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With the recent growth of sensors, cloud computing handles the data processing of many applications. Processing some of this data on the cloud raises, however, many concerns regarding, e.g., privacy, latency, or single points of failure. Alternatively, thanks to the development of embedded systems, smart wireless devices can share their computation capacity, creating a local wireless cloud for in-network processing. In this context, the processing of an application is divided into smaller jobs so that a device can run one or more jobs.
The contribution of this thesis to this scenario is divided into three parts. In part one, I focus on wireless aspects, such as power control and interference management, for deciding which jobs to run on which node and how to route data between nodes. Hence, I formulate optimization problems and develop heuristic and meta-heuristic algorithms to allocate wireless and computation resources. Additionally, to deal with multiple applications competing for these resources, I develop a reinforcement learning (RL) admission controller to decide which application should be admitted. Next, I look into acoustic applications to improve wireless throughput by using microphone clock synchronization to synchronize wireless transmissions.
In the second part, I jointly work with colleagues from the acoustic processing field to optimize both network and application (i.e., acoustic) qualities. My contribution focuses on the network part, where I study the relation between acoustic and network qualities when selecting a subset of microphones for collecting audio data or selecting a subset of optional jobs for processing these data; too many microphones or too many jobs can lessen quality by unnecessary delays. Hence, I develop RL solutions to select the subset of microphones under network constraints when the speaker is moving while still providing good acoustic quality. Furthermore, I show that autonomous vehicles carrying microphones improve the acoustic qualities of different applications. Accordingly, I develop RL solutions (single and multi-agent ones) for controlling these vehicles.
In the third part, I close the gap between theory and practice. I describe the features of my open-source framework used as a proof of concept for wireless in-network processing. Next, I demonstrate how to run some algorithms developed by colleagues from acoustic processing using my framework. I also use the framework for studying in-network delays (wireless and processing) using different distributions of jobs and network topologies.
Functional characterization of ROS-responsive genes, ANAC085 and ATR7, in Arabidopsis thaliana
(2023)
This thesis explores the variation in coreference patterns across language modes (i.e., spoken and written) and text genres. The significance of research on variation in language use has been emphasized in a number of linguistic studies. For instance, Biber and Conrad [2009] state that “register/genre variation is a fundamental aspect of human language” and “Given the ubiquity of register/genre variation, an understanding of how linguistic features are used in patterned ways across text varieties is of central importance for both the description of particular languages and the development of cross-linguistic theories of language use.”[p.23]
We examine the variation across genres with the primary goal of contributing to the body of knowledge on the description of language use in English. On the computational side, we believe that incorporating linguistic knowledge into learning-based systems can boost the performance of automatic natural language processing systems, particularly for non-standard texts. Therefore, in addition to their descriptive value, the linguistic findings we provide in this study may prove to be helpful for improving the performance of automatic coreference resolution, which is essential for a good text understanding and beneficial for several downstream NLP applications, including machine translation and text summarization.
In particular, we study a genre of texts that is formed of conversational interactions on the well-known social media platform Twitter. Two factors motivate us: First, Twitter conversations are realized in written form but resemble spoken communication [Scheffler, 2017], and therefore they form an atypical genre for the written mode. Second, while Twitter texts are a complicated genre for automatic coreference resolution, due to their widespread use in the digital sphere, at the same time they are highly relevant for applications that seek to extract information or sentiments from users’ messages. Thus, we are interested in discovering more about the linguistic and computational aspects of coreference in Twitter conversations. We first created a corpus of such conversations for this purpose and annotated it for coreference. We are interested in not only the coreference patterns but the overall discourse behavior of Twitter conversations. To address this, in addition to the coreference relations, we also annotated the coherence relations on the corpus we compiled. The corpus is available online in a newly developed form that allows for separating the tweets from their annotations.
This study consists of three empirical analyses where we independently apply corpus-based, psycholinguistic and computational approaches for the investigation of variation in coreference patterns in a complementary manner. (1) We first make a descriptive analysis of variation across genres through a corpus-based study. We investigate the linguistic aspects of nominal coreference in Twitter conversations and we determine how this genre relates to other text genres in spoken and written modes. In addition to the variation across genres, studying the differences in spoken-written modes is also in focus of linguistic research since from Woolbert [1922]. (2) In order to investigate whether the language mode alone has any effect on coreference patterns, we carry out a crowdsourced experiment and analyze the patterns in the same genre for both spoken and written modes. (3) Finally, we explore the potentials of domain adaptation of automatic coreference resolution (ACR) for the conversational Twitter data. In order to answer the question of how the genre of Twitter conversations relates to other genres in spoken and written modes with respect to coreference patterns, we employ a state-of-the-art neural ACR model [Lee et al., 2018] to examine whether ACR on Twitter conversations will benefit from mode-based separation in out-of-domain training data.
Insight by de—sign
(2023)
The calculus of design is a diagrammatic approach towards the relationship between design and insight. The thesis I am evolving is that insights are not discovered, gained, explored, revealed, or mined, but are operatively de—signed. The de in design neglects the contingency of the space towards the sign. The — is the drawing of a distinction within the operation. Space collapses through the negativity of the sign; the command draws a distinction that neglects the space for the form's sake. The operation to de—sign is counterintuitively not the creation of signs, but their removal, the exclusion of possible sign propositions of space. De—sign is thus an act of exclusion; the possibilities of space are crossed into form.
Planets outside our solar system, so-called "exoplanets", can be detected with different methods, and currently more than 5000 exoplanets have been confirmed, according to NASA Exoplanet Archive. One major highlight of the studies on exoplanets in the past twenty years is the characterization of their atmospheres usingtransmission spectroscopy as the exoplanet transits. However, this characterization is a challenging process and sometimes there are reported discrepancies in the literature regarding the atmosphere of the same exoplanet. One potential reason for the observed atmospheric inconsistencies is called impact parameter degeneracy, and it is highly driven by the limb darkening effect of the host star. A brief introductionto those topics in presented in chapter 1, while the motivation and objectives of thiswork are described in chapter 2.The first goal is to clarify the origin of the transmission spectrum, which is anindicator of an exoplanet’s atmosphere; whether it is real or influenced by the impactparameter degeneracy. A second goal is to determine whether photometry from space using the Transiting Exoplanet Survey Satellite (TESS), could improve on the major parameters, which are responsible for the aforementioned degeneracy, of known exoplanetary systems. Three individual projects were conducted in order toaddress those goals. The three manuscripts are presented, in short, in the manuscriptoverview in chapter 3.More specifically, in chapter 4, the first manuscript is presented, which is an ex-tended investigation on the impact parameter degeneracy and its application onsynthetic transmission spectra. Evidently, the limb darkening of the host star isan important driver for this effect. It keeps the degeneracy persisting through different groups of exoplanets, based on the uncertainty of their impact parameter and on the type of their host star. The second goal, was addressed in the second and third manuscripts (chapter 5 and chapter 6 respectively). Using observationsfrom the TESS mission, two samples of exoplanets were studied; 10 transiting inflated hot-Jupiters and 43 transiting grazing systems. Potentially, the refinement or confirmation of their major system parameters’ measurements can assist in solving current or future discrepancies regarding their atmospheric characterization.In chapter 7 the conclusions of this work are discussed, while in chapter 8 itis proposed how TESS’s measurements can be able to discern between erroneousinterpretations of transmission spectra, especially on systems where the impact parameter degeneracy is likely not applicable.
The African weakly electric fish genus Campylomormyrus includes 15 described species mostly native to the Congo River and its tributaries. They are considered sympatric species, because their distribution area overlaps. These species generate species-specific electric organ discharges (EODs) varying in waveform characteristics, including duration, polarity, and phase number. They exhibit also pronounced divergence in their snout, i.e. the length, thickness, and curvature. The diversifications in these two phenotypical traits (EOD and snout) have been proposed as key factors promoting adaptive radiation in Campylomormyrus. The role of EODs as a pre-zygotic isolation mechanism driving sympatric speciation by promoting assortative mating has been examined using behavioral, genetical, and histological approaches. However, the evolutionary effects of the snout morphology and its link to species divergence have not been closely examined. Hence, the main objective of this study is to investigate the effect of snout morphology diversification and its correlated EOD to better understand their sympatric speciation and evolutionary drivers. Moreover, I aim to utilize the intragenus and intergenus hybrids of Campylomormyrus to better understand trait divergence as well as underlying molecular/genetic mechanisms involved in the radiation scenario. To this end, I utilized three different approaches: feeding behavior analysis, diet assessment, and geometric morphometrics analysis. I performed feeding behavior experiments to evaluate the concept of the phenotype-environment correlation by testing whether Campylomormyrus species show substrate preferences. The behavioral experiments showed that the short snout species exhibits preference to sandy substrate, the long snout species prefers a stone substrate, and the species with intermediate snout size does not exhibit any substrate preference. The experiments suggest that the diverse feeding apparatus in the genus Campylomormyrus may have evolved in adaptation to their microhabitats. I also performed diet assessments of sympatric Campylomormyrus species and a sister genus species (Gnathonemus petersii) with markedly different snout morphologies and EOD using NGS-based DNA metabarcoding of their stomach contents. The diet of each species was documented showing that aquatic insects such as dipterans, coleopterans and trichopterans represent the major diet component. The results showed also that all species are able to exploit diverse food niches in their habitats. However, comparing the diet overlap indices showed that different snout morphologies and the associated divergence in the EOD translated into different prey spectra. These results further support the idea that the EOD could be a ‘magic trait’ triggering both adaptation and reproductive isolation. Geometric morphometrics method was also used to compare the phenotypical shape traits of the F1 intragenus (Campylomormyrus) and intergenus (Campylomormyrus species and Gnathonemus petersii) hybrids relative to their parents. The hybrids of these species were well separated based on the morphological traits, however the hybrid phenotypic traits were closer to the short-snouted species. In addition, the likelihood that the short snout expressed in the hybrids increases with increasing the genetic distance of the parental species. The results confirmed that additive effects produce intermediate phenotypes in F1-hybrids. It seems, therefore, that morphological shape traits in hybrids, unlike the physiological traits, were not expressed straightforward.
Starch is an essential biopolymer produced by plants. Starch can be made inside source tissue (such as leaves) and sink tissue (such as fruits and tubers). Nevertheless, understanding how starch metabolism is regulated in source and sink tissues is fundamental for improving crop production.
Despite recent advances in the understanding of starch and its metabolism, there is still a knowledge gap in the source and sink metabolism. Therefore, this study aimed to summarize the state of the art regarding starch structure and metabolism inside plants. In addition, this study aimed to elucidate the regulation of starch metabolism in the source tissue using the leaves of a model organism, Arabidopsis thaliana, and the sink tissue of oil palm (Elaeis guineensis) fruit as a commercial crop.
The research regarding the source tissue will focus on the effect of the blockage of starch degradation on the starch parameter in leaves, especially in those of A. thaliana, which lack both disproportionating enzyme 2 (DPE2) and plastidial glucan phosphorylase 1 (PHS1) (dpe2/phs1). The additional elimination of phosphoglucan water dikinase (PWD), starch excess 4 (SEX4), isoamylase 3 (ISA3), and disproportionating enzyme 1 (DPE1) in the dpe2/phs1 mutant background demonstrates the alteration of starch granule number per chloroplast. This study provides insights into the control mechanism of granule number regulation in the chloroplast.
The research regarding the sink tissue will emphasize the relationship between starch metabolism and the lipid metabolism pathway in oil palm fruits. This study was conducted to observe the alteration of starch parameters, metabolite abundance, and gene expression during oil palm fruit development with different oil yields. This study shows that starch and sucrose can be used as biomarkers for oil yield in oil palms. In addition, it is revealed that the enzyme isoforms related to starch metabolism influence the oil production in oil palm fruit.
Overall, this thesis presents novel information regarding starch metabolism in the source tissue of A.thaliana and the sink tissue of E.guineensis. The results shown in this thesis can be applied to many applications, such as modifying the starch parameter in other plants for specific needs.
The electrical resistivity tomography (ERT) method is widely used to investigate geological, geotechnical, and hydrogeological problems in inland and aquatic environments (i.e., lakes, rivers, and seas). The objective of the ERT method is to obtain reliable resistivity models of the subsurface that can be interpreted in terms of the subsurface structure and petrophysical properties. The reliability of the resulting resistivity models depends not only on the quality of the acquired data, but also on the employed inversion strategy. Inversion of ERT data results in multiple solutions that explain the measured data equally well. Typical inversion approaches rely on different deterministic (local) strategies that consider different smoothing and damping strategies to stabilize the inversion. However, such strategies suffer from the trade-off of smearing possible sharp subsurface interfaces separating layers with resistivity contrasts of up to several orders of magnitude. When prior information (e.g., from outcrops, boreholes, or other geophysical surveys) suggests sharp resistivity variations, it might be advantageous to adapt the parameterization and inversion strategies to obtain more stable and geologically reliable model solutions. Adaptations to traditional local inversions, for example, by using different structural and/or geostatistical constraints, may help to retrieve sharper model solutions. In addition, layer-based model parameterization in combination with local or global inversion approaches can be used to obtain models with sharp boundaries.
In this thesis, I study three typical layered near-surface environments in which prior information is used to adapt 2D inversion strategies to favor layered model solutions. In cooperation with the coauthors of Chapters 2-4, I consider two general strategies. Our first approach uses a layer-based model parameterization and a well-established global inversion strategy to generate ensembles of model solutions and assess uncertainties related to the non-uniqueness of the inverse problem. We apply this method to invert ERT data sets collected in an inland coastal area of northern France (Chapter~2) and offshore of two Arctic regions (Chapter~3). Our second approach consists of using geostatistical regularizations with different correlation lengths. We apply this strategy to a more complex subsurface scenario on a local intermountain alluvial fan in southwestern Germany (Chapter~4). Overall, our inversion approaches allow us to obtain resistivity models that agree with the general geological understanding of the studied field sites. These strategies are rather general and can be applied to various geological environments where a layered subsurface structure is expected. The flexibility of our strategies allows adaptations to invert other kinds of geophysical data sets such as seismic refraction or electromagnetic induction methods, and could be considered for joint inversion approaches.
Background: Physical fitness is a key aspect of children’s ability to perform activities of daily living, engage in leisure activities, and is associated with important health characteristics. As such, it shows multi-directional associations with weight status as well as executive functions, and varies according to a variety of moderating factors, such as the child’s gender, age, geographical location, and socioeconomic conditions and context. The assessment and monitoring of children’s physical fitness has gained attention in recent decades, as has the question of how to promote physical fitness through the implementation of a variety of programs and interventions. However, these programs and interventions rarely focus on children with deficits in their physical fitness. Due to their deficits, these children are at the highest risk of suffering health impairments compared to their more average fit peers. In efforts to promote physical fitness, schools could offer promising and viable approaches to interventions, as they provide access to large youth populations while providing useful infrastructure. Evidence suggests that school-based physical fitness interventions, particularly those that include supplementary physical education, are useful for promoting and improving physical fitness in children with normal fitness. However, there is little evidence on whether these interventions have similar or even greater effects on children with deficits in their physical fitness. Furthermore, the question arises whether these measures help to sustainably improve the development/trajectories of physical fitness in these children.
