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Research on novel and advanced biomaterials is an indispensable step towards their applications in desirable fields such as tissue engineering, regenerative medicine, cell culture, or biotechnology. The work presented here focuses on such a promising material: polyelectrolyte multilayer (PEM) composed of hyaluronic acid (HA) and poly(L-lysine) (PLL). This gel-like polymer surface coating is able to accumulate (bio-)molecules such as proteins or drugs and release them in a controlled manner. It serves as a mimic of the extracellular matrix (ECM) in composition and intrinsic properties. These qualities make the HA/PLL multilayers a promising candidate for multiple bio-applications such as those mentioned above. The work presented aims at the development of a straightforward approach for assessment of multi-fractional diffusion in multilayers (first part) and at control of local molecular transport into or from the multilayers by laser light trigger (second part).
The mechanism of the loading and release is governed by the interaction of bioactives with the multilayer constituents and by the diffusion phenomenon overall. The diffusion of a molecule in HA/PLL multilayers shows multiple fractions of different diffusion rate. Approaches, that are able to assess the mobility of molecules in such a complex system, are limited. This shortcoming motivated the design of a novel evaluation tool presented here.
The tool employs a simulation-based approach for evaluation of the data acquired by fluorescence recovery after photobleaching (FRAP) method. In this approach, possible fluorescence recovery scenarios are primarily simulated and afterwards compared with the data acquired while optimizing parameters of a model until a sufficient match is achieved. Fluorescent latex particles of different sizes and fluorescein in an aqueous medium are utilized as test samples validating the analysis results. The diffusion of protein cytochrome c in HA/PLL multilayers is evaluated as well.
This tool significantly broadens the possibilities of analysis of spatiotemporal FRAP data, which originate from multi-fractional diffusion, while striving to be widely applicable. This tool has the potential to elucidate the mechanisms of molecular transport and empower rational engineering of the drug release systems.
The second part of the work focuses on the fabrication of such a spatiotemporarily-controlled drug release system employing the HA/PLL multilayer. This release system comprises different layers of various functionalities that together form a sandwich structure. The bottom layer, which serves as a reservoir, is formed by HA/PLL PEM deposited on a planar glass substrate. On top of the PEM, a layer of so-called hybrids is deposited. The hybrids consist of thermoresponsive poly(N-isopropylacrylamide) (PNIPAM) -based hydrogel microparticles with surface-attached gold nanorods. The layer of hybrids is intended to serve as a gate that controls the local molecular transport through the PEM–solution-interface. The possibility of stimulating the molecular transport by near-infrared (NIR) laser irradiation is being explored.
From several tested approaches for the deposition of hybrids onto the PEM surface, the drying-based approach was identified as optimal. Experiments, that examine the functionality of the fabricated sandwich at elevated temperature, document the reversible volume phase transition of the PEM-attached hybrids while sustaining the sandwich stability. Further, the gold nanorods were shown to effectively absorb light radiation in the tissue- and cell-friendly NIR spectral region while transducing the energy of light into heat. The rapid and reversible shrinkage of the PEM-attached hybrids was thereby achieved. Finally, dextran was employed as a model transport molecule. It loads into the PEM reservoir in a few seconds with the partition constant of 2.4, while it spontaneously releases in a slower, sustained manner. The local laser irradiation of the sandwich, which contains the fluorescein isothiocyanate tagged dextran, leads to a gradual reduction of fluorescence intensity in the irradiated region.
The release system fabricated employs renowned photoresponsivity of the hybrids in an innovative setting. The results of the research are a step towards a spatially-controlled on-demand drug release system that paves the way to spatiotemporally controlled drug release.
The approaches developed in this work have the potential to elucidate the molecular dynamics in ECM and to foster engineering of multilayers with properties tuned to mimic the ECM. The work aims at spatiotemporal control over the diffusion of bioactives and their presentation to the cells.
