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In this thesis, I examine different A-bar movement dependencies in Igbo, a Benue-Congo language spoken in southern Nigeria. Movement dependencies are found in constructions where an element is moved to the left edge of the clause to express information-structural categories such as in questions, relativization and focus. I show that these constructions in Igbo are very uniform from a syntactic point of view. The constructions are built on two basic fronting operations: relativization and focus movement, and are biclausal. I further investigate several morphophonological effects that are found in these A-bar constructions. I propose that these effects are reflexes of movement that are triggered when an element is moved overtly in relativization or focus. This proposal helps to explain the tone patterns that have previously been assumed to be a property of relative clauses. The thesis adds to the growing body of tonal reflexes of A-bar movement reported for a few African languages. The thesis also provides an insight into the complementizer domain (C-domain) of Igbo.
The PhD thesis entitled “Actions through the lens of communicative cues. The influence of verbal cues and emotional cues on action processing and action selection in the second year of life” is based on four studies, which examined the cognitive integration of another person’s communicative cues (i.e., verbal cues, emotional cues) with behavioral cues in 18- and 24-month-olds. In the context of social learning of instrumental actions, it was investigated how the intention-related coherence of either a verbally announced action intention or an emotionally signaled action evaluation with an action demonstration influenced infants’ neuro-cognitive processing (Study I) and selection (Studies II, III, IV) of a novel object-directed action. Developmental research has shown that infants benefit from another’s behavioral cues (e.g., action effect, persistency, selectivity) to infer the underlying goal or intention, respectively, of an observed action (e.g., Cannon & Woodward, 2012; Woodward, 1998). Particularly action effects support infants in distinguishing perceptual action features (e.g., target object identity, movement trajectory, final target object state) from conceptual action features such as goals and intentions. However, less is known about infants’ ability to cognitively integrate another’s behavioral cues with additional action-related communicative cues. There is some evidence showing that in the second year of life, infants selectively imitate a novel action that is verbally (“There!”) or emotionally (positive expression) marked as aligning with the model’s action intention over an action that is verbally (“Whoops!”) or emotionally (negative expression) marked as unintentional (Carpenter, Akhtar, & Tomasello, 1998; Olineck & Poulin-Dubois, 2005, 2009; Repacholi, 2009; Repacholi, Meltzoff, Toub, & Ruba, 2016). Yet, it is currently unclear which role the specific intention-related coherence of a communicative cue with a behavioral cue plays in infants’ action processing and action selection that is, whether the communicative cue confirms, contrasts, clarifies, or is unrelated to the behavioral cue. Notably, by using both verbal cues and emotional cues, we examined not only two domains of communicative cues but also two qualitatively distinct relations between behavioral cues on the one hand and communicative cues on the other hand. More specifically, a verbal cue has the potential to communicate an action intention in the absence of an action demonstration and thus a prior-intention (Searle, 1983), whereas an emotional cue evaluates an ongoing or past action demonstration and thus signals an intention-in-action (Searle, 1983). In a first research focus, this thesis examined infants’ capacity to cognitively integrate another’s intention-related communicative cues and behavioral cues, and also focused on the role of the social cues’ coherence in infants’ action processing and action selection. In a second research focus, and to gain more elaborate insights into how the sub-processes of social learning (attention, encoding, response; cf. Bandura, 1977) are involved in this coherence-sensitive integrative processing, we employed a multi-measures approach. More specifically, we used Electroencephalography (EEG) and looking times to examine how the cues’ coherence influenced the compound of attention and encoding, and imitation (including latencies to first-touch and first-action) to address the compound of encoding and response. Based on the action-reconstruction account (Csibra, 2007), we predicted that infants use extra-motor information (i.e., communicative cues) together with behavioral cues to reconstruct another’s action intention. Accordingly, we expected infants to possess a flexibly organized internal action hierarchy, which they adapt according to the cues’ coherence that is, according to what they inferred to be the overarching action goal. More specifically, in a social-learning situation that comprised an adult model, who demonstrated an action on a novel object that offered two actions, we expected the demonstrated action to lead infants’ action hierarchy when the communicative (i.e., verbal, emotional) cue conveyed similar (confirming coherence) or no additional (un-related coherence) intention-related information relative to the behavioral cue. In terms of action selection, this action hierarchy should become evident in a selective imitation of the demonstrated action. However, when the communicative cue questioned (contrasting coherence) the behaviorally implied action goal or was the only cue conveying meaningful intention-related information (clarifying coherence), the verbally/emotionally intended action should ascend infants’ action hierarchy. Consequently, infants’ action selection should align with the verbally/emotionally intended action (goal emulation). Notably, these predictions oppose the direct-matching perspective (Rizzolatti & Craighero, 2004), according to which the observation of another’s action directly resonates with the observer’s motor repertoire, with this motor resonance enabling the identification of the underlying action goal. Importantly, the direct-matching perspective predicts a rather inflexible action hierarchy inasmuch as the process of goal identification should solely rely on the behavioral cue, irrespective of the behavioral cue’s coherence with extra-motor intention-related information, as it may be conveyed via communicative cues. As to the role of verbal cues, Study I used EEG to examine the influence of a confirming (Congruent) versus contrasting (Incongruent) coherence of a verbal action intention with the same action demonstration on 18-month-olds’ conceptual action processing (as measured via mid-latency mean negative ERP amplitude) and motor activation (as measured via central mu-frequency band power). The action was demonstrated on a novel object that offered two action alternatives from a neutral position. We expected mid-latency ERP negativity to be enhanced in Incongruent compared to Congruent, because past EEG research has demonstrated enhanced conceptual processing for stimuli that mismatched rather than matched the semantic context (Friedrich & Friederici, 2010; Kaduk et al., 2016). Regarding motor activation, Csibra (2007) posited that the identification of a clear action goal constitutes a crucial basis for motor activation to occur. We therefore predicted reduced mu power (indicating enhanced motor activation) for Congruent than Incongruent, because in Congruent, the cues’ match provides unequivocal information about the model’s action goal, whereas in Incongruent, the conflict may render the model’s action goal more unclear. Unexpectedly, in the entire sample, 18-month-olds’ mid-latency ERP negativity during the observation of the same action demonstration did not differ significantly depending on whether this action was congruent or incongruent with the model’s verbal action intention. Yet, post hoc analyses revealed the presence of two subgroups of infants, each of which exhibited significantly different mid-latency ERP negativity for Congruent versus Incongruent, but in opposing directions. The subgroups differed in their productive action-related language skills, with the linguistically more advanced infants exhibiting the expected response pattern of enhanced ERP mean negativity in Incongruent than Congruent, indicating enhanced conceptual processing of an action demonstration that was contrasted rather than confirmed by the verbal action context. As expected, central mu power in the entire sample was reduced in Congruent relative to Incongruent, indicating enhanced motor activation when the action demonstration was preceded by a confirming relative to a contrasting verbal action intention. This finding may indicate the covert preparation for a preferential imitation of the congruent relative to the incongruent action (Filippi et al., 2016; Frey & Gerry, 2006). Overall, these findings are in line with the action-reconstruction account (Csibra, 2007), because they suggest a coherence-sensitive attention to and encoding of the same perceptual features of another’s behavior and thus a cognitive integration of intention-related verbal cues and behavioral cues. Yet, because the subgroup constellation in infants’ ERPs was only discovered post hoc, future research is clearly required to substantiate this finding. Also, future research should validate our interpretation that enhanced motor activation may reflect an electrophysiological marker of subsequent imitation by employing EEG and imitation in a within-subjects design. Study II built on Study I by investigating the impact of coherence of a verbal cue and a behavioral cue on 18- and 24-month-olds’ action selection in an imitation study. When infants of both age groups observed a confirming (Congruent) or unrelated (Pseudo-word: action demonstration was associated with novel verb-like cue) coherence, they selectively imitated the demonstrated action over the not demonstrated, alternative action, with no difference between these two conditions. These findings suggest that, as expected, infants’ action hierarchy was led by the demonstrated action when the verbal cue provided similar (Congruent) or no additional (Pseudo-word) intention-related information relative to a meaningful behavioral cue. These findings support the above-mentioned interpretation that enhanced motor activation during action observation may reflect a covert preparation for imitation (Study I). Interestingly, infants did not seem to benefit from the intention-highlighting effect of the verbal cue in Congruent, suggesting that the verbal cue had an unspecific (e.g., attention-guiding) effect on infants’ action selection. Contrary, when infants observed a contrasting (Incongruent) or clarifying (Failed-attempt: model failed to manipulate the object but verbally announced a certain action intention) coherence, their action selection varied with age and also varied across the course of the experiment (block 1 vs. block 2). More specifically, the 24-month-olds made stronger use of the verbal cue for their action selection in block 1 than did the 18-month-olds. However, while the 18-month-olds’ use of the verbal cue increased across blocks, particularly in Incongruent, the 24-month-olds’ use of the verbal cue decreased across blocks. Overall, these results suggest that, as expected, infants’ action hierarchy in Incongruent (both age groups) and Failed-attempt (only 24-month-olds) drew on the verbal action intention, because in both age groups, infants emulated the verbal intention about as often as they imitated the demonstrated action or even emulated the verbal action intention preferentially. Yet, these findings were confined to certain blocks. It may be argued that the younger age group had a harder time inferring and emulating the intended, yet never observed action, because this requirement is more demanding in cognitive and motor terms. These demands may explain why the 18-month-olds needed some time to take account of the verbal action intention. Contrary, it seems that the 24-month-olds, although demonstrating their principle capacity to take account of the verbal cue in block 1, lost trust in the model’s verbal cue, maybe because the verbal cue did not have predictive value for the model’s actual behavior. Supporting this interpretation, research on selective trust has demonstrated that already infants evaluate another’s reliability or competence, respectively, based on how that model handles familiar objects (behavioral reliability) or labels familiar objects (verbal reliability; for reviews, see Mills, 2013; Poulin-Dubois & Brosseau-Liard, 2016). Relatedly, imitation research has demonstrated that the interpersonal aspects of a social-learning situation gain increasing relevance for infants during the second year of life (Gellén & Buttelmann, 2019; Matheson, Moore, & Akhtar, 2013; Uzgiris, 1981). It may thus be argued that when the 24-month-olds were repeatedly faced with a verbally unreliable model, they de-evaluated the verbal cue as signaling the model’s action intention and instead relied more heavily on alternative cues such as the behavioral cue (Incongruent) or the action context (e.g., object affordances, salience; Failed-attempt). Infants’ first-action latencies were higher in Incongruent and Failed-attempt than in both Congruent and Pseudo-word, and were also higher in Failed-attempt than in Incongruent. These latency-findings thus indicate that situations involving a meaningful verbal cue that deviated from the behavioral cue are cognitively more demanding, resulting in a delayed initiation of a behavioral response. In sum, the findings of Study II suggest that both age groups were highly flexible in their integration of a verbal cue and behavioral cue. Moreover, our results do not indicate a general superiority of either cue. Instead, it seems to depend on the informational gain conveyed by the verbal cue whether it exerts a specific, intention-highlighting effect (Incongruent, Failed-attempt) or an unspecific (e.g., attention-guiding) effect (Congruent, Pseudo-word). Studies III and IV investigated the impact of another’s action-related emotional cues on 18-month-olds’ action selection. In Study III, infants observed a model, who demonstrated two actions on a novel object in direct succession, and who combined one of the two actions with a positive (happy) emotional expression and the other action with a negative (sad) emotional expression. As expected, infants imitated the positively emoted (PE) action more often than the negatively emoted (NE) action. This preference arose from an increase in infants’ readiness to perform the PE action from the baseline period (prior to the action demonstrations) to the test period (following the action demonstrations), rather than from a decrease in readiness to the perform the NE action. The positive cue thus had a stronger behavior-regulating effect than the negative cue. Notably, infants’ more general object-directed behavior in terms of first-touch latencies remained unaffected by the emotional cues’ valence, indicating that infants had linked the emotional cues specifically to the corresponding action and not the object as a whole (Repacholi, 2009). Also, infants’ looking times during the action demonstration did not differ significantly as a function of emotional valence and were characterized by a predominant attentional focus to the action/object rather than to the model’s face. Together with the findings on infants’ first-touch latencies, these results indicate a sensitivity for the notion that emotions can have very specific referents (referential specificity; Martin, Maza, McGrath, & Phelps, 2014). Together, Study III provided evidence for selective imitation based on another’s intention-related (particularly positive) emotional cues in an action-selection task, and thus indicates that infants’ action hierarchy flexibly responds to another’s emotional evaluation of observed actions. According to Repacholi (2009), we suggest that infants used the model’s emotional evaluation to re-appraise the corresponding action (effect), for instance in terms of desirability. Study IV followed up on Study III by investigating the role of the negative emotional cue for infants’ action selection in more detail. Specifically, we investigated whether a contrasting (negative) emotional cue alone would be sufficient to differentially rank the two actions along infants’ action hierarchy or whether instead infants require direct information about the model’s action intention (in the form of a confirming action-emotion pair) to align their action selection with the emotional cues. Also, we examined whether the absence of a direct behavior-regulating effect of the negative cue in Study III was due to the negative cue itself or to the concurrently available positive cue masking the negative cue’s potential effect. To this end, we split the demonstration of the two action-emotion pairs across two trials. In each trial, one action was thus demonstrated and emoted (PE, NE action), and one action was not demonstrated and un-emoted (UE action). For trial 1, we predicted that infants, who observed a PE action demonstration, would selectively imitate the PE action, whereas infants, who observed a NE action demonstration would selectively emulate the UE action. As to trial 2, we expected the complementary action-emotion pair to provide additional clarifying information as the model’s emotional evaluation of both actions, which should either lead to adaptive perseveration (if infants’ action selection in trial 1 had already drawn on the emotional cue) or adaptive change (if infants’ action selection in trial 1 signaled a disregard of the emotional cue). As to trial 1, our findings revealed that, as expected, infants imitated the PE action more often than they emulated the UE action. Like in Study III, this selectivity arose from an increase in infants’ propensity to perform the PE action from baseline to trial 1. Also like in Study III, infants performed the NE action about equally often in baseline and trial 1, which speaks against a direct behavior-regulating effect of the negative cue also when presented in isolation. However, after a NE action demonstration, infants emulated the UE action more often in trial 1 than in baseline, suggesting an indirect behavior-regulating effect of the negative cue. Yet, this indirect effect did not yield a selective emulation of the UE action, because infants performed both action alternatives about equally often in trial 1. Unexpectedly, infants’ action selection in trial 2 was unaffected by the emotional cue. Instead, infants perseverated their action selection of trial 1 in trial 2, irrespective of whether it was adaptive or non-adaptive with respect to the model’s emotional evaluation of the action. It seems that infants changed their strategy across trials, from an initial adherence to the emotional (particularly positive) cue, towards bringing about a salient action effect (Marcovich & Zelazo, 2009). In sum, Studies III and IV indicate a dynamic interplay of different action-selection strategies, depending on valence and presentation order. Apparently, at least in infancy, action reconstruction as one basis for selective action performance reaches its limits when infants can only draw on indirect intention-related information (i.e., which action should be avoided). Overall, our findings favor the action-reconstruction account (Csibra, 2007), according to which actions are flexibly organized along a hierarchy, depending on inferential processes based on extra-motor intention-related information. At the same time, the findings question the direct-matching hypothesis (Rizzolatti & Craighero, 2004), according to which the identification (and pursuit) of action goals hinges on a direct simulation of another’s behavioral cues. Based on the studies’ findings, a preliminary working model is introduced, which seeks to integrate the two theoretical accounts by conceptualizing the routes that activation induced by social cues may take to eventually influence an infant’s action selection. Our findings indicate that it is useful to strive a differentiated conceptualization of communicative cues, because they seem to operate at different places within the process of cue integration, depending on their potential to convey direct intention-related information. Moreover, we suggest that there is bidirectional exchange within each compound of adjacent sub-processes (i.e., between attention and encoding, and encoding and response), and between the compounds. Hence, our findings highlight the benefits of a multi-measures approach when studying the development of infants’ social-cognitive abilities, because it provides a more comprehensive picture how the concerted use of social cues from different domains influences infants’ processing and selection of instrumental actions. Finally, this thesis points to potential future directions to substantiate our current interpretation of the findings.. Moreover, an extension to additional kinds of coherence is suggested to get closer to infants’ everyday-world of experience.
