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This dissertation examines the integration of incongruent visual-scene and morphological-case information (“cues”) in building thematic-role representations of spoken relative clauses in German.
Addressing the mutual influence of visual and linguistic processing, the Coordinated Interplay Account (CIA) describes a mechanism in two steps supporting visuo-linguistic integration (Knoeferle & Crocker, 2006, Cog Sci). However, the outcomes and dynamics of integrating incongruent thematic-role representations from distinct sources have been investigated scarcely. Further, there is evidence that both second-language (L2) and older speakers may rely on non-syntactic cues relatively more than first-language (L1)/young speakers. Yet, the role of visual information for thematic-role comprehension has not been measured in L2 speakers, and only limitedly across the adult lifespan.
Thematically unambiguous canonically ordered (subject-extracted) and noncanonically ordered (object-extracted) spoken relative clauses in German (see 1a-b) were presented in isolation and alongside visual scenes conveying either the same (congruent) or the opposite (incongruent) thematic relations as the sentence did.
1 a Das ist der Koch, der die Braut verfolgt.
This is the.NOM cook who.NOM the.ACC bride follows
This is the cook who is following the bride.
b Das ist der Koch, den die Braut verfolgt.
This is the.NOM cook whom.ACC the.NOM bride follows
This is the cook whom the bride is following.
The relative contribution of each cue to thematic-role representations was assessed with agent identification. Accuracy and latency data were collected post-sentence from a sample of L1 and L2 speakers (Zona & Felser, 2023), and from a sample of L1 speakers from across the adult lifespan (Zona & Reifegerste, under review). In addition, the moment-by-moment dynamics of thematic-role assignment were investigated with mouse tracking in a young L1 sample (Zona, under review).
The following questions were addressed: (1) How do visual scenes influence thematic-role representations of canonical and noncanonical sentences? (2) How does reliance on visual-scene, case, and word-order cues vary in L1 and L2 speakers? (3) How does reliance on visual-scene, case, and word-order cues change across the lifespan?
The results showed reliable effects of incongruence of visually and linguistically conveyed thematic relations on thematic-role representations. Incongruent (vs. congruent) scenes yielded slower and less accurate responses to agent-identification probes presented post-sentence. The recently inspected agent was considered as the most likely agent ~300ms after trial onset, and the convergence of visual scenes and word order enabled comprehenders to assign thematic roles predictively.
L2 (vs. L1) participants relied more on word order overall. In response to noncanonical clauses presented with incongruent visual scenes, sensitivity to case predicted the size of incongruence effects better than L1-L2 grouping. These results suggest that the individual’s ability to exploit specific cues might predict their weighting.
Sensitivity to case was stable throughout the lifespan, while visual effects increased with increasing age and were modulated by individual interference-inhibition levels. Thus, age-related changes in comprehension may stem from stronger reliance on visually (vs. linguistically) conveyed meaning.
These patterns represent evidence for a recent-role preference – i.e., a tendency to re-assign visually conveyed thematic roles to the same referents in temporally coordinated utterances. The findings (i) extend the generalizability of CIA predictions across stimuli, tasks, populations, and measures of interest, (ii) contribute to specifying the outcomes and mechanisms of detecting and indexing incongruent representations within the CIA, and (iii) speak to current efforts to understand the sources of variability in sentence comprehension.
This research addressed the question, if it is possible to simplify current microcontact printing systems for the production of anisotropic building blocks or patchy particles, by using common chemicals while still maintaining reproducibility, high precision and tunability of the Janus-balance
Chapter 2 introduced the microcontact printing materials as well as their defined electrostatic interactions. In particular polydimethylsiloxane stamps, silica particles and high molecular weight polyethylenimine ink were mainly used in this research. All of these components are commercially available in large quantities and affordable, which gives this approach a huge potential for further up-scaling developments. The benefits of polymeric over molecular inks was described including its flexible influence on the printing pressure. With this alteration of the µCP concept, a new method of solvent assisted particle release mechanism enabled the switch from two-dimensional surface modification to three-dimensional structure printing on colloidal silica particles, without changing printing parameters or starting materials. This effect opened the way to use the internal volume of the achieved patches for incorporation of nano additives, introducing additional physical properties into the patches without alteration of the surface chemistry.
The success of this system and its achievable range was further investigated in chapter 3 by giving detailed information about patch geometry parameters including diameter, thickness and yield. For this purpose, silica particles in a size range between 1µm and 5µm were printed with different ink concentrations to change the Janus-balance of these single patched particles. A necessary intermediate step, consisting of air-plasma treatment, for the production of trivalent particles using "sandwich" printing was discovered and comparative studies concerning the patch geometry of single and double patched particles were conducted. Additionally, the usage of structured PDMS stamps during printing was described. These results demonstrate the excellent precision of this approach and opens the pathway for even greater accuracy as further parameters can be finely tuned and investigated, e.g. humidity and temperature during stamp loading.
The performance of these synthesized anisotropic colloids was further investigated in chapter 4, starting with behaviour studies in alcoholic and aqueous dispersions. Here, the stability of the applied patches was studied in a broad pH range, discovering a release mechanism by disabling the electrostatic bonding between particle surface and polyelectrolyte ink. Furthermore, the absence of strong attractive forces between divalent particles in water was investigated using XPS measurements. These results lead to the conclusion that the transfer of small PDMS oligomers onto the patch surface is shielding charges, preventing colloidal agglomeration. However, based on this knowledge, further patch modifications for particle self-assembly were introduced including physical approaches using magnetic nano additives, chemical patch functionalization with avidin-biotin or the light responsive cyclodextrin-arylazopyrazoles coupling as well as particle surface modification for the synthesis of highly amphiphilic colloids. The successful coupling, its efficiency, stability and behaviour in different solvents were evaluated to find a suitable coupling system for future assembly experiments. Based on these results the possibility of more sophisticated structures by colloidal self-assembly is given.
Certain findings needed further analysis to understand their underlying mechanics, including the relatively broad patch diameter distribution and the decreasing patch thickness for smaller silica particles. Mathematical assumptions for both effects are introduced in chapter 5. First, they demonstrate the connection between the naturally occurring particle size distribution and the broadening of the patch diameter, indicating an even higher precision for this µCP approach. Second, explaining the increase of contact area between particle and ink surface due to higher particle packaging, leading to a decrease in printing pressure for smaller particles.
These calculations ultimately lead to the development of a new mechanical microcontact printing approach, using centrifugal forces for high pressure control and excellent parallel alignment of printing substrates. First results with this device and the comparison with previously conducted by-hand experiments conclude this research. It furthermore displays the advantages of such a device for future applications using a mechanical printing approach, especially for accessing even smaller nano particles with great precision and excellent yield.
In conclusion, this work demonstrates the successful adjustment of the µCP approach using commercially available and affordable silica particles and polyelectrolytes for high flexibility, reduced costs and higher scale-up value. Furthermore, its was possible to increase the modification potential by introducing three-dimensional patches for additional functionalization volume. While keeping a high colloidal stability, different coupling systems showed the self-assembly capabilities of this toolbox for anisotropic particles.
As land-cover conversion continues to expand into ever more remote areas in the humid tropics, montane rainforests are increasingly threatened. In the south Ecuadorian Andes, they are not only subject to man-made disturbances but also to naturally occurring landslides. I was interested in the impact of this ecosystem dynamics on a key parameter of the hydrologic cycle, the soil saturated hydraulic conductivity (synonym: permeability; Ks from here on), because it is a sensitive indicator for soil disturbances. My general objective was to quantify the effects of the regional natural and human disturbances on the saturated hydraulic conductivity and to describe the resulting spatial-temporal patterns. The main hypotheses were: 1) disturbances cause an apparent displacement of the less permeable soil layer towards the surface, either due to a loss of the permeable surface soil after land-sliding, or as a consequence of the surface soil compaction under cattle pastures; 2) ‘recovery’ from disturbance, either because of landslide re-vegetation or because of secondary succession after pasture abandonment, involves an apparent displacement of the less permeable layer back towards the original depth an 3) disturbances cause a simplification of the Ks spatial structure, i.e. the spatially dependent random variation diminishes; the subsequent recovery entails the re-establishment of the original structure. In my first study, I developed a synthesis of recent geostatistical research regarding its applicability to soil hydraulic data, including exploratory data analysis and variogram estimation techniques; I subsequently evaluated the results in terms of spatial prediction uncertainty. Concerning the exploratory data analysis, my main results were: 1) Gaussian uni- and bivariate distributions of the log-transformed data; 2) the existence of significant local trends; 3) no need for robust estimation; 4) no anisotropic variation. I found partly considerable differences in covariance parameters resulting from different variogram estimation techniques, which, in the framework of spatial prediction, were mainly reflected in the spatial connectivity of the Ks-field. Ignoring the trend component and an arbitrary use of robust estimators, however, would have the most severe consequences in this respect. Regarding variogram modeling, I encouraged restricted maximum likelihood estimation because of its accuracy and independence on the selected lags needed for experimental variograms. The second study dealt with the Ks spatial-temporal pattern in the sequences of natural and man-made disturbances characteristic for the montane rainforest study area. To investigate the disturbance effects both on global means and the spatial structure of Ks, a combined design-and model-based sampling approach was used for field-measurements at soil depths of 12.5, 20, and 50 cm (n=30-150/depth) under landslides of different ages (2 and 8 years), under actively grazed pasture, fallows following pasture abandonment (2 to 25 years of age), and under natural forest. Concerning global means, our main findings were 1) global means of the soil permeability generally decrease with increasing soil depth; 2) no significant Ks differences can be observed among landslides and compared to the natural forest; 3) a distinct permeability decrease of two orders of magnitude occurs after forest conversion to pasture at shallow soil depths, and 4) the slow regeneration process after pasture abandonment requires at least one decade. Regarding the Ks spatial structure, we found that 1) disturbances affect the Ks spatial structure in the topsoil, and 2) the largest differences in spatial patterns are associated with the subsoil permeability. In summary, the regional landslide activity seems to affect soil hydrology to a marginal extend only, which is in contrast to the pronounced drop of Ks after forest conversion. We used this spatial-temporal information combined with local rain intensities to assess the partitioning of rainfall into vertical and lateral flowpaths under undisturbed, disturbed, and regenerating land-cover types in the third study. It turned out that 1) the montane rainforest is characterized by prevailing vertical flowpaths in the topsoil, which can switch to lateral directions below 20 cm depth for a small number of rain events, which may, however, transport a high portion of the annual runoff; 2) similar hydrological flowpaths occur under the landslides except for a somewhat higher probability of impermeable layer formation in the topsoil of a young landslide, and 3) pronounced differences in runoff components can be observed for the human disturbance sequence involving the development of near-surface impeding layers for 24, 44, and 8 % of rain events for pasture, a two-year-old fallow, and a ten-year-old fallow, respectively.