We recently demonstrated that the sympathetic nervous system can be voluntarily activated following a training program consisting of cold exposure, breathing exercises, and meditation. This resulted in profound attenuation of the systemic inflammatory response elicited by lipopolysaccharide (LPS) administration. Herein, we assessed whether this training program affects the plasma metabolome and if these changes are linked to the immunomodulatory effects observed. A total of 224 metabolites were identified in plasma obtained from 24 healthy male volunteers at six timepoints, of which 98 were significantly altered following LPS administration. Effects of the training program were most prominent shortly after initiation of the acquired breathing exercises but prior to LPS administration, and point towards increased activation of the Cori cycle. Elevated concentrations of lactate and pyruvate in trained individuals correlated with enhanced levels of anti-inflammatory interleukin (IL)-10. In vitro validation experiments revealed that co-incubation with lactate and pyruvate enhances IL-10 production and attenuates the release of pro-inflammatory IL-1 beta and IL-6 by LPS-stimulated leukocytes. Our results demonstrate that practicing the breathing exercises acquired during the training program results in increased activity of the Cori cycle. Furthermore, this work uncovers an important role of lactate and pyruvate in the anti-inflammatory phenotype observed in trained subjects.
Objective: We investigated the effects of combined balance and strength training on measures of balance and muscle strength in older women with a history of falls.
Methods: Twenty-seven older women aged 70.4 ± 4.1 years (age range: 65 to 75 years) were randomly allocated to either an intervention (IG, n = 12) or an active control (CG, n = 15) group. The IG completed 8 weeks combined balance and strength training program with three sessions per week including visual biofeedback using force plates. The CG received physical therapy and gait training at a rehabilitation center. Training volumes were similar between the groups. Pre and post training, tests were applied for the assessment of muscle strength (weight-bearing squat [WBS] by measuring the percentage of body mass borne by each leg at different knee flexions [0°, 30°, 60°, and 90°], sit-to-stand test [STS]), and balance. Balance tests used the modified clinical test of sensory interaction (mCTSIB) with eyes closed (EC) and opened (EO), on stable (firm) and unstable (foam) surfaces as well as spatial parameters of gait such as step width and length (cm) and walking speed (cm/s).
Results: Significant group × time interactions were found for different degrees of knee flexion during WBS (0.0001 < p < 0.013, 0.441 < d < 0.762). Post hoc tests revealed significant pre-to-post improvements for both legs and for all degrees of flexion (0.0001 < p < 0.002, 0.697 < d < 1.875) for IG compared to CG. Significant group × time interactions were found for firm EO, foam EO, firm EC, and foam EC (0.006 < p < 0.029; 0.302 < d < 0.518). Post hoc tests showed significant pre-to-post improvements for both legs and for all degrees of oscillations (0.0001 < p < 0.004, 0.753 < d < 2.097) for IG compared to CG. This study indicates that combined balance and strength training improved percentage distribution of body weight between legs at different conditions of knee flexion (0°, 30°, 60°, and 90°) and also decreased the sway oscillation on a firm surface with eyes closed, and on foam surface (with eyes opened or closed) in the IG.
Conclusion: The higher positive effects of training seen in standing balance tests, compared with dynamic tests, suggests that balance training exercises including lateral, forward, and backward exercises improved static balance to a greater extent in older women.
Lava domes are severely hazardous, mound-shaped extrusions of highly viscous lava and commonly erupt at many active stratovolcanoes around the world. Due to gradual growth and flank oversteepening, such lava domes regularly experience partial or full collapses, resulting in destructive and far-reaching pyroclastic density currents. They are also associated with cyclic explosive activity as the complex interplay of cooling, degassing, and solidification of dome lavas regularly causes gas pressurizations on the dome or the underlying volcano conduit. Lava dome extrusions can last from days to decades, further highlighting the need for accurate and reliable monitoring data.