Cardiac valves are essential for the continuous and unidirectional flow of blood throughout the body. During embryonic development, their formation is strictly connected to the mechanical forces exerted by blood flow. The endocardium that lines the interior of the heart is a specialized endothelial tissue and is highly sensitive to fluid shear stress. Endocardial cells harbor a signal transduction machinery required for the translation of these forces into biochemical signaling, which strongly impacts cardiac morphogenesis and physiology. To date, we lack a solid understanding on the mechanisms by which endocardial cells sense the dynamic mechanical stimuli and how they trigger different cellular responses. In the zebrafish embryo, endocardial cells at the atrioventricular canal respond to blood flow by rearranging from a monolayer to a double-layer, composed of a luminal cell population subjected to blood flow and an abluminal one that is not exposed to it. These early morphological changes lead to the formation of an immature valve leaflet. While previous studies mainly focused on genes that are positively regulated by shear stress, the mechanisms regulating cell behaviors and fates in cells that lack the stimulus of blood flow are largely unknown. One key discovery of my work is that the flow-sensitive Notch receptor and Krüppel-like factor (Klf) 2, one of the best characterized flow-regulated transcriptional factors, are activated by shear stress but that they function in two parallel signal transduction pathways. Each of these two pathways is essential for the rearrangement of atrioventricular cells into an immature double-layered valve leaflets. A second key discovery of my study is the finding that both Notch and Klf2 signaling negatively regulate the expression of the angiogenesis receptor Vegfr3/Flt4, which becomes restricted to abluminal endocardial cells of the valve leaflet. Within these cells, Flt4 downregulates the expressions of the cell adhesion proteins Alcam and VE-cadherin. A loss of Flt4 causes abluminal endocardial cells to ectopically express Notch, which is normally restricted to luminal cells, and impairs valve morphology. My study suggests that abluminal endocardial cells that do not experience mechanical stimuli loose Notch expression and this triggers expression of Flt4. In turn, Flt4 negatively regulates Notch on the abluminal side of the valve leaflet. These antagonistic signaling activities and fine-tuned gene regulatory mechanisms ultimately shape cardiac valve leaflets by inducing unique differences in the fates of endocardial cells.
The East Asian monsoons characterize the modern-day Asian climate, yet their geological history and driving mechanisms remain controversial. The southeasterly summer monsoon provides moisture, whereas the northwesterly winter monsoon sweeps up dust from the arid Asian interior to form the Chinese Loess Plateau. The onset of this loess accumulation, and therefore of the monsoons, was thought to be 8 million years ago (Ma). However, in recent years these loess records have been extended further back in time to the Eocene (56-34 Ma), a period characterized by significant changes in both the regional geography and global climate. Yet the extent to which these reconfigurations drive atmospheric circulation and whether the loess-like deposits are monsoonal remains debated. In this thesis, I study the terrestrial deposits of the Xining Basin previously identified as Eocene loess, to derive the paleoenvironmental evolution of the region and identify the geological processes that have shaped the Asian climate.
I review dust deposits in the geological record and conclude that these are commonly represented by a mix of both windblown and water-laid sediments, in contrast to the pure windblown material known as loess. Yet by using a combination of quartz surface morphologies, provenance characteristics and distinguishing grain-size distributions, windblown dust can be identified and quantified in a variety of settings. This has important implications for tracking aridification and dust-fluxes throughout the geological record.
Past reversals of Earth’s magnetic field are recorded in the deposits of the Xining Basin and I use these together with a dated volcanic ash layer to accurately constrain the age to the Eocene period. A combination of pollen assemblages, low dust abundances and other geochemical data indicates that the early Eocene was relatively humid suggesting an intensified summer monsoon due to the warmer greenhouse climate at this time. A subsequent shift from predominantly freshwater to salt lakes reflects a long-term aridification trend possibly driven by global cooling and the continuous uplift of the Tibetan Plateau. Superimposed on this aridification are wetter intervals reflected in more abundant lake deposits which correlate with highstands of the inland proto-Paratethys Sea. This sea covered the Eurasian continent and thereby provided additional moisture to the winter-time westerlies during the middle to late Eocene.
The long-term aridification culminated in an abrupt shift at 40 Ma reflected by the onset of windblown dust, an increase in steppe-desert pollen, the occurrence of high-latitude orbital cycles and northwesterly winds identified in deflated salt deposits. Together, these indicate the onset of a Siberian high atmospheric pressure system driving the East Asian winter monsoon as well as dust storms and was triggered by a major sea retreat from the Asian interior. These results therefore show that the proto-Paratethys Sea, though less well recognized than the Tibetan Plateau and global climate, has been a major driver in setting up the modern-day climate in Asia.
Largescale patterns of global land use change are very frequently accompanied by natural habitat loss. To assess the consequences of habitat loss for the remaining natural and semi-natural biotopes, inclusion of cumulative effects at the landscape level is required. The interdisciplinary concept of vulnerability constitutes an appropriate assessment framework at the landscape level, though with few examples of its application for ecological assessments. A comprehensive biotope vulnerability analysis allows identification of areas most affected by landscape change and at the same time with the lowest chances of regeneration.
To this end, a series of ecological indicators were reviewed and developed. They measured spatial attributes of individual biotopes as well as some ecological and conservation characteristics of the respective resident species community. The final vulnerability index combined seven largely independent indicators, which covered exposure, sensitivity and adaptive capacity of biotopes to landscape changes. Results for biotope vulnerability were provided at the regional level. This seems to be an appropriate extent with relevance for spatial planning and designing the distribution of nature reserves.
Using the vulnerability scores calculated for the German federal state of Brandenburg, hot spots and clusters within and across the distinguished types of biotopes were analysed. Biotope types with high dependence on water availability, as well as biotopes of the open landscape containing woody plants (e.g., orchard meadows) are particularly vulnerable to landscape changes. In contrast, the majority of forest biotopes appear to be less vulnerable. Despite the appeal of such generalised statements for some biotope types, the distribution of values suggests that conservation measures for the majority of biotopes should be designed specifically for individual sites. Taken together, size, shape and spatial context of individual biotopes often had a dominant influence on the vulnerability score.
The implementation of biotope vulnerability analysis at the regional level indicated that large biotope datasets can be evaluated with high level of detail using geoinformatics. Drawing on previous work in landscape spatial analysis, the reproducible approach relies on transparent calculations of quantitative and qualitative indicators. At the same time, it provides a synoptic overview and information on the individual biotopes. It is expected to be most useful for nature conservation in combination with an understanding of population, species, and community attributes known for specific sites. The biotope vulnerability analysis facilitates a foresighted assessment of different land uses, aiding in identifying options to slow habitat loss to sustainable levels. It can also be incorporated into planning of restoration measures, guiding efforts to remedy ecological damage. Restoration of any specific site could yield synergies with the conservation objectives of other sites, through enhancing the habitat network or buffering against future landscape change.
Biotope vulnerability analysis could be developed in line with other important ecological concepts, such as resilience and adaptability, further extending the broad thematic scope of the vulnerability concept. Vulnerability can increasingly serve as a common framework for the interdisciplinary research necessary to solve major societal challenges.
Early numeracy is one of the strongest predictors for later success in school mathematics (e.g., Duncan et al., 2007). The main goal of first grade mathematics teachers should therefore be to provide learning opportunities that enable all students to develop sound early numeracy skills. Developmental models, or learning progressions, can describe how early numerical understanding typically develops. Assessments that are aligned to empirically validated learning progressions can support teachers to understand their students learning better and target instruction accordingly. To date, there have been no progression-based instruments made available for German teachers to monitor their students’ progress in the domain of early numeracy. This dissertation contributes to the design of such an instrument. The first study analysed the suitability of early numeracy assessments currently used in German primary schools at school entry to identify students’ individual starting points for subsequent progress monitoring. The second study described the development of progression-based items and investigated the items in regards to main test quality criteria, such as reliability, validity, and test fairness, to find a suitable item pool to build targeted tests. The third study described the construction of the progress monitoring measure, referred to as the learning progress assessment (LPA). The study investigated the extent to which the LPA was able to monitor students’ individual learning progress in early numeracy over time. The results of the first study indicated that current school entry assessments were not able to provide meaningful information about the students’ initial learning status. Thus, the MARKO-D test (Ricken, Fritz, & Balzer, 2013) was used to determine the students’ initial numerical understanding in the other two studies, because it has been shown to be an effective measure of conceptual numerical understanding (Fritz, Ehlert, & Leutner, 2018). Both studies provided promising evidence for the quality of the LPA and its ability to detect changes in numerical understanding over the course of first grade. The studies of this dissertation can be considered an important step in the process of designing an empirically validated instrument that supports teachers to monitor their students’ early numeracy development and to adjust their teaching accordingly to enhance school achievement.
Even though the majority of individuals know that exercising is healthy, a high percentage struggle to achieve the recommended amount of exercise. The (social-cognitive) theories that are commonly applied to explain exercise motivation refer to the assumption that people base their decisions mainly on rational reasoning. However, behavior is not only bound to reflection. In recent years, the role of automaticity and affect for exercise motivation has been increasingly discussed. In this dissertation, central assumptions of the affective–reflective theory of physical inactivity and exercise (ART; Brand & Ekkekakis, 2018), an exercise-specific dual-process theory that emphasizes the role of a momentary automatic affective reaction for exercise-decisions, were examined. The central aim of this dissertation was to investigate exercisers and non-exercisers automatic affective reactions to exercise-related stimuli (i.e., type-1 process). In particular, the two components of the ART’s type-1 process, that are, automatic associations with exercise and the automatic affective valuation to exercise, were under study.
In the first publication (Schinkoeth & Antoniewicz, 2017), research on automatic (evaluative) associations with exercise was summarized and evaluated in a systematic review. The results indicated that automatic associations with exercise appeared to be relevant predictors for exercise behavior and other exercise-related variables, providing evidence for a central assumption of the ART’s type-1 process. Furthermore, indirect methods seem to be suitable to assess automatic associations. The aim of the second publication (Schinkoeth, Weymar, & Brand, 2019) was to approach the somato-affective core of the automatic valuation of exercise using analysis of reactivity in vagal HRV while viewing exercise-related pictures. Results revealed that differences in exercise volume could be regressed on HRV reactivity. In light of the ART, these findings were interpreted as evidence of an inter-individual affective reaction elicited at the thought of exercise and triggered by exercise-stimuli. In the third publication (Schinkoeth & Brand, 2019, subm.), it was sought to disentangle and relate to each other the ART’s type-1 process components—automatic associations and the affective valuation of exercise. Automatic associations to exercise were assessed with a recoding-free variant of an implicit association test (IAT). Analysis of HRV reactivity was applied to approach a somatic component of the affective valuation, and facial reactions in a facial expression (FE) task served as indicators of the automatic affective reaction’s valence. Exercise behavior was assessed via self-report. The measurement of the affective valuation’s valence with the FE task did not work well in this study. HRV reactivity was predicted by the IAT score and did also statistically predict exercise behavior. These results thus confirm and expand upon the results of publication two and provide empirical evidence for the type-1 process, as defined in the ART. This dissertation advances the field of exercise psychology concerning the influence of automaticity and affect on exercise motivation. Moreover, both methodical implications and theoretical extensions for the ART can be derived from the results.
Depending on the biochemical and biotechnical approach, the aim of this work was to understand the mechanism of protein-glucan interactions in regulation and control of starch degradation. Although starch degradation starts with the phosphorylation process, the mechanisms by which this process is controlling and adjusting starch degradation are not yet fully understood. Phosphorylation is a major process performed by the two dikinases enzymes α-glucan, water dikinase (GWD) and phosphoglucan water dikinase (PWD). GWD and PWD enzymes phosphorylate the starch granule surface; thereby stimulate starch degradation by hydrolytic enzymes. Despite these important roles for GWD and PWD, so far the biochemical processes by which these enzymes are able to regulate and adjust the rate of phosphate incorporation into starch during the degradation process haven‘t been understood. Recently, some proteins were found associated with the starch granule. Two of these proteins are named Early Starvation Protein 1 (ESV1) and its homologue Like-Early Starvation Protein 1 (LESV). It was supposed that both are involved in the control of starch degradation, but their function has not been clearly known until now. To understand how ESV1 and LESV-glucan interactions are regulated and affect the starch breakdown, it was analyzed the influence of ESV1 and LESV proteins on the phosphorylating enzyme GWD and PWD and hydrolysing enzymes ISA, BAM, and AMY. However, the analysis determined the location of LESV and ESV1 in the chloroplast stroma of Arabidopsis. Mass spectrometry data predicted ESV1and LESV proteins as a product of the At1g42430 and At3g55760 genes with a predicted mass of ~50 kDa and ~66 kDa, respectively. The ChloroP program predicted that ESV1 lacks the chloroplast transit peptide, but it predicted the first 56 amino acids N-terminal region as a chloroplast transit peptide for LESV. Usually, the transit peptide is processed during transport of the proteins into plastids. Given that this processing is critical, two forms of each ESV1 and LESV were generated and purified, a full-length form and a truncated form that lacks the transit peptide, namely, (ESV1and tESV1) and (LESV and tLESV), respectively. Both protein forms were included in the analysis assays, but only slight differences in glucan binding and protein action between ESV1 and tESV1 were observed, while no differences in the glucan binding and effect on the GWD and PWD action were observed between LESV and tLESV. The results revealed that the presence of the N-terminal is not massively altering the action of ESV1 or LESV. Therefore, it was only used the ESV1 and tLESV forms data to explain the function of both proteins.