The present thesis aims to elucidate the following four objectives: (1) to evaluate the effects of a 14 week intervention with 2 x 45 minutes per week additional remedial physical education on physical fitness and executive function in children with deficits in their physical fitness; (2) to assess moderating effects of body height and body mass on physical fitness components in children with physical fitness deficits; (3) to assess moderating effects of age and skeletal growth on physical fitness in children with physical fitness deficits; and (4) to analyse moderating effects of different physical fitness components on executive function in children with physical fitness deficits.
Methods: Using physical fitness data from the EMOTIKON study, 76 third graders with physical fitness deficits were identified in 11 schools in Brandenburg state that met the requirements for implementing a remedial physical education intervention (i.e., employing specially trained physical education teachers). The fitness intervention was implemented in a cross-over design and schools were randomly assigned to either an intervention-control or control-intervention group. The remedial physical education intervention consisted of a 14 week, 2 x 45 minutes per week remedial physical education curriculum supplemented by a physical exercise homework program. Assessments were conducted at the beginning and end of each intervention and control period, and further assessments were conducted at the beginning and end of each school year until the end of sixth grade. Physical fitness as the primary outcome was assessed using fitness tests implemented in the EMOTIKON study (i.e., lower body muscular strength (standing long jump), speed (20 m sprint), cardiorespiratory fitness (6 min run), agility (star run), upper body muscular strength (ball push test), and balance (one leg balance)). Executive functions as a secondary outcome were assessed using attention and psychomotor processing speed (digit symbol substitution test), mental flexibility and fine motor skills (trail making test), and inhibitory control (Simon task). Anthropometric measures such as body height, body mass, maturity offset, and body composition parameters, as well as socioeconomic information were recorded as potential moderators.
Results: (1) The evaluation of possible effects of the remedial physical education intervention on physical fitness and executive functions of children with deficits in their physical fitness did not reveal any detectable intervention-related improvements in physical fitness or executive functions. The implemented analysis strategies also showed moderating effects of body mass index (BMI) on performance in 6 min run, star run, and standing long jump, with children with a lower BMI performing better, moderating effects of proximity to Berlin on performance in the 6 min run and standing long jump, better performances being found in children living closer to Berlin, and overall gendered differences in executive function test performance, with boys performing better compared to girls. (2) Analysing moderating effects of body height and body mass on physical fitness performance, better overall physical fitness performance was found for taller children. For body mass, a negative effect was found on performance in the 6 min run (linear), standing long jump (linear), and 20 m sprint (quadratic), with better performance associated with lighter children, and a positive effect of body mass on performance in the ball push test, with heavier children performing better. In addition, the analysis revealed significant interactions between body height and body mass on performance in 6 min run and 20 m sprint, with higher body mass being associated with performance improvements in larger children, while higher body mass was associated with performance declines in smaller children. In addition, the analysis revealed overall age-related improvements in physical fitness and was able to show that children with better overall physical fitness also elicit greater age-related improvements. (3) In the analysis of moderating effects of age and maturity offset on physical fitness performances, two unrotated principal components of z-transformed age and maturity offset values were calculated (i.e., relative growth = (age + maturity offset)/2; growth delay = (age - maturity offset)) to avoid colinearity. Analysing these constructs revealed positive effects of relative growth on performances in star run, 20 m sprint, and standing long jump, with children of higher relative growth performing better. For growth delay, positive effects were found on performances in 6 min run and 20 m sprint, with children having larger growth delays showing better performances. Further, the model revealed gendered differences in 6 min run and 20 m sprint performances with girls performing better than boys. (4) Analysing the effects of physical fitness tests on executive function revealed a positive effect of star run and one leg balance performance and a negative effect of 6 min run performance on reaction speed in the Simon task. However, these effects were not detectable when individual differences were accounted for. Then these effects showed overall positive effects, with better performances being associated with faster reaction speeds. In addition, the analysis revealed a positive correlation between overall reaction speed and effects of the 6 min run, suggesting that children with greater effects of 6 min run had faster overall reaction speeds. Negative correlations were found between star run effects and age effects on Simon task reaction speed, meaning that children with larger star run effects had smaller age effects, and between 6 min run effects and star run effects on Simon task reaction speed, meaning that children with larger 6 min run effects tended to have smaller star run effects on Simon task reaction speed and vice versa.
Conclusions: (1) The lack of detectable intervention-related effects could have been caused by an insufficient intervention period, by the implementation of comprehensive and thus non- specific exercises, or by both. Accordingly, longer intervention periods and/or more specific exercises may have been more beneficial and could have led to detectable improvements in physical fitness and/or executive function. However, it remains unclear whether these interventions can benefit children with deficits in physical fitness, as it is possible that their deficits are not caused by a mere lack of exercise, but rather depend on the socioeconomic conditions of the children and their families and areas. Therefore, further research is needed to assess the moderation of physical fitness in children with physical fitness deficits and, in particular, the links between children’s environment and their physical fitness trajectories. (2) Findings from this work suggest that using BMI as a composite of body height and body mass may not be able to capture the variation associated with these parameters and their interactions. In particular, because of their multidirectional associations, further research would help elucidate how BMI and its subcomponents influence physical fitness and how they vary between children with and without physical fitness deficits. (3) The assessment of growth- related changes indicated negative effects associated with the growth spurt approaching age of peak height velocity, and furthermore showed significant differences in these effects between children. Thus, these effects and possible interindividual differences should be considered in the assessment of the development of physical fitness in children. (4) Furthermore, this work has shown that the associations between physical fitness and executive functions vary between children and may be moderated by children’s socioeconomic conditions and the structure of their daily activities. Further research is needed to explore these associations using approaches that account for individual variance.
In the last two decades, process mining has developed from a niche
discipline to a significant research area with considerable impact on academia and industry. Process mining enables organisations to identify the running business processes from historical execution data. The first requirement of any process mining technique is an event log, an artifact that represents concrete business process executions in the form of sequence of events. These logs can be extracted from the organization's information systems and are used by process experts to retrieve deep insights from the organization's running processes. Considering the events pertaining to such logs, the process models can be automatically discovered and enhanced or annotated with performance-related information. Besides behavioral information, event logs contain domain specific data, albeit implicitly. However, such data are usually overlooked and, thus, not utilized to their full potential.
Within the process mining area, we address in this thesis the research gap of discovering, from event logs, the contextual information that cannot be captured by applying existing process mining techniques. Within this research gap, we identify four key problems and tackle them by looking at an event log from different angles. First, we address the problem of deriving an event log in the absence of a proper database access and domain knowledge. The second problem is related to the under-utilization of the implicit domain knowledge present in an event log that can increase the understandability of the discovered process model. Next, there is a lack of a holistic representation of the historical data manipulation at the process model level of abstraction. Last but not least, each process model presumes to be independent of other process models when discovered from an event log, thus, ignoring possible data dependencies between processes within an organization.
For each of the problems mentioned above, this thesis proposes a dedicated method. The first method provides a solution to extract an event log only from the transactions performed on the database that are stored in the form of redo logs. The second method deals with discovering the underlying data model that is implicitly embedded in the event log, thus, complementing the discovered process model with important domain knowledge information. The third method captures, on the process model level, how the data affects the running process instances. Lastly, the fourth method is about the discovery of the relations between business processes (i.e., how they exchange data) from a set of event logs and explicitly representing such complex interdependencies in a business process architecture.
All the methods introduced in this thesis are implemented as a prototype and their feasibility is proven by being applied on real-life event logs.
Seasonal forecasts are of great interest in many areas. Knowing the amount of precipitation for the upcoming season in regions of water scarcity would facilitate a better water management. If farmers knew the weather conditions of the upcoming summer at sowing time, they could select those cereal species that are best adapted to these conditions. This would allow farmers to improve the harvest and potentially even reduce the amount of pesticides used. However, the undoubted advantages of seasonal forecasts are often opposed by their high degree of uncertainty. The great challenge of generating seasonal forecasts with lead times of several months mainly originates from the chaotic nature of the earth system. In a chaotic system, even tiny differences in the initial conditions can lead to strong deviations in the system’s state in the long run.
In this dissertation we propose an emergent machine learning approach for seasonal forecasting, called the AnlgModel. The AnlgModel combines the analogue method with myopic feature selection and bootstrapping. To benchmark the abilities of the AnlgModel we apply it to seasonal cyclone activity forecasts in the North Atlantic and Northwest Pacific. The AnlgModel demonstrates competitive hindcast skills with two operational forecasts and even outperforms these for long lead times.
In the second chapter we comprehend the forecasting strategy of the Anlg-Model. We thereby analyse the analogue selection process for the 2017 North Atlantic and the 2018 Northwest Pacific seasonal cyclone activity. The analysis shows that those climate indices which are known to influence the seasonal cyclone activity, such as the Niño 3.4 SST, are correctly represented among the selected analogues. Furthermore the selected analogues reflect large-scale climate patterns that were identified by expert reports as being determinative for these particular seasons.
In the third chapter we analyse the features that are used by the AnlgModel for its predictions. We therefore inspect the feature relevance (FR). The FR patterns learned by the AnlgModel show a high congruence with the predictor regions used by the operational forecasts. However, the AnlgModel also discovered new features, such as the SST anomaly in the Gulf of Guinea during November. This SST pattern exhibits a remarkably high predictive potential for the upcoming Atlantic hurricane activity.
In the final chapter we investigate potential mechanisms, that link two of these regions with high feature relevance to the Atlantic hurricane activity. We mainly focus on ocean surface transport. The ocean surface flow paths are calculated using Lagrangian particle analysis. We demonstrate that the FR patterns in the region of the Canary islands do not correspond with ocean surface transport. It is instead likely that these FR patterns fingerprint a wind transport of latent heat. The second region to be studied is situated in the Gulf of Guinea. Our analysis shows that the FR patterns seen there do fingerprint ocean surface transport. However, our simulations also show that at least one other mechanism is involved in linking the Gulf of Guinea SST anomaly in November to the hurricane activity of the upcoming season.
In this work the AnlgModel does not only demonstrate its outstanding forecast skills but also shows its capabilities as research tool for detecting oceanic and atmospheric mechanisms.
Arthur Schopenhauer (1788–1860) was perhaps the last polymath among the great Germanic philosophers. Switching with ease and elegance between epistemic positions and fields as diverse as idealism and empiricism, fideism and rationalism, realism and nominalism, art and religion, jurisprudence and politics, psychology and occultism, Schopenhauer erected an imposing edifice bearing testimony to his universal learning. This study is an investigation into the very conclusion of Schopenhauer’s philosophy and endeavours to answer the following question: did Schopenhauer’s doctrine of salvation issue forth organically from his intellectual output or was it annexed to his philosophy as a result of his critical engagement with religion? The labyrinthine paths through which Schopenhauer arrives at the soteriological culmination of his philosophy are subjected to critical assessment; the picture that emerges is of a philosopher who seemed convinced that he had solved some of the most pressing cosmic riddles to have tormented mankind through the ages.
Social networking sites
(2023)
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
Plant metabolism serves as the primary mechanism for converting assimilated carbon into essential compounds crucial for plant growth and ultimately, crop yield. This renders it a focal point of research with significant implications. Despite notable strides in comprehending the genetic principles underpinning metabolism and yield, there remains a dearth of knowledge regarding the genetic factors responsible for trait variation under varying environmental conditions. Given the burgeoning global population and the advancing challenges posed by climate change, unraveling the intricacies of metabolic and yield responses to water scarcity became increasingly important in safeguarding food security.
Our research group has recently started to work on the genetic resources of legume species. To this end, the study presented here investigates the metabolic diversity across five different legume species at a tissue level, identifying species-specific biosynthesis of alkaloids as well as iso-/flavonoids with diverse functional groups, namely prenylation, phenylacylation as well as methoxylation, to create a resource for follow up studies investigation the metabolic diversity in natural diverse populations of legume species.
Following this, the second study investigates the genetic architecture of drought-induced changes in a global common bean population. Here, a plethora of quantitative trait loci (QTL) associated with various traits are identified by performing genome-wide association studies (GWAS), including for lipid signaling. On this site, overexpression of candidates highlighted the induction of several oxylipins reported to be pivotal in coping with harsh environmental conditions such as water scarcity.
Diverging from the common bean and GWAS, the following study focuses on identifying drought-related QTL in tomato using a bi-parental breeding population. This descriptive study highlights novel multi-omic QTL, including metabolism, photosynthesis as well as fruit setting, some of which are uniquely assigned under drought. Compared to conventional approaches using the bi-parental IL population, the study presented improves the resolution by assessing further backcrossed ILs, named sub-ILs.
In the final study, a photosynthetic gene, namely a PetM subunit of the cytochrome b6f complex encoding gene, involved in electron flow is characterized in an horticultural important crop. While several advances have been made in model organisms, this study highlights the transition of this fundamental knowledge to horticultural important crops, such as tomato, and investigates its function under differing light conditions. Overall, the presented thesis combines different strategies in unveiling the genetic components in multi-omic traits under drought using conventional breeding populations as well as a diverse global population. To this end, it allows a comparison of either approach and highlights their strengths and weaknesses.
Increasing demand for food, healthcare, and transportation arising from the growing world population is accompanied by and driving global warming challenges due to the rise of the atmospheric CO2 concentration. Industrialization for human needs has been increasingly releasing CO2 into the atmosphere for the last century or more. In recent years, the possibility of recycling CO2 to stabilize the atmospheric CO2 concentration and combat rising temperatures has gained attention. Thus, using CO2 as the feedstock to address future world demands is the ultimate solution while controlling the rapid climate change. Valorizing CO2 to produce activated and stable one-carbon feedstocks like formate and methanol and further upgrading them to industrial microbial processes to replace unsustainable feedstocks would be crucial for a future biobased circular economy. However, not all microbes can grow on formate as a feedstock, and those microbes that can grow are not well established for industrial processes.
S. cerevisiae is one of the industrially well-established microbes, and it is a significant contributor to bioprocess industries. However, it cannot grow on formate as a sole carbon and energy source. Thus, engineering S. cerevisiae to grow on formate could potentially pave the way to sustainable biomass and value-added chemicals production.
The Reductive Glycine Pathway (RGP), designed as the aerobic twin of the anaerobic Reductive Acetyl-CoA pathway, is an efficient formate and CO2 assimilation pathway. The RGP comprises of the glycine synthesis module (Mis1p, Gcv1p, Gcv2p, Gcv3p, and Lpd1p), the glycine to serine conversion module (Shmtp), the pyruvate synthesis module (Cha1p), and the energy supply module (Fdh1p). The RGP requires formate and elevated CO2 levels to operate the glycine synthesis module. In this study, I established the RGP in the yeast system using growth-coupled selection strategies to achieve formate and CO2-dependent biomass formation in aerobic conditions.