This thesis aims to improve our understanding of lava dome processes and to contribute to the monitoring and prediction of hazards posed by these domes. The recent rise and sophistication of photogrammetric techniques allows for the extraction of observational data in unprecedented detail and creates ideal tools for accomplishing this purpose. Here, I study natural lava dome extrusions as well as laboratory-based analogue models of lava dome extrusions and employ photogrammetric monitoring by Structure-from-Motion (SfM) and Particle-Image-Velocimetry (PIV) techniques. I primarily use aerial photography data obtained by helicopter, airplanes, Unoccupied Aircraft Systems (UAS) or ground-based timelapse cameras. Firstly, by combining a long time-series of overflight data at Volcán de Colima, México, with seismic and satellite radar data, I construct a detailed timeline of lava dome and crater evolution. Using numerical model, the impact of the extrusion on dome morphology and loading stress is further evaluated and an impact on the growth direction is identified, bearing important implications for the location of collapse hazards. Secondly, sequential overflight surveys at the Santiaguito lava dome, Guatemala, reveal surface motion data in high detail. I quantify the growth of the lava dome and the movement of a lava flow, showing complex motions that occur on different timescales and I provide insight into rock properties relevant for hazard assessment inferred purely by photogrammetric processing of remote sensing data. Lastly, I recreate artificial lava dome and spine growth using analogue modelling under controlled conditions, providing new insights into lava extrusion processes and structures as well as the conditions in which they form.
These findings demonstrate the capabilities of photogrammetric data analyses to successfully monitor lava dome growth and evolution while highlighting the advantages of complementary modelling methods to explain the observed phenomena. The results presented herein further bear important new insights and implications for the hazards posed by lava domes.
This thesis aims to investigate the visualization approaches in the field of annotated discourse relations and to find a solution that meets the requirements best by comparing different programming tools. The subject of this research are coherence relations, which have several properties that can be challenging for many visualization methods. The thesis presents five different visualization options from both the application and the development perspective. The initially tested simple HTML approaches as well as the software package displaCy show the insufficient level for the visualization purposes of this work. The alternative implementation with D3 would optimally meet the requirements but goes beyond the scope of the project. The main method chosen in this thesis was implemented as a single web application and uses the brat annotation tool, which fulfills most of the defined requirements for the representation of the coherence relations. The application graphically displays the coherence relations annotated in the text and offers a filter function for different relation types.
Human and murine studies identified the lysosomal enzyme acid sphingomyelinase (ASM) as a target for antidepressant therapy and revealed its role in the pathophysiology of major depression. In this study, we generated a mouse model with overexpression of Asm (Asm-tg(fb)) that is restricted to the forebrain to rule out any systemic effects of Asm overexpression on depressive-like symptoms. The increase in Asm activity was higher in male Asm-tg(fb) mice than in female Asm-tg(fb) mice due to the breeding strategy, which allows for the generation of wild-type littermates as appropriate controls. Asm overexpression in the forebrain of male mice resulted in a depressive-like phenotype, whereas in female mice, Asm overexpression resulted in a social anxiogenic-like phenotype. Ceramides in male Asm-tg(fb) mice were elevated specifically in the dorsal hippocampus. mRNA expression analyses indicated that the increase in Asm activity affected other ceramide-generating pathways, which might help to balance ceramide levels in cortical brain regions. This forebrain-specific mouse model offers a novel tool for dissecting the molecular mechanisms that play a role in the pathophysiology of major depression.
Objective: To determine immediate performance measures for short-term, multicomponent cardiac rehabilitation (CR) in clinical routine in patients of working age, taking into
account cardiovascular risk factors, physical performance, social medicine, and subjective health parameters and to explore the underlying dimensionality.
Design: Prospective observational multicenter register study in 12 rehabilitation centers throughout Germany.
Setting: Comprehensive 3-week CR.
