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In den vergangenen Jahren hat sich die Politikdidaktik zunehmend mit dem Einsatz von Narrationen im Politikunterricht beschäftigt, denn neben Sachtexten bietet auch die Belletristik die Möglichkeit, sich mit politischen Themen auseinanderzusetzen. Insbesondere die Literatur von Ferdinand von Schirach hat in den letzten Jahren zunehmend Anklang in der Gesellschaft gefunden. Von Schirachs Texte greifen gesellschaftskritische Themen auf, beleuchten diese aus verschiedenen Perspektiven und fordern zur Meinungsbildung heraus. Aus diesem Grund weisen von Schirachs Narrationen ein hohes Potential für die Politische Bildung auf. Politische Bildung schließt auch die Rechterziehung ein. Der Fall Collini von Ferdinand von Schirach setzt sich sowohl mit rechtlichen, als auch mit politischen Themen im Sinne der Rechtserziehung auseinander. In der vorliegenden Masterarbeit wird der Frage nachgegangen, inwieweit der Roman Der Fall Collini von Ferdinand von Schirach als Narration eine Chance für politisch-rechtliches Lernen im Politikunterricht darstellt. Um die Forschungsfrage zu beantworten, werden die Lernchancen und -grenzen des Romans hinsichtlich seiner Thematik und seines Genres, sowie durch den Roman geförderten Kompetenzen herausgearbeitet und die durch ihn möglichen fächerübergreifenden Bezüge verdeutlicht. Durch die Auseinandersetzung mit von Schirachs Werk beschäftigen sich die Schülerinnen und Schüler mit politisch-rechtlichen Themen, wie dem Spannungsverhältnis von Recht und Gerechtigkeit, dem Ablauf von Strafgerichtsverfahren, dem theoretischen Anspruch des Rechtsstaates und dessen realen Schwächen. Zudem fördert die Auseinandersetzung mit dem Roman Der Fall Collini die vier fachbezogenen Kompetenzen der Politischen Bildung, sowie Multiperspektivität und exemplarisches Lernen. Des Weiteren verknüpft der Roman historische, politisch-rechtliche und moralisch-ethische Aspekte miteinander, wodurch fächerübergreifende Bezüge mit den Fächern Geschichte, Deutsch und L-E-R hergestellt werden können. Darüber hinaus spricht der Justizroman als Narration seine Leserinnen und Leser auch emotional an und fördert somit eine ganzheitliche und nachhaltige Wissensvermittlung im Sinne der Rechtserziehung. Es hat sich gezeigt, dass Der Fall Collini von Ferdinand von Schirach sich für die unterrichtliche Beschäftigung innerhalb der Politischen Bildung besonders eignet.
Die Technologie des 3D-Drucks hat sich in den letzten Jahrzehnten rasant entwickelt. Im Industriebereich entstehen immer modernere und spezialisiertere Druckverfahren, im Hobby- und Privatanwenderbereich hingegen werden stetig kostengünstigere und einfacher zu bedienende Geräte zugänglich. Einzig im Bildungsbereich scheint das Themenfeld hingegen erst langsam eine Rolle zu spielen, obwohl sich zahlreiche Bezugspunkte für einen Einsatz in verschiedensten Fächern finden lassen. Insbesondere im Fach Wirtschaft-Arbeit-Technik sind die Schnittstellen zum Rahmenlehrplan Berlin/Brandenburg augenscheinlich, doch es liegen erst vereinzelt konkrete und systematische didaktische Konzepte und Vorschläge zur unterrichtspraktischen Einbettung vor. Die Verfasserin versucht daher in dieser Arbeit die Relevanz des Themas für die technische Bildung deutlich zu machen, eine kurze technische Einführung in das für einen schulischen Einsatz besonders geeignete FDM-Druckverfahren zu geben und daran anknüpfend konkrete Umsetzungsvorschläge aufzuzeigen: einerseits in Form eines allgemeinen Phasenmodells zur Planung von Technikunterricht sowie andererseits in Form eines exemplarischen Unterrichtskonzepts. Am Beispiel eines Schachsets wird verdeutlicht, wie Schülerinnen und Schüler zum Anfertigen der Konstruktionsunterlagen digitale CAD-Programme nutzen und anschließend mit Hilfe eines 3D-Druckers additiv fertigen können.
Over the past decades, natural hazards, many of which are aggravated by climate change and reveal an increasing trend in frequency and intensity, have caused significant human and economic losses and pose a considerable obstacle to sustainable development. Hence, dedicated action toward disaster risk reduction is needed to understand the underlying drivers and create efficient risk mitigation plans. Such action is requested by the Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR), a global agreement launched in 2015 that establishes stating priorities for action, e.g. an improved understanding of disaster risk. Turkey is one of the SFDRR contracting countries and has been severely affected by many natural hazards, in particular earthquakes and floods. However, disproportionately little is known about flood hazards and risks in Turkey. Therefore, this thesis aims to carry out a comprehensive analysis of flood hazards for the first time in Turkey from triggering drivers to impacts. It is intended to contribute to a better understanding of flood risks, improvements of flood risk mitigation and the facilitated monitoring of progress and achievements while implementing the SFDRR.
