral alleles are equally expressed in P. formosa. Allele-specific expression (ASE) has been previously assessed in various organisms, e.g., human and fish, and ASE was found to be important in the context of phenotypic variability and disease. In this study, we utilized Real-Time PCR techniques to estimate ASE of the androgen receptor alpha (arα) gene in several distinct tissues of Amazon mollies. We found an allelic bias favoring the maternal ancestor (P. mexicana) allele in ovarian tissue. This allelic bias was not observed in the gill or the brain tissue. Sequencing of the promoter regions of both alleles revealed an association between an Indel in a known CpG island and differential expression. Future studies may reveal whether our observed cis-regulatory divergence is caused by an ovary-specific trans-regulatory element, preferentially activating the allele of the maternal ancestor.
The European Water Framework Directive (WFD) has identified river morphological alteration and diffuse pollution as the two main pressures affecting water bodies in Europe at the catchment scale. Consequently, river restoration has become a priority to achieve the WFD's objective of good ecological status. However, little is known about the effects of stream morphological changes, such as re-meandering, on in-stream nitrate retention at the river network scale. Therefore, catchment nitrate modeling is necessary to guide the implementation of spatially targeted and cost-effective mitigation measures. Meanwhile, Germany, like many other regions in central Europe, has experienced consecutive summer droughts from 2015-2018, resulting in significant changes in river nitrate concentrations in various catchments. However, the mechanistic exploration of catchment nitrate responses to changing weather conditions is still lacking.
Firstly, a fully distributed, process-based catchment Nitrate model (mHM-Nitrate) was used, which was properly calibrated and comprehensively evaluated at numerous spatially distributed nitrate sampling locations. Three calibration schemes were designed, taking into account land use, stream order, and mean nitrate concentrations, and they varied in spatial coverage but used data from the same period (2011–2019). The model performance for discharge was similar among the three schemes, with Nash-Sutcliffe Efficiency (NSE) scores ranging from 0.88 to 0.92. However, for nitrate concentrations, scheme 2 outperformed schemes 1 and 3 when compared to observed data from eight gauging stations. This was likely because scheme 2 incorporated a diverse range of data, including low discharge values and nitrate concentrations, and thus provided a better representation of within-catchment heterogenous. Therefore, the study suggests that strategically selecting gauging stations that reflect the full range of within-catchment heterogeneity is more important for calibration than simply increasing the number of stations.
Secondly, the mHM-Nitrate model was used to reveal the causal relations between sequential droughts and nitrate concentration in the Bode catchment (3200 km2) in central Germany, where stream nitrate concentrations exhibited contrasting trends from upstream to downstream reaches. The model was evaluated using data from six gauging stations, reflecting different levels of runoff components and their associated nitrate-mixing from upstream to downstream. Results indicated that the mHM-Nitrate model reproduced dynamics of daily discharge and nitrate concentration well, with Nash-Sutcliffe Efficiency ≥ 0.73 for discharge and Kling-Gupta Efficiency ≥ 0.50 for nitrate concentration at most stations. Particularly, the spatially contrasting trends of nitrate concentration were successfully captured by the model. The decrease of nitrate concentration in the lowland area in drought years (2015-2018) was presumably due to (1) limited terrestrial export loading (ca. 40% lower than that of normal years 2004-2014), and (2) increased in-stream retention efficiency (20% higher in summer within the whole river network). From a mechanistic modelling perspective, this study provided insights into spatially heterogeneous flow and nitrate dynamics and effects of sequential droughts, which shed light on water-quality responses to future climate change, as droughts are projected to be more frequent.
Thirdly, this study investigated the effects of stream restoration via re-meandering on in-stream nitrate retention at network-scale in the well-monitored Bode catchment. The mHM-Nitrate model showed good performance in reproducing daily discharge and nitrate concentrations, with median Kling-Gupta values of 0.78 and 0.74, respectively. The mean and standard deviation of gross nitrate retention efficiency, which accounted for both denitrification and assimilatory uptake, were 5.1 ± 0.61% and 74.7 ± 23.2% in winter and summer, respectively, within the stream network. The study found that in the summer, denitrification rates were about two times higher in lowland sub-catchments dominated by agricultural lands than in mountainous sub-catchments dominated by forested areas, with median ± SD of 204 ± 22.6 and 102 ± 22.1 mg N m-2 d-1, respectively. Similarly, assimilatory uptake rates were approximately five times higher in streams surrounded by lowland agricultural areas than in those in higher-elevation, forested areas, with median ± SD of 200 ± 27.1 and 39.1 ± 8.7 mg N m-2 d-1, respectively. Therefore, restoration strategies targeting lowland agricultural areas may have greater potential for increasing nitrate retention. The study also found that restoring stream sinuosity could increase net nitrate retention efficiency by up to 25.4 ± 5.3%, with greater effects seen in small streams. These results suggest that restoration efforts should consider augmenting stream sinuosity to increase nitrate retention and decrease nitrate concentrations at the catchment scale.
In this talk, I would like to share my experiences gained from participating in four CSP solver competitions and the second ASP solver competition. In particular, I’ll talk about how various programming techniques can make huge differences in solving some of the benchmark problems used in the competitions. These techniques include global constraints, table constraints, and problem-specific propagators and labeling strategies for selecting variables and values. I’ll present these techniques with experimental results from B-Prolog and other CLP(FD) systems.
How We Found Our IMU
(2020)
Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection procedures. However, selecting the most suitable IMU device for a certain use case is increasingly challenging. In this study, guidelines for IMU selection are proposed. In particular, seven IMUs were compared in terms of their specifications, data collection procedures, and raw data quality. Data collected from the IMUs were then analyzed by a gait analysis algorithm. The difference in accuracy of the calculated gait parameters between the IMUs could be used to retrace the issues in raw data, such as acceleration range or sensor calibration. Based on our algorithm, we were able to identify the best-suited IMUs for our needs. This study provides an overview of how to select the IMUs based on the area of study with concrete examples, and gives insights into the features of seven commercial IMUs using real data.
To what extent cities can be made sustainable under the mega-trends of urbanization and climate change remains a matter of unresolved scientific debate. Our inability in answering this question lies partly in the deficient knowledge regarding pivotal humanenvironment interactions. Regarded as the most well documented anthropogenic climate modification, the urban heat island (UHI) effect – the warmth of urban areas relative to the rural hinterland – has raised great public health concerns globally. Worse still, heat waves are being observed and are projected to increase in both frequency and intensity, which further impairs the well-being of urban dwellers. Albeit with a substantial increase in the number of publications on UHI in the recent decades, the diverse urban-rural definitions applied in previous studies have remarkably hampered the general comparability of results achieved. In addition, few studies have attempted to synergize the land use data and thermal remote sensing to systematically assess UHI and its contributing factors.
