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Institute
- Institut für Biochemie und Biologie (49)
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- Hasso-Plattner-Institut für Digital Engineering GmbH (30)
- Institut für Physik und Astronomie (30)
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Studies from several countries suggest that COVID-19 vaccination rates are lower among migrants compared to the general population. Urgent calls have been made to improve vaccine outreach to migrants, however, there is limited evidence on effective approaches, especially using social media. We assessed a targeted, low-cost, Facebook campaign disseminating COVID-19 vaccine information among Arabic, Turkish and Russian speakers in Germany (N = 888,994). As part of the campaign, we conducted two randomized, online experiments to assess the impact of the advertisement (1) language and (2) depicted messenger (government authority, religious leader, doctor or family). Key outcomes included reach, click-through rates, conversion rates and cost-effectiveness. Within 29 days, the campaign reached 890 thousand Facebook users. On average, 2.3 individuals accessed the advertised COVID-19 vaccination appointment tool for every euro spent on the campaign. Migrants were 2.4 (Arabic), 1.8 (Russian) and 1.2 (Turkish) times more likely to click on advertisements translated to their native language compared to German-language advertisements. Furthermore, findings showed that government representatives can be more successful in engaging migrants online compared to other messengers, despite common claims of lower trust in government institutions among migrants. This study highlights the potential of tailored, and translated, vaccination campaigns on social media for reaching migrants who may be left out by traditional media campaigns.
Polyglot programming allows developers to use multiple programming languages within the same software project. While it is common to use more than one language in certain programming domains, developers also apply polyglot programming for other purposes such as to re-use software written in other languages. Although established approaches to polyglot programming come with significant limitations, for example, in terms of performance and tool support, developers still use them to be able to combine languages.
Polyglot virtual machines (VMs) such as GraalVM provide a new level of polyglot programming, allowing languages to directly interact with each other. This reduces the amount of glue code needed to combine languages, results in better performance, and enables tools such as debuggers to work across languages. However, only a little research has focused on novel tools that are designed to support developers in building software with polyglot VMs. One reason is that tool-building is often an expensive activity, another one is that polyglot VMs are still a moving target as their use cases and requirements are not yet well understood.
In this thesis, we present an approach that builds on existing self-sustaining programming systems such as Squeak/Smalltalk to enable exploratory programming, a practice for exploring and gathering software requirements, and re-use their extensive tool-building capabilities in the context of polyglot VMs. Based on TruffleSqueak, our implementation for the GraalVM, we further present five case studies that demonstrate how our approach helps tool developers to design and build tools for polyglot programming. We further show that TruffleSqueak can also be used by application developers to build and evolve polyglot applications at run-time and by language and runtime developers to understand the dynamic behavior of GraalVM languages and internals. Since our platform allows all these developers to apply polyglot programming, it can further help to better understand the advantages, use cases, requirements, and challenges of polyglot VMs. Moreover, we demonstrate that our approach can also be applied to other polyglot VMs and that insights gained through it are transferable to other programming systems.
We conclude that our research on tools for polyglot programming is an important step toward making polyglot VMs more approachable for developers in practice. With good tool support, we believe polyglot VMs can make it much more common for developers to take advantage of multiple languages and their ecosystems when building software.
Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.
The estimation of financial losses is an integral part of flood risk assessment. The application of existing flood loss models on locations or events different from the ones used to train the models has led to low performance, showing that characteristics of the flood damaging process have not been sufficiently well represented yet. To improve flood loss model transferability, I explore various model structures aiming at incorporating different (inland water) flood types and pathways. That is based on a large survey dataset of approximately 6000 flood-affected households which addresses several aspects of the flood event, not only the hazard characteristics but also information on the affected building, socioeconomic factors, the household's preparedness level, early warning, and impacts. Moreover, the dataset reports the coincidence of different flood pathways. Whilst flood types are a classification of flood events reflecting their generating process (e.g. fluvial, pluvial), flood pathways represent the route the water takes to reach the receptors (e.g. buildings). In this work, the following flood pathways are considered: levee breaches, river floods, surface water floods, and groundwater floods.
The coincidence of several hazard processes at the same time and place characterises a compound event. In fact, many flood events develop through several pathways, such as the ones addressed in the survey dataset used. Earlier loss models, although developed with one or multiple predictor variables, commonly use loss data from a single flood event which is attributed to a single flood type, disregarding specific flood pathways or the coincidence of multiple pathways. This gap is addressed by this thesis through the following research questions: 1. In which aspects do flood pathways of the same (compound inland) flood event differ? 2. How much do factors which contribute to the overall flood loss in a building differ in various settings, specifically across different flood pathways? 3. How well can Bayesian loss models learn from different settings? 4. Do compound, that is, coinciding flood pathways result in higher losses than a single pathway, and what does the outcome imply for future loss modelling?
Statistical analysis has found that households affected by different flood pathways also show, in general, differing characteristics of the affected building, preparedness, and early warning, besides the hazard characteristics. Forecasting and early warning capabilities and the preparedness of the population are dominated by the general flood type, but characteristics of the hazard at the object-level, the impacts, and the recovery are more related to specific flood pathways, indicating that risk communication and loss models could benefit from the inclusion of flood-pathway-specific information.
For the development of the loss model, several potentially relevant predictors are analysed: water depth, duration, velocity, contamination, early warning lead time, perceived knowledge about self-protection, warning information, warning source, gap between warning and action, emergency measures, implementation of property-level precautionary measures (PLPMs), perceived efficacy of PLPMs, previous flood experience, awareness of flood risk, ownership, building type, number of flats, building quality, building value, house/flat area, building area, cellar, age, household size, number of children, number of elderly residents, income class, socioeconomic status, and insurance against floods. After a variable selection, descriptors of the hazard, building, and preparedness were deemed significant, namely: water depth, contamination, duration, velocity, building area, building quality, cellar, PLPMs, perceived efficacy of PLPMs, emergency measures, insurance, and previous flood experience. The inclusion of the indicators of preparedness is relevant, as they are rarely involved in loss datasets and in loss modelling, although previous studies have shown their potential in reducing losses. In addition, the linear model fit indicates that the explanatory factors are, in several cases, differently relevant across flood pathways.
Next, Bayesian multilevel models were trained, which intrinsically incorporate uncertainties and allow for partial pooling (i.e. different groups of data, such as households affected by different flood pathways, can learn from each other), increasing the statistical power of the model. A new variable selection was performed for this new model approach, reducing the number of predictors from twelve to seven variables but keeping factors of the hazard, building, and preparedness, namely: water depth, contamination, duration, building area, PLPMs, insurance, and previous flood experience. The new model was trained not only across flood pathways but also across regions of Germany, divided according to general socioeconomic factors and insurance policies, and across flood events. The distinction across regions and flood events did not improve loss modelling and led to a large overlap of regression coefficients, with no clear trend or pattern. The distinction of flood pathways showed credibly distinct regression coefficients, leading to a better understanding of flood loss modelling and indicating one potential reason why model transferability has been challenging.
Finally, new model structures were trained to include the possibility of compound inland floods (i.e. when multiple flood pathways coincide on the same affected asset). The dataset does not allow for verifying in which sequence the flood pathway waves occurred and predictor variables reflect only their mixed or combined outcome. Thus, two Bayesian models were trained: 1. a multi-membership model, a structure which learns the regression coefficients for multiple flood pathways at the same time, and 2. a multilevel model wherein the combination of coinciding flood pathways makes individual categories. The multi-membership model resulted in credibly different coefficients across flood pathways but did not improve model performance in comparison to the model assuming only a single dominant flood pathway. The model with combined categories signals an increase in impacts after compound floods, but due to the uncertainty in model coefficients and estimates, it is not possible to ascertain such an increase as credible. That is, with the current level of uncertainty in differentiating the flood pathways, the loss estimates are not credibly distinct from individual flood pathways.
To overcome the challenges faced, non-linear or mixed models could be explored in the future. Interactions, moderation, and mediation effects, as well as non-linear effects, should also be further studied. Loss data collection should regularly include preparedness indicators, and either data collection or hydraulic modelling should focus on the distinction of coinciding flood pathways, which could inform loss models and further improve estimates. Flood pathways show distinct (financial) impacts, and their inclusion in loss modelling proves relevant, for it helps in clarifying the different contribution of influencing factors to the final loss, improving understanding of the damaging process, and indicating future lines of research.
Extending synchrotron X-ray refraction techniques to the quantitative analysis of metallic materials
(2022)
In this work, two X-ray refraction based imaging methods, namely, synchrotron X-ray refraction radiography (SXRR) and synchrotron X-ray refraction computed tomography (SXRCT), are applied to analyze quantitatively cracks and porosity in metallic materials. SXRR and SXRCT make use of the refraction of X-rays at inner surfaces of the material, e.g., the surfaces of cracks and pores, for image contrast. Both methods are, therefore, sensitive to smaller defects than their absorption based counterparts X-ray radiography and computed tomography. They can detect defects of nanometric size. So far the methods have been applied to the analysis of ceramic materials and fiber reinforced plastics. The analysis of metallic materials requires higher photon energies to achieve sufficient X-ray transmission due to their higher density. This causes smaller refraction angles and, thus, lower image contrast because the refraction index depends on the photon energy. Here, for the first time, a conclusive study is presented exploring the possibility to apply SXRR and SXRCT to metallic materials. It is shown that both methods can be optimized to overcome the reduced contrast due to smaller refraction angles. Hence, the only remaining limitation is the achievable X-ray transmission which is common to all X-ray imaging methods. Further, a model for the quantitative analysis of the inner surfaces is presented and verified.
For this purpose four case studies are conducted each posing a specific challenge to the imaging task. Case study A investigates cracks in a coupon taken from an aluminum weld seam. This case study primarily serves to verify the model for quantitative analysis and prove the sensitivity to sub-resolution features. In case study B, the damage evolution in an aluminum-based particle reinforced metal-matrix composite is analyzed. Here, the accuracy and repeatability of subsequent SXRR measurements is investigated showing that measurement errors of less than 3 % can be achieved. Further, case study B marks the fist application of SXRR in combination with in-situ tensile loading. Case study C is out of the highly topical field of additive manufacturing. Here, porosity in additively manufactured Ti-Al6-V4 is analyzed with a special interest in the pore morphology. A classification scheme based on SXRR measurements is devised which allows to distinguish binding defects from keyhole pores even if the defects cannot be spatially resolved. In case study D, SXRCT is applied to the analysis of hydrogen assisted cracking in steel. Due to the high X-ray attenuation of steel a comparatively high photonenergy of 50 keV is required here. This causes increased noise and lower contrast in the data compared to the other case studies. However, despite the lower data quality a quantitative analysis of the occurance of cracks in dependence of hydrogen content and applied mechanical load is possible.
OBJECTIVE: For an effective control of the SARS-CoV-2 pandemic with vaccines, most people in a population need to be vaccinated. It is thus important to know how to inform the public with reference to individual preferences–while also acknowledging the societal preference to encourage vaccinations. According to the health care standard of informed decision-making, a comparison of the benefits and harms of (not) having the vaccination would be required to inform undecided and skeptical people. To test evidence-based fact boxes, an established risk communication format, and to inform their development, we investigated their contribution to knowledge and evaluations of COVID-19 vaccines.
METHODS: We conducted four studies (1, 2, and 4 were population-wide surveys with N = 1,942 to N = 6,056): Study 1 assessed the relationship between vaccination knowledge and intentions in Germany over three months. Study 2 assessed respective information gaps and needs of the population in Germany. In parallel, an experiment (Study 3) with a mixed design (presentation formats; pre-post-comparison) assessed the effect of fact boxes on risk perceptions and fear, using a convenience sample (N = 719). Study 4 examined how effective two fact box formats are for informing vaccination intentions, with a mixed experimental design: between-subjects (presentation formats) and within-subjects (pre-post-comparison).
RESULTS: Study 1 showed that vaccination knowledge and vaccination intentions increased between November 2020 and February 2021. Study 2 revealed objective information requirements and subjective information needs. Study 3 showed that the fact box format is effective in adjusting risk perceptions concerning COVID-19. Based on those results, fact boxes were revised and implemented with the help of a national health authority in Germany. Study 4 showed that simple fact boxes increase vaccination knowledge and positive evaluations in skeptics and undecideds.
CONCLUSION: Fact boxes can inform COVID-19 vaccination intentions of undecided and skeptical people without threatening societal vaccination goals of the population.
Muscle quality defined as the ratio of muscle strength to muscle mass disregards underlying factors which influence muscle strength. The aim of this review was to investigate the relationship of phase angle (PhA), echo intensity (EI), muscular adipose tissue (MAT), muscle fiber type, fascicle pennation angle (θf), fascicle length (lf), muscle oxidative capacity, insulin sensitivity (IS), neuromuscular activation, and motor unit to muscle strength. PubMed search was performed in 2021. The inclusion criteria were: (i) original research, (ii) human participants, (iii) adults (≥18 years). Exclusion criteria were: (i) no full-text, (ii) non-English or -German language, (iii) pathologies. Forty-one studies were identified. Nine studies found a weak–moderate negative (range r: [−0.26]–[−0.656], p < 0.05) correlation between muscle strength and EI. Four studies found a weak–moderate positive correlation (range r: 0.177–0.696, p < 0.05) between muscle strength and PhA. Two studies found a moderate-strong negative correlation (range r: [−0.446]–[−0.87], p < 0.05) between muscle strength and MAT. Two studies found a weak-strong positive correlation (range r: 0.28–0.907, p < 0.05) between θf and muscle strength. Muscle oxidative capacity was found to be a predictor of muscle strength. This review highlights that the current definition of muscle quality should be expanded upon as to encompass all possible factors of muscle quality.
Language developers who design domain-specific languages or new language features need a way to make fast changes to language definitions. Those fast changes require immediate feedback. Also, it should be possible to parse the developed languages quickly to handle extensive sets of code.
Parsing expression grammars provides an easy to understand method for language definitions. Packrat parsing is a method to parse grammars of this kind, but this method is unable to handle left-recursion properly. Existing solutions either partially rewrite left-recursive rules and partly forbid them, or use complex extensions to packrat parsing that are hard to understand and cost-intensive. We investigated methods to make parsing as fast as possible, using easy to follow algorithms while not losing the ability to make fast changes to grammars.
We focused our efforts on two approaches.
One is to start from an existing technique for limited left-recursion rewriting and enhance it to work for general left-recursive grammars. The second approach is to design a grammar compilation process to find left-recursion before parsing, and in this way, reduce computational costs wherever possible and generate ready to use parser classes.
Rewriting parsing expression grammars is a task that, if done in a general way, unveils a large number of cases such that any rewriting algorithm surpasses the complexity of other left-recursive parsing algorithms. Lookahead operators introduce this complexity. However, most languages have only little portions that are left-recursive and in virtually all cases, have no indirect or hidden left-recursion. This means that the distinction of left-recursive parts of grammars from components that are non-left-recursive holds great improvement potential for existing parsers.
In this report, we list all the required steps for grammar rewriting to handle left-recursion, including grammar analysis, grammar rewriting itself, and syntax tree restructuring. Also, we describe the implementation of a parsing expression grammar framework in Squeak/Smalltalk and the possible interactions with the already existing parser Ohm/S. We quantitatively benchmarked this framework directing our focus on parsing time and the ability to use it in a live programming context. Compared with Ohm, we achieved massive parsing time improvements while preserving the ability to use our parser it as a live programming tool.
The work is essential because, for one, we outlined the difficulties and complexity that come with grammar rewriting. Also, we removed the existing limitations that came with left-recursion by eliminating them before parsing.
We consider a one-dimensional oscillatory medium with a coupling through a diffusive linear field. In the limit of fast diffusion this setup reduces to the classical Kuramoto–Battogtokh model. We demonstrate that for a finite diffusion stable chimera solitons, namely localized synchronous domain in an infinite asynchronous environment, are possible. The solitons are stable also for finite density of oscillators, but in this case they sway with a nearly constant speed. This finite-density-induced motility disappears in the continuum limit, as the velocity of the solitons is inverse proportional to the density. A long-wave instability of the homogeneous asynchronous state causes soliton turbulence, which appears as a sequence of soliton mergings and creations. As the instability of the asynchronous state becomes stronger, this turbulence develops into a spatio-temporal intermittency.
Fitness, risk taking, and spatial behavior covary with boldness in experimental vole populations
(2022)
Individuals of a population may vary along a pace-of-life syndrome from highly fecund, short-lived, bold, dispersive “fast” types at one end of the spectrum to less fecund, long-lived, shy, plastic “slow” types at the other end. Risk-taking behavior might mediate the underlying life history trade-off, but empirical evidence supporting this hypothesis is still ambiguous. Using experimentally created populations of common voles (Microtus arvalis)—a species with distinct seasonal life history trajectories—we aimed to test whether individual differences in boldness behavior covary with risk taking, space use, and fitness. We quantified risk taking, space use (via automated tracking), survival, and reproductive success (via genetic parentage analysis) in 8 to 14 experimental, mixed-sex populations of 113 common voles of known boldness type in large grassland enclosures over a significant part of their adult life span and two reproductive events. Populations were assorted to contain extreme boldness types (bold or shy) of both sexes. Bolder individuals took more risks than shyer ones, which did not affect survival. Bolder males but not females produced more offspring than shy conspecifics. Daily home range and core area sizes, based on 95% and 50% Kernel density estimates (20 ± 10 per individual, n = 54 individuals), were highly repeatable over time. Individual space use unfolded differently for sex-boldness type combinations over the course of the experiment. While day ranges decreased for shy females, they increased for bold females and all males. Space use trajectories may, hence, indicate differences in coping styles when confronted with a novel social and physical environment. Thus, interindividual differences in boldness predict risk taking under near-natural conditions and have consequences for fitness in males, which have a higher reproductive potential than females. Given extreme inter- and intra-annual fluctuations in population density in the study species and its short life span, density-dependent fluctuating selection operating differently on the sexes might maintain (co)variation in boldness, risk taking, and pace-of-life.
Following excited-state chemical shifts in molecular ultrafast x-ray photoelectron spectroscopy
(2022)
The conversion of photon energy into other energetic forms in molecules is accompanied by charge moving on ultrafast timescales. We directly observe the charge motion at a specific site in an electronically excited molecule using time-resolved x-ray photoelectron spectroscopy (TR-XPS). We extend the concept of static chemical shift from conventional XPS by the excited-state chemical shift (ESCS), which is connected to the charge in the framework of a potential model. This allows us to invert TR-XPS spectra to the dynamic charge at a specific atom. We demonstrate the power of TR-XPS by using sulphur 2p-core-electron-emission probing to study the UV-excited dynamics of 2-thiouracil. The method allows us to discover that a major part of the population relaxes to the molecular ground state within 220–250 fs. In addition, a 250-fs oscillation, visible in the kinetic energy of the TR-XPS, reveals a coherent exchange of population among electronic states.
Perceived predation risk varies in space and time. Foraging in this landscape of fear alters forager-resource interactions via cascading nonconsumptive effects. Estimating these indirect effects is difficult in natural systems. Here, we applied a novel measure to quantify the diversity at giving-up density that allows to test how spatial variation in perceived predation risk modifies the diversity of multispecies resources at local and regional spatial levels. Furthermore, we evaluated whether the nonconsumptive effects on resource species diversity can be explained by the preferences of foragers for specific functional traits and by the forager species richness. We exposed rodents of a natural community to artificial food patches, each containing an initial multispecies resource community of eight species (10 items each) mixed in sand. We sampled 35 landscapes, each containing seven patches in a spatial array, to disentangle effects at local (patch) and landscape levels. We used vegetation height as a proxy for perceived predation risk. After a period of three nights, we counted how many and which resource species were left in each patch to measure giving-up density and resource diversity at the local level (alpha diversity) and the regional level (gamma diversity and beta diversity). Furthermore, we used wildlife cameras to identify foragers and assess their species richness. With increasing vegetation height, i.e., decreasing perceived predation risk, giving-up density, and local alpha and regional gamma diversity decreased, and patches became less similar within a landscape (beta diversity increased). Foragers consumed more of the bigger and most caloric resources. The higher the forager species richness, the lower the giving-up density, and alpha and gamma diversity. Overall, spatial variation of perceived predation risk of foragers had measurable cascading effects on local and regional resource species biodiversity, independent of the forager species. Thus, nonconsumptive predation effects modify forager-resource interactions and might act as an equalizing mechanism for species coexistence.
We demonstrate how the incentives of firms that partially own their suppliers or customers to foreclose rivals depend on how the partial owner can extract profits from the target (tunneling). Compared to a fully vertically integrated firm, a partial owner may obtain only a share of the target’s profit but influence the target’s strategy significantly. We show that the incentives for customer and input foreclosure can be higher, equal, or even lower with partial ownership than with a vertical merger, depending on how the protection of minority shareholders and transfer price regulations affect the scope for profit extraction.
Distances affect economic decision-making in numerous situations. The time at which we make a decision about future consumption has an impact on our consumption behavior. The spatial distance to employer, school or university impacts the place where we live and vice versa. The emotional closeness to other individuals influences our willingness to give money to them. This cumulative thesis aims to enrich the literature on the role of distance for economic decision-making. Thereby, each of my research projects sheds light on the impact of one kind of distance for efficient decision-making.
