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Carbohydrates play a vital role in all living organisms; serving as a cornerstone in primary metabolism through the release of energy from their hydrolysis and subsequent re-utilization (Apriyanto et al., 2022). Starch is the principal carbohydrate reserve in plants, providing essential energy for plant growth. Furthermore, starch serves as a significant carbohydrate source in the human diet. Beyond its nutritional value, starch has extensive industrial application associated with many aspects of human society, such as feed, pharmacy, textiles, and the production of biodegradable plastics. Understanding the mechanisms underlying starch metabolism in plants carries multifaceted benefits. Not only does it contribute to increasing crop yield and refining grain quality, but also can improve the efficiency of industrial applications.
Starch in plants is categorized into two classes based on their location and function: transitory starch and storage starch. Transitory starch is produced in chloroplasts of autotrophic tissues/organs, such as leaves. It is synthesized during the day and degraded during the night. Storage starch is synthesized in heterotrophic tissues/organs, such as endosperm, roots and tubers, which is utilized for plant reproduction and industrial application in human life. Most studies aiming to comprehend starch metabolism of Arabidopsis thaliana primarily focus on transitory starch.
Starch is stored as granular form in chloroplast and amyloplast. The parameters of starch granules, including size, morphology, and quantity per chloroplast serve as indicators of starch metabolism status. However, the understanding of their regulatory mechanism is still incomplete. In this research, I initially employed a simple and adapted method based on laser confocal scanning microscopy (LCSM) to observe size, morphology and quantity of starch granules within chloroplasts in Arabidopsis thaliana in vivo. This method facilitated a rapid and versatile analysis of starch granule parameters across numerous samples. Utilizing this approach, I compared starch granule number per chloroplast between mesophyll cells and guard cells in both wild type plants (Col-0) and several starch related mutants. The results revealed that the granule number is distinct between mesophyll cells and guard cells, even within the same genetic background, suggesting that guard cells operate a unique regulatory mechanism of starch granule number.
Subsequently, I redirected my attention toward examining starch morphology. Through microscopy analyses, I observed a gradual alteration in starch granule morphology in certain mutants during leaf aging. Specifically, in mutants such as sex1-8 and dpe2phs1ss4, there was a progressive alteration in starch granule morphology over time. Conversely, in Col-0 and ss4 mutant, these morphological alterations were not evident. This discovery suggests a new perspective to understand the development of starch morphology.
Further investigation revealed that mutants lacking either Disproportionating enzyme 2 (DPE2) or MALTOSE-EXCESS 1 (MEX1) exhibited gradual alterations in starch morphology with leaf aging. Notably, the most severe effects on starch morphology occurred in double mutants lacking either DPE2 or MEX1 in conjunction with a lack of starch synthase 4 (SS4). In these mutations, a transformation of the starch granule morphology from the typical discoid morphology to oval and eventually to a spherical shape.
To investigate the changes in the internal structure of starch during this alteration, I analyzed the chain length distribution (CLD) of the amylopectin of young, intermediate and old leaves of the mutants. Throughout starch granule development, I found an increased presence of short glucan chains within the granules, particularly evident in dpe2ss4 and mex1ss4 mutants, as well as their parental single mutants. Notably, the single mutant ss4 also showed an affected granule morphology, albeit not influenced by leaf aging..
The CLD pattern of the amylopectin reflects an integrative regulation involving several participants in starch synthesis, including starch synthases (SSs), starch branching/debranching enzymes (SBEs/DBEs). Therefore, I further detected the expression of related genes on transcription level and the enzymatic activity of their respective proteins. Results indicated altered gene expression of several regulators in these mutants, particularly demonstrating dramatic alterations in dpe2 and dpe2ss4 with leaf aging. These changes corresponded with the observed alterations in starch granule morphology.