However, the analysis of the results revealed that LESV and ESV1 proteins bind strongly at the starch granule surface. Furthermore, not all of both proteins were released after their incubation with starches after washing the granules with 2% [w/v] SDS indicates to their binding to the deeper layers of the granule surface. Supporting of this finding comes after the binding of both proteins to starches after removing the free glucans chains from the surface by the action of ISA and BAM. Although both proteins are capable of binding to the starch structure, only LESV showed binding to amylose, while in ESV1, binding was not observed. The alteration of glucan structures at the starch granule surface is essential for the incorporation of phosphate into starch granule while the phosphorylation of starch by GWD and PWD increased after removing the free glucan chains by ISA. Furthermore, PWD showed the possibility of starch phosphorylation without prephosphorylation by GWD.
Biochemical studies on protein-glucan interactions between LESV or ESV1 with different types of starch showed a potentially important mechanism of regulating and adjusting the phosphorylation process while the binding of LESV and ESV1 leads to altering the glucan structures of starches, hence, render the effect of the action of dikinases enzymes (GWD and PWD) more able to control the rate of starch degradation. Despite the presence of ESV1 which revealed an antagonistic effect on the PWD action as the PWD action was decreased without prephosphorylation by GWD and increased after prephosphorylation by GWD (Chapter 4), PWD showed a significant reduction in its action with or without prephosphorylation by GWD in the presence of ESV1 whether separately or together with LESV (Chapter 5). However, the presence of LESV and ESV1 together revealed the same effect compared to the effect of each one alone on the phosphorylation process, therefore it is difficult to distinguish the specific function between them. However, non-interactions were detected between LESV and ESV1 or between each of them with GWD and PWD or between GWD and PWD indicating the independent work for these proteins. It was also observed that the alteration of the starch structure by LESV and ESV1 plays a role in adjusting starch degradation rates not only by affecting the dikinases but also by affecting some of the hydrolysing enzymes since it was found that the presence of LESV and ESV1leads to the reduction of the action of BAM, but does not abolish it.
Ferruginous conditions were a prominent feature of the oceans throughout the Precambrian Eons and thus throughout much of Earth’s history. Organic matter mineralization and diagenesis within the ferruginous sediments that deposited from Earth’s early oceans likely played a key role in global biogeochemical cycling. Knowledge of organic matter mineralization in ferruginous sediments, however, remains almost entirely conceptual, as modern analogue environments are extremely rare and largely unstudied, to date. Lake Towuti on the island of Sulawesi, Indonesia is such an analogue environment and the purpose of this PhD project was to investigate the rates and pathways of organic matter mineralization in its ferruginous sediments.
Lake Towuti is the largest tectonic lake in Southeast Asia and is hosted in the mafic and ultramafic rocks of the East Sulawesi Ophiolite. It has a maximum water depth of 203 m and is weakly thermally stratified. A well-oygenated surface layer extends to 70 m depth, while waters below 130 m are persistently anoxic. Intensive weathering of the ultramafic catchment feeds the lake with large amounts of iron(oxy)hydroxides while the runoff contains only little sulfate, leading to sulfate-poor (< 20 µM) lake water and anoxic ferruginous conditions below 130 m. Such conditions are analogous to the ferruginous water columns that persisted throughout much of the Archean and Proterozoic eons. Short (< 35 cm) sediment cores were collected from different water depths corresponding to different bottom water redox conditions. Also, a drilling campaign of the International Continental Scientific Drilling Program (ICDP) retrieved a 114 m long sediment core dedicated for geomicrobiological investigations from a water depth of 153 m, well below the depth of oxygen penetration at the time of sampling. Samples collected from these sediment cores form the fundament of this thesis and were used to perform a suite of biogeochemical and microbiological analyses.
Geomirobiological investigations depend on uncontaminated samples. However, exploration of subsurface environments relies on drilling, which requires the use of a drilling fluid. Drilling fluid infiltration during drilling can not be avoided. Thus, in order to trace contamination of the sediment core and to identify uncontaminated samples for further analyses a simple and inexpensive technique for assessing contamination during drilling operations was developed and applied during the ICDP drilling campaign. This approach uses an aqeous fluorescent pigment dispersion commonly used in the paint industry as a particulate tracer. It has the same physical properties as conventionally used particulate tracers. However, the price is nearly four orders of magnitude lower solving the main problem of particulate tracer approaches. The approach requires only a minimum of equipment and allows for a rapid contamination assessment potentially even directly on site, while the senstitivity is in the range of already established approaches. Contaminated samples in the drill core were identified and not included for further geomicrobiological investigations.
Biogeochemical analyses of short sediment cores showed that Lake Towutis sediments are strongly depleted in electron acceptors commonly used in microbial organic matter mineralization (i.e. oxygen, nitrate, sulfate). Still, the sediments harbor high microbial cell densities, which are a function of redox conditions of Lake Towuti’s bottom water. In shallow water depths bottom water oxygenation leads to a higher input of labile organic matter and electron acceptors like sulfate and iron, which promotes a higher microbial abundance. Microbial analyses showed that a versatile microbial community with a potential to perform metabolisms related to iron and sulfate reduction, fermentation as well as methanogenesis inhabits Lake Towuti’s surface sediments.
Biogeochemical investigations of the upper 12 m of the 114 m sediment core showed that Lake Towuti’s sediment is extremely rich in iron with total concentrations up to 2500 µmol cm-3 (20 wt. %), which makes it the natural sedimentary environment with the highest total iron concentrations studied to date. In the complete or near absence of oxygen, nitrate and sulfate, organic matter mineralization in ferruginous sediments would be expected to proceed anaerobically via the energetically most favorable terminal electron acceptors available - in this case ferric iron. Astonishingly, however, methanogenesis is the dominant (>85 %) organic matter mineralization process in Lake Towuti’s sediment. Reactive ferric iron known to be available for microbial iron reduction is highly abundant throughout the upper 12 m and thus remained stable for at least 60.000 years. The produced methane is not oxidized anaerobically and diffuses out of the sediment into the water column. The proclivity towards methanogenesis, in these very iron-rich modern sediments, implies that methanogenesis may have played a more important role in organic matter mineralization thoughout the Precambrian than previously thought and thus could have been a key contributor to Earth’s early climate dynamics.
Over the whole sequence of the 114 m long sediment core siderites were identified and characterized using high-resolution microscopic and spectroscopic imaging together with microchemical and geochemical analyses. The data show early diagenetic growth of siderite crystals as a response to sedimentary organic matter mineralization. Microchemical zoning was identified in all siderite crystals. Siderite thus likely forms during diagenesis through growth on primary existing phases and the mineralogical and chemical features of these siderites are a function of changes in redox conditions of the pore water and sediment over time. Identification of microchemical zoning in ancient siderites deposited in the Precambrian may thus also be used to infer siderite growth histories in ancient sedimentary rocks including sedimentary iron formations.
From self-help books and nootropics, to self-tracking and home health tests, to the tinkering with technology and biological particles – biohacking brings biology, medicine, and the material foundation of life into the sphere of »do-it-yourself«. This trend has the potential to fundamentally change people's relationship with their bodies and biology but it also creates new cultural narratives of responsibility, authority, and differentiation. Covering a broad range of examples, this book explores practices and representations of biohacking in popular culture, discussing their ambiguous position between empowerment and requirement, promise and prescription.
The goal of regenerative medicine is to guide biological systems towards natural healing outcomes using a combination of niche-specific cells, bioactive molecules and biomaterials. In this regard, mimicking the extracellular matrix (ECM) surrounding cells and tissues in vivo is an effective strategy to modulate cell behaviors. Cellular function and phenotype is directed by the biochemical and biophysical signals present in the complex 3D network of ECMs composed mainly of glycoproteins and hydrophilic proteoglycans. While cellular modulation in response to biophysical cues emulating ECM features has been investigated widely, the influence of biochemical display of ECM glycoproteins mimicking their presentation in vivo is not well characterized. It remains a significant challenge to build artificial biointerfaces using ECM glycoproteins that precisely match their presentation in nature in terms of morphology, orientation and conformation. This challenge becomes clear, when one understands how ECM glycoproteins self-assemble in the body. Glycoproteins produced inside the cell are secreted in the extra-cellular space, where they are bound to the cell membrane or other glycoproteins by specific interactions. This leads to elevated local concentration and 2Dspatial confinement, resulting in self-assembly by the reciprocal interactions arising from the molecular complementarity encoded in the glycoprotein domains. In this thesis, air-water (A-W) interface is presented as a suitable platform, where self-assembly parameters of ECM glycoproteins such as pH, temperature and ionic strength can be controlled to simulate in vivo conditions (Langmuir technique), resulting in the formation of glycoprotein layers with defined characteristics. The layer can be further compressed with surface barriers to enhance glycoprotein-glycoprotein contacts and defined layers of glycoproteins can be immobilized on substrates by horizontal lift and touch method, called Langmuir-Schäfer (LS) method. Here, the benefit of Langmuir and LS methods in achieving ECM glycoprotein biointerfaces with controlled network morphology and ligand density on substrates is highlighted and contrasted with the commonly used (glyco)protein solution deposition (SO) method on substrates. In general, the (glyco)protein layer formation by SO is rather uncontrolled, influenced strongly by (glyco)protein-substrate interactions and it results in multilayers and aggregations on substrates, while the LS method results in (glyco)proteins layers with a more homogenous presentation. To achieve the goal of realizing defined ECM layers on substrates, ECM glycoproteins having the ability to self-assemble were selected: Collagen-IV (Col-IV) and fibronectin (FN). Highly packed FN layer with uniform presentation of ligands was deposited on polydimethysiloxane VIII (PDMS) by LS method, while a heterogeneous layer was formed on PDMS by SO with prominent aggregations visible. Mesenchymal stem cells (MSC) on PDMS equipped with FN by LS exhibited more homogeneous and elevated vinculin expression and weaker stress fiber formation than on PDMS equipped with FN by SO and these divergent responses could be attributed to the differences in glycoprotein presentation at the interface. Col-IV are scaffolding components of specialized ECM called basement membranes (BM), and have the propensity to form 2D networks by self-polymerization associated with cells. Col- IV behaves as a thin-disordered network at the A-W interface. As the Col-IV layer was compressed at the A-W interface using trough barriers, there was negligible change in thickness (layer thickness ~ 50 nm) or orientation of molecules. The pre-formed organization of Col-IV was transferred by LS method in a controlled fashion onto substrates meeting the wettability criterion (CA ≤ 80°). MSC adhesion (24h) on PET substrates deposited with Col-IV LS films at 10, 15 and 20 mN·m-1 surface pressures was (12269.0 ± 5856.4) cells for LS10, (16744.2 ± 1280.1) cells for LS15 and (19688.3 ± 1934.0) cells for LS20 respectively. Remarkably, by selecting the surface areal density of Col-IV on the Langmuir trough on PET, there is a linear increase between the number of adherent MSCs and the Col-IV ligand density. Further, FN has the ability to self-stabilize and form 2D networks (even without compression) while preserving native β-sheet structure at the A-W interface on a defined subphase (pH = 2). This provides the possibility to form such layers on any vessel (even on standard six-well culture plates) and the cohesive FN layers can be deposited by LS transfer, without the need for expensive LB instrumentation. Multilayers of FN can be immobilized on substrates by this approach, as easily as Layer-by-Layer method, even without the need for secondary adlayer or activated bare substrate. Thus, this facile glycoprotein coating strategy approach is accessible to many researchers to realize defined FN films on substrates for cell culture. In conclusion, Langmuir and LS methods can create biomimetic glycoprotein biointerfaces on substrates controlling aspects of presentation such as network morphology and ligand density. These methods will be utilized to produce artificial BM mimics and interstitial ECM mimics composed of more than one ECM glycoprotein layer on substrates, serving as artificial niches instructing stem cells for cell-replacement therapies in the future.
Some of the most frequent questions surrounding business negotiations address not only the nature of such negotiations, but also how they should be conducted. The answers given by business people from different cultural backgrounds to these questions are likely to differ from the standard answers found in business manuals.
In her book, Milene Mendes de Oliveira investigates how Brazilian and German business people conceptualize and act out business negotiations using English as a Lingua Franca. The frameworks of Cultural Linguistics, English as a Lingua Franca, World Englishes, and Business Discourse offer the theoretical and methodological grounding for the analysis of interviews with high-ranking Brazilian and German business people. Moreover, a side study on e-mail exchanges between Brazilian and German employees of a healthcare company serves as a test case for the results arising from the interviews, and helps understand other facets of authentic intercultural business communication.
Offering new insights on English as a Lingua Franca in international business contexts, Business Negotiations in ELF from a Cultural Linguistic Perspective simultaneously provides a detailed cultural-conceptual account of business negotiations from the viewpoint of Brazilian and German business people and a secondary analysis of their pragmatic aspects.
Carbonates play a key role in the chemistry and dynamics of our planet. They are directly connected to the CO2 budget of our atmosphere and have a great impact on the deep carbon cycle. Moreover, recent studies have shown that carbonates are stable along the geothermal gradient down to Earth's lower mantle conditions, changing their crystal structure and related properties. Subducted carbonates may also react with silicates to form new phases. These reactions will redistribute elements, such as calcium (Ca), magnesium (Mg), iron (Fe) and carbon in the form of carbon dioxide (CO2), but also trace elements, that are carried by the carbonates. The trace elements of most interest are strontium (Sr) and rare earth elements (REE) which have been found to be important constituents in the composition of the primitive lower mantle and in mineral inclusions found in super-deep diamonds. However, the stability of carbonates in presence of mantle silicates at relevant temperatures is far from being well understood. Related to this, very little is known about distribution processes of trace elements between carbonates and mantle silicates. To shed light on these processes, we studied reactions between Sr- and REE-containing CaCO3 and Mg/Fe-bearing silicates of the system (Mg,Fe)2SiO4 - (Mg,Fe)SiO3 at high pressure and high temperature using synchrotron radiation based μ-X-ray diffraction (μ-XRD) and μ-X-ray fluorescence (μ-XRF) with μm-resolution in a laser-heated diamond anvil cell. X-ray diffraction is used to derive the structural changes of the phase reactions whereas X-ray fluorescence gives information on the chemical changes in the sample. In-situ experiments at high pressure and high temperature were performed at beamline P02.2 at PETRA III (Hamburg, Germany) and at beamline ID27 at ESRF (Grenoble, France). In addition to μ-XRD and μ-XRF, ex-situ measurements were made on the recovered sample material using transmission electron microscopy (TEM) and provided further insights into the reaction kinetics of carbonate-silicate reactions.
Our investigations show that CaCO3 is unstable in presence of mantle silicates above 1700 K and a reaction takes place in which magnesite plus CaSiO3-perovskite are formed. In addition, we observed that a high content of iron in the carbonate-silicate system favours dolomite formation during the reaction. The subduction of natural carbonates with significant amounts of Sr leads to a comprehensive investigation of the stability not only of CaCO3 phases in contact with mantle silicates but also of SrCO3 (and of Sr-bearing CaCO3). We found that SrCO3 reacts with (Mg,Fe)SiO3-perovskite to form magnesite and gained evidence for the formation of SrSiO3-perovskite.