In plant cells, subcellular transport of cargo proteins relies to a large extent on post-Golgi transport pathways, many of which are mediated by clathrin-coated vesicles (CCVs). Vesicle formation is facilitated by different factors like accessory proteins and adaptor protein complexes (APs), the latter serving as a bridge between cargo proteins and the coat protein clathrin. One type of accessory proteins is defined by a conserved EPSIN N-TERMINAL HOMOLOGY (ENTH) domain and interacts with APs and clathrin via motifs in the C-terminal part. In Arabidopsis thaliana, there are three closely related ENTH domain proteins (EPSIN1, 2 and 3) and one highly conserved but phylogenetically distant outlier, termed MODIFIED TRANSPORT TO THE VACUOLE1 (MTV1). In case of the trans-Golgi network (TGN) located MTV1, clathrin association and a role in vacuolar transport have been shown previously (Sauer et al. 2013). In contrast, for EPSIN1 and EPSIN2 limited functional and localization data were available; and EPSIN3 remained completely uncharacterized prior to this study (Song et al. 2006; Lee et al. 2007). The molecular details of ENTH domain proteins in plants are still unknown. In order to systematically characterize all four ENTH proteins in planta, we first investigated expression and subcellular localization by analysis of stable reporter lines under their endogenous promotors. Although all four genes are ubiquitously expressed, their subcellular distribution differs markedly. EPSIN1 and MTV1 are located at the TGN, whereas EPSIN2 and EPSIN3 are associated with the plasma membrane (PM) and the cell plate. To examine potential functional redundancy, we isolated knockout T-DNA mutant lines and created all higher order mutant combinations. The clearest evidence for functional redundancy was observed in the epsin1 mtv1 double mutant, which is a dwarf displaying overall growth reduction. These findings are in line with the TGN localization of both MTV1 and EPS1. In contrast, loss of EPSIN2 and EPSIN3 does not result in a growth phenotype compared to wild type, however, a triple knockout of EPSIN1, EPSIN2 and EPSIN3 shows partially sterile plants. We focused mainly on the epsin1 mtv1 double mutant and addressed the functional role of these two genes in clathrin-mediated vesicle transport by comprehensive molecular, biochemical, and genetic analyses. Our results demonstrate that EPSIN1 and MTV1 promote vacuolar transport and secretion of a subset of cargo. However, they do not seem to be involved in endocytosis and recycling. Importantly, employing high-resolution imaging, genetic and biochemical experiments probing the relationship of the AP complexes, we found that EPSIN1/AP1 and MTV1/AP4 define two spatially and molecularly distinct subdomains of the TGN. The AP4 complex is essential for MTV1 recruitment to the TGN, whereas EPSIN1 is independent of AP4 but presumably acts in an AP1-dependent framework. Our findings suggest that this ENTH/AP pairing preference is conserved between animals and plants.
Functional traits determine biomass dynamics, coexistence and energetics in plankton food webs
(2022)
Plankton food webs are the basis of marine and limnetic ecosystems. Especially aquatic ecosystems of high biodiversity provide important ecosystem services for humankind as providers of food, coastal protection, climate regulation, and tourism. Understanding the dynamics of biomass and coexistence in these food webs is a first step to understanding the ecosystems. It also lays the foundation for the development of management strategies for the maintenance of the marine and freshwater biodiversity despite anthropogenic influences.
Natural food webs are highly complex, and thus often equally complex methods are needed to analyse and understand them well. Models can help to do so as they depict simplified parts of reality. In the attempt to get a broader understanding of the complex food webs, diverse methods are used to investigate different questions.
In my first project, we compared the energetics of a food chain in two versions of an allometric trophic network model. In particular, we solved the problem of unrealistically high trophic transfer efficiencies (up to 70%) by accounting for both basal respiration and activity respiration, which decreased the trophic transfer efficiency to realistic values of ≤30%. Next in my second project I turned to plankton food webs and especially phytoplankton traits. Investigating a long-term data set from Lake Constance we found evidence for a trade-off between defence and growth rate in this natural phytoplankton community. I continued working with this data set in my third project focusing on ciliates, the main grazer of phytoplankton in spring. Boosted regression trees revealed that temperature and predators have the highest influence on net growth rates of ciliates. We finally investigated in my fourth project a food web model inspired by ciliates to explore the coexistence of plastic competitors and to study the new concept of maladaptive switching, which revealed some drawbacks of plasticity: faster adaptation led to higher maladaptive switching towards undefended phenotypes which reduced autotroph biomass and coexistence and increased consumer biomass.
It became obvious that even well-established models should be critically questioned as it is important not to forget reality on the way to a simplistic model. The results showed furthermore that long-term data sets are necessary as they can help to disentangle complex natural processes. Last, one should keep in mind that the interplay between models and experiments/ field data can deliver fruitful insights about our complex world.
Findings in the extant literature are mixed concerning when and how gender diversity benefits team performance. We develop and test a model that posits that gender-diverse teams outperform gender-homogeneous teams when perceived time pressure is low, whereas the opposite is the case when perceived time pressure is high. Drawing on the categorization-elaboration model (CEM; van Knippenberg, De Dreu, & Homan, 2004), we begin with the assumption that information elaboration is the process whereby gender diversity fosters positive effects on team performance. However, also in line with the CEM, we argue that this process can be disrupted by adverse team dynamics. Specifically, we argue that as time pressure increases, higher gender diversity leads to more team withdrawal, which, in turn, moderates the positive indirect effect of gender diversity on team performance via information elaboration such that this effect becomes weaker as team withdrawal increases. In an experimental study of 142 four-person teams, we found support for this model that explains why perceived time pressure affects the performance of gender-diverse teams more negatively than that of gender-homogeneous teams. Our study sheds new light on when and how gender diversity can become either an asset or a liability for team performance.
Salt deposits offer a variety of usage types. These include the mining of rock salt and potash salt as important raw materials, the storage of energy in man-made underground caverns, and the disposal of hazardous substances in former mines. The most serious risk with any of these usage types comes from the contact with groundwater or surface water. It causes an uncontrolled dissolution of salt rock, which in the worst case can result in the flooding or collapse of underground facilities. Especially along potash seams, cavernous structures can spread quickly, because potash salts show a much higher solubility than rock salt. However, as their chemical behavior is quite complex, previous models do not account for these highly soluble interlayers. Therefore, the objective of the present thesis is to describe the evolution of cavernous structures along potash seams in space and time in order to improve hazard mitigation during the utilization of salt deposits.
The formation of cavernous structures represents an interplay of chemical and hydraulic processes. Hence, the first step is to systematically investigate the dissolution and precipitation reactions that occur when water and potash salt come into contact. For this purpose, a geochemical reaction model is used. The results show that the minerals are only partially dissolved, resulting in a porous sponge like structure. With the saturation of the solution increasing, various secondary minerals are formed, whose number and type depend on the original rock composition. Field data confirm a correlation between the degree of saturation and the distance from the center of the cavern, where solution is entering. Subsequently, the reaction model is coupled with a flow and transport code and supplemented by a novel approach called ‘interchange’. The latter enables the exchange of solution and rock between areas of different porosity and mineralogy, and thus ultimately the growth of the cavernous structure. By means of several scenario analyses, cavern shape, growth rate and mineralogy are systematically investigated, taking also heterogeneous potash seams into account. The results show that basically four different cases can be distinguished, with mixed forms being a frequent occurrence in nature. The classification scheme is based on the dimensionless numbers Péclet and Damköhler, and allows for a first assessment of the hazard potential. In future, the model can be applied to any field case, using measurement data for calibration.
The presented research work provides a reactive transport model that is able to spatially and temporally characterize the propagation of cavernous structures along potash seams for the first time. Furthermore, it allows to determine thickness and composition of transition zones between cavern center and unaffected salt rock. The latter is particularly important in potash mining, so that natural cavernous structures can be located at an early stage and the risk of mine flooding can thus be reduced. The models may also contribute to an improved hazard prevention in the construction of storage caverns and the disposal of hazardous waste in salt deposits. Predictions regarding the characteristics and evolution of cavernous structures enable a better assessment of potential hazards, such as integrity or stability loss, as well as of suitable mitigation measures.
The Permo-Triassic period marks the time interval between Hercynian (Variscan) orogenic events in the Tien Shan and the North Pamir, and the Cimmerian accretion of the Gondwana-derived Central and South Pamir to the southern margin of the Paleo-Asian continent. A well-preserved Permo-Triassic volcano-sedimentary sequence from the Chinese North Pamir yields important information on the geodynamic evolution of Asia’s pre-Cimmerian southern margin. The oldest volcanic rocks from that section are dated to the late Guadalupian epoch by a rhyolite and a dacitic dike that gave zircon U-Pb ages of ~260 Ma. Permian volcanism was largely pyroclastic and mafic to intermediate. Upsection, a massive ignimbritic crystal tuff in the Chinese Qimgan valley was dated to 244.1 +/- 1.1 Ma, a similar unit in the nearby Gez valley to 245 +/- 11 Ma, and an associated rhyolite to 233.4 +/- 1.1 Ma. Deposition of the locally ~200 m thick crystal tuff unit follows an unconformity and marks the onset of intense, mainly mafic to intermediate, calc-alkaline magmatic activity. Triassic volcanic activity in the North Pamir was coeval with the major phase of Cimmerian intrusive activity in the Karakul-Mazar arc-accretionary complex to the south, caused by northward subduction of the Paleo-Tethys. It also coincided with the emplacement of basanitic and carbonatitic dikes and a thermal event in the South Tien Shan, to the north of our study area. Evidence for arc-related magmatic activity in a back-arc position provides strong arguments for back-arc extension or transtension and basin formation. This puts the Qimgan succession in line with a more than 1000 km long realm of extensional Triassic back-arc basins known from the North Pamir in the Kyrgyz Altyn Darya valley (Myntekin formation), the North Pamir of Tajikistan and Afghanistan, and the Afghan Hindukush (Doab formation) and further west from the Paropamisus and Kopet Dag (Aghdarband, NE Iran).
Global heat adaptation among urban populations and its evolution under different climate futures
(2022)
Heat and increasing ambient temperatures under climate change represent a serious threat to human health in cities. Heat exposure has been studied extensively at a global scale. Studies comparing a defined temperature threshold with the future daytime temperature during a certain period of time, had concluded an increase in threat to human health. Such findings however do not explicitly account for possible changes in future human heat adaptation and might even overestimate heat exposure. Thus, heat adaptation and its development is still unclear. Human heat adaptation refers to the local temperature to which populations are adjusted to. It can be inferred from the lowest point of the U- or V-shaped heat-mortality relationship (HMR), the Minimum Mortality Temperature (MMT). While epidemiological studies inform on the MMT at the city scale for case studies, a general model applicable at the global scale to infer on temporal change in MMTs had not yet been realised. The conventional approach depends on data availability, their robustness, and on the access to daily mortality records at the city scale. Thorough analysis however must account for future changes in the MMT as heat adaptation happens partially passively. Human heat adaptation consists of two aspects: (1) the intensity of the heat hazard that is still tolerated by human populations, meaning the heat burden they can bear and (2) the wealth-induced technological, social and behavioural measures that can be employed to avoid heat exposure. The objective of this thesis is to investigate and quantify human heat adaptation among urban populations at a global scale under the current climate and to project future adaptation under climate change until the end of the century. To date, this has not yet been accomplished. The evaluation of global heat adaptation among urban populations and its evolution under climate change comprises three levels of analysis. First, using the example of Germany, the MMT is calculated at the city level by applying the conventional method. Second, this thesis compiles a data pool of 400 urban MMTs to develop and train a new model capable of estimating MMTs on the basis of physical and socio-economic city characteristics using multivariate non-linear multivariate regression. The MMT is successfully described as a function of the current climate, the topography and the socio-economic standard, independently of daily mortality data for cities around the world. The city-specific MMT estimates represents a measure of human heat adaptation among the urban population. In a final third analysis, the model to derive human heat adaptation was adjusted to be driven by projected climate and socio-economic variables for the future. This allowed for estimation of the MMT and its change for 3 820 cities worldwide for different combinations of climate trajectories and socio-economic pathways until 2100. The knowledge on the evolution of heat adaptation in the future is a novelty as mostly heat exposure and its future development had been researched. In this work, changes in heat adaptation and exposure were analysed jointly. A wide range of possible health-related outcomes up to 2100 was the result, of which two scenarios with the highest socio-economic developments but opposing strong warming levels were highlighted for comparison. Strong economic growth based upon fossil fuel exploitation is associated with a high gain in heat adaptation, but may not be able to compensate for the associated negative health effects due to increased heat exposure in 30% to 40% of the cities investigated caused by severe climate change. A slightly less strong, but sustainable growth brings moderate gains in heat adaptation but a lower heat exposure and exposure reductions in 80% to 84% of the cities in terms of frequency (number of days exceeding the MMT) and intensity (magnitude of the MMT exceedance) due to a milder global warming. Choosing a 2 ° C compatible development by 2100 would therefore lower the risk of heat-related mortality at the end of the century. In summary, this thesis makes diverse and multidisciplinary contributions to a deeper understanding of human adaptation to heat under the current and the future climate. It is one of the first studies to carry out a systematic and statistical analysis of urban characteristics which are useful as MMT drivers to establish a generalised model of human heat adaptation, applicable at the global level. A broad range of possible heat-related health options for various future scenarios was shown for the first time. This work is of relevance for the assessment of heat-health impacts in regions where mortality data are not accessible or missing. The results are useful for health care planning at the meso- and macro-level and to urban- and climate change adaptation planning. Lastly, beyond having met the posed objective, this thesis advances research towards a global future impact assessment of heat on human health by providing an alternative method of MMT estimation, that is spatially and temporally flexible in its application.
The importance of carbohydrate structures is enormous due to their ubiquitousness in our lives. The development of so-called glycomaterials is the result of this tremendous significance. These are not exclusively used for research into fundamental biological processes, but also, among other things, as inhibitors of pathogens or as drug delivery systems. This work describes the development of glycomaterials involving the synthesis of glycoderivatives, -monomers and -polymers. Glycosylamines were synthesized as precursors in a single synthesis step under microwave irradiation to significantly shorten the usual reaction time. Derivatization at the anomeric position was carried out according to the methods developed by Kochetkov and Likhorshetov, which do not require the introduction of protecting groups. Aminated saccharide structures formed the basis for the synthesis of glycomonomers in β-configuration by methacrylation. In order to obtain α-Man-based monomers for interactions with certain α-Man-binding lectins, a monomer synthesis by Staudinger ligation was developed in this work, which also does not require protective groups. Modification of the primary hydroxyl group of a saccharide was accomplished by enzyme-catalyzed synthesis. Ribose-containing cytidine was transesterified using the lipase Novozym 435 and microwave irradiation. The resulting monomer synthesis was optimized by varying the reaction partners. To create an amide bond instead of an ester bond, protected cytidine was modified by oxidation followed by amide coupling to form the monomer. This synthetic route was also used to isolate the monomer from its counterpart guanosine. After obtaining the nucleoside-based monomers, they were block copolymerized using the RAFT method. Pre-synthesized pHPMA served as macroCTA to yield cytidine- or guanosine-containing block copolymer. These isolated block copolymers were then investigated for their self-assembly behavior using UV-Vis, DLS and SEM to serve as a potential thermoresponsive drug delivery system.
In recent years digital technologies have become a major means for providing health-related services and this trend was strongly reinforced by the current Coronavirus disease 2019 (COVID-19) pandemic. As it is well-known that regular physical activity has positive effects on individual physical and mental health and thus is an important prerequisite for healthy aging, digital technologies are also increasingly used to promote unstructured and structured forms of physical activity. However, in the course of this development, several terms (e.g., Digital Health, Electronic Health, Mobile Health, Telehealth, Telemedicine, and Telerehabilitation) have been introduced to refer to the application of digital technologies to provide health-related services such as physical interventions. Unfortunately, the above-mentioned terms are often used in several different ways, but also relatively interchangeably. Given that ambiguous terminology is a major source of difficulty in scientific communication which can impede the progress of theoretical and empirical research, this article aims to make the reader aware of the subtle differences between the relevant terms which are applied at the intersection of physical activity and Digital Health and to provide state-of-art definitions for them.
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.
Business incubators hatch start-ups, helping them to survive their early stage and to create a solid foundation for sustainable growth by providing services and access to knowledge. The great practical relevance led to a strong interest of researchers and a high output of scholarly publications, which made the field complex and scattered. To organize the research on incubators and provide a systematic overview of the field, we conducted bibliometric performance analyses and science mappings. The performance analyses depict the temporal development of the number of incubator publications and their citations, the most cited and most productive journals, countries, and authors, and the 20 most cited articles. The author keyword co-occurrence analysis distinguishes six, and the bibliographic coupling seven research themes. Based on a content analysis of the science mappings, we propose a research framework for future research on business incubators.
While estimated numbers of past and future climate migrants are alarming, the growing empirical evidence suggests that the association between adverse climate-related events and migration is not universally positive. This dissertation seeks to advance our understanding of when and how climate migration emerges by analyzing heterogeneous climatic influences on migration in low- and middle-income countries. To this end, it draws on established economic theories of migration, datasets from physical and social sciences, causal inference techniques and approaches from systematic literature review. In three of its five chapters, I estimate causal effects of processes of climate change on inequality and migration in India and Sub-Saharan Africa. By employing interaction terms and by analyzing sub-samples of data, I explore how these relationships differ for various segments of the population. In the remaining two chapters, I present two systematic literature reviews. First, I undertake a comprehensive meta-regression analysis of the econometric climate migration literature to summarize general climate migration patterns and explain the conflicting findings. Second, motivated by the broad range of approaches in the field, I examine the literature from a methodological perspective to provide best practice guidelines for studying climate migration empirically. Overall, the evidence from this dissertation shows that climatic influences on human migration are highly heterogeneous. Whether adverse climate-related impacts materialize in migration depends on the socio-economic characteristics of the individual households, such as wealth, level of education, agricultural dependence or access to adaptation technologies and insurance. For instance, I show that while adverse climatic shocks are generally associated with an increase in migration in rural India, they reduce migration in the agricultural context of Sub-Saharan Africa, where the average wealth levels are much lower so that households largely cannot afford the upfront costs of moving. I find that unlike local climatic shocks which primarily enhance internal migration to cities and hence accelerate urbanization, shocks transmitted via agricultural producer prices increase migration to neighboring countries, likely due to the simultaneous decrease in real income in nearby urban areas. These findings advance our current understanding by showing when and how economic agents respond to climatic events, thus providing explicit contexts and mechanisms of climate change effects on migration in the future. The resulting collection of findings can guide policy interventions to avoid or mitigate any present and future welfare losses from climate change-related migration choices.
Flares are magnetically driven explosions that occur in the atmospheres of all main sequence stars that possess an outer convection zone. Flaring activity is rooted in the magnetic dynamo that operates deep in the stellar interior, propagates through all layers of the atmosphere from the corona to the photosphere, and emits electromagnetic radiation from radio bands to X-ray. Eventually, this radiation, and associated eruptions of energetic particles, are ejected out into interplanetary space, where they impact planetary atmospheres, and dominate the space weather environments of young star-planet systems.
Thanks to the Kepler and the Transit Exoplanet Survey Satellite (TESS) missions, flare observations have become accessible for millions of stars and star-planet systems. The goal of this thesis is to use these flares as multifaceted messengers to understand stellar magnetism across the main sequence, investigate planetary habitability, and explore how close-in planets can affect the host star.
Using space based observations obtained by the Kepler/K2 mission, I found that flaring activity declines with stellar age, but this decline crucially depends on stellar mass and rotation. I calibrated the age of the stars in my sample using their membership in open clusters from zero age main sequence to solar age. This allowed me to reveal the rapid transition from an active, saturated flaring state to a more quiescent, inactive flaring behavior in early M dwarfs at about 600-800 Myr. This result is an important observational constraint on stellar activity evolution that I was able to de-bias using open clusters as an activity-independent age indicator.
The TESS mission quickly superseded Kepler and K2 as the main source of flares in low mass M dwarfs. Using TESS 2-minute cadence light curves, I developed a new technique for flare localization and discovered, against the commonly held belief, that flares do not occur uniformly across their stellar surface: In fast rotating fully convective stars, giant flares are preferably located at high latitudes. This bears implications for both our understanding of magnetic field emergence in these stars, and the impact on the exoplanet atmospheres: A planet that orbits in the equatorial plane of its host may be spared from the destructive effects of these poleward emitting flares.
AU Mic is an early M dwarf, and the most actively flaring planet host detected to date. Its innermost companion, AU Mic b is one of the most promising targets for a first observation of flaring star-planet interactions. In these interactions, the planet influences the star, as opposed to space weather, where the planet is always on the receiving side. The effect reflects the properties of the magnetosphere shared by planet and star, as well as the so far inaccessible magnetic properties of planets. In the about 50 days of TESS monitoring data of AU Mic, I searched for statistically robust signs of flaring interactions with AU Mic b as flares that occur in surplus of the star's intrinsic activity. I found the strongest yet still marginal signal in recurring excess flaring in phase with the orbital period of AU Mic b. If it reflects true signal, I estimate that extending the observing time by a factor of 2-3 will yield a statistically significant detection. Well within the reach of future TESS observations, this additional data may bring us closer to robustly detecting this effect than we have ever been.