Taken together, I have identified and characterized a progressive alteration in starch granule morphology primarily resulting from the deficiencies in DPE2 and MEX1. Furthermore, I have associated the CLD pattern with the granule morphogenesis, as well as the gene expression and enzymatic activity of proteins involved in starch synthesis. Unlike SS4, which is implicated in starch initiation, MEX1 and DPE2 are involved into starch degradation. MEX1 is located in chloroplast envelope and DPE2 is situated in the cytosol. Considering the locations and known functions of DPE2/MEX1 and SS4, I infer that there might be two pathways influencing starch morphology: an initiation-affected pathway via SS4 and a degradation-affected pathway via DPE2/MEX1.
Massive stars (Mini > 8 Msol) are the key feedback agents within galaxies, as they shape their surroundings via their powerful winds, ionizing radiation, and explosive supernovae. Most massive stars are born in binary systems, where interactions with their companions significantly alter their evolution and the feedback they deposit in their host galaxy. Understanding binary evolution, particularly in the low-metallicity environments as proxies for the Early Universe, is crucial for interpreting the rest-frame ultraviolet spectra observed in high-redshift galaxies by telescopes like Hubble and James Webb.
This thesis aims to tackle this challenge by investigating in detail massive binaries within the low-metallicity environment of the Small Magellanic Cloud galaxy. From ultraviolet and multi-epoch optical spectroscopic data, we uncovered post-interaction binaries. To comprehensively characterize these binary systems, their stellar winds, and orbital parameters, we use a multifaceted approach. The Potsdam Wolf-Rayet stellar atmosphere code is employed to obtain the stellar and wind parameters of the stars. Additionally, we perform consistent light and radial velocity fitting with the Physics of Eclipsing Binaries software, allowing for the independent determination of orbital parameters and component masses. Finally, we utilize these results to challenge the standard picture of stellar evolution and improve our understanding of low-metallicity stellar populations by calculating our binary evolution models with the Modules for Experiments in Stellar Astrophysics code.
We discovered the first four O-type post-interaction binaries in the SMC (Chapters 2, 5, and 6). Their primary stars have temperatures similar to other OB stars and reside far from the helium zero-age main sequence, challenging the traditional view of binary evolution. Our stellar evolution models suggest this may be due to enhanced mixing after core-hydrogen burning. Furthermore, we discovered the so-far most massive binary system undergoing mass transfer (Chapter 3), offering a unique opportunity to test mass-transfer efficiency in extreme conditions. Our binary evolution calculations revealed unexpected evolutionary pathways for accreting stars in binaries, potentially providing the missing link to understanding the observed Wolf-Rayet population within the SMC (Chapter 4). The results presented in this thesis unveiled the properties of massive binaries at low-metallicity which challenge the way the spectra of high-redshift galaxies are currently being analyzed as well as our understanding of massive-star feedback within galaxies.
Astrophysical shocks, driven by explosive events such as supernovae, efficiently accelerate charged particles to relativistic energies. The majority of these shocks occur in collisionless plasmas where the energy transfer is dominated by particle-wave interactions.Strong nonrelativistic shocks found in supernova remnants are plausible sites of galactic cosmic ray production, and the observed emission indicates the presence of nonthermal electrons. To participate in the primary mechanism of energy gain - Diffusive Shock Acceleration - electrons must have a highly suprathermal energy, implying a need for very efficient pre-acceleration. This poorly understood aspect of the shock acceleration theory is known as the electron injection problem. Studying electron-scale phenomena requires the use of fully kinetic particle-in-cell (PIC) simulations, which describe collisionless plasma from first principles.
Most published studies consider a homogenous upstream medium, but turbulence is ubiquitous in astrophysical environments and is typically driven at magnetohydrodynamic scales, cascading down to kinetic scales. For the first time, I investigate how preexisting turbulence affects electron acceleration at nonrelativistic shocks using the fully kinetic approach. To accomplish this, I developed a novel simulation framework that allows the study of shocks propagating in turbulent media. It involves simulating slabs of turbulent plasma separately, which are further continuously inserted into a shock simulation. This demands matching of the plasma slabs at the interface. A new procedure of matching electromagnetic fields and currents prevents numerical transients, and the plasma evolves self-consistently. The versatility of this framework has the potential to render simulations more consistent with turbulent systems in various astrophysical environments.
