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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.