This thesis demonstrates the immense scientific value of space based, long baseline flare monitoring, and the versatility of flares as a carrier of information about the magnetism of star-planet systems. Many discoveries still lay in wait in the vast archives that Kepler and TESS have produced over the years. Flares are intense spotlights into the magnetic structures in star-planet systems that are otherwise far below our resolution limits. The ongoing TESS mission, and soon PLATO, will further open the door to in-depth understanding of small and dynamic scale magnetic fields on low mass stars, and the space weather environment they effect.
Objective: A role for microRNAs is implicated in several biological and pathological processes. We investigated the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on molecular markers of diabetic cardiomyopathy in rats.
Methods: Eighteen male Wistar rats (260 ± 10 g; aged 8 weeks) with streptozotocin (STZ)-induced type 1 diabetes mellitus (55 mg/kg, IP) were randomly allocated to three groups: control, MICT, and HIIT. The two different training protocols were performed 5 days each week for 5 weeks. Cardiac performance (end-systolic and end-diastolic dimensions, ejection fraction), the expression of miR-206, HSP60, and markers of apoptosis (cleaved PARP and cytochrome C) were determined at the end of the exercise interventions.
Results: Both exercise interventions (HIIT and MICT) decreased blood glucose levels and improved cardiac performance, with greater changes in the HIIT group (p < 0.001, η2: 0.909). While the expressions of miR-206 and apoptotic markers decreased in both training protocols (p < 0.001, η2: 0.967), HIIT caused greater reductions in apoptotic markers and produced a 20% greater reduction in miR-206 compared with the MICT protocol (p < 0.001). Furthermore, both training protocols enhanced the expression of HSP60 (p < 0.001, η2: 0.976), with a nearly 50% greater increase in the HIIT group compared with MICT.
Conclusions: Our results indicate that both exercise protocols, HIIT and MICT, have the potential to reduce diabetic cardiomyopathy by modifying the expression of miR-206 and its downstream targets of apoptosis. It seems however that HIIT is even more effective than MICT to modulate these molecular markers.
River-valley morphology preserves information on tectonic and climatic conditions that shape landscapes. Observations suggest that river discharge and valley-wall lithology are the main controls on valley width. Yet, current models based on these observations fail to explain the full range of cross-sectional valley shapes in nature, suggesting hitherto unquantified controls on valley width. In particular, current models cannot explain the existence of paired terrace sequences that form under cyclic climate forcing. Paired river terraces are staircases of abandoned floodplains on both valley sides, and hence preserve past valley widths. Their formation requires alternating phases of predominantly river incision and predominantly lateral planation, plus progressive valley narrowing. While cyclic Quaternary climate changes can explain shifts between incision and lateral erosion, the driving mechanism of valley narrowing is unknown. Here, we extract valley geometries from climatically formed, alluvial river-terrace sequences and show that across our dataset, the total cumulative terrace height (here: total valley height) explains 90%–99% of the variance in valley width at the terrace sites. This finding suggests that valley height, or a parameter that scales linearly with valley height, controls valley width in addition to river discharge and lithology. To explain this valley-width-height relationship, we reformulate existing valley-width models and suggest that, when adjusting to new boundary conditions, alluvial valleys evolve to a width at which sediment removal from valley walls matches lateral sediment supply from hillslope erosion. Such a hillslope-channel coupling is not captured in current valley-evolution models. Our model can explain the existence of paired terrace sequences under cyclic climate forcing and relates valley width to measurable field parameters. Therefore, it facilitates the reconstruction of past climatic and tectonic conditions from valley topography.
This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free-form chat communication among firms in a laboratory experiment, we identify typical communication patterns for both explicit cartel formation and indirect attempts to collude tacitly. We document that firms are less likely to communicate explicitly about price fixing and more likely to use indirect messages when sanctioning institutions are present. This effect of sanctions on communication reinforces the direct cartel-deterring effect of sanctions as collusion is more difficult to reach and sustain without an explicit agreement. Indirect messages have no, or even a negative, effect on prices.
Throughout the years 2020 and 2021, schools were temporarily closed to slow the spread of SarsCoV-2. For some periods, children were locked out of sports in schools (physical education lessons, school sports working groups) and organized sports in sports clubs which often resulted in physical inactivity. Did these restrictions affect children’s physical fitness? The EMOTIKON project (www.uni-potsdam.de/emotikon) annually assesses the physical fitness (cardiorespiratory endurance [6-minute-run test], coordination [star-run test], speed [20-m sprint test], lower [standing long jump test] and upper [ball push test] limbs muscle power, and balance [one-legged stance test]) of all third graders in the Federal State of Brandenburg, Germany. Participation is mandatory for all public primary schools. In the falls from 2016 to 2021, 83,476 keyage children (i.e., school enrollment according to the legal key date, between eight and nine years in third grade) from 512 schools were assessed with the EMOTIKON test battery. We tested the Covid pandemic effect on a composite score of the four highly correlated physical fitness tests assessing cardiorespiratory endurance, coordination, speed and powerLOW and on another composite score of the three running tests (cardiorespiratory endurance, coordination, speed), as well as separately on all six physical fitness components. Secular trends for each of the physical fitness components and differences between schools and children were taken into account in linear mixed models. We found a negative Covid pandemic effect on the two composite physical fitness scores, as well as on cardiorespiratory endurance, coordination, and speed. We found a positive Covid pandemic effect on powerLOW. Coordination was associated with the largest negative Covid pandemic effect, also passing the threshold of smallest meaningful change (SMC, i.e., 0.2 Cohen’s d) when accumulated across two years. Given the educational context, Covid pandemic effects were also compared relative to the expected age-related development of the physical fitness components between eight and nine years. The Covid pandemic-related developmental costs/gains ranged from three to seven months relative to a longitudinal age effect, and from five to 17 months relative to a cross-sectional age effect. We propose that a longitudinal assessment yields a more reliable estimate of the developmental (age-related) gain than a cross-sectional one. Therefore, we consider the smaller Covid pandemic-related developmental costs/gains to be more credible. Interestingly, on the school level, „fitter” schools (relatively higher Grand Mean) exhibited larger negative Covid pandemic effects than schools with a lower physical fitness score. Negative Covid pandemic effects for the three run tasks were also found by Bähr et al. (2022), who tested the physical fitness of 16,496 Thuringian third-graders from 292 schools with the same six physical fitness tests used in EMOTIKON. Our results may be used to prioritize health-related interventions.
In light of climate change mitigation efforts, revenues from climate policies are growing, with no consensus yet on how they should be used. Potential efficiency gains from reducing distortionary taxes and the distributional implications of different revenue recycling schemes are currently debated. To account for households heterogeneity and dynamic trade-offs, we study the macroeconomic and welfare performance of different revenue recycling schemes using an Environmental Two-Agent New-Keynesian model, calibrated on the German economy. We find that, in the long run, welfare gains are higher when revenues are used to reduce distortionary taxes on capital, but this comes at the cost of higher inequality: while all households prefer labor income tax reductions to lump-sum transfers, only financially unconstrained households are better off when reducing taxes on capital income. Interestingly, we find that over the transition period relevant to meet short-medium run climate targets, labor income tax cuts are the most efficient and equitable instrument.
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 2018. Selected projects have presented their results on April 17th and November 14th 2017 at the Future SOC Lab Day events.
Objective
Insulin regulates mitochondrial function, thereby propagating an efficient metabolism. Conversely, diabetes and insulin resistance are linked to mitochondrial dysfunction with a decreased expression of the mitochondrial chaperone HSP60. The aim of this investigation was to determine the effect of a reduced HSP60 expression on the development of obesity and insulin resistance.
Methods
Control and heterozygous whole-body HSP60 knockout (Hsp60+/−) mice were fed a high-fat diet (HFD, 60% calories from fat) for 16 weeks and subjected to extensive metabolic phenotyping. To understand the effect of HSP60 on white adipose tissue, microarray analysis of gonadal WAT was performed, ex vivo experiments were performed, and a lentiviral knockdown of HSP60 in 3T3-L1 cells was conducted to gain detailed insights into the effect of reduced HSP60 levels on adipocyte homeostasis.
Results
Male Hsp60+/− mice exhibited lower body weight with lower fat mass. These mice exhibited improved insulin sensitivity compared to control, as assessed by Matsuda Index and HOMA-IR. Accordingly, insulin levels were significantly reduced in Hsp60+/− mice in a glucose tolerance test. However, Hsp60+/− mice exhibited an altered adipose tissue metabolism with elevated insulin-independent glucose uptake, adipocyte hyperplasia in the presence of mitochondrial dysfunction, altered autophagy, and local insulin resistance.
Conclusions
We discovered that the reduction of HSP60 in mice predominantly affects adipose tissue homeostasis, leading to beneficial alterations in body weight, body composition, and adipocyte morphology, albeit exhibiting local insulin resistance.
The availability of commercial 3D printers and matching 3D design software has allowed a wide range of users to create physical prototypes – as long as these objects are not larger than hand size. However, when attempting to create larger, "human-scale" objects, such as furniture, not only are these machines too small, but also the commonly used 3D design software is not equipped to design with forces in mind — since forces increase disproportionately with scale.
In this thesis, we present a series of end-to-end fabrication software systems that support users in creating human-scale objects. They achieve this by providing three main functions that regular "small-scale" 3D printing software does not offer: (1) subdivision of the object into small printable components combined with ready-made objects, (2) editing based on predefined elements sturdy enough for larger scale, i.e., trusses, and (3) functionality for analyzing, detecting, and fixing structural weaknesses. The presented software systems also assist the fabrication process based on either 3D printing or steel welding technology.
The presented systems focus on three levels of engineering challenges: (1) fabricating static load-bearing objects, (2) creating mechanisms that involve motion, such as kinematic installations, and finally (3) designing mechanisms with dynamic repetitive movement where power and energy play an important role.
We demonstrate and verify the versatility of our systems by building and testing human-scale prototypes, ranging from furniture pieces, pavilions, to animatronic installations and playground equipment. We have also shared our system with schools, fablabs, and fabrication enthusiasts, who have successfully created human-scale objects that can withstand with human-scale forces.
During his trip to New Spain in 1803, Alexander von Humboldt visited large tracts of New Spanish territory, which includes modern Mexico and part of the United States. This trip provided the data for his geographical Atlas of the region, as well as information about the ancient Mexican cultures that he would later include in the general Atlas and in other major works, such as Vues des Cordillères. Likewise, Humboldt’s Political Essay on the Kingdom of New Spain displayed a comprehensive physical, natural, economic, and social description of Mexico in the colonial period, which will also be analysed. With these works, Humboldt presented a new geographical and cultural image of New Spain to the European audiences. In addition to this, his work made important contributions to cartographic knowledge.
Hunting Down Animal Verbs
(2022)
Language change is an essential feature of human language, and it is therefore one of the focal areas of the scientific study of language. Language change is always tacitly at work in all languages of the world and at all levels of a given language, be it phonology, morphology, syntax, semantics, etc. It has been suggested that it is precisely the capacity to constantly change and adjust that allows language to keep serving the communicative goals of its users, from ancient to modern times (Fauconnier & Turner, 2003, p. 179).
This thesis investigates an especially salient pattern of lexicogrammatical change, namely word-formation of verbs from animal nouns by zero-derivation, in the process of which such nouns as, for example, dog, horse, or beaver change their usage and meaning to produce animal verbs: to dog ‘to follow someone persistently and with a malicious intent’, to horse about/around ‘to make fun of, to ‘rag’, to ridicule someone’ and to beaver away ‘to work at working with great enthusiasm’ respectively. In the previous literature this pattern of language change has been termed verbal zoosemy (e.g. Kiełtyka, 2016), i.e. metaphorical construal of human actions by means of linguistic material from the domain of animals.
The approach taken in this study is not to simply report on the objective changes in the morphology, syntactic distribution and meaning of such linguistic units before and after conversion, but to uncover the complexity of cognitive mechanisms which allow the speakers of English to reclassify such well-established nominal units as animal noun into verbs. It is assumed that the grammatical change in these lexical units is predicated on and triggered by preceding semantic change. Thus, the study is set in the framework of Cognitive Historical Semantics and employs the Conceptual Metaphor and Metonymy Theory (CMMT) to untangle the intricacies of the semantic change making the grammatical change of animal nouns into verbs possible and acceptable in the minds of English speakers.
To this end, this study employed the Oxford English Dictionary Online (OED Online) to compile a glossary of 96 denominal animal verbal forms tied to 209 verbal senses (most verbs in the dataset displayed polysemy). The data collected from the OED Online included not only the senses of the verbs, but also the date of the earliest recorded use of the verbal form with the given sense (regarded in the study as the date of conversion), the earliest usage examples for individual senses and morphologically or semantically related linguistic units from the lexical field of the respective parent noun which were amenable to explaining the observed instances of semantic change. Each instance of zoosemisation, i.e. of the creation of a separate metaphorical verbal sense, was then carefully analysed on the basis of the data collected and classified with the help of the CMMT. In the final stage, a comprehensive and systematic classification of the senses of animal verbs in accordance with the cognitive mechanisms of their creation (metaphor, metonymy, or a combination thereof) was produced together with a timeline of the first appearance of individual metaphorical senses of animal verbs recorded in the OED.
The results show that animal verbs are produced through the interaction of conceptual metaphor and metonymy. Specifically, it was established that two major patterns of metaphor-metonymy interaction underpinning the process of verbal zoosemisation are metaphor from metonymy and metonymy from metaphor. In the former pattern, either an already existing metonymic animal verb is expanded to include the target domain PEOPLE, or the animal noun itself acts as a metonymic vehicle to a certain element of the idealised cognitive model of the given animal, which is metaphorically projected onto people. In the latter mechanism, a metaphorical projection of an animal term initially enters the lexicon in the form of a metaphorical animal noun referring to a human entity, and later in the course of language development it comes to metonymically stand for the action, which the given entity either performs or is involved in. Secondarily, it was observed that individual animal nouns can undergo multiple rounds of zoosemic conversion over time depending on the semantic frame in which the given linguistic unit undergoes denominal conversion, and that results in the polysemy of most animal verbs.
Hydraulic-driven fractures play a key role in subsurface energy technologies across several scales. By injecting fluid at high hydraulic pressure into rock with intrinsic low permeability, in-situ stress field and fracture development pattern can be characterised as well as rock permeability can be enhanced. Hydraulic fracturing is a commercial standard procedure for enhanced oil and gas production of rock reservoirs with low permeability in petroleum industry. However, in EGS utilization, a major geological concern is the unsolicited generation of earthquakes due to fault reactivation, referred to as induced seismicity, with a magnitude large enough to be felt on the surface or to damage facilities and buildings. Furthermore, reliable interpretation of hydraulic fracturing tests for stress measurement is a great challenge for the energy technologies. Therefore, in this cumulative doctoral thesis the following research questions are investigated. (1): How do hydraulic fractures grow in hard rock at various scales?; (2): Which parameters control hydraulic fracturing and hydro-mechanical coupling?; and (3): How can hydraulic fracturing in hard rock be modelled?
In the laboratory scale study, several laboratory hydraulic fracturing experiments are investigated numerically using Irazu2D that were performed on intact cubic Pocheon granite samples from South Korea applying different injection protocols. The goal of the laboratory experiments is to test the concept of cyclic soft stimulation which may enable sustainable permeability enhancement (Publication 1).
In the borehole scale study, hydraulic fracturing tests are reported that were performed in boreholes located in central Hungary to determine the in-situ stress for a geological site investigation. At depth of about 540 m, the recorded pressure versus time curves in mica schist with low dip angle foliation show atypical evolution. In order to provide explanation for this observation, a series of discrete element computations using Particle Flow Code 2D are performed (Publication 2).
In the reservoir scale study, the hydro-mechanical behaviour of fractured crystalline rock due to one of the five hydraulic stimulations at the Pohang Enhanced Geothermal site in South Korea is studied. Fluid pressure perturbation at faults of several hundred-meter lengths during hydraulic stimulation is simulated using FracMan (Publication 3).
The doctoral research shows that the resulting hydraulic fracturing geometry will depend “locally”, i.e. at the length scale of representative elementary volume (REV) and below that (sub-REV), on the geometry and strength of natural fractures, and “globally”, i.e. at super-REV domain volume, on far-field stresses. Regarding hydro-mechanical coupling, it is suggested to define separate coupling relationship for intact rock mass and natural fractures. Furthermore, the relative importance of parameters affecting the magnitude of formation breakdown pressure, a parameter characterising hydro-mechanical coupling, is defined. It can be also concluded that there is a clear gap between the capacity of the simulation software and the complexity of the studied problems. Therefore, the computational time of the simulation of complex hydraulic fracture geometries must be reduced while maintaining high fidelity simulation results. This can be achieved either by extending the computational resources via parallelization techniques or using time scaling techniques. The ongoing development of used numerical models focuses on tackling these methodological challenges.
Objective
To improve consumer decision making, the results of risk assessments on food, feed, consumer products or chemicals need to be communicated not only to experts but also to non-expert audiences. The present study draws on evidence from literature reviews and focus groups with diverse stakeholders to identify content to integrate into an existing risk assessment communication (Risk Profile).
Methods
A combination of rapid literature reviews and focus groups with experts (risk assessors (n = 15), risk managers (n = 8)), and non-experts (general public (n = 18)) were used to identify content and strategies for including information about risk assessment results in the “Risk Profile” from the German Federal Institute for Risk Assessment. Feedback from initial focus groups was used to develop communication prototypes that informed subsequent feedback rounds in an iterative process. A final prototype was validated in usability tests with experts.
Results
Focus group feedback and suggestions from risk assessors were largely in line with findings from the literature. Risk managers and lay persons offered similar suggestions on how to improve the existing communication of risk assessment results (e.g., including more explanatory detail, reporting probabilities for individual health impairments, and specifying risks for subgroups in additional sections). Risk managers found information about quality of evidence important to communicate, whereas people from the general public found this information less relevant. Participants from lower educational backgrounds had difficulties understanding the purpose of risk assessments. User tests found that the final prototype was appropriate and feasible to implement by risk assessors.
Conclusion
An iterative and evidence-based process was used to develop content to improve the communication of risk assessments to the general public while being feasible to use by risk assessors. Remaining challenges include how to communicate dose-response relationships and standardise quality of evidence ratings across disciplines.
Here we present an exome-wide rare genetic variant association study for 30 blood biomarkers in 191,971 individuals in the UK Biobank. We compare gene- based association tests for separate functional variant categories to increase interpretability and identify 193 significant gene-biomarker associations. Genes associated with biomarkers were ~ 4.5-fold enriched for conferring Mendelian disorders. In addition to performing weighted gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for mis- sense variants, splicing and the binding of RNA-binding proteins. For these tests, we present a computationally efficient combination of the likelihood- ratio and score tests that found 36% more associations than the score test alone while also controlling the type-1 error. Kernel-based tests identified 13% more associations than their gene-based collapsing counterparts and had advantages in the presence of gain of function missense variants. We introduce local collapsing by amino acid position for missense variants and use it to interpret associations and identify potential novel gain of function variants in PIEZO1. Our results show the benefits of investigating different functional mechanisms when performing rare-variant association tests, and demonstrate pervasive rare-variant contribution to biomarker variability.
Diabetes is hallmarked by high blood glucose levels, which cause progressive generalised vascular damage, leading to microvascular and macrovascular complications. Diabetes-related complications cause severe and prolonged morbidity and are a major cause of mortality among people with diabetes. Despite increasing attention to risk factors of type 2 diabetes, existing evidence is scarce or inconclusive regarding vascular complications and research investigating both micro- and macrovascular complications is lacking. This thesis aims to contribute to current knowledge by identifying risk factors – mainly related to lifestyle – of vascular complications, addressing methodological limitations of previous literature and providing comparative data between micro- and macrovascular complications.
To address this overall aim, three specific objectives were set. The first was to investigate the effects of diabetes complication burden and lifestyle-related risk factors on the incidence of (further) complications. Studies suggest that diabetes complications are interrelated. However, they have been studied mainly independently of individuals’ complication burden. A five-state time-to-event model was constructed to examine the longitudinal patterns of micro- (kidney disease, neuropathy and retinopathy) and macrovascular complications (myocardial infarction and stroke) and their association with the occurrence of subsequent complications. Applying the same model, the effect of modifiable lifestyle factors, assessed alone and in combination with complication load, on the incidence of diabetes complications was studied. The selected lifestyle factors were body mass index (BMI), waist circumference, smoking status, physical activity, and intake of coffee, red meat, whole grains, and alcohol. Analyses were conducted in a cohort of 1199 participants with incident type 2 diabetes from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam, who were free of vascular complications at diabetes diagnosis. During a median follow-up time of 11.6 years, 96 cases of macrovascular complications (myocardial infarction and stroke) and 383 microvascular complications (kidney disease, neuropathy and retinopathy) were identified. In multivariable-adjusted models, the occurrence of a microvascular complication was associated with a higher incidence of further micro- (Hazard ratio [HR] 1.90; 95% Confidence interval [CI] 0.90, 3.98) and macrovascular complications (HR 4.72; 95% CI 1.25, 17.68), compared with persons without a complication burden. In addition, participants who developed a macrovascular event had a twofold higher risk of future microvascular complications (HR 2.26; 95% CI 1.05, 4.86). The models were adjusted for age, sex, state duration, education, lifestyle, glucose-lowering medication, and pre-existing conditions of hypertension and dyslipidaemia. Smoking was positively associated with macrovascular disease, while an inverse association was observed with higher coffee intake. Whole grain and alcohol intake were inversely associated with microvascular complications, and a U-shaped association was observed for red meat intake. BMI and waist circumference were positively associated with microvascular events. The associations between lifestyle factors and incidence of complications were not modified by concurrent complication burden, except for red meat intake and smoking status, where the associations were attenuated among individuals with a previous complication.