Firstly, I constructed serine biosensor strains by disrupting the native serine and glycine biosynthesis routes in the prototrophic S288c and FL100 yeast strains and insulated serine, glycine, and one-carbon metabolism from the central metabolic network. These strains cannot grow on glucose as the sole carbon source but require the supply of serine or glycine to complement the engineered auxotrophies. Using growth as a readout, I employed these strains as selection hosts to establish the RGP. Initially, to achieve this, I engineered different serine-hydroxymethyltransferases in the genome of serine biosensor strains for efficient glycine to serine conversion. Then, I implemented the glycine synthesis module of the RGP in these strains for the glycine and serine synthesis from formate and CO2. I successfully conducted Adaptive Laboratory Evolution (ALE) using these strains, which yielded a strain capable of glycine and serine biosynthesis from formate and CO2. Significant growth improvements from 0.0041 h-1 to 0.03695 h-1 were observed during ALE. To validate glycine and serine synthesis, I conducted carbon tracing experiments with 13C formate and 13CO2, confirming that more than 90% of glycine and serine biosynthesis in the evolved strains occurs via the RGP. Interestingly, labeling data also revealed that 10-15% of alanine was labelled, indicating pyruvate synthesis from the formate-derived serine using native serine deaminase (Cha1p) activity. Thus, RGP contributes to a small pyruvate pool which is converted to alanine without any selection pressure for pyruvate synthesis from formate. Hence, this data confirms the activity of all three modules of RGP even in the presence of glucose. Further, ALE in glucose limiting conditions did not improve pyruvate flux via the RGP.
Growth characterization of these strains showed that the best growth rates were achieved in formate concentrations between 25 mM to 300 mM. Optimum growth required 5% CO2, and dropped when the CO2 concentration was reduced from 5% to 2.5%.
Whole-genome sequencing of these evolved strains revealed mutations in genes that encode Gdh1p, Pet9p, and Idh1p. These enzymes might influence intracellular NADPH, ATP, and NADH levels, indicating adjustment to meet the energy demand of the RGP. I reverse-engineered the GDH1 truncation mutation on unevolved serine biosensor strains and reproduced formate dependent growth. To elucidate the effect of the GDH1 mutation on formate assimilation, I reintroduced this mutation in the S288c strain and conducted carbon-tracing experiments to compared formate assimilation between WT and ∆gdh1 mutant strains. Comparatively, enhanced formate assimilation was recorded in the ∆gdh1 mutant strain.
Although the 13C carbon tracing experiments confirmed the activity of all three modules of the RGP, the overall pyruvate flux via the RGP might be limited by the supply of reducing power. Hence, in a different approach, I overexpressed the formate dehydrogenase (Fdh1p) for energy supply and serine deaminase (Cha1p) for active pyruvate synthesis in the S288c parental strain and established growth on formate and serine without glucose in the medium. Further reengineering and evolution of this strain with a consistent energy, and formate-derived serine supply for pyruvate synthesis, is essential to achieve complete formatotrophic growth in the yeast system.
The G protein-coupled estrogen receptor (GPER1) is acknowledged as an important mediator of estrogen signaling. Given the ubiquitous expression of GPER1, it is likely that the receptor plays a role in a variety of malignancies, not only in the classic hormonally regulated tissues (e.g., breast, ovary, and prostate), but also in the colon. As colorectal cancer (CRC) is the third most common cancer in both men and women worldwide and environmental factors and dietary habits are important risk factors, it is increasingly recognized that natural and synthetic hormones and their associated receptors might play a role in CRC. Through oral consumption, environmental contaminants with endocrine activity are in contact with the gastrointestinal mucosa, where they might exert their toxic effects. Although GPER1 has been shown to be engaged in physiological and pathophysiological processes, its role in CRC remains poorly understood. Thus, pro- as well as anti-tumorigenic effects are described in the literature. This thesis has uncovered novel roles of GPER1 in mediating major CRC-associated phenotypes in transformed and non-transformed colon cell lines. Exposure to the estrogens 17β-estradiol (E2), bisphenol-A (BPA) and diethylstilbestrol (DES) but also the androgen dihydrotestosterone (DHT) resulted in GPER1-dependent induction of supernumerary centrosomes, whole chromosomal instability (w-CIN) and aneuploidy. Indeed, both knockdown and inhibition of GPER1 attenuated the generation of (xeno)hormone-driven supernumerary centrosomes and karyotype instability. Mechanistically, (xeno)hormone-induced centrosome amplification was associated with transient multipolar mitosis and the generation of so called anaphase “lagging” chromosomes. The results of this thesis propose a GPER1/PKA/AKAP9-pathway in regulating centrosome numbers in colorectal cancer cells and the involvement of the centriolar protein centrin. Remarkably, exposure to (xeno)hormones resulted in atypical enlargement and unexpected phosphorylation of the centriole marker centrin in interphase. These findings provide a novel role for GPER1 in key CRC-prone lesions and shed light on underlying mechanisms that involve GPER1 function in the colon. Elucidating to what extent centrosomal proteins are involved in the GPER1-mediated aneugenic effect will be an important task for future studies. The present study was intended to lay a first foundation to understand the molecular basis and potential risk factors of CRC which might help to reduce the use of laboratory animals. Since numerous animal experiments are conducted in biomedical research, the development of alternative methods is indispensable. The Federal Institute for Risk Assessment (BfR) as the German Center for the Protection of Laboratory Animals (Bf3R) addresses this issue by uncovering underlying mechanisms leading to colorectal cancer as necessary prerequisite in order to develop alternative methods.
Conservation of the jaguar relies on holistic and transdisciplinary conservation strategies that integratively safeguard essential, connected habitats, sustain viable populations and their genetic exchange, and foster peaceful human-jaguar coexistence. These strategies define four research priorities to advance jaguar conservation throughout the species’ range. In this thesis I provide several relevant ecological and sociological insights into these research priorities, each addressed in a separate chapter. I focus on the effects of anthropogenic landscapes on jaguar habitat use and population gene flow, spatial patterns of jaguar habitat suitability and functional population connectivity, and on innovative governance approaches which can work synergistically to help achieve human-wildlife conviviality. Furthermore, I translate these insights into recommendations for conservation practice by providing tools and suggestions that conservation managers and stakeholders can use to implement local actions but also make broad scale conservation decisions in Central America. In Chapter 2, I model regional habitat use of jaguars, producing spatially-explicit maps for management of key areas of habitat suitability. Using an occupancy model of 13-year-camera-trap occurrence data, I show that human influence has the strongest impact on jaguar habitat use, and that Jaguar Conservation Units are the most important reservoirs of high quality habitat in this region. I build upon these results by zooming in to an area of high habitat suitability loss in Chapter 3, northern Central America. Here I study the drivers of jaguar gene flow and I produce spatially-explicit maps for management of key areas of functional population connectivity in this region. I use microsatellite data and pseudo-optimized multiscale, multivariate resistance surfaces of gene flow to show that jaguar gene flow is influenced by environmental, and even more strongly, by human influence variables; and that the areas of lowest gene flow resistance largely coincide with the location of the Jaguar Conservation Units. Given that human activities significantly impact jaguar habitat use and gene flow, securing viable jaguar populations in anthropogenic landscapes also requires fostering peaceful human-wildlife coexistence. This is a complex challenge that cannot be met without transdisciplinary academic research and cross-sectoral, collaborative governance structures that effectively respond to the multiple challenges of such coexistence. With this in mind, I focus in Chapter 4 on carnivore conservation initiatives that apply transformative governance approaches to enact transformative change towards human-carnivore coexistence. Using the frameworks of transformative biodiversity governance and convivial conservation, I highlight in this chapter concrete pathways, supported by more inclusive, democratic forms of conservation decision-making and participation that promote truly transformative changes towards human-jaguar conviviality.
Soil is today considered a non-renewable resource on societal time scale, as the rate of soil loss is higher than the one of soil formation.
Soil formation is complex, can take several thousands of years and is influenced by a variety of factors, one of them is time. Oftentimes, there is the assumption of constant and progressive conditions for soil and/or profile development (i.e., steady-state). In reality, for most of the soils, their (co-)evolution leads to a complex and irregular soil development in time and space characterised by “progressive” and “regressive” phases.
Lateral transport of soil material (i.e., soil erosion) is one of the principal processes shaping the land surface and soil profile during “regressive” phases and one of the major environmental problems the world faces.
Anthropogenic activities like agriculture can exacerbate soil erosion. Thus, it is of vital importance to distinguish short-term soil redistribution rates (i.e., within decades) influenced by human activities differ from long-term natural rates. To do so, soil erosion (and denudation) rates can be determined by using a set of isotope methods that cover different time scales at landscape level.
With the aim to unravel the co-evolution of weathering, soil profile development and lateral redistribution on a landscape level, we used Pluthonium-239+240 (239+240Pu), Beryllium-10 (10Be, in situ and meteoric) and Radiocarbon (14C) to calculate short- and long-term erosion rates in two settings, i.e., a natural and an anthropogenic environment in the hummocky ground moraine landscape of the Uckermark, North-eastern Germany. The main research questions were:
1. How do long-term and short-term rates of soil redistributing processes differ?
2. Are rates calculated from in situ 10Be comparable to those of using meteoric 10Be?
3. How do soil redistribution rates (short- and long-term) in an agricultural and in a natural landscape compare to each other?
4. Are the soil patterns observed in northern Germany purely a result of past events (natural and/or anthropogenic) or are they imbedded in ongoing processes?
Erosion and deposition are reflected in a catena of soil profiles with no or almost no erosion on flat positions (hilltop), strong erosion on the mid-slope and accumulation of soil material at the toeslope position. These three characteristic process domains were chosen within the CarboZALF-D experimental site, characterised by intense anthropogenic activities. Likewise, a hydrosequence in an ancient forest was chosen for this study and being regarded as a catena strongly influenced by natural soil transport.
The following main results were obtained using the above-mentioned range of isotope methods available to measure soil redistribution rates depending on the time scale needed (e.g., 239+240Pu, 10Be, 14C):
1. Short-term erosion rates are one order of magnitude higher than long-term rates in agricultural settings.
2. Both meteoric and in situ 10Be are suitable soil tracers to measure the long-term soil redistribution rates giving similar results in an anthropogenic environment for different landscape positions (e.g., hilltop, mid-slope, toeslope)
3. Short-term rates were extremely low/negligible in a natural landscape and very high in an agricultural landscape – -0.01 t ha-1 yr-1 (average value) and -25 t ha-1 yr-1 respectively. On the contrary, long-term rates in the forested landscape are comparable to those calculated in the agricultural area investigated with average values of -1.00 t ha-1 yr-1 and -0.79 t ha-1 yr-1.
4. Soil patterns observed in the forest might be due to human impact and activities started after the first settlements in the region, earlier than previously postulated, between 4.5 and 6.8 kyr BP, and not a result of recent soil erosion.
5. Furthermore, long-term soil redistribution rates are similar independently from the settings, meaning past natural soil mass redistribution processes still overshadow the present anthropogenic erosion processes.
Overall, this study could make important contributions to the deciphering of the co-evolution of weathering, soil profile development and lateral redistribution in North-eastern Germany. The multi-methodological approach used can be challenged by the application in a wider range of landscapes and geographic regions.
Enacted in 2009, the National Policy on Climate Change (PNMC) is a milestone in the institutionalisation of climate action in Brazil. It sets greenhouse gas (GHG) emission reduction targets and a set of principles and directives that are intended to lay the foundations for a cross-sectoral and multilevel climate policy in the country. However, after more than a decade since its establishment, the PNMC has experienced several obstacles related to its governance, such as coordination, planning and implementation issues. All of these issues pose threats to the effectiveness of GHG mitigation actions in the country.
By looking at the intragovernmental and intergovernmental relationships that have taken place during the lifetime of the PNMC and its sectoral plans on agriculture (the Sectoral Plan for Mitigation and Adaptation to Climate Change for the Consolidation of a Low-Carbon Economy in Agriculture [ABC Plan]), transport and urban mobility (the Sectoral Plan for Transportation and Urban Mobility for Mitigation and Adaption of Climate Change [PSTM]), this exploratory qualitative research investigates the Brazilian climate change governance guided by the following relevant questions: how are climate policy arrangements organised and coordinated among governmental actors to mitigate GHG emissions in Brazil? What might be the reasons behind how such arrangements are established? What are the predominant governance gaps of the different GHG mitigation actions examined? Why do these governance gaps occur?
Theoretically grounded in the literature on multilevel governance and coordination of public policies, this study employs a novel analytical framework that aims to identify and discuss the occurrence of four types of governance gaps (i.e. politics, institutions and processes, resources and information) in the three GHG mitigation actions (cases) examined (i.e. the PNMC, ABC Plan and PSTM). The research results are twofold. First, they reveal that Brazil has struggled to organise and coordinate governmental actors from different policy constituencies and different levels of government in the implementation of the GHG mitigation actions examined. Moreover, climate policymaking has mostly been influenced by the Ministry of Environment (MMA) overlooking the multilevel and cross-sectoral approaches required for a country’s climate policy to mitigate and adapt to climate change, especially if it is considered an economy-wide Nationally Determined Contribution (NDC), as the Brazilian one is.
Second, the study identifies a greater manifestation of gaps in politics (e.g. lack of political will in supporting climate action), institutions and processes (e.g. failures in the design of institutions and policy instruments, coordination and monitoring flaws, and difficulties in building climate federalism) in all cases studied. It also identifies that there have been important advances in the production of data and information for decision-making and, to a lesser extent, in the allocation of technical and financial resources in the cases studied; however, it is necessary to highlight the limitation of these improvements due to turf wars, a low willingness to share information among federal government players, a reduced volume of financial resources and an unequal distribution of capacities among the federal ministries and among the three levels of government.
A relevant finding is that these gaps tend to be explained by a combination of general and sectoral set aspects. Regarding the general aspects, which are common to all cases examined, the following can be mentioned: i) unbalanced policy capabilities existing among the different levels of government, ii) a limited (bureaucratic) practice to produce a positive coordination mode within cross-sectoral policies, iii) the socioeconomic inequalities that affect the way different governments and economic sectors perceive the climate issue (selective perception) and iv) the reduced dialogue between national and subnational governments on the climate agenda (poor climate federalism). The following sectoral aspects can be mentioned: i) the presence of path dependencies that make the adoption of transformative actions harder and ii) the absence of perceived co-benefits that the climate agenda can bring to each economic sector (e.g. reputational gains, climate protection and access to climate financial markets).
By addressing the theoretical and practical implications of the results, this research provides key insights to tackle the governance gaps identified and to help Brazil pave the way to achieving its NDCs and net-zero targets. At the theoretical level, this research and the current country’s GHG emissions profile suggest that the Brazilian climate policy is embedded in a cross-sectoral and multilevel arena, which requires the effective involvement of different levels of political and bureaucratic powers and the consideration of the country’s socioeconomic differences. Thus, the research argues that future improvements of the Brazilian climate policy and its governance setting must frame climate policy as an economic development agenda, the ramifications of which go beyond the environmental sector. An initial consequence of this new perspective may be a shift in the political and technical leadership from the MMA to the institutions of the centre of government (Executive Office of the President of Brazil) and those in charge of the country’s economic policy (Ministry of Economy). This change could provide greater capacity for coordination, integration and enforcement as well as for addressing certain expected gaps (e.g. financial and technical resources). It could also lead to greater political prioritisation of the agenda at the highest levels of government. Moreover, this shift of the institutional locus could contribute to greater harmonisation between domestic development priorities and international climate politics. Finally, the research also suggests that this approach would reduce bureaucratic elitism currently in place due to climate policy being managed by Brazilian governmental institutions, which is still a theme of a few ministries and a reason for the occurrence of turf wars.