In order to investigate the occurrence and severity of flooding in comparison to other natural hazards in Turkey and provide an overview of the temporal and spatial distribution of flood losses, the Turkey Disaster Database (TABB) was examined for the years 1960-2014. The TABB database was reviewed through comparison with the Emergency Events Database (EM-DAT), the Dartmouth Flood Observatory database, the scientific literature and news archives. In addition, data on the most severe flood events between 1960 and 2014 were retrieved. These served as a basis for analyzing triggering mechanisms (i.e. atmospheric circulation and precipitation amounts) and aggravating pathways (i.e. topographic features, catchment size, land use types and soil properties). For this, a new approach was developed and the events were classified using hierarchical cluster analyses to identify the main influencing factor per event and provide additional information about the dominant flood pathways for severe floods. The main idea of the study was to start with the event impacts based on a bottom-up approach and identify the causes that created damaging events, instead of applying a model chain with long-term series as input and searching for potentially impacting events as model outcomes. However, within the frequency analysis of the flood-triggering circulation pattern types, it was discovered that events in terms of heavy precipitation were not included in the list of most severe floods, i.e. their impacts were not recorded in national and international loss databases but were mentioned in news archives and reported by the Turkish State Meteorological Service. This finding challenges bottom-up modelling approaches and underlines the urgent need for consistent event and loss documentation. Therefore, as a next step, the aim was to enhance the flood loss documentation by calibrating, validating and applying the United Nations Office for Disaster Risk Reduction (UNDRR) loss estimation method for the recent severe flood events (2015-2020). This provided, a consistent flood loss estimation model for Turkey, allowing governments to estimate losses as quickly as possible after events, e.g. to better coordinate financial aid.
This thesis reveals that, after earthquakes, floods have the second most destructive effects in Turkey in terms of human and economic impacts, with over 800 fatalities and US$ 885.7 million in economic losses between 1960 and 2020, and that more attention should be paid on the national scale. The clustering results of the dominant flood-producing mechanisms (e.g. circulation pattern types, extreme rainfall, sudden snowmelt) present crucial information regarding the source and pathway identification, which can be used as base information for hazard identification in the preliminary risk assessment process. The implementation of the UNDRR loss estimation model shows that the model with country-specific parameters, calibrated damage ratios and sufficient event documentation (i.e. physically damaged units) can be recommended in order to provide first estimates of the magnitude of direct economic losses, even shortly after events have occurred, since it performed well when estimates were compared to documented losses.
The presented results can contribute to improving the national disaster loss database in Turkey and thus enable a better monitoring of the national progress and achievements with regard to the targets stated by the SFDRR. In addition, the outcomes can be used to better characterize and classify flood events. Information on the main underlying factors and aggravating flood pathways further supports the selection of suitable risk reduction policies.
All input variables used in this thesis were obtained from publicly available data. The results are openly accessible and can be used for further research.
As an overall conclusion, it can be stated that consistent loss data collection and better event documentation should gain more attention for a reliable monitoring of the implementation of the SFDRR. Better event documentation should be established according to a globally accepted standard for disaster classification and loss estimation in Turkey. Ultimately, this enables stakeholders to create better risk mitigation actions based on clear hazard definitions, flood event classification and consistent loss estimations.
Exendin-4 is a pharmaceutical peptide used in the control of insulin secretion. Structural information on exendin-4 and related peptides especially on the level of quaternary structure is scarce. We present the first published association equilibria of exendin-4 directly measured by static and dynamic light scattering. We show that exendin-4 oligomerization is pH dependent and that these oligomers are of low compactness. We relate our experimental results to a structural hypothesis to describe molecular details of exendin-4 oligomers. Discussion of the validity of this hypothesis is based on NMR, circular dichroism and fluorescence spectroscopy, and light scattering data on exendin-4 and a set of exendin-4 derived peptides. The essential forces driving oligomerization of exendin-4 are helix–helix interactions and interactions of a conserved hydrophobic moiety. Our structural hypothesis suggests that key interactions of exendin-4 monomers in the experimentally supported trimer take place between a defined helical segment and a hydrophobic triangle constituted by the Phe22 residues of the three monomeric subunits. Our data rationalize that Val19 might function as an anchor in the N-terminus of the interacting helix-region and that Trp25 is partially shielded in the oligomer by C-terminal amino acids of the same monomer. Our structural hypothesis suggests that the Trp25 residues do not interact with each other, but with C-terminal Pro residues of their own monomers.
The large literature that aims to find evidence of climate migration delivers mixed findings. This meta-regression analysis i) summarizes direct links between adverse climatic events and migration, ii) maps patterns of climate migration, and iii) explains the variation in outcomes. Using a set of limited dependent variable models, we meta-analyze thus-far the most comprehensive sample of 3,625 estimates from 116 original studies and produce novel insights on climate migration. We find that extremely high temperatures and drying conditions increase migration. We do not find a significant effect of sudden-onset events. Climate migration is most likely to emerge due to contemporaneous events, to originate in rural areas and to take place in middle-income countries, internally, to cities. The likelihood to become trapped in affected areas is higher for women and in low-income countries, particularly in Africa. We uniquely quantify how pitfalls typical for the broader empirical climate impact literature affect climate migration findings. We also find evidence of different publication biases.
With the downscaling of CMOS technologies, the radiation-induced Single Event Transient (SET) effects in combinational logic have become a critical reliability issue for modern integrated circuits (ICs) intended for operation under harsh radiation conditions. The SET pulses generated in combinational logic may propagate through the circuit and eventually result in soft errors. It has thus become an imperative to address the SET effects in the early phases of the radiation-hard IC design. In general, the soft error mitigation solutions should accommodate both static and dynamic measures to ensure the optimal utilization of available resources. An efficient soft-error-aware design should address synergistically three main aspects: (i) characterization and modeling of soft errors, (ii) multi-level soft error mitigation, and (iii) online soft error monitoring. Although significant results have been achieved, the effectiveness of SET characterization methods, accuracy of predictive SET models, and efficiency of SET mitigation measures are still critical issues. Therefore, this work addresses the following topics: (i) Characterization and modeling of SET effects in standard combinational cells, (ii) Static mitigation of SET effects in standard combinational cells, and (iii) Online particle detection, as a support for dynamic soft error mitigation.