To complement our study on the stability of SrCO3 at conditions of the Earth's lower mantle, we performed powder X-ray diffraction and single crystal X-ray diffraction experiments at ambient temperature and up to 49 GPa. We observed a transformation from SrCO3-I into a new high-pressure phase SrCO3-II at around 26 GPa with Pmmn crystal structure and a bulk modulus of 103(10) GPa. This information is essential to fully understand the phase behaviour and stability of carbonates in the Earth's lower mantle and to elucidate the possibility of introducing Sr into mantle silicates by carbonate-silicate reactions.
Simultaneous recording of μ-XRD and μ-XRF in the μm-range over the heated areas provides spatial information not only about phase reactions but also on the elemental redistribution during the reactions. A comparison of the spatial intensity distribution of the XRF signal before and after heating indicates a change in the elemental distribution of Sr and an increase in Sr-concentration was found around the newly formed SrSiO3-perovskite. With the help of additional TEM analyses on the quenched sample material the elemental redistribution was studied at a sub-micrometer scale. Contrary to expectations from combined μ-XRD and μ-XRF measurements, we found that La and Eu were not incorporated into the silicate phases, instead they tend to form either isolated oxide phases (e.g. Eu2O3, La2O3) or hydroxyl-bastnäsite (La(CO3)(OH)). In addition, we observed the transformation from (Mg,Fe)SiO3-perovskite to low-pressure clinoenstatite during pressure release. The monoclinic structure (P21/c) of this phase allows the incorporation of Ca as shown by additional EDX analyses and, to a minor extent, Sr too.
Based on our experiments, we can conclude that a detection of the trace elements in-situ at high pressure and high temperature remains challenging. However, our first findings imply that silicates may incorporate the trace elements provided by the carbonates and indicate that carbonates may have a major effect on the trace element contents of mantle phases.
The significant environmental and socioeconomic consequences of hydrometeorological extreme events, such as extreme rainfall, are constituted as a most important motivation for analyzing these events in the south-central Andes of NW Argentina. The steep topographic and climatic gradients and their interactions frequently lead to the formation of deep convective storms and consequently trigger extreme rainfall generation.
In this dissertation, I focus on identifying the dominant climatic variables and atmospheric conditions and their spatiotemporal variability leading to deep convection and extreme rainfall in the south-central Andes.
This dissertation first examines the significant contribution of temperature on atmospheric humidity (dew-point temperature, Td) and on convection (convective available potential energy, CAPE) for deep convective storms and hence, extreme rainfall along the topographic and climatic gradients. It was found that both climatic variables play an important role in extreme rainfall generation. However, their contributions differ depending on topographic and climatic sub-regions, as well as rainfall percentiles.
Second, this dissertation explores if (near real-time) the measurements conducted by the Global Navigation Satellite System (GNSS) on integrated water vapor (IWV) provide reliable data for explaining atmospheric humidity. I argue that GNSS-IWV, in conjunction with other atmospheric stability parameters such as CAPE, is able to decipher the extreme rainfall in the eastern central Andes. In my work, I rely on a multivariable regression analysis described by a theoretical relationship and fitting function analysis.
Third, this dissertation identifies the local impact of convection on extreme rainfall in the eastern Andes. Relying on a Principal Component Analysis (PCA) it was found that during the existence of moist and warm air, extreme rainfall is observed more often during local night hours. The analysis includes the mechanisms for this observation.
Exploring the atmospheric conditions and climatic variables leading to extreme rainfall is one of the main findings of this dissertation. The conditions and variables are a prerequisite for understanding the dynamics of extreme rainfall and predicting these events in the eastern Andes.
Cleft exhaustivity
(2020)
In this dissertation a series of experimental studies are presented which demonstrate that the exhaustive inference of focus-background it-clefts in English and their cross-linguistic counterparts in Akan, French, and German is neither robust nor systematic. The inter-speaker and cross-linguistic variability is accounted for with a discourse-pragmatic approach to cleft exhaustivity, in which -- following Pollard & Yasavul 2016 -- the exhaustive inference is derived from an interaction with another layer of meaning, namely, the existence presupposition encoded in clefts.
Completely water-based systems are of interest for the development of novel material for various reasons: On one hand, they provide benign environment for biological systems and on the other hand they facilitate effective molecular transport in a membrane-free environment. In order to investigate the general potential of aqueous two-phase systems (ATPSs) for biomaterials and compartmentalized systems, various solid particles were applied to stabilize all-aqueous emulsion droplets. The target ATPS to be investigated should be prepared via mixing of two aqueous solutions of water-soluble polymers, which turn biphasic when exceeding a critical polymer concentration. Hydrophilic polymers with a wide range of molar mass such as dextran/poly(ethylene glycol) (PEG) can therefore be applied. Solid particles adsorbed at the interfaces can be exceptionally efficient stabilizers forming so-called Pickering emulsions, and nanoparticles can bridge the correlation length of polymer solutions and are thereby the best option for water-in-water emulsions.
The first approach towards the investigation of ATPS was conducted with all aqueous dextran-PEG emulsions in the presence of poly(dopamine) particles (PDP) in Chapter 4. The water-in-water emulsions were formed with a PEG/dextran system via utilizing PDP as stabilizers. Studies of the formed emulsions were performed via laser scanning confocal microscope (CLSM), optical microscope (OM), cryo-scanning electron microscope (SEM) and tensiometry. The stable emulsions (at least 16 weeks) were demulsified easily via dilution or surfactant addition. Furthermore, the solid PDP at the water-water interface were crosslinked in order to inhibit demulsification of the Pickering emulsion. Transmission electron microscope (TEM) and scanning electron microscope (SEM) were used to visualize the morphology of PDP before and after crosslinking. PDP stabilized water-in-water emulsions were utilized in the following Chapter 5 to form supramolecular compartmentalized hydrogels. Here, hydrogels were prepared in pre-formed water-in-water emulsions and gelled via α-cyclodextrin-PEG (α-CD-PEG) inclusion complex formation. Studies of the formed complexes were performed via X-ray powder diffraction (XRD) and the mechanical properties of the hydrogels were measured with oscillatory shear rheology. In order to verify the compartmentalized state and its triggered decomposition, hydrogels and emulsions were assessed via OM, SEM and CLSM. The last chapter broadens the investigations from the previous two systems by utilizing various carbon nitrides (CN) as different stabilizers in ATPS. CN introduces another way to trigger demulsification, namely irradiation with visible light. Therefore, emulsification and demulsification with various triggers were probed. The investigated all aqueous multi-phase systems will act as model for future fabrication of biocompatible materials, cell micropatterning as well as separation of compartmentalized systems.
The earth’s ecosystems undergo considerable changes characterized by human-induced alterations of environmental factors. In order to develop conservation goals for vulnerable ecosystems, research on ecosystem functioning is required.. Therefore, it is crucial to explore organismal interactions, such as trophic interaction or competition, which are decisive for key processes in ecosystems. These interactions are determined by the performance responses of organisms to environmental changes, which in turn, are shaped by the organism’s functional traits. Exploring traits, their variation, and the environmental factors that act on them may provide insights on how ecological interactions affect
populations, community structures and dynamics, and thus ecosystem
functioning. In aquatic ecosystems, global warming intensifies
phytoplankton blooms, which are more frequently dominated by
cyanobacteria. As cyanobacteria are poor in polyunsaturated fatty acids
(PUFA) and sterols, this compositional change alters the biochemical
food quality of phytoplankton for consumer species with potential
effects on ecological interactions. Within this thesis, I studied the
effects of biochemical food quality on consumer traits and performance responses at the phytoplankton-zooplankton interface using different strains of two closely related generalist rotifer species Brachionus calyciflorus and Brachionus fernandoi and three phytoplankton species that differ in their biochemical food quality, i.e. in their content and composition of PUFA and sterols. In a series of laboratory feeding experiments I found that biochemical food quality affected rotifer’s performance, i.e. fecundity, survival, and population growth, across a broad range of food quantities. Biochemical food quality constraints,
which are often underestimated as influencing environmental factors, had strong impacts on performance responses. I further explored the potential of biochemical food quality in mediating consumer response variation between species and among strains of one species. Co-limitation by food quantity and biochemical food quality resulted in differences in performance responses, which were more pronounced within than between rotifer species. Furthermore, I demonstrated that the body PUFA compositions of rotifer species and strains were differently affected by the dietary PUFA supply, which indicates inter- and intraspecific differences in physiological traits, such as PUFA retention, allocation, and/or bioconversion capacity, within the genus Brachionus. This indicates that dietary PUFA are involved in shaping traits and performance responses of rotifers. This thesis reveals that biochemical food quality is an environmental factor with strong effects on individual traits and performance responses of consumers. Biochemical food quality constraints can further mediate trait and response variation among species or strains. Consequently, they carry the potential to shape ecological interactions and evolutionary processes with effects on community structures and dynamics. Trait-based approaches, which include food quality research, thus may provide further insights into the linkage between functional diversity and the maintenance of crucial ecosystem functions.
In the present study, we employ the angle-resolved photoemission spectroscopy (ARPES) technique to study the electronic structure of topological states of matter. In particular, the so-called topological crystalline insulators (TCIs) Pb1-xSnxSe and Pb1-xSnxTe, and the Mn-doped Z2 topological insulators (TIs) Bi2Te3 and Bi2Se3. The Z2 class of strong topological insulators is protected by time-reversal symmetry and is characterized by an odd number of metallic Dirac type surface states in the surface Brillouin zone. The topological crystalline insulators on the other hand are protected by the individual crystal symmetries and exhibit an even number of Dirac cones.
The topological properties of the lead tin chalcogenides topological crystalline insulators can be tuned by temperature and composition. Here, we demonstrate that Bi-doping of the Pb1-xSnxSe(111) epilayers induces a quantum phase transition from a topological crystalline insulator to a Z2 topological insulator. This occurs because Bi-doping lifts the fourfold valley degeneracy in the bulk. As a consequence a gap appears at ⌈¯, while the three Dirac cones at the M̅ points of the surface Brillouin zone remain intact. We interpret this new phase transition is caused by lattice distortion. Our findings extend the topological phase diagram enormously and make strong topological insulators switchable by distortions or electric field. In contrast, the bulk Bi doping of epitaxial Pb1-xSnxTe(111) films induces a giant Rashba splitting at the surface that can be tuned by the doping level. Tight binding calculations identify their origin as Fermi level pinning by trap states at the surface.
Magnetically doped topological insulators enable the quantum anomalous Hall effect (QAHE) which provide quantized edge states for lossless charge transport applications. The edge states are hosted by a magnetic energy gap at the Dirac point which has not been experimentally observed to date. Our low temperature ARPES studies unambiguously reveal the magnetic gap of Mn-doped Bi2Te3. Our analysis shows a five times larger gap size below the Tc than theoretically predicted. We assign this enhancement to a remarkable structure modification induced by Mn doping. Instead of a disordered impurity system, a self-organized alternating sequence of MnBi2Te4 septuple and Bi2Te3quintuple layers is formed. This enhances the wave-function overlap and gives rise to a large magnetic gap. Mn-doped Bi2Se3 forms similar heterostructure, but only a nonmagnetic gap is observed in this system. This correlates with the difference in magnetic anisotropy due to the much larger spin-orbit interaction in Bi2Te3 compared to Bi2Se3. These findings provide crucial insights for pushing lossless transport in topological insulators towards room-temperature applications.
The Andean Plateau (Altiplano-Puna Plateau) of the southern Central Andes is the second-highest orogenic plateau on our planet after Tibet. The Andean Plateau and its foreland exhibit a pronounced segmentation from north to south regarding the style and magnitude of deformation. In the Altiplano (northern segment), more than 300 km of tectonic shortening has been recorded, which started during the Eocene. A well-developed thin-skinned thrust wedge located at the eastern flank of the plateau (Subandes) indicates a simple-shear shortening mode. In contrast, the Puna (southern segment) records approximately half of the shortening of the Altiplano - and the shortening started later. The tectonic style in the Puna foreland switches to a thick-skinned mode, which is related to pure-shear shortening. In this study, carried out in the framework of the StRATEGy project, high-resolution 2D thermomechanical models were developed to systematically investigate controls of deformation patterns in the orogen-foreland pair. The 2D and 3D models were subsequently applied to study the evolution of foreland deformation and surface topography in the Altiplano-Puna Plateau. The models demonstrate that three principal factors control the foreland-deformation patterns: (i) strength differences in the upper lithosphere between the orogen and its foreland, rather than a strength difference in the entire lithosphere; (ii) gravitational potential energy of the orogen (GPE) controlled by crustal and lithospheric thicknesses, and (iii) the strength and thickness of foreland-basin sediments. The high-resolution 2D models are constrained by observations and successfully reproduce deformation structures and surface topography of different segments of the Altiplano-Puna plateau and its foreland. The developed 3D models confirm these results and suggest that a relatively high shortening rate in the Altiplano foreland (Subandean foreland fold-and-thrust belt) is due to simple-shear shortening facilitated by thick and mechanically weak sediments, a process which requires a much lower driving force than the pure-shear shortening deformation mode in the adjacent broken foreland of the Puna, where these thick sedimentary basin fills are absent. Lower shortening rate in the Puna foreland is likely accommodated in the forearc by the slab retreat.
Unlike today’s prevailing terrestrial features, the geologic past of Central Asia witnessed marine environments and conditions as well. A vast, shallow sea, known as proto-Paratethys, extended across Eurasia from the Mediterranean Tethys to the Tarim Basin in western China during Cretaceous to Paleogene times. This sea formed about 160 million years ago (during Jurassic times) when the waters of the Tethys Ocean flooded into Eurasia. It drastically retreated to the west and became isolated as the Paratethys during the Late Eocene-Oligocene (ca. 34 Ma).
Having well-constrained timing and paleogeography for the Cretaceous-Paleogene proto-Paratethys sea incursions in Central Asia is essential to properly understand and distinguish the controlling mechanisms and their link to Asian paleoenvironmental and paleoclimatic change. The Cretaceous-Paleogene tectonic evolution of the Pamir and Tibet and their far-field effects play a significant role on the sedimentological and structural evolution of the Central Asian basins and on the evolution of the proto-Paratethys sea fluctuations as well. Comparing the records of the sea incursions to the tectonic and eustatic events has paramount importance to reveal the controlling mechanisms behind the sea incursions. However, due to inaccuracies in the dating of rocks (mostly continental rocks and marine rocks with benthic microfossils providing low-resolution biostratigraphic constraints) and conflicting results, there has been no consensus on the timing of the sea incursions and interpretation of their records has been in question. Here, we present a new chronostratigraphic framework based on biostratigraphy and magnetostratigraphy as well as a detailed paleoenvironmental analysis for the Cretaceous and Paleogene proto-Paratethys Sea incursions in the Tajik and Tarim basins, in Central Asia. This enables us to identify the major drivers of marine fluctuations and their potential consequences on regional and global climate, particularly Asian aridification and the global carbon cycle perturbations such as the Paleocene-Eocene Thermal Maximum (PETM). To estimate the paleogeographic evolution of the proto-Paratethys Sea, the refined age constraints and detailed paleoenvironmental interpretations are combined with successive paleogeographic maps. Regional coastlines and depositional environments during the Cretaceous-Paleogene sea advances and retreats were drawn based on the results of this thesis and integrated with existing literature to generate new paleogeographic maps.