Transposable elements (TEs) are loci that can replicate and multiply within the genome of their host. Within the host, TEs through transposition are responsible for variation on genomic architecture and gene regulation across all vertebrates. Genome assemblies have increased in numbers in recent years. However, to explore in deep the variations within different genomes, such as SNPs (single nucleotide polymorphism), INDELs (Insertion-deletion), satellites and transposable elements, we need high-quality genomes. Studies of molecular markers in the past 10 years have limitations to correlate with biological differences because molecular markers rely on the accuracy of the genomic resources. This has generated that a substantial part of the studies of TE in recent years have been on high quality genomic resources such as Drosophila, zebrafinch and maize. As testudine have a slow mutation rate lower only to crocodilians, with more than 300 species, adapted to different environments all across the globe, the testudine clade can help us to study variation. Here we propose Testudines as a clade to study variation and the abundance of TE on different species that diverged a long time ago. We investigated the genomic diversity of sea turtles, identifying key genomic regions associated to gene family duplication, specific expansion of particular TE families for Dermochelyidae and that are important for phenotypic differentiation, the impact of environmental changes on their populations, and the dynamics of TEs within different lineages. In chapter 1, we identify that despite high levels of genome synteny within sea turtles, we identified that regions of reduced collinearity and microchromosomes showed higher concentrations of multicopy gene families, as well as genetic distances between species, indicating their potential importance as sources of variation underlying phenotypic differentiation. We found that differences in the ecological niches occupied by leatherback and green turtles have led to contrasting evolutionary paths for their olfactory receptor genes. We identified in leatherback turtles a long-term low population size. Nonetheless, we identify no correlation between the regions of reduced collinearity with abundance of TEs or an accumulation of a particular TE group. In chapter 2, we identified that sea turtle genomes contain a significant proportion of TEs, with differences in TE abundance between species, and the discovery of a recent expansion of Penelope-like elements (PLEs) in the highly conserved sea turtle genome provides new insights into the dynamics of TEs within Testudines. In chapter 3, we compared the proportion of TE across the Testudine clade, and we identified that the proportion of transposable elements within the clade is stable, regardless of the quality of the assemblies. However, we identified that the proportion of TEs orders has correlation with genome quality depending of their expanded abundancy. For retrotransposon, a highly abundant element for this clade, we identify no correlation. However, for DNA elements a rarer element on this clade, correlate with the quality of the assemblies.
Here we confirm that high-quality genomes are fundamental for the study of transposable element evolution and the conservation within the clade. The detection and abundance of specific orders of TEs are influenced by the quality of the genomes. We identified that a reduction in the population size on D. coriacea had left signals of long-term low population sizes on their genomes. On the same note we identified an expansion of TE on D. coriacea, not present in any other member of the available genomes of Testudines, strongly suggesting that it is a response of deregulation of TE on their genomes as consequences of the low population sizes.
Here we have identified important genomic regions and gene families for phenotypic differentiation and highlighted the impact of environmental changes on the populations of sea turtles. We stated that accurate classification and analysis of TE families are important and require high-quality genome assemblies. Using TE analysis we manage to identify differences in highly syntenic species. These findings have significant implications for conservation and provide a foundation for further research into genome evolution and gene function in turtles and other vertebrates. Overall, this study contributes to our understanding of evolutionary change and adaptation mechanisms.
Lanthanide based ceria nanomaterials are important practical materials due to their redox properties that are useful in technology and life sciences. This PhD thesis examined various properties and potential for catalytic and bio-applications of Ln3+-doped ceria nanomaterials. Ce1-xGdxO2-y: Eu3+, gadolinium doped ceria (GDC) (0 ≤ x ≤ 0.4) nanoparticles were synthesized by flame spray pyrolysis (FSP) and studied, followed by 15 % CexZr1-xO2-y: Eu3+|YSZ (0 ≤ x ≤ 1) nanocomposites. Furthermore, Ce1-xYb xO2-y (0.004 ≤ x ≤ 0.22) nanoparticles were synthesized by thermal decomposition and characterized. Finally, CeO2-y: Eu3+ nanoparticles were synthesized by a microemulsion method, biofunctionalized and characterized. The studies undertaken presents a novel approach to structurally elucidate ceria-based nanomaterials by way of Eu3+ and Yb3+ spectroscopy and processing the spectroscopic data with the multi-way decomposition method PARAFAC. Data sets of the three variables: excitation wavelength, emission wavelength and time were used to perform the deconvolution of spectra.
GDC nanoparticles from FSP are nano-sized and of roughly cubic shape and crystal structure (Fm3̅m). Raman data revealed four vibrational modes exhibited by Gd3+ containing samples whereas CeO2-y: Eu3+ displays only two. The room temperature, time-resolved emission spectra recorded at λexcitation = 464 nm show that Gd3+ doping results in significantly altered emission spectra compared to pure ceria. The PARAFAC analysis for the pure ceria samples reveals two species; a high-symmetry species and a low-symmetry species. The GDC samples yield two low-symmetry spectra in the same experiment. High-resolution emission spectra recorded at 4 K after probing the 5D0-7F0 transition revealed additional variation in the low symmetry Eu3+ sites in pure ceria and GDC. The data of the Gd3+-containing samples indicates that the average charge density around the Eu3+ ions in the lattice is inversely related to Gd3+ and oxygen vacancy concentration.
The particle crystallites of the 773 K and 1273 K annealed Yb3+ -ceria nanostructure materials are nano-sized and have a cubic fluorite structure with four Raman vibrational modes. Elemental maps clearly show that cluster formation occurs for 773 K annealed with high Yb3+ ion concentration from 15 mol % in the ceria lattice. These clusters are destroyed with annealing to 1273 K. The emission spectra observed from room temperature and 4 K measurements for the Ce1-xYb xO2-y samples have a manifold that corresponds to the 2F5/2-2F7/2 transition of Yb3+ ions. Some small shifts are observed in the Stark splitting pattern and are induced by the variations of the crystal field influenced by where the Yb3+ ions are located in the crystal lattices in the samples. Upon mixing ceria with high Yb3+ concentrations, the 2F5/2-2F7/2 transition is also observed in the Stark splitting pattern, but the spectra consist of two broad high background dominated peaks. Annealing the nanomaterials at 1273 K for 2 h changes the spectral signature as new peaks emerge. The deconvolution yielded luminescence decay kinetics as well as the accompanying luminescence spectra of three species for each of the low Yb3+ doped ceria samples annealed at 773 K and one species for the 1273 K annealed samples. However, the ceria samples with high Yb3+ concentration annealed at the two temperatures yielded one species with lower decay times as compared to the Yb3+ doped ceria samples after PARAFAC analysis.
Through the calcination of the nanocomposites at two high temperatures, the evolution of the emission patterns from specific Eu3+ lattice sites to indicate structural changes for the nanocomposites was followed. The spectroscopy results effectively complemented the data obtained from the conventional techniques. Annealing the samples at 773 K, resulted in amorphous, unordered domains whereas the TLS of the 1273 K nanocomposites reveal two distinct sites, with most red shifted Eu3+ species coming from pure Eu3+ doped ZrO2 on the YSZ support.
Finally, for Eu3+ doped ceria, successful transfer from hydrophobic to water phase and subsequent biocompatibility was achieved using ssDNA. PARAFAC analysis for the Eu3+ in nanoparticles dispersed in toluene and water revealed one Eu3+ species, with slightly differing surface properties for the nanoparticles as far as the luminescence kinetics and solvent environments were concerned. Several functionalized nanoparticles conjugated onto origami triangles after hybridization were visualized by atomic force microscopy (AFM). Putting all into consideration, Eu3+ and Yb3+ spectroscopy was used to monitor the structural changes and determining the feasibility of the nanoparticle transfer into water. PARAFAC proves to be a powerful tool to analyze lanthanide spectra in crystalline solid materials and in solutions, which are characterized by numerous Stark transitions and where measurements usually yield a superposition of different emission contributions to any given spectrum.
As a result of CMOS scaling, radiation-induced Single-Event Effects (SEEs) in electronic circuits became a critical reliability issue for modern Integrated Circuits (ICs) operating under harsh radiation conditions. SEEs can be triggered in combinational or sequential logic by the impact of high-energy particles, leading to destructive or non-destructive faults, resulting in data corruption or even system failure. Typically, the SEE mitigation methods are deployed statically in processing architectures based on the worst-case radiation conditions, which is most of the time unnecessary and results in a resource overhead. Moreover, the space radiation conditions are dynamically changing, especially during Solar Particle Events (SPEs). The intensity of space radiation can differ over five orders of magnitude within a few hours or days, resulting in several orders of magnitude fault probability variation in ICs during SPEs. This thesis introduces a comprehensive approach for designing a self-adaptive fault resilient multiprocessing system to overcome the static mitigation overhead issue. This work mainly addresses the following topics: (1) Design of on-chip radiation particle monitor for real-time radiation environment detection, (2) Investigation of space environment predictor, as support for solar particle events forecast, (3) Dynamic mode configuration in the resilient multiprocessing system. Therefore, according to detected and predicted in-flight space radiation conditions, the target system can be configured to use no mitigation or low-overhead mitigation during non-critical periods of time. The redundant resources can be used to improve system performance or save power. On the other hand, during increased radiation activity periods, such as SPEs, the mitigation methods can be dynamically configured appropriately depending on the real-time space radiation environment, resulting in higher system reliability. Thus, a dynamic trade-off in the target system between reliability, performance and power consumption in real-time can be achieved. All results of this work are evaluated in a highly reliable quad-core multiprocessing system that allows the self-adaptive setting of optimal radiation mitigation mechanisms during run-time. Proposed methods can serve as a basis for establishing a comprehensive self-adaptive resilient system design process. Successful implementation of the proposed design in the quad-core multiprocessor shows its application perspective also in the other designs.
Climate change of anthropogenic origin is affecting Earth’s biodiversity and therefore ecosystems and their services. High latitude ecosystems are even more impacted than the rest of Northern Hemisphere because of the amplified polar warming. Still, it is challenging to predict the dynamics of high latitude ecosystems because of complex interaction between abiotic and biotic components. As the past is the key to the future, the interpretation of past ecological changes to better understand ongoing processes is possible. In the Quaternary, the Pleistocene experienced several glacial and interglacial stages that affected past ecosystems. During the last Glacial, the Pleistocene steppe-tundra was covering most of unglaciated northern hemisphere and disappeared in parallel to the megafauna’s extinction at the transition to the Holocene (~11,700 years ago). The origin of the steppe-tundra decline is not well understood and knowledge on the mechanisms, which caused shifts in past communities and ecosystems, is of high priority as they are likely comparable to those affecting modern ecosystems. Lake or permafrost core sediments can be retrieved to investigate past biodiversity at transitions between glacial and interglacial stages. Siberia and Beringia were the origin of dispersal of the steppe-tundra, which make investigation this area of high priority. Until recently, macrofossils and pollen were the most common approaches. They are designed to reconstruct past composition changes but have limit and biases. Since the end of the 20th century, sedimentary ancient DNA (sedaDNA) can also be investigated. My main objectives were, by using sedaDNA approaches to provide scientific evidence of compositional and diversity changes in the Northern Hemisphere ecosystems at the transition between Quaternary glacial and interglacial stages.
In this thesis, I provide snapshots of entire ancient ecosystems and describe compositional changes between Quaternary glacial and interglacial stages, and confirm the vegetation composition and the spatial and temporal boundaries of the Pleistocene steppe-tundra. I identify a general loss of plant diversity with extinction events happening in parallel of megafauna’ extinction. I demonstrate how loss of biotic resilience led to the collapse of a previously well-established system and discuss my results in regards to the ongoing climate change. With further work to constrain biases and limits, sedaDNA can be used in parallel or even replace the more established macrofossils and pollen approaches as my results support the robustness and potential of sedaDNA to answer new palaeoecological questions such as plant diversity changes, loss and provide snapshots of entire ancient biota.
The evolution of a galaxy is pivotally governed by its pattern of star formation over a given period of time. The star formation rate at any given time is strongly dependent on the amount of cold gas available in the galaxy. Accretion of pristine gas from the Intergalactic medium (IGM) is thought to be one of the primary sources for star-forming gas. This gas first passes through the virial regions of the galaxy before reaching the Interstellar medium (ISM), the hub of star formation. On the other hand, owing to the evolutionary course of young and massive stars, energetic winds are ejected from the ISM to the virial regions of the galaxy. A bunch of interlinked, complex astrophysical processes, arising from the concurrent presence of both infalling as well as outbound gas, play out over a range of timescales in the halo region or the Circumgalactic medium (CGM) of a galaxy. It would not be incorrect to say that the CGM has a stronghold over the gas reserves of a galaxy and thus, plays a backhand, yet, rather pivotal role in shaping many galactic properties, some of which are also readily observable. Observing the multi-phase CGM (via spectral-line ion measurements), however, remains a non-trivial effort even today. Low particle densities as well as the CGM’s vast spatial extent, coupled with likely deviations from a spherical distribution, marr the possibility of obtaining complete, unbiased, high-quality spectral information tracing the full extent of the gaseous halo. This often incomplete information leads to multiple inferences about the CGM properties that give rise to multiple contradicting models. In this regard, computer simulations offer a neat solution towards testing and, subsequently, falsifying many of these existing CGM models. Thanks to their controlled environments, simulations are able to not only effortlessly transcend several orders of magnitude in time and space, but also get around many of the observational limitations and provide some unique views on many CGM properties. In this thesis, I focus on effectively using different computer simulations to understand the role of CGM in various astrophysical contexts, namely, the effect of Local Group (LG) environment, major merger events and satellite galaxies. In Chapter 2, I discuss the approach used for modeling various phases of the simulated z = 0 LG CGM in Hestia constrained simulations. Each of the three realizations contain a Milky Way (MW)–Andromeda (M31) galaxy pair, along with their corresponding sets of satellite galaxies, all embedded within the larger cosmological context. For characterizing the different temperature–density phases within the CGM, I model five tracer ions with cloudy ionization modeling. The cold and cool–ionized CGM (H i and Si iii respectively) in Hestia is very clumpy and distributed close to the galactic centers, while the warm-hot and hot CGM (O vi, O vii and O viii) is tenuous and volume-filling. On comparing the H i and Si iii column densities for the simulated M31 with observational measurements from Project AMIGA survey and other low-z galaxies, I found that Hestia galaxies produced less gas in the outer CGM, unlike observations. My carefully designed observational bias model subsequently revealed the possibility that some MW gas clouds might be incorrectly associated with the M31 CGM in observations, and hence, may be partly responsible for giving rise to the detected mismatch between simulated data and observations. In Chapter 3, I present results from four zoom–in, major merger, gas–rich simulations and the subsequent role of the gas, originally situated in the CGM, in influencing some of the galactic observables. The progenitor parameters are selected such that the post–merger remnants are MW–mass galaxies. We generally see a very clear gas bridge joining the merging galaxies in case of multiple passage mergers while such a bridge is mostly absent when a direct collision occurs. On the basis of particle–to–galaxy distance computations and tracer particle analysis, I found that about 33–48 percent of the cold gas contributing to the merger–induced star formation in the bridge originated from the CGM regions. In Chapter 4, I used a sample of 234 MW-mass, L* galaxies from the TNG50 cosmological simulations, with an aim of characterizing the impact of their global satellite populations on the extended cold CGM properties of their host L* halos. On the basis of halo mass and number of satellite galaxies (N_sats ), I categorized the sample into low and high mass bins, and subsequently into bottom, inter and top quartiles respectively. After confirming that satellites indeed influence the extended cold halo gas density profiles of the host galaxies, I investigated the effects of different satellite population parameters on the host halo cold CGMs. My analysis showed that there is hardly any cold gas associated with the satellite population of the lowest mass halos. The stellar mass of the most massive satellite (M_*mms ) impacted the cold gas in low mass bin halos the most, while N_sats (followed by M_*mms ) was the most influential factor for the high mass halos. In any case, how easily cold gas was stripped off the most massive satellite did not play much role. The number of massive (Stellar mass, M* > 10^8 M_solar) satellites as well as the M_*mms associated with a galaxy are two of the most crucial parameters determining how much cold gas ultimately finds its way from the satellites to the host halo. Low mass galaxies are found rather lacking on both these fronts unlike their high mass counterparts. This work highlights some aspects of the complex gas physics that constitute the basic essence of a low-z CGM. My analysis proved the importance of a cosmological environment, local surroundings and merger history in defining some key observable properties of a galactic CGM. Furthermore, I found that different satellite properties were responsible for affecting the cold–dense CGM of the low and high-mass parent galaxies. Finally, the LG emerged as an exciting prospect for testing and pinning down several intricate details about the CGM.