Motivations and research objectives: During the passage of rain water through a forest canopy two main processes take place. First, water is redistributed; and second, its chemical properties change substantially. The rain water redistribution and the brief contact with plant surfaces results in a large variability of both throughfall and its chemical composition. Since throughfall and its chemistry influence a range of physical, chemical and biological processes at or below the forest floor the understanding of throughfall variability and the prediction of throughfall patterns potentially improves the understanding of near-surface processes in forest ecosystems. This thesis comprises three main research objectives. The first objective is to determine the variability of throughfall and its chemistry, and to investigate some of the controlling factors. Second, I explored throughfall spatial patterns. Finally, I attempted to assess the temporal persistence of throughfall and its chemical composition. Research sites and methods: The thesis is based on investigations in a tropical montane rain forest in Ecuador, and lowland rain forest ecosystems in Brazil and Panama. The first two studies investigate both throughfall and throughfall chemistry following a deterministic approach. The third study investigates throughfall patterns with geostatistical methods, and hence, relies on a stochastic approach. Results and Conclusions: Throughfall is highly variable. The variability of throughfall in tropical forests seems to exceed that of many temperate forests. These differences, however, do not solely reflect ecosystem-inherent characteristics, more likely they also mirror management practices. Apart from biotic factors that influence throughfall variability, rainfall magnitude is an important control. Throughfall solute concentrations and solute deposition are even more variable than throughfall. In contrast to throughfall volumes, the variability of solute deposition shows no clear differences between tropical and temperate forests, hence, biodiversity is not a strong predictor of solute deposition heterogeneity. Many other factors control solute deposition patterns, for instance, solute concentration in rainfall and antecedent dry period. The temporal variability of the latter factors partly accounts for the low temporal persistence of solute deposition. In contrast, measurements of throughfall volume are quite stable over time. Results from the Panamanian research site indicate that wet and dry areas outlast consecutive wet seasons. At this research site, throughfall exhibited only weak or pure nugget autocorrelation structures over the studies lag distances. A close look at the geostatistical tools at hand provided evidence that throughfall datasets, in particular those of large events, require robust variogram estimation if one wants to avoid outlier removal. This finding is important because all geostatistical throughfall studies that have been published so far analyzed their data using the classical, non-robust variogram estimator.
This work incorporates three treatises which are commonly concerned with a stochastic theory of the Lyapunov exponents. With the help of this theory universal scaling laws are investigated which appear in coupled chaotic and disordered systems. First, two continuous-time stochastic models for weakly coupled chaotic systems are introduced to study the scaling of the Lyapunov exponents with the coupling strength (coupling sensitivity of chaos). By means of the the Fokker-Planck formalism scaling relations are derived, which are confirmed by results of numerical simulations. Next, coupling sensitivity is shown to exist for coupled disordered chains, where it appears as a singular increase of the localization length. Numerical findings for coupled Anderson models are confirmed by analytic results for coupled continuous-space Schrödinger equations. The resulting scaling relation of the localization length resembles the scaling of the Lyapunov exponent of coupled chaotic systems. Finally, the statistics of the exponential growth rate of the linear oscillator with parametric noise are studied. It is shown that the distribution of the finite-time Lyapunov exponent deviates from a Gaussian one. By means of the generalized Lyapunov exponents the parameter range is determined where the non-Gaussian part of the distribution is significant and multiscaling becomes essential.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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 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.
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.
This work describes the realization of physically crosslinked networks based on gelatin by the introduction of functional groups enabling specific supramolecular interactions. Molecular models were developed in order to predict the material properties and permit to establish a knowledge-based approach to material design. The effect of additional supramolecular interactions with hydroxyapaptite was then studied in composite materials. The calculated properties are compared to experimental results to validate the models. The models are then further used for the study of physically crosslinked networks. Gelatin was functionalized with desaminotyrosine (DAT) and desaminotyrosyl-tyrosine (DATT) side groups, derived from the natural amino acid tyrosine. These group can potentially undergo to π-π and hydrogen bonding interactions also under physiological conditions. Molecular dynamics (MD) simulations were performed on models with 0.8 wt.-% or 25 wt.-% water content, using the second generation forcefield CFF91. The validation of the models was obtained by the comparison with specific experimental data such as, density, peptide conformational angles and X-ray scattering spectra. The models were then used to predict the supramolecular organization of the polymer chain, analyze the formation of physical netpoints and calculate the mechanical properties. An important finding of simulation was that with the increase of aromatic groups also the number of observed physical netpoints increased. The number of relatively stable physical netpoints, on average zero 0 for natural gelatin, increased to 1 and 6 for DAT and DATT functionalized gelatins respectively. A comparison with the Flory-Rehner model suggested reduced equilibrium swelling by factor 6 of the DATT-functionalized materials in water. The functionalized gelatins could be synthesized by chemoselective coupling of the free carboxylic acid groups of DAT and DATT to the free amino groups of gelatin. At 25 wt.-% water content, the simulated and experimentally determined elastic mechanical properties (e.g. Young Modulus) were both in the order of GPa and were not influenced by the degree of aromatic modification. The experimental equilibrium degree of swelling in water decreased with increasing the number of inserted aromatic functions (from 2800 vol.-% for pure gelatin to 300 vol.-% for the DATT modified gelatin), at the same time, Young’s modulus, elongation at break, and maximum tensile strength increased. It could be show that the functionalization with DAT and DATT influences the chain organization of gelatin based materials together with a controlled drying condition. Functionalization with DAT and DATT lead to a drastic reduction of helical renaturation, that could be more finely controlled by the applied drying conditions. The properties of the materials could then be influenced by application of two independent methods. Composite materials of DAT and DATT functionalized gelatins with hydroxyapatite (HAp) show a drastic reduction of swelling degree. In tensile tests and rheological measurements, the composites equilibrated in water had increased Young’s moduli (from 200 kPa up to 2 MPa) and tensile strength (from 57 kPa up to 1.1 MPa) compared to the natural polymer matrix without affecting the elongation at break. Furthermore, an increased thermal stability from 40 °C to 85 °C of the networks could be demonstrated. The differences of the behaviour of the functionalized gelatins to pure gelatin as matrix suggested an additional stabilizing bond between the incorporated aromatic groups to the hydroxyapatite.
This thesis focuses on the study of marked Gibbs point processes, in particular presenting some results on their existence and uniqueness, with ideas and techniques drawn from different areas of statistical mechanics: the entropy method from large deviations theory, cluster expansion and the Kirkwood--Salsburg equations, the Dobrushin contraction principle and disagreement percolation.
We first present an existence result for infinite-volume marked Gibbs point processes. More precisely, we use the so-called entropy method (and large-deviation tools) to construct marked Gibbs point processes in R^d under quite general assumptions. In particular, the random marks belong to a general normed space S and are not bounded. Moreover, we allow for interaction functionals that may be unbounded and whose range is finite but random. The entropy method relies on showing that a family of finite-volume Gibbs point processes belongs to sequentially compact entropy level sets, and is therefore tight.
We then present infinite-dimensional Langevin diffusions, that we put in interaction via a Gibbsian description. In this setting, we are able to adapt the general result above to show the existence of the associated infinite-volume measure. We also study its correlation functions via cluster expansion techniques, and obtain the uniqueness of the Gibbs process for all inverse temperatures β and activities z below a certain threshold. This method relies in first showing that the correlation functions of the process satisfy a so-called Ruelle bound, and then using it to solve a fixed point problem in an appropriate Banach space. The uniqueness domain we obtain consists then of the model parameters z and β for which such a problem has exactly one solution.
Finally, we explore further the question of uniqueness of infinite-volume Gibbs point processes on R^d, in the unmarked setting. We present, in the context of repulsive interactions with a hard-core component, a novel approach to uniqueness by applying the discrete Dobrushin criterion to the continuum framework. We first fix a discretisation parameter a>0 and then study the behaviour of the uniqueness domain as a goes to 0. With this technique we are able to obtain explicit thresholds for the parameters z and β, which we then compare to existing results coming from the different methods of cluster expansion and disagreement percolation.
Throughout this thesis, we illustrate our theoretical results with various examples both from classical statistical mechanics and stochastic geometry.
Taking advantage of ATRP and using functionalized initiators, different functionalities were introduced in both α and ω chain-ends of synthetic polymers. These functionalized polymers could then go through modular synthetic pathways such as click cycloaddition (copper-catalyzed or copper-free) or amidation to couple synthetic polymers to other synthetic polymers, biomolecules or silica monoliths. Using this general strategy and designing these co/polymers so that they are thermoresponsive, yet bioinert and biocompatible with adjustable cloud point values (as it is the case in the present thesis), the whole generated system becomes "smart" and potentially applicable in different branches. The applications which were considered in the present thesis were in polymer post-functionalization (in situ functionalization of micellar aggregates with low and high molecular weight molecules), hydrophilic/hydrophobic tuning, chromatography and bioconjugation (enzyme thermoprecipitation and recovery, improvement of enzyme activity). Different α-functionalized co/polymers containing cholesterol moiety, aldehyde, t-Boc protected amine, TMS-protected alkyne and NHS-activated ester were designed and synthesized in this work.
Interactions and feedbacks between tectonics, climate, and upper plate architecture control basin geometry, relief, and depositional systems. The Andes is part of a longlived continental margin characterized by multiple tectonic cycles which have strongly modified the Andean upper plate architecture. In the Andean retroarc, spatiotemporal variations in the structure of the upper plate and tectonic regimes have resulted in marked along-strike variations in basin geometry, stratigraphy, deformational style, and mountain belt morphology. These along-strike variations include high-elevation plateaus (Altiplano and Puna) associated with a thin-skin fold-and-thrust-belt and thick-skin deformation in broken foreland basins such as the Santa Barbara system and the Sierras Pampeanas. At the confluence of the Puna Plateau, the Santa Barbara system and the Sierras Pampeanas, major along-strike changes in upper plate architecture, mountain belt morphology, basement exhumation, and deformation style can be recognized. I have used a source to sink approach to unravel the spatiotemporal tectonic evolution of the Andean retroarc between 26 and 28°S. I obtained a large low-temperature thermochronology data set from basement units which includes apatite fission track, apatite U-Th-Sm/He, and zircon U-Th/He (ZHe) cooling ages. Stratigraphic descriptions of Miocene units were temporally constrained by U-Pb LA-ICP-MS zircon ages from interbedded pyroclastic material.