Before its final westward retreat in the Eocene, a total of six Cretaceous and Paleogene major sea incursions have been distinguished from the sedimentary records of the Tajik and Tarim basins in Central Asia. All have been studied and documented here.
We identify the presence of marine conditions already in the Early Cretaceous in the western Tajik Basin, followed by the Cenomanian (ca. 100 Ma) and Santonian (ca. 86 Ma) major marine incursions far into the eastern Tajik and Tarim basins separated by a Turonian-Coniacian (ca. 92-86 Ma) regression. Basin-wide tectonic subsidence analyses imply that the Early Cretaceous invasion of the sea into the Tajik Basin is related to increased Pamir tectonism (at ca. 130 – 90 Ma) in a retro-arc basin setting inferred to be linked to collision and subduction. This tectonic event mainly governed the Cenomanian (ca. 100 Ma) sea incursion in conjunction with a coeval global eustatic high resulting in the maximum geographic extent of the sea. The following Turonian-Coniacian (ca. 92-86 Ma) major regression, driven by eustasy, coincides with a sharp slowdown in tectonic subsidence related to a regime change in Pamir tectonism from compression to extension. The Santonian (ca. 86 Ma) major sea incursion was more likely controlled dominantly by eustasy as also evidenced by the coeval fluctuations in the west Siberian Basin. During the early Maastrichtian, the global Late Cretaceous cooling is inferred from the disappearance of mollusk-rich limestones and the dominance of bryozoan-rich and echinoderm-rich limestones in the Tajik Basin documenting the first evidence for the Late Cretaceous cooling event in Central Asia.
Following the last Cretaceous sea incursion, a major regional restriction event, marked by the exceptionally thick (≤ 400 m) shelf evaporites is assigned a Danian-Selandian age (ca. 63-59 Ma). This is followed by the largest recorded proto-Paratethys sea incursion with a transgression estimated as early Thanetian (ca. 59-57 Ma) and a regression within the Ypresian (ca. 53-52 Ma). The transgression of the next incursion is now constrained as early Lutetian (ca. 47-46 Ma), whereas its regression is constrained as late Lutetian (ca. 41 Ma) and is associated with a drastic increase in both tectonic subsidence and basin infilling. The age of the final and least pronounced sea incursion restricted to the westernmost margin of the Tarim Basin is assigned as Bartonian–Priabonian (ca. 39.7-36.7 Ma). We interpret the long-term westward retreat of the proto-Paratethys Sea starting at ca. 41 Ma to be associated with far-field tectonic effects of the Indo-Asia collision and Pamir/Tibetan plateau uplift. Short-term eustatic sea level transgressions are superimposed on this long-term regression and seem coeval with the transgression events in the other northern Peri-Tethyan sedimentary provinces for the 1st and 2nd Paleogene sea incursions. However, the last Paleogene sea incursion is interpreted as related to tectonism. The transgressive and regressive intervals of the proto-Paratethys Sea correlate well with the reported humid and arid phases, respectively in the Qaidam and Xining basins, thus demonstrating the role of the proto-Paratethys Sea as an important moisture source for the Asian interior and its regression as a contributor to Asian aridification.
We lastly study the mechanics, relative contribution and preservation efficiency of ancient epicontinental seas as carbon sinks with new and existing data, using organic rich (sapropel) deposits dated to the PETM from the extensive epicontinental proto-Paratethys and West Siberian seas. We estimate ca. 1390±230 Gt organic C burial, a substantial amount compared to previously estimated global total excess organic C burial (ca. 1700-2900 Gt) is focused in the proto-Paratethys and West Siberian seas alone. We also speculate that enhanced organic carbon burial later over much of the proto-Paratethys (and later Paratethys) basin (during the deposition of the Kuma Formation and Maikop series, repectively) may have majorly contributed to drawdown of atmospheric carbon dioxide before and during the EOT cooling and glaciation of Antarctica. For past periods with smaller epicontinental seas, the effectiveness of this negative carbon cycle feedback was arguably diminished, and the same likely applies to the present-day.
Successfully completing any data science project demands careful consideration across its whole process. Although the focus is often put on later phases of the process, in practice, experts spend more time in earlier phases, preparing data, to make them consistent with the systems' requirements or to improve their models' accuracies. Duplicate detection is typically applied during the data cleaning phase, which is dedicated to removing data inconsistencies and improving the overall quality and usability of data. While data cleaning involves a plethora of approaches to perform specific operations, such as schema alignment and data normalization, the task of detecting and removing duplicate records is particularly challenging. Duplicates arise when multiple records representing the same entities exist in a database. Due to numerous reasons, spanning from simple typographical errors to different schemas and formats of integrated databases. Keeping a database free of duplicates is crucial for most use-cases, as their existence causes false negatives and false positives when matching queries against it. These two data quality issues have negative implications for tasks, such as hotel booking, where users may erroneously select a wrong hotel, or parcel delivery, where a parcel can get delivered to the wrong address. Identifying the variety of possible data issues to eliminate duplicates demands sophisticated approaches.
While research in duplicate detection is well-established and covers different aspects of both efficiency and effectiveness, our work in this thesis focuses on the latter. We propose novel approaches to improve data quality before duplicate detection takes place and apply the latter in datasets even when prior labeling is not available. Our experiments show that improving data quality upfront can increase duplicate classification results by up to 19%. To this end, we propose two novel pipelines that select and apply generic as well as address-specific data preparation steps with the purpose of maximizing the success of duplicate detection. Generic data preparation, such as the removal of special characters, can be applied to any relation with alphanumeric attributes. When applied, data preparation steps are selected only for attributes where there are positive effects on pair similarities, which indirectly affect classification, or on classification directly. Our work on addresses is twofold; first, we consider more domain-specific approaches to improve the quality of values, and, second, we experiment with known and modified versions of similarity measures to select the most appropriate per address attribute, e.g., city or country.
To facilitate duplicate detection in applications where gold standard annotations are not available and obtaining them is not possible or too expensive, we propose MDedup. MDedup is a novel, rule-based, and fully automatic duplicate detection approach that is based on matching dependencies. These dependencies can be used to detect duplicates and can be discovered using state-of-the-art algorithms efficiently and without any prior labeling. MDedup uses two pipelines to first train on datasets with known labels, learning to identify useful matching dependencies, and then be applied on unseen datasets, regardless of any existing gold standard. Finally, our work is accompanied by open source code to enable repeatability of our research results and application of our approaches to other datasets.
This work presents a new design for programming environments that promote the exploration of domain-specific software artifacts and the construction of graphical tools for such program comprehension tasks. In complex software projects, tool building is essential because domain- or task-specific tools can support decision making by representing concerns concisely with low cognitive effort. In contrast, generic tools can only support anticipated scenarios, which usually align with programming language concepts or well-known project domains.
However, the creation and modification of interactive tools is expensive because the glue that connects data to graphics is hard to find, change, and test. Even if valuable data is available in a common format and even if promising visualizations could be populated, programmers have to invest many resources to make changes in the programming environment. Consequently, only ideas of predictably high value will be implemented. In the non-graphical, command-line world, the situation looks different and inspiring: programmers can easily build their own tools as shell scripts by configuring and combining filter programs to process data.
We propose a new perspective on graphical tools and provide a concept to build and modify such tools with a focus on high quality, low effort, and continuous adaptability. That is, (1) we propose an object-oriented, data-driven, declarative scripting language that reduces the amount of and governs the effects of glue code for view-model specifications, and (2) we propose a scalable UI-design language that promotes short feedback loops in an interactive, graphical environment such as Morphic known from Self or Squeak/Smalltalk systems.
We implemented our concept as a tool building environment, which we call VIVIDE, on top of Squeak/Smalltalk and Morphic. We replaced existing code browsing and debugging tools to iterate within our solution more quickly. In several case studies with undergraduate and graduate students, we observed that VIVIDE can be applied to many domains such as live language development, source-code versioning, modular code browsing, and multi-language debugging. Then, we designed a controlled experiment to measure the effect on the time to build tools. Several pilot runs showed that training is crucial and, presumably, takes days or weeks, which implies a need for further research.
As a result, programmers as users can directly work with tangible representations of their software artifacts in the VIVIDE environment. Tool builders can write domain-specific scripts to populate views to approach comprehension tasks from different angles. Our novel perspective on graphical tools can inspire the creation of new trade-offs in modularity for both data providers and view designers.
The development of methods such as super-resolution microscopy (Nobel prize in Chemistry, 2014) and multi-scale computer modelling (Nobel prize in Chemistry, 2013) have provided scientists with powerful tools to study microscopic systems. Sub-micron particles or even fluorescently labelled single molecules can now be tracked for long times in a variety of systems such as living cells, biological membranes, colloidal solutions etc. at spatial and temporal resolutions previously inaccessible. Parallel to such single-particle tracking experiments, super-computing techniques enable simulations of large atomistic or coarse-grained systems such as biologically relevant membranes or proteins from picoseconds to seconds, generating large volume of data. These have led to an unprecedented rise in the number of reported cases of anomalous diffusion wherein the characteristic features of Brownian motion—namely linear growth of the mean squared displacement with time and the Gaussian form of the probability density function (PDF) to find a particle at a given position at some fixed time—are routinely violated. This presents a big challenge in identifying the underlying stochastic process and also estimating the corresponding parameters of the process to completely describe the observed behaviour. Finding the correct physical mechanism which leads to the observed dynamics is of paramount importance, for example, to understand the first-arrival time of transcription factors which govern gene regulation, or the survival probability of a pathogen in a biological cell post drug administration. Statistical Physics provides useful methods that can be applied to extract such vital information. This cumulative dissertation, based on five publications, focuses on the development, implementation and application of such tools with special emphasis on Bayesian inference and large deviation theory. Together with the implementation of Bayesian model comparison and parameter estimation methods for models of diffusion, complementary tools are developed based on different observables and large deviation theory to classify stochastic processes and gather pivotal information. Bayesian analysis of the data of micron-sized particles traced in mucin hydrogels at different pH conditions unveiled several interesting features and we gained insights into, for example, how in going from basic to acidic pH, the hydrogel becomes more heterogeneous and phase separation can set in, leading to observed non-ergodicity (non-equivalence of time and ensemble averages) and non-Gaussian PDF. With large deviation theory based analysis we could detect, for instance, non-Gaussianity in seeming Brownian diffusion of beads in aqueous solution, anisotropic motion of the beads in mucin at neutral pH conditions, and short-time correlations in climate data. Thus through the application of the developed methods to biological and meteorological datasets crucial information is garnered about the underlying stochastic processes and significant insights are obtained in understanding the physical nature of these systems.
Metal halide perovskites have merged as an attractive class of materials for photovoltaic applications due to their excellent optoelectronic properties. However, the long term stability is a roadblock for this class of material’s industrial pathway. Increasing evidence shows that intrinsic defects in perovskite promote material degradation. Consequently, understanding defect behaviours in perovskite materials is essential to further improve device stability and performance. This dissertation, hence, focuses on the topic of defect chemistry in halide perovskites.
The first part of the dissertation gives a brief overview of the defect properties in halide perovskite. Subsequently, the second part shows that doping methylammonium lead iodide with a small amount of alkaline earth metals (Sr and Mg) creates a higher quality, less defective material resulted in high open circuit voltages in both n-i-p and p-i-n architecture. It has been found that the mechanism of doping has two distinct regimes in which a low doping concentration enables the inclusion of the dopants into the lattice whereas higher doping concentrations lead to phase segregation. The material can be more n-doped in the low doping regime while being less n-doped in the high doping regime. The threshold of these two regimes is based on the atomic size of the dopants.
The next part of the dissertation examines the photo-induced degradation in methylammonium lead iodide. This degradation mechanism links closely to the formation and migration of ionic defects. After they are formed, these ionic defects can migrate, however, not freely depending on the defect concentration and their distribution. In fact, a highly concentrated defect region such as the grain boundaries can inhibit the migration of ionic defects. This has implications for material design as perovskite solar cells normally employ a polycrystalline thin-film which has a high density of grain boundary.
The final study presented in this PhD dissertation focuses on the stability of the state-of-the-art triple cation perovskite-based solar devices under external bias. Prolonged bias (more than three hours) is found to promote amorphization in halide perovskite. The amorphous phase is suspected to accumulate at the interfaces especially between the hole selective layer and perovskite. This amorphous phase inhibits the charge collection and severely affects the device performance. Nonetheless, the devices can recover after resting without bias in the dark. This amorphization is attributed to ionic defect migration most likely halides. This provides a new understanding of the potential degradation mechanisms in perovskite solar cells under operational conditions.
In recent years people have realised non-renewability of our modern society which relays on spending huge amounts of energy mostly produced from fosil fuels, such as oil and coal, and the shift towards more sustainable energy sources has started. However, sustainable sources of energy, such as wind-, solar- and hydro-energy, produce primarily electrical energy and can not just be poured in canister like many fosil fuels, creating necessity for rechragable batteries. However, modern Li-ion batteries are made from toxic heavy metals and sustainable alternatives are needed. Here we show that naturally abundant catecholic and guaiacyl groups can be utilised to replace heavy metals in Li-ion batteries.
Foremost vanillin, a naturally occurring food additive that can be sustainably synthesised from industrial biowaste, lignin, was utilised to synthesise materials that showed extraordinary performance as cathodes in Li-ion batteries. Furthermore, behaviour of catecholic and guiacyl groups in Li-ion system was compared, confirming usability of guiacayl containing biopolymers as cathodes in Li-ion batteries. Lastly, naturally occurring polyphenol, tannic acid, was incorporated in fully bioderived hybrid material that shows performance comparable to commercial Li-ion batteries and good stability.
This thesis presents an important advancement in understanding of biowaste derived cathode materials for Li-ion batteries. Further research should be conducted to better understand behaviour of guaiacyl groups during Li-ion battery cycling. Lastly, challenges of incorporation of lignin, an industrial biowaste, have to be addressed and lignin should be incorporated as a cathode material in Li-ion batteries.