Given these research gaps, this work presents a general framework to systematically quantify the UHI effect based on an automated algorithm, whereby cities are defined as clusters of maximum spatial continuity on the basis of land use data, with their rural hinterland being defined analogously. By combining land use data with spatially explicit surface skin temperatures from satellites, the surface UHI intensity can be calculated in a consistent and robust manner. This facilitates monitoring, benchmarking, and categorizing UHI intensities for cities across scales. In light of this innovation, the relationship between city size and UHI intensity has been investigated, as well as the contributions of urban form indicators to the UHI intensity.
This work delivers manifold contributions to the understanding of the UHI, which have complemented and advanced a number of previous studies. Firstly, a log-linear relationship between surface UHI intensity and city size has been confirmed among the 5,000 European cities. The relationship can be extended to a log-logistic one, when taking a wider range of small-sized cities into account. Secondly, this work reveals a complex interplay between UHI intensity and urban form. City size is found to have the strongest influence on the UHI intensity, followed by the fractality and the anisometry. However, their relative contributions to the surface UHI intensity depict a pronounced regional heterogeneity, indicating the importance of considering spatial patterns of UHI while implementing UHI adaptation measures.
Lastly, this work presents a novel seasonality of the UHI intensity for individual clusters in the form of hysteresis-like curves, implying a phase shift between the time series of UHI intensity and background temperatures. Combining satellite observation and urban boundary layer simulation, the seasonal variations of UHI are assessed from both screen and skin levels. Taking London as an example, this work ascribes the discrepancies between the seasonality observed at different levels mainly to the peculiarities of surface skin temperatures associated with the incoming solar radiation. In addition, the efforts in classifying cities according to their UHI characteristics highlight the important role of regional climates in determining the UHI.
This work serves as one of the first studies conducted to systematically and statistically scrutinize the UHI. The outcomes of this work are of particular relevance for the overall spatial planning and regulation at meso- and macro levels in order to harness the benefits of rapid urbanization, while proactively minimizing its ensuing thermal stress.
Organic photovoltaics based on non-fullerene acceptors (NFAs) show record efficiency of 16 to 17% and increased photovoltage owing to the low driving force for interfacial charge-transfer. However, the low driving force potentially slows down charge generation, leading to a tradeoff between voltage and current. Here, we disentangle the intrinsic charge-transfer rates from morphology-dependent exciton diffusion for a series of polymer:NFA systems. Moreover, we establish the influence of the interfacial energetics on the electron and hole transfer rates separately. We demonstrate that charge-transfer timescales remain at a few hundred femtoseconds even at near-zero driving force, which is consistent with the rates predicted by Marcus theory in the normal region, at moderate electronic coupling and at low re-organization energy. Thus, in the design of highly efficient devices, the energy offset at the donor:acceptor interface can be minimized without jeopardizing the charge-transfer rate and without concerns about a current-voltage tradeoff.
Noise is ubiquitous in nature and usually results in rich dynamics in stochastic systems such as oscillatory systems, which exist in such various fields as physics, biology and complex networks. The correlation and synchronization of two or many oscillators are widely studied topics in recent years.
In this thesis, we mainly investigate two problems, i.e., the stochastic bursting phenomenon in noisy excitable systems and synchronization in a three-dimensional Kuramoto model with noise. Stochastic bursting here refers to a sequence of coherent spike train, where each spike has random number of followers due to the combined effects of both time delay and noise. Synchronization, as a universal phenomenon in nonlinear dynamical systems, is well illustrated in the Kuramoto model, a prominent model in the description of collective motion.
In the first part of this thesis, an idealized point process, valid if the characteristic timescales in the problem are well separated, is used to describe statistical properties such as the power spectral density and the interspike interval distribution. We show how the main parameters of the point process, the spontaneous excitation rate, and the probability to induce a spike during the delay action can be calculated from the solutions of a stationary and a forced Fokker-Planck equation. We extend it to the delay-coupled case and derive analytically the statistics of the spikes in each neuron, the pairwise correlations between any two neurons, and the spectrum of the total output from the network.
In the second part, we investigate the three-dimensional noisy Kuramoto model, which can be used to describe the synchronization in a swarming model with helical trajectory. In the case without natural frequency, the Kuramoto model can be connected with the Vicsek model, which is widely studied in collective motion and swarming of active matter. We analyze the linear stability of the incoherent state and derive the critical coupling strength above which the incoherent state loses stability. In the limit of no natural frequency, an exact self-consistent equation of the mean field is derived and extended straightforward to any high-dimensional case.
The plasmasphere is a dynamic region of cold, dense plasma surrounding the Earth. Its shape and size are highly susceptible to variations in solar and geomagnetic conditions. Having an accurate model of plasma density in the plasmasphere is important for GNSS navigation and for predicting hazardous effects of radiation in space on spacecraft. The distribution of cold plasma and its dynamic dependence on solar wind and geomagnetic conditions remain, however, poorly quantified. Existing empirical models of plasma density tend to be oversimplified as they are based on statistical averages over static parameters. Understanding the global dynamics of the plasmasphere using observations from space remains a challenge, as existing density measurements are sparse and limited to locations where satellites can provide in-situ observations. In this dissertation, we demonstrate how such sparse electron density measurements can be used to reconstruct the global electron density distribution in the plasmasphere and capture its dynamic dependence on solar wind and geomagnetic conditions.
First, we develop an automated algorithm to determine the electron density from in-situ measurements of the electric field on the Van Allen Probes spacecraft. In particular, we design a neural network to infer the upper hybrid resonance frequency from the dynamic spectrograms obtained with the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite, which is then used to calculate the electron number density. The developed Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm is applied to more than four years of EMFISIS measurements to produce the publicly available electron density data set.
We utilize the obtained electron density data set to develop a new global model of plasma density by employing a neural network-based modeling approach. In addition to the location, the model takes the time history of geomagnetic indices and location as inputs, and produces electron density in the equatorial plane as an output. It is extensively validated using in-situ density measurements from the Van Allen Probes mission, and also by comparing the predicted global evolution of the plasmasphere with the global IMAGE EUV images of He+ distribution. The model successfully reproduces erosion of the plasmasphere on the night side as well as plume formation and evolution, and agrees well with data.
The performance of neural networks strongly depends on the availability of training data, which is limited during intervals of high geomagnetic activity. In order to provide reliable density predictions during such intervals, we can employ physics-based modeling. We develop a new approach for optimally combining the neural network- and physics-based models of the plasmasphere by means of data assimilation. The developed approach utilizes advantages of both neural network- and physics-based modeling and produces reliable global plasma density reconstructions for quiet, disturbed, and extreme geomagnetic conditions.