Since the standard digital libraries are widely used in the design of radiation-hard ICs, the characterization of SET effects in standard cells and the availability of accurate SET models for the Soft Error Rate (SER) evaluation are the main prerequisites for efficient radiation-hard design. This work introduces an approach for the SPICE-based standard cell characterization with the reduced number of simulations, improved SET models and optimized SET sensitivity database. It has been shown that the inherent similarities in the SET response of logic cells for different input levels can be utilized to reduce the number of required simulations. Based on characterization results, the fitting models for the SET sensitivity metrics (critical charge, generated SET pulse width and propagated SET pulse width) have been developed. The proposed models are based on the principle of superposition, and they express explicitly the dependence of the SET sensitivity of individual combinational cells on design, operating and irradiation parameters. In contrast to the state-of-the-art characterization methodologies which employ extensive look-up tables (LUTs) for storing the simulation results, this work proposes the use of LUTs for storing the fitting coefficients of the SET sensitivity models derived from the characterization results. In that way the amount of characterization data in the SET sensitivity database is reduced significantly.
The initial step in enhancing the robustness of combinational logic is the application of gate-level mitigation techniques. As a result, significant improvement of the overall SER can be achieved with minimum area, delay and power overheads. For the SET mitigation in standard cells, it is essential to employ the techniques that do not require modifying the cell structure. This work introduces the use of decoupling cells for improving the robustness of standard combinational cells. By insertion of two decoupling cells at the output of a target cell, the critical charge of the cell’s output node is increased and the attenuation of short SETs is enhanced. In comparison to the most common gate-level techniques (gate upsizing and gate duplication), the proposed approach provides better SET filtering. However, as there is no single gate-level mitigation technique with optimal performance, a combination of multiple techniques is required. This work introduces a comprehensive characterization of gate-level mitigation techniques aimed to quantify their impact on the SET robustness improvement, as well as introduced area, delay and power overhead per gate. By characterizing the gate-level mitigation techniques together with the standard cells, the required effort in subsequent SER analysis of a target design can be reduced. The characterization database of the hardened standard cells can be utilized as a guideline for selection of the most appropriate mitigation solution for a given design.
As a support for dynamic soft error mitigation techniques, it is important to enable the online detection of energetic particles causing the soft errors. This allows activating the power-greedy fault-tolerant configurations based on N-modular redundancy only at the high radiation levels. To enable such a functionality, it is necessary to monitor both the particle flux and the variation of particle LET, as these two parameters contribute significantly to the system SER. In this work, a particle detection approach based on custom-sized pulse stretching inverters is proposed. Employing the pulse stretching inverters connected in parallel enables to measure the particle flux in terms of the number of detected SETs, while the particle LET variations can be estimated from the distribution of SET pulse widths. This approach requires a purely digital processing logic, in contrast to the standard detectors which require complex mixed-signal processing. Besides the possibility of LET monitoring, additional advantages of the proposed particle detector are low detection latency and power consumption, and immunity to error accumulation.
The results achieved in this thesis can serve as a basis for establishment of an overall soft-error-aware database for a given digital library, and a comprehensive multi-level radiation-hard design flow that can be implemented with the standard IC design tools. The following step will be to evaluate the achieved results with the irradiation experiments.
Atmospheric water vapour content is a key variable that controls the development of deep convective storms and rainfall extremes over the central Andes. Direct measurements of water vapour are challenging; however, recent developments in microwave processing allow the use of phase delays from L-band radar to measure the water vapour content throughout the atmosphere: Global Navigation Satellite System (GNSS)-based integrated water vapour (IWV) monitoring shows promising results to measure vertically integrated water vapour at high temporal resolutions. Previous works also identified convective available potential energy (CAPE) as a key climatic variable for the formation of deep convective storms and rainfall in the central Andes. Our analysis relies on GNSS data from the Argentine Continuous Satellite Monitoring Network, Red Argentina de Monitoreo Satelital Continuo (RAMSAC) network from 1999 to 2013. CAPE is derived from version 2.0 of the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) and rainfall from the TRMM (Tropical Rainfall Measuring Mission) product. In this study, we first analyse the rainfall characteristics of two GNSS-IWV stations by comparing their complementary cumulative distribution function (CCDF). Second, we separately derive the relation between rainfall vs. CAPE and GNSS-IWV. Based on our distribution fitting analysis, we observe an exponential relation of rainfall to GNSS-IWV. In contrast, we report a power-law relationship between the daily mean value of rainfall and CAPE at the GNSS-IWV station locations in the eastern central Andes that is close to the theoretical relationship based on parcel theory. Third, we generate a joint regression model through a multivariable regression analysis using CAPE and GNSS-IWV to explain the contribution of both variables in the presence of each other to extreme rainfall during the austral summer season. We found that rainfall can be characterised with a higher statistical significance for higher rainfall quantiles, e.g., the 0.9 quantile based on goodness-of-fit criterion for quantile regression. We observed different contributions of CAPE and GNSS-IWV to rainfall for each station for the 0.9 quantile. Fourth, we identify the temporal relation between extreme rainfall (the 90th, 95th, and 99th percentiles) and both GNSS-IWV and CAPE at 6 h time steps. We observed an increase before the rainfall event and at the time of peak rainfall—both for GNSS-integrated water vapour and CAPE. We show higher values of CAPE and GNSS-IWV for higher rainfall percentiles (99th and 95th percentiles) compared to the 90th percentile at a 6-h temporal scale. Based on our correlation analyses and the dynamics of the time series, we show that both GNSS-IWV and CAPE had comparable magnitudes, and we argue to consider both climatic variables when investigating their effect on rainfall extremes.