Modeled ZHe ages suggest that the basement of the study area was exhumed during the Famatinian orogeny (550-450 Ma), followed by a period of relative tectonic quiescence during the Paleozoic and the Triassic. The basement experienced horst exhumation during the Cretaceous development of the Salta rift. After initial exhumation, deposition of thick Cretaceous syn-rift strata caused reheating of several basement blocks within the Santa Barbara system. During the Eocene-Oligocene, the Andean compressional setting was responsible for the exhumation of several disconnected basement blocks. These exhumed blocks were separated by areas of low relief, in which humid climate and low erosion rates facilitated the development of etchplains on the crystalline basement. The exhumed basement blocks formed an Eocene to Oligocene broken foreland basin in the back-bulge depozone of the Andean foreland. During the Early Miocene, foreland basin strata filled up the preexisting Paleogene topography. The basement blocks in lower relief positions were reheated; associated geothermal gradients were higher than 25°C/km. Miocene volcanism was responsible for lateral variations on the amount of reheating along the Campo-Arenal basin. Around 12 Ma, a new deformational phase modified the drainage network and fragmented the lacustrine system. As deformation and rock uplift continued, the easily eroded sedimentary cover was efficiently removed and reworked by an ephemeral fluvial system, preventing the development of significant relief. After ~6 Ma, the low erodibility of the basement blocks which began to be exposed caused relief increase, leading to the development of stable fluvial systems. Progressive relief development modified atmospheric circulation, creating a rainfall gradient. After 3 Ma, orographic rainfall and high relief lead to the development of proximal fluvial-gravitational depositional systems in the surrounding basins.
The recent discovery of an intricate and nontrivial interaction topology among the elements of a wide range of natural systems has altered the manner we understand complexity. For example, the axonal fibres transmitting electrical information between cortical regions form a network which is neither regular nor completely random. Their structure seems to follow functional principles to balance between segregation (functional specialisation) and integration. Cortical regions are clustered into modules specialised in processing different kinds of information, e.g. visual or auditory. However, in order to generate a global perception of the real world, the brain needs to integrate the distinct types of information. Where this integration happens, nobody knows. We have performed an extensive and detailed graph theoretical analysis of the cortico-cortical organisation in the brain of cats, trying to relate the individual and collective topological properties of the cortical areas to their function. We conclude that the cortex possesses a very rich communication structure, composed of a mixture of parallel and serial processing paths capable of accommodating dynamical processes with a wide variety of time scales. The communication paths between the sensory systems are not random, but largely mediated by a small set of areas. Far from acting as mere transmitters of information, these central areas are densely connected to each other, strongly indicating their functional role as integrators of the multisensory information. In the quest of uncovering the structure-function relationship of cortical networks, the peculiarities of this network have led us to continuously reconsider the stablished graph measures. For example, a normalised formalism to identify the “functional roles” of vertices in networks with community structure is proposed. The tools developed for this purpose open the door to novel community detection techniques which may also characterise the overlap between modules. The concept of integration has been revisited and adapted to the necessities of the network under study. Additionally, analytical and numerical methods have been introduced to facilitate understanding of the complicated statistical interrelations between the distinct network measures. These methods are helpful to construct new significance tests which may help to discriminate the relevant properties of real networks from side-effects of the evolutionary-growth processes.
Modern anthropogenic forcing of atmospheric chemistry poses the question of how the Earth System will respond as thousands of gigatons of greenhouse gas are rapidly added to the atmosphere. A similar, albeit nonanthropogenic, situation occurred during the early Paleogene, when catastrophic release of carbon to the atmosphere triggered abrupt increase in global temperatures. The best documented of these events is the Paleocene-Eocene Thermal Maximum (PETM, ~55 Ma) when the magnitude of carbon addition to the oceans and atmosphere was similar to those expected for the future. This event initiated global warming, changes in hydrological cycles, biotic extinction and migrations. A recently proposed hypothesis concerning changes in marine ecosystems suggests that this global warming strongly influenced the shallow-water biosphere, triggering extinctions and turnover in the Larger Foraminifera (LF) community and the demise of corals. The successions from the Adriatic Carbonate Platform (SW Slovenia) represent an ideal location to test the hypothesis of a possible causal link between the PETM and evolution of shallow-water organisms because they record continuous sedimentation from the Late Paleocene to the Early Eocene and are characterized by a rich biota, especially LF, fundamental for detailed biostratigraphic studies. In order to reconstruct paleoenvironmental conditions during deposition, I focused on sedimentological analysis and paleoecological study of benthic assemblages. During the Late Paleocene-earliest Eocene, sedimentation occurred on a shallow-water carbonate ramp system characterized by enhanced nutrient levels. LF represent the common constituent of the benthic assemblages that thrived in this setting throughout the Late Paleocene to the Early Eocene. With detailed biostratigraphic and chemostratigraphic analyses documenting the most complete record to date available for the PETM event in a shallow-water marine environment, I correlated chemostratigraphically for the first time the evolution of LF with the δ¹³C curves. This correlation demonstrated that no major turnover in the LF communities occurred synchronous with the PETM; thus the evolution of LF was mainly controlled by endogenous biotic forces. The study of Late Thanetian metric-sized microbialite-coral mounds which developed in the middle part of the ramp, documented the first Cenozoic occurrence of microbially-cemented mounds. The development of these mounds, with temporary dominance of microbial communities over corals, suggest environmentally-triggered “phase shifts” related to frequent fluctuations of nutrient/turbidity levels during recurrent wet phases which preceding the extreme greenhouse conditions of the PETM. The paleoecological study of the coral community in the microbialites-coral mounds, the study of corals from Early Eocene platform from SW France, and a critical, extensive literature research of Late Paleocene – Early Eocene coral occurrences from the Tethys, the Atlantic, the Caribbean realms suggested that these corals types, even if not forming extensive reefs, are common in the biofacies as small isolated colonies, piles of rubble or small patch-reefs. These corals might have developed ‘alternative’ life strategies to cope with harsh conditions (high/fluctuating nutrients/turbidity, extreme temperatures, perturbation of aragonite saturation state) during the greenhouse times of the early Paleogene, representing a good fossil analogue to modern corals thriving close to their thresholds for survival. These results demonstrate the complexity of the biological responses to extreme conditions, not only in terms of temperature but also nutrient supply, physical disturbance and their temporal variability and oscillating character.
Volcanoes are one of the Earth’s most dynamic zones and responsible for many changes in our planet. Volcano seismology aims to provide an understanding of the physical processes in volcanic systems and anticipate the style and timing of eruptions by analyzing the seismic records. Volcanic tremor signals are usually observed in the seismic records before or during volcanic eruptions. Their analysis contributes to evaluate the evolving volcanic activity and potentially predict eruptions. Years of continuous seismic monitoring now provide useful information for operational eruption forecasting. The continuously growing amount of seismic recordings, however, poses a challenge for analysis, information extraction, and interpretation, to support timely decision making during volcanic crises. Furthermore, the complexity of eruption processes and precursory activities makes the analysis challenging.
A challenge in studying seismic signals of volcanic origin is the coexistence of transient signal swarms and long-lasting volcanic tremor signals. Separating transient events from volcanic tremors can, therefore, contribute to improving our understanding of the underlying physical processes. Some similar issues (data reduction, source separation, extraction, and classification) are addressed in the context of music information retrieval (MIR). The signal characteristics of acoustic and seismic recordings comprise a number of similarities. This thesis is going beyond classical signal analysis techniques usually employed in seismology by exploiting similarities of seismic and acoustic signals and building the information retrieval strategy on the expertise developed in the field of MIR.
First, inspired by the idea of harmonic–percussive separation (HPS) in musical signal processing, I have developed a method to extract harmonic volcanic tremor signals and to detect transient events from seismic recordings. This provides a clean tremor signal suitable for tremor investigation along with a characteristic function suitable for earthquake detection. Second, using HPS algorithms, I have developed a noise reduction technique for seismic signals. This method is especially useful for denoising ocean bottom seismometers, which are highly contaminated by noise. The advantage of this method compared to other denoising techniques is that it doesn’t introduce distortion to the broadband earthquake waveforms, which makes it reliable for different applications in passive seismological analysis. Third, to address the challenge of extracting information from high-dimensional data and investigating the complex eruptive phases, I have developed an advanced machine learning model that results in a comprehensive signal processing scheme for volcanic tremors. Using this method seismic signatures of major eruptive phases can be automatically detected. This helps to provide a chronology of the volcanic system. Also, this model is capable to detect weak precursory volcanic tremors prior to the eruption, which could be used as an indicator of imminent eruptive activity. The extracted patterns of seismicity and their temporal variations finally provide an explanation for the transition mechanism between eruptive phases.
In this work the first observation of new type of liquid crystals is presented. This is ionic self-assembly (ISA) liquid crystals formed by introduction of oppositely charged ions between different low molecular tectonic units. As practically all conventional liquid crystals consist of rigid core and alkyl chains the attention is focused to the simplest case where oppositely charged ions are placed between a rigid core and alkyl tails. The aim of this work is to investigate and understand liquid crystalline and alignment properties of these materials. It was found that ionic interactions within complexes play the main role. Presence of these interactions restricts transition to isotropic phase. In addition, these interactions hold the system (like network) allowing crystallization into a single domain from aligned LC state. Alignment of these simple ISA complexes was spontaneous on a glass substrate. In order to show potentials for application perylenediimide and azobenzene containing ISA complexes have been investigated for correlations between phase behavior and their alignment properties. The best results of macroscopic alignment of perylenediimide-based ISA complexes have been obtained by zone-casting method. In the aligned films the columns of the complex align perpendicular to the phase-transition front. The obtained anisotropy (DR = 18) is thermally stable. The investigated photosensitive (azobenzene-based) ISA complexes show formation of columnar LC phases. It was demonstrated that photo alignment of such complexes was very effective (DR = 50 has been obtained). It was shown that photo-reorientation in the photosensitive ISA complexes is cooperative process. The size of domains has direct influence on efficiency of the photo-reorientation process. In the case of small domains the photo-alignment is the most effective. Under irradiation with linearly polarized light domains reorient in the plane of the film leading to macroscopic alignment of columns parallel to the light polarization and joining of small domains into big ones. Finally, the additional distinguishable properties of the ISA liquid crystalline complexes should be noted: (I) the complexes do not solve in water but readily solve in organic solvents; (II) the complexes have good film-forming properties when cast or spin-coated from organic solvent; (III) alignment of the complexes depends on their structure and secondary interactions between tectonic units.