Portal Wissen = Energy
(2020)
Energy – there is something to it. There is, of course, the matter-of-fact definition in every student encyclopedia: “the capacity to do mechanical work, transfer heat, or emit light.” In this way, energy accompanies us, often undetected, all day long: getting out of bed, turning on the heat, switching on the lights, taking a hot shower, getting dressed, making coffee, having breakfast – before we have even left the house, we have already released, transformed, applied, and refueled a lot of energy. And we haven’t even worked, at least not in the traditional sense.
But energy is not just a physical quantity that, due to its omnipresence, plays a key role in every natural science discipline, such as biology and chemistry, but also in almost every technical field. It is also indispensable when it comes to how we understand and describe our world and our activities – and it has been for a long time. How about an example? The Greek philosopher Aristotle was the first to speak of enérgeia, for him a rather nonphysical thing, a living “reality and effectiveness ” – that which makes the possible real. About 2,100 years later, the uncrowned king of German literature Johann Wolfgang von Goethe declared it to be a humanistic essence. “What can we call our own if not energy, strength, and will!” And for his contemporary Wilhelm von Humboldt, energy “was the human’s first and only virtue”. Although physics began to dominate the concept of energy when it became the leading science in the 19th century, energy remained significant in many areas.
Reason enough for us to take a look at energy-related matters at the University of Potsdam. We found them in a wide range of disciplines: While Iranian physicist Safa Shoaee is researching how organic materials can be used to manufacture the solar cells of the future, Swedish environmental researcher Johan Lilliestam is focusing on the different dimensions of the energy transition to learn what makes it successful. Slavicist Susanne Strätling, on the other hand, crosses the boundaries of her discipline as she examines a complex conceptual history and tries to find out why energy electrifies us today more than ever. And physicist Markus Gühr is able to use ultrashort flashes of light to investigate how molecules change under its influence and convert energy in the process.
Of course, we have enough energy to highlight the diversity of research at the University of Potsdam besides the feature topic of this issue. A cognitive researcher, for example, explains why our brain processes both music and language according to its own respective rhythm, while an environmental researcher presents a method that uses particles from outer space to measure soil moisture. Educational researchers have also launched a study on hate speech in schools and we introduce a palaeoclimatologist who is one of twelve researchers in the new postdoc program at the University of Potsdam. We have spared no energy!
Polypropylene as one of the world's top commodity polymers is also widely used in the textile industry. However, its non-polar nature and partially crystalline structure significantly complicate the process of industrial coloring of polypropylene. Currently, textiles made of polypropylene or with a significant proportion of polypropylene are dyed under quite harsh conditions, including the use of high pressures and temperatures, which makes this process energy intensive. This research presents a three-step synthesis of coloring agents, capable of adhering onto synthetic polypropylene yarns without harsh energy-consuming conditions. This is possible by encapsulation of organic pigments using trimethoxyphenylsilane, introduction of surface double bonds via modification of the silica shell with trimethoxysilylpropylmethacrylate and final attachment of highly adhesive anchor peptides using thiol-ene chemistry. We demonstrate the applicability of this approach by dyeing polypropylene yarns in a simple process under ambient conditions after giving a step-by-step guide for the synthesis of these new dyeing agents. Finally, the successful dyeing of the yarns is visualized, and its practicability is discussed.
We present novel experimental evidence on the availability and the status of exhaustivity inferences with focus partitioning in German, English, and Hungarian. Results suggest that German and English focus-background clefts and Hungarian focus share important properties, (É. Kiss 1998, 1999; Szabolcsi 1994; Percus 1997; Onea & Beaver 2009). Those constructions are anaphoric devices triggering an existence presupposition. EXH-inferences are not obligatory in such constructions in English, German, or Hungarian, against some previous literature (Percus 1997; Büring & Križ 2013; É. Kiss 1998), but in line with pragmatic analyses of EXH-inferences in clefts (Horn 1981, 2016; Pollard & Yasavul 2016). The cross-linguistic differences in the distribution of EXH-inferences are attributed to properties of the Hungarian number marking system.