Finally, we extend the developed machine learning-based tools and apply them to another important problem in the field of space weather, the prediction of the geomagnetic index Kp. The Kp index is one of the most widely used indicators for space weather alerts and serves as input to various models, such as for the thermosphere, the radiation belts and the plasmasphere. It is therefore crucial to predict the Kp index accurately. Previous work in this area has mostly employed artificial neural networks to nowcast and make short-term predictions of Kp, basing their inferences on the recent history of Kp and solar wind measurements at L1. We analyze how the performance of neural networks compares to other machine learning algorithms for nowcasting and forecasting Kp for up to 12 hours ahead. Additionally, we investigate several machine learning and information theory methods for selecting the optimal inputs to a predictive model of Kp. The developed tools for feature selection can also be applied to other problems in space physics in order to reduce the input dimensionality and identify the most important drivers.
Research outlined in this dissertation clearly demonstrates that machine learning tools can be used to develop empirical models from sparse data and also can be used to understand the underlying physical processes. Combining machine learning, physics-based modeling and data assimilation allows us to develop novel methods benefiting from these different approaches.
Although the use of stable transformation technology has led to great insight into gene function, its application in high-throughput studies remains arduous. Agro-infiltration have been widely used in species such as Nicotiana benthamiana for the rapid detection of gene expression and protein interaction analysis, but this technique does not work efficiently in other plant species, including Arabidopsis thaliana. As an efficient high-throughput transient expression system is currently lacking in the model plant species A. thaliana, we developed a method that is characterized by high efficiency, reproducibility, and suitability for transient expression of a variety of functional proteins in A. thaliana and 7 other plant species, including Brassica oleracea, Capsella rubella, Thellungiella salsuginea, Thellungiella halophila, Solanum tuberosum, Capsicum annuum, and N. benthamiana. Efficiency of this method was independently verified in three independent research facilities, pointing to the robustness of this technique. Furthermore, in addition to demonstrating the utility of this technique in a range of species, we also present a case study employing this method to assess protein-protein interactions in the sucrose biosynthesis pathway in Arabidopsis.
Evaluation of nitrogen dynamics in high-order streams and rivers based on high-frequency monitoring
(2023)
Nutrient storage, transform and transport are important processes for achieving environmental and ecological health, as well as conducting water management plans. Nitrogen is one of the most noticeable elements due to its impacts on tremendous consequences of eutrophication in aquatic systems. Among all nitrogen components, researches on nitrate are blooming because of widespread deployments of in-situ high-frequency sensors. Monitoring and studying nitrate can become a paradigm for any other reactive substances that may damage environmental conditions and cause economic losses.
Identifying nitrate storage and its transport within a catchment are inspiring to the management of agricultural activities and municipal planning. Storm events are periods when hydrological dynamics activate the exchange between nitrate storage and flow pathways. In this dissertation, long-term high-frequency monitoring data at three gauging stations in the Selke river were used to quantify event-scale nitrate concentration-discharge (C-Q) hysteretic relationships. The Selke catchment is characterized into three nested subcatchments by heterogeneous physiographic conditions and land use. With quantified hysteresis indices, impacts of seasonality and landscape gradients on C-Q relationships are explored. For example, arable area has deep nitrate legacy and can be activated with high intensity precipitation during wetting/wet periods (i.e., the strong hydrological connectivity). Hence, specific shapes of C-Q relationships in river networks can identify targeted locations and periods for agricultural management actions within the catchment to decrease nitrate output into downstream aquatic systems like the ocean.
The capacity of streams for removing nitrate is of both scientific and social interest, which makes the quantification motivated. Although measurements of nitrate dynamics are advanced compared to other substances, the methodology to directly quantify nitrate uptake pathways is still limited spatiotemporally. The major problem is the complex convolution of hydrological and biogeochemical processes, which limits in-situ measurements (e.g., isotope addition) usually to small streams with steady flow conditions. This makes the extrapolation of nitrate dynamics to large streams highly uncertain. Hence, understanding of in-stream nitrate dynamic in large rivers is still necessary. High-frequency monitoring of nitrate mass balance between upstream and downstream measurement sites can quantitatively disentangle multi-path nitrate uptake dynamics at the reach scale (3-8 km). In this dissertation, we conducted this approach in large stream reaches with varying hydro-morphological and environmental conditions for several periods, confirming its success in disentangling nitrate uptake pathways and their temporal dynamics. Net nitrate uptake, autotrophic assimilation and heterotrophic uptake were disentangled, as well as their various diel and seasonal patterns. Natural streams generally can remove more nitrate under similar environmental conditions and heterotrophic uptake becomes dominant during post-wet seasons. Such two-station monitoring provided novel insights into reach-scale nitrate uptake processes in large streams.
Long-term in-stream nitrate dynamics can also be evaluated with the application of water quality model. This is among the first time to use a data-model fusion approach to upscale the two-station methodology in large-streams with complex flow dynamics under long-term high-frequency monitoring, assessing the in-stream nitrate retention and its responses to drought disturbances from seasonal to sub-daily scale. Nitrate retention (both net uptake and net release) exhibited substantial seasonality, which also differed in the investigated normal and drought years. In the normal years, winter and early spring seasons exhibited extensive net releases, then general net uptake occurred after the annual high-flow season at later spring and early summer with autotrophic processes dominating and during later summer-autumn low-flow periods with heterotrophy-characteristics predominating. Net nitrate release occurred since late autumn until the next early spring. In the drought years, the late-autumn net releases were not so consistently persisted as in the normal years and the predominance of autotrophic processes occurred across seasons. Aforementioned comprehensive results of nitrate dynamics on stream scale facilitate the understanding of instream processes, as well as raise the importance of scientific monitoring schemes for hydrology and water quality parameters.
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2017. Selected projects have presented their results on April 25th and November 15th 2017 at the Future SOC Lab Day events.
Completely water-based systems are of interest for the development of novel material for various reasons: On one hand, they provide benign environment for biological systems and on the other hand they facilitate effective molecular transport in a membrane-free environment. In order to investigate the general potential of aqueous two-phase systems (ATPSs) for biomaterials and compartmentalized systems, various solid particles were applied to stabilize all-aqueous emulsion droplets. The target ATPS to be investigated should be prepared via mixing of two aqueous solutions of water-soluble polymers, which turn biphasic when exceeding a critical polymer concentration. Hydrophilic polymers with a wide range of molar mass such as dextran/poly(ethylene glycol) (PEG) can therefore be applied. Solid particles adsorbed at the interfaces can be exceptionally efficient stabilizers forming so-called Pickering emulsions, and nanoparticles can bridge the correlation length of polymer solutions and are thereby the best option for water-in-water emulsions.