Supernova remnants are considered to be the primary sources of galactic cosmic rays. These cosmic rays are assumed to be accelerated by the diffusive shock acceleration mechanism, specifically at shocks in the remnants. Particularly in the core-collapse scenario, these supernova remnant shocks expand inside the wind-blown bubbles structured by massive progenitors during their lifetime. Therefore, the complex environment of wind bubbles can influence the particle acceleration and radiation from the remnants. Further, the evolution of massive stars depends on their Zero Age Main Sequence mass, rotation, and metallicity. Consequently, the structures of the wind bubbles generated during the lifetime of massive stars should be considerably different. Hence, the particle acceleration in the core-collapse supernova remnants should vary, not only from the remnants evolving in the uniform environment but also from one another, depending on their progenitor stars.
A core-collapse supernova remnant with a very massive 60 𝑀 ⊙ progenitor star has been considered to study the particle acceleration at the shock considering Bohm-like diffusion. This dissertation demonstrates the modification in particle acceleration and radiation while the remnant propagates through different regions of the wind bubble by impacts from the profiles of gas density, the temperature of the bubble and the magnetic field structure. Subsequently, in this thesis, I discuss the impacts of the non-identical ambient environment of core-collapse supernova remnants on particle spectra and the non-thermal emissions, considering 20 𝑀 ⊙ and 60 𝑀⊙ massive progenitors having different evolutionary tracks. Additionally, I also analyse the effect of cosmic ray streaming instabilities on particle spectra.
To model the particle acceleration in the remnants, I have performed simulations in one-dimensional spherical symmetry using RATPaC code. The transport equation for cosmic rays and magnetic turbulence in test-particle approximation, along with the induction equation for the evolution of the large-scale magnetic field, have been solved simultaneously with the hydrodynamic equations for the expansion of remnants inside the pre-supernova circumstellar medium.
The results from simulations describe that the spectra of accelerated particles in supernova remnants are regulated by density fluctuations, temperature variations, the large-scale magnetic field configuration and scattering turbulence. Although the diffusive shock acceleration mechanism at supernova remnant shock predicts the spectral index of 2 for the accelerated non-thermal particles, I have obtained the particle spectra that deviate from this prediction, in the core-collapse scenario. I have found that the particle spectral index reaches 2.5 for the supernova remnant with 60 𝑀 ⊙ progenitor when the remnant resides inside the shocked wind region of the wind bubble, and this softness persists at later evolutionary stages even with Bohm-like diffusion for accelerated particles. However, the supernova remnant with 20 𝑀 ⊙ progenitor does not demonstrate persistent softness in particle spectra from the influence of the hydrodynamics of the corresponding wind bubble. At later stages of evolution, the particle spectra illustrate softness at higher energies for both remnants as the consequence of the escape of high-energy particles from the remnants while considering the cosmic ray streaming instabilities. Finally, I have probed the emission morphology of remnants that varies depending on the progenitors, particularly in earlier evolutionary stages. This dissertation provides insight into different core-collapse remnants expanding inside wind bubbles, for instance, the calculated gamma-ray spectral index from the supernova remnant with 60 𝑀 ⊙ progenitor at later evolutionary stages is consistent with that of the observed supernova remnants expanding in dense molecular clouds.
In recent decades, astronomy has seen a boom in large-scale stellar surveys of the Galaxy. The detailed information obtained about millions of individual stars in the Milky Way is bringing us a step closer to answering one of the most outstanding questions in astrophysics: how do galaxies form and evolve? The Milky Way is the only galaxy where we can dissect many stars into their high-dimensional chemical composition and complete phase space, which analogously as fossil records can unveil the past history of the genesis of the Galaxy. The processes that lead to large structure formation, such as the Milky Way, are critical for constraining cosmological models; we call this line of study Galactic archaeology or near-field cosmology.
At the core of this work, we present a collection of efforts to chemically and dynamically characterise the disks and bulge of our Galaxy. The results we present in this thesis have only been possible thanks to the advent of the Gaia astrometric satellite, which has revolutionised the field of Galactic archaeology by precisely measuring the positions, parallax distances and motions of more than a billion stars. Another, though not less important, breakthrough is the APOGEE survey, which has observed spectra in the near-infrared peering into the dusty regions of the Galaxy, allowing us to determine detailed chemical abundance patterns in hundreds of thousands of stars. To accurately depict the Milky Way structure, we use and develop the Bayesian isochrone fitting tool/code called StarHorse; this software can predict stellar distances, extinctions and ages by combining astrometry, photometry and spectroscopy based on stellar evolutionary models. The StarHorse code is pivotal to calculating distances where Gaia parallaxes alone cannot allow accurate estimates.
We show that by combining Gaia, APOGEE, photometric surveys and using StarHorse, we can produce a chemical cartography of the Milky way disks from their outermost to innermost parts. Such a map is unprecedented in the inner Galaxy. It reveals a continuity of the bimodal chemical pattern previously detected in the solar neighbourhood, indicating two populations with distinct formation histories. Furthermore, the data reveals a chemical gradient within the thin disk where the content of 𝛼-process elements and metals is higher towards the centre. Focusing on a sample in the inner MW we confirm the extension of the chemical duality to the innermost regions of the Galaxy. We find stars with bar shape orbits to show both high- and low-𝛼 abundances, suggesting the bar formed by secular evolution trapping stars that already existed. By analysing the chemical orbital space of the inner Galactic regions, we disentangle the multiple populations that inhabit this complex region. We reveal the presence of the thin disk, thick disk, bar, and a counter-rotating population, which resembles the outcome of a perturbed proto-Galactic disk. Our study also finds that the inner Galaxy holds a high quantity of super metal-rich stars up to three times solar suggesting it is a possible repository of old super-metal-rich stars found in the solar neighbourhood.
We also enter into the complicated task of deriving individual stellar ages. With StarHorse, we calculate the ages of main-sequence turn-off and sub-giant stars for several public spectroscopic surveys. We validate our results by investigating linear relations between chemical abundances and time since the 𝛼 and neutron capture elements are sensitive to age as a reflection of the different enrichment timescales of these elements. For further study of the disks in the solar neighbourhood, we use an unsupervised machine learning algorithm to delineate a multidimensional separation of chrono-chemical stellar groups revealing the chemical thick disk, the thin disk, and young 𝛼-rich stars. The thick disk is shown to have a small age dispersion indicating its fast formation contrary to the thin disk that spans a wide range of ages.
With groundbreaking data, this thesis encloses a detailed chemo-dynamical view of the disk and bulge of our Galaxy. Our findings on the Milky Way can be linked to the evolution of high redshift disk galaxies, helping to solve the conundrum of galaxy formation.
Following the extinction of dinosaurs, the great adaptive radiation of mammals occurred, giving rise to an astonishing ecological and phenotypic diversity of mammalian species. Even closely related species often inhabit vastly different habitats, where they encounter diverse environmental challenges and are exposed to different evolutionary pressures. As a response, mammals evolved various adaptive phenotypes over time, such as morphological, physiological and behavioural ones. Mammalian genomes vary in their content and structure and this variation represents the molecular mechanism for the long-term evolution of phenotypic variation. However, understanding this molecular basis of adaptive phenotypic variation is usually not straightforward.
The recent development of sequencing technologies and bioinformatics tools has enabled a better insight into mammalian genomes. Through these advances, it was acknowledged that mammalian genomes differ more, both within and between species, as a consequence of structural variation compared to single-nucleotide differences. Structural variant types investigated in this thesis - such as deletion, duplication, inversion and insertion, represent a change in the structure of the genome, impacting the size, copy number, orientation and content of DNA sequences. Unlike short variants, structural variants can span multiple genes. They can alter gene dosage, and cause notable gene expression differences and subsequently phenotypic differences. Thus, they can lead to a more dramatic effect on the fitness (reproductive success) of individuals, local adaptation of populations and speciation.
In this thesis, I investigated and evaluated the potential functional effect of structural variations on the genomes of mustelid species. To detect the genomic regions associated with phenotypic variation I assembled the first reference genome of the tayra (Eira barbara) relying on linked-read sequencing technology to achieve a high level of genome completeness important for reliable structural variant discovery. I then set up a bioinformatics pipeline to conduct a comparative genomic analysis and explore variation between mustelid species living in different environments. I found numerous genes associated with species-specific phenotypes related to diet, body condition and reproduction among others, to be impacted by structural variants.
Furthermore, I investigated the effects of artificial selection on structural variants in mice selected for high fertility, increased body mass and high endurance. Through selective breeding of each mouse line, the desired phenotypes have spread within these populations, while maintaining structural variants specific to each line. In comparison to the control line, the litter size has doubled in the fertility lines, individuals in the high body mass lines have become considerably larger, and mice selected for treadmill performance covered substantially more distance. Structural variants were found in higher numbers in these trait-selected lines than in the control line when compared to the mouse reference genome. Moreover, we have found twice as many structural variants spanning protein-coding genes (specific to each line) in trait-selected lines. Several of these variants affect genes associated with selected phenotypic traits. These results imply that structural variation does indeed contribute to the evolution of the selected phenotypes and is heritable.
Finally, I suggest a set of critical metrics of genomic data that should be considered for a stringent structural variation analysis as comparative genomic studies strongly rely on the contiguity and completeness of genome assemblies. Because most of the available data used to represent reference genomes of mammalian species is generated using short-read sequencing technologies, we may have incomplete knowledge of genomic features. Therefore, a cautious structural variation analysis is required to minimize the effect of technical constraints.
The impact of structural variants on the adaptive evolution of mammalian genomes is slowly gaining more focus but it is still incorporated in only a small number of population studies. In my thesis, I advocate the inclusion of structural variants in studies of genomic diversity for a more comprehensive insight into genomic variation within and between species, and its effect on adaptive evolution.
Today, point clouds are among the most important categories of spatial data, as they constitute digital 3D models of the as-is reality that can be created at unprecedented speed and precision. However, their unique properties, i.e., lack of structure, order, or connectivity information, necessitate specialized data structures and algorithms to leverage their full precision. In particular, this holds true for the interactive visualization of point clouds, which requires to balance hardware limitations regarding GPU memory and bandwidth against a naturally high susceptibility to visual artifacts.
This thesis focuses on concepts, techniques, and implementations of robust, scalable, and portable 3D visualization systems for massive point clouds. To that end, a number of rendering, visualization, and interaction techniques are introduced, that extend several basic strategies to decouple rendering efforts and data management: First, a novel visualization technique that facilitates context-aware filtering, highlighting, and interaction within point cloud depictions. Second, hardware-specific optimization techniques that improve rendering performance and image quality in an increasingly diversified hardware landscape. Third, natural and artificial locomotion techniques for nausea-free exploration in the context of state-of-the-art virtual reality devices. Fourth, a framework for web-based rendering that enables collaborative exploration of point clouds across device ecosystems and facilitates the integration into established workflows and software systems.
In cooperation with partners from industry and academia, the practicability and robustness of the presented techniques are showcased via several case studies using representative application scenarios and point cloud data sets. In summary, the work shows that the interactive visualization of point clouds can be implemented by a multi-tier software architecture with a number of domain-independent, generic system components that rely on optimization strategies specific to large point clouds. It demonstrates the feasibility of interactive, scalable point cloud visualization as a key component for distributed IT solutions that operate with spatial digital twins, providing arguments in favor of using point clouds as a universal type of spatial base data usable directly for visualization purposes.
Mechanosensation is a fundamental biological process that provides the basis for sensing touch and pain as well as for hearing and proprioception. A special class of ion-channel proteins known as mechanosensitive proteins convert the mechanical stimuli into electrochemical signals to mediate this process. Mechanosensitive proteins undergo conformational changes in response to mechanical force, which eventually leads to the opening of the proteins' ion channel. Mammalian mechanosensitive proteins remained a long sought-after mystery until 2010 when a family of two proteins - Piezo1 and Piezo2 - was identifed as mechanosensors [1]. The cryo-EM structures of Piezo1 and Piezo2 protein were resolved in the last years and reveal a propeller-shaped homotrimer with 114 transmembrane helices [2, 3, 4, 5]. The protein structures are curved and have been suggested to deform the surrounding membrane into a nano-dome, which mechanically responds to membrane tension resulting from external forces [2]. In this thesis, the conformations of membrane-embedded Piezo1 and Piezo2 proteins and their tension-induced conformational changes are investigated using molecular dynamics simulations. Our coarse-grained molecular dynamics simulations show that the Piezo proteins induce curvature in the surrounding membrane and form a stable protein-membrane nano-dome in the tensionless membrane. These membrane-embedded Piezo proteins, however, adopt substantially less curved conformations in our simulations compared to the cryo-EM structures solved in detergent micelles, which agrees with recent experimental investigations of the overall Piezo nano-dome shape in membrane vesicles [6, 7, 8]. At high membrane tension, the Piezo proteins attain nearly planar conformations in our simulations. Our systematic investigation of Piezo proteins under different membrane tensions indicates a half-maximal conformational response at membrane tension values rather close to the experimentally suggested values of Piezo activation [9, 10]. In addition, our simulations indicate a widening of the Piezo1 ion channel at high membrane tension, which agrees with the channel widening observed in recent nearly flattened cryo-EM structures of Piezo1 in small membrane vesicles [11]. In contrast, the Piezo2 ion channel does not respond to membrane tension in our simulations. These different responses of the Piezo1 and Piezo2 ion channels in our simulations are in line with patch-clamp experiments, in which Piezo1, but not Piezo2, was shown to be activated by membrane tension alone [12].