The second objective was to perform an in-depth investigation of the association between BMI and BMI change and risk of micro- and macrovascular complications. There is an ongoing debate on the association between obesity and risk of macrovascular and microvascular outcomes in type 2 diabetes, with studies suggesting a protective effect among people with overweight or obesity. These findings, however, might be limited due to suboptimal control for smoking, pre-existing chronic disease, or short-follow-up. After additional exclusion of persons with cancer history at diabetes onset, the associations between pre-diagnosis BMI and relative annual change between pre- and post-diagnosis BMI and incidence of complications were evaluated in multivariable-adjusted Cox models. The analyses were adjusted for age, sex, education, smoking status and duration, physical activity, alcohol consumption, adherence to the Mediterranean diet, and family history of diabetes and cardiovascular disease (CVD). Among 1083 EPIC-Potsdam participants, 85 macrovascular and 347 microvascular complications were identified during a median follow-up period of 10.8 years. Higher pre-diagnosis BMI was associated with an increased risk of total microvascular complications (HR per 5 kg/m2 1.21; 95% CI 1.07, 1.36), kidney disease (HR 1.39; 95% CI 1.21, 1.60) and neuropathy (HR 1.12; 95% CI 0.96, 1.31); but no association was observed for macrovascular complications (HR 1.05; 95% CI 0.81, 1.36). Effect modification was not evident by sex, smoking status, or age groups. In analyses according to BMI change categories, BMI loss of more than 1% indicated a decreased risk of total microvascular complications (HR 0.62; 95% CI 0.47, 0.80), kidney disease (HR 0.57; 95% CI 0.40, 0.81) and neuropathy (HR 0.73; 95% CI 0.52, 1.03), compared with participants with a stable BMI. No clear association was observed for macrovascular complications (HR 1.04; 95% CI 0.62, 1.74). The impact of BMI gain on diabetes-related vascular disease was less evident. Associations were consistent across strata of age, sex, pre-diagnosis BMI, or medication but appeared stronger among never-smokers than current or former smokers.
The last objective was to evaluate whether individuals with a high-risk profile for diabetes and cardiovascular disease (CVD) also have a greater risk of complications. Within the EPIC-Potsdam study, two accurate prognostic tools were developed, the German Diabetes Risk Score (GDRS) and the CVD Risk Score (CVDRS), which predict the 5-year type 2 diabetes risk and 10-year CVD risk, respectively. Both scores provide a non-clinical and clinical version. Components of the risk scores include age, sex, waist circumference, prevalence of hypertension, family history of diabetes or CVD, lifestyle factors, and clinical factors (only in clinical versions). The association of the risk scores with diabetes complications and their discriminatory performance for complications were assessed. In crude Cox models, both versions of GDRS and CVDRS were positively associated with macrovascular complications and total microvascular complications, kidney disease and neuropathy. Higher GDRS was also associated with an elevated risk of retinopathy. The discrimination of the scores (clinical and non-clinical) was poor for all complications, with the C-index ranging from 0.58 to 0.66 for macrovascular complications and from 0.60 to 0.62 for microvascular complications.
In conclusion, this work illustrates that the risk of complication development among individuals with type 2 diabetes is related to the existing complication load, and attention should be given to regular monitoring for future complications. It underlines the importance of weight management and adherence to healthy lifestyle behaviours, including high intake of whole grains, moderation in red meat and alcohol consumption and avoidance of smoking to prevent major diabetes-associated complications, regardless of complication burden. Risk scores predictive for type 2 diabetes and CVD were related to elevated risks of complications. By optimising several lifestyle and clinical factors, the risk score can be improved and may assist in lowering complication risk.
Enhanced geothermal systems (EGS) are considered a cornerstone of future sustainable energy production. In such systems, high-pressure fluid injections break the rock to provide pathways for water to circulate in and heat up. This approach inherently induces small seismic events that, in rare cases, are felt or can even cause damage. Controlling and reducing the seismic impact of EGS is crucial for a broader public acceptance. To evaluate the applicability of hydraulic fracturing (HF) in EGS and to improve the understanding of fracturing processes and the hydromechanical relation to induced seismicity, six in-situ, meter-scale HF experiments with different injection schemes were performed under controlled conditions in crystalline rock in a depth of 410 m at the Äspö Hard Rock Laboratory (Sweden).
I developed a semi-automated, full-waveform-based detection, classification, and location workflow to extract and characterize the acoustic emission (AE) activity from the continuous recordings of 11 piezoelectric AE sensors. Based on the resulting catalog of 20,000 AEs, with rupture sizes of cm to dm, I mapped and characterized the fracture growth in great detail. The injection using a novel cyclic injection scheme (HF3) had a lower seismic impact than the conventional injections. HF3 induced fewer AEs with a reduced maximum magnitude and significantly larger b-values, implying a decreased number of large events relative to the number of small ones. Furthermore, HF3 showed an increased fracture complexity with multiple fractures or a fracture network. In contrast, the conventional injections developed single, planar fracture zones (Publication 1).
An independent, complementary approach based on a comparison of modeled and observed tilt exploits transient long-period signals recorded at the horizontal components of two broad-band seismometers a few tens of meters apart from the injections. It validated the efficient creation of hydraulic fractures and verified the AE-based fracture geometries. The innovative joint analysis of AEs and tilt signals revealed different phases of the fracturing process, including the (re-)opening, growth, and aftergrowth of fractures, and provided evidence for the reactivation of a preexisting fault in one of the experiments (Publication 2). A newly developed network-based waveform-similarity analysis applied to the massive AE activity supports the latter finding.
To validate whether the reduction of the seismic impact as observed for the cyclic injection schemes during the Äspö mine-scale experiments is transferable to other scales, I additionally calculated energy budgets for injection experiments from previously conducted laboratory tests and from a field application. Across all three scales, the cyclic injections reduce the seismic impact, as depicted by smaller maximum magnitudes, larger b-values, and decreased injection efficiencies (Publication 3).
Weather extremes pose a persistent threat to society on multiple layers. Besides an average of ~37,000 deaths per year, climate-related disasters cause destroyed properties and impaired economic activities, eroding people's livelihoods and prosperity. While global temperature rises – caused by anthropogenic greenhouse gas emissions – the direct impacts of climatic extreme events increase and will further intensify without proper adaptation measures. Additionally, weather extremes do not only have local direct effects. Resulting economic repercussions can propagate either upstream or downstream along trade chains causing indirect effects. One approach to analyze these indirect effects within the complex global supply network is the agent-based model Acclimate. Using and extending this loss-propagation model, I focus in this thesis on three aspects of the relation between weather extremes and economic repercussions.
First, extreme weather events cause direct impacts on local economic performance. I compute daily local direct output loss time series of heat stress, river floods, tropical cyclones, and their consecutive occurrence using (near-future) climate projection ensembles. These regional impacts are estimated based on physical drivers and local productivity distribution. Direct effects of the aforementioned disaster categories are widely heterogeneous concerning regional and temporal distribution. As well, their intensity changes differently under future warming. Focusing on the hurricane-impacted capital, I find that long-term growth losses increase with higher heterogeneity of a shock ensemble.
Second, repercussions are sectorally and regionally distributed via economic ripples within the trading network, causing higher-order effects. I use Acclimate to identify three phases of those economic ripples. Furthermore, I compute indirect impacts and analyze overall regional and global production and consumption changes. Regarding heat stress, global consumer losses double while direct output losses increase by a factor 1.5 between 2000 – 2039. In my research I identify the effect of economic ripple resonance and introduce it to climate impact research. This effect occurs if economic ripples of consecutive disasters overlap, which increases economic responses such as an enhancement of consumption losses. These loss enhancements can even be more amplified with increasing direct output losses, e.g. caused by climate crises.
Transport disruptions can cause economic repercussions as well. For this, I extend the model Acclimate with a geographical transportation route and expand the decision horizon of economic agents. Using this, I show that policy-induced sudden trade restrictions (e.g. a no-deal Brexit) can significantly reduce the longer-term economic prosperity of affected regions. Analyses of transportation disruptions in typhoon seasons indicate that severely affected regions must reduce production as demand falls during a storm. Substituting suppliers may compensate for fluctuations at the beginning of the storm, which fails for prolonged disruptions.
Third, possible coping mechanisms and adaptation strategies arise from direct and indirect economic responses to weather extremes. Analyzing annual trade changes due to typhoon-induced transport disruptions depict that overall exports rise. This trade resilience increases with higher network node diversification. Further, my research shows that a basic insurance scheme may diminish hurricane-induced long-term growth losses due to faster reconstruction in disasters aftermaths. I find that insurance coverage could be an economically reasonable coping scheme towards higher losses caused by the climate crisis. Indirect effects within the global economic network from weather extremes indicate further adaptation possibilities. For one, diversifying linkages reduce the hazard of sharp price increases. Next to this, close economic interconnections with regions that do not share the same extreme weather season can be economically beneficial in the medium run. Furthermore, economic ripple resonance effects should be considered while computing costs. Overall, an increase in local adaptation measures reduces economic ripples within the trade network and possible losses elsewhere. In conclusion, adaptation measures are necessary and potential present, but it seems rather not possible to avoid all direct or indirect losses.
As I show in this thesis, dynamical modeling gives valuable insights into how direct and indirect economic impacts arise from different categories of weather extremes. Further, it highlights the importance of resolving individual extremes and reflecting amplifying effects caused by incomplete recovery or consecutive disasters.
The reduction in cost and increasing benefits of 3D printing technologies suggest the potential for printing dental prosthetics. However, although 3D printing technologies seem to be promising, their implementation in practice is complicated. To identify and rank the greatest implementation challenges of 3D printing in dental practices, the present study surveys dentists, dental technicians, and 3D printing companies using a ranking-type Delphi study. Our findings imply that a lack of knowledge is the most crucial obstacle to the implementation of 3D printing technologies. The high training effort of staff and the favoring of conventional methods, such as milling, are ranked as the second and third most relevant factors. Investment costs ranked in seventh place, whereas the lack of manufacturing facilities and the obstacle of print duration ranked below average. An inclusive implementation of additive manufacturing could be achieved primarily through the education of dentists and other staff in dental practices. In this manner, production may be managed internally, and the implementation speed may be increased.
Pictures are a medium that helps make the past tangible and preserve memories. Without context, they are not able to do so. Pictures are brought to life by their associated stories. However, the older pictures become, the fewer contemporary witnesses can tell these stories.
Especially for large, analog picture archives, knowledge and memories are spread over many people. This creates several challenges: First, the pictures must be digitized to save them from decaying and make them available to the public. Since a simple listing of all the pictures is confusing, the pictures should be structured accessibly. Second, known information that makes the stories vivid needs to be added to the pictures. Users should get the opportunity to contribute their knowledge and memories. To make this usable for all interested parties, even for older, less technophile generations, the interface should be intuitive and error-tolerant.
The resulting requirements are not covered in their entirety by any existing software solution without losing the intuitive interface or the scalability of the system.
Therefore, we have developed our digital picture archive within the scope of a bachelor project in cooperation with the Bad Harzburg-Stiftung. For the implementation of this web application, we use the UI framework React in the frontend, which communicates via a GraphQL interface with the Content Management System Strapi in the backend. The use of this system enables our project partner to create an efficient process from scanning analog pictures to presenting them to visitors in an organized and annotated way. To customize the solution for both picture delivery and information contribution for our target group, we designed prototypes and evaluated them with people from Bad Harzburg. This helped us gain valuable insights into our system’s usability and future challenges as well as requirements.
Our web application is already being used daily by our project partner. During the project, we still came up with numerous ideas for additional features to further support the exchange of knowledge.
Accurately solving classification problems nowadays is likely to be the most relevant machine learning task. Binary classification separating two classes only is algorithmically simpler but has fewer potential applications as many real-world problems are multi-class. On the reverse, separating only a subset of classes simplifies the classification task. Even though existing multi-class machine learning algorithms are very flexible regarding the number of classes, they assume that the target set Y is fixed and cannot be restricted once the training is finished. On the other hand, existing state-of-the-art production environments are becoming increasingly interconnected with the advance of Industry 4.0 and related technologies such that additional information can simplify the respective classification problems. In light of this, the main aim of this thesis is to introduce dynamic classification that generalizes multi-class classification such that the target class set can be restricted arbitrarily to a non-empty class subset M of Y at any time between two consecutive predictions.
This task is solved by a combination of two algorithmic approaches. First, classifier calibration, which transforms predictions into posterior probability estimates that are intended to be well calibrated. The analysis provided focuses on monotonic calibration and in particular corrects wrong statements that appeared in the literature. It also reveals that bin-based evaluation metrics, which became popular in recent years, are unjustified and should not be used at all. Next, the validity of Platt scaling, which is the most relevant parametric calibration approach, is analyzed in depth. In particular, its optimality for classifier predictions distributed according to four different families of probability distributions as well its equivalence with Beta calibration up to a sigmoidal preprocessing are proven. For non-monotonic calibration, extended variants on kernel density estimation and the ensemble method EKDE are introduced. Finally, the calibration techniques are evaluated using a simulation study with complete information as well as on a selection of 46 real-world data sets.
Building on this, classifier calibration is applied as part of decomposition-based classification that aims to reduce multi-class problems to simpler (usually binary) prediction tasks. For the involved fusing step performed at prediction time, a new approach based on evidence theory is presented that uses classifier calibration to model mass functions. This allows the analysis of decomposition-based classification against a strictly formal background and to prove closed-form equations for the overall combinations. Furthermore, the same formalism leads to a consistent integration of dynamic class information, yielding a theoretically justified and computationally tractable dynamic classification model. The insights gained from this modeling are combined with pairwise coupling, which is one of the most relevant reduction-based classification approaches, such that all individual predictions are combined with a weight. This not only generalizes existing works on pairwise coupling but also enables the integration of dynamic class information.
Lastly, a thorough empirical study is performed that compares all newly introduced approaches to existing state-of-the-art techniques. For this, evaluation metrics for dynamic classification are introduced that depend on corresponding sampling strategies. Thereafter, these are applied during a three-part evaluation. First, support vector machines and random forests are applied on 26 data sets from the UCI Machine Learning Repository. Second, two state-of-the-art deep neural networks are evaluated on five benchmark data sets from a relatively recent reference work. Here, computationally feasible strategies to apply the presented algorithms in combination with large-scale models are particularly relevant because a naive application is computationally intractable. Finally, reference data from a real-world process allowing the inclusion of dynamic class information are collected and evaluated. The results show that in combination with support vector machines and random forests, pairwise coupling approaches yield the best results, while in combination with deep neural networks, differences between the different approaches are mostly small to negligible. Most importantly, all results empirically confirm that dynamic classification succeeds in improving the respective prediction accuracies. Therefore, it is crucial to pass dynamic class information in respective applications, which requires an appropriate digital infrastructure.
The heterogeneity of today's state-of-the-art computer architectures is confronting application developers with an immense degree of complexity which results from two major challenges. First, developers need to acquire profound knowledge about the programming models or the interaction models associated with each type of heterogeneous system resource to make efficient use thereof. Second, developers must take into account that heterogeneous system resources always need to exchange data with each other in order to work on a problem together. However, this data exchange is always associated with a certain amount of overhead, which is why the amounts of data exchanged should be kept as low as possible.
This thesis proposes three programming abstractions to lessen the burdens imposed by these major challenges with the goal of making heterogeneous system resources accessible to a wider range of application developers. The lib842 compression library provides the first method for accessing the compression and decompression facilities of the NX-842 on-chip compression accelerator available in IBM Power CPUs from user space applications running on Linux. Addressing application development of scale-out GPU workloads, the CloudCL framework makes the resources of GPU clusters more accessible by hiding many aspects of distributed computing while enabling application developers to focus on the aspects of the data parallel programming model associated with GPUs. Furthermore, CloudCL is augmented with transparent data compression facilities based on the lib842 library in order to improve the efficiency of data transfers among cluster nodes. The improved data transfer efficiency provided by the integration of transparent data compression yields performance improvements ranging between 1.11x and 2.07x across four data-intensive scale-out GPU workloads. To investigate the impact of programming abstractions for data placement in NUMA systems, a comprehensive evaluation of the PGASUS framework for NUMA-aware C++ application development is conducted. On a wide range of test systems, the evaluation demonstrates that PGASUS does not only improve the developer experience across all workloads, but that it is also capable of outperforming NUMA-agnostic implementations with average performance improvements of 1.56x.
Based on these programming abstractions, this thesis demonstrates that by providing a sufficient degree of abstraction, the accessibility of heterogeneous system resources can be improved for application developers without occluding performance-critical properties of the underlying hardware.
As of late, epidemiological studies have highlighted a strong association of dairy intake with lower disease risk, and similarly with an increased amount of odd-chain fatty acids (OCFA). While the OCFA also demonstrate inverse associations with disease incidence, the direct dietary sources and mode of action of the OCFA remain poorly understood.
The overall aim of this thesis was to determine the impact of two main fractions of dairy, milk fat and milk protein, on OCFA levels and their influence on health outcomes under high-fat (HF) diet conditions. Both fractions represent viable sources of OCFA, as milk fats contain a significant amount of OCFA and milk proteins are high in branched chain amino acids (BCAA), namely valine (Val) and isoleucine (Ile), which can produce propionyl-CoA (Pr-CoA), a precursor for endogenous OCFA synthesis, while leucine (Leu) does not. Additionally, this project sought to clarify the specific metabolic effects of the OCFA heptadecanoic acid (C17:0).
Both short-term and long-term feeding studies were performed using male C57BL/6JRj mice fed HF diets supplemented with milk fat or C17:0, as well as milk protein or individual BCAA (Val; Leu) to determine their influences on OCFA and metabolic health. Short-term feeding revealed that both milk fractions induce OCFA in vivo, and the increases elicited by milk protein could be, in part, explained by Val intake. In vitro studies using primary hepatocytes further showed an induction of OCFA after Val treatment via de novo lipogenesis and increased α-oxidation. In the long-term studies, both milk fat and milk protein increased hepatic and circulating OCFA levels; however, only milk protein elicited protective effects on adiposity and hepatic fat accumulation—likely mediated by the anti-obesogenic effects of an increased Leu intake. In contrast, Val feeding did not increase OCFA levels nor improve obesity, but rather resulted in glucotoxicity-induced insulin resistance in skeletal muscle mediated by its metabolite 3-hydroxyisobutyrate (3-HIB). Finally, while OCFA levels correlated with improved health outcomes, C17:0 produced negligible effects in preventing HF-diet induced health impairments.
The results presented herein demonstrate that the beneficial health outcomes associated with dairy intake are likely mediated through the effects of milk protein, while OCFA levels are likely a mere association and do not play a significant causal role in metabolic health under HF conditions. Furthermore, the highly divergent metabolic effects of the two BCAA, Leu and Val, unraveled herein highlight the importance of protein quality.
The increasing demand for energy in the current technological era and the recent political decisions about giving up on nuclear energy diverted humanity to focus on alternative environmentally friendly energy sources like solar energy. Although silicon solar cells are the product of a matured technology, the search for highly efficient and easily applicable materials is still ongoing. These properties made the efficiency of halide perovskites comparable with silicon solar cells for single junctions within a decade of research. However, the downside of halide perovskites are poor stability and lead toxicity for the most stable ones.
On the other hand, chalcogenide perovskites are one of the most promising absorber materials for the photovoltaic market, due to their elemental abundance and chemical stability against moisture and oxygen. In the search of the ultimate solar absorber material, combining the good optoelectronic properties of halide perovskites with the stability of chalcogenides could be the promising candidate.
Thus, this work investigates new techniques for the synthesis and design of these novel chalcogenide perovskites, that contain transition metals as cations, e.g., BaZrS3, BaHfS3, EuZrS3, EuHfS3 and SrHfS3. There are two stages in the deposition techniques of this study: In the first stage, the binary compounds are deposited via a solution processing method. In the second stage, the deposited materials are annealed in a chalcogenide atmosphere to form the perovskite structure by using solid-state reactions.
The research also focuses on the optimization of a generalized recipe for a molecular ink to deposit precursors of chalcogenide perovskites with different binaries. The implementation of the precursor sulfurization resulted in either binaries without perovskite formation or distorted perovskite structures, whereas some of these materials are reported in the literature as they are more favorable in the needle-like non-perovskite configuration.
Lastly, there are two categories for the evaluation of the produced materials: The first category is about the determination of the physical properties of the deposited layer, e.g., crystal structure, secondary phase formation, impurities, etc. For the second category, optoelectronic properties are measured and compared to an ideal absorber layer, e.g., band gap, conductivity, surface photovoltage, etc.