The first approach towards the investigation of ATPS was conducted with all aqueous dextran-PEG emulsions in the presence of poly(dopamine) particles (PDP) in Chapter 4. The water-in-water emulsions were formed with a PEG/dextran system via utilizing PDP as stabilizers. Studies of the formed emulsions were performed via laser scanning confocal microscope (CLSM), optical microscope (OM), cryo-scanning electron microscope (SEM) and tensiometry. The stable emulsions (at least 16 weeks) were demulsified easily via dilution or surfactant addition. Furthermore, the solid PDP at the water-water interface were crosslinked in order to inhibit demulsification of the Pickering emulsion. Transmission electron microscope (TEM) and scanning electron microscope (SEM) were used to visualize the morphology of PDP before and after crosslinking. PDP stabilized water-in-water emulsions were utilized in the following Chapter 5 to form supramolecular compartmentalized hydrogels. Here, hydrogels were prepared in pre-formed water-in-water emulsions and gelled via α-cyclodextrin-PEG (α-CD-PEG) inclusion complex formation. Studies of the formed complexes were performed via X-ray powder diffraction (XRD) and the mechanical properties of the hydrogels were measured with oscillatory shear rheology. In order to verify the compartmentalized state and its triggered decomposition, hydrogels and emulsions were assessed via OM, SEM and CLSM. The last chapter broadens the investigations from the previous two systems by utilizing various carbon nitrides (CN) as different stabilizers in ATPS. CN introduces another way to trigger demulsification, namely irradiation with visible light. Therefore, emulsification and demulsification with various triggers were probed. The investigated all aqueous multi-phase systems will act as model for future fabrication of biocompatible materials, cell micropatterning as well as separation of compartmentalized systems.
Synonymous codon usage and variations in the level of isoaccepting tRNAs exert a powerful selective force on translation fidelity. We have developed an algorithm to evaluate the relative rate of translation which allows large-scale comparisons of the non-uniform translation rate on the protein biogenesis. Using the complete genomes of Escherichia coli and Bacillus subtilis we show that stretches of codons pairing to minor tRNAs form putative sites to locally attenuate translation; thereby the tendency is to cluster in near proximity whereas long contiguous stretches of slow-translating triplets are avoided. The presence of slow-translating segments positively correlates with the protein length irrespective of the protein abundance. The slow-translating clusters are predominantly located down-stream of the domain boundaries presumably to fine-tune translational accuracy with the folding fidelity of multidomain proteins. Translation attenuation patterns at highly structurally and functionally conserved domains are preserved across the species suggesting a concerted selective pressure on the codon selection and species-specific tRNA abundance in these regions.
Microfabricated solid-state surfaces, also called atom chip', have become a well-established technique to trap and manipulate atoms. This has simplified applications in atom interferometry, quantum information processing, and studies of many-body systems. Magnetic trapping potentials with arbitrary geommetries are generated with atom chip by miniaturized current-carrying conductors integrated on a solid substrate. Atoms can be trapped and cooled to microKelvin and even nanoKelvin temperatures in such microchip trap. However, cold atoms can be significantly perturbed by the chip surface, typically held at room temperature. The magnetic field fluctuations generated by thermal currents in the chip elements may induce spin flips of atoms and result in loss, heating and decoherence. In this thesis, we extend previous work on spin flip rates induced by magnetic noise and consider the more complex geometries that are typically encountered in atom chips: layered structures and metallic wires of finite cross-section. We also discuss a few aspects of atom chips traps built with superconducting structures that have been suggested as a means to suppress magnetic field fluctuations. The thesis describes calculations of spin flip rates based on magnetic Green functions that are computed analytically and numerically. For a chip with a top metallic layer, the magnetic noise depends essentially on the thickness of that layer, as long as the layers below have a much smaller conductivity. Based on this result, scaling laws for loss rates above a thin metallic layer are derived. A good agreement with experiments is obtained in the regime where the atom-surface distance is comparable to the skin depth of metal. Since in the experiments, metallic layers are always etched to separate wires carrying different currents, the impact of the finite lateral wire size on the magnetic noise has been taken into account. The local spectrum of the magnetic field near a metallic microstructure has been investigated numerically with the help of boundary integral equations. The magnetic noise significantly depends on polarizations above flat wires with finite lateral width, in stark contrast to an infinitely wide wire. Correlations between multiple wires are also taken into account. In the last part, superconducting atom chips are considered. Magnetic traps generated by superconducting wires in the Meissner state and the mixed state are studied analytically by a conformal mapping method and also numerically. The properties of the traps created by superconducting wires are investigated and compared to normal conducting wires: they behave qualitatively quite similar and open a route to further trap miniaturization, due to the advantage of low magnetic noise. We discuss critical currents and fields for several geometries.
This thesis aimed to investigate several fundamental and perplexing questions relating to the phloem loading and transport mechanisms of Cucurbita maxima, by combining metabolomic analysis with cell biological techniques. This putative symplastic loading species has long been used for experiments on phloem anatomy, phloem biochemistry, phloem transport physiology and phloem signalling. Symplastic loading species have been proposed to use a polymer trapping mechanism to accumulate RFO (raffinose family oligosaccharides) sugars to build up high osmotic pressure in minor veins which sustains a concentration gradient that drives mass flow. However, extensive evidence indicating a low sugar concentration in their phloem exudates is a long-known problem that conflicts with this hypothesis. Previous metabolomic analysis shows the concentration of many small molecules in phloem exudates is higher than that of leaf tissues, which indicates an active apoplastic loading step. Therefore, in the view of the phloem metabolome, a symplastic loading mechanism cannot explain how small molecules other than RFO sugars are loaded into phloem. Most studies of phloem physiology using cucurbits have neglected the possible functions of vascular architecture in phloem transport. It is well known that there are two phloem systems in cucurbits with distinctly different anatomical features: central phloem and extrafascicular phloem. However, mistaken conclusions on sources of cucurbit phloem exudation from previous reports have hindered consideration of the idea that there may be important differences between these two phloem systems. The major results are summarized as below: 1) O-linked glycans in C.maxima were structurally identified as beta-1,3 linked glucose polymers, and the composition of glycans in cucurbits was found to be species-specific. Inter-species grafting experiments proved that these glycans are phloem mobile and transported uni-directionally from scion to stock. 2) As indicated by stable isotopic labelling experiments, a considerable amount of carbon is incorporated into small metabolites in phloem exudates. However, the incorporation of carbon into RFO sugars is much faster than for other metabolites. 3) Both CO2 labelling experiments and comparative metabolomic analysis of phloem exudates and leaf tissues indicated that metabolic processes other than RFO sugar metabolism play an important role in cucurbit phloem physiology. 4) The underlying assumption that the central phloem of cucurbits continuously releases exudates after physical incision was proved wrong by rigorous experiments including direct observation by normal microscopy and combined multiple-microscopic methods. Errors in previous experimental confirmation of phloem exudation in cucurbits are critically discussed. 5) Extrafascicular phloem was proved to be functional, as indicated by phloem-mobile carboxyfluorescein tracer studies. Commissural sieve tubes interconnect phloem bundles into a complete super-symplastic network. 6) Extrafascicular phloem represents the main source of exudates following physical incision. The major transported metabolites by these extrafacicular phloem are non-sugar compounds including amino acids, O-glycans, amines. 7) Central phloem contains almost exclusively RFO sugars, the estimated amount of which is up to 1 to 2 molar. The major RFO sugar present in central phloem is stachyose. 8) Cucurbits utilize two structurally different phloem systems for transporting different group of metabolites (RFO sugars and non-RFO sugar compounds). This implies that cucurbits may use spatially separated loading mechanisms (apoplastic loading for extrafascicular phloem and symplastic loading for central phloem) for supply of nutrients to sinks. 9) Along the transport systems, RFO sugars were mainly distributed within central phloem tissues. There were only small amounts of RFO sugars present in xylem tissues (millimolar range) and trace amounts of RFO sugars in cortex and pith. The composition of small molecules in external central phloem is very different from that in internal central phloem. 10) Aggregated P-proteins were manually dissected from central phloem and analysed by both SDS-PAGE and mass spectrometry. Partial sequences of peptides were obtained by QTOF de novo sequencing from trypsin digests of three SDS-PAGE bands. None of these partial sequences shows significant homology to known cucurbit phloem proteins or other plant proteins. This proves that these central phloem proteins are a completely new group of proteins different from those in extrafascicular phloem. The extensively analysed P-proteins reported in literature to date are therefore now shown to arise from extrafascicular phloem and not central phloem, and therefore do not appear to be involved in the occlusion processes in central phloem.