The Fram Strait is an area with a relatively low and irregular distribution of diatom microfossils in surface sediments, and thus microfossil records are scarce, rarely exceed the Holocene, and contain sparse information about past richness and taxonomic composition. These attributes make the Fram Strait an ideal study site to test the utility of sedimentary ancient DNA (sedaDNA) metabarcoding. Amplifying a short, partial rbcL marker from samples of sediment core MSM05/5-712-2 resulted in 95.7 % of our sequences being assigned to diatoms across 18 different families, with 38.6 % of them being resolved to species and 25.8 % to genus level. Independent replicates show a high similarity of PCR products, especially in the oldest samples. Diatom sedaDNA richness is highest in the Late Weichselian and lowest in Mid- and Late Holocene samples. Taxonomic composition is dominated by cold-water and sea-ice-associated diatoms and suggests several reorganisations – after the Last Glacial Maximum, after the Younger Dryas, and after the Early and after the Mid-Holocene. Different sequences assigned to, amongst others, Chaetoceros socialis indicate the detectability of intra-specific diversity using sedaDNA. We detect no clear pattern between our diatom sedaDNA record and the previously published IP25 record of this core, although proportions of pennate diatoms increase with higher IP25 concentrations and proportions of Nitzschia cf. frigida exceeding 2 % of the assemblage point towards past sea-ice presence.
The European rabbit (Oryctolagus cuniculus) is declining in large parts of Europe but populations in some German cities remained so far unaffected by this decline. The question arises of how urbanization affects patterns of population genetic variation and differentiation in German rabbit populations, as urban habitat fragmentation may result in altered meta-population dynamics. To address this question, we used microsatellite markers to genotype rabbit populations occurring along a rural-to-urban gradient in and around the city of Frankfurt, Germany. We found no effect of urbanization on allelic richness. However, the observed heterozygosity was significantly higher in urban than rural populations and also the inbreeding coefficients were lower, most likely reflecting the small population sizes and possibly on-going loss of genetic diversity in structurally impoverished rural areas. Global FST and G'ST-values suggest moderate but significant differentiation between populations. Multiple matrix regression with randomization ascribed this differentiation to isolation-by-environment rather than isolation-by-distance. Analyses of migration rates revealed asymmetrical gene flow, which was higher from rural into urban populations than vice versa and may again reflect intensified agricultural land-use practices in rural areas. We discuss that populations inhabiting urban areas will likely play an important role in the future distribution of European rabbits.
How We Found Our IMU
(2020)
Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection procedures. However, selecting the most suitable IMU device for a certain use case is increasingly challenging. In this study, guidelines for IMU selection are proposed. In particular, seven IMUs were compared in terms of their specifications, data collection procedures, and raw data quality. Data collected from the IMUs were then analyzed by a gait analysis algorithm. The difference in accuracy of the calculated gait parameters between the IMUs could be used to retrace the issues in raw data, such as acceleration range or sensor calibration. Based on our algorithm, we were able to identify the best-suited IMUs for our needs. This study provides an overview of how to select the IMUs based on the area of study with concrete examples, and gives insights into the features of seven commercial IMUs using real data.
Organic photovoltaics based on non-fullerene acceptors (NFAs) show record efficiency of 16 to 17% and increased photovoltage owing to the low driving force for interfacial charge-transfer. However, the low driving force potentially slows down charge generation, leading to a tradeoff between voltage and current. Here, we disentangle the intrinsic charge-transfer rates from morphology-dependent exciton diffusion for a series of polymer:NFA systems. Moreover, we establish the influence of the interfacial energetics on the electron and hole transfer rates separately. We demonstrate that charge-transfer timescales remain at a few hundred femtoseconds even at near-zero driving force, which is consistent with the rates predicted by Marcus theory in the normal region, at moderate electronic coupling and at low re-organization energy. Thus, in the design of highly efficient devices, the energy offset at the donor:acceptor interface can be minimized without jeopardizing the charge-transfer rate and without concerns about a current-voltage tradeoff.