Since the golden era of antibiotics natural products are of ever growing interest to both basic research and applied sciences as they are the main source of new bioactive compounds delivering lead structures for new pharmaceuticals with potent antibiotic, anti-inflammatory or anti-cancer activities. Alongside the technological advances in high-throughput genome sequencing and the better understanding of the general organization of those modular biosynthetic assembly lines of secondary metabolites, there was also a shift from wet-lab screening of active cell extracts towards algorithm-based in silico screening for new natural product biosynthesis gene clusters (BGCs). Although the increasing availability of full genome sequences revealed that such non-ribosomal peptide synthetases (NRPS), polyketide synthases (PKS) and ribosomally synthesized and post-translationally modified peptides (RiPPs) can be found in all three kingdoms of life, certain phyla like actinobacteria and cyanobacteria show a very high density of these secondary metabolite BGCs.
The facultative symbiotic, N2-fixing model organism N. punctiforme PCC73102 is a terrestrial type IV cyanobacterium that not only dedicates are very large fraction of its genome to secondary metabolite production but is also amenable to genetic modification. AntiSMASH analysis of the genome showed that there are sixteen potential secondary metabolite BGCs encoded in N. punctiforme, but until now there were only two compounds assigned to their respective BGC leaving the remaining fourteen orphan. This makes the organism a perfect subject for the establishment of a novel combinatorial genomic mining approach for the detection of new natural products.
In the course of this study a combinatorial approach of genomic mining, independent monitoring techniques and alteration of cultivation conditions lead to new insights in cyanobacterial natural product biosynthesis and ultimately to the description of a novel compound produced by N. punctiforme. With the generation and investigation of a reporter strain library consisting of CFP-producing transcriptional reporter mutants for every predicted secondary metabolite BGC of N. punctiforme, it could be shown that natural product expression is in fact not silent for all those BGCs where no compound can be detected. Instead several distinct expression patterns could be described highlighting that secondary metabolite production is under tight regulation and only a minor fraction of these BGCs is in fact silent under standard laboratory conditions. Furthermore, increasing light intensity and carbon dioxide availability and cultivating N. punctiforme to very high cell densities had a tremendous impact on the overall metabolic activity of the organism. Investigation of high density cultivated cell extracts ultimately lead to the detection of a so far undescribed set of microviridins with unusual extended peptide sequences named Microviridin N3 – N9. Both cultivation of the transcriptional reporter mutants as well as RTqPCR-based detection of secondary metabolite BGC transcription levels revealed that in fact 50% of N. punctiforme’s natural product BGCs are upregulated under high cell density conditions. In contrast to this very broad response, co-cultivation of N. punctiforme in chemical or physical contact with a N-deprived host plant (Blasia pusilla) lead to a very specific upregulation of two natural product BGCs, namely RIPP3 and RIPP4. Although this response could be confirmed by various independent monitoring techniques and heavy analytical efforts were spent, no compound could be assigned to either of these BGCs.
This study is the first in-depth systematic investigation of a cyanobacterial secondary metabolome by a combinatorial approach of genome mining and independent monitoring techniques that can serve as a new strategic approach to gain further insight into natural product synthesis of various organisms. Although there are single well described examples of secondary metabolites like the cell differentiation factor PatS in Anabaena sp. strain PCC 7120, the level and extent of regulation observed in this study is unprecedented and understanding of these mechanisms might be the key to streamline natural product discovery. However, the results of this study also highlight that induction of secondary metabolite BGCs is not the real challenge. Instead the new insights point towards analytical issues being a severe hurdle and finding reliable strategies to overcome these problems might as well drive natural product discovery.
Recent advances in microscopy have led to an improved visualization of different cell processes. Yet, this also leads to a higher demand of tools which can process images in an automated and quantitative fashion. Here, we present two applications that were developed to quantify different processes in eukaryotic cells which rely on the organization and dynamics of the cytoskeleton.. In plant cells, microtubules and actin filaments form the backbone of the cytoskeleton. These structures support cytoplasmic streaming, cell wall organization and tracking of cellular material to and from the plasma membrane. To better understand the underlying mechanisms of cytoskeletal organization, dynamics and coordination, frameworks for the quantification are needed. While this is fairly well established for the microtubules, the actin cytoskeleton has remained difficult to study due to its highly dynamic behaviour. One aim of this thesis was therefore to provide an automated framework to quantify and describe actin organization and dynamics. We used the framework to represent actin structures as networks and examined the transport efficiency in Arabidopsis thaliana hypocotyl cells. Furthermore, we applied the framework to determine the growth mode of cotton fibers and compared the actin organization in wild-type and mutant cells of rice. Finally, we developed a graphical user interface for easy usage. Microtubules and the actin cytoskeleton also play a major role in the morphogenesis of epidermal leaf pavement cells. These cells have highly complex and interdigitated shapes which are hard to describe in a quantitative way. While the relationship between microtubules, the actin cytoskeleton and shape formation is the object of many studies, it is still not clear how and if the cytoskeletal components predefine indentations and protrusions in pavement cell shapes. To understand the underlying cell processes which coordinate cell morphogenesis, a quantitative shape descriptor is needed. Therefore, the second aim of this thesis was the development of a network-based shape descriptor which captures global and local shape features, facilitates shape comparison and can be used to evaluate shape complexity. We demonstrated that our framework can be used to describe and compare shapes from various domains. In addition, we showed that the framework accurately detects local shape features of pavement cells and outperform contending approaches. In the third part of the thesis, we extended the shape description framework to describe pavement cell shape features on tissue-level by proposing different network representations of the underlying imaging data.
Methane is an important greenhouse gas contributing to global climate change. Natural environments and restored wetlands contribute a large proportion to the global methane budget. Methanogenic archaea (methanogens) and methane oxidizing bacteria (methanotrophs), the biogenic producers and consumers of methane, play key roles in the methane cycle in those environments. A large number of studies revealed the distribution, diversity and composition of these microorganisms in individual habitats. However, uncertainties exist in predicting the response and feedback of methane-cycling microorganisms to future climate changes and related environmental changes due to the limited spatial scales considered so far, and due to a poor recognition of the biogeography of these important microorganisms combining global and local scales.
With the aim of improving our understanding about whether and how methane-cycling microbial communities will be affected by a series of dynamic environmental factors in response to climate change, this PhD thesis investigates the biogeographic patterns of methane-cycling communities, and the driving factors which define these patterns at different spatial scales. At the global scale, a meta-analysis was performed by implementing 94 globally distributed public datasets together with environmental data from various natural environments including soils, lake sediments, estuaries, marine sediments, hydrothermal sediments and mud volcanos. In combination with a global biogeographic map of methanogenic archaea from multiple natural environments, this thesis revealed that biogeographic patterns of methanogens exist. The terrestrial habitats showed higher alpha diversities than marine environments. Methanoculleus and Methanosaeta (Methanothrix) are the most frequently detected taxa in marine habitats, while Methanoregula prevails in terrestrial habitats. Estuary ecosystems, the transition zones between marine and terrestrial/limnic ecosystems, have the highest methanogenic richness but comparably low methane emission rates. At the local scale, this study compared two rewetted fens with known high methane emissions in northeastern Germany, a coastal brackish fen (Hütelmoor) and a freshwater riparian fen (Polder Zarnekow). Consistent with different geochemical conditions and land-use history, the two rewetted fens exhibit dissimilar methanogenic and, especially, methanotrophic community compositions. The methanotrophic community was generally under-represented among the prokaryotic communities and both fens show similarly low ratios of methanotrophic to methanogenic abundances. Since few studies have characterized methane-cycling microorganisms in rewetted fens, this study provides first evidence that the rapid and well re-established methanogenic community in combination with the low and incomplete re-establishment of the methanotrophic community after rewetting contributes to elevated sustained methane fluxes following rewetting.
Finally, this thesis demonstrates that dispersal limitation only slightly regulates the biogeographic distribution patterns of methanogenic microorganisms in natural environments and restored wetlands. Instead, their existence, adaption and establishment are more associated with the selective pressures under different environmental conditions. Salinity, pH and temperature are identified as the most important factors in shaping microbial community structure at different spatial scales (global versus terrestrial environments). Predicted changes in climate, such as increasing temperature, changes in precipitation patterns and increasing frequency of flooding events, are likely to induce a series of environmental alterations, which will either directly or indirectly affect the driving environmental forces of methanogenic communities, leading to changes in their community composition and thus potentially also in methane emission patterns in the future.
Potato is the 4th most important food crop in the world. Especially in tropical and sub-tropical potato production, drought is a yield limiting factor. Potato is sensitive to water stress. Potato yield loss under water stress could be reduced by using tolerant varieties and adjusted agronomic practices. Direct selection for yield under water-stressed conditions requires long selection cycles. Thus, identification of markers for marker-assisted selection may speed up breeding. The objective of this thesis is to identify morphological markers for drought tolerance by continuously monitoring plant growth and canopy temperature with an automatic phenotyping system.
The phenotyping was performed in drought-stress experiments that were conducted in population A with 64 genotypes and population B with 21 genotypes in the screenhouse in 2015 and 2016 (population A) and in 2017 and 2018 (population B). Drought tolerance was quantified as deviation of the relative tuber starch yield from the experimental median (DRYM) and parent median (DRYMp). Relative tuber starch yield is starch yield under drought stress relative to the average starch yield of the respective cultivar under control conditions in the same experiment. The specific DRYM value was calculated based on the yield data of the same experiment or the global DRYM that was calculated from yield data derived from data combined over yeas of respective population or across multiple experiments including VALDIS and TROST experiments (2011-2016).
Analysis of variance found a significant effect of genotype on DRYM indicating that the tolerance variation required for marker identification was given in both populations.
Canopy growth was monitored continuously six times a day over five to ten weeks by a laser scanner system and yielded information on leaf area, plant height and leaf angle for population A and additionally on leaf inclination and light penetration depth for population B. Canopy temperature was measured 48 times a day over six to seven weeks by infrared thermometry in population B. From the continuous IRT surface temperature data set, the canopy temperature for each plant was selected by matching the time stamp of the IRT data with laser scanner data.
Mean, maximum, range and growth rate values were calculated from continuous laser scanner measurements of respective canopy parameters. Among the canopy parameters, the maximum and mean values in long-term stress conditions showed better correlation with DRYM values calculated in the same experiment than growth rate and diurnal range values. Therefore, drought tolerance index prediction was done from maximum and mean values of canopy parameters.
The tolerance index in specific experiment condition was linearly predicted by simple regression model from different single canopy parameters under long-term stress condition in population A (2016) and population B (2017 and 2018). Among the canopy parameters maximum light penetration depth (2017), mean leaf angle (2017, 2018, and 2016), mean leaf inclination or mean canopy temperature depression (2017 and 2018), maximum plant height (2017) were selected as tolerance predictors. However, no single parameters were sufficient to predict DRYM. Therefore, several independent parameters were integrated in a multiple regression model.
In multiple regression model, specific experiment DRYM values in population A was predicted from mean leaf angle (2016). In population B, specific tolerance could be predicted from maximum light penetration depth and mean leaf inclination (2017) and mean leaf inclination (2018) or mean canopy temperature depression and mean leaf angle (2018).
In data combined over season of population A, the multiple linear regression model selected maximum plant height and mean leaf angle as tolerance predictor. In Population B, mean leaf inclination was selected as tolerance predictor. However, in population A, the variation explained by the final model was too low.
Furthermore, the average tolerances respective to parent median (2011-2018) across FGH plants or all plants (FGH and field) were predicted from maximum plant height (population A) and maximum plant height and mean leaf inclination (population B). Altogether, canopy parameters could be used as markers for drought tolerance. Therefore, water stress breeding in potato could be speed up through using leaf inclination, light penetration depth, plant height and canopy temperature depression as markers for drought tolerance, especially in long-term stress conditions.
To investigate the reliability and stability of spherical harmonic models based on archeo/-paleomagnetic data, 2000 Geomagnetic models were calculated. All models are based on the same data set but with randomized uncertainties. Comparison of these models to the geomagnetic field model gufm1 showed that large scale magnetic field structures up to spherical harmonic degree 4 are stable throughout all models. Through a ranking of all models by comparing the dipole coefficients to gufm1 more realistic uncertainty estimates were derived than the authors of the data provide.
The derived uncertainty estimates were used in further modelling, which combines archeo/-paleomagnetic and historical data. The huge difference in data count, accuracy and coverage of these two very different data sources made it necessary to introduce a time dependent spatial damping, which was constructed to constrain the spatial complexity of the model. Finally 501 models were calculated by considering that each data point is a Gaussian random variable, whose mean is the original value and whose standard deviation is its uncertainty. The final model arhimag1k is calculated by taking the mean of the 501 sets of Gauss coefficients. arhimag1k fits different dependent and independent data sets well. It shows an early reverse flux patch at the core-mantle boundary between 1000 AD and 1200 AD at the location of the South Atlantic Anomaly today. Another interesting feature is a high latitude flux patch over Greenland between 1200 and 1400 AD. The dipole moment shows a constant behaviour between 1600 and 1840 AD.
In the second part of the thesis 4 new paleointensities from 4 different flows of the island Fogo, which is part of Cape Verde, are presented. The data is fitted well by arhimag1k with the exception of the value at 1663 of 28.3 microtesla, which is approximately 10 microtesla lower than the model suggest.
Seismic receiver arrays have variety of applications in seismology, particularly when the signal enhancement is a prerequisite to detect seismic events, and in situations where installing and maintaining sparse networks are impractical. This thesis has mainly focused on the development of a new approach for seismological source and receiver array design.The proposed approach deals with the array design task as an optimization problem. The criteria and prerequisite constraints in array design task are integrated in objective function definition and evaluation of a optimization process. Three cases are covered in this thesis: (1) a 2-D receiver array geometry optimization, (2) a 3-D source array optimization, and (3) an array application to monitor microseismic data, where the effect of different types of noise are evaluated.
A flexible receiver array design framework implements a customizable scenario modelling and optimization scheme by making use of synthetic seismograms. Using synthetic seismograms to evaluate array performance makes it possible to consider additional constraints, e.g. land ownership, site-specific noise levels or characteristics of the seismic sources under investigation. The use of synthetic array beamforming as an array design criteria is suggested. The framework is customized by designing a 2-D small scale receiver array to monitor earthquake swarm activity in northwest Bohemia/ Vogtland in central Europe. Two sub-functions are defined to verify the accuracy of horizontal slowness estimation; one to suppress aliasing effects due to possible secondary lobes of synthetic array beamforming calculated in horizontal slowness space, and the other to reduce the event's mislocation caused by miscalculation of the horizontal slowness vector. Subsequently, a weighting technique is applied to combine the sub-functions into one single scalar objective function to use in the optimization process.
The idea of optimal array is employed to design a 3-D source array, given a well-located catalog of events. The conditions to make source arrays are formulated in four objective functions and a weighted sum technique is used to combine them in one single scalar function. The criteria are: (1) accurate slowness vector estimation, (2) high waveform coherency, (3) low location error and (4) high energy of coda phases. The method is evaluated by two experiments, (1) a synthetic test using realistic synthetic seismograms, (2) using real seismograms, and for each case optimized SA elements are configured using the data from the Vogtland area.