The purpose of this study was to compare the effects of combined resistance and plyometric/sprint training with plyometric/sprint training or typical soccer training alone on muscle strength and power, speed, change-of-direction ability in young soccer players. Thirty-one young (14.5 ± 0.52 years; tanner stage 3–4) soccer players were randomly assigned to either a combined- (COMB, n = 14), plyometric-training (PLYO, n = 9) or an active control group (CONT, n = 8). Two training sessions were added to the regular soccer training consisting of one session of light-load high-velocity resistance exercises combined with one session of plyometric/sprint training (COMB), two sessions of plyometric/sprint training (PLYO) or two soccer training sessions (CONT). Training volume was similar between the experimental groups. Before and after 7-weeks of training, peak torque, as well as absolute and relative (normalized to torque; RTDr) rate of torque development (RTD) during maximal voluntary isometric contraction of the knee extensors (KE) were monitored at time intervals from the onset of contraction to 200 ms. Jump height, sprinting speed at 5, 10, 20-m and change-of-direction ability performances were also assessed. There were no significant between–group baseline differences. Both COMB and PLYO significantly increased their jump height (Δ14.3%; ES = 0.94; Δ12.1%; ES = 0.54, respectively) and RTD at mid to late phases but with greater within effect sizes in COMB in comparison with PLYO. However, significant increases in peak torque (Δ16.9%; p < 0.001; ES = 0.58), RTD (Δ44.3%; ES = 0.71), RTDr (Δ27.3%; ES = 0.62) and sprint performance at 5-m (Δ-4.7%; p < 0.001; ES = 0.73) were found in COMB without any significant pre-to-post change in PLYO and CONT groups. Our results suggest that COMB is more effective than PLYO or CONT for enhancing strength, sprint and jump performances.
We combine ultrafast X-ray diffraction (UXRD) and time-resolved Magneto-Optical Kerr Effect (MOKE) measurements to monitor the strain pulses in laser-excited TbFe2/Nb heterostructures. Spatial separation of the Nb detection layer from the laser excitation region allows for a background-free characterization of the laser-generated strain pulses. We clearly observe symmetric bipolar strain pulses if the excited TbFe2 surface terminates the sample and a decomposition of the strain wavepacket into an asymmetric bipolar and a unipolar pulse, if a SiO2 glass capping layer covers the excited TbFe2 layer. The inverse magnetostriction of the temporally separated unipolar strain pulses in this sample leads to a MOKE signal that linearly depends on the strain pulse amplitude measured through UXRD. Linear chain model simulations accurately predict the timing and shape of UXRD and MOKE signals that are caused by the strain reflections from multiple interfaces in the heterostructure.
Reciprocal space slicing
(2021)
An experimental technique that allows faster assessment of out-of-plane strain dynamics of thin film heterostructures via x-ray diffraction is presented. In contrast to conventional high-speed reciprocal space-mapping setups, our approach reduces the measurement time drastically due to a fixed measurement geometry with a position-sensitive detector. This means that neither the incident (ω) nor the exit (2θ) diffraction angle is scanned during the strain assessment via x-ray diffraction. Shifts of diffraction peaks on the fixed x-ray area detector originate from an out-of-plane strain within the sample. Quantitative strain assessment requires the determination of a factor relating the observed shift to the change in the reciprocal lattice vector. The factor depends only on the widths of the peak along certain directions in reciprocal space, the diffraction angle of the studied reflection, and the resolution of the instrumental setup. We provide a full theoretical explanation and exemplify the concept with picosecond strain dynamics of a thin layer of NbO2.
In the present thesis I investigate the lattice dynamics of thin film hetero structures of magnetically ordered materials upon femtosecond laser excitation as a probing and manipulation scheme for the spin system. The quantitative assessment of laser induced thermal dynamics as well as generated picosecond acoustic pulses and their respective impact on the magnetization dynamics of thin films is a challenging endeavor. All the more, the development and implementation of effective experimental tools and comprehensive models are paramount to propel future academic and technological progress.
In all experiments in the scope of this cumulative dissertation, I examine the crystal lattice of nanoscale thin films upon the excitation with femtosecond laser pulses. The relative change of the lattice constant due to thermal expansion or picosecond strain pulses is directly monitored by an ultrafast X-ray diffraction (UXRD) setup with a femtosecond laser-driven plasma X-ray source (PXS). Phonons and spins alike exert stress on the lattice, which responds according to the elastic properties of the material, rendering the lattice a versatile sensor for all sorts of ultrafast interactions. On the one hand, I investigate materials with strong magneto-elastic properties; The highly magnetostrictive rare-earth compound TbFe2, elemental Dysprosium or the technological relevant Invar material FePt. On the other hand I conduct a comprehensive study on the lattice dynamics of Bi1Y2Fe5O12 (Bi:YIG), which exhibits high-frequency coherent spin dynamics upon femtosecond laser excitation according to the literature. Higher order standing spinwaves (SSWs) are triggered by coherent and incoherent motion of atoms, in other words phonons, which I quantified with UXRD. We are able to unite the experimental observations of the lattice and magnetization dynamics qualitatively and quantitatively. This is done with a combination of multi-temperature, elastic, magneto-elastic, anisotropy and micro-magnetic modeling.