We consider a sequential cascade of molecular first-reaction events towards a terminal reaction centre in which each reaction step is controlled by diffusive motion of the particles. The model studied here represents a typical reaction setting encountered in diverse molecular biology systems, in which, e.g. a signal transduction proceeds via a series of consecutive 'messengers': the first messenger has to find its respective immobile target site triggering a launch of the second messenger, the second messenger seeks its own target site and provokes a launch of the third messenger and so on, resembling a relay race in human competitions. For such a molecular relay race taking place in infinite one-, two- and three-dimensional systems, we find exact expressions for the probability density function of the time instant of the terminal reaction event, conditioned on preceding successful reaction events on an ordered array of target sites. The obtained expressions pertain to the most general conditions: number of intermediate stages and the corresponding diffusion coefficients, the sizes of the target sites, the distances between them, as well as their reactivities are arbitrary.
This thesis focuses on the study of marked Gibbs point processes, in particular presenting some results on their existence and uniqueness, with ideas and techniques drawn from different areas of statistical mechanics: the entropy method from large deviations theory, cluster expansion and the Kirkwood--Salsburg equations, the Dobrushin contraction principle and disagreement percolation.
We first present an existence result for infinite-volume marked Gibbs point processes. More precisely, we use the so-called entropy method (and large-deviation tools) to construct marked Gibbs point processes in R^d under quite general assumptions. In particular, the random marks belong to a general normed space S and are not bounded. Moreover, we allow for interaction functionals that may be unbounded and whose range is finite but random. The entropy method relies on showing that a family of finite-volume Gibbs point processes belongs to sequentially compact entropy level sets, and is therefore tight.
We then present infinite-dimensional Langevin diffusions, that we put in interaction via a Gibbsian description. In this setting, we are able to adapt the general result above to show the existence of the associated infinite-volume measure. We also study its correlation functions via cluster expansion techniques, and obtain the uniqueness of the Gibbs process for all inverse temperatures β and activities z below a certain threshold. This method relies in first showing that the correlation functions of the process satisfy a so-called Ruelle bound, and then using it to solve a fixed point problem in an appropriate Banach space. The uniqueness domain we obtain consists then of the model parameters z and β for which such a problem has exactly one solution.
Finally, we explore further the question of uniqueness of infinite-volume Gibbs point processes on R^d, in the unmarked setting. We present, in the context of repulsive interactions with a hard-core component, a novel approach to uniqueness by applying the discrete Dobrushin criterion to the continuum framework. We first fix a discretisation parameter a>0 and then study the behaviour of the uniqueness domain as a goes to 0. With this technique we are able to obtain explicit thresholds for the parameters z and β, which we then compare to existing results coming from the different methods of cluster expansion and disagreement percolation.
Throughout this thesis, we illustrate our theoretical results with various examples both from classical statistical mechanics and stochastic geometry.
Monoclonal antibodies are used worldwide as highly potent and efficient detection reagents for research and diagnostic applications. Nevertheless, the specific targeting of complex antigens such as whole microorganisms remains a challenge. To provide a comprehensive workflow, we combined bioinformatic analyses with novel immunization and selection tools to design monoclonal antibodies for the detection of whole microorganisms. In our initial study, we used the human pathogenic strain E. coli O157:H7 as a model target and identified 53 potential protein candidates by using reverse vaccinology methodology. Five different peptide epitopes were selected for immunization using epitope-engineered viral proteins. The identification of antibody-producing hybridomas was performed by using a novel screening technology based on transgenic fusion cell lines. Using an artificial cell surface receptor expressed by all hybridomas, the desired antigen-specific cells can be sorted fast and efficiently out of the fusion cell pool. Selected antibody candidates were characterized and showed strong binding to the target strain E. coli O157:H7 with minor or no cross-reactivity to other relevant microorganisms such as Legionella pneumophila and Bacillus ssp. This approach could be useful as a highly efficient workflow for the generation of antibodies against microorganisms.
The spread of shrubs in Namibian savannas raises questions about the resilience of these ecosystems to global change. This makes it necessary to understand the past dynamics of the vegetation, since there is no consensus on whether shrub encroachment is a new phenomenon, nor on its main drivers. However, a lack of long-term vegetation datasets for the region and the scarcity of suitable palaeoecological archives, makes reconstructing past vegetation and land cover of the savannas a challenge.
To help meet this challenge, this study addresses three main research questions: 1) is pollen analysis a suitable tool to reflect the vegetation change associated with shrub encroachment in savanna environments? 2) Does the current encroached landscape correspond to an alternative stable state of savanna vegetation? 3) To what extent do pollen-based quantitative vegetation reconstructions reflect changes in past land cover?
The research focuses on north-central Namibia, where despite being the region most affected by shrub invasion, particularly since the 21st century, little is known about the dynamics of this phenomenon.
Field-based vegetation data were compared with modern pollen data to assess their correspondence in terms of composition and diversity along precipitation and grazing intensity gradients. In addition, two sediment cores from Lake Otjikoto were analysed to reveal changes in vegetation composition that have occurred in the region over the past 170 years and their possible drivers. For this, a multiproxy approach (fossil pollen, sedimentary ancient DNA (sedaDNA), biomarkers, compound specific carbon (δ13C) and deuterium (δD) isotopes, bulk carbon isotopes (δ13Corg), grain size, geochemical properties) was applied at high taxonomic and temporal resolution. REVEALS modelling of the fossil pollen record from Lake Otjikoto was run to quantitatively reconstruct past vegetation cover. For this, we first made pollen productivity estimates (PPE) of the most relevant savanna taxa in the region using the extended R-value model and two pollen dispersal options (Gaussian plume model and Lagrangian stochastic model). The REVEALS-based vegetation reconstruction was then validated using remote sensing-based regional vegetation data.