The plasmasphere is a dynamic region of cold, dense plasma surrounding the Earth. Its shape and size are highly susceptible to variations in solar and geomagnetic conditions. Having an accurate model of plasma density in the plasmasphere is important for GNSS navigation and for predicting hazardous effects of radiation in space on spacecraft. The distribution of cold plasma and its dynamic dependence on solar wind and geomagnetic conditions remain, however, poorly quantified. Existing empirical models of plasma density tend to be oversimplified as they are based on statistical averages over static parameters. Understanding the global dynamics of the plasmasphere using observations from space remains a challenge, as existing density measurements are sparse and limited to locations where satellites can provide in-situ observations. In this dissertation, we demonstrate how such sparse electron density measurements can be used to reconstruct the global electron density distribution in the plasmasphere and capture its dynamic dependence on solar wind and geomagnetic conditions.
First, we develop an automated algorithm to determine the electron density from in-situ measurements of the electric field on the Van Allen Probes spacecraft. In particular, we design a neural network to infer the upper hybrid resonance frequency from the dynamic spectrograms obtained with the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite, which is then used to calculate the electron number density. The developed Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm is applied to more than four years of EMFISIS measurements to produce the publicly available electron density data set.
We utilize the obtained electron density data set to develop a new global model of plasma density by employing a neural network-based modeling approach. In addition to the location, the model takes the time history of geomagnetic indices and location as inputs, and produces electron density in the equatorial plane as an output. It is extensively validated using in-situ density measurements from the Van Allen Probes mission, and also by comparing the predicted global evolution of the plasmasphere with the global IMAGE EUV images of He+ distribution. The model successfully reproduces erosion of the plasmasphere on the night side as well as plume formation and evolution, and agrees well with data.
The performance of neural networks strongly depends on the availability of training data, which is limited during intervals of high geomagnetic activity. In order to provide reliable density predictions during such intervals, we can employ physics-based modeling. We develop a new approach for optimally combining the neural network- and physics-based models of the plasmasphere by means of data assimilation. The developed approach utilizes advantages of both neural network- and physics-based modeling and produces reliable global plasma density reconstructions for quiet, disturbed, and extreme geomagnetic conditions.
Finally, we extend the developed machine learning-based tools and apply them to another important problem in the field of space weather, the prediction of the geomagnetic index Kp. The Kp index is one of the most widely used indicators for space weather alerts and serves as input to various models, such as for the thermosphere, the radiation belts and the plasmasphere. It is therefore crucial to predict the Kp index accurately. Previous work in this area has mostly employed artificial neural networks to nowcast and make short-term predictions of Kp, basing their inferences on the recent history of Kp and solar wind measurements at L1. We analyze how the performance of neural networks compares to other machine learning algorithms for nowcasting and forecasting Kp for up to 12 hours ahead. Additionally, we investigate several machine learning and information theory methods for selecting the optimal inputs to a predictive model of Kp. The developed tools for feature selection can also be applied to other problems in space physics in order to reduce the input dimensionality and identify the most important drivers.
Research outlined in this dissertation clearly demonstrates that machine learning tools can be used to develop empirical models from sparse data and also can be used to understand the underlying physical processes. Combining machine learning, physics-based modeling and data assimilation allows us to develop novel methods benefiting from these different approaches.
Although the use of stable transformation technology has led to great insight into gene function, its application in high-throughput studies remains arduous. Agro-infiltration have been widely used in species such as Nicotiana benthamiana for the rapid detection of gene expression and protein interaction analysis, but this technique does not work efficiently in other plant species, including Arabidopsis thaliana. As an efficient high-throughput transient expression system is currently lacking in the model plant species A. thaliana, we developed a method that is characterized by high efficiency, reproducibility, and suitability for transient expression of a variety of functional proteins in A. thaliana and 7 other plant species, including Brassica oleracea, Capsella rubella, Thellungiella salsuginea, Thellungiella halophila, Solanum tuberosum, Capsicum annuum, and N. benthamiana. Efficiency of this method was independently verified in three independent research facilities, pointing to the robustness of this technique. Furthermore, in addition to demonstrating the utility of this technique in a range of species, we also present a case study employing this method to assess protein-protein interactions in the sucrose biosynthesis pathway in Arabidopsis.