The collective data from UXRD, to probe the lattice, and time-resolved magneto-optical Kerr effect (tr-MOKE) measurements, to monitor the magnetization, were previously collected at different experimental setups. To improve the precision of the quantitative assessment of lattice and magnetization dynamics alike, our group implemented a combination of UXRD and tr-MOKE in a singular experimental setup, which is to my knowledge, the first of its kind. I helped with the conception and commissioning of this novel experimental station, which allows the simultaneous observation of lattice and magnetization dynamics on an ultrafast timescale under identical excitation conditions. Furthermore, I developed a new X-ray diffraction measurement routine which significantly reduces the measurement time of UXRD experiments by up to an order of magnitude. It is called reciprocal space slicing (RSS) and utilizes an area detector to monitor the angular motion of X-ray diffraction peaks, which is associated with lattice constant changes, without a time-consuming scan of the diffraction angles with the goniometer. RSS is particularly useful for ultrafast diffraction experiments, since measurement time at large scale facilities like synchrotrons and free electron lasers is a scarce and expensive resource. However, RSS is not limited to ultrafast experiments and can even be extended to other diffraction techniques with neutrons or electrons.
The aim of these lectures is a reformulation and generalization of the fundamental investigations of Alexander Bach [2, 3] on the concept of probability in the work of Boltzmann [6] in the language of modern point process theory. The dominating point of view here is its subordination under the disintegration theory of Krickeberg [14]. This enables us to make Bach's consideration much more transparent. Moreover the point process formulation turns out to be the natural framework for the applications to quantum mechanical models.
StudyMe
(2022)
N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals. Although several tools for N-of-1 trials exist, there is a gap in supporting non-experts in conducting their own user-centric trials. In this study, we present StudyMe, an open-source mobile application that is freely available from https://play.google.com/store/apps/details?id=health.studyu.me and offers users flexibility and guidance in configuring every component of their trials. We also present research that informed the development of StudyMe, focusing on trial creation. Through an initial survey with 272 participants, we learned that individuals are interested in a variety of personal health aspects and have unique ideas on how to improve them. In an iterative, user-centered development process with intermediate user tests, we developed StudyMe that features an educational part to communicate N-of-1 trial concepts. A final empirical evaluation of StudyMe showed that all participants were able to create their own trials successfully using StudyMe and the app achieved a very good usability rating. Our findings suggest that StudyMe provides a significant step towards enabling individuals to apply a systematic science-oriented approach to personalize health-related interventions and behavior modifications in their everyday lives.
The aim of this thesis is the quantum dynamical study of two examples of scanning tunneling microscope (STM)-controllable, Si(100)(2x1) surface-mounted switches of atomic and molecular scale. The first example considers the switching of single H-atoms between two dangling-bond chemisorption sites on a Si-dimer of the Si(100) surface (Grey et al., 1996). The second system examines the conformational switching of single 1,5-cyclooctadiene molecules chemisorbed on the Si(100) surface (Nacci et al., 2008). The temporal dynamics are provided by the propagation of the density matrix in time via an according set of equations of motion (EQM). The latter are based on the open-system density matrix theory in Lindblad form. First order perturbation theory is used to evaluate those transition rates between vibrational levels of the system part. In order to account for interactions with the surface phonons, two different dissipative models are used, namely the bilinear, harmonic and the Ohmic bath model. IET-induced vibrational transitions in the system are due to the dipole- and the resonance-mechanism. A single surface approach is used to study the influence of dipole scattering and resonance scattering in the below-threshold regime. Further, a second electronic surface was included to study the resonance-induced switching in the above-threshold regime. Static properties of the adsorbate, e.g., potentials and dipole function and potentials, are obtained from quantum chemistry and used within the established quantum dynamical models.
The article provides historical background for Alexander von Humboldt’s expedition into Russia in 1829. It includes information on Humboldt’s works and publications in Russia over the course of his lifetime, as well as an explanation of the Russian scientific community’s response to those works. Humboldt’s ideas on the existence of an active volcano in Central Asia attracted the attention of two prominent Russian geographers, P. Semenov and P. Kropotkin, whose views on the nature of volcanism were quite different. P. Semenov personally met Humboldt in Berlin. P. Kropotkin made one of the most important geological discoveries of the 19th Century: he found the fresh volcanic cones near Lake Baikal.
Soon after Humboldt’s Russian expedition, and partly as a result of it, an important mineral was found in the Ilmen mountains – samarskite, which later gave its name to the chemical element Samarium, developed in 1879. At the beginning of the 20th Century, the Russian scientist V. Vernadskiy pointed out that samarskite was the first uranium-rich mineral found in Russia.
Cell-free protein synthesis as a novel tool for directed glycoengineering of active erythropoietin
(2018)
As one of the most complex post-translational modification, glycosylation is widely involved in cell adhesion, cell proliferation and immune response. Nevertheless glycoproteins with an identical polypeptide backbone mostly differ in their glycosylation patterns. Due to this heterogeneity, the mapping of different glycosylation patterns to their associated function is nearly impossible. In the last years, glycoengineering tools including cell line engineering, chemoenzymatic remodeling and site-specific glycosylation have attracted increasing interest. The therapeutic hormone erythropoietin (EPO) has been investigated in particular by various groups to establish a production process resulting in a defined glycosylation pattern. However commercially available recombinant human EPO shows batch-to-batch variations in its glycoforms. Therefore we present an alternative method for the synthesis of active glycosylated EPO with an engineered O-glycosylation site by combining eukaryotic cell-free protein synthesis and site-directed incorporation of non-canonical amino acids with subsequent chemoselective modifications.
The mammalian brain is, with its numerous neural elements and structured complex connectivity, one of the most complex systems in nature. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex networks. Here, we try to shed some light on the relationship between structural and functional connectivities by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the cortical areas by a subnetwork of interacting excitable neurons (multilevel model) and by a neural mass model (population model). With weak couplings, the multilevel model displays biologically plausible dynamics and the synchronization patterns reveal a hierarchical cluster organization in the network structure. We can identify a group of brain areas involved in multifunctional tasks by comparing the dynamical clusters to the topological communities of the network. With strong couplings of multilevel model and by using neural mass model, the dynamics are characterized by well-defined oscillations. The synchronization patterns are mainly determined by the node intensity (total input strengths of a node); the detailed network topology is of secondary importance. The biologically improved multilevel model exhibits similar dynamical patterns in the two regimes. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks.