The negative impact of crude oil on the environment has led to a necessary transition toward alternative, renewable, and sustainable resources. In this regard, lignocellulosic biomass (LCB) is a promising renewable and sustainable alternative to crude oil for the production of fine chemicals and fuels in a so-called biorefinery process. LCB is composed of polysaccharides (cellulose and hemicellulose), as well as aromatics (lignin). The development of a sustainable and economically advantageous biorefinery depends on the complete and efficient valorization of all components. Therefore, in the new generation of biorefinery, the so-called biorefinery of type III, the LCB feedstocks are selectively deconstructed and catalytically transformed into platform chemicals. For this purpose, the development of highly stable and efficient catalysts is crucial for progress toward viability in biorefinery. Furthermore, a modern and integrated biorefinery relies on process and reactor design, toward more efficient and cost-effective methodologies that minimize waste. In this context, the usage of continuous flow systems has the potential to provide safe, sustainable, and innovative transformations with simple process integration and scalability for biorefinery schemes.
This thesis addresses three main challenges for future biorefinery: catalyst synthesis, waste feedstock valorization, and usage of continuous flow technology. Firstly, a cheap, scalable, and sustainable approach is presented for the synthesis of an efficient and stable 35 wt.-% Ni catalyst on highly porous nitrogen-doped carbon support (35Ni/NDC) in pellet shape. Initially, the performance of this catalyst was evaluated for the aqueous phase hydrogenation of LCB-derived compounds such as glucose, xylose, and vanillin in continuous flow systems. The 35Ni/NDC catalyst exhibited high catalytic performances in three tested hydrogenation reactions, i.e., sorbitol, xylitol, and 2-methoxy-4-methylphenol with yields of 82 mol%, 62 mol%, and 100 mol% respectively. In addition, the 35Ni/NDC catalyst exhibited remarkable stability over a long time on stream in continuous flow (40 h). Furthermore, the 35Ni/NDC catalyst was combined with commercially available Beta zeolite in a dual–column integrated process for isosorbide production from glucose (yield 83 mol%).
Finally, 35Ni/NDC was applied for the valorization of industrial waste products, namely sodium lignosulfonate (LS) and beech wood sawdust (BWS) in continuous flow systems. The LS depolymerization was conducted combining solvothermal fragmentation of water/alcohol mixtures (i.e.,methanol/water and ethanol/water) with catalytic hydrogenolysis/hydrogenation (SHF). The depolymerization was found to occur thermally in absence of catalyst with a tunable molecular weight according to temperature. Furthermore, the SHF generated an optimized cumulative yield of lignin-derived phenolic monomers of 42 mg gLS-1. Similarly, a solvothermal and reductive catalytic fragmentation (SF-RCF) of BWS was conducted using MeOH and MeTHF as a solvent. In this case, the optimized total lignin-derived phenolic monomers yield was found of 247 mg gKL-1.
Enterprise systems have long played an important role in businesses of various sizes. With the increasing complexity of today’s business relationships, pecialized application systems are being used more and more. Moreover, emerging technologies such as artificial intelligence are becoming accessible for enterprise systems. This raises the question of the future role of enterprise systems. This minitrack covers novel ideas that contribute to and shape the future role of enterprise systems with five contributions.
The analysis of behavioral models such as Graph Transformation Systems (GTSs) is of central importance in model-driven engineering. However, GTSs often result in intractably large or even infinite state spaces and may be equipped with multiple or even infinitely many start graphs. To mitigate these problems, static analysis techniques based on finite symbolic representations of sets of states or paths thereof have been devised. We focus on the technique of k-induction for establishing invariants specified using graph conditions. To this end, k-induction generates symbolic paths backwards from a symbolic state representing a violation of a candidate invariant to gather information on how that violation could have been reached possibly obtaining contradictions to assumed invariants. However, GTSs where multiple agents regularly perform actions independently from each other cannot be analyzed using this technique as of now as the independence among backward steps may prevent the gathering of relevant knowledge altogether.
In this paper, we extend k-induction to GTSs with multiple agents thereby supporting a wide range of additional GTSs. As a running example, we consider an unbounded number of shuttles driving on a large-scale track topology, which adjust their velocity to speed limits to avoid derailing. As central contribution, we develop pruning techniques based on causality and independence among backward steps and verify that k-induction remains sound under this adaptation as well as terminates in cases where it did not terminate before.
Neural conversation models aim to predict appropriate contributions to a (given) conversation by using neural networks trained on dialogue data. A specific strand focuses on non-goal driven dialogues, first proposed by Ritter et al. (2011): They investigated the task of transforming an utterance into an appropriate reply. Then, this strand evolved into dialogue system approaches using long dialogue histories and additional background context. Contributing meaningful and appropriate to a conversation is a complex task, and therefore research in this area has been very diverse: Serban et al. (2016), for example, looked into utilizing variable length dialogue histories, Zhang et al. (2018) added additional context to the dialogue history, Wolf et al. (2019) proposed a model based on pre-trained Self-Attention neural networks (Vasvani et al., 2017), and Dinan et al. (2021) investigated safety issues of these approaches. This trend can be seen as a transformation from trying to somehow carry on a conversation to generating appropriate replies in a controlled and reliable way.
In this thesis, we first elaborate the meaning of appropriateness in the context of neural conversation models by drawing inspiration from the Cooperative Principle (Grice, 1975). We first define what an appropriate contribution has to be by operationalizing these maxims as demands on conversation models: being fluent, informative, consistent towards given context, coherent and following a social norm. Then, we identify different targets (or intervention points) to achieve the conversational appropriateness by investigating recent research in that field.
In this thesis, we investigate the aspect of consistency towards context in greater detail, being one aspect of our interpretation of appropriateness.
During the research, we developed a new context-based dialogue dataset (KOMODIS) that combines factual and opinionated context to dialogues. The KOMODIS
dataset is publicly available and we use the data in this thesis to gather new insights in context-augmented dialogue generation.
We further introduced a new way of encoding context within Self-Attention based neural networks. For that, we elaborate the issue of space complexity from knowledge graphs,
and propose a concise encoding strategy for structured context inspired from graph neural networks (Gilmer et al., 2017) to reduce the space complexity of the additional context. We discuss limitations of context-augmentation for neural conversation models, explore the characteristics of knowledge graphs, and explain how we create and augment knowledge graphs for our experiments.
Lastly, we analyzed the potential of reinforcement and transfer learning to improve context-consistency for neural conversation models. We find that current reward functions need to be more precise to enable the potential of reinforcement learning, and that sequential transfer learning can improve the subjective quality of generated dialogues.
There is a large variety of goals instructors have for laboratory courses, with different courses focusing on different subsets of goals. An often implicit, but crucial, goal is to develop students’ attitudes, views, and expectations about experimental physics to align with practicing experimental physicists. The assessment of laboratory courses upon this one dimension of learning has been intensively studied in U.S. institutions using the Colorado Learning Attitudes about Science Survey for Experimental Physics (E-CLASS). However, there is no such an instrument available to use in Germany, and the influence of laboratory courses on students views about the nature of experimental physics is still unexplored at German-speaking institutions. Motivated by the lack of an assessment tool to investigate this goal in laboratory courses at German-speaking institutions, we present a translated version of the E-CLASS adapted to the context at German-speaking institutions. We call the German version of the E-CLASS, the GE-CLASS. We describe the translation process and the creation of an automated web-based system for instructors to assess their laboratory courses. We also present first results using GE-CLASS obtained at the University of Potsdam. A first comparison between E-CLASS and GE-CLASS results shows clear differences between University of Potsdam and U.S. students’ views and beliefs about experimental physics.
More than a century ago the phenomenon of non-Mendelian inheritance (NMI), defined as any type of inheritance pattern in which traits do not segregate in accordance with Mendel’s laws, was first reported. In the plant kingdom three genomic compartments, the nucleus, chloroplast, and mitochondrion, can participate in such a phenomenon. High-throughput sequencing (HTS) proved to be a key technology to investigate NMI phenomena by assembling and/or resequencing entire genomes. However, generation, analysis and interpretation of such datasets remain challenging by the multi-layered biological complexity. To advance our knowledge in the field of NMI, I conducted three studies involving different HTS technologies and implemented two new algorithms to analyze them.
In the first study I implemented a novel post-assembly pipeline, called Semi-Automated Graph-Based Assembly Curator (SAGBAC), which visualizes non-graph-based assemblies as graphs, identifies recombinogenic repeat pairs (RRPs), and reconstructs plant mitochondrial genomes (PMG) in a semiautomated workflow. We applied this pipeline to assemblies of three Oenothera species resulting in a spatially folded and circularized model. This model was confirmed by PCR and Southern blot analyses and was used to predict a defined set of 70 PMG isoforms. With Illumina Mate Pair and PacBio RSII data, the stoichiometry of the RRPs was determined quantitatively differing up to three-fold.
In the second study I developed a post-multiple sequence alignment algorithm, called correlation mapping (CM), which correlates segment-wise numbers of nucleotide changes to a numeric ascertainable phenotype. We applied this algorithm to 14 wild type and 18 mutagenized plastome assemblies within the Oenothera genus and identified two genes, accD and ycf2 that may cause the competitive behavior of plastid genotypes as plastids can be biparental inherited in Oenothera. Moreover, lipid composition of the plastid envelope membrane is affected by polymorphisms within these two genes.
For the third study, I programmed a pipeline to investigate a NMI phenomenon, known as paramutation, in tomato by analyzing DNA and bisulfite sequencing data as well as microarray data. We identified the responsible gene (Solyc02g0005200) and were able to fully repress its caused phenotype by heterologous complementation with a paramutation insensitive transgene of the Arabidopsis thaliana orthologue. Additionally, a suppressor mutant shows a globally altered DNA methylation pattern and carries a large deletion leading to a gene fusion involving a histone deacetylase.
In conclusion, my developed and implemented algorithms and data analysis pipelines are suitable to investigate NMI and led to novel insights about such phenomena by reconstructing PMGs (SAGBAC) as a requirement to study mitochondria-associated phenotypes, by identifying genes (CM) causing interplastidial competition as well by applying a DNA/Bisulfite-seq analysis pipeline to shed light in a transgenerational epigenetic inheritance phenomenon.
Dementia as one of the most prevalent diseases urges for a better understanding of the central mechanisms responsible for clinical symptoms, and necessitates improvement of actual diagnostic capabilities. The brainstem nucleus locus coeruleus (LC) is a promising target for early diagnosis because of its early structural alterations and its relationship to the functional disturbances in the patients. In this study, we applied our improved method of localisation-based LC resting-state fMRI to investigate the differences in central sensory signal processing when comparing functional connectivity (fc) of a patient group with mild cognitive impairment (MCI, n = 28) and an age-matched healthy control group (n = 29). MCI and control participants could be differentiated in their Mini-Mental-State-Examination (MMSE) scores (p < .001) and LC intensity ratio (p = .010). In the fMRI, LC fc to anterior cingulate cortex (FDR p < .001) and left anterior insula (FDR p = .012) was elevated, and LC fc to right temporoparietal junction (rTPJ, FDR p = .012) and posterior cingulate cortex (PCC, FDR p = .021) was decreased in the patient group. Importantly, LC to rTPJ connectivity was also positively correlated to MMSE scores in MCI patients (p = .017). Furthermore, we found a hyperactivation of the left-insula salience network in the MCI patients. Our results and our proposed disease model shed new light on the functional pathogenesis of MCI by directing to attentional network disturbances, which could aid new therapeutic strategies and provide a marker for diagnosis and prediction of disease progression.
The NAC transcription factor (TF) JUNGBRUNNEN1 (JUB1) is an important negative regulator of plant senescence, as well as of gibberellic acid (GA) and brassinosteroid (BR) biosynthesis in Arabidopsis thaliana. Overexpression of JUB1 promotes longevity and enhances tolerance to drought and other abiotic stresses. A similar role of JUB1 has been observed in other plant species, including tomato and banana. Our data show that JUB1 overexpressors (JUB1-OXs) accumulate higher levels of proline than WT plants under control conditions, during the onset of drought stress, and thereafter. We identified that overexpression of JUB1 induces key proline biosynthesis and suppresses key proline degradation genes. Furthermore, bZIP63, the transcription factor involved in proline metabolism, was identified as a novel downstream target of JUB1 by Yeast One-Hybrid (Y1H) analysis and Chromatin immunoprecipitation (ChIP). However, based on Electrophoretic Mobility Shift Assay (EMSA), direct binding of JUB1 to bZIP63 could not be confirmed. Our data indicate that JUB1-OX plants exhibit reduced stomatal conductance under control conditions. However, selective overexpression of JUB1 in guard cells did not improve drought stress tolerance in Arabidopsis. Moreover, the drought-tolerant phenotype of JUB1 overexpressors does not solely depend on the transcriptional control of the DREB2A gene. Thus, our data suggest that JUB1 confers tolerance to drought stress by regulating multiple components. Until today, none of the previous studies on JUB1´s regulatory network focused on identifying protein-protein interactions. We, therefore, performed a yeast two-hybrid screen (Y2H) which identified several protein interactors of JUB1, two of which are the calcium-binding proteins CaM1 and CaM4. Both proteins interact with JUB1 in the nucleus of Arabidopsis protoplasts. Moreover, JUB1 is expressed with CaM1 and CaM4 under the same conditions. Since CaM1.1 and CaM4.1 encode proteins with identical amino acid sequences, all further experiments were performed with constructs involving the CaM4 coding sequence. Our data show that JUB1 harbors multiple CaM-binding sites, which are localized in both the N-terminal and C-terminal regions of the protein. One of the CaM-binding sites, localized in the DNA-binding domain of JUB1, was identified as a functional CaM-binding site since its mutation strongly reduced the binding of CaM4 to JUB1. Furthermore, JUB1 transactivates expression of the stress-related gene DREB2A in mesophyll cells; this effect is significantly reduced when the calcium-binding protein CaM4 is expressed as well. Overexpression of both genes in Arabidopsis results in early senescence observed through lower chlorophyll content and an enhanced expression of senescence-associated genes (SAGs) when compared with single JUB1 overexpressors. Our data also show that JUB1 and CaM4 proteins interact in senescent leaves, which have increased Ca2+ levels when compared to young leaves. Collectively, our data indicate that JUB1 activity towards its downstream targets is fine-tuned by calcium-binding proteins during leaf senescence.
We collect a network dataset of tenured economics faculty in Austria, Germany and Switzerland. We rank the 100 institutions included with a minimum violation ranking. This ranking is positively and significantly correlated with the Times Higher Education ranking of economics institutions. According to the network ranking, individuals on average go down about 23 ranks from their doctoral institution to their employing institution. While the share of females in our dataset is only 15%, we do not observe a significant gender hiring gap (a difference in rank changes between male and female faculty). We conduct a robustness check with the Handelsblatt and the Times Higher Education ranking. According to these rankings, individuals on average go down only about two ranks. We do not observe a significant gender hiring gap using these two rankings (although the dataset underlying this analysis is small and these estimates are likely to be noisy). Finally, we discuss the limitations of the network ranking in our context.
Is There a Rural Penalty in Language Acquisition? Evidence From Germany's Refugee Allocation Policy
(2022)
Emerging evidence has highlighted the important role of local contexts for integration trajectories of asylum seekers and refugees. Germany's policy of randomly allocating asylum seekers across Germany may advantage some and disadvantage others in terms of opportunities for equal participation in society. This study explores the question whether asylum seekers that have been allocated to rural areas experience disadvantages in terms of language acquisition compared to those allocated to urban areas. We derive testable assumptions using a Directed Acyclic Graph (DAG) which are then tested using large-N survey data (IAB-BAMF-SOEP refugee survey). We find that living in a rural area has no negative total effect on language skills. Further the findings suggest that the “null effect” is the result of two processes which offset each other: while asylum seekers in rural areas have slightly lower access for formal, federally organized language courses, they have more regular exposure to German speakers.
Isometric muscle function
(2022)
The cumulative dissertation consists of four original articles. These considered isometric muscle ac-tions in healthy humans from a basic physiological view (oxygen and blood supply) as well as possibilities of their distinction. It includes a novel approach to measure a specific form of isometric hold-ing function which has not been considered in motor science so far. This function is characterized by an adaptation to varying external forces with particular importance in daily activities and sports.
The first part of the research program analyzed how the biceps brachii muscle is supplied with oxygen and blood by adapting to a moderate constant load until task failure (publication 1). In this regard, regulative mechanisms were investigated in relation to the issue of presumably compressed capillaries due to high intramuscular pressures (publication 2).
Furthermore, it was examined if oxygenation and time to task failure (TTF) differs compared to an-other isometric muscle function (publication 3). This function is mainly of diagnostic interest by measuring the maximal voluntary isometric contraction (MVIC) as a gold standard. For that, a person pulls on or pushes against an insurmountable resistance. However, the underlying pulling or pushing form of isometric muscle action (PIMA) differs compared to the holding one (HIMA).
HIMAs have mainly been examined by using constant loads. In order to quantify the adaptability to varying external forces, a new approach was necessary and considered in the second part of the research program. A device was constructed based on a previously developed pneumatic measurement system. The device should have been able to measure the Adaptive Force (AF) of elbow ex-tensor muscles. The AF determines the adaptability to increasing external forces under isometric (AFiso) and eccentric (AFecc) conditions. At first, it was questioned if these parameters can be relia-bly assessed by use of the new device (publication 4). Subsequently, the main research question was investigated: Is the maximal AFiso a specific and independent variable of muscle function in comparison to the MVIC? Furthermore, both research parts contained a sub-question of how results can be influenced.
Parameters of local oxygen saturation (SvO2) and capillary blood filling (rHb) were non-invasively recorded by a spectrophotometer during maximal and submaximal HIMAs and PIMAs.
These were the main findings: Under load, SvO2 and rHb always adjusted into a steady state after an initial decrease. Nevertheless, their behavior could roughly be categorized into two types. In type I, both parameters behaved nearly parallel to each other. In contrast, their progression over time was partly inverse in type II. The inverse behavior probably depends on the level of deoxygenation since rHb increased reliably at a suggested threshold of about 59% SvO2. This triggered mechanism and the found homeostatic steady states seem to be in conflict with the concept of mechanically compressed capillaries and consequently with a restricted blood flow. Anatomical configuration of blood vessels might provide one hypothetical explanation of how blood flow might be maintained. HIMA and PIMA did not differ regarding oxygenation and allocation to the described types. The TTF tended to be longer during PIMA.
As a sub-question, oxygenation and TTF were compared between (HIMA) and intermittent voluntary muscle twitches during a weight holding task. TTF but not oxygenation differed significantly
(Twitch > HIMA). A changed neuromuscular control might serve as a speculative explanation of how the results can be explained. This is supported by the finding that the TTF did not correlate significantly with the extent of deoxygenation irrespective of the performed task (HIMA, PIMA or Twitch).
Other neuromuscular aspects of muscle function were considered in second part of the re-search program. The new device mentioned above detected different force capacities within four trials at two days each. Among AF measurements, the functional counterpart of a concentric muscle action merging into an isometric one was analyzed in comparison to the MVIC.
Based on the results, it can be assumed that a prior concentric muscle action does not influence the MVIC. However, the results were inconsistent and possibly influenced by systematic errors. In con-trast, maximal variables of the AF (AFisomax and AFeccmax) could be measured in a reliable way which is indicated by a high test-retest reliability. Despite substantial correlations between force variables, the AFisomax differed significantly from MVIC and AFmax, which was identical with AFeccmax in almost all cases. Moreover, AFisomax revealed the highest variability between trials.
These results indicate that maximal force capacities should be assessed separately. The adaptive holding capacity of a muscle can be lower compared to a commonly determined MVIC. This is of relevance since muscles frequently need to respond adequately to external forces. If their response does not correspond to the external impact, the muscle is forced to lengthen. In this scenario, joints are not completely stabilized and an injury may occur. This outlined issue should be addressed in future research in the field of sport and health sciences.
At last, the dissertation presents another possibility to quantify the AFisomax by use of a handheld device applied in combination with a manual muscle test. This assessment delivers a more practical way for clinical purposes.
Job satisfaction has been found to impact behavioral choices at the workplace. Since levels of satisfaction are not guaranteed to remain high, understanding the consequences of job dissatisfaction is essential. Hence, I analyze the relationship between a worker’s job satisfaction and her training investments. Based on my theoretical model, I expect a U-shaped relationship if dissatisfied workers attempt to improve the situation or plan to quit. In contrast, there is an overall positive relationship if dissatisfied workers neglect their duties. Using logit regressions with the Household, Income and Labour Dynamics in Australia (HILDA) survey I find tentative evidence that there is on average an overall positive relationship with a 1 standard deviation increase in job satisfaction being associated with a 1.5% increased likelihood of participating in training. A closer inspection of the reasons for training as well as quit intentions reveals some hints of a U-shaped relationship. My results highlight the importance of considering the source of dissatisfaction as there are heterogeneous effects along different job satisfaction facets.
We present the first systematic literature review on stress and burnout in K−12 teachers during the COVID-19 pandemic. Based on a systematic literature search, we identified 17 studies that included 9,874 K−12 teachers from around the world. These studies showed some indication that burnout did increase during the COVID-19 pandemic. There were, however, almost no differences in the levels of stress and burnout experienced by K−12 teachers compared to individuals employed in other occupational fields. School principals' leadership styles emerged as an organizational characteristic that is highly relevant for K−12 teachers' levels of stress and burnout. Individual teacher characteristics associated with burnout were K−12 teachers' personality, self-efficacy in online teaching, and perceived vulnerability to COVID-19. In order to reduce stress, there was an indication that stress-management training in combination with training in technology use for teaching may be superior to stress-management training alone. Future research needs to adopt more longitudinal designs and examine the interplay between individual and organizational characteristics in the development of teacher stress and burnout during the COVID-19 pandemic and beyond.