The results show that modern pollen reflects the composition of the vegetation well, but diversity less well. Interestingly, precipitation and grazing explain a significant amount of the compositional change in the pollen and vegetation spectra. The multiproxy record shows that a state change from open Combretum woodland to encroached Terminalia shrubland can occur over a century, and that the transition between states spans around 80 years and is characterized by a unique vegetation composition. This transition is supported by gradual environmental changes induced by management (i.e. broad-scale logging for the mining industry, selective grazing and reduced fire activity associated with intensified farming) and related land-use change. Derived environmental changes (i.e. reduced soil moisture, reduced grass cover, changes in species composition and competitiveness, reduced fire intensity) may have affected the resilience of Combretum open woodlands, making them more susceptible to change to an encroached state by stochastic events such as consecutive years of precipitation and drought, and by high concentrations of pCO2. We assume that the resulting encroached state was further stabilized by feedback mechanisms that favour the establishment and competitiveness of woody vegetation.
The REVEALS-based quantitative estimates of plant taxa indicate the predominance of a semi-open landscape throughout the 20th century and a reduction in grass cover below 50% since the 21st century associated with the spread of encroacher woody taxa. Cover estimates show a close match with regional vegetation data, providing support for the vegetation dynamics inferred from multiproxy analyses. Reasonable PPEs were made for all woody taxa, but not for Poaceae.
In conclusion, pollen analysis is a suitable tool to reconstruct past vegetation dynamics in savannas. However, because pollen cannot identify grasses beyond family level, a multiproxy approach, particularly the use of sedaDNA, is required. I was able to separate stable encroached states from mere woodland phases, and could identify drivers and speculate about related feedbacks. In addition, the REVEALS-based quantitative vegetation reconstruction clearly reflects the magnitude of the changes in the vegetation cover that occurred during the last 130 years, despite the limitations of some PPEs.
This research provides new insights into pollen-vegetation relationships in savannas and highlights the importance of multiproxy approaches when reconstructing past vegetation dynamics in semi-arid environments. It also provides the first time series with sufficient taxonomic resolution to show changes in vegetation composition during shrub encroachment, as well as the first quantitative reconstruction of past land cover in the region. These results help to identify the different stages in savanna dynamics and can be used to calibrate predictive models of vegetation change, which are highly relevant to land management.
Objective
The Caribbean is an important global biodiversity hotspot. Adaptive radiations there lead to many speciation events within a limited period and hence are particularly prominent biodiversity generators. A prime example are freshwater fish of the genus Limia, endemic to the Greater Antilles. Within Hispaniola, nine species have been described from a single isolated site, Lake Miragoâne, pointing towards extraordinary sympatric speciation. This study examines the evolutionary history of the Limia species in Lake Miragoâne, relative to their congeners throughout the Caribbean.
Results
For 12 Limia species, we obtained almost complete sequences of the mitochondrial cytochrome b gene, a well-established marker for lower-level taxonomic relationships. We included sequences of six further Limia species from GenBank (total N = 18 species). Our phylogenies are in concordance with other published phylogenies of Limia. There is strong support that the species found in Lake Miragoâne in Haiti are monophyletic, confirming a recent local radiation. Within Lake Miragoâne, speciation is likely extremely recent, leading to incomplete lineage sorting in the mtDNA. Future studies using multiple unlinked genetic markers are needed to disentangle the relationships within the Lake Miragoâne clade.
Background
Relatively little is known about protective factors and the emergence and maintenance of positive outcomes in the field of adolescents with chronic conditions. Therefore, the primary aim of the study is to acquire a deeper understanding of the dynamic process of resilience factors, coping strategies and psychosocial adjustment of adolescents living with chronic conditions.
Methods/design
We plan to consecutively recruit N = 450 adolescents (12–21 years) from three German patient registries for chronic conditions (type 1 diabetes, cystic fibrosis, or juvenile idiopathic arthritis). Based on screening for anxiety and depression, adolescents are assigned to two parallel groups – “inconspicuous” (PHQ-9 and GAD-7 < 7) vs. “conspicuous” (PHQ-9 or GAD-7 ≥ 7) – participating in a prospective online survey at baseline and 12-month follow-up. At two time points (T1, T2), we assess (1) intra- and interpersonal resiliency factors, (2) coping strategies, and (3) health-related quality of life, well-being, satisfaction with life, anxiety and depression. Using a cross-lagged panel design, we will examine the bidirectional longitudinal relations between resiliency factors and coping strategies, psychological adaptation, and psychosocial adjustment. To monitor Covid-19 pandemic effects, participants are also invited to take part in an intermediate online survey.
Discussion
The study will provide a deeper understanding of adaptive, potentially modifiable processes and will therefore help to develop novel, tailored interventions supporting a positive adaptation in youths with a chronic condition. These strategies should not only support those at risk but also promote the maintenance of a successful adaptation.
Trial registration
German Clinical Trials Register (DRKS), no. DRKS00025125. Registered on May 17, 2021.
In Systems Medicine, in addition to high-throughput molecular data (*omics), the wealth of clinical characterization plays a major role in the overall understanding of a disease. Unique problems and challenges arise from the heterogeneity of data and require new solutions to software and analysis methods. The SMART and EurValve studies establish a Systems Medicine approach to valvular heart disease -- the primary cause of subsequent heart failure.
With the aim to ascertain a holistic understanding, different *omics as well as the clinical picture of patients with aortic stenosis (AS) and mitral regurgitation (MR) are collected. Our task within the SMART consortium was to develop an IT platform for Systems Medicine as a basis for data storage, processing, and analysis as a prerequisite for collaborative research. Based on this platform, this thesis deals on the one hand with the transfer of the used Systems Biology methods to their use in the Systems Medicine context and on the other hand with the clinical and biomolecular differences of the two heart valve diseases. To advance differential expression/abundance (DE/DA) analysis software for use in Systems Medicine, we state 21 general software requirements and features of automated DE/DA software, including a novel concept for the simple formulation of experimental designs that can represent complex hypotheses, such as comparison of multiple experimental groups, and demonstrate our handling of the wealth of clinical data in two research applications DEAME and Eatomics. In user interviews, we show that novice users are empowered to formulate and test their multiple DE hypotheses based on clinical phenotype. Furthermore, we describe insights into users' general impression and expectation of the software's performance and show their intention to continue using the software for their work in the future. Both research applications cover most of the features of existing tools or even extend them, especially with respect to complex experimental designs. Eatomics is freely available to the research community as a user-friendly R Shiny application.