The Greenland Ice Sheet is the second-largest mass of ice on Earth. Being almost 2000 km long, more than 700 km wide, and more than 3 km thick at the summit, it holds enough ice to raise global sea levels by 7m if melted completely. Despite its massive size, it is particularly vulnerable to anthropogenic climate change: temperatures over the Greenland Ice Sheet have increased by more than 2.7◦C in the past 30 years, twice as much as the global mean temperature. Consequently, the ice sheet has been significantly losing mass since the 1980s and the rate of loss has increased sixfold since then. Moreover, it is one of the potential tipping elements of the Earth System, which might undergo irreversible change once a warming threshold is exceeded. This thesis aims at extending the understanding of the resilience of the Greenland Ice Sheet against global warming by analyzing processes and feedbacks relevant to its centennial to multi-millennial stability using ice sheet modeling.
One of these feedbacks, the melt-elevation-feedback is driven by the temperature rise with decreasing altitudes: As the ice sheet melts, its thickness and surface elevation decrease, exposing the ice surface to warmer air and thus increasing the melt rates even further. The glacial isostatic adjustment (GIA) can partly mitigate this melt-elevation feedback as the bedrock lifts in response to an ice load decrease, forming the negative GIA feedback. In my thesis, I show that the interaction between these two competing feedbacks can lead to qualitatively different dynamical responses of the Greenland Ice Sheet to warming – from permanent loss to incomplete recovery, depending on the feedback parameters. My research shows that the interaction of those feedbacks can initiate self-sustained oscillations of the ice volume while the climate forcing remains constant.
Furthermore, the increased surface melt changes the optical properties of the snow or ice surface, e.g. by lowering their albedo, which in turn enhances melt rates – a process known as the melt-albedo feedback. Process-based ice sheet models often neglect this melt-albedo feedback. To close this gap, I implemented a simplified version of the diurnal Energy Balance Model, a computationally efficient approach that can capture the first-order effects of the melt-albedo feedback, into the Parallel Ice Sheet Model (PISM). Using the coupled model, I show in warming experiments that the melt-albedo feedback almost doubles the ice loss until the year 2300 under the low greenhouse gas emission scenario RCP2.6, compared to simulations where the melt-albedo feedback is neglected,
and adds up to 58% additional ice loss under the high emission scenario RCP8.5. Moreover, I find that the melt-albedo feedback dominates the ice loss until 2300, compared to the melt-elevation feedback.
Another process that could influence the resilience of the Greenland Ice Sheet is the warming induced softening of the ice and the resulting increase in flow. In my thesis, I show with PISM how the uncertainty in Glen’s flow law impacts the simulated response to warming. In a flow line setup at fixed climatic mass balance, the uncertainty in flow parameters leads to a range of ice loss comparable to the range caused by different warming levels.
While I focus on fundamental processes, feedbacks, and their interactions in the first three projects of my thesis, I also explore the impact of specific climate scenarios on the sea level rise contribution of the Greenland Ice Sheet. To increase the carbon budget flexibility, some warming scenarios – while still staying within the limits of the Paris Agreement – include a temporal overshoot of global warming. I show that an overshoot by 0.4◦C increases the short-term and long-term ice loss from Greenland by several centimeters. The long-term increase is driven by the warming at high latitudes, which persists even when global warming is reversed. This leads to a substantial long-term commitment of the sea level rise contribution from the Greenland Ice Sheet.
Overall, in my thesis I show that the melt-albedo feedback is most relevant for the ice loss of the Greenland Ice Sheet on centennial timescales. In contrast, the melt-elevation feedback and its interplay with the GIA feedback become increasingly relevant on millennial timescales. All of these influence the resilience of the Greenland Ice Sheet against global warming, in the near future and on the long term.
Integration of digital elevation models and satellite images to investigate geological processes.
(2006)
In order to better understand the geological boundary conditions for ongoing or past surface processes geologists face two important questions: 1) How can we gain additional knowledge about geological processes by analyzing digital elevation models (DEM) and satellite images and 2) Do these efforts present a viable approach for more efficient research. Here, we will present case studies at a variety of scales and levels of resolution to illustrate how we can substantially complement and enhance classical geological approaches with remote sensing techniques. Commonly, satellite and DEM based studies are being used in a first step of assessing areas of geologic interest. While in the past the analysis of satellite imagery (e.g. Landsat TM) and aerial photographs was carried out to characterize the regional geologic characteristics, particularly structure and lithology, geologists have increasingly ventured into a process-oriented approach. This entails assessing structures and geomorphic features with a concept that includes active tectonics or tectonic activity on time scales relevant to humans. In addition, these efforts involve analyzing and quantifying the processes acting at the surface by integrating different remote sensing and topographic data (e.g. SRTM-DEM, SSM/I, GPS, Landsat 7 ETM, Aster, Ikonos…). A combined structural and geomorphic study in the hyperarid Atacama desert demonstrates the use of satellite and digital elevation data for assessing geological structures formed by long-term (millions of years) feedback mechanisms between erosion and crustal bending (Zeilinger et al., 2005). The medium-term change of landscapes during hundred thousands to millions years in a more humid setting is shown in an example from southern Chile. Based on an analysis of rivers/watersheds combined with landscapes parameterization by using digital elevation models, the geomorphic evolution and change in drainage pattern in the coastal Cordillera can be quantified and put into the context of seismotectonic segmentation of a tectonically active region. This has far-reaching implications for earthquake rupture scenarios and hazard mitigation (K. Rehak, see poster on IMAF Workshop). Two examples illustrate short-term processes on decadal, centennial and millennial time scales: One study uses orogen scale precipitation gradients derived from remotely sensed passive microwave data (Bookhagen et al., 2005a). They demonstrate how debris flows were triggered as a response of slopes to abnormally strong rainfall in the interior parts of the Himalaya during intensified monsoons. The area of the orogen that receives high amounts of precipitation during intensified monsoons also constitutes numerous landslide deposits of up to 1km<sup>3 volume that were generated during intensified monsoon phase at about 27 and 9 ka (Bookhagen et al., 2005b). Another project in the Swiss Alps compared sets of aerial photographs recorded in different years. By calculating high resolution surfaces the mass transport in a landslide could be reconstructed (M. Schwab, Universität Bern). All these examples, although representing only a short and limited selection of projects using remote sense data in geology, have as a common approach the goal to quantify geological processes. With increasing data resolution and new sensors future projects will even enable us to recognize more patterns and / or structures indicative of geological processes in tectonically active areas. This is crucial for the analysis of natural hazards like earthquakes, tsunamis and landslides, as well as those hazards that are related to climatic variability. The integration of remotely sensed data at different spatial and temporal scales with field observations becomes increasingly important. Many of presently highly populated places and increasingly utilized regions are subject to significant environmental pressure and often constitute areas of concentrated economic value. Combined remote sensing and ground-truthing in these regions is particularly important as geologic, seismicity and hydrologic data may be limited here due to the recency of infrastructural development. Monitoring ongoing processes and evaluating the remotely sensed data in terms of recurrence of events will greatly enhance our ability to assess and mitigate natural hazards. <hr> Dokument 1: Foliensatz | Dokument 2: Abstract <hr> Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006
In this paper I argue that both parametric variation and the alleged differences between languages in terms of their internal complexity straightforwardly follow from the Strongest Minimalist Thesis that takes the Faculty of Language (FL) to be an optimal solution to conditions that neighboring mental modules impose on it. In this paper I argue that hard conditions like legibility at the linguistic interfaces invoke simplicity metrices that, given that they stem from different mental modules, are not harmonious. I argue that widely attested expression strategies, such as agreement or movement, are a direct result of conflicting simplicity metrices, and that UG, perceived as a toolbox that shapes natural language, can be taken to consist of a limited number of markings strategies, all resulting from conflicting simplicity metrices. As such, the contents of UG follow from simplicity requirements, and therefore no longer necessitate linguistic principles, valued or unvalued, to be innately present. Finally, I show that the SMT does not require that languages themselves have to be optimal in connecting sound to meaning.