The location of a possible scatterer in the velocity model, that makes the converted/reflected phases, e.g. sp-phases, is retrieved by a grid search method using the optimized SA. The accuracy of the approach and the obtained results demonstrated that the method is applicable to study the crustal structure and the location of crustal scatterers when the strong converted phases are observed in the data and a well-located catalog is available.
Small aperture arrays are employed in seismology for a variety of applications, ranging from pure event detection to monitor and study of microcosmic activities. The monitoring of microseismicity during temporary human activities is often difficult, as the signal-to-noise ratio is very low and noise is strongly increased during the operation. The combination of small aperture seismic arrays with shallow borehole sensors offers a solution. We tested this monitoring approach at two different sites, (1) accompanying a fracking experiment in sedimentary shale at 4~km depth, and (2) above a gas field under depletion. Arrays recordings are compared with recordings available from shallow borehole sensors and examples of detection and location performance of the array are given. The effect of different types of noise at array and borehole stations are compared and discussed.
As one of the most-produced commodity polymers, polypropylene draws considerable scientific and commercial interest as an electret material. In the present thesis, the influence of the surface chemical modification and crystalline reconstruction on the electret properties of the polypropylene thin films will be discussed. The chemical treatment with orthophosphoric acid can significantly improve the surface charge stability of the polypropylene electrets by introducing phosphorus- and oxygen-containing structures onto the modified surface. The thermally stimulated discharge measurement and charge profiling by means of piezoelectrically generated pressure steps are used to investigate the electret behaviour. It is concluded that deep traps of limited number density are created during the treatment with inorganic chemicals. Hence, the improvement dramatically decreases when the surface-charge density is substantially higher than ±1.2×10^(-3) C·m^(-2). The newly formed traps also show a higher trapping energy for negative charges. The energetic distributions of the traps in the non-treated and chemically treated samples offer an insight regarding the surface and foreign-chemical dominance on the charge storage and transport in the polypropylene electrets.
Additionally, different electret properties are observed on the polypropylene films with the spherulitic and transcrystalline structures. It indicates the dependence of the charge storage and transport on the crystallite and molecular orientations in the crystalline phase. In general, a more diverse crystalline growth in the spherulitic samples can result in a more complex energetic trap distribution, in comparison to that in a transcrystalline polypropylene. The double-layer transcrystalline polypropylene film with a crystalline interface in the middle can be obtained by crystallising the film in contact with rough moulding surfaces on both sides. A layer of heterocharges appears on each side of the interface in the double-layer transcrystalline polypropylene electrets after the thermal poling. However, there is no charge captured within the transcrystalline layers. The phenomenon reveals the importance of the crystalline interface in terms of creating traps with the higher activation energy in polypropylene. The present studies highlight the fact that even slight variations in the polypropylene film may lead to dramatic differences in its electret properties.
Near-Earth space represents a significant scientific and technological challenge. Particularly at magnetic low-latitudes, the horizontal magnetic field geometry at the dip equator and its closed field-lines support the existence of a distinct electric current system, abrupt electric field variations and the development of plasma irregularities. Of particular interest are small-scale irregularities associated with equatorial plasma depletions (EPDs). They are responsible for the disruption of trans-ionospheric radio waves used for navigation, communication, and Earth observation. The fast increase of satellite missions makes it imperative to study the near-Earth space, especially the phenomena known to harm space technology or disrupt their signals. EPDs correspond to the large-scale structure (i.e., tens to hundreds of kilometers) of topside F region irregularities commonly known as Spread F. They are observed as depleted-plasma density channels aligned with the ambient magnetic field in the post-sunset low-latitude ionosphere. Although the climatological variability of their occurrence in terms of season, longitude, local time and solar flux is well-known, their day to day variability is not. The sparse observations from ground-based instruments like radars and the few simultaneous measurements of ionospheric parameters by space-based instruments have left gaps in the knowledge of EPDs essential to comprehend their variability.
In this dissertation, I profited from the unique observations of the ESA’s Swarm constellation mission launched in November 2013 to tackle three issues that revealed novel and significant results on the current knowledge of EPDs. I used Swarm’s measurements of the electron density, magnetic, and electric fields to answer, (1.) what is the direction of propagation of the electromagnetic energy associated with EPDs?, (2.) what are the spatial and temporal characteristics of the electric currents (field-aligned and diamagnetic currents) related to EPDs, i.e., seasonal/geographical, and local time dependencies?, and (3.) under what conditions does the balance between magnetic and plasma pressure across EPDs occur?
The results indicate that: (1.) The electromagnetic energy associated with EPDs presents a preference for interhemispheric flows; that is, the related Poynting flux directs from one magnetic hemisphere to the other and varies with longitude and season. (2.) The field-aligned currents at the edges of EPDs are interhemispheric. They generally close in the hemisphere with the highest Pedersen conductance. Such hemispherical preference presents a seasonal/longitudinal dependence. The diamagnetic currents increase or decrease the magnetic pressure inside EPDs. These two effects rely on variations of the plasma temperature inside the EPDs that depend on longitude and local time. (3.) EPDs present lower or higher plasma pressure than the ambient. For low-pressure EPDs the plasma pressure gradients are mostly dominated by variations of the plasma density so that variations of the temperature are negligible. High-pressure EPDs suggest significant temperature variations with magnitudes of approximately twice the ambient. Since their occurrence is more frequent in the vicinity of the South Atlantic magnetic anomaly, such high temperatures are suggested to be due to particle precipitation.
In a broader context, this dissertation shows how dedicated satellite missions with high-resolution capabilities improve the specification of the low-latitude ionospheric electrodynamics and expand knowledge on EPDs which is valuable for current and future communication, navigation, and Earth-observing missions. The contributions of this investigation represent several ’firsts’ in the study of EPDs: (1.) The first observational evidence of interhemispheric electromagnetic energy flux and field-aligned currents. (2.) The first spatial and temporal characterization of EPDs based on their associated field-aligned and diamagnetic currents. (3.) The first evidence of high plasma pressure in regions of depleted plasma density in the ionosphere. These findings provide new insights that promise to advance our current knowledge of not only EPDs but the low-latitude post-sunset ionosphere environment.
To meet the demands of a growing world population while reducing carbon dioxide (CO2) emissions, it is necessary to capture CO2 and convert it into value-added compounds. In recent years, metabolic engineering of microbes has gained strong momentum as a strategy for the production of valuable chemicals. As common microbial feedstocks like glucose directly compete with human consumption, the one carbon (C1) compound formate was suggested as an alternative feedstock. Formate can be easily produced by various means including electrochemical reduction of CO2 and could serve as a feedstock for microbial production, hence presenting a novel entry point for CO2 to the biosphere and a storage option for excess electricity. Compared to the gaseous molecule CO2, formate is a highly soluble compound that can be easily handled and stored. It can serve as a carbon and energy source for natural formatotrophs, but these microbes are difficult to cultivate and engineer. In this work, I present the results of several projects that aim to establish efficient formatotrophic growth of E. coli – which cannot naturally grow on formate – via synthetic formate assimilation pathways. In the first study, I establish a workflow for growth-coupled metabolic engineering of E. coli. I demonstrate this approach by presenting an engineering scheme for the PFL-threonine cycle, a synthetic pathway for anaerobic formate assimilation in E. coli. The described methods are intended to create a standardized toolbox for engineers that aim to establish novel metabolic routes in E. coli and related organisms. The second chapter presents a study on the catalytic efficiency of C1-oxidizing enzymes in vivo. As formatotrophic growth requires generation of both energy and biomass from formate, the engineered E. coli strains need to be equipped with a highly efficient formate dehydrogenase, which provides reduction equivalents and ATP for formate assimilation. I engineered a strain that cannot generate reducing power and energy for cellular growth, when fed on acetate. Under this condition, the strain depends on the introduction of an enzymatic system for NADH regeneration, which could further produce ATP via oxidative phosphorylation. I show that the strain presents a valuable testing platform for C1-oxidizing enzymes by testing different NAD-dependent formate and methanol dehydrogenases in the energy auxotroph strain. Using this platform, several candidate enzymes with high in vivo activity, were identified and characterized as potential energy-generating systems for synthetic formatotrophic or methylotrophic growth in E. coli. In the third chapter, I present the establishment of the serine threonine cycle (STC) – a synthetic formate assimilation pathway – in E. coli. In this pathway, formate is assimilated via formate tetrahydrofolate ligase (FtfL) from Methylobacterium extorquens (M. extorquens). The carbon from formate is attached to glycine to produce serine, which is converted into pyruvate entering central metabolism. Via the natural threonine synthesis and cleavage route, glycine is regenerated and acetyl-CoA is produced as the pathway product. I engineered several selection strains that depend on different STC modules for growth and determined key enzymes that enable high flux through threonine synthesis and cleavage. I could show that expression of an auxiliary formate dehydrogenase was required to achieve growth via threonine synthesis and cleavage on pyruvate. By overexpressing most of the pathway enzymes from the genome, and applying adaptive laboratory evolution, growth on glycine and formate was achieved, indicating the activity of the complete cycle. The fourth chapter shows the establishment of the reductive glycine pathway (rGP) – a short, linear formate assimilation route – in E. coli. As in the STC, formate is assimilated via M. extorquens FtfL. The C1 from formate is condensed with CO2 via the reverse reaction of the glycine cleavage system to produce glycine. Another carbon from formate is attached to glycine to form serine, which is assimilated into central metabolism via pyruvate. The engineered E. coli strain, expressing most of the pathway genes from the genome, can grow via the rGP with formate or methanol as a sole carbon and energy source.
NADPH is an essential cofactor that drives biosynthetic reactions in all living organisms. It is a reducing agent and thus electron donor of anabolic reactions that produce major cellular components as well as many products in biotechnology. Indeed, the engineering of metabolic pathways for the production of many products is often limited by the availability of NADPH. One common strategy to address this issue is to swap cofactor specificity from NADH to NADPH of enzymes. However, this process is time consuming and challenging because multiple parameters need to be engineered in parallel. Therefore, the first aim of this project is to establish an efficient metabolic biosensor to select enzymes that can reduce NADP+. An NADPH auxotroph strain was constructed by deleting major reactions involved in NADPH biosynthesis in E. coli’s central carbon metabolism with the exception of 6-phosphogluconate dehydrogenase. To validate this strain, two enzymes were tested in the presence of several carbon sources: a dihydrolipoamide dehydrogenase variant of E. coli harboring seven mutations and a formate dehydrogenase (FDH) from Mycobacterium vaccae N10 harboring four mutations were found to support NADPH biosynthesis and growth. The strain was subjected to adaptive laboratory evolution with the goal of testing its robustness under different carbon sources. Our evolution experiment resulted in the random mutagenesis of the malic enzyme (maeA), enabling it to produce NADPH. The additional deletion of maeA rendered a more robust second-generation biosensor strain for NADP+ reduction. We devised a structure-guided directed evolution approach to change cofactor specificity in Pseudomonas sp. 101 FDH. To this end, a library of >106 variants was tested using in vivo selection. Compared to the best engineered enzymes reported, our best variant carrying five mutations shows 5-fold higher catalytic efficiency and 13-fold higher specificity towards NADP+, as well as 2-fold higher affinity towards formate. In conclusion, we demonstrate the potential of in vivo selection and evolution-guided approaches to develop better NADPH biosensors and to engineer cofactor specificity by the simultaneous improvement of multiple parameters (kinetic efficiency with NADP+, specificity towards NADP+, and affinity towards formate), which is a major challenge in protein engineering due to the existence of tradeoffs and epistasis.
Carbon nitride and poly(ionic liquid)s (PILs) have been successfully applied in various fields of materials science owing to their outstanding properties. This thesis aims at the successful application of these polymers as innovative materials in the interfaces of hybrid organic–inorganic perovskite solar cells. A critical problem in harnessing the full thermodynamic potential of halide perovskites in solar cells is the design and modification of interfaces to reduce carrier recombination. Therefore, the interface must be properly studied and improved. This work investigated the effect of applying carbon nitride and PILs on a perovskite surface on the device performance. The facile synthetic method for modifying carbon nitride with vinyl thiazole and barbituric acid (CMB-vTA) yields 2.3 nm layers when solution processing is performed using isopropanol. The nanosheets were applied as a metal-free electron transport layer in inverted perovskite solar cells. The application of carbon nitride layers (CMB-vTA) resulted in negligible current-voltage hysteresis with a high open circuit voltage (Voc) of 1.1 V and a short-circuit current (Jsc) of 20.28 mA cm-2, which afforded efficiencies of up to 17%. Thus, the successful implementation of a carbon nitride-based structure enabled good charge extraction with minimized interface recombination between the perovskite and PCBM. Similarly, PILs represent a new strategy of interfacial modification using an ionic polymer in an n-i-p perovskite architecture.. The application of PILs as an interfacial modifier resulted in solar cell devices with an extraordinarily high efficiency of 21.8% and a Voc of 1.17 V. The implementation reduced non-radiative recombination at the perovskite surface through defect passivation. Finally, our work proposes a novel method to efficiently suppress non-radiative charge recombination using the unexplored properties of carbon nitride and PILs in the solar cell field. Additionally, the method for interfacial modification has general applicability because of the simplicity of the post-treatment approach, and therefore has potential applicability in other solar cells. Thus, this work opens the door to a new class of materials to be implemented.
In nature, bacteria are found to reside in multicellular communities encased in self-produced extracellular matrices. Indeed, biofilms are the default lifestyle of the bacteria which cause persistent infections in humans. The biofilm assembly protects bacterial cells from desiccation and limits the effectiveness of antimicrobial treatments. A myriad of biomolecules in the extracellular matrix, including proteins, exopolysaccharides, lipids, extracellular DNA and other, form a dense and viscoelastic three dimensional network. Many studies emphasized that a destabilization of the mechanical integrity of biofilm architectures potentially eliminates the protective shield and renders bacteria more susceptible to the immune system and antibiotics. Pantoea stewartii is a plant pathogen which infects monocotyledons such as maize and sweet corn. These bacteria produce dense biofilms in the xylem of infected plants which cause wilting of plants and crops. Stewartan is an exopolysaccharide which is produced by Pantoea stewartii and secreted as the major component to the extracellular matrix. It consists of heptasaccharide repeating units with a high degree of polymerization (2-4 MDa). In this work, the physicochemical properties of stewartan were investigated to understand the contributions of this exopolysaccharide to the mechanical integrity and cohesiveness of Pantoea stewartii biofilms. Therefore, a coarse-grained model of stewartan was developed with computational techniques to obtain a model for its three dimensional structural features. Here, coarse-grained molecular dynamic simulations revealed that the exopolysaccharide forms a hydrogel in which the exopolysaccharide chains arrange into a three dimensional mesh-like network. Simulations at different concentrations were used to investigate the influence of the water content on the network formation. Stewartan was further purified from 72 h grown Pantoea stewartii biofilms and the diffusion of bacteriophage and differently-sized nanoparticles (which ranged from 1.1 to 193 nm diameter) was analyzed in reconstituted stewartan solutions. Fluorescence correlation spectroscopy and single-particle tracking revealed that the stewartan network impeded the mobility of a set of differently-sized fluorescent particles in a size-dependent manner. Diffusion of these particles became more anomalous, as characterized by fitting the diffusion data to an anomalous diffusion model, with increasing stewartan concentrations. Further bulk and microrheological experiments were used to analyze the transitions in stewartan fluid behavior and stewartan chain entanglements were described. Moreover, it was noticed, that a small fraction of bacteriophage particles was trapped in small-sized pores deviating from classical random walks which highlighted the structural heterogeneity of the stewartan network. Additionally, the mobility of fluorescent particles
also depended on the charge of the stewartan exopolysaccharide and a model of a molecular sieve for the stewartan network was proposed. The here reported structural features of the stewartan polymers were used to provide a detailed description of the mechanical properties of typically glycan-based biofilms such as the one from Pantoea stewartii.