Analysis and modeling of transient earthquake patterns and their dependence on local stress regimes
(2015)
Investigations in the field of earthquake triggering and associated interactions, which includes aftershock triggering as well as induced seismicity, is important for seismic hazard assessment due to earthquakes destructive power. One of the approaches to study earthquake triggering and their interactions is the use of statistical earthquake models, which are based on knowledge of the basic seismicity properties, in particular, the magnitude distribution and spatiotemporal properties of the triggered events.
In my PhD thesis I focus on some specific aspects of aftershock properties, namely, the relative seismic moment release of the aftershocks with respect to the mainshocks; the spatial correlation between aftershock occurrence and fault deformation; and on the influence of aseismic transients on the aftershock parameter estimation. For the analysis of aftershock sequences I choose a statistical approach, in particular, the well known Epidemic Type Aftershock Sequence (ETAS) model, which accounts for the input of background and triggered seismicity. For my specific purposes, I develop two ETAS model modifications in collaboration with Sebastian Hainzl. By means of this approach, I estimate the statistical aftershock parameters and performed simulations of aftershock sequences as well.
In the case of seismic moment release of aftershocks, I focus on the ratio of cumulative seismic moment release with respect to the mainshocks. Specifically, I investigate the ratio with respect to the focal mechanism of the mainshock and estimate an effective magnitude, which represents the cumulative aftershock energy (similar to Bath's law, which defines the average difference between mainshock and the largest aftershock magnitudes). Furthermore, I compare the observed seismic moment ratios with the results of the ETAS simulations. In particular, I test a restricted ETAS (RETAS) model which is based on results of a clock advanced model and static stress triggering.
To analyze spatial variations of triggering parameters I focus in my second approach on the aftershock occurrence triggered by large mainshocks and the study of the aftershock parameter distribution and their spatial correlation with the coseismic/postseismic slip and interseismic locking. To invert the aftershock parameters I improve the modified ETAS (m-ETAS) model, which is able to take the extension of the mainshock rupture into account. I compare the results obtained by the classical approach with the output of the m-ETAS model.
My third approach is concerned with the temporal clustering of seismicity, which might not only be related to earthquake-earthquake interactions, but also to a time-dependent background rate, potentially biasing the parameter estimations. Thus, my coauthors and I also applied a modification of the ETAS model, which is able to take into account time-dependent background activity. It can be applicable for two different cases: when an aftershock catalog has a temporal incompleteness or when the background seismicity rate changes with time, due to presence of aseismic forces.
An essential part of any research is the testing of the developed models using observational data sets, which are appropriate for the particular study case. Therefore, in the case of seismic moment release I use the global seismicity catalog. For the spatial distribution of triggering parameters I exploit two aftershock sequences of the Mw8.8 2010 Maule (Chile) and Mw 9.0 2011 Tohoku (Japan) mainshocks. In addition, I use published geodetic slip models of different authors. To test our ability to detect aseismic transients my coauthors and I use the data sets from Western Bohemia (Central Europe) and California.
Our results indicate that:
(1) the seismic moment of aftershocks with respect to mainshocks depends on the static stress changes and is maximal for the normal, intermediate for thrust and minimal for strike-slip stress regimes, where the RETAS model shows a good correspondence with the results;
(2) The spatial distribution of aftershock parameters, obtained by the m-ETAS model, shows anomalous values in areas of reactivated crustal fault systems. In addition, the aftershock density is found to be correlated with coseismic slip gradient, afterslip, interseismic coupling and b-values. Aftershock seismic moment is positively correlated with the areas of maximum coseismic slip and interseismically locked areas. These correlations might be related to the stress level or to material properties variations in space;
(3) Ignoring aseismic transient forcing or temporal catalog incompleteness can lead to the significant under- or overestimation of the underlying trigger parameters. In the case when a catalog is complete, this method helps to identify aseismic sources.
Background: Individuals with aphasia after stroke (IWA) often present with working memory (WM) deficits. Research investigating the relationship between WM and language abilities has led to the promising hypothesis that treatments of WM could lead to improvements in language, a phenomenon known as transfer. Although recent treatment protocols have been successful in improving WM, the evidence to date is scarce and the extent to which improvements in trained tasks of WM transfer to untrained memory tasks, spoken sentence comprehension, and functional communication is yet poorly understood.
Aims: We aimed at (a) investigating whether WM can be improved through an adaptive n-back training in IWA (Study 1–3); (b) testing whether WM training leads to near transfer to unpracticed WM tasks (Study 1–3), and far transfer to spoken sentence comprehension (Study 1–3), functional communication (Study 2–3), and memory in daily life in IWA (Study 2–3); and (c) evaluating the methodological quality of existing WM treatments in IWA (Study 3). To address these goals, we conducted two empirical studies – a case-controls study with Hungarian speaking IWA (Study 1) and a multiple baseline study with German speaking IWA (Study 2) – and a systematic review (Study 3).
Methods: In Study 1 and 2 participants with chronic, post-stroke aphasia performed an adaptive, computerized n-back training. ‘Adaptivity’ was implemented by adjusting the tasks’ difficulty level according to the participants’ performance, ensuring that they always practiced at an optimal level of difficulty. To assess the specificity of transfer effects and to better understand the underlying mechanisms of transfer on spoken sentence comprehension, we included an outcome measure testing specific syntactic structures that have been proposed to involve WM processes (e.g., non-canonical structures with varying complexity).
Results: We detected a mixed pattern of training and transfer effects across individuals: five participants out of six significantly improved in the n-back training. Our most important finding is that all six participants improved significantly in spoken sentence comprehension (i.e., far transfer effects). In addition, we also found far transfer to functional communication (in two participants out of three in Study 2) and everyday memory functioning (in all three participants in Study 2), and near transfer to unpracticed n-back tasks (in four participants out of six). Pooled data analysis of Study 1 and 2 showed a significant negative relationship between initial spoken sentence comprehension and the amount of improvement in this ability, suggesting that the more severe the participants’ spoken sentence comprehension deficit was at the beginning of training, the more they improved after training. Taken together, we detected both near far and transfer effects in our studies, but the effects varied across participants. The systematic review evaluating the methodological quality of existing WM treatments in stroke IWA (Study 3) showed poor internal and external validity across the included 17 studies. Poor internal validity was mainly due to use of inappropriate design, lack of randomization of study phases, lack of blinding of participants and/or assessors, and insufficient sampling. Low external validity was mainly related to incomplete information on the setting, lack of use of appropriate analysis or justification for the suitability of the analysis procedure used, and lack of replication across participants and/or behaviors. Results in terms of WM, spoken sentence comprehension, and reading are promising, but further studies with more rigorous methodology and stronger experimental control are needed to determine the beneficial effects of WM intervention.
Conclusions: Results of the empirical studies suggest that WM can be improved with a computerized and adaptive WM training, and improvements can lead to transfer effects to spoken sentence comprehension and functional communication in some individuals with chronic post-stroke aphasia. The fact that improvements were not specific to certain syntactic structures (i.e., non-canonical complex sentences) in spoken sentence comprehension suggest that WM is not involved in the online, automatic processing of syntactic information (i.e., parsing and interpretation), but plays a more general role in the later stage of spoken sentence comprehension (i.e., post-interpretive comprehension). The individual differences in treatment outcomes call for future research to clarify how far these results are generalizable to the population level of IWA. Future studies are needed to identify a few mechanisms that may generalize to at least a subpopulation of IWA as well as to investigate baseline non-linguistic cognitive and language abilities that may play a role in transfer effects and the maintenance of such effects. These may require larger yet homogenous samples.
Optical frequency combs (OFC) constitute an array of phase-correlated equidistant spectral lines with nearly equal intensities over a broad spectral range. The adaptations of combs generated in mode-locked lasers proved to be highly efficient for the calibration of high-resolution (resolving power > 50000) astronomical spectrographs. The observation of different galaxy structures or the studies of the Milky Way are done using instruments in the low- and medium resolution range. To such instruments belong, for instance, the Multi Unit Spectroscopic Explorer (MUSE) being developed for the Very Large Telescope (VLT) of the European Southern Observatory (ESO) and the 4-metre Multi-Object Spectroscopic Telescope (4MOST) being in development for the ESO VISTA 4.1 m Telescope. The existing adaptations of OFC from mode-locked lasers are not resolvable by these instruments.
Within this work, a fibre-based approach for generation of OFC specifically in the low- and medium resolution range is studied numerically. This approach consists of three optical fibres that are fed by two equally intense continuous-wave (CW) lasers. The first fibre is a conventional single-mode fibre, the second one is a suitably pumped amplifying Erbium-doped fibre with anomalous dispersion, and the third one is a low-dispersion highly nonlinear optical fibre. The evolution of a frequency comb in this system is governed by the following processes: as the two initial CW-laser waves with different frequencies propagate through the first fibre, they generate an initial comb via a cascade of four-wave mixing processes. The frequency components of the comb are phase-correlated with the original laser lines and have a frequency spacing that is equal to the initial laser frequency separation (LFS), i.e. the difference in the laser frequencies. In the time domain, a train of pre-compressed pulses with widths of a few pico-seconds arises out of the initial bichromatic deeply-modulated cosine-wave. These pulses undergo strong compression in the subsequent amplifying Erbium-doped fibre: sub-100 fs pulses with broad OFC spectra are formed. In the following low-dispersion highly nonlinear fibre, the OFC experience a further broadening and the intensity of the comb lines are fairly equalised. This approach was mathematically modelled by means of a Generalised Nonlinear Schrödinger Equation (GNLS) that contains terms describing the nonlinear optical Kerr effect, the delayed Raman response, the pulse self-steepening, and the linear optical losses as well as the wavelength-dependent Erbium gain profile for the second fibre. The initial condition equation being a deeply-modulated cosine-wave mimics the radiation of the two initial CW lasers. The numerical studies are performed with the help of Matlab scripts that were specifically developed for the integration of the GNLS and the initial condition according to the proposed approach for the OFC generation. The scripts are based on the Fourth-Order Runge-Kutta in the Interaction Picture Method (RK4IP) in combination with the local error method.