The doctoral thesis presented provides a comprehensive view of laser-based ablation techniques promoted to new fields of operation, including, but not limited to, size, composition, and concentration analyses. It covers various applications of laser ablation techniques over a wide range of sizes, from single molecules all the way to aerosol particles. The research for this thesis started with broadening and deepening the field of application and the fundamental understanding of liquid-phase IR-MALDI. Here, the hybridization of ion mobility spectrometry and microfluidics was realized by using IR-MALDI as the coupling technique for the first time. The setup was used for monitoring the photocatalytic performance of the E-Z isomerization of olefins. Using this hybrid, measurement times were so drastically reduced that such photocatalyst screenings became a matter of minutes rather than hours. With this on hand, triple measurements screenings could not only be performed within ten minutes, but also with a minimum amount of resources highlighting its potential as a green chemistry alternative to batch-sized reactions. Along the optimizing process of the IR-MALDI source for microfluidics came its application for another liquid sample supply method, the hanging drop. This demarcated one of the first applications of IR-MALDI for the charging of sub-micron particles directly from suspensions via their gas-phase transfer, followed by their characterization with differential mobility analysis. Given the high spectral quality of the data up to octuply charged particles became experimentally accessible, this laid the foundation for deriving a new charge distribution model for IR-MALDI in that size regime. Moving on to even larger analyte sizes, LIBS and LII were employed as ablation techniques for the solid phase, namely the aerosol particles themselves. Both techniques produce light-emitting events and were used to quantify and classify different aerosols. The unique configuration of stroboscopic imaging, photoacoustics, LII, and LIBS measurements opened new realms for analytical synergies and their potential application in industry. The concept of using low fluences, below 100 J/cm2, and high repetition rates of up to 500 Hz for LIBS makes for an excellent phase-selective LIBS setup. This concept was combined with a new approach to the photoacoustic normalization of LIBS. Also, it was possible to acquire statistically relevant amounts of data in a matter of seconds, showing its potential as a real-time optimization technique. On the same time axis, but at much lower fluences, LII was used with a similar methodology to quickly quantify and classify airborne particles of different compositions. For the first time, aerosol particles were evaluated on their LII susceptibility by using a fluence screening approach.
Learning from failure
(2022)
Regression testing is a widespread practice in today's software industry to ensure software product quality. Developers derive a set of test cases, and execute them frequently to ensure that their change did not adversely affect existing functionality. As the software product and its test suite grow, the time to feedback during regression test sessions increases, and impedes programmer productivity: developers wait longer for tests to complete, and delays in fault detection render fault removal increasingly difficult.
Test case prioritization addresses the problem of long feedback loops by reordering test cases, such that test cases of high failure probability run first, and test case failures become actionable early in the testing process. We ask, given test execution schedules reconstructed from publicly available data, to which extent can their fault detection efficiency improved, and which technique yields the most efficient test schedules with respect to APFD?
To this end, we recover regression 6200 test sessions from the build log files of Travis CI, a popular continuous integration service, and gather 62000 accompanying changelists. We evaluate the efficiency of current test schedules, and examine the prioritization results of state-of-the-art lightweight, history-based heuristics. We propose and evaluate a novel set of prioritization algorithms, which connect software changes and test failures in a matrix-like data structure.
Our studies indicate that the optimization potential is substantial, because the existing test plans score only 30% APFD. The predictive power of past test failures proves to be outstanding: simple heuristics, such as repeating tests with failures in recent sessions, result in efficiency scores of 95% APFD. The best-performing matrix-based heuristic achieves a similar score of 92.5% APFD. In contrast to prior approaches, we argue that matrix-based techniques are useful beyond the scope of effective prioritization, and enable a number of use cases involving software maintenance.
We validate our findings from continuous integration processes by extending a continuous testing tool within development environments with means of test prioritization, and pose further research questions. We think that our findings are suited to propel adoption of (continuous) testing practices, and that programmers' toolboxes should contain test prioritization as an existential productivity tool.
Li and B in ascending magmas: an experimental study on their mobility and isotopic fractionation
(2022)
This research study focuses on the behaviour of Li and B during magmatic ascent, and decompression-driven degassing related to volcanic systems. The main objective of this dissertation is to determine whether it is possible to use the diffusion properties of the two trace elements as a tool to trace magmatic ascent rate. With this objective, diffusion-couple and decompression experiments have been performed in order to study Li and B mobility in intra-melt conditions first, and then in an evolving system during decompression-driven degassing.
Synthetic glasses were prepared with rhyolitic composition and an initial water content of 4.2 wt%, and all the experiments were performed using an internally heated pressure vessel, in order to ensure a precise control on the experimental parameters such as temperature and pressure.
Diffusion-couple experiments were performed with a fix pressure 300 MPa. The temperature was varied in the range of 700-1250 °C with durations between 0 seconds and 24 hours. The diffusion-couple results show that Li diffusivity is very fast and starts already at very low temperature. Significant isotopic fractionation occurs due to the faster mobility of 6Li compared to 7Li. Boron diffusion is also accelerated by the presence of water, but the results of the isotopic ratios are unclear, and further investigation would be necessary to well constrain the isotopic fractionation process of boron in hydrous silicate melts. The isotopic ratios results show that boron isotopic fractionation might be affected by the speciation of boron in the silicate melt structure, as 10B and 11B tend to have tetrahedral and trigonal coordination, respectively.
Several decompression experiments were performed at 900 °C and 1000 °C, with pressures going from 300 MPa to 71-77 MPa and durations of 30 minutes, two, five and ten hours, in order to trigger water exsolution and the formation of vesicles in the sample. Textural observations and the calculation of the bubble number density confirmed that the bubble size and distribution after decompression is directly proportional to the decompression rate.
The overall SIMS results of Li and B show that the two trace elements tend to progressively decrease their concentration with decreasing decompression rates. This is explained because for longer decompression times, the diffusion of Li and B into the bubbles has more time to progress and the melt continuously loses volatiles as the bubbles expand their volumes.
For fast decompression, Li and B results show a concentration increase with a δ7Li and δ11B decrease close to the bubble interface, related to the sudden formation of the gas bubble, and the occurrence of a diffusion process in the opposite direction, from the bubble meniscus to the unaltered melt. When the bubble growth becomes dominant and Li and B start to exsolve into the gas phase, the silicate melt close to the bubble gets depleted in Li and B, because of a stronger diffusion of the trace elements into the bubble.
Our data are being applied to different models, aiming to combine the dynamics of bubble nucleation and growth with the evolution of trace elements concentration and isotopic ratios. Here, first considerations on these models will be presented, giving concluding remarks on this research study. All in all, the final remarks constitute a good starting point for further investigations. These results are a promising base to continue to study this process, and Li and B can indeed show clear dependences on decompression-related magma ascent rates in volcanic systems.
Artificial light at night (ALAN) is altering the behaviour of nocturnal animals in a manifold of ways. Nocturnal invertebrates are particularly affected, due to their fatal attraction to ALAN. This selective pressure has the potential to reduce the strength of the flight-to-light response in insects, as shown recently in a moth species. Here we investigated light attraction of ground beetles (Coleoptera: Carabidae).We compared among animals (three genera) from a highly light polluted (HLP) grassland in the centre of Berlin and animals collected at a low-polluted area in a Dark Sky Reserve (DSR), captured using odour bait. In an arena setting tested at night time, HLP beetles (n = 75 across all genera) showed a reduced attraction towards ALAN. Tested during daytime, HLP beetles were less active in an open field test (measured as latency to start moving), compared to DSR (n = 143). However, we did not observe a reduced attraction towards ALAN within the species most common at both sides, Calathus fuscipes (HLP = 37, DSR = 118 individuals) indicating that not all species may be equally affected by ALAN. Reduced attraction to ALAN in urban beetles may either be a result of phenotypic selection in each generation removing HLP individuals that are attracted to light, or an indication for ongoing evolutionary differentiation among city and rural populations in their light response. Reduced attraction to light sources may directly enhance survival and reproductive success of urban individuals. However, decrease in mobility may negatively influence dispersal, reproduction and foraging success, highlighting the selective pressure that light pollution may have on fitness, by shaping and modifying the behaviour of insects.
The development of novel programmable materials aiming to control friction in real-time holds potential to facilitate innovative lubrication solutions for reducing wear and energy losses. This work describes the integration of light-responsiveness into two lubricating materials, silicon oils and polymer brush surfaces.
The first part focusses on the assessment on 9-anthracene ester-terminated polydimethylsiloxanes (PDMS-A) and, in particular, on the variability of rheological properties and the implications that arise with UV-light as external trigger. The applied rheometer setup contains an UV-transparent quartz-plate, which enables radiation and simultaneous measurement of the dynamic moduli. UV-A radiation (354 nm) triggers the cycloaddition reaction between the terminal functionalities of linear PDMS, resulting in chain extension. The newly-formed anthracene dimers cleave by UV-C radiation (254 nm) or at elevated temperatures (T > 130 °C). The sequential UV-A radiation and thermal reprogramming over three cycles demonstrate high conversions and reproducible programming of rheological properties. In contrast, the photochemical back reaction by UV-C is incomplete and can only partially restore the initial rheological properties. The dynamic moduli increase with each cycle in photochemical programming, presumably resulting from a chain segment re-arrangement as a result of the repeated partial photocleavage and subsequent chain length-dependent dimerization. In addition, long periods of radiation cause photooxidative degradation, which damages photo-responsive functions and consequently reduces the programming range. The absence of oxygen, however, reduces undesired side reactions. Anthracene-functionalized PDMS and native PDMS mix depending on the anthracene ester content and chain length, respectively, and allow fine-tuning of programmable rheological properties. The work shows the influence of mixing conditions during the photoprogramming step on the rheological properties, indicating that material property gradients induced by light attenuation along the beam have to be considered. Accordingly, thin lubricant films are suggested as potential application for light-programmable silicon fluids.
The second part compares strategies for the grafting of spiropyran (SP) containing copolymer brushes from Si wafers and evaluates the light-responsiveness of the surfaces. Pre-experiments on the kinetics of the thermally initiated RAFT copolymerization of 2-hydroxyethyl acrylate (HEA) and spiropyran acrylate (SPA) in solution show, first, a strong retardation by SP and, second, the dependence of SPA polymerization on light. Surprisingly, the copolymerization of SPA is inhibited in the dark. These findings contribute to improve the synthesis of polar, spiropyran-containing copolymers. The comparison between initiator systems for the grafting-from approach indicates PET-RAFT superior to thermally initiated RAFT, suggesting a more efficient initiation of surface-bound CTA by light. Surface-initiated polymerization via PET-RAFT with an initiator system of EosinY (EoY) and ascorbic acid (AscA) facilitates copolymer synthesis from HEA and 5-25 mol% SPA. The resulting polymer film with a thickness of a few nanometers was detected by atomic force microscopy (AFM) and ellipsometry. Water contact angle (CA) measurements demonstrate photo-switchable surface polarity, which is attributed to the photoisomerization between non-polar spiropyran and zwitterionic merocyanine isomer. Furthermore, the obtained spiropyran brushes show potential for further studies on light-programmable properties. In this context, it would be interesting to investigate whether swollen spiropyran-containing polymers change their configuration and thus their film thickness under the influence of light. In addition, further experiments using an AFM or microtribometer should evaluate whether light-programmable solvation enables a change in frictional properties between polymer brush surfaces.
Studies have revealed mixed results on how antidepressant drugs affect lipid profiles of patients with major depression disorder (MDD). Even less is known about how patients respond to a switch of antidepressant medication with respect to their metabolic profile. For this, effects of a switch in antidepressants medication on lipid markers were studied in MDD patients. 15 participants (females = 86.67%; males = 13.33%; age: 49.45 ± 7.45 years) with MDD and a prescribed switch in their antidepressant medication were recruited at a psychosomatic rehabilitation clinic. Participants were characterized (with questionnaires and blood samples) at admission to the rehabilitation clinic (baseline, T0) and followed up with a blood sample two weeks (T1) later. HDL, LDL, total cholesterol, and triglycerides were determined (T0), and their change analyzed (Wilcoxon test) at follow up (T1). Decrements in HDL (p = 0.041), LDL (p < 0.001), and total cholesterol (p < 0.001) were observed two weeks after a switch in antidepressant medication. Triglycerides showed no difference (p = 0.699). Overall, LDL, HDL, and total cholesterol are affected by a change in antidepressant drugs in patients with MDD. These observations are of clinical relevance for medical practitioners in the planning and management of treatment strategies for MDD patients.
Background
The association between bivariate variables may not necessarily be homogeneous throughout the whole range of the variables. We present a new technique to describe inhomogeneity in the association of bivariate variables.
Methods
We consider the correlation of two normally distributed random variables. The 45° diagonal through the origin of coordinates represents the line on which all points would lie if the two variables completely agreed. If the two variables do not completely agree, the points will scatter on both sides of the diagonal and form a cloud. In case of a high association between the variables, the band width of this cloud will be narrow, in case of a low association, the band width will be wide. The band width directly relates to the magnitude of the correlation coefficient. We then determine the Euclidean distances between the diagonal and each point of the bivariate correlation, and rotate the coordinate system clockwise by 45°. The standard deviation of all Euclidean distances, named “global standard deviation”, reflects the band width of all points along the former diagonal. Calculating moving averages of the standard deviation along the former diagonal results in “locally structured standard deviations” and reflect patterns of “locally structured correlations (LSC)”. LSC highlight inhomogeneity of bivariate correlations. We exemplify this technique by analyzing the association between body mass index (BMI) and hip circumference (HC) in 6313 healthy East German adults aged 18 to 70 years.
Results
The correlation between BMI and HC in healthy adults is not homogeneous. LSC is able to identify regions where the predictive power of the bivariate correlation between BMI and HC increases or decreases, and highlights in our example that slim people have a higher association between BMI and HC than obese people.
Conclusion
Locally structured correlations (LSC) identify regions of higher or lower than average correlation between two normally distributed variables.
Text collections, such as corpora of books, research articles, news, or business documents are an important resource for knowledge discovery. Exploring large document collections by hand is a cumbersome but necessary task to gain new insights and find relevant information. Our digitised society allows us to utilise algorithms to support the information seeking process, for example with the help of retrieval or recommender systems. However, these systems only provide selective views of the data and require some prior knowledge to issue meaningful queries and asses a system’s response. The advancements of machine learning allow us to reduce this gap and better assist the information seeking process. For example, instead of sighting countless business documents by hand, journalists and investigator scan employ natural language processing techniques, such as named entity recognition. Al-though this greatly improves the capabilities of a data exploration platform, the wealth of information is still overwhelming. An overview of the entirety of a dataset in the form of a two-dimensional map-like visualisation may help to circumvent this issue. Such overviews enable novel interaction paradigms for users, which are similar to the exploration of digital geographical maps. In particular, they can provide valuable context by indicating how apiece of information fits into the bigger picture.This thesis proposes algorithms that appropriately pre-process heterogeneous documents and compute the layout for datasets of all kinds. Traditionally, given high-dimensional semantic representations of the data, so-called dimensionality reduction algorithms are usedto compute a layout of the data on a two-dimensional canvas. In this thesis, we focus on text corpora and go beyond only projecting the inherent semantic structure itself. Therefore,we propose three dimensionality reduction approaches that incorporate additional information into the layout process: (1) a multi-objective dimensionality reduction algorithm to jointly visualise semantic information with inherent network information derived from the underlying data; (2) a comparison of initialisation strategies for different dimensionality reduction algorithms to generate a series of layouts for corpora that grow and evolve overtime; (3) and an algorithm that updates existing layouts by incorporating user feedback provided by pointwise drag-and-drop edits. This thesis also contains system prototypes to demonstrate the proposed technologies, including pre-processing and layout of the data and presentation in interactive user interfaces.
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.
Mammalian arachidonic acid lipoxygenases (ALOXs) have been implicated in cell differentiation and in the pathogenesis of inflammation. The mouse genome involves seven functional Alox genes and the encoded enzymes share a high degree of amino acid conservation with their human orthologs. There are, however, functional differences between mouse and human ALOX orthologs. Human ALOX15B oxygenates arachidonic acid exclusively to its 15-hydroperoxy derivative (15S-HpETE), whereas 8S-HpETE is dominantly formed by mouse Alox15b. The structural basis for this functional difference has been explored and in vitro mutagenesis humanized the reaction specificity of the mouse enzyme. To explore whether this mutagenesis strategy may also humanize the reaction specificity of mouse Alox15b in vivo, we created Alox15b knock-in mice expressing the arachidonic acid 15-lipoxygenating Tyr603Asp+His604Val double mutant instead of the 8-lipoxygenating wildtype enzyme. These mice are fertile, display slightly modified plasma oxylipidomes and develop normally up to an age of 24 weeks. At later developmental stages, male Alox15b-KI mice gain significantly less body weight than outbred wildtype controls, but this effect was not observed for female individuals. To explore the possible reasons for the observed gender-specific growth arrest, we determined the basic hematological parameters and found that aged male Alox15b-KI mice exhibited significantly attenuated red blood cell parameters (erythrocyte counts, hematocrit, hemoglobin). Here again, these differences were not observed in female individuals. These data suggest that humanization of the reaction specificity of mouse Alox15b impairs the functionality of the hematopoietic system in males, which is paralleled by a premature growth arrest.
We provide the first estimates of the impact of managers’ risk preferences on their training allocation decisions. Our conceptual framework links managers’ risk preferences to firms’ training decisions through the bonuses they expect to receive. Risk-averse managers are expected to select workers with low turnover risk and invest in specific rather than general training. Empirical evidence supporting these predictions is provided using a novel vignette study embedded in a nationally representative survey of firm managers. Risk-tolerant and risk-averse decision makers have significantly different training preferences. Risk aversion results in increased sensitivity to turnover risk. Managers who are risk-averse offer significantly less general training and, in some cases, are more reluctant to train workers with a history of job mobility. All managers, irrespective of their risk preferences, are sensitive to the investment risk associated with training, avoiding training that is more costly or targets those with less occupational expertise or nearing retirement. This suggests the risks of training are primarily due to the risk that trained workers will leave the firm (turnover risk) rather than the risk that the benefits of training do not outweigh the costs (investment risk).
Background
Maximal isokinetic strength ratios of joint flexors and extensors are important parameters to indicate the level of muscular balance at the joint. Further, in combat sports athletes, upper and lower limb muscle strength is affected by the type of sport. Thus, this study aimed to examine the differences in maximal isokinetic strength of the flexors and extensors and the corresponding flexor–extensor strength ratios of the elbows and knees in combat sports athletes.
Method
Forty male participants (age = 22.3 ± 2.5 years) from four different combat sports (amateur boxing, taekwondo, karate, and judo; n = 10 per sport) were tested for eccentric peak torque of the elbow/knee flexors (EF/KF) and concentric peak torque of the elbow/knee extensors (EE/KE) at three different angular velocities (60, 120, and 180°/s) on the dominant and non-dominant side using an isokinetic device.
Results
Analyses revealed significant, large-sized group × velocity × limb interactions for EF, EE, and EF–EE ratio, KF, KE, and KF–KE ratio (p ≤ 0.03; 0.91 ≤ d ≤ 1.75). Post-hoc analyses indicated that amateur boxers displayed the largest EE strength values on the non-dominant side at ≤ 120°/s and the dominant side at ≥ 120°/s (p < 0.03; 1.21 ≤ d ≤ 1.59). The largest EF–EE strength ratios were observed on amateur boxers’ and judokas’ non-dominant side at ≥ 120°/s (p < 0.04; 1.36 ≤ d ≤ 2.44). Further, we found lower KF–KE strength measures in karate (p < 0.04; 1.12 ≤ d ≤ 6.22) and judo athletes (p ≤ 0.03; 1.60 ≤ d ≤ 5.31) particularly on the non-dominant side.
Conclusions
The present findings indicated combat sport-specific differences in maximal isokinetic strength measures of EF, EE, KF, and KE particularly in favor of amateur boxers on the non-dominant side.
Strategic uncertainty is the uncertainty that players face with respect to the purposeful behavior of other players in an interactive decision situation. Our paper develops a new method for measuring strategic-uncertainty attitudes and distinguishing them from risk and ambiguity attitudes. We vary the source of uncertainty (whether strategic or not) across conditions in a ceteris paribus manner. We elicit certainty equivalents of participating in two strategic 2x2 games (a stag-hunt and a market-entry game) as well as certainty equivalents of related lotteries that yield the same possible payoffs with exogenously given probabilities (risk) and lotteries with unknown probabilities (ambiguity). We provide a structural model of uncertainty attitudes that allows us to measure a preference for or an aversion against the source of uncertainty, as well as optimism or pessimism regarding the desired outcome. We document systematic attitudes towards strategic uncertainty that vary across contexts. Under strategic complementarity [substitutability], the majority of participants tend to be pessimistic [optimistic] regarding the desired outcome. However, preferences for the source of uncertainty are distributed around zero.