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2017. Selected projects have presented their results on April 25th and November 15th 2017 at the Future SOC Lab Day events.
Completely water-based systems are of interest for the development of novel material for various reasons: On one hand, they provide benign environment for biological systems and on the other hand they facilitate effective molecular transport in a membrane-free environment. In order to investigate the general potential of aqueous two-phase systems (ATPSs) for biomaterials and compartmentalized systems, various solid particles were applied to stabilize all-aqueous emulsion droplets. The target ATPS to be investigated should be prepared via mixing of two aqueous solutions of water-soluble polymers, which turn biphasic when exceeding a critical polymer concentration. Hydrophilic polymers with a wide range of molar mass such as dextran/poly(ethylene glycol) (PEG) can therefore be applied. Solid particles adsorbed at the interfaces can be exceptionally efficient stabilizers forming so-called Pickering emulsions, and nanoparticles can bridge the correlation length of polymer solutions and are thereby the best option for water-in-water emulsions.
The first approach towards the investigation of ATPS was conducted with all aqueous dextran-PEG emulsions in the presence of poly(dopamine) particles (PDP) in Chapter 4. The water-in-water emulsions were formed with a PEG/dextran system via utilizing PDP as stabilizers. Studies of the formed emulsions were performed via laser scanning confocal microscope (CLSM), optical microscope (OM), cryo-scanning electron microscope (SEM) and tensiometry. The stable emulsions (at least 16 weeks) were demulsified easily via dilution or surfactant addition. Furthermore, the solid PDP at the water-water interface were crosslinked in order to inhibit demulsification of the Pickering emulsion. Transmission electron microscope (TEM) and scanning electron microscope (SEM) were used to visualize the morphology of PDP before and after crosslinking. PDP stabilized water-in-water emulsions were utilized in the following Chapter 5 to form supramolecular compartmentalized hydrogels. Here, hydrogels were prepared in pre-formed water-in-water emulsions and gelled via α-cyclodextrin-PEG (α-CD-PEG) inclusion complex formation. Studies of the formed complexes were performed via X-ray powder diffraction (XRD) and the mechanical properties of the hydrogels were measured with oscillatory shear rheology. In order to verify the compartmentalized state and its triggered decomposition, hydrogels and emulsions were assessed via OM, SEM and CLSM. The last chapter broadens the investigations from the previous two systems by utilizing various carbon nitrides (CN) as different stabilizers in ATPS. CN introduces another way to trigger demulsification, namely irradiation with visible light. Therefore, emulsification and demulsification with various triggers were probed. The investigated all aqueous multi-phase systems will act as model for future fabrication of biocompatible materials, cell micropatterning as well as separation of compartmentalized systems.