Complex emulsions are dispersions of kinetically stabilized multiphasic emulsion droplets comprised of two or more immiscible liquids that provide a novel material platform for the generation of active and dynamic soft materials. In recent years, the intrinsic reconfigurable morphological behavior of complex emulsions, which can be attributed to the unique force equilibrium between the interfacial tensions acting at the various interfaces, has become of fundamental and applied interest. As such, particularly biphasic Janus droplets have been investigated as structural templates for the generation of anisotropic precision objects, dynamic optical elements or as transducers and signal amplifiers in chemo- and bio-sensing applications. In the present thesis, switchable internal morphological responses of complex droplets triggered by stimuli-induced alterations of the balance of interfacial tensions have been explored as a universal building block for the design of multiresponsive, active, and adaptive liquid colloidal systems. A series of underlying principles and mechanisms that influence the equilibrium of interfacial tensions have been uncovered, which allowed the targeted design of emulsion bodies that can alter their shape, bind and roll on surfaces, or change their geometrical shape in response to chemical stimuli. Consequently, combinations of the unique triggerable behavior of Janus droplets with designer surfactants, such as a stimuli-responsive photosurfactant (AzoTAB) resulted for instance in shape-changing soft colloids that exhibited a jellyfish inspired buoyant motion behavior, holding great promise for the design of biological inspired active material architectures and transformable soft robotics.
In situ observations of spherical Janus emulsion droplets using a customized side-view microscopic imaging setup with accompanying pendant dropt measurements disclosed the sensitivity regime of the unique chemical-morphological coupling inside complex emulsions and enabled the recording of calibration curves for the extraction of critical parameters of surfactant effectiveness. The deduced new "responsive drop" method permitted a convenient and cost-efficient quantification and comparison of the critical micelle concentrations (CMCs) and effectiveness of various cationic, anionic, and nonionic surfactants. Moreover, the method allowed insightful characterization of stimuli-responsive surfactants and monitoring of the impact of inorganic salts on the CMC and surfactant effectiveness of ionic and nonionic surfactants. Droplet functionalization with synthetic crown ether surfactants yielded a synthetically minimal material platform capable of autonomous and reversible adaptation to its chemical environment through different supramolecular host-guest recognition events. Addition of metal or ammonium salts resulted in the uptake of the resulting hydrophobic complexes to the hydrocarbon hemisphere, whereas addition of hydrophilic ammonium compounds such as amino acids or polypeptides resulted in supramolecular assemblies at the hydrocarbon-water interface of the droplets. The multiresponsive material platform enabled interfacial complexation and
thus triggered responses of the droplets to a variety of chemical triggers including metal ions, ammonium compounds, amino acids, antibodies, carbohydrates as well as amino-functionalized solid surfaces.
In the final chapter, the first documented optical logic gates and combinatorial logic circuits based on complex emulsions are presented. More specifically, the unique reconfigurable and multiresponsive properties of complex emulsions were exploited to realize droplet-based logic gates of varying complexity using different stimuli-responsive surfactants in combination with diverse readout methods. In summary, different designs for multiresponsive, active, and adaptive liquid colloidal systems were presented and investigated, enabling the design of novel transformative chemo-intelligent soft material platforms.
In this thesis, we investigate language learning in the formalisation of Gold [Gol67]. Here, a learner, being successively presented all information of a target language, conjectures which language it believes to be shown. Once these hypotheses converge syntactically to a correct explanation of the target language, the learning is considered successful. Fittingly, this is termed explanatory learning. To model learning strategies, we impose restrictions on the hypotheses made, for example requiring the conjectures to follow a monotonic behaviour. This way, we can study the impact a certain restriction has on learning.
Recently, the literature shifted towards map charting. Here, various seemingly unrelated restrictions are contrasted, unveiling interesting relations between them. The results are then depicted in maps. For explanatory learning, the literature already provides maps of common restrictions for various forms of data presentation.
In the case of behaviourally correct learning, where the learners are required to converge semantically instead of syntactically, the same restrictions as in explanatory learning have been investigated. However, a similarly complete picture regarding their interaction has not been presented yet.
In this thesis, we transfer the map charting approach to behaviourally correct learning. In particular, we complete the partial results from the literature for many well-studied restrictions and provide full maps for behaviourally correct learning with different types of data presentation. We also study properties of learners assessed important in the literature. We are interested whether learners are consistent, that is, whether their conjectures include the data they are built on. While learners cannot be assumed consistent in explanatory learning, the opposite is the case in behaviourally correct learning. Even further, it is known that learners following different restrictions may be assumed consistent. We contribute to the literature by showing that this is the case for all studied restrictions.
We also investigate mathematically interesting properties of learners. In particular, we are interested in whether learning under a given restriction may be done with strongly Bc-locking learners. Such learners are of particular value as they allow to apply simulation arguments when, for example, comparing two learning paradigms to each other. The literature gives a rich ground on when learners may be assumed strongly Bc-locking, which we complete for all studied restrictions.
Aptamers are single-stranded DNA (ssDNA) or RNA molecules that can bind specifically and with high affinity to target molecules due to their unique three-dimensional structure. For this reason, they are often compared to antibodies and sometimes even referred to as “chemical antibodies”. They are simple and inexpensive to synthesize, easy to modify, and smaller than conventional antibodies. Enzymes, especially hydrolases, are interesting targets in this context. This class of enzymes is capable of hydrolytically cleaving various macromolecules such as proteins, as well as smaller molecules such as antibiotics. Hence, they play an important role in many biological processes including diseases and their treatment. Hydrolase detection as well as the understanding of their function is therefore of great importance for diagnostics and therapy. Due to their various desirable features compared to antibodies, aptamers are being discussed as alternative agents for analytical and diagnostic use in various applications. The use of aptamers in therapy is also frequently investigated, as the binding of aptamers can have effects on the catalytic activity, protein-protein interactions, or proteolytic cascades. Aptamers are generated by an in vitro selection process. Potential aptamer candidates are selected from a pool of enriched nucleic acid sequences with affinity to the target, and their binding affinity and specificity is investigated. This is one of the most important steps in aptamer generation to obtain specific aptamers with high affinity for use in analytical and diagnostic applications. The binding properties or binding domains and their effects on enzyme functions form the basis for therapeutic applications.
In this work, the binding properties of DNA aptamers against two different hydrolases were investigated. In view of their potential utility for analytical methods, aptamers against human urokinase (uPA) and New Delhi metallo-β-lactamase-1 (NDM-1) were evaluated for their binding affinity and specificity using different methods. Using the uPA aptamers, a protocol for measuring the binding kinetics of an aptamer-protein-interaction by surface plasmon resonance spectroscopy (SPR) was developed. Based on the increased expression of uPA in different types of cancer, uPA is discussed as a prognostic and diagnostic tumor marker. As uPA aptamers showed different binding sites on the protein, microtiter plate-based aptamer sandwich assay systems for the detection of uPA were developed. Because of the function of urokinase in cancer cell proliferation and metastasis, uPA is also discussed as a therapeutic target. In this regard, the different binding sites of aptamers showed different effects on uPA function. In vitro experiments demonstrated both inhibition of uPA binding to its receptor as well as the inhibition of uPA catalytic activity for different aptamers. Thus, in addition to their specificity and affinity for their targets, the utility of the aptamers for potential diagnostic and therapeutic applications was demonstrated. First, as an alternative inhibitor of human urokinase for therapeutic purposes, and second, as valuable recognition molecules for the detection of urokinase, as a prognostic and diagnostic marker for cancer, and for NDM-1 to detect resistance to carbapenem antibiotics.
Selenium (Se) is an essential trace element that is ubiquitously present in the environment in small concentrations. Essential functions of Se in the human body are manifested through the wide range of proteins, containing selenocysteine as their active center. Such proteins are called selenoproteins which are found in multiple physiological processes like antioxidative defense and the regulation of thyroid hormone functions. Therefore, Se deficiency is known to cause a broad spectrum of physiological impairments, especially in endemic regions with low Se content. Nevertheless, being an essential trace element, Se could exhibit toxic effects, if its intake exceeds tolerable levels. Accordingly, this range between deficiency and overexposure represents optimal Se supply. However, this range was found to be narrower than for any other essential trace element. Together with significantly varying Se concentrations in soil and the presence of specific bioaccumulation factors, this represents a noticeable difficulty in the assessment of Se
epidemiological status. While Se is acting in the body through multiple selenoproteins, its intake occurs mainly in form of small organic or inorganic molecular mass species. Thus, Se exposure not only depends on daily intake but also on the respective chemical form, in which it is present.
The essential functions of selenium have been known for a long time and its primary forms in different food sources have been described. Nevertheless, analytical capabilities for a comprehensive investigation of Se species and their derivatives have been introduced only in the last decades. A new Se compound was identified in 2010 in the blood and tissues of bluefin tuna. It was called selenoneine (SeN) since it is an isologue of naturally occurring antioxidant ergothioneine (ET), where Se replaces sulfur. In the following years, SeN was identified in a number of edible fish species and attracted attention as a new dietary Se source and potentially strong antioxidant. Studies in populations whose diet largely relies on fish revealed that SeN
represents the main non-protein bound Se pool in their blood. First studies, conducted with enriched fish extracts, already demonstrated the high antioxidative potential of SeN and its possible function in the detoxification of methylmercury in fish. Cell culture studies demonstrated, that SeN can utilize the same transporter as ergothioneine, and SeN metabolite was found in human urine.
Until recently, studies on SeN properties were severely limited due to the lack of ways to obtain the pure compound. As a predisposition to this work was firstly a successful approach to SeN synthesis in the University of Graz, utilizing genetically modified yeasts. In the current study, by use of HepG2 liver carcinoma cells, it was demonstrated, that SeN does not cause toxic effectsup to 100 μM concentration in hepatocytes. Uptake experiments showed that SeN is not bioavailable to the used liver cells.
In the next part a blood-brain barrier (BBB) model, based on capillary endothelial cells from the porcine brain, was used to describe the possible transfer of SeN into the central nervous system (CNS). The assessment of toxicity markers in these endothelial cells and monitoring of barrier conditions during transfer experiments demonstrated the absence of toxic effects from SeN on the BBB endothelium up to 100 μM concentration. Transfer data for SeN showed slow but substantial transfer. A statistically significant increase was observed after 48 hours following SeN incubation from the blood-facing side of the barrier. However, an increase in Se content was clearly visible already after 6 hours of incubation with 1 μM of SeN. While the transfer rate of SeN after application of 0.1 μM dose was very close to that for 1 μM, incubation with 10 μM of SeN resulted in a significantly decreased transfer rate. Double-sided application of SeN caused no side-specific transfer of SeN, thus suggesting a passive diffusion mechanism of SeN across the BBB. This data is in accordance with animal studies, where ET accumulation was observed in the rat brain, even though rat BBB does not have the primary ET transporter – OCTN1. Investigation of capillary endothelial cell monolayers after incubation with SeN and reference selenium compounds showed no significant increase of intracellular selenium concentration. Speciesspecific Se measurements in medium samples from apical and basolateral compartments, as good as in cell lysates, showed no SeN metabolization. Therefore, it can be concluded that SeN may reach the brain without significant transformation.
As the third part of this work, the assessment of SeN antioxidant properties was performed in Caco-2 human colorectal adenocarcinoma cells. Previous studies demonstrated that the intestinal epithelium is able to actively transport SeN from the intestinal lumen to the blood side and accumulate SeN. Further investigation within current work showed a much higher antioxidant potential of SeN compared to ET. The radical scavenging activity after incubation with SeN was close to the one observed for selenite and selenomethionine. However, the SeN effect on the viability of intestinal cells under oxidative conditions was close to the one caused by ET. To answer the question if SeN is able to be used as a dietary Se source and induce the activity of selenoproteins, the activity of glutathione peroxidase (GPx) and the secretion of selenoprotein P (SelenoP) were measured in Caco-2 cells, additionally. As expected, reference selenium compounds selenite and selenomethionine caused efficient induction of GPx activity. In contrast to those SeN had no effect on GPx activity. To examine the possibility of SeN being embedded into the selenoproteome, SelenoP was measured in a culture medium. Even though Caco-2 cells effectively take up SeN in quantities much higher than selenite or selenomethionine, no secretion of SelenoP was observed after SeN incubation.
Summarizing, we can conclude that SeN can hardly serve as a Se source for selenoprotein synthesis. However, SeN exhibit strong antioxidative properties, which appear when sulfur in ET is exchanged by Se. Therefore, SeN is of particular interest for research not as part of Se metabolism, but important endemic dietary antioxidant.
Understanding hydrological processes is of fundamental importance for the Vietnamese national food security and the livelihood of the population in the Vietnamese Mekong Delta (VMD). As a consequence of sparse data in this region, however, hydrologic processes, such as the controlling processes of precipitation, the interaction between surface and groundwater, and groundwater dynamics, have not been thoroughly studied. The lack of this knowledge may negatively impact the long-term strategic planning for sustainable groundwater resources management and may result in insufficient groundwater recharge and freshwater scarcity. It is essential to develop useful methods for a better understanding of hydrological processes in such data-sparse regions. The goal of this dissertation is to advance methodologies that can improve the understanding of fundamental hydrological processes in the VMD, based on the analyses of stable water isotopes and monitoring data. The thesis mainly focuses on the controlling processes of precipitation, the mechanism of surface–groundwater interaction, and the groundwater dynamics. These processes have not been fully addressed in the VMD so far. The thesis is based on statistical analyses of the isotopic data of Global Network of Isotopes in Precipitation (GNIP), of meteorological and hydrological data from Vietnamese agencies, and of the stable water isotopes and monitoring data collected as part of this work.
First, the controlling processes of precipitation were quantified by the combination of trajectory analysis, multi-factor linear regression, and relative importance analysis (hereafter, a model‐based statistical approach). The validity of this approach is confirmed by similar, but mainly qualitative results obtained in other studies. The total variation in precipitation isotopes (δ18O and δ2H) can be better explained by multiple linear regression (up to 80%) than single-factor linear regression (30%). The relative importance analysis indicates that atmospheric moisture regimes control precipitation isotopes rather than local climatic conditions. The most crucial factor is the upstream rainfall along the trajectories of air mass movement. However, the influences of regional and local climatic factors vary in importance over the seasons. The developed model‐based statistical approach is a robust tool for the interpretation of precipitation isotopes and could also be applied to understand the controlling processes of precipitation in other regions.