This work includes the studies and results on the length optimisation of the first and the second fibre depending on different values of the group-velocity dispersion of the first fibre. Such length optimisation studies are necessary because the OFC have the biggest possible broadband and exhibit a low level of noise exactly at the optimum lengths. Further, the optical pulse build-up in the first and the second fibre was studied by means of the numerical technique called Soliton Radiation Beat Analysis (SRBA). It was shown that a common soliton crystal state is formed in the first fibre for low laser input powers. The soliton crystal continuously dissolves into separated optical solitons as the input power increases. The pulse formation in the second fibre is critically dependent on the features of the pulses formed in the first fibre. I showed that, for low input powers, an adiabatic soliton compression delivering low-noise OFC occurs in the second fibre. At high input powers, the pulses in the first fibre have more complicated structures which leads to the pulse break-up in the second fibre with a subsequent degradation of the OFC noise performance. The pulse intensity noise studies that were performed within the framework of this thesis allow making statements about the noise performance of an OFC. They showed that the intensity noise of the whole system decreases with the increasing value of LFS.
At present, carbon sequestration in terrestrial ecosystems slows the growth rate of atmospheric CO2 concentrations, and thereby reduces the impact of anthropogenic fossil fuel emissions on the climate system. Changes in climate and land use affect terrestrial biosphere structure and functioning at present, and will likely impact on the terrestrial carbon balance during the coming decades - potentially providing a positive feedback to the climate system due to soil carbon releases under a warmer climate. Quantifying changes, and the associated uncertainties, in regional terrestrial carbon budgets resulting from these effects is relevant for the scientific understanding of the Earth system and for long-term climate mitigation strategies. A model describing the relevant processes that govern the terrestrial carbon cycle is a necessary tool to project regional carbon budgets into the future. This study (1) provides an extensive evaluation of the parameter-based uncertainty in model results of a leading terrestrial biosphere model, the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM), against a range of observations and under climate change, thereby complementing existing studies on other aspects of model uncertainty; (2) evaluates different hypotheses to explain the age-related decline in forest growth, both from theoretical and experimental evidence, and introduces the most promising hypothesis into the model; (3) demonstrates how forest statistics can be successfully integrated with process-based modelling to provide long-term constraints on regional-scale forest carbon budget estimates for a European forest case-study; and (4) elucidates the combined effects of land-use and climate changes on the present-day and future terrestrial carbon balance over Europe for four illustrative scenarios - implemented by four general circulation models - using a comprehensive description of different land-use types within the framework of LPJ-DGVM. This study presents a way to assess and reduce uncertainty in process-based terrestrial carbon estimates on a regional scale. The results of this study demonstrate that simulated present-day land-atmosphere carbon fluxes are relatively well constrained, despite considerable uncertainty in modelled net primary production. Process-based terrestrial modelling and forest statistics are successfully combined to improve model-based estimates of vegetation carbon stocks and their change over time. Application of the advanced model for 77 European provinces shows that model-based estimates of biomass development with stand age compare favourably with forest inventory-based estimates for different tree species. Driven by historic changes in climate, atmospheric CO2 concentration, forest area and wood demand between 1948 and 2000, the model predicts European-scale, present-day age structure of forests, ratio of biomass removals to increment, and vegetation carbon sequestration rates that are consistent with inventory-based estimates. Alternative scenarios of climate and land-use change in the 21<sup>st century suggest carbon sequestration in the European terrestrial biosphere during the coming decades will likely be on magnitudes relevant to climate mitigation strategies. However, the uptake rates are small in comparison to the European emissions from fossil fuel combustion, and will likely decline towards the end of the century. Uncertainty in climate change projections is a key driver for uncertainty in simulated land-atmosphere carbon fluxes and needs to be accounted for in mitigation studies of the terrestrial biosphere.
The world energy consumption has constantly increased every year due to economic development and population growth. This inevitably caused vast amount of CO2 emission, and the CO2 concentration in the atmosphere keeps increasing with economic growth. To reduce CO2 emission, various methods have been developed but there are still many bottlenecks to be solved. Solvents easily absorbing CO2 such as monoethanol-amine (MEA) and diethanolamine, for example, have limitations of solvent loss, amine degradation, vulnerability to heat and toxicity, and the high cost of regeneration which is especially caused due to chemisorption process. Though some of these drawbacks can be compensated through physisorption with zeolites and metal-organic frameworks (MOFs) by displaying significant adsorption selectivity and capacity even in ambient conditions, limitations for these materials still exist. Zeolites demand relatively high regeneration energy and have limited adsorption kinetics due to the exceptionally narrow pore structure. MOFs have low stability against heat and moisture and high manufacturing cost.
Nanoporous carbons have recently received attention as an attractive functional porous material due to their unique properties. These materials are crucial in many applications of modern science and industry such as water and air purification, catalysis, gas separation, and energy storage/conversion due to their high chemical and thermal stability, and in particular electronic conductivity in combination with high specific surface areas. Nanoporous carbons can be used to adsorb environmental pollutants or small gas molecules such as CO2 and to power electrochemical energy storage devices such as batteries and fuel cells. In all fields, their pore structure or electrical properties can be modified depending on their purposes.
This thesis provides an in-depth look at novel nanoporous carbons from the synthetic and the application point of view. The interplay between pore structure, atomic construction, and the adsorption properties of nanoporous carbon materials are investigated. Novel nanoporous carbon materials are synthesized by using simple precursor molecules containing heteroatoms through a facile
templating method. The affinity, and in turn the adsorption capacity, of carbon materials toward polar gas molecules (CO2 and H2O) is enhanced by the modification of their chemical construction. It is also shown that these properties are important in electrochemical energy storage, here especially for supercapacitors with aqueous electrolytes which are basically based on the physisorption of ions on carbon surfaces. This shows that nanoporous carbons can be a “functional” material with specific physical or chemical interactions with guest species just like zeolites and MOFs.
The synthesis of sp2-conjugated materials with high heteroatom content from a mixture of citrazinic acid and melamine in which heteroatoms are already bonded in specific motives is illustrated. By controlling the removal procedure of the salt-template and the condensation temperature, the role of salts in the formation of porosity and as coordination sites for the stabilization of heteroatoms is proven. A high amount of nitrogen of up to 20 wt. %, oxygen contents of up to 19 wt.%, and a high CO2/N2 selectivity with maximum CO2 uptake at 273 K of 5.31 mmol g–1 are achieved. Besides, the further controlled thermal condensation of precursor molecules and advanced functional properties on applications of the synthesized porous carbons are described. The materials have different porosity and atomic construction exhibiting a high nitrogen content up to 25 wt. % as well as a high porosity with a specific surface area of more than 1800 m2 g−1, and a high performance in selective CO2 gas adsorption of 62.7. These pore structure as well as properties of surface affect to water adsorption with a remarkably high Qst of over 100 kJ mol−1 even higher than that of zeolites or CaCl2 well known as adsorbents. In addition to that, the pore structure of HAT-CN-derived carbon materials during condensation in vacuum is fundamentally understood which is essential to maximize the utilization of porous system in materials showing significant difference in their pore volume of 0.5 cm3 g−1 and 0.25 cm3 g−1 without and with vacuum, respectively.
The molecular designs of heteroatom containing porous carbon derived from abundant and simple molecules are introduced in the presented thesis. Abundant precursors that already containing high amount of nitrogen or oxygen are beneficial to achieve enhanced interaction with adsorptives. The physical and chemical properties of these heteroatom-doped porous carbons are affected by mainly two parameters, that is, the porosity from the pore structure and the polarity from the atomic composition on the surface. In other words, controlling the porosity as well as the polarity of the carbon materials is studied to understand interactions with different guest species which is a fundamental knowledge for the utilization on various applications.
The Milky Way is a spiral galaxy consisting of a disc of gas, dust and stars embedded in a halo of dark matter. Within this dark matter halo there is also a diffuse population of stars called the stellar halo, that has been accreting stars for billions of years from smaller galaxies that get pulled in and disrupted by the large gravitational potential of the Milky Way. As they are disrupted, these galaxies leave behind long streams of stars that can take billions of years to mix with the rest of the stars in the halo. Furthermore, the amount of heavy elements (metallicity) of the stars in these galaxies reflects the rate of chemical enrichment that occurred in them, since the Universe has been slowly enriched in heavy elements (e.g. iron) through successive generations of stars which produce them in their cores and supernovae explosions. Therefore, stars that contain small amounts of heavy elements (metal-poor stars) either formed at early times before the Universe was significantly enriched, or in isolated environments. The aim of this thesis is to develop a better understanding of the substructure content and chemistry of the Galactic stellar halo, in order to gain further insight into the formation and evolution of the Milky Way.
The Pristine survey uses a narrow-band filter which specifically targets the Ca II H & K spectral absorption lines to provide photometric metallicities for a large number of stars down to the extremely metal-poor (EMP) regime, making it a very powerful data set for Galactic archaeology studies. In Chapter 2, we quantify the efficiency of the survey using a preliminary spectroscopic follow-up sample of ~ 200 stars. We also use this sample to establish a set of selection criteria to improve the success rate of selecting EMP candidates for follow-up spectroscopy. In Chapter 3, we extend this work and present the full catalogue of ~ 1000 stars from a three year long medium resolution spectroscopic follow-up effort conducted as part of the Pristine survey. From this sample, we compute success rates of 56% and 23% for recovering stars with [Fe/H] < -2.5 and [Fe/H] < -3.0, respectively. This demonstrates a high efficiency for finding EMP stars as compared to previous searches with success rates of 3-4%.