Eatomics continued to help drive the collaborative analysis and interpretation of the proteomic profile of 75 human left myocardial tissue samples from the SMART and EurValve studies. Here, we investigate molecular changes within the two most common types of valvular heart disease: aortic valve stenosis (AS) and mitral valve regurgitation (MR). Through DE/DA analyses, we explore shared and disease-specific protein alterations, particularly signatures that could only be found in the sex-stratified analysis. In addition, we relate changes in the myocardial proteome to parameters from clinical imaging. We find comparable cardiac hypertrophy but differences in ventricular size, the extent of fibrosis, and cardiac function. We find that AS and MR show many shared remodeling effects, the most prominent of which is an increase in the extracellular matrix and a decrease in metabolism. Both effects are stronger in AS. In muscle and cytoskeletal adaptations, we see a greater increase in mechanotransduction in AS and an increase in cortical cytoskeleton in MR. The decrease in proteostasis proteins is mainly attributable to the signature of female patients with AS. We also find relevant therapeutic targets.
In addition to the new findings, our work confirms several concepts from animal and heart failure studies by providing the largest collection of human tissue from in vivo collected biopsies to date. Our dataset contributing a resource for isoform-specific protein expression in two of the most common valvular heart diseases. Apart from the general proteomic landscape, we demonstrate the added value of the dataset by showing proteomic and transcriptomic evidence for increased expression of the SARS-CoV-2- receptor at pressure load but not at volume load in the left ventricle and also provide the basis of a newly developed metabolic model of the heart.
A tale of shifting relations
(2021)
Understanding the dynamics between the East Asian summer (EASM) and winter monsoon (EAWM) is needed to predict their variability under future global warming scenarios. Here, we investigate the relationship between EASM and EAWM as well as the mechanisms driving their variability during the last 10,000 years by stacking marine and terrestrial (non-speleothem) proxy records from the East Asian realm. This provides a regional and proxy independent signal for both monsoonal systems. The respective signal was subsequently analysed using a linear regression model. We find that the phase relationship between EASM and EAWM is not time-constant and significantly depends on orbital configuration changes. In addition, changes in the Atlantic Meridional Overturning circulation, Arctic sea-ice coverage, El Niño-Southern Oscillation and Sun Spot numbers contributed to millennial scale changes in the EASM and EAWM during the Holocene. We also argue that the bulk signal of monsoonal activity captured by the stacked non-speleothem proxy records supports the previously argued bias of speleothem climatic archives to moisture source changes and/or seasonality.
Iron-sulfur clusters are essential enzyme cofactors. The most common and stable clusters are [2Fe-2S] and [4Fe-4S] that are found in nature. They are involved in crucial biological processes like respiration, gene regulation, protein translation, replication and DNA repair in prokaryotes and eukaryotes. In Escherichia coli, Fe-S clusters are essential for molybdenum cofactor (Moco) biosynthesis, which is a ubiquitous and highly conserved pathway. The first step of Moco biosynthesis is catalyzed by the MoaA protein to produce cyclic pyranopterin monophosphate (cPMP) from 5’GTP. MoaA is a [4Fe-4S] cluster containing radical S-adenosyl-L-methionine (SAM) enzyme. The focus of this study was to investigate Fe-S cluster insertion into MoaA under nitrate and TMAO respiratory conditions using E. coli as a model organism. Nitrate and TMAO respiration usually occur under anaerobic conditions, where oxygen is depleted. Under these conditions, E. coli uses nitrate and TMAO as terminal electron. Previous studies revealed that Fe-S cluster insertion is performed by Fe-S cluster carrier proteins. In E. coli, these proteins are known as A-type carrier proteins (ATC) by phylogenomic and genetic studies. So far, three of them have been characterized in detail in E. coli, namely IscA, SufA, and ErpA. This study shows that ErpA and IscA are involved in Fe-S cluster insertion into MoaA under nitrate and TMAO respiratory conditions. ErpA and IscA can partially replace each other in their role to provide [4Fe-4S] clusters for MoaA. SufA is not able to replace the functions of IscA or ErpA under nitrate respiratory conditions.
Nitrate reductase is a molybdoenzyme that coordinates Moco and Fe-S clusters. Under nitrate respiratory conditions, the expression of nitrate reductase is significantly increased in E. coli. Nitrate reductase is encoded in narGHJI genes, the expression of which is regulated by the transcriptional regulator, fumarate and nitrate reduction (FNR). The activation of FNR under conditions of nitrate respiration requires one [4Fe-4S] cluster. In this part of the study, we analyzed the insertion of Fe-S cluster into FNR for the expression of narGHJI genes in E. coli. The results indicate that ErpA is essential for the FNR-dependent expression of the narGHJI genes, a role that can be replaced partially by IscA and SufA when they are produced sufficiently under the conditions tested. This observation suggests that ErpA is indirectly regulating nitrate reductase expression via inserting Fe-S clusters into FNR.
Most molybdoenzymes are complex multi-subunit and multi-cofactor-containing enzymes that coordinate Fe-S clusters, which are functioning as electron transfer chains for catalysis. In E. coli, periplasmic aldehyde oxidoreductase (PaoAC) is a heterotrimeric molybdoenzyme that
consists of flavin, two [2Fe-2S], one [4Fe-4S] cluster and Moco. In the last part of this study, we investigated the insertion of Fe-S clusters into E. coli periplasmic aldehyde oxidoreductase (PaoAC). The results show that SufA and ErpA are involved in inserting [4Fe-4S] and [2Fe-2S] clusters into PaoABC, respectively under aerobic respiratory conditions.