Many participants in Massive Open Online Courses are full-time employees seeking greater flexibility in their time commitment and the available learning paths. We recently addressed these requirements by splitting up our 6-week courses into three 2-week modules followed by a separate exam. Modularizing courses offers many advantages: Shorter modules are more sustainable and can be combined, reused, and incorporated into learning paths more easily. Time flexibility for learners is also improved as exams can now be offered multiple times per year, while the learning content is available independently. In this article, we answer the question of which impact this modularization has on key learning metrics, such as course completion rates, learning success, and no-show rates. Furthermore, we investigate the influence of longer breaks between modules on these metrics. According to our analysis, course modules facilitate more selective learning behaviors that encourage learners to focus on topics they are the most interested in. At the same time, participation in overarching exams across all modules seems to be less appealing compared to an integrated exam of a 6-week course. While breaks between the modules increase the distinctive appearance of individual modules, a break before the final exam further reduces initial interest in the exams. We further reveal that participation in self-paced courses as a preparation for the final exam is unlikely to attract new learners to the course offerings, even though learners' performance is comparable to instructor-paced courses. The results of our long-term study on course modularization provide a solid foundation for future research and enable educators to make informed decisions about the design of their courses.
The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.
Deep geological repositories represent a promising solution for the final disposal of nuclear waste. Due to its low permeability, high sorption capacity and self-sealing potential, Opalinus Clay (OPA) is considered a suitable host rock formation for the long-term storage of nuclear waste in Switzerland and Germany. However, the clay formation is characterized by compositional and structural variabilities including the occurrence of carbonate- and quartz-rich layers, pronounced bedding planes as well as tectonic elements such as pre-existing fault zones and fractures, suggesting heterogeneous rock mass properties.
Characterizing the heterogeneity of host rock properties is therefore essential for safety predictions of future repositories. This includes a detailed understanding of the mechanical and hydraulic properties, deformation behavior and the underlying deformation processes for an improved assessment of the sealing integrity and long-term safety of a deep repository in OPA. Against this background, this thesis presents the results of deformation experiments performed on intact and artificially fractured specimens of the quartz-rich, sandy and clay-rich, shaly facies of OPA. The experiments focus on the influence of mineralogical composition on the deformation behavior as well as the reactivation and sealing properties of pre-existing faults and fractures at different boundary conditions (e.g., pressure, temperature, strain rate).
The anisotropic mechanical properties of the sandy facies of OPA are presented in the first section, which were determined from triaxial deformation experiments using dried and resaturated samples loaded at 0°, 45° and 90° to the bedding plane orientation. A Paterson-type deformation apparatus was used that allowed to investigate how the deformation behavior is influenced by the variation of confining pressure (50 – 100 MPa), temperature (25 – 200 °C), and strain rate (1 × 10-3 – 5 × 10-6 s-1). Constant strain rate experiments revealed brittle to semi-brittle deformation behavior of the sandy facies at the applied conditions. Deformation behavior showed a strong dependence on confining pressure, degree of water saturation as well as bedding orientation, whereas the variation of temperature and strain rate had no significant effect on deformation. Furthermore, the sandy facies displays higher strength and stiffness compared to the clay-rich shaly facies deformed at similar conditions by Nüesch (1991). From the obtained results it can be concluded that cataclastic mechanisms dominate the short-term deformation behavior of dried samples from both facies up to elevated pressure (<200 MPa) and temperature (<200 °C) conditions.
The second part presents triaxial deformation tests that were performed to investigate how structural discontinuities affect the deformation behavior of OPA and how the reactivation of preexisting faults is influenced by mineral composition and confining pressure. To this end, dried cylindrical samples of the sandy and shaly facies of OPA were used, which contained a saw-cut fracture oriented at 30° to the long axis. After hydrostatic pre-compaction at 50 MPa, constant strain rate deformation tests were performed at confining pressures of 5, 20 or 35 MPa. With increasing confinement, a gradual transition from brittle, highly localized fault slip including a stress drop at fault reactivation to semi-brittle deformation behavior, characterized by increasing delocalization and non-linear strain hardening without dynamic fault reactivation, can be observed. Brittle localization was limited by the confining pressure at which the fault strength exceeded the matrix yield strength, above which strain partitioning between localized fault slip and distributed matrix deformation occurred. The sandy facies displayed a slightly higher friction coefficient (≈0.48) compared to the shaly facies (≈0.4). In addition, slide-hold-slide tests were conducted, revealing negative or negligible frictional strengthening, which suggests stable creep and long-term weakness of faults in both facies of OPA. The conducted experiments demonstrate that dilatant brittle fault reactivation in OPA may be favored at high overconsolidation ratios and shallow depths, increasing the risk of seismic hazard and the creation of fluid pathways.
The final section illustrates how the sealing capacity of fractures in OPA is affected by mineral composition. Triaxial flow-through experiments using Argon-gas were performed with dried samples from the sandy and shaly facies of OPA containing a roughened, artificial fracture. Slate, graywacke, quartzite, natural fault gouge, and granite samples were also tested to highlight the influence of normal stress, mineralogy and diagenesis on the sustainability of fracture transmissivity. With increasing normal stress, a non-linear decrease of fracture transmissivity can be observed that resulted in a permanent reduction of transmissivity after stress release. The transmissivity of rocks with a high portion of strong minerals (e.g., quartz) and high unconfined compressive strength was less sensitive to stress changes. In accordance with this, the sandy facies of OPA displayed a higher initial transmissivity that was less sensitive to stress changes compared to the shaly facies. However, transmissivity of rigid slate was less sensitive to stress changes than the sandy facies of OPA, although the slate is characterized by a higher phyllosilicate content. This demonstrates that in addition to mineral composition, other factors such as the degree of metamorphism, cementation and consolidation have to be considered when evaluating the sealing capacity of phyllosilicate-rich rocks.
The results of this thesis highlighted the role of confining pressure on the failure behavior of intact and artificially fractured OPA. Although the quartz-rich sandy facies may be considered as being more favorable for underground constructions due to its higher shear strength and stiffness than the shaly facies, the results indicate that when fractures develop in the sandy facies, they are more conductive and remain more permeable compared to fractures in the clay-dominated shaly facies at a given stress. The results may provide the basis for constitutive models to predict the integrity and evolution of a future repository. Clearly, the influence of composition and consolidation, e.g., by geological burial and uplift, on the mechanical sealing behavior of OPA highlights the need for a detailed site-specific material characterization for a future repository.
The Covid-19 pandemic imposed new constraints on empirical research and forced researchers to transfer from traditional laboratory research to the online environment. This study tested the validity of a web-based episodic memory paradigm by comparing participants’ memory performance for trustworthy and untrustworthy facial stimuli in a supervised laboratory setting and an unsupervised web setting. Consistent with previous results, we observed enhanced episodic memory for untrustworthy compared to trustworthy faces. Most importantly, this memory bias was comparable in the online and the laboratory experiment, suggesting that web-based procedures are a promising tool for memory research.
Microplastics in the environments are estimated to increase in the near future due to increasing consumption of plastic product and also due to further fragmentation in small pieces. The fate and effects of MP once released into the freshwater environment are still scarcely studied, compared to the marine environment. In order to understand possible effect and interaction of MPs in freshwater environment, planktonic zooplankton organisms are very useful for their crucial trophic role. In particular freshwater rotifers are one of the most abundant organisms and they are the interface between primary producers and secondary consumers. The aim of my thesis was to investigate the ingestion and the effect of MPs in rotifers from a more natural scenario and to individuate processes such as the aggregation of MPs, the food dilution effect and the increasing concentrations of MPs that could influence the final outcome of MPs in the environment. In fact, in a near natural scenario MPs interaction with bacteria and algae, aggregations together with the size and concentration are considered drivers of ingestion and effect. The aggregation of MPs makes smaller MPs more available for rotifers and larger MPs less ingested. The negative effect caused by the ingestion of MPs was modulated by their size but also by the quantity and the quality of food that cause variable responses. In fact, rotifers in the environment are subjected to food limitation and the presence of MPs could exacerbate this condition and decrease the population and the reproduction input. Finally, in a scenario incorporating an entire zooplanktonic community, MPs were ingested by most individuals taking into account their feeding mode but also the concentration of MPs, which was found to be essential for the availability of MPs. This study highlights the importance to investigate MPs from a more environmental perspective, this in fact could provide an alternative and realistic view of effect of MPs in the ecosystem.
On January 1, 2015, Germany introduced a general statutory minimum wage of €8.50 gross per hour. This thesis analyses the effects of the minimum wage introduction in Germany as well as wage floors in the European context, contributing to national and international research.
The second chapter of this dissertation summarizes the short-run effects of the minimum wage reform found in previous studies.
We show that the introduction of the minimum wage had a positive effect on wages at the bottom of the distribution. Yet, there was still a significant amount of non-compliance shortly after the reform. Additionally, previous evidence points to small negative employment effects mainly driven by a reduction in mini-jobs. Contrary to expectations, though, there were no effects on poverty and general inequality found in the short run. This is mostly due to the fact that working hours were reduced and the increase of hourly wages was therefore not reflected in monthly wages.
The third chapter identifies whether the job losses predicted in ex-ante studies materialized in the short run and, if so, which type of employment was affected the most. To identify the effects, this chapter (as well as chapter four) uses a regional difference-in-difference approach to estimate the effects on regular employment (part- and full-time) and mini-jobs.
Our results suggest that the minimum wage has slightly reduced overall employment, mainly due to a decline in mini-jobs.
The fourth chapter has the same methodological approach as the previous one. Its motivated by the fact that women are often overrepresented among low-wage employees. Thus, the primary research question in this chapter is whether the minimum wage has led to a narrowing of the gender wage gap. In order to answer that, we identify the effects on the wage gap at the 10th and 25th percentiles and at the mean of the underlying gender-specific wage distributions. Our results imply that for eligible employees the gender wage gap at the 10th percentile decreased by 4.6 percentage points between 2014 and 2018 in high-bite regions compared to low-bite regions. We estimate this to be a reduction of 32% compared to 2014. Higher up the distribution – i.e. at the 25th percentile and the mean – the effects are smaller and not as robust.
The fifth chapter keeps the gender-specific emphasis on minimum wage effects. However, in contrast to the rest of the dissertation, it widens the scope to other European Union countries. Following the rationale of the previous chapter, women could potentially benefit particularly from a minimum wage. However, they could also be more prone to suffer from the possibly induced job losses or reductions in working hours. Therefore, this chapter summarizes existing evidence from EU member states dealing with the relationship between wage floors and the gender wage gap. In addition, it provides a systematic summary of studies that examine the impact of minimum wages on employment losses or changes in working hours that particularly affect women. The evidence shows that higher wage floors are often associated with smaller gender wage gaps. With respect to employment, women do not appear to experience greater employment losses than men per se. However, studies show that the minimum wage has a particular impact on part-time workers. Therefore, it cannot be ruled out that the negative correlation between the minimum wage and the gender wage gap is related to the job losses of these lower-paid, often female, part-time workers. This working arrangement should therefore be specially focused on in the context of minimum wages.
This dissertation aimed to determine differential expressed miRNAs in the context of chronic pain in polyneuropathy. For this purpose, patients with chronic painful polyneuropathy were compared with age matched healthy patients. Taken together, all miRNA pre library preparation quality controls were successful and none of the samples was identified as an outlier or excluded for library preparation. Pre sequencing quality control showed that library preparation worked for all samples as well as that all samples were free of adapter dimers after BluePippin size selection and reached the minimum molarity for further processing. Thus, all samples were subjected to sequencing. The sequencing control parameters were in their optimal range and resulted in valid sequencing results with strong sample to sample correlation for all samples. The resulting FASTQ file of each miRNA library was analyzed and used to perform a differential expression analysis. The differentially expressed and filtered miRNAs were subjected to miRDB to perform a target prediction. Three of those four miRNAs were downregulated: hsa-miR-3135b, hsa-miR-584-5p and hsa-miR-12136, while one was upregulated: hsa-miR-550a-3p. miRNA target prediction showed that chronic pain in polyneuropathy might be the result of a combination of miRNA mediated high blood flow/pressure and neural activity dysregulations/disbalances. Thus, leading to the promising conclusion that these four miRNAs could serve as potential biomarkers for the diagnosis of chronic pain in polyneuropathy.
Since TRPV1 seems to be one of the major contributors of nociception and is associated with neuropathic pain, the influence of PKA phosphorylated ARMS on the sensitivity of TRPV1 as well as the part of AKAP79 during PKA phosphorylation of ARMS was characterized. Therefore, possible PKA-sites in the sequence of ARMS were identified. This revealed five canonical PKA-sites: S882, T903, S1251/52, S1439/40 and S1526/27. The single PKA-site mutants of ARMS revealed that PKA-mediated ARMS phosphorylation seems not to influence the interaction rate of TRPV1/ARMS. While phosphorylation of ARMST903 does not increase the interaction rate with TRPV1, ARMSS1526/27 is probably not phosphorylated and leads to an increased interaction rate. The calcium flux measurements indicated that the higher the interaction rate of TRPV1/ARMS, the lower the EC50 for capsaicin of TRPV1, independent of the PKA phosphorylation status of ARMS. In addition, the western blot analysis confirmed the previously observed TRPV1/ARMS interaction. More importantly, AKAP79 seems to be involved in the TRPV1/ARMS/PKA signaling complex. To overcome the problem of ARMS-mediated TRPV1 sensitization by interaction, ARMS was silenced by shRNA. ARMS silencing resulted in a restored TRPV1 desensitization without affecting the TRPV1 expression and therefore could be used as new topical therapeutic analgesic alternative to stop ARMS mediated TRPV1 sensitization.
Eight d-metal-containing N-butylpyridinium ionic liquids (ILs) with the nominal composition (C4Py)2[Ni0.5M0.5Cl4] or (C4Py)2[Zn0.5M0.5Cl4] (M = Cu, Co, Mn, Ni, Zn; C4Py = N-butylpyridinium) were synthesized, characterized, and investigated for their optical properties. Single crystal and powder X-ray analysis shows that the compounds are isostructural to existing examples based on other d-metal ions. Inductively coupled plasma optical emission spectroscopy measurements confirm that the metal/metal ratio is around 50 : 50. UV-Vis spectroscopy shows that the optical absorption can be tuned by selection of the constituent metals. Moreover, the compounds can act as an optical sensor for the detection of gases such as ammonia as demonstrated via a simple prototype setup.
Modeling and Formal Analysis of Meta-Ecosystems with Dynamic Structure using Graph Transformation
(2022)
The dynamics of ecosystems is of crucial importance. Various model-based approaches exist to understand and analyze their internal effects. In this paper, we model the space structure dynamics and ecological dynamics of meta-ecosystems using the formal technique of Graph Transformation (short GT). We build GT models to describe how a meta-ecosystem (modeled as a graph) can evolve over time (modeled by GT rules) and to analyze these GT models with respect to qualitative properties such as the existence of structural stabilities. As a case study, we build three GT models describing the space structure dynamics and ecological dynamics of three different savanna meta-ecosystems. The first GT model considers a savanna meta-ecosystem that is limited in space to two ecosystem patches, whereas the other two GT models consider two savanna meta-ecosystems that are unlimited in the number of ecosystem patches and only differ in one GT rule describing how the space structure of the meta-ecosystem grows. In the first two GT models, the space structure dynamics and ecological dynamics of the meta-ecosystem shows two main structural stabilities: the first one based on grassland-savanna-woodland transitions and the second one based on grassland-desert transitions. The transition between these two structural stabilities is driven by high-intensity fires affecting the tree components. In the third GT model, the GT rule for savanna regeneration induces desertification and therefore a collapse of the meta-ecosystem. We believe that GT models provide a complementary avenue to that of existing approaches to rigorously study ecological phenomena.
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.
Science education researchers have developed a refined understanding of the structure of science teachers’ pedagogical content knowledge (PCK), but how to develop applicable and situation-adequate PCK remains largely unclear. A potential problem lies in the diverse conceptualisations of the PCK used in PCK research. This study sought to systematize existing science education research on PCK through the lens of the recently proposed refined consensus model (RCM) of PCK. In this review, the studies’ approaches to investigating PCK and selected findings were characterised and synthesised as an overview comparing research before and after the publication of the RCM. We found that the studies largely employed a qualitative case-study methodology that included specific PCK models and tools. However, in recent years, the studies focused increasingly on quantitative aspects. Furthermore, results of the reviewed studies can mostly be integrated into the RCM. We argue that the RCM can function as a meaningful theoretical lens for conceptualizing links between teaching practice and PCK development by proposing pedagogical reasoning as a mechanism and/or explanation for PCK development in the context of teaching practice.
The current generation of ground-based instruments has rapidly extended the limits of the range accessible to us with very-high-energy (VHE) gamma-rays, and more than a hundred sources have now been detected in the Milky Way. These sources represent only the tip of the iceberg, but their number has reached a level that allows population studies. In this work, a model of the global population of VHE gamma-ray sources based on the most comprehensive census of Galactic sources in this energy regime, the H.E.S.S. Galactic plane survey (HGPS), will be presented. A population synthesis approach was followed in the construction of the model. Particular attention was paid to correcting for the strong observational bias inherent in the sample of detected sources. The methods developed for estimating the model parameters have been validated with extensive Monte Carlo simulations and will be shown to provide unbiased estimates of the model parameters. With these methods, five models for different spatial distributions of sources have been constructed. To test the validity of these models, their predictions for the composition of sources within the sensitivity range of the HGPS are compared with the observed sample. With one exception, similar results are obtained for all spatial distributions, showing that the observed longitude profile and the source distribution over photon flux are in fair agreement with observation. Regarding the latitude profile and the source distribution over angular extent, it becomes apparent that the model needs to be further adjusted to bring its predictions in agreement with observation. Based on the model, predictions of the global properties of the Galactic population of VHE gamma-ray sources and the prospects of the Cherenkov Telescope Array (CTA) will be presented.
CTA will significantly increase our knowledge of VHE gamma-ray sources by lowering the threshold for source detection, primarily through a larger detection area compared to current-generation instruments. In ground-based gamma-ray astronomy, the sensitivity of an instrument depends strongly, in addition to the detection area, on the ability to distinguish images of air showers produced by gamma-rays from those produced by cosmic rays, which are a strong background. This means that the number of detectable sources depends on the background rejection algorithm used and therefore may also be increased by improving the performance of such algorithms. In this context, in addition to the population model, this work presents a study on the application of deep-learning techniques to the task of gamma-hadron separation in the analysis of data from ground-based gamma-ray instruments. Based on a systematic survey of different neural-network architectures, it is shown that robust classifiers can be constructed with competitive performance compared to the best existing algorithms. Despite the broad coverage of neural-network architectures discussed, only part of the potential offered by the
application of deep-learning techniques to the analysis of gamma-ray data is exploited in the context of this study. Nevertheless, it provides an important basis for further research on this topic.
Macrophages play an integral role for the innate immune system. It is critically important for basic research and therapeutic applications to find approaches to potentially modulate their function as the first line of defense. Transient genetic engineering via delivery of synthetic mRNA can serve for such purposes as a robust, reliable and safe technology to modulate macrophage functions. However, a major drawback particularly in the transfection of sensitive immune cells such as macrophages is the immunogenicity of exogenous IVT-mRNAs. Consequently, the direct modulation of human macrophage activity by mRNA-mediated genetic engineering was the aim of this work. The synthetic mRNA can instruct macrophages to synthesize specific target proteins, which can steer macrophage activity in a tailored fashion. Thus, the focus of this dissertation was to identify parameters triggering unwanted immune activation of macrophages, and to find approaches to minimize such effects. When comparing different carrier types as well as mRNA chemistries, the latter had unequivocally a more pronounced impact on activation of human macrophages and monocytes. Exploratory investigations revealed that the choice of nucleoside chemistry, particularly of modified uridine, plays a crucial role for IVT-mRNA-induced immune activation, in a dose-dependent fashion. Additionally, the contribution of the various 5’ cap structures tested was only minor. Moreover, to address the technical aspects of the delivery of multiple genes as often mandatory for advanced gene delivery studies, two different strategies of payload design were investigated, namely “bicistronic” delivery and “monocistronic” co-delivery. The side-by-side comparison of mRNA co-delivery via a bicistronic design (two genes, one mRNA) with a monocistronic design (two gene, two mRNAs) unexpectedly revealed that, despite the intrinsic equimolar nature of the bicistronic approach, it was outperformed by the monocistronic approach in terms of reliable co-expression when quantified on the single cell level. Overall, the incorporation of chemical modifications into IVT-mRNA by using respective building blocks, primarily with the aim to minimize immune activation as exemplified in this thesis, has the potential to facilitate the selection of the proper mRNA chemistry to address specific biological and clinical challenges. The technological aspects of gene delivery evaluated and validated by the quantitative methods allowed us to shed light on crucial process parameters and mRNA design criteria, required for reliable co-expression schemes of IVT-mRNA delivery.
Plants can be primed to survive the exposure to a severe heat stress (HS) by prior exposure to a mild HS. The information about the priming stimulus is maintained by the plant for several days. This maintenance of acquired thermotolerance, or HS memory, is genetically separable from the acquisition of thermotolerance itself and several specific regulatory factors have been identified in recent years.
On the molecular level, HS memory correlates with two types of transcriptional memory, type I and type II, that characterize a partially overlapping subset of HS-inducible genes. Type I transcriptional memory or sustained induction refers to the sustained transcriptional induction above non-stressed expression levels of a gene for a prolonged time period after the end of the stress exposure. Type II transcriptional memory refers to an altered transcriptional response of a gene after repeated exposure to a stress of similar duration and intensity. In particular, enhanced re-induction refers to a transcriptional pattern in which a gene is induced to a significantly higher degree after the second stress exposure than after the first.