In addition, the mechanical properties of the biofilm architecture are permanently sensed by the embedded bacteria and enzymatic modifications of the extracellular matrix take place to address environmental cues. Hence, in this work the influence of enzymatic degradation of the stewartan exopolysaccharides on the overall exopolysaccharide network structure was analyzed to describe relevant physiological processes in Pantoea stewartii biofilms. Here, the stewartan hydrolysis kinetics of the tailspike protein from the ΦEa1h bacteriophage, which is naturally found to infect Pantoea stewartii cells, was compared to WceF. The latter protein is expressed from the Pantoea stewartii stewartan biosynthesis gene cluster wce I-III. The degradation of stewartan by the ΦEa1h tailspike protein was shown to be much faster than the hydrolysis kinetics of WceF, although both enzymes cleaved the β D GalIII(1→3)-α-D-GalI glycosidic linkage from the stewartan backbone. Oligosaccharide fragments which were produced during the stewartan cleavage, were analyzed in size-exclusion chromatography and capillary electrophoresis. Bioinformatic studies and the analysis of a WceF crystal structure revealed a remarkably high structural similarity of both proteins thus unveiling WceF as a bacterial tailspike-like protein. As a consequence, WceF might play a role in stewartan chain length control in Pantoea stewartii biofilms.
Escaping the plant cell
(2020)
This thesis offers new insights on the effects of Start-Up Subsidies (SUS) for unemployed individuals as a special kind of active labor market program (ALMP) that aims to re-integrate individuals into the labor market via the route of self-employment. Moreover, this thesis contributes to the literature on methods for causal inference when the treatment variable is continuous rather than binary. For example, this is the case when individuals differ in their degree of exposure to a common treatment.
The analysis of the effects of SUS focuses on the main current German program called “Gründungszuschuss” (New Start-Up Subsidy, NSUS) after its reform in 2011. Average Effects on participants' labor market outcomes - as measured by employment and earnings - as well as subjective well-being are estimated mainly based on propensity score matching (PSM) techniques. PSM aims to achieve balance in terms of observed characteristics by matching participants with at least one comparable non-participant in terms of their probability to receive the treatment. This estimation strategy is valid as long as all relevant characteristics that explain selection patterns into treatment are observed and included in the estimation of the propensity score. To make our analysis as credible as possible, we control for a large vector of characteristics as observed through the combination of rich administrative data from the Federal Employment Agency as well as through survey data.
Chapters two to four of this thesis puts special emphasis on aspects regarding (the evaluation of) SUS programs that have received no or only limited attention thus far. The first aspect relates to the interplay of institutional details of the program and its effectiveness. So far, relatively little is known about the importance of SUS program features such as the duration of support. Second, there is no experimental benchmark evaluation of SUS available and thus, the reliability of non-experimental estimation techniques such as PSM is of crucial importance as estimates are biased when relevant confounders are omitted from the analysis. Third, there may be potentially detrimental effects of transitioning into (relatively risky) self-employment on subjective well-being among subsidized founders out of unemployment. These were to remain undetected if the analysis would focus exclusively on labor market outcomes of participants. The results indicate positive long-term effects of SUS participation on employment and earnings among participants. These effects are substantially larger than what estimated before the reform, indicating room for improvement in program design via changes in institutional details. Moreover, non-experimental estimates of treatment effects are remarkably robust to hidden confounding. Regarding subjective well-being, this thesis finds a positive long-run impact on job satisfaction and a detrimental effect on satisfaction with social security. The latter appears to be driven by adverse effects on social insurance contributions.
In chapter five, a novel automated covariate balancing technique for the estimation of causal effects in the context of continuous treatments is derived and assessed regarding its performance compared to other (automated) balancing techniques. Although binary research designs that only differentiate between participants and non-participants of some treatment remain the most-common case in empirical practice, many applications can be adapted to include continuous treatments as well. Often, this will allow for more meaningful estimates of causal effects in order to further improve the design of programs. In the context of SUS, one may further investigate the effects of the size of monetary support or its duration on participants' labor market outcomes. Both Monte-Carlo investigations and analysis of two well-known datasets suggests superior performance of the proposed Entropy Balancing for continuous treatments (EBCT) compared to other existing estimation strategies.
Understanding how organisms adapt to their local environment is a major focus of evolutionary biology. Local adaptation occurs when the forces of divergent natural selection are strong enough compared to the action of other evolutionary forces. An improved understanding of the genetic basis of local adaptation can inform about the evolutionary processes in populations and is of major importance because of its relevance to altered selection pressures due to climate change. So far, most insights have been gained by studying model organisms, but our understanding about the genetic basis of local adaptation in wild populations of species with little genomic resources is still limited.
With the work presented in this thesis I therefore set out to provide insights into the genetic basis of local adaptation in populations of two voles species: the common vole (Microtus arvalis) and the bank vole (Myodes glareolus). Both voles species are small mammals, they have a high evolutionary potential compared to their dispersal capabilities and are thus likely to show genetic responses to local conditions, moreover, they have a wide distribution in which they experience a broad range of different environmental conditions, this makes them an ideal species to study local adaptation.
The first study focused on producing a novel mitochondrial genome to facilitate further research in M. arvalis. To this end, I generated the first mitochondrial genome of M. arvalis using shotgun sequencing and an iterative mapping approach. This was subsequently used in a phylogenetic analysis that produced novel insights into the phylogenetic relationships of the Arvicolinae.
The following two studies then focused on the genetic basis of local adaptation using ddRAD-sequencing data and genome scan methods. The first of these involved sequencing the genomic DNA of individuals from three low-altitude and three high-altitude M. arvalis study sites in the Swiss Alps. High-altitude environments with their low temperatures and low levels of oxygen (hypoxia) pose considerable challenges for small mammals. With their small body size and proportional large body surface they have to sustain high rates of aerobic metabolism to support thermogenesis and locomotion, which can be restricted with only limited levels of oxygen available. To generate insights into high-altitude adaptation I identified a large number of single nucleotide polymorphisms (SNPs). These data were first used to identify high levels of differentiation between study sites and a clear pattern of population structure, in line with a signal of isolation by distance. Using genome scan methods, I then identified signals of selection associated with differences in altitude in genes with functions related to oxygen transport into tissue and genes related to aerobic metabolic pathways. This indicates that hypoxia is an important selection pressure driving local adaptation at high altitude in M. arvalis. A number of these genes were linked with high-altitude adaptation in other species before, which lead to the suggestion that high-altitude populations of several species have evolved in a similar manner as a response to the unique conditions at high altitude
The next study also involved the genetic basis of local adaptation, here I provided insights into climate-related adaptation in M. glareolus across its European distribution. Climate is an important environmental factor affecting the physiology of all organisms. In this study I identified a large number of SNPs in individuals from twelve M. glareolus populations distributed across Europe. I used these, to first establish that populations are highly differentiated and found a strong pattern of population structure with signal of isolation by distance. I then employed genome scan methods to identify candidate loci showing signals of selection associated with climate, with a particular emphasis on polygenic loci. A multivariate analysis was used to determine that temperature was the most important climate variable responsible for adaptive genetic variation among all variables tested. By using novel methods and genome annotation of related species I identified the function of genes of candidate loci. This showed that genes under selection have functions related to energy homeostasis and immune processes. Suggesting that M. glareolus populations have evolved in response to local temperature and specific local pathogenic selection pressures.
The studies presented in this thesis provide evidence for the genetic basis of local adaptation in two vole species across different environmental gradients, suggesting that the identified genes are involved in local adaptation. This demonstrates that with the help of novel methods the study of wild populations, which often have little genomic resources available, can provide unique insights into evolutionary processes.
Feminist Solidarities after Modulation produces an intersectional analysis of transnational feminist movements and their contemporary digital frameworks of identity and solidarity. Engaging media theory, critical race theory, and Black feminist theory, as well as contemporary feminist movements, this book argues that digital feminist interventions map themselves onto and make use of the multiplicity and ambiguity of digital spaces to question presentist and fixed notions of the internet as a white space and technologies in general as objective or universal. Understanding these frameworks as colonial constructions of the human, identity is traced to a socio-material condition that emerges with the modernity/colonialism binary. In the colonial moment, race and gender become the reasons for, as well as the effects of, technologies of identification, and thus need to be understood as and through technologies. What Deleuze has called modulation is not a present modality of control, but is placed into a longer genealogy of imperial division, which stands in opposition to feminist, queer, and anti-racist activism that insists on non-modular solidarities across seeming difference. At its heart, Feminist Solidarities after Modulation provides an analysis of contemporary digital feminist solidarities, which not only work at revealing the material histories and affective ""leakages"" of modular governance, but also challenges them to concentrate on forms of political togetherness that exceed a reductive or essentialist understanding of identity, solidarity, and difference.
With his September 2015 speech “Breaking the tragedy of the horizon”, the President of the Central Bank of England, Mark Carney, put climate change on the agenda of financial market regulators. Until then, climate change had been framed mainly as a problem of negative externalities leading to long-term economic costs, which resulted in countries trying to keep the short-term costs of climate action to a minimum. Carney argued that climate change, as well as climate policy, can also lead to short-term financial risks, potentially causing strong adjustments in asset prices. Analysing the effect of a sustainability transition on the financial sector challenges traditional economic and financial analysis and requires a much deeper understanding of the interrelations between climate policy and financial markets.
This dissertation thus investigates the implications of climate policy for financial markets as well as the role of financial markets in a transition to a sustainable economy. The approach combines insights from macroeconomic and financial risk analysis. Following an introduction and classification in Chapter 1, Chapter 2 shows a macroeconomic analysis that combines ambitious climate targets (negative externality) with technological innovation (positive externality), adaptive expectations and an investment program, resulting in overall positive macroeconomic outcomes. The analysis also reveals the limitations of climate economic models in their representation of financial markets. Therefore, the subsequent part of this dissertation is concerned with the link between climate policies and financial markets. In Chapter 3, an empirical analysis of stock-market responses to the announcement of climate policy targets is performed to investigate impacts of climate policy on financial markets. Results show that 1) international climate negotiations have an effect on asset prices and 2) investors increasingly recognize transition risks in carbon-intensive investments. In Chapter 4, an analysis of equity markets and the interbank market shows that transition risks can potentially affect a large part of the equity market and that financial interconnections can amplify negative shocks. In Chapter 5, an analysis of mortgage loans shows how information on climate policy and the energy performance of buildings can be integrated into risk management and reflected in interest rates.
While costs of climate action have been explored at great depth, this dissertation offers two main contributions. First, it highlights the importance of a green investment program to strengthen the macroeconomic benefits of climate action. Second, it shows different approaches on how to integrate transition risks and opportunities into financial market analysis. Anticipating potential losses and gains in the value of financial assets as early as possible can make the financial system more resilient to transition risks and can stimulate investments into the decarbonization of the economy.
Living cells rely on transport and interaction of biomolecules to perform their diverse functions. A powerful toolbox to study these highly dynamic processes in the native environment is provided by fluorescence fluctuation spectroscopy (FFS) techniques. In more detail, FFS takes advantage of the inherent dynamics present in biological systems, such as diffusion, to infer molecular parameters from fluctuations of the signal emitted by an ensemble of fluorescently tagged molecules. In particular, two parameters are accessible: the concentration of molecules and their transit times through the observation volume. In addition, molecular interactions can be measured by analyzing the average signal emitted per molecule - the molecular brightness - and the cross-correlation of signals detected from differently tagged species.
In the present work, several FFS techniques were implemented and applied in different biological contexts. In particular, scanning fluorescence correlation spectroscopy (sFCS) was performed to measure protein dynamics and interactions at the plasma membrane (PM) of cells, and number and brightness (N&B) analysis to spatially map molecular aggregation. To account for technical limitations and sample related artifacts, e.g. detector noise, photobleaching, or background signal, several correction schemes were explored. In addition, sFCS was combined with spectral detection and higher moment analysis of the photon count distribution to resolve multiple species at the PM.
Using scanning fluorescence cross-correlation spectroscopy and cross-correlation N&B, the interactions of amyloid precursor-like protein 1 (APLP1), a synaptic membrane protein, were investigated. It is shown for the first time directly in living cells, that APLP1 undergoes specific interactions at cell-cell contacts. It is further demonstrated that zinc ions induce formation of large APLP1 clusters that enrich at contact sites and bind to clusters on the opposing cell. Altogether, these results provide direct evidence that APLP1 is a zinc ion dependent neuronal adhesion protein.
In the context of APLP1, discrepancies of oligomeric state estimates were observed, which were attributed to non-fluorescent states of the chosen red fluorescent protein (FP) tag mCardinal (mCard). Therefore, multiple FPs and their performance in FFS based measurements of protein interactions were systematically evaluated. The study revealed superior properties of monomeric enhanced green fluorescent protein (mEGFP) and mCherry2. Furthermore, a simple correction scheme allowed unbiased in situ measurements of protein oligomerization by quantifying non-fluorescent state fractions of FP tags. The procedure was experimentally confirmed for biologically relevant protein complexes consisting of up to 12 monomers.
In the last part of this work, fluorescence correlation spectroscopy (FCS) and single particle tracking (SPT) were used to characterize diffusive transport dynamics in a bacterial biofilm model. Biofilms are surface adherent bacterial communities, whose structural organization is provided by extracellular polymeric substances (EPS) that form a viscous polymer hydrogel. The presented study revealed a probe size and polymer concentration dependent (anomalous) diffusion hindrance in a reconstituted EPS matrix system caused by polymer chain entanglement at physiological concentrations. This result indicates a meshwork-like organization of the biofilm matrix that allows free diffusion of small particles, but strongly hinders diffusion of larger particles such as bacteriophages. Finally, it is shown that depolymerization of the matrix by phage derived enzymes rapidly facilitated free diffusion. In the context of phage infections, such enzymes may provide a key to evade trapping in the biofilm matrix and promote efficient infection of bacteria. In combination with phage application, matrix depolymerizing enzymes may open up novel antimicrobial strategies against multiresistant bacterial strains, as a promising, more specific alternative to conventional antibiotics.