Gravitational-wave (GW) astrophysics is a field in full blossom. Since the landmark detection of GWs from a binary black hole on September 14th 2015, fifty-two compact-object binaries have been reported by the LIGO-Virgo collaboration. Such events carry astrophysical and cosmological information ranging from an understanding of how black holes and neutron stars are formed, what neutron stars are composed of, how the Universe expands, and allow testing general relativity in the highly-dynamical strong-field regime. It is the goal of GW astrophysics to extract such information as accurately as possible. Yet, this is only possible if the tools and technology used to detect and analyze GWs are advanced enough. A key aspect of GW searches are waveform models, which encapsulate our best predictions for the gravitational radiation under a certain set of parameters, and that need to be cross-correlated with data to extract GW signals. Waveforms must be very accurate to avoid missing important physics in the data, which might be the key to answer the fundamental questions of GW astrophysics. The continuous improvements of the current LIGO-Virgo detectors, the development of next-generation ground-based detectors such as the Einstein Telescope or the Cosmic Explorer, as well as the development of the Laser Interferometer Space Antenna (LISA), demand accurate waveform models. While available models are enough to capture the low spins, comparable-mass binaries routinely detected in LIGO-Virgo searches, those for sources from both current and next-generation ground-based and spaceborne detectors must be accurate enough to detect binaries with large spins and asymmetry in the masses. Moreover, the thousands of sources that we expect to detect with future detectors demand accurate waveforms to mitigate biases in the estimation of signals’ parameters due to the presence of a foreground of many sources that overlap in the frequency band. This is recognized as one of the biggest challenges for the analysis of future-detectors’ data, since biases might hinder the extraction of important astrophysical and cosmological information from future detectors’ data. In the first part of this thesis, we discuss how to improve waveform models for binaries with high spins and asymmetry in the masses. In the second, we present the first generic metrics that have been proposed to predict biases in the presence of a foreground of many overlapping signals in GW data.
For the first task, we will focus on several classes of analytical techniques. Current models for LIGO and Virgo studies are based on the post-Newtonian (PN, weak-field, small velocities) approximation that is most natural for the bound orbits that are routinely detected in GW searches. However, two other approximations have risen in prominence, the post-Minkowskian (PM, weak- field only) approximation natural for unbound (scattering) orbits and the small-mass-ratio (SMR) approximation typical of binaries in which the mass of one body is much bigger than the other. These are most appropriate to binaries with high asymmetry in the masses that challenge current waveform models. Moreover, they allow one to “cover” regions of the parameter space of coalescing binaries, thereby improving the interpolation (and faithfulness) of waveform models. The analytical approximations to the relativistic two-body problem can synergically be included within the effective-one-body (EOB) formalism, in which the two-body information from each approximation can be recast into an effective problem of a mass orbiting a deformed Schwarzschild (or Kerr) black hole. The hope is that the resultant models can cover both the low-spin comparable-mass binaries that are routinely detected, and the ones that challenge current models. The first part of this thesis is dedicated to a study about how to best incorporate information from the PN, PM, SMR and EOB approaches in a synergistic way. We also discuss how accurate the resulting waveforms are, as compared against numerical-relativity (NR) simulations. We begin by comparing PM models, whether alone or recast in the EOB framework, against PN models and NR simulations. We will show that PM information has the potential to improve currently-employed models for LIGO and Virgo, especially if recast within the EOB formalism. This is very important, as the PM approximation comes with a host of new computational techniques from particle physics to exploit. Then, we show how a combination of PM and SMR approximations can be employed to access previously-unknown PN orders, deriving the third subleading PN dynamics for spin-orbit and (aligned) spin1-spin2 couplings. Such new results can then be included in the EOB models currently used in GW searches and parameter estimation studies, thereby improving them when the binaries have high spins. Finally, we build an EOB model for quasi-circular nonspinning binaries based on the SMR approximation (rather than the PN one as usually done). We show how this is done in detail without incurring in the divergences that had affected previous attempts, and compare the resultant model against NR simulations. We find that the SMR approximation is an excellent approximation for all (quasi-circular nonspinning) binaries, including both the equal-mass binaries that are routinely detected in GW searches and the ones with highly asymmetric masses. In particular, the SMR-based models compare much better than the PN models, suggesting that SMR-informed EOB models might be the key to model binaries in the future. In the second task of this thesis, we work within the linear-signal ap- proximation and describe generic metrics to predict inference biases on the parameters of a GW source of interest in the presence of confusion noise from unfitted foregrounds and from residuals of other signals that have been incorrectly fitted out. We illustrate the formalism with simple (yet realistic) LISA sources, and demonstrate its validity against Monte-Carlo simulations. The metrics we describe pave the way for more realistic studies to quantify the biases with future ground-based and spaceborne detectors.
Magmatic continental rifts often constitute the earliest stage of nascent plate boundaries. These extensional tectonic provinces are characterized by ubiquitous normal faulting and volcanic activity; the spatial pattern, the geometry, and the age of these normal faults can help to unravel the spatiotemporal relationships between extensional deformation, magmatism, and long-wavelength crustal deformation of continental rift provinces. This study focuses on the active faulting in the Kenya Rift of the Cenozoic East African Rift System (EARS) with a focus on the mid-Pleistocene to the present-day.
