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Interlocutors typically link their utterances to the discourse environment and enrich communication by linguistic (e.g., information packaging) and extra-linguistic (e.g., eye gaze, gestures) means to optimize information transfer. Psycholinguistic studies underline that ‒for meaning computation‒ listeners profit from linguistic and visual cues that draw their focus of attention to salient information. This dissertation is the first work that examines how linguistic compared to visual salience cues influence sentence comprehension using the very same experimental paradigms and materials, that is, German subject-before-object (SO) and object-before-subject (OS) sentences, across the two cue modalities. Linguistic salience was induced by indicating a referent as the aboutness topic. Visual salience was induced by implicit (i.e., unconscious) or explicit (i.e., shared) manipulations of listeners’ attention to a depicted referent.
In Study 1, a selective, facilitative impact of linguistic salience on the context-sensitive OS word order was found using offline comprehensibility judgments. More precisely, during online sentence processing, this impact was characterized by a reduced sentence-initial Late positivity which reflects reduced processing costs for updating the current mental representation of discourse. This facilitative