In this Thesis, I present the results of 2D3V PIC simulations of high-Mach-number nonrelativistic shocks with preexisting compressive turbulence in an electron-ion plasma. The chosen amplitudes of the density fluctuations ($\lesssim15\%$) concord with \textit{in situ} measurements in the heliosphere and the local interstellar medium. I explored how these fluctuations impact the dynamics of upstream electrons, the driving of the plasma instabilities, electron heating and acceleration. My results indicate that while the presence of the turbulence enhances variations in the upstream magnetic field, their levels remain too low to influence the behavior of electrons at perpendicular shocks significantly. However, the situation is different at oblique shocks. The external magnetic field inclined at an angle between $50^\circ \lesssim \theta_\text{Bn} \lesssim 75^\circ$ relative to the shock normal allows the escape of fast electrons toward the upstream region. An extended electron foreshock region is formed, where these particles drive various instabilities. Results of an oblique shock with $\theta_\text{Bn}=60^\circ$ propagating in preexisting compressive turbulence show that the foreshock becomes significantly shorter, and the shock-reflected electrons have higher temperatures. Furthermore, the energy spectrum of downstream electrons shows a well-pronounced nonthermal tail that follows a power law with an index up to -2.3.
The methods and results presented in this Thesis could serve as a starting point for more realistic modeling of interactions between shocks and turbulence in plasmas from first principles.
Condensation and crystallization are omnipresent phenomena in nature. The formation of droplets or crystals on a solid surface are familiar processes which, beyond their scientific interest, are required in many technological applications. In recent years, experimental techniques have been developed which allow patterning a substrate with surface domains of molecular thickness, surface area in the mesoscopic scale, and different wettabilities (i.e., different degrees of preference for a substance that is in contact with the substrate). The existence of new patterned surfaces has led to increased theoretical efforts to understand wetting phenomena in such systems.
In this thesis, we deal with some problems related to the equilibrium of phases (e.g., liquid-vapor coexistence) and the kinetics of phase separation in the presence of chemically patterned surfaces. Two different cases are considered: (i) patterned surfaces in contact with liquid and vapor, and (ii) patterned surfaces in contact with a crystalline phase. One of the problems that we have studied is the following: It is widely believed that if air containing water vapor is cooled to its dew point, droplets of water are immediately formed. Although common experience seems to support this view, it is not correct. It is only when air is cooled well below its dew point that the phase transition occurs immediately. A vapor cooled slightly below its dew point is in a metastable state, meaning that the liquid phase is more stable than the vapor, but the formation of droplets requires some time to occur, which can be very long.
It was first pointed out by J. W. Gibbs that the metastability of a vapor depends on the energy necessary to form a nucleus (a droplet of a critical size). Droplets smaller than the critical size will tend to disappear, while droplets larger than the critical size will tend to grow. This is consistent with an energy barrier that has its maximum at the critical size, as is the case for droplets formed directly in the vapor or in contact with a chemically uniform planar wall. Classical nucleation theory describes the time evolution of the condensation in terms of the random process of droplet growth through this energy barrier. This process is activated by thermal fluctuations, which eventually will form a droplet of the critical size.
We consider nucleation of droplets from a vapor on a substrate patterned with easily wettable (lyophilic) circular domains. Under certain conditions of pressure and temperature, the condensation of a droplet on a lyophilic circular domain proceeds through a barrier with two maxima (a double barrier). We have extended classical nucleation theory to account for the kinetics of nucleation through a double barrier, and applied this extension to nucleation on lyophilic circular domains.