To examine the early stages of continental break-up in the EARS, this thesis presents a time-averaged minimum extension rate for the inner graben of the Northern Kenya Rift (NKR) for the last 0.5 m.y. Using the TanDEM-X digital elevation model, fault-scarp geometries and associated throws are determined across the volcano-tectonic axis of the inner graben of the NKR. By integrating existing geochronology of faulted units with new ⁴⁰Ar/³⁹Ar radioisotopic dates, time-averaged extension rates are calculated. This study reveals that in the inner graben of the NKR, the long-term extension rate based on mid-Pleistocene to recent brittle deformation has minimum values of 1.0 to 1.6 mm yr⁻¹, locally with values up to 2.0 mm yr⁻¹. In light of virtually inactive border faults of the NKR, we show that extension is focused in the region of the active volcano-tectonic axis in the inner graben, thus highlighting the maturing of continental rifting in the NKR.
The phenomenon of focused extension is further investigated with a structural analysis of the youngest volcanic manifestations of the Kenya Rift, their relationship with extensional structures, and their overprint by Holocene faulting. In this context I analyzed the fault characteristics at the ~36 ka old Menengai Caldera and adjacent areas in the Central Kenya Rift using detailed field mapping and a structure-from-motion-based DEM generated from UAV data. In general, the Holocene intra-rift normal faults are dip-slip faults which strike NNE and thus reflect the present-day tectonic stress field; however, inside Menengai caldera persistent magmatic activity and magmatic resurgence overprints these young structures significantly. The caldera is located at the center of an actively extending rift segment and this and the other volcanic edifices of the Kenya Rift may constitute nucleation points of faulting an magmatic extensional processes that ultimately lead into a future stage of magma-assisted rifting.
When viewed at the scale of the entire Kenya Rift the protracted normal faulting in this region compartmentalizes the larger rift depressions, and influences the sedimentology and the hydrology of the intra-rift basins at a scale of less than 100 km. In the present day, most of the fault-bounded sub-basins of the Kenya Rift are hydrologically isolated due to this combination of faulting and magmatic activity that has generated efficient hydrological barriers that maintain these basins as semi-independent geomorphic entities. This isolation, however, was overcome during wetter climatic conditions during the past when the basins were transiently connected. I therefore also investigated the hydrological connectivity of the rift basins during the African Humid Period of the early Holocene, when climate was wetter. With the help of DEM analysis, lake-highstand indicators, radiocarbon dating, and a review of the fossil record, two lake-river-cascades could be identified: one directed southward, and one directed northward. Both cascades connected presently isolated rift basins during the early Holocene via spillovers of lakes and incised river gorges. This hydrological connection fostered the dispersal of aquatic faunas along the rift, and in addition, the water divide between the two river systems represented the only terrestrial dispersal corridor across the Kenya Rift. The reconstruction explains isolated distributions of Nilotic fish species in Kenya Rift lakes and of Guineo-Congolian mammal species in forests east of the Kenya Rift. On longer timescales, repeated episodes of connectivity and isolation must have occurred. To address this problem I participated in research to analyze a sediment drill core from the Koora basin of the Southern Kenya Rift, which provides a paleo-environmental record of the last 1 Ma. Based on this record it can be concluded that at ~400 ka relatively stable environmental conditions were disrupted by tectonic, hydrological, and ecological changes, resulting in increasingly large and frequent fluctuations in water availability, grassland communities, and woody plant cover. The major environmental shifts reflected in the drill core data coincide with phases where volcano-tectonic activity affected the basin. This thesis therefore shows how protracted extensional tectonic processes and the resulting geomorphologic conditions can affect the hydrology, the paleo-environment and the biodiversity of extensional zones in Kenya and elsewhere.
Background: High-intensity muscle actions have the potential to temporarily improve the performance which has been denoted as postactivation performance enhancement.
Objectives: This study determined the acute effects of different stretch-shortening (fast vs. low) and strength (dynamic vs. isometric) exercises executed during one training session on subsequent balance performance in youth weightlifters.
Materials and Methods: Sixteen male and female young weightlifters, aged 11.3±0.6years, performed four strength exercise conditions in randomized order, including dynamic strength (DYN; 3 sets of 3 repetitions of 10 RM) and isometric strength exercises (ISOM; 3 sets of maintaining 3s of 10 RM of back-squat), as well as fast (FSSC; 3 sets of 3 repetitions of 20-cm drop-jumps) and slow (SSSC; 3 sets of 3 hurdle jumps over a 20-cm obstacle) stretch-shortening cycle protocols. Balance performance was tested before and after each of the four exercise conditions in bipedal stance on an unstable surface (i.e., BOSU ball with flat side facing up) using two dependent variables, i.e., center of pressure surface area (CoP SA) and velocity (CoP V).
Results: There was a significant effect of time on CoP SA and CoP V [F(1,60)=54.37, d=1.88, p<0.0001; F(1,60)=9.07, d=0.77, p=0.003]. In addition, a statistically significant effect of condition on CoP SA and CoP V [F(3,60)=11.81, d=1.53, p<0.0001; F(3,60)=7.36, d=1.21, p=0.0003] was observed. Statistically significant condition-by-time interactions were found for the balance parameters CoP SA (p<0.003, d=0.54) and CoP V (p<0.002, d=0.70). Specific to contrast analysis, all specified hypotheses were tested and demonstrated that FSSC yielded significantly greater improvements than all other conditions in CoP SA and CoP V [p<0.0001 (d=1.55); p=0.0004 (d=1.19), respectively]. In addition, FSSC yielded significantly greater improvements compared with the two conditions for both balance parameters [p<0.0001 (d=2.03); p<0.0001 (d=1.45)].
Conclusion: Fast stretch-shortening cycle exercises appear to be more effective to improve short-term balance performance in young weightlifters. Due to the importance of balance for overall competitive achievement in weightlifting, it is recommended that young weightlifters implement dynamic plyometric exercises in the fast stretch-shortening cycle during the warm-up to improve their balance performance.