Millennial-scale palaeoclimate variability has been documented in various terrestrial and marine palaeoclimate proxy records throughout the Northern Hemisphere for the last glacial cycle. Its clear expression and rapid shifts between different states of climate (Greenland Interstadials and Stadials) represents a correlation tool beyond the resolution of e.g. luminescence dating, especially relevant for terrestrial deposits. Usually, comparison of terrestrial proxy datasets and the Greenland ice cores indicates a complex expression of millennial-scale climate variability as recorded in terrestrial geoarchives including loess. Loess is the most widespread terrestrial geoarchive of the Quaternary and especially widespread over Eurasia. However, loess often records a smoothed representation of millennial-scale variability without all fidelity when compared to the Greenland data, this being a relevant limiting feature in integrating loess with other palaeoclimate records. To better understand the loess proxy-response to millennial-scale climate variability, we simulate a proxy signal smoothing by natural processes through application of low-pass filters of delta O-18 data from Greenland, a high-resolution palaeoclimate reference record, alongside speleothem isotope records from the Black Sea-Mediterranean region. We show that low-pass filters represent rather simple models for better constraining the expression of millennial-scale climate variability in low sedimentation environments, and in sediments where proxy-response signals are most likely affected by natural smoothing (by e.g. bioturbation). Interestingly, smoothed datasets from Greenland and the Black Sea-Mediterranean region are most similar in the last similar to 15 ka and between similar to 50-30 ka. Between similar to 30-15 ka, roughly corresponding to the Last Glacial Maximum and the deglaciation, the records show dissimilarities, challenging the construction of robust correlative time-scales in this age range. From our analysis it becomes apparent that patterns of palaeoclimate signals in loess-palaeosol sequences often might be better explained by smoothed Greenland reference data than the original high-resolution Greenland dataset, or other reference data. This opens the possibility to better assess the temporal resolution and palaeoclimate potential of loess-palaeosol sequences in recording supra-regional climate patterns, as well as to securely integrate loess with other chronologically better-resolved palaeoclimate records.
Seismological and seismotectonic analysis of the northwestern Argentine Central Andean foreland
(2020)
After a severe M W 5.7 earthquake on October 17, 2015 in El Galpón in the province of Salta NW Argentina, I installed a local seismological network around the estimated epicenter. The network covered an area characterized by inherited Cretaceous normal faults and neotectonic faults with unknown recurrence intervals, some of which may have been reactivated normal faults. The 13 three-component seismic stations recorded data continuously for 15 months.
The 2015 earthquake took place in the Santa Bárbara System of the Andean foreland, at about 17km depth. This region is the easternmost morphostructural region of the central Andes. As a part of the broken foreland, it is bounded to the north by the Subandes fold-and-thrust belt and the Sierras Pampeanas to the south; to the east lies the Chaco-Paraná basin.
A multi-stage morphotectonic evolution with thick-skinned basement uplift and coeval thin-skinned deformation in the intermontane basins is suggested for the study area. The release of stresses associated with the foreland deformation can result in strong earthquakes, as the study area is known for recurrent and historical, destructive earthquakes. The available continuous record reaches back in time, when the strongest event in 1692 (magnitude 7 or intensity IX) destroyed the city of Esteco. Destructive earthquakes and surface deformation are thus a hallmark of this part of the Andean foreland.
With state-of-the-art Python packages (e.g. pyrocko, ObsPy), a semi-automatic approach is followed to analyze the collected continuous data of the seismological network. The resulting 1435 hypocenter locations consist of three different groups: 1.) local crustal earthquakes (nearly half of the events belong to this group), 2.) interplate activity, of regional distance in the slab of the Nazca-plate, and 3.) very deep earthquakes at about 600km depth. My major interest focused on the first event class. Those crustal events are partly aftershock events of the El Galpón earthquake and a second earthquake, in the south of the same fault. Further events can be considered as background seismicity of other faults within the study area. Strikingly, the seismogenic zone encompass the whole crust and propagates brittle deformation down, close to the Moho.
From the collected seismological data, a local seismic velocity model is estimated, using VELEST. After the execution of various stability tests, the robust minimum 1D-velocity model implies guiding values for the composition of the local, subsurface structure of the crust. Afterwards, performing a hypocenter relocation enables the assignment of individual earthquakes to aftershock clusters or extended seismotectonic structures. This allows the mapping of previously unknown seismogenic faults.
Finally, focal mechanisms are modeled for events with acurately located hypocenters, using the newly derived local velocity model. A compressive regime is attested by the majority of focal mechanisms, while the strike direction of the individual seismogenic structures is in agreement with the overall north – south orientation of the Central Andes, its mountain front, and individual mountain ranges in the southern Santa-Bárbara-System.