Second, the concept of the two-component lumped-parameter model (LPM) in conjunction with stable water isotopes was applied to examine the surface–groundwater interaction in the VMD. A calibration framework was also set up to evaluate the behaviour, parameter identifiability, and uncertainties of two-component LPMs. The modelling results provided insights on the subsurface flow conditions, the recharge contributions, and the spatial variation of groundwater transit time. The subsurface flow conditions at the study site can be best represented by the linear-piston flow distribution. The contributions of the recharge sources change with distance to the river. The mean transit time (mTT) of riverbank infiltration increases with the length of the horizontal flow path and the decreasing gradient between river and groundwater. River water infiltrates horizontally mainly via the highly permeable aquifer, resulting in short mTTs (<40 weeks) for locations close to the river (<200 m). The vertical infiltration from precipitation takes place primarily via a low‐permeable overlying aquitard, resulting in considerably longer mTTs (>80 weeks). Notably, the transit time of precipitation infiltration is independent of the distance to the river. All these results are hydrologically plausible and could be quantified by the presented method for the first time. This study indicates that the highly complex mechanism of surface–groundwater interaction at riverbank infiltration systems can be conceptualized by exploiting two‐component LPMs. It is illustrated that the model concept can be used as a tool to investigate the hydrological functioning of mixing processes and the flow path of multiple water components in riverbank infiltration systems.
Lastly, a suite of time series analysis approaches was applied to examine the groundwater dynamics in the VMD. The assessment was focused on the time-variant trends of groundwater levels (GWLs), the groundwater memory effect (representing the time that an aquifer holds water), and the hydraulic response between surface water and multi-layer alluvial aquifers. The analysis indicates that the aquifers act as low-pass filters to reduce the high‐frequency signals in the GWL variations, and limit the recharge to the deep groundwater. The groundwater abstraction has exceeded groundwater recharge between 1997 and 2017, leading to the decline of groundwater levels (0.01-0.55 m/year) in all considered aquifers in the VMD. The memory effect varies according to the geographical location, being shorter in shallow aquifers and flood-prone areas and longer in deep aquifers and coastal regions. Groundwater depth, season, and location primarily control the variation of the response time between the river and alluvial aquifers. These findings are important contributions to the hydrogeological literature of a little-known groundwater system in an alluvial setting. It is suggested that time series analysis can be used as an efficient tool to understand groundwater systems where resources are insufficient to develop a physical-based groundwater model.
This doctoral thesis demonstrates that important aspects of hydrological processes can be understood by statistical analysis of stable water isotope and monitoring data. The approaches developed in this thesis can be easily transferred to regions in similar tropical environments, particularly those in alluvial settings. The results of the thesis can be used as a baseline for future isotope-based studies and contribute to the hydrogeological literature of little-known groundwater systems in the VMD.
The central gas in half of all galaxy clusters shows short cooling times. Assuming unimpeded cooling, this should lead to high star formation and mass cooling rates, which are not observed. Instead, it is believed that condensing gas is accreted by the central black hole that powers an active galactic nuclei jet, which heats the cluster. The detailed heating mechanism remains uncertain. A promising mechanism invokes cosmic ray protons that scatter on self-generated magnetic fluctuations, i.e. Alfvén waves. Continuous damping of Alfvén waves provides heat to the intracluster medium. Previous work has found steady state solutions for a large sample of clusters where cooling is balanced by Alfvénic wave heating. To verify modeling assumptions, we set out to study cosmic ray injection in three-dimensional magnetohydrodynamical simulations of jet feedback in an idealized cluster with the moving-mesh code arepo. We analyze the interaction of jet-inflated bubbles with the turbulent magnetized intracluster medium.
Furthermore, jet dynamics and heating are closely linked to the largely unconstrained jet composition. Interactions of electrons with photons of the cosmic microwave background result in observational signatures that depend on the bubble content. Those recent observations provided evidence for underdense bubbles with a relativistic filling while adopting simplifying modeling assumptions for the bubbles. By reproducing the observations with our simulations, we confirm the validity of their modeling assumptions and as such, confirm the important finding of low-(momentum) density jets.
In addition, the velocity and magnetic field structure of the intracluster medium have profound consequences for bubble evolution and heating processes. As velocity and magnetic fields are physically coupled, we demonstrate that numerical simulations can help link and thereby constrain their respective observables. Finally, we implement the currently preferred accretion model, cold accretion, into the moving-mesh code arepo and study feedback by light jets in a radiatively cooling magnetized cluster. While self-regulation is attained independently of accretion model, jet density and feedback efficiencies, we find that in order to reproduce observed cold gas morphology light jets are preferred.
Within the context of United Nations (UN) environmental institutions, it has become apparent that intergovernmental responses alone have been insufficient for dealing with pressing transboundary environmental problems. Diverging economic and political interests, as well as broader changes in power dynamics and norms within global (environmental) governance, have resulted in negotiation and implementation efforts by UN member states becoming stuck in institutional gridlock and inertia. These developments have sparked a renewed debate among scholars and practitioners about an imminent crisis of multilateralism, accompanied by calls for reforming UN environmental institutions. However, with the rise of transnational actors and institutions, states are not the only relevant actors in global environmental governance. In fact, the fragmented architectures of different policy domains are populated by a hybrid mix of state and non-state actors, as well as intergovernmental and transnational institutions. Therefore, coping with the complex challenges posed by severe and ecologically interdependent transboundary environmental problems requires global cooperation and careful management from actors beyond national governments.
This thesis investigates the interactions of three intergovernmental UN treaty secretariats in global environmental governance. These are the secretariats of the United Nations Framework Convention on Climate Change, the Convention on Biological Diversity, and the United Nations Convention to Combat Desertification. While previous research has acknowledged the increasing autonomy and influence of treaty secretariats in global policy-making, little attention has been paid to their strategic interactions with non-state actors, such as non-governmental organizations, civil society actors, businesses, and transnational institutions and networks, or their coordination with other UN agencies. Through qualitative case-study research, this thesis explores the means and mechanisms of these interactions and investigates their consequences for enhancing the effectiveness and coherence of institutional responses to underlying and interdependent environmental issues.
Following a new institutionalist ontology, the conceptual and theoretical framework of this study draws on global governance research, regime theory, and scholarship on international bureaucracies. From an actor-centered perspective on institutional interplay, the thesis employs concepts such as orchestration and interplay management to assess the interactions of and among treaty secretariats. The research methodology involves structured, focused comparison, and process-tracing techniques to analyze empirical data from diverse sources, including official documents, various secondary materials, semi-structured interviews with secretariat staff and policymakers, and observations at intergovernmental conferences.
The main findings of this research demonstrate that secretariats employ tailored orchestration styles to manage or bypass national governments, thereby raising global ambition levels for addressing transboundary environmental problems. Additionally, they engage in joint interplay management to facilitate information sharing, strategize activities, and mobilize relevant actors, thereby improving coherence across UN environmental institutions. Treaty secretariats play a substantial role in influencing discourses and knowledge exchange with a wide range of actors. However, they face barriers, such as limited resources, mandates, varying leadership priorities, and degrees of politicization within institutional processes, which may hinder their impact. Nevertheless, the secretariats, together with non-state actors, have made progress in advancing norm-building processes, integrated policy-making, capacity building, and implementation efforts within and across framework conventions. Moreover, they utilize innovative means of coordination with actors beyond national governments, such as data-driven governance, to provide policy-relevant information for achieving overarching governance targets.
Importantly, this research highlights the growing interactions between treaty secretariats and non-state actors, which not only shape policy outcomes but also have broader implications for the polity and politics of international institutions. The findings offer opportunities for rethinking collective agency and actor dynamics within UN entities, addressing gaps in institutionalist theory concerning the interaction of actors in inter-institutional spaces. Furthermore, the study addresses emerging challenges and trends in global environmental governance that are pertinent to future policy-making. These include reflections for the debate on reforming international institutions, the role of emerging powers in a changing international world order, and the convergence of public and private authority through new alliance-building and a division of labor between international bureaucracies and non-state actors in global environmental governance.
Continental rifts are key geodynamic regions where the complex interplay of magmatism and faulting activity can be studied to understand the driving forces of extension and the formation of new divergent plate boundaries. Well-preserved rift morphology can provide a wealth of information on the growth, interaction, and linkage of normal-fault systems through time. If rift basins are preserved over longer geologic time periods, sedimentary archives generated during extensional processes may mirror tectonic and climatic influences on erosional and sedimentary processes that have varied over time. Rift basins are furthermore strategic areas for hydrocarbon and geothermal energy exploration, and they play a central role in species dispersal and evolution as well as providing or inhibiting hydrologic connectivity along basins at emerging plate boundaries.
The Cenozoic East African rift system (EARS) is one of the most important continental extension zones, reflecting a range of evolutionary stages from an early rift stage with isolated basins in Malawi to an advanced stage of continental extension in southern Afar. Consequently, the EARS is an ideal natural laboratory that lends itself to the study of different stages in the breakup of a continent. The volcanically and seismically active eastern branch of the EARS is characterized by multiple, laterally offset tectonic and magmatic segments where adjacent extensional basins facilitate crustal extension either across a broad deformation zone or via major transfer faulting. The Broadly Rifted Zone (BRZ) in southern Ethiopia is an integral part of the eastern branch of the EARS; in this region, rift segments of the southern Ethiopian Rift (sMER) and northern Kenyan Rift (nKR) propagate in opposite directions in a region with one of the earliest manifestations of volcanism and extensional tectonism in East Africa. The basin margins of the Chew-Bahir Basin and the Gofa Province, characterized by a semi-arid climate and largely uniform lithology, provide ideal conditions for studying the tectonic and geomorphologic features of this complex kinematic transfer zone, but more importantly, this area is suitable for characterizing and quantifying the overlap between the propagating structures of the sMER and nKR and the resulting deformation patterns of the BRZ transfer zones.
In this study, I have combined data from thermochronology, thermal modeling, morphometry, paleomagnetic analysis, geochronology, and geomorphological field observations with information from published studies to reconstruct the spatiotemporal relationship between volcanism and fault activity in the BRZ and quantify the deformation patterns of the overlapping rift segments. I present the following results: (1) new thermochronological data from the en-échelon basin margins and footwall blocks of the rift flanks and morphometric results verified in the field to link different phases of magmatism and faulting during extension and infer geomorphological landscape features related to the current tectonic interaction between the nKR and the sMER; (2) temporally constrained paleomagnetic data from the BRZ overlap zone between the Ethiopian and Kenyan rifts to quantitatively determine block rotation between the two segments. Combining the collected data, time-temperature histories of thermal modeling results from representative samples show well-defined deformation phases between 25–20 Ma, 15–9Ma, and ~5 Ma to the present. Each deformation phase is characterized by the onset of rapid cooling (>2°C/Ma) of the crust associated with uplift or exhumation of the rift shoulder. After an initial, spatially very diffuse phase of extension, the rift has gradually evolved into a system of connected structures formed in an increasingly focused rift zone during the last 5 Ma. Regarding the morphometric analysis of the rift structures, it can be shown that normalized slope indices of the river courses, spatial arrangement of knickpoints in the river longitudinal profiles of the footwall blocks, local relief values, and the average maximum values of the slope of the river profiles indicate a gradual increase in the extension rate from north (Sawula basin: mature) to south (Chew Bahir: young). The complexity of the structural evolution of the BRZ overlap zone between nKR and sMER is further emphasized by the documentation of crustal blocks around a vertical axis. A comparison of the mean directions obtained for the Eo-Oligocene (Ds=352.6°, Is=-17.0°, N=18, α95=5.5°) and Miocene (Ds=2.9°, Is=0.9°, N=9, α95=12.4°) volcanics relative to the pole for stable South Africa and with respect to the corresponding ages of the analyzed units record a significant counterclockwise rotation of ~11.1°± 6.4° and insignificant CCW rotation of ~3.2° ± 11.5°, respectively.
The urge of light utilization in fabrication of materials is as encouraging as challenging. Steadily increasing energy consumption in accordance with rapid population growth, is requiring a corresponding solution within the same rate of occurrence speed. Therefore, creating, designing and manufacturing materials that can interact with light and in further be applicable as well as disposable in photo-based applications are very much under attention of researchers. In the era of sustainability for renewable energy systems, semiconductor-based photoactive materials have received great attention not only based on solar and/or hydrocarbon fuels generation from solar energy, but also successful stimulation of photocatalytic reactions such as water splitting, pollutant degradation and organic molecule synthesisThe turning point had been reached for water splitting with an electrochemical cell consisting of TiO2-Pt electrode illuminated by UV light as energy source rather than an external voltage, that successfully pursued water photolysis by Fujishima and Honda in 1972. Ever since, there has been a great deal of interest in research of semiconductors (e.g. metal oxide, metal-free organic, noble-metal complex) exhibiting effective band gap for photochemical reactions. In the case of environmental friendliness, toxicity of metal-based semiconductors brings some restrictions in possible applications. Regarding this, very robust and ‘earth-abundant’ organic semiconductor, graphitic carbon nitride has been synthesized and successfully applied in photoinduced applications as novel photocatalyst. Properties such as suitable band gap, low charge carrier recombination and feasibility for scaling up, pave the way of advance combination with other catalysts to gather higher photoactivity based on compatible heterojunction.
This dissertation aims to demonstrate a series of combinations between organic semiconductor g-CN and polymer materials that are forged through photochemistry, either in synthesis or in application. Fabrication and design processes as well as applications performed in accordance to the scope of thesis will be elucidated in detail. In addition to UV light, more attention is placed on visible light as energy source with a vision of more sustainability and better scalability in creation of novel materials and solar energy based applications.
Background: The concept self-compassion (SC), a special way of being compassionate with oneself while dealing with stressful life circumstances, has attracted increasing attention in research over the past two decades. Research has already shown that SC has beneficial effects on affective well-being and other mental health outcomes. However, little is known in which ways SC might facilitate our affective well-being in stressful situations. Hence, a central concern of this dissertation was to focus on the question which underlying processes might influence the link between SC and affective well-being. Two established components in stress processing, which might also play an important role in this context, could be the amount of experienced stress and the way of coping with a stressor. Thus, using a multi-method approach, this dissertation aimed at finding to which extent SC might help to alleviate the experienced stress and promotes the use of more salutary coping, while dealing with stressful circumstances. These processes might ultimately help improve one’s affective well-being. Derived from that, it was hypothesized that more SC is linked to less perceived stress and intensified use of salutary coping responses. Additionally, it was suggested that perceived stress and coping mediate the relation between SC and affective well-being.
Method: The research questions were targeted in three single studies and one meta-study. To test my assumptions about the relations of SC and coping in particular, a systematic literature search was conducted resulting in k = 136 samples with an overall sample size of N = 38,913. To integrate the z-transformed Pearson correlation coefficients, random-effects models were calculated. All hypotheses were tested with a three-wave cross-lagged design in two short-term longitudinal online studies assessing SC, perceived stress and coping responses in all waves. The first study explored the assumptions in a student sample (N = 684) with a mean age of 27.91 years over a six-week period, whereas the measurements were implemented in the GESIS Panel (N = 2934) with a mean age of 52.76 years analyzing the hypotheses in a populationbased sample across eight weeks. Finally, an ambulatory assessment study was designed to expand the findings of the longitudinal studies to the intraindividual level. Thus, a sample of 213 participants completed questionnaires of momentary SC, perceived stress, engagement and disengagement coping, and affective well-being on their smartphones three times per day over seven consecutive days. The data was processed using 1-1-1 multilevel mediation analyses.