In Chapter 4, we select a sample of ~ 80000 halo stars using colour and magnitude cuts to select a main sequence turnoff population in the distance range 6 < dʘ < 20 kpc. We then use the spectroscopic follow-up sample presented in Chapter 3 to statistically rescale the Pristine photometric metallicities of this sample, and present the resulting corrected metallicity distribution function (MDF) of the halo. The slope at the metal-poor end is significantly shallower than previous spectroscopic efforts have shown, suggesting that there may be more metal-poor stars with [Fe/H] < -2.5 in the halo than previously thought. This sample also shows evidence that the MDF of the halo may not be bimodal as was proposed by previous works, and that the lack of globular clusters in the Milky Way may be the result of a physical truncation of the MDF rather than just statistical under-sampling.
Chapter 5 showcases the unexpected capability of the Pristine filter for separating blue horizontal branch (BHB) stars from Blue Straggler (BS) stars. We demonstrate a purity of 93% and completeness of 91% for identifying BHB stars, a substantial improvement over previous works. We then use this highly pure and complete sample of BHB stars to trace the halo density profile out to d > 100 kpc, and the Sagittarius stream substructure out to ~ 130 kpc.
In Chapter 6 we use the photometric metallicities from the Pristine survey to perform a clustering analysis of the halo as a function of metallicity. Separating the Pristine sample into four metallicity bins of [Fe/H] < -2, -2 < [Fe/H] < -1.5, -1.5 < [Fe/H] < -1 and -0.9 < [Fe/H] < -0.8, we compute the two-point correlation function to measure the amount of clustering on scales of < 5 deg. For a smooth comparison sample we make a mock Pristine data set generated using the Galaxia code based on the Besançon model of the Galaxy. We find enhanced clustering on small scales (< 0.5 deg) for some regions of the Galaxy for the most metal-poor bin ([Fe/H] < -2), while in others we see large scale signals that correspond to known substructures in those directions. This confirms that the substructure content of the halo is highly anisotropic and diverse in different Galactic environments. We discuss the difficulties of removing systematic clustering signals from the data and the limitations of disentangling weak clustering signals from real substructures and residual systematic structure in the data.
Taken together, the work presented in this thesis approaches the problem of better understanding the halo of our Galaxy from multiple angles. Firstly, presenting a sizeable sample of EMP stars and improving the selection efficiency of EMP stars for the Pristine survey, paving the way for the further discovery of metal-poor stars to be used as probes to early chemical evolution. Secondly, improving the selection of BHB distance tracers to map out the halo to large distances, and finally, using the large samples of metal-poor stars to derive the MDF of the inner halo and analyse the substructure content at different metallicities. The results of this thesis therefore expand our understanding of the physical and chemical properties of the Milky Way stellar halo, and provide insight into the processes involved in its formation and evolution.
CHAMP (CHAllenging Minisatellite Payload) is a German small satellite mission to study the earth's gravity field, magnetic field and upper atmosphere. Thanks to the good condition of the satellite so far, the planned 5 years mission is extended to year 2009. The satellite provides continuously a large quantity of measurement data for the purpose of Earth study. The measurements of the magnetic field are undertaken by two Fluxgate Magnetometers (vector magnetometer) and one Overhauser Magnetometer (scalar magnetometer) flown on CHAMP. In order to ensure the quality of the data during the whole mission, the calibration of the magnetometers has to be performed routinely in orbit. The scalar magnetometer serves as the magnetic reference and its readings are compared with the readings of the vector magnetometer. The readings of the vector magnetometer are corrected by the parameters that are derived from this comparison, which is called the scalar calibration. In the routine processing, these calibration parameters are updated every 15 days by means of scalar calibration. There are also magnetic effects coming from the satellite which disturb the measurements. Most of them have been characterized during tests before launch. Among them are the remanent magnetization of the spacecraft and fields generated by currents. They are all considered to be constant over the mission life. The 8 years of operation experience allow us to investigate the long-term behaviors of the magnetometers and the satellite systems. According to the investigation, it was found that for example the scale factors of the FGM show obvious long-term changes which can be described by logarithmic functions. The other parameters (offsets and angles between the three components) can be considered constant. If these continuous parameters are applied for the FGM data processing, the disagreement between the OVM and the FGM readings is limited to \pm1nT over the whole mission. This demonstrates, the magnetometers on CHAMP exhibit a very good stability. However, the daily correction of the parameter Z component offset of the FGM improves the agreement between the magnetometers markedly. The Z component offset plays a very important role for the data quality. It exhibits a linear relationship with the standard deviation of the disagreement between the OVM and the FGM readings. After Z offset correction, the errors are limited to \pm0.5nT (equivalent to a standard deviation of 0.2nT). We improved the corrections of the spacecraft field which are not taken into account in the routine processing. Such disturbance field, e.g. from the power supply system of the satellite, show some systematic errors in the FGM data and are misinterpreted in 9-parameter calibration, which brings false local time related variation of the calibration parameters. These corrections are made by applying a mathematical model to the measured currents. This non-linear model is derived from an inversion technique. If the disturbance field of the satellite body are fully corrected, the standard deviation of scalar error \triangle B remains about 0.1nT. Additionally, in order to keep the OVM readings a reliable standard, the imperfect coefficients of the torquer current correction for the OVM are redetermined by solving a minimization problem. The temporal variation of the spacecraft remanent field is investigated. It was found that the average magnetic moment of the magneto-torquers reflects well the moment of the satellite. This allows for a continuous correction of the spacecraft field. The reasons for the possible unknown systemic error are discussed in this thesis. Particularly, both temperature uncertainties and time errors have influence on the FGM data. Based on the results of this thesis the data processing of future magnetic missions can be designed in an improved way. In particular, the upcoming ESA mission Swarm can take advantage of our findings and provide all the auxiliary measurements needed for a proper recovery of the ambient magnetic field.
The aim of this thesis is to achieve a deep understanding of the working mechanism of polymer based solar cells and to improve the device performance. Two types of the polymer based solar cells are studied here: all-polymer solar cells comprising macromolecular donors and acceptors based on poly(p-phenylene vinylene) and hybrid cells comprising a PPV copolymer in combination with a novel small molecule electron acceptor. To understand the interplay between morphology and photovoltaic properties in all-polymer devices, I compared the photocurrent characteristics and excited state properties of bilayer and blend devices with different nano-morphology, which was fine tuned by using solvents with different boiling points. The main conclusion from these complementary measurements was that the performance-limiting step is the field-dependent generation of free charge carriers, while bimolecular recombination and charge extraction do not compromise device performance. These findings imply that the proper design of the donor-acceptor heterojunction is of major importance towards the goal of high photovoltaic efficiencies. Regarding polymer-small molecular hybrid solar cells I combined the hole-transporting polymer M3EH-PPV with a novel Vinazene-based electron acceptor. This molecule can be either deposited from solution or by thermal evaporation, allowing for a large variety of layer architectures to be realized. I then demonstrated that the layer architecture has a large influence on the photovoltaic properties. Solar cells with very high fill factors of up to 57 % and an open circuit voltage of 1V could be achieved by realizing a sharp and well-defined donor-acceptor heterojunction. In the past, fill factors exceeding 50 % have only been observed for polymers in combination with soluble fullerene-derivatives or nanocrystalline inorganic semiconductors as the electron-accepting component. The finding that proper processing of polymer-vinazene devices leads to similar high values is a major step towards the design of efficient polymer-based solar cells.
In this work, the role of the TusA protein was investigated for the cell functionality and FtsZ ring assembly in Escherichia coli. TusA is the tRNA-2-thiouridine synthase that acts as a sulfur transferase in tRNA thiolation for the formation of 2-thiouridine at the position 34 (wobble base) of tRNALys, tRNAGlu and tRNAGln. It binds the persulfide form of sulfur and transfers it to further proteins during mnm5s2U tRNA modification at wobble position and for Moco biosynthesis. With this thiomodification of tRNA, the ribosome binding is more efficient and frameshifting is averted during the protein translation. Previous studies have revealed an essential role of TusA in bacterial cell physiology since deletion of the tusA gene resulted in retarded growth and filamentous cells during the exponential growth phase in a rich medium which suddenly disappeared during the stationary phase. This indicates a problem in the cell division process. Therefore the focus of this work was to investigate the role of TusA for cell functionality and FtsZ ring formation and thus the cell separation.
The reason behind the filamentous growth of the tusA mutant strain was investigated by growth and morphological analyses. ΔtusA cells showed a retarded growth during the exponential phase compared to the WT strain. Also, morphological analysis of ΔtusA cells confirmed the filamentous cell shape. The growth and cell division defects in ΔtusA indicated a defect in FtsZ protein as a key player of cell division. The microscopic investigation revealed that filamentous ΔtusA cells possessed multiple DNA parts arranged next to each other. This suggested that although the DNA replication occurred correctly, there was a defect in the step where FtsZ should act; probably FtsZ is unable to assemble to the ring structure or the assembled ring is not able to constrict. All tested mutant strains (ΔtusD, ΔtusE and ΔmnmA) involved in the mnm5s2U34 tRNA modification pathway shared the similar retarded growth and filamentous cell shape like ΔtusA strain. Thus, the cell division defect arises from a defect in mnm5s2U34 tRNA thiolation.
Since the FtsZ ring formation was supposed to be defective in filaments, a possible intracellular interaction of TusA and FtsZ was examined by fluorescent (EGFP and mCherry) fusion proteins expression and FRET. FtsZ expressing tusA mutant (DE3) cells showed a red mCherry signal at the cell poles, indicating that FtsZ is still in the assembling phase. Interestingly, the cellular region of EGFP-TusA fusion protein expressed in ΔtusA (DE3) was conspicuous; the EGFP signal was spread throughout the whole cell and, in addition, a slight accumulation of the EGFP-TusA fluorescence was detectable at the cell poles, the same part of the cell as for mCherry-FtsZ. Thus, this strongly suggested an interaction of TusA and FtsZ.
Furthermore, the cellular FtsZ and Fis concentrations, and their change during different growth phases were determined via immunoblotting. All tested deletion strains of mnm5s2U34 tRNA modification show high cellular FtsZ and Fis levels in the exponential phase, shifting to the later growth phases. This shift reflects the retarded growth, whereby the deletion strains reach later the exponential phase. Conclusively, the growth and cell division defect, and thus the formation of filaments, is most likely caused by changes in the cellular FtsZ and Fis concentrations.