Genome-scale metabolic models are mathematical representations of all known reactions occurring in a cell. Combined with constraints based on physiological measurements, these models have been used to accurately predict metabolic fluxes and effects of perturbations (e.g. knock-outs) and to inform metabolic engineering strategies. Recently, protein-constrained models have been shown to increase predictive potential (especially in overflow metabolism), while alleviating the need for measurement of nutrient uptake rates. The resulting modelling frameworks quantify the upkeep cost of a certain metabolic flux as the minimum amount of enzyme required for catalysis. These improvements are based on the use of in vitro turnover numbers or in vivo apparent catalytic rates of enzymes for model parameterization. In this thesis several tools for the estimation and refinement of these parameters based on in vivo proteomics data of Escherichia coli, Saccharomyces cerevisiae, and Chlamydomonas reinhardtii have been developed and applied. The difference between in vitro and in vivo catalytic rate measures for the three microorganisms was systematically analyzed. The results for the facultatively heterotrophic microalga C. reinhardtii considerably expanded the apparent catalytic rate estimates for photosynthetic organisms. Our general finding pointed at a global reduction of enzyme efficiency in heterotrophy compared to other growth scenarios. Independent of the modelled organism, in vivo estimates were shown to improve accuracy of predictions of protein abundances compared to in vitro values for turnover numbers. To further improve the protein abundance predictions, machine learning models were trained that integrate features derived from protein-constrained modelling and codon usage. Combining the two types of features outperformed single feature models and yielded good prediction results without relying on experimental transcriptomic data. The presented work reports valuable advances in the prediction of enzyme allocation in unseen scenarios using protein constrained metabolic models. It marks the first successful application of this modelling framework in the biotechnological important taxon of green microalgae, substantially increasing our knowledge of the enzyme catalytic landscape of phototrophic microorganisms.
Wie ist der „gute Ruf“ von Unternehmen und Einzelpersonen im Umfeld von Online-Bewertungsplattformen geschützt? Das Werk erforscht, ob und inwieweit das geltende Recht einen adäquaten und lückenlosen Schutz für die unternehmerische und personelle Reputation gewährleitstet. Die Systematisierung und Untersuchung des bestehenden Regelungsgefüges konzentriert sich auf das Lauterkeitsrecht und das allgemeine Deliktsrecht unter besonderer Berücksichtigung der rechtlichen Innovationen auf nationaler (UWG-Reform 2022) und europäischer (New Deal for Consumers, Digital Services Act) Ebene.
Die Dissertation wurde für den ›Justizpreis Berlin-Brandenburg – Carl Gottlieb Svarez 2024‹ vorgeschlagen.
Organizations are investing billions on innovation and agility initiatives to stay competitive in their increasingly uncertain business environments. Design Thinking, an innovation approach based on human-centered exploration, ideation and experimentation, has gained increasing popularity. The market for Design Thinking, including software products and general services, is projected to reach 2.500 million $ (US-Dollar) by 2028. A dispersed set of positive outcomes have been attributed to Design Thinking. However, there is no clear understanding of what exactly comprises the impact of Design Thinking and how it is created. To support a billion-dollar market, it is essential to understand the value Design Thinking is bringing to organizations not only to justify large investments, but to continuously improve the approach and its application.
Following a qualitative research approach combined with results from a systematic literature review, the results presented in this dissertation offer a structured understanding of Design Thinking impact. The results are structured along two main perspectives of impact: the individual and the organizational perspective. First, insights from qualitative data analysis demonstrate that measuring and assessing the impact of Design Thinking is currently one central challenge for Design Thinking practitioners in organizations. Second, the interview data revealed several effects Design Thinking has on individuals, demonstrating how Design Thinking can impact boundary management behaviors and enable employees to craft their jobs more actively.
Contributing to innovation management research, the work presented in this dissertation systematically explains the Design Thinking impact, allowing other researchers to both locate and integrate their work better. The results of this research advance the theoretical rigor of Design Thinking impact research, offering multiple theoretical underpinnings explaining the variety of Design Thinking impact. Furthermore, this dissertation contains three specific propositions on how Design Thinking creates an impact: Design Thinking creates an impact through integration, enablement, and engagement. Integration refers to how Design Thinking enables organizations through effectively combining things, such as for example fostering balance between exploitation and exploration activities. Through Engagement, Design Thinking impacts organizations involving users and other relevant stakeholders in their work. Moreover, Design Thinking creates impact through Enablement, making it possible for individuals to enact a specific behavior or experience certain states.