Results: Results of the meta-analysis indicated that higher SC is significantly associated with more use of engagement coping and less use of disengagement coping. Considering the relations between SC and stress processing variables in all three single studies, cross-lagged paths from the longitudinal data, as well as multilevel modeling paths from the ambulatory assessment data indicated a notable relation between all relevant stress variables. As expected, results showed a significant negative relation between SC and perceived stress and disengagement coping, as well as a positive connection with engagement coping responses at the dispositional and intra-individual level. However, considering the mediational hypothesis, the most promising pathway in the link between SC and affective well-being turned out to be perceived stress in all three studies, while effects of the mediational pathways through coping responses were less robust.
Conclusion: Thus, a more self-compassionate attitude and higher momentary SC, when needed in specific situations, can help to engage in effective stress processing. Considering the underlying mechanisms in the link between SC and affective well-being, stress perception in particular seemed to be the most promising candidate for enhancing affective well-being at the dispositional and at the intraindividual level. Future research should explore the pathways between SC and affective well-being in specific contexts and samples, and also take into account additional influential factors.
Starch is a biopolymer for which, despite its simple composition, understanding the precise mechanism behind its formation and regulation has been challenging. Several approaches and bioanalytical tools can be used to expand the knowledge on the different parts involved in the starch metabolism. In this sense, a comprehensive analysis targeting two of the main groups of molecules involved in this process: proteins, as effectors/regulators of the starch metabolism, and maltodextrins as starch components and degradation products, was conducted in this research work using potato plants (Solanum tuberosum L. cv. Desiree) as model of study. On one side, proteins physically interacting to potato starch were isolated and analyzed through mass spectrometry and western blot for their identification. Alternatively, starch interacting proteins were explored in potato tubers from transgenic plants having antisense inhibition of starch-related enzymes and on tubers stored under variable environmental conditions. Most of the proteins recovered from the starch granules corresponded to previously described proteins having a specific role in the starch metabolic pathway. Another set of proteins could be grouped as protease inhibitors, which were found weakly interacting to starch. Variations in the protein profile obtained after electrophoresis separation became clear when tubers were stored under different temperatures, indicating a differential expression of proteins in response to changing environmental conditions.
On the other side, since maltodextrin metabolism is thought to be involved in both starch initiation and degradation, soluble maltooligosaccharide content in potato tubers was analyzed in this work under diverse experimental variables. For this, tuber disc samples from wild type and transgenic lines strongly repressing either the plastidial or cytosolic form of the -glucan phosphorylase and phosphoglucomutase were incubated with glucose, glucose-6-phosphate, and glucose-1-phosphate solutions to evaluate the influence of such enzymes on the conversion of the carbon sources into soluble maltodextrins, in comparison to wild-type samples. Relative maltodextrin amounts analyzed through capillary electrophoresis equipped with laser-induced fluorescence (CE-LIF) revealed that tuber discs could immediately uptake glucose-1-phosphate and use it to produce maltooligosaccharides with a degree of polymerization of up to 30 (DP30), in contrast to transgenic tubers with strong repression of the plastidial glucan phosphorylase. The results obtained from the maltodextrin analysis support previous indications that a specific transporter for glucose-1-phosphate may exist in both the plant cells and the plastidial membranes, thereby allowing a glucose-6-phosphate independent transport. Furthermore, it confirms that the plastidial glucan phosphorylase is responsible for producing longer maltooligosaccharides in the plastids by catalyzing a glucan polymerization reaction when glucose-1-phosphate is available. All these findings contribute to a better understanding of the role of the plastidial glucan phosphorylase as a key enzyme directly involved in the synthesis and degradation of glucans and their implication on starch metabolism.
Hybrid nanomaterials offer the combination of individual properties of different types of nanoparticles. Some strategies for the development of new nanostructures in larger scale rely on the self-assembly of nanoparticles as a bottom-up approach. The use of templates provides ordered assemblies in defined patterns. In a typical soft-template, nanoparticles and other surface-active agents are incorporated into non-miscible liquids. The resulting self-organized dispersions will mediate nanoparticle interactions to control the subsequent self-assembly. Especially interactions between nanoparticles of very different dispersibility and functionality can be directed at a liquid-liquid interface.
In this project, water-in-oil microemulsions were formulated from quasi-ternary mixtures with Aerosol-OT as surfactant. Oleyl-capped superparamagnetic iron oxide and/or silver nanoparticles were incorporated in the continuous organic phase, while polyethyleneimine-stabilized gold nanoparticles were confined in the dispersed water droplets. Each type of nanoparticle can modulate the surfactant film and the inter-droplet interactions in diverse ways, and their combination causes synergistic effects. Interfacial assemblies of nanoparticles resulted after phase-separation. On one hand, from a biphasic Winsor type II system at low surfactant concentration, drop-casting of the upper phase afforded thin films of ordered nanoparticles in filament-like networks. Detailed characterization proved that this templated assembly over a surface is based on the controlled clustering of nanoparticles and the elongation of the microemulsion droplets. This process offers versatility to use different nanoparticle compositions by keeping the surface functionalization, in different solvents and over different surfaces. On the other hand, a magnetic heterocoagulate was formed at higher surfactant concentration, whose phase-transfer from oleic acid to water was possible with another auxiliary surfactant in ethanol-water mixture. When the original components were initially mixed under heating, defined oil-in-water, magnetic-responsive nanostructures were obtained, consisting on water-dispersible nanoparticle domains embedded by a matrix-shell of oil-dispersible nanoparticles.
Herein, two different approaches were demonstrated to form diverse hybrid nanostructures from reverse microemulsions as self-organized dispersions of the same components. This shows that microemulsions are versatile soft-templates not only for the synthesis of nanoparticles, but also for their self-assembly, which suggest new approaches towards the production of new sophisticated nanomaterials in larger scale.
The Andes reflect Cenozoic deformation and uplift along the South American margin in the context of regional shortening associated with the interaction between the subducting Nazca plate and the overriding continental South American plate. Simultaneously, multiple levels of uplifted marine terraces constitute laterally continuous geomorphic features related to the accumulation of permanent forearc deformation in the coastal realm. However, the mechanisms responsible for permanent coastal uplift and the persistency of current/decadal deformation patterns over millennial timescales are still not fully understood. This dissertation presents a continental-scale database of last interglacial terrace elevations and uplift rates along the South American coast that provides the basis for an analysis of a variety of mechanisms that are possibly responsible for the accumulation of permanent coastal uplift. Regional-scale mapping and analysis of multiple, late Pleistocene terrace levels in central Chile furthermore provide valuable insights regarding the persistency of current seismic asperities, the role of upper-plate faulting, and the impact of bathymetric ridges on permanent forearc deformation.
The database of last interglacial terrace elevations reveals an almost continuous signal of background-uplift rates along the South American coast at ~0.22 mm/yr that is modified by various short- to long-wavelength changes. Spatial correlations with crustal faults and subducted bathymetric ridges suggest long-term deformation to be affected by these features, while the latitudinal variability of climate forcing factors has a profound impact on the generation and preservation of marine terraces. Systematic wavelength analyses and comparisons of the terrace-uplift rate signal with different tectonic parameters reveal short-wavelength deformation to result from crustal faulting, while intermediate- to long-wavelength deformation might indicate various extents of long-term seismotectonic segments on the megathrust, which are at least partially controlled by the subduction of bathymetric anomalies. The observed signal of background-uplift rate is likely accumulated by moderate earthquakes near the Moho, suggesting multiple, spatiotemporally distinct phases of uplift that manifest as a continuous uplift signal over millennial timescales.
Various levels of late Pleistocene marine terraces in the 2015 M8.3 Illapel-earthquake area reveal a range of uplift rates between 0.1 and 0.6 mm/yr and indicate decreasing uplift rates since ~400 ka. These glacial-cycle uplift rates do not correlate with current or decadal estimates of coastal deformation suggesting seismic asperities not to be persistent features on the megathrust that control the accumulation of permanent forearc deformation over long timescales of 105 years. Trench-parallel, crustal normal faults modulate the characteristics of permanent forearc-deformation; upper-plate extension likely represents a second-order phenomenon resulting from subduction erosion and subsequent underplating that lead to regional tectonic uplift and local gravitational collapse of the forearc. In addition, variable activity with respect to the subduction of the Juan Fernández Ridge can be detected in the upper plate over the course of multiple interglacial periods, emphasizing the role of bathymetric anomalies in causing local increases in terrace-uplift rate. This thesis therefore provides new insights into the current understanding of subduction-zone processes and the dynamics of coastal forearc deformation, whose different interacting forcing factors impact the topographic and geomorphic evolution of the western South American coast.
Traditionally, mental disorders have been identified based on specific symptoms and standardized diagnostic systems such as the DSM-5 and ICD-10. However, these symptom-based definitions may only partially represent neurobiological and behavioral research findings, which could impede the development of targeted treatments. A transdiagnostic approach to mental health research, such as the Research Domain Criteria (RDoC) approach, maps resilience and broader aspects of mental health to associated components. By investigating mental disorders in a transnosological way, we can better understand disease patterns and their distinguishing and common factors, leading to more precise prevention and treatment options.
Therefore, this dissertation focuses on (1) the latent domain structure of the RDoC approach in a transnosological sample including healthy controls, (2) its domain associations to disease severity in patients with anxiety and depressive disorders, and (3) an overview of the scientific results found regarding Positive (PVS) and Negative Valence Systems (NVS) associated with mood and anxiety disorders.
The following main results were found: First, the latent RDoC domain structure for PVS and NVS, Cognitive Systems (CS), and Social Processes (SP) could be validated using self-report and behavioral measures in a transnosological sample. Second, we found transdiagnostic and disease-specific associations between those four domains and disease severity in patients with depressive and anxiety disorders. Third, the scoping review showed a sizable amount of RDoC research conducted on PVS and NVS in mood and anxiety disorders, with research gaps for both domains and specific conditions.
In conclusion, the research presented in this dissertation highlights the potential of the transnosological RDoC framework approach in improving our understanding of mental disorders. By exploring the latent RDoC structure and associations with disease severity and disease-specific and transnosological associations for anxiety and depressive disorders, this research provides valuable insights into the full spectrum of psychological functioning. Additionally, this dissertation highlights the need for further research in this area, identifying both RDoC indicators and research gaps. Overall, this dissertation represents an important contribution to the ongoing efforts to improve our understanding and the treatment of mental disorders, particularly within the commonly comorbid disease spectrum of mood and anxiety disorders.
The relevance of physical fitness for children’s and adolescents’ health is indisputable and it is crucial to regularly assess and evaluate children’s and adolescents’ individual physical fitness development to detect potential negative health consequences in time. Physical fitness tests are easy-to-administer, reliable, and valid which is why they should be widely used to provide information on performance development and health status of children and adolescents. When talking about development of physical fitness, two perspectives can be distinguished. One perspective is how the physical fitness status of children and adolescents changed / developed over the past decades (i.e., secular trends). The other perspective covers the analyses how physical fitness develops with increasing age due to growth and maturation processes. Although, the development of children’s and adolescents’ physical fitness has been extensively described and analyzed in the literature, still some questions remain to be uncovered that will be addressed in the present doctoral thesis.
Previous systematic reviews and meta-analyses have examined secular trends in children’s and adolescents’ physical fitness. However, considering that those analyses are by now 15 years old and that updates are available only to limited components of physical fitness, it is time to re-analyze the literature and examine secular trends for selected components of physical fitness (i.e., cardiorespiratory endurance, muscle strength, proxies of muscle power, and speed). Fur-thermore, the available studies on children’s development of physical fitness as well as the ef-fects of moderating variables such as age and sex have been investigated within a long-term ontogenetic perspective. However, the effects of age and sex in the transition from pre-puberty to puberty in the ninth year of life using a short-term ontogenetic perspective and the effect of timing of school enrollment on children’s development of physical fitness have not been clearly identified. Therefore, the present doctoral thesis seeks to complement the knowledge of children’s and adolescents’ physical fitness development by updating secular trend analysis in selected components of physical fitness, by examining short-term ontogenetic cross-sectional developmental differences in children`s physical fitness, and by comparing physical fitness of older- and younger-than-keyage children versus keyage-children. These findings provide valuable information about children’s and adolescents’ physical fitness development to help prevent potential deficits in physical fitness as early as possible and consequently ensure a holistic development and a lifelong healthy life.
Initially, a systematic review to provide an ‘update’ on secular trends in selected components of physical fitness (i.e., cardiorespiratory endurance, relative muscle strength, proxies of muscle power, speed) in children and adolescents aged 6 to 18 years was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement guidelines. To examine short-term ontogenetic cross-sectional developmental differences and to compare physical fitness of older- and younger-than-keyage children versus keyage-children physical fitness data of 108,295 keyage-children (i.e., aged 8.00 to 8.99 years), 2,586 younger-than-keyage children (i.e., aged 7.00 to 7.99 years), and 26,540 older-than-keyage children (i.e., aged 9.00 to 9.99 years) from the third grade were analyzed. Physical fitness was assessed through the EMOTIKON test battery measuring cardiorespiratory endurance (i.e., 6-min-run test), coordina-tion (i.e., star-run test), speed (i.e., 20-m linear sprint test), and proxies of lower (i.e., standing long jump test) and upper limbs (i.e., ball-push test) muscle power. Statistical inference was based on Linear Mixed Models.
Findings from the systematic review revealed a large initial improvement and an equally large subsequent decline between 1986 and 2010 as well as a stabilization between 2010 and 2015 in cardiorespiratory endurance, a general trend towards a small improvement in relative muscle strength from 1972 to 2015, an overall small negative quadratic trend for proxies of muscle power from 1972 to 2015, and a small-to-medium improvement in speed from 2002 to 2015. Findings from the cross-sectional studies showed that even in a single prepubertal year of life (i.e., ninth year) physical fitness performance develops linearly with increasing chronological age, boys showed better performances than girls in all physical fitness components, and the components varied in the size of sex and age effects. Furthermore, findings revealed that older-than-keyage children showed poorer performance in physical fitness compared to keyage-children, older-than-keyage girls showed better performances than older-than-keyage boys, and younger-than-keyage children outperformed keyage-children.
Due to the varying secular trends in physical fitness, it is recommended to promote initiatives for physical activity and physical fitness for children and adolescents to prevent adverse effects on health and well-being. More precisely, public health initiatives should specifically consider exercising cardiorespiratory endurance and muscle strength because both components showed strong positive associations with markers of health. Furthermore, the findings implied that physical education teachers, coaches, or researchers can utilize a proportional adjustment to individually interpret physical fitness of prepubertal school-aged children. Special attention should be given to the promotion of physical fitness of older-than-keyage children because they showed poorer performance in physical fitness than keyage-children. Therefore, it is necessary to specifically consider this group and provide additional health and fitness programs to reduce their deficits in physical fitness experienced during prior years to guarantee a holistic development.