Finally, the translation efficiencies of certain proteins (RpoS, Fur, Fis and mFis) in tusA mutant and in additional gene deletion strains were studied whether they were affected by using unmodified U34 tRNAs of Lys, Glu and Gln. The translation efficiency is decreased in mnm5s2U34 tRNA modification-impaired strains in addition to their existing growth and cell division defect due to the elimination of these three amino acids. Finally, these results confirm and reinforce the importance of Lys, Glu and Gln and the mnm5s2U34 tRNA thiolation for efficient protein translation. Thus, these findings verify that the translation of fur, fis and rpoS is regulated by mnm5s2U34 tRNA modifications, which is growth phase-dependent.
In total, this work showed the importance of the role of TusA for bacterial cell functionality and physiology. The deletion of the tusA gene disrupted a complex regulatory network within the cell, that most influenced by the decreased translation of Fis and RpoS, caused by the absence of mnm5s2U34 tRNA modifications. The disruption of RpoS and Fis cellular network influences in turn the cellular FtsZ level in the early exponential phase. Finally, the reduced FtsZ concentration leads to elongated, filamentous E. coli cells, which are unable to divide.
Synchronization is a fundamental phenomenon in nature. It can be considered as a general property of self-sustained oscillators to adjust their rhythm in the presence of an interaction.
In this work we investigate complex regimes of synchronization phenomena by means of theoretical analysis, numerical modeling, as well as practical analysis of experimental data.
As a subject of our investigation we consider chimera state, where due to spontaneous symmetry-breaking of an initially homogeneous oscillators lattice split the system into two parts with different dynamics. Chimera state as a new synchronization phenomenon was first found in non-locally coupled oscillators system, and has attracted a lot of attention in the last decade. However, the recent studies indicate that this state is also possible in globally coupled systems. In the first part of this work, we show under which conditions the chimera-like state appears in a system of globally coupled identical oscillators with intrinsic delayed feedback. The results of the research explain how initially monostable oscillators became effectivly bistable in the presence of the coupling and create a mean field that sustain the coexistence of synchronized and desynchronized states. Also we discuss other examples, where chimera-like state appears due to frequency dependence of the phase shift in the bistable system.
In the second part, we make further investigation of this topic by modeling influence of an external periodic force to an oscillator with intrinsic delayed feedback. We made stability analysis of the synchronized state and constructed Arnold tongues. The results explain formation of the chimera-like state and hysteric behavior of the synchronization area. Also, we consider two sets of parameters of the oscillator with symmetric and asymmetric Arnold tongues, that correspond to mono- and bi-stable regimes of the oscillator.
In the third part, we demonstrate the results of the work, which was done in collaboration with our colleagues from Psychology Department of University of Potsdam. The project aimed to study the effect of the cardiac rhythm on human perception of time using synchronization analysis. From our part, we made a statistical analysis of the data obtained from the conducted experiment on free time interval reproduction task. We examined how ones heartbeat influences the time perception and searched for possible phase synchronization between heartbeat cycles and time reproduction responses. The findings support the prediction that cardiac cycles can serve as input signals, and is used for reproduction of time intervals in the range of several seconds.
Water quality in river systems is of growing concern due to rising anthropogenic pressures and climate change. Mitigation efforts have been placed under the guidelines of different governance conventions during last decades (e.g., the Water Framework Directive in Europe). Despite significant improvement through relatively straightforward measures, the environmental status has likely reached a plateau. A higher spatiotemporal accuracy of catchment nitrate modeling is, therefore, needed to identify critical source areas of diffuse nutrient pollution (especially for nitrate) and to further guide implementation of spatially differentiated, cost-effective mitigation measures. On the other hand, the emerging high-frequency sensor monitoring upgrades the monitoring resolution to the time scales of biogeochemical processes and enables more flexible monitoring deployments under varying conditions. The newly available information offers new prospects in understanding nitrate spatiotemporal dynamics. Formulating such advanced process understanding into catchment models is critical for model further development and environmental status evaluation. This dissertation is targeting on a comprehensive analysis of catchment and in-stream nitrate dynamics and is aiming to derive new insights into their spatial and temporal variabilities through the new fully distributed model development and the new high-frequency data.
Firstly, a new fully distributed, process-based catchment nitrate model (the mHM-Nitrate model) is developed based on the mesoscale Hydrological Model (mHM) platform. Nitrate process descriptions are adopted from the Hydrological Predictions for the Environment (HYPE), with considerable improved implementations. With the multiscale grid-based discretization, mHM-Nitrate balances the spatial representation and the modeling complexity. The model has been thoughtfully evaluated in the Selke catchment (456 km2), central Germany, which is characterized by heterogeneous physiographic conditions. Results show that the model captures well the long-term discharge and nitrate dynamics at three nested gauging stations. Using daily nitrate-N observations, the model is also validated in capturing short-term fluctuations due to changes in runoff partitioning and spatial contribution during flooding events. By comparing the model simulations with the values reported in the literature, the model is capable of providing detailed and reliable spatial information of nitrate concentrations and fluxes. Therefore, the model can be taken as a promising tool for environmental scientists in advancing environmental modeling research, as well as for stakeholders in supporting their decision-making, especially for spatially differentiated mitigation measures.
Secondly, a parsimonious approach of regionalizing the in-stream autotrophic nitrate uptake is proposed using high-frequency data and further integrated into the new mHM-Nitrate model. The new regionalization approach considers the potential uptake rate (as a general parameter) and effects of above-canopy light and riparian shading (represented by global radiation and leaf area index data, respectively). Multi-parameter sensors have been continuously deployed in a forest upstream reach and an agricultural downstream reach of the Selke River. Using the continuous high-frequency data in both streams, daily autotrophic uptake rates (2011-2015) are calculated and used to validate the regionalization approach. The performance and spatial transferability of the approach is validated in terms of well-capturing the distinct seasonal patterns and value ranges in both forest and agricultural streams. Integrating the approach into the mHM-Nitrate model allows spatiotemporal variability of in-stream nitrate transport and uptake to be investigated throughout the river network.
Thirdly, to further assess the spatial variability of catchment nitrate dynamics, for the first time the fully distributed parameterization is investigated through sensitivity analysis. Sensitivity results show that parameters of soil denitrification, in-stream denitrification and in-stream uptake processes are the most sensitive parameters throughout the Selke catchment, while they all show high spatial variability, where hot-spots of parameter sensitivity can be explicitly identified. The Spearman rank correlation is further analyzed between sensitivity indices and multiple catchment factors. The correlation identifies that the controlling factors vary spatially, reflecting heterogeneous catchment responses in the Selke catchment. These insights are, therefore, informative in informing future parameter regionalization schemes for catchment water quality models. In addition, the spatial distributions of parameter sensitivity are also influenced by the gauging information that is being used for sensitivity evaluation. Therefore, an appropriate monitoring scheme is highly recommended to truly reflect the catchment responses.
Supercapacitors are electrochemical energy storage devices with rapid charge/discharge rate and long cycle life. Their biggest challenge is the inferior energy density compared to other electrochemical energy storage devices such as batteries. Being the most widely spread type of supercapacitors, electrochemical double-layer capacitors (EDLCs) store energy by electrosorption of electrolyte ions on the surface of charged electrodes. As a more recent development, Na-ion capacitors (NICs) are expected to be a more promising tactic to tackle the inferior energy density due to their higher-capacity electrodes and larger operating voltage. The charges are simultaneously stored by ion adsorption on the capacitive-type cathode surface and via faradic process in the battery-type anode, respectively. Porous carbon electrodes are of great importance in these devices, but the paramount problems are the facile synthetic routes for high-performance carbons and the lack of fundamental understanding of the energy storage mechanisms. Therefore, the aim of the present dissertation is to develop novel synthetic methods for (nitrogen-doped) porous carbon materials with superior performance, and to reveal a deeper understanding energy storage mechanisms of EDLCs and NICs.
The first part introduces a novel synthetic method towards hierarchical ordered meso-microporous carbon electrode materials for EDLCs. The large amount of micropores and highly ordered mesopores endow abundant sites for charge storage and efficient electrolyte transport, respectively, giving rise to superior EDLC performance in different electrolytes. More importantly, the controversial energy storage mechanism of EDLCs employing ionic liquid (IL) electrolytes is investigated by employing a series of porous model carbons as electrodes. The results not only allow to conclude on the relations between the porosity and ion transport dynamics, but also deliver deeper insights into the energy storage mechanism of IL-based EDLCs which is different from the one usually dominating in solvent-based electrolytes leading to compression double-layers.
The other part focuses on anodes of NICs, where novel synthesis of nitrogen-rich porous carbon electrodes and their sodium storage mechanism are investigated. Free-standing fibrous nitrogen-doped carbon materials are synthesized by electrospinning using the nitrogen-rich monomer (hexaazatriphenylene-hexacarbonitrile, C18N12) as the precursor followed by condensation at high temperature. These fibers provide superior capacity and desirable charge/discharge rate for sodium storage. This work also allows insights into the sodium storage mechanism in nitrogen-doped carbons. Based on this mechanism, further optimization is done by designing a composite material composed of nitrogen-rich carbon nanoparticles embedded in conductive carbon matrix for a better charge/discharge rate. The energy density of the assembled NICs significantly prevails that of common EDLCs while maintaining the high power density and long cycle life.
When azobenzene-modified photosensitive polymer films are irradiated with light interference patterns, topographic variations in the film develop that follow the electric field vector distribution resulting in the formation of surface relief grating (SRG). The exact correspondence of the electric field vector orientation in interference pattern in relation to the presence of local topographic minima or maxima of SRG is in general difficult to determine. In my thesis, we have established a systematic procedure to accomplish the correlation between different interference patterns and the topography of SRG. For this, we devise a new setup combining an atomic force microscope and a two-beam interferometer (IIAFM). With this set-up, it is possible to track the topography change in-situ, while at the same time changing polarization and phase of the impinging interference pattern. To validate our results, we have compared two photosensitive materials named in short as PAZO and trimer. This is the first time that an absolute correspondence between the local distribution of electric field vectors of interference pattern and the local topography of the relief grating could be established exhaustively. In addition, using our IIAFM we found that for a certain polarization combination of two orthogonally polarized interfering beams namely SP (↕, ↔) interference pattern, the topography forms SRG with only half the period of the interference patterns. Exploiting this phenomenon we are able to fabricate surface relief structures below diffraction limit with characteristic features measuring only 140 nm, by using far field optics with a wavelength of 491 nm. We have also probed for the stresses induced during the polymer mass transport by placing an ultra-thin gold film on top (5–30 nm). During irradiation, the metal film not only deforms along with the SRG formation, but ruptures in regular and complex manner. The morphology of the cracks differs strongly depending on the electric field distribution in the interference pattern even when the magnitude and the kinetic of the strain are kept constant. This implies a complex local distribution of the opto-mechanical stress along the topography grating. The neutron reflectivity measurements of the metal/polymer interface indicate the penetration of metal layer within the polymer resulting in the formation of bonding layer that confirms the transduction of light induced stresses in the polymer layer to a metal film.