By synthesizing multiple theoretical streams into these three overarching themes, the results of this research can help bridge disciplinary boundaries, for example between business, psychology and design, and enhance future collaborative research. Practitioners benefit from the results as multiple desirable outcomes are detailed in this thesis, such as successful individual job crafting behaviors, which can be expected from practicing Design Thinking. This allows practitioners to enact more evidence-based decision-making concerning Design Thinking implementation. Overall, considering multiple levels of impact as well as a broad range of theoretical underpinnings are paramount to understanding and fostering Design Thinking impact.
Plate tectonic boundaries constitute the suture zones between tectonic plates. They are shaped by a variety of distinct and interrelated processes and play a key role in geohazards and georesource formation. Many of these processes have been previously studied, while many others remain unaddressed or undiscovered. In this work, the geodynamic numerical modeling software ASPECT is applied to shed light on further process interactions at continental plate boundaries. In contrast to natural data, geodynamic modeling has the advantage that processes can be directly quantified and that all parameters can be analyzed over the entire evolution of a structure. Furthermore, processes and interactions can be singled out from complex settings because the modeler has full control over all of the parameters involved. To account for the simplifying character of models in general, I have chosen to study generic geological settings with a focus on the processes and interactions rather than precisely reconstructing a specific region of the Earth.
In Chapter 2, 2D models of continental rifts with different crustal thicknesses between 20 and 50 km and extension velocities in the range of 0.5-10 mm/yr are used to obtain a speed limit for the thermal steady-state assumption, commonly employed to address the temperature fields of continental rifts worldwide. Because the tectonic deformation from ongoing rifting outpaces heat conduction, the temperature field is not in equilibrium, but is characterized by a transient, tectonically-induced heat flow signal. As a result, I find that isotherm depths of the geodynamic evolution models are shallower than a temperature distribution in equilibrium would suggest. This is particularly important for deep isotherms and narrow rifts. In narrow rifts, the magnitude of the transient temperature signal limits a well-founded applicability of the thermal steady-state assumption to extension velocities of 0.5-2 mm/yr. Estimation of the crustal temperature field affects conclusions on all temperature-dependent processes ranging from mineral assemblages to the feasible exploitation of a geothermal reservoir.
In Chapter 3, I model the interactions of different rheologies with the kinematics of folding and faulting using the example of fault-propagation folds in the Andean fold-and-thrust belt. The evolution of the velocity fields from geodynamic models are compared with those from trishear models of the same structure. While the latter use only geometric and kinematic constraints of the main fault, the geodynamic models capture viscous, plastic, and elastic deformation in the entire model domain. I find that both models work equally well for early, and thus relatively simple stages of folding and faulting, while results differ for more complex situations where off-fault deformation and secondary faulting are present. As fault-propagation folds can play an important role in the formation of reservoirs, knowledge of fluid pathways, for example via fractures and faults, is crucial for their characterization.
Chapter 4 deals with a bending transform fault and the interconnections between tectonics and surface processes. In particular, the tectonic evolution of the Dead Sea Fault is addressed where a releasing bend forms the Dead Sea pull-apart basin, while a restraining bend further to the North resulted in the formation of the Lebanese mountains. I ran 3D coupled geodynamic and surface evolution models that included both types of bends in a single setup. I tested various randomized initial strain distributions, showing that basin asymmetry is a consequence of strain localization. Furthermore, by varying the surface process efficiency, I find that the deposition of sediment in the pull-apart basin not only controls basin depth, but also results in a crustal flow component that increases uplift at the restraining bend.
Finally, in Chapter 5, I present the computational basis for adding further complexity to plate boundary models in ASPECT with the implementation of earthquake-like behavior using the rate-and-state friction framework. Despite earthquakes happening on a relatively small time scale, there are many interactions between the seismic cycle and the long time spans of other geodynamic processes. Amongst others, the crustal state of stress as well as the presence of fluids or changes in temperature may alter the frictional behavior of a fault segment. My work provides the basis for a realistic setup of involved structures and processes, which is therefore important to obtain a meaningful estimate for earthquake hazards.
While these findings improve our understanding of continental plate boundaries, further development of geodynamic software may help to reveal even more processes and interactions in the future.