This thesis describes the functional characterization of a novel positive transcriptional regulator of type I transcriptional memory, the heat shock transcription factor HSFA3, and compares it to HSFA2, a known positive regulator of type I and type II transcriptional memory. It investigates type I transcriptional memory and its dependence on HSFA2 and HSFA3 for the first time on a genome-wide level, and gives insight on the formation of heteromeric HSF complexes in response to HS. This thesis confirms the tight correlation between transcriptional memory and H3K4 hyper-methylation, reported here in a case study that aimed to reduce H3K4 hyper-methylation of the type II transcriptional memory gene APX2 by CRISPR/dCas9-mediated epigenome editing. Finally, this thesis gives insight into the requirements for a heat shock transcription factor to function as a positive regulator of transcriptional memory, both in terms of its expression profile and protein abundance after HS and the contribution of individual functional domains.
In summary, this thesis contributes to a more detailed understanding of the molecular processes underlying transcriptional memory and therefore HS memory, in Arabidopsis thaliana.
The world energy consumption has constantly increased every year due to economic development and population growth. This inevitably caused vast amount of CO2 emission, and the CO2 concentration in the atmosphere keeps increasing with economic growth. To reduce CO2 emission, various methods have been developed but there are still many bottlenecks to be solved. Solvents easily absorbing CO2 such as monoethanol-amine (MEA) and diethanolamine, for example, have limitations of solvent loss, amine degradation, vulnerability to heat and toxicity, and the high cost of regeneration which is especially caused due to chemisorption process. Though some of these drawbacks can be compensated through physisorption with zeolites and metal-organic frameworks (MOFs) by displaying significant adsorption selectivity and capacity even in ambient conditions, limitations for these materials still exist. Zeolites demand relatively high regeneration energy and have limited adsorption kinetics due to the exceptionally narrow pore structure. MOFs have low stability against heat and moisture and high manufacturing cost.
Nanoporous carbons have recently received attention as an attractive functional porous material due to their unique properties. These materials are crucial in many applications of modern science and industry such as water and air purification, catalysis, gas separation, and energy storage/conversion due to their high chemical and thermal stability, and in particular electronic conductivity in combination with high specific surface areas. Nanoporous carbons can be used to adsorb environmental pollutants or small gas molecules such as CO2 and to power electrochemical energy storage devices such as batteries and fuel cells. In all fields, their pore structure or electrical properties can be modified depending on their purposes.
This thesis provides an in-depth look at novel nanoporous carbons from the synthetic and the application point of view. The interplay between pore structure, atomic construction, and the adsorption properties of nanoporous carbon materials are investigated. Novel nanoporous carbon materials are synthesized by using simple precursor molecules containing heteroatoms through a facile
templating method. The affinity, and in turn the adsorption capacity, of carbon materials toward polar gas molecules (CO2 and H2O) is enhanced by the modification of their chemical construction. It is also shown that these properties are important in electrochemical energy storage, here especially for supercapacitors with aqueous electrolytes which are basically based on the physisorption of ions on carbon surfaces. This shows that nanoporous carbons can be a “functional” material with specific physical or chemical interactions with guest species just like zeolites and MOFs.
The synthesis of sp2-conjugated materials with high heteroatom content from a mixture of citrazinic acid and melamine in which heteroatoms are already bonded in specific motives is illustrated. By controlling the removal procedure of the salt-template and the condensation temperature, the role of salts in the formation of porosity and as coordination sites for the stabilization of heteroatoms is proven. A high amount of nitrogen of up to 20 wt. %, oxygen contents of up to 19 wt.%, and a high CO2/N2 selectivity with maximum CO2 uptake at 273 K of 5.31 mmol g–1 are achieved. Besides, the further controlled thermal condensation of precursor molecules and advanced functional properties on applications of the synthesized porous carbons are described. The materials have different porosity and atomic construction exhibiting a high nitrogen content up to 25 wt. % as well as a high porosity with a specific surface area of more than 1800 m2 g−1, and a high performance in selective CO2 gas adsorption of 62.7. These pore structure as well as properties of surface affect to water adsorption with a remarkably high Qst of over 100 kJ mol−1 even higher than that of zeolites or CaCl2 well known as adsorbents. In addition to that, the pore structure of HAT-CN-derived carbon materials during condensation in vacuum is fundamentally understood which is essential to maximize the utilization of porous system in materials showing significant difference in their pore volume of 0.5 cm3 g−1 and 0.25 cm3 g−1 without and with vacuum, respectively.
The molecular designs of heteroatom containing porous carbon derived from abundant and simple molecules are introduced in the presented thesis. Abundant precursors that already containing high amount of nitrogen or oxygen are beneficial to achieve enhanced interaction with adsorptives. The physical and chemical properties of these heteroatom-doped porous carbons are affected by mainly two parameters, that is, the porosity from the pore structure and the polarity from the atomic composition on the surface. In other words, controlling the porosity as well as the polarity of the carbon materials is studied to understand interactions with different guest species which is a fundamental knowledge for the utilization on various applications.
Background
Isometric muscle actions can be performed either by initiating the action, e.g., pulling on an immovable resistance (PIMA), or by reacting to an external load, e.g., holding a weight (HIMA). In the present study, it was mainly examined if these modalities could be differentiated by oxygenation variables as well as by time to task failure (TTF). Furthermore, it was analyzed if variables are changed by intermittent voluntary muscle twitches during weight holding (Twitch). It was assumed that twitches during a weight holding task change the character of the isometric muscle action from reacting (≙ HIMA) to acting (≙ PIMA).
Methods
Twelve subjects (two drop outs) randomly performed two tasks (HIMA vs. PIMA or HIMA vs. Twitch, n = 5 each) with the elbow flexors at 60% of maximal torque maintained until muscle failure with each arm. Local capillary venous oxygen saturation (SvO2) and relative hemoglobin amount (rHb) were measured by light spectrometry.
Results
Within subjects, no significant differences were found between tasks regarding the behavior of SvO2 and rHb, the slope and extent of deoxygenation (max. SvO2 decrease), SvO2 level at global rHb minimum, and time to SvO2 steady states. The TTF was significantly longer during Twitch and PIMA (incl. Twitch) compared to HIMA (p = 0.043 and 0.047, respectively). There was no substantial correlation between TTF and maximal deoxygenation independently of the task (r = − 0.13).
Conclusions
HIMA and PIMA seem to have a similar microvascular oxygen and blood supply. The supply might be sufficient, which is expressed by homeostatic steady states of SvO2 in all trials and increases in rHb in most of the trials. Intermittent voluntary muscle twitches might not serve as a further support but extend the TTF. A changed neuromuscular control is discussed as possible explanation.
Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality.
Sharing marketplaces emerged as the new Holy Grail of value creation by enabling exchanges between strangers. Identity reveal, encouraged by platforms, cuts both ways: While inducing pre-transaction confidence, it is suspected of backfiring on the information senders with its discriminative potential. This study employs a discrete choice experiment to explore the role of names as signifiers of discriminative peculiarities and the importance of accompanying cues in peer choices of a ridesharing offer. We quantify users' preferences for quality signals in monetary terms and evidence comparative disadvantage of Middle Eastern descent male names for drivers and co-travelers. It translates into a lower willingness to accept and pay for an offer. Market simulations confirm the robustness of the findings. Further, we discover that females are choosier and include more signifiers of involuntary personal attributes in their decision-making. Price discounts and positive information only partly compensate for the initial disadvantage, and identity concealment is perceived negatively.
The post-antiretroviral therapy era has transformed HIV into a chronic disease and non-HIV comorbidities (i.e., cardiovascular and mental diseases) are more prevalent in PLWH. The source of these non-HIV comorbidities aside from traditional risk factor include HIV infection, inflammation, distorted immune activation, burden of chronic diseases, and unhealthy lifestyle like sedentarism. Exercise is known for its beneficial effects in mental and physical health; reasons why exercise is recommended to prevent and treat difference cardiovascular and mental diseases in the general population. This cumulative thesis aimed to comprehend the relation exercise has to non-HIV comorbidities in German PLWH. Four studies were conducted to 1) understand exercise effects in cardiorespiratory fitness and muscle strength on PLWH through a systematic review and meta-analyses and 2) determine the likelihood of German PLWH developing non-HIV comorbidities, in a cross-sectional study. Meta-analytic examination indicates PLWH cardiorespiratory fitness (VO2max SMD = 0.61 ml·kg·min-1, 95% CI: 0.35-0.88, z = 4.47, p < 0.001, I2 = 50%) and strength (of remark lowerbody strength by 16.8 kg, 95% CI: 13–20.6, p< 0.001) improves after an exercise intervention in comparison to a control group. Cross-sectional data suggest exercise has a positive effect on German PLWH mental health (less anxiety and depressive symptoms) and protects against the development of anxiety (PR: 0.57, 95%IC: 0.36 – 0.91, p = 0.01) and depression (PR: 0.62, 95%IC: 0.41 – 0.94, p = 0.01). Likewise, exercise duration is related to a lower likelihood of reporting heart arrhythmias (PR: 0.20, 95%IC: 0.10 – 0.60, p < 0.01) and exercise frequency to a lower likelihood of reporting diabetes mellitus (PR: 0.40, 95%IC: 0.10 – 1, p < 0.01) in German PLWH. A preliminary recommendation for German PLWH who want to engage in exercise can be to exercise ≥ 1 time per week, at an intensity of 5 METs per session or > 103 MET·min·day-1, with a duration ≥ 150 minutes per week. Nevertheless, further research is needed to comprehend exercise dose response and protective effect for cardiovascular diseases, anxiety, and depression in German PLWH.
Organic solar cells (OSCs), in recent years, have shown high efficiencies through the development of novel non-fullerene acceptors (NFAs). Fullerene derivatives have been the centerpiece of the accepting materials used throughout organic photovoltaic (OPV) research. However, since 2015 novel NFAs have been a game-changer and have overtaken fullerenes. However, the current understanding of the properties of NFAs for OPV is still relatively limited and critical mechanisms defining the performance of OPVs are still topics of debate.
In this thesis, attention is paid to understanding reduced-Langevin recombination with respect to the device physics properties of fullerene and non-fullerene systems. The work is comprised of four closely linked studies. The first is a detailed exploration of the fill factor (FF) expressed in terms of transport and recombination properties in a comparison of fullerene and non-fullerene acceptors. We investigated the key reason behind the reduced FF in the NFA (ITIC-based) devices which is faster non-geminate recombination relative to the fullerene (PCBM[70]-based) devices. This is then followed by a consideration of a newly synthesized NFA Y-series derivative which exhibits the highest power conversion efficiency for OSC at the time. Such that in the second study, we illustrated the role of disorder on the non-geminate recombination and charge extraction of thick NFA (Y6-based) devices. As a result, we enhanced the FF of thick PM6:Y6 by reducing the disorder which leads to suppressing the non-geminate recombination toward non-Langevin system. In the third work, we revealed the reason behind thickness independence of the short circuit current of PM6:Y6 devices, caused by the extraordinarily long diffusion length of Y6. The fourth study entails a broad comparison of a selection of fullerene and non-fullerene blends with respect to charge generation efficiency and recombination to unveil the importance of efficient charge generation for achieving reduced recombination.
I employed transient measurements such as Time Delayed Collection Field (TDCF), Resistance dependent Photovoltage (RPV), and steady-state techniques such as Bias Assisted Charge Extraction (BACE), Temperature-Dependent Space Charge Limited Current (T-SCLC), Capacitance-Voltage (CV), and Photo-Induce Absorption (PIA), to analyze the OSCs.
The outcomes in this thesis together draw a complex picture of multiple factors that affect reduced-Langevin recombination and thereby the FF and overall performance. This provides a suitable platform for identifying important parameters when designing new blend systems. As a result, we succeeded to improve the overall performance through enhancing the FF of thick NFA device by adjustment of the amount of the solvent additive in the active blend solution. It also highlights potentially critical gaps in the current experimental understanding of fundamental charge interaction and recombination dynamics.
The discovery that certain diseases have specific miRNA signatures which correspond to disease progression opens a new biomarker category. The detection of these small non-coding RNAs is performed routinely using body fluids or tissues with real-time PCR, next-generation sequencing, or amplification-based miRNA assays. Antibody-based detection systems allow an easy onset handling compared to PCR or sequencing and can be considered as alternative methods to support miRNA diagnostic in the future. In this study, we describe the generation of a camelid heavy-chain-only antibody specifically recognizing miRNAs to establish an antibody-based detection method. The generation of nucleic acid-specific binders is a challenge. We selected camelid binders via phage display, expressed them as VHH as well as full-length antibodies, and characterized the binding to several miRNAs from a signature specific for dilated cardiomyopathy. The described workflow can be used to create miRNA-specific binders and establish antibody-based detection methods to provide an additional way to analyze disease-specific miRNA signatures.
The key to reduce the energy required for specific transformations in a selective manner is the employment of a catalyst, a very small molecular platform that decides which type of energy to use. The field of photocatalysis exploits light energy to shape one type of molecules into others, more valuable and useful.
However, many challenges arise in this field, for example, catalysts employed usually are based on metal derivatives, which abundance is limited, they cannot be recycled and are expensive. Therefore, carbon nitrides materials are used in this work to expand horizons in the field of photocatalysis.
Carbon nitrides are organic materials, which can act as recyclable, cheap, non-toxic, heterogeneous photocatalysts. In this thesis, they have been exploited for the development of new catalytic methods, and shaped to develop new types of processes.
Indeed, they enabled the creation of a new photocatalytic synthetic strategy, the dichloromethylation of enones by dichloromethyl radical generated in situ from chloroform, a novel route for the making of building blocks to be used for the productions of active pharmaceutical compounds.
Then, the ductility of these materials allowed to shape carbon nitride into coating for lab vials, EPR capillaries, and a cell of a flow reactor showing the great potential of such flexible technology in photocatalysis.
Afterwards, their ability to store charges has been exploited in the reduction of organic substrates under dark conditions, gaining new insights regarding multisite proton coupled electron transfer processes.
Furthermore, the combination of carbon nitrides with flavins allowed the development of composite materials with improved photocatalytic activity in the CO2 photoreduction.
Concluding, carbon nitrides are a versatile class of photoactive materials, which may help to unveil further scientific discoveries and to develop a more sustainable future.
Due to the major role of greenhouse gas emissions in global climate change, the development of non-fossil energy technologies is essential. Deep geothermal energy represents such an alternative, which offers promising properties such as a high base load capability and a large untapped potential. The present work addresses barite precipitation within geothermal systems and the associated reduction in rock permeability, which is a major obstacle to maintaining high efficiency. In this context, hydro-geochemical models are essential to quantify and predict the effects of precipitation on the efficiency of a system.
The objective of the present work is to quantify the induced injectivity loss using numerical and analytical reactive transport simulations. For the calculations, the fractured-porous reservoirs of the German geothermal regions North German Basin (NGB) and Upper Rhine Graben (URG) are considered.
Similar depth-dependent precipitation potentials could be determined for both investigated regions (2.8-20.2 g/m3 fluid). However, the reservoir simulations indicate that the injectivity loss due to barite deposition in the NGB is significant (1.8%-6.4% per year) and the longevity of the system is affected as a result; this is especially true for deeper reservoirs (3000 m). In contrast, simulations of URG sites indicate a minor role of barite (< 0.1%-1.2% injectivity loss per year). The key differences between the investigated regions are reservoir thicknesses and the presence of fractures in the rock, as well as the ionic strength of the fluids. The URG generally has fractured-porous reservoirs with much higher thicknesses, resulting in a greater distribution of precipitates in the subsurface. Furthermore, ionic strengths are higher in the NGB, which accelerates barite precipitation, causing it to occur more concentrated around the wellbore. The more concentrated the precipitates occur around the wellbore, the higher the injectivity loss.
In this work, a workflow was developed within which numerical and analytical models can be used to estimate and quantify the risk of barite precipitation within the reservoir of geothermal systems. A key element is a newly developed analytical scaling score that provides a reliable estimate of induced injectivity loss. The key advantage of the presented approach compared to fully coupled reservoir simulations is its simplicity, which makes it more accessible to plant operators and decision makers. Thus, in particular, the scaling score can find wide application within geothermal energy, e.g., in the search for potential plant sites and the estimation of long-term efficiency.
The intake of high-fat diets (HFDs) containing large amounts of saturated long-chain fatty acids leads to obesity, oxidative stress, inflammation, and insulin resistance. The trace element selenium, as a crucial part of antioxidative selenoproteins, can protect against the development of diet-induced insulin resistance in white adipose tissue (WAT) by increasing glutathione peroxidase 3 (GPx3) and insulin receptor (IR) expression. Whether selenite (Se) can attenuate insulin resistance in established lipotoxic and obese conditions is unclear. We confirm that GPX3 mRNA expression in adipose tissue correlates with BMI in humans. Cultivating 3T3-L1 pre-adipocytes in palmitate-containing medium followed by Se treatment attenuates insulin resistance with enhanced GPx3 and IR expression and adipocyte differentiation. However, feeding obese mice a selenium-enriched high-fat diet (SRHFD) only resulted in a modest increase in overall selenoprotein gene expression in WAT in mice with unaltered body weight development, glucose tolerance, and insulin resistance. While Se supplementation improved adipocyte morphology, it did not alter WAT insulin sensitivity. However, mice fed a SRHFD exhibited increased insulin content in the pancreas. Overall, while selenite protects against palmitate-induced insulin resistance in vitro, obesity impedes the effect of selenite on insulin action and adipose tissue metabolism in vivo.
Balkan varieties of Turkic, particularly those on the periphery of the Turkic spread area in the region, such as Gagauz and West Rumelian Turkish, are commonly observed to have head-initial verb phrases. Based on a wide survey, this paper attempts a more precise description of the pattern of VP directionality across Balkan Turkic and shows that there is considerable variation in how prevalent VX order is, a pattern that turns out to be more complex than the previous descriptions suggest: Two spectrums of directionality can be discerned between XV and VX orders, contingent upon type of the dependent of the verb and dialect locale. The paper also explores the grammatical causes underlying this shift in constituent order. First, VX order seems to be dependent upon whether a clause is nominal or not. Nonfinite clauses of the nominal type have XV order across Balkan Turkic, while finite clauses and nonfinite clauses of the converbial type show differing degrees of VX order depending on type of dependent and geographical location. Second, VX order appears to be an outcome of verb movement to the left of the dependent in finite clauses and nonfinite clauses of the converbial type, rather than head parameter shift.
Organic solar cells offer an efficient and cost-effective alternative for solar energy harvesting. This type of photovoltaic cell typically consists of a blend of two organic semiconductors, an electron donating polymer and a low molecular weight electron acceptor to create what is known as a bulk heterojunction (BHJ) morphology. Traditionally, fullerene-based acceptors have been used for this purpose. In recent years, the development of new acceptor molecules, so-called non-fullerene acceptors (NFA), has breathed new life into organic solar cell research, enabling record efficiencies close to 19%. Today, NFA-based solar cells are approaching their inorganic competitors in terms of photocurrent generation, but lag in terms of open circuit voltage (V_OC). Interestingly, the V_OC of these cells benefits from small offsets of orbital energies at the donor-NFA interface, although previous knowledge considered large energy offsets to be critical for efficient charge carrier generation. In addition, there are several other electronic and structural features that distinguish NFAs from fullerenes.
My thesis focuses on understanding the interplay between the unique attributes of NFAs and the physical processes occurring in solar cells. By combining various experimental techniques with drift-diffusion simulations, the generation of free charge carriers as well as their recombination in state-of-the-art NFA-based solar cells is characterized. For this purpose, solar cells based on the donor polymer PM6 and the NFA Y6 have been investigated. The generation of free charge carriers in PM6:Y6 is efficient and independent of electric field and excitation energy. Temperature-dependent measurements show a very low activation energy for photocurrent generation (about 6 meV), indicating barrierless charge carrier separation. Theoretical modeling suggests that Y6 molecules have large quadrupole moments, leading to band bending at the donor-acceptor interface and thereby reducing the electrostatic Coulomb dissociation barrier. In this regard, this work identifies poor extraction of free charges in competition with nongeminate recombination as a dominant loss process in PM6:Y6 devices. Subsequently, the spectral characteristics of PM6:Y6 solar cells were investigated with respect to the dominant process of charge carrier recombination. It was found that the photon emission under open-circuit conditions can be almost entirely attributed to the occupation and recombination of Y6 singlet excitons. Nevertheless, the recombination pathway via the singlet state contributes only 1% to the total recombination, which is dominated by the charge transfer state (CT-state) at the donor-acceptor interface. Further V_OC gains can therefore only be expected if the density and/or recombination rate of these CT-states can be significantly reduced. Finally, the role of energetic disorder in NFA solar cells is investigated by comparing Y6 with a structurally related derivative, named N4. Layer morphology studies combined with temperature-dependent charge transport experiments show significantly lower structural and energetic disorder in the case of the PM6:Y6 blend. For both PM6:Y6 and PM6:N4, disorder determines the maximum achievable V_OC, with PM6:Y6 benefiting from improved morphological order. Overall, the obtained findings point to avenues for the realization of NFA-based solar cells with even smaller V_OC losses. Further reduction of nongeminate recombination and energetic disorder should result in organic solar cells with efficiencies above 20% in the future.