Successful sentence comprehension requires the comprehender to correctly figure out who did what to whom. For example, in the sentence John kicked the ball, the comprehender has to figure out who did the action of kicking and what was being kicked. This process of identifying and connecting the syntactically-related words in a sentence is called dependency completion. What are the cognitive constraints that determine dependency completion? A widely-accepted theory is cue-based retrieval. The theory maintains that dependency completion is driven by a content-addressable search for the co-dependents in memory. The cue-based retrieval explains a wide range of empirical data from several constructions including subject-verb agreement, subject-verb non-agreement, plausibility mismatch configurations, and negative polarity items.
However, there are two major empirical challenges to the theory: (i) Grammatical sentences’ data from subject-verb number agreement dependencies, where the theory predicts a slowdown at the verb in sentences like the key to the cabinet was rusty compared to the key to the cabinets was rusty, but the data are inconsistent with this prediction; and, (ii) Data from antecedent-reflexive dependencies, where a facilitation in reading times is predicted at the reflexive in the bodybuilder who worked with the trainers injured themselves vs. the bodybuilder who worked with the trainer injured themselves, but the data do not show a facilitatory effect.
The work presented in this dissertation is dedicated to building a more general theory of dependency completion that can account for the above two datasets without losing the original empirical coverage of the cue-based retrieval assumption. In two journal articles, I present computational modeling work that addresses the above two empirical challenges.
To explain the grammatical sentences’ data from subject-verb number agreement dependencies, I propose a new model that assumes that the cue-based retrieval operates on a probabilistically distorted representation of nouns in memory (Article I). This hybrid distortion-plus-retrieval model was compared against the existing candidate models using data from 17 studies on subject-verb number agreement in 4 languages. I find that the hybrid model outperforms the existing models of number agreement processing suggesting that the cue-based retrieval theory must incorporate a feature distortion assumption.
To account for the absence of facilitatory effect in antecedent-reflexive dependencies, I propose an individual difference model, which was built within the cue-based retrieval framework (Article II). The model assumes that individuals may differ in how strongly they weigh a syntactic cue over a number cue. The model was fitted to data from two studies on antecedent-reflexive dependencies, and the participant-level cue-weighting was estimated. We find that one-fourth of the participants, in both studies, weigh the syntactic cue higher than the number cue in processing reflexive dependencies and the remaining participants weigh the two cues equally. The result indicates that the absence of predicted facilitatory effect at the level of grouped data is driven by some, not all, participants who weigh syntactic cues higher than the number cue. More generally, the result demonstrates that the assumption of differential cue weighting is important for a theory of dependency completion processes. This differential cue weighting idea was independently supported by a modeling study on subject-verb non-agreement dependencies (Article III).
Overall, the cue-based retrieval, which is a general theory of dependency completion, needs to incorporate two new assumptions: (i) the nouns stored in memory can undergo probabilistic feature distortion, and (ii) the linguistic cues used for retrieval can be weighted differentially. This is the cumulative result of the modeling work presented in this dissertation.
The dissertation makes an important theoretical contribution: Sentence comprehension in humans is driven by a mechanism that assumes cue-based retrieval, probabilistic feature distortion, and differential cue weighting. This insight is theoretically important because there is some independent support for these three assumptions in sentence processing and the broader memory literature. The modeling work presented here is also methodologically important because for the first time, it demonstrates (i) how the complex models of sentence processing can be evaluated using data from multiple studies simultaneously, without oversimplifying the models, and (ii) how the inferences drawn from the individual-level behavior can be used in theory development.
The correlations between the chemical structures of the 2,5-diphenyl-1,3,4-oxadiazole compounds and their corresponding vapour deposited film structures on Si/SiO2 were systematically investigated with AFM, XSR and IR for the first time. The result shows that the film structure depends strongly on the substrate temperature (Ts). For the compounds with ether bridge group, the film periodicity depends linearly on the length of the aliphatic chain. The films based on those oxadiazols have ordered structure in the investigated substrate temperature region, while die amide bridged compounds form ordered film only at high Ts due to the formation of intermolecular H-bond. The tilt angle of most molecules is determined by the pi-pi complexes between the molecules. The intermolecular interaction between head groups leads to the structural transformation during the thermal treatment after deposition. All the ether bridged oxadiazoles form films with bilayer structure, while amide bridged oxadiazole form film bilayer structure only when the molecule has a head group.
Time-dependent correlation function based methods to study optical spectroscopy involving electronic transitions can be traced back to the work of Heller and coworkers. This intuitive methodology can be expected to be computationally efficient and is applied in the current work to study the vibronic absorption, emission, and resonance Raman spectra of selected organic molecules. Besides, the "non-standard" application of this approach to photoionization processes is also explored. The application section consists of four chapters as described below.
In Chapter 4, the molar absorptivities and vibronic absorption/emission spectra of perylene and several of its N-substituted derivatives are investigated. By systematically varying the number and position of N atoms, it is shown that the presence of nitrogen heteroatoms has a negligible effect on the molecular structure and geometric distortions upon electronic transitions, while spectral properties are more sensitive: In particular the number of N atoms is important while their position is less decisive. Thus, N-substitution can be used to fine-tune the optical properties of perylene-based molecules.
In Chapter 5, the same methods are applied to study the vibronic absorption/emission and resonance Raman spectra of a newly synthesized donor-acceptor type molecule. The simulated absorption/emission spectra agree fairly well with experimental data, with discrepancies being attributed to solvent effects. Possible modes which may dominate the fine-structure in the vibronic spectra are proposed by analyzing the correlation function with the aid of Raman and resonance Raman spectra.
In the next two chapters, besides the above types of spectra, the methods are extended to study photoelectron spectra of several small diamondoid-related systems (molecules, radicals, and cations). Comparison of the photoelectron spectra with available experimental data suggests that the correlation function based approach can describe ionization processes reasonably well. Some of these systems, cationic species in particular, exhibit somewhat peculiar optical behavior, which presents them as possible candidates for functional devices.
Correlation function based methods in a more general sense can be very versatile. In fact, besides the above radiative processes, formulas for non-radiative processes such as internal conversion have been derived in literature. Further implementation of the available methods is among our next goals.
The present thesis focuses on the synthesis of nanostructured iron-based compounds by using β-FeOOH nanospindles and poly(ionic liquid)s (PILs) vesicles as hard and soft templates, respectively, to suppress the shuttle effect of lithium polysulfides (LiPSs) in Li-S batteries. Three types of composites with different nanostructures (mesoporous nanospindle, yolk-shell nanospindle, and nanocapsule) have been synthesized and applied as sulfur host material for Li-S batteries. Their interactions with LiPSs and effects on the electrochemical performance of Li-S batteries have been systematically studied.
In the first part of the thesis, carbon-coated mesoporous Fe3O4 (C@M-Fe3O4) nanospindles have been synthesized to suppress the shuttle effect of LiPSs. First, β-FeOOH nanospindles have been synthesized via the hydrolysis of iron (III) chloride in aqueous solution and after silica coating and subsequent calcination, mesoporous Fe2O3 (M-Fe2O3) have been obtained inside the confined silica layer through pyrolysis of β-FeOOH. After the removal of the silica layer, electron tomography (ET) has been applied to rebuild the 3D structure of the M-Fe2O3 nanospindles. After coating a thin layer of polydopamine (PDA) as carbon source, the PDA-coated M-Fe2O3 particles have been calcinated to synthesize C@M-Fe3O4 nanospindles. With the chemisorption of Fe3O4 and confinement of mesoporous structure to anchor LiPSs, the composite C@M-Fe3O4/S electrode delivers a remaining capacity of 507.7 mAh g-1 at 1 C after 600 cycles.
In the second part of the thesis, a series of iron-based compounds (Fe3O4, FeS2, and FeS) with the same yolk-shell nanospindle morphology have been synthesized, which allows for the direct comparison of the effects of compositions on the electrochemical performance of Li-S batteries. The Fe3O4-carbon yolk-shell nanospindles have been synthesized by using the β-FeOOH nanospindles as hard template. Afterwards, Fe3O4-carbon yolk-shell nanospindles have been used as precursors to obtain iron sulfides (FeS and FeS2)-carbon yolk-shell nanospindles through sulfidation at different temperatures. Using the three types of yolk-shell nanospindles as sulfur host, the effects of compositions on interactions with LiPSs and electrochemical performance in Li-S batteries have been systematically investigated and compared. Benefiting from the chemisorption and catalytic effect of FeS2 particles and the physical confinement of the carbon shell, the FeS2-C/S electrode exhibits the best electrochemical performance with an initial specific discharge capacity of 877.6 mAh g-1 at 0.5 C and a retention ratio of 86.7% after 350 cycles.
In the third part, PILs vesicles have been used as soft template to synthesize carbon nanocapsules embedded with iron nitride particles to immobilize and catalyze LiPSs in Li-S batteries. First, 3-n-decyl-1-vinylimidazolium bromide has been used as monomer to synthesize PILs nanovesicles by free radical polymerization. Assisted by PDA coating route and ion exchange, PIL nanovesicles have been successfully applied as soft template in morphology-maintaining carbonization to prepare carbon nanocapsules embedded with iron nitride nanoparticles (FexN@C). The well-dispersed iron nitride nanoparticles effectively catalyze the conversion of LiPSs to Li2S, owing to their high electrical conductivity and strong chemical binding to LiPSs. The constructed FexN@C/S cathode demonstrates a high initial discharge capacity of 1085.0 mAh g-1 at 0.5 C with a remaining value of 930.0 mAh g-1 after 200 cycles.
The results in the present thesis demonstrate the facile synthetic routes of nanostructured iron-based compounds with controllable morphologies and compositions using soft and hard colloidal templates, which can be applied as sulfur host to suppress the shuttle behavior of LiPSs. The synthesis approaches developed in this thesis are also applicable to fabricating other transition metal-based compounds with porous nanostructures for other applications.