Ionogels (IGs) based on poly(methyl methacrylate) (PMMA) and the metal-containing ionic liquids (ILs) bis-1-butyl-3-methlimidazolium tetrachloridocuprate(II), tetrachloride cobaltate(II), and tetrachlorido manganate(II) have been synthesized and their mechanical and electrical properties have been correlated with their microstructure. Unlike many previous examples, the current IGs show a decreasing stability in stress-strain experiments on increasing IL fractions. The conductivities of the current IGs are lower than those observed in similar examples in the literature. Both effects are caused by a two-phase structure with micrometer-sized IL-rich domains homogeneously dispersed an IL-deficient continuous PMMA phase. This study demonstrates that the IL-polymer miscibility and the morphology of the IGs are key parameters to control the (macroscopic) properties of IGs.
Millennial-scale palaeoclimate variability has been documented in various terrestrial and marine palaeoclimate proxy records throughout the Northern Hemisphere for the last glacial cycle. Its clear expression and rapid shifts between different states of climate (Greenland Interstadials and Stadials) represents a correlation tool beyond the resolution of e.g. luminescence dating, especially relevant for terrestrial deposits. Usually, comparison of terrestrial proxy datasets and the Greenland ice cores indicates a complex expression of millennial-scale climate variability as recorded in terrestrial geoarchives including loess. Loess is the most widespread terrestrial geoarchive of the Quaternary and especially widespread over Eurasia. However, loess often records a smoothed representation of millennial-scale variability without all fidelity when compared to the Greenland data, this being a relevant limiting feature in integrating loess with other palaeoclimate records. To better understand the loess proxy-response to millennial-scale climate variability, we simulate a proxy signal smoothing by natural processes through application of low-pass filters of delta O-18 data from Greenland, a high-resolution palaeoclimate reference record, alongside speleothem isotope records from the Black Sea-Mediterranean region. We show that low-pass filters represent rather simple models for better constraining the expression of millennial-scale climate variability in low sedimentation environments, and in sediments where proxy-response signals are most likely affected by natural smoothing (by e.g. bioturbation). Interestingly, smoothed datasets from Greenland and the Black Sea-Mediterranean region are most similar in the last similar to 15 ka and between similar to 50-30 ka. Between similar to 30-15 ka, roughly corresponding to the Last Glacial Maximum and the deglaciation, the records show dissimilarities, challenging the construction of robust correlative time-scales in this age range. From our analysis it becomes apparent that patterns of palaeoclimate signals in loess-palaeosol sequences often might be better explained by smoothed Greenland reference data than the original high-resolution Greenland dataset, or other reference data. This opens the possibility to better assess the temporal resolution and palaeoclimate potential of loess-palaeosol sequences in recording supra-regional climate patterns, as well as to securely integrate loess with other chronologically better-resolved palaeoclimate records.
Seismological and seismotectonic analysis of the northwestern Argentine Central Andean foreland
(2020)
After a severe M W 5.7 earthquake on October 17, 2015 in El Galpón in the province of Salta NW Argentina, I installed a local seismological network around the estimated epicenter. The network covered an area characterized by inherited Cretaceous normal faults and neotectonic faults with unknown recurrence intervals, some of which may have been reactivated normal faults. The 13 three-component seismic stations recorded data continuously for 15 months.
The 2015 earthquake took place in the Santa Bárbara System of the Andean foreland, at about 17km depth. This region is the easternmost morphostructural region of the central Andes. As a part of the broken foreland, it is bounded to the north by the Subandes fold-and-thrust belt and the Sierras Pampeanas to the south; to the east lies the Chaco-Paraná basin.
A multi-stage morphotectonic evolution with thick-skinned basement uplift and coeval thin-skinned deformation in the intermontane basins is suggested for the study area. The release of stresses associated with the foreland deformation can result in strong earthquakes, as the study area is known for recurrent and historical, destructive earthquakes. The available continuous record reaches back in time, when the strongest event in 1692 (magnitude 7 or intensity IX) destroyed the city of Esteco. Destructive earthquakes and surface deformation are thus a hallmark of this part of the Andean foreland.
With state-of-the-art Python packages (e.g. pyrocko, ObsPy), a semi-automatic approach is followed to analyze the collected continuous data of the seismological network. The resulting 1435 hypocenter locations consist of three different groups: 1.) local crustal earthquakes (nearly half of the events belong to this group), 2.) interplate activity, of regional distance in the slab of the Nazca-plate, and 3.) very deep earthquakes at about 600km depth. My major interest focused on the first event class. Those crustal events are partly aftershock events of the El Galpón earthquake and a second earthquake, in the south of the same fault. Further events can be considered as background seismicity of other faults within the study area. Strikingly, the seismogenic zone encompass the whole crust and propagates brittle deformation down, close to the Moho.
From the collected seismological data, a local seismic velocity model is estimated, using VELEST. After the execution of various stability tests, the robust minimum 1D-velocity model implies guiding values for the composition of the local, subsurface structure of the crust. Afterwards, performing a hypocenter relocation enables the assignment of individual earthquakes to aftershock clusters or extended seismotectonic structures. This allows the mapping of previously unknown seismogenic faults.
Finally, focal mechanisms are modeled for events with acurately located hypocenters, using the newly derived local velocity model. A compressive regime is attested by the majority of focal mechanisms, while the strike direction of the individual seismogenic structures is in agreement with the overall north – south orientation of the Central Andes, its mountain front, and individual mountain ranges in the southern Santa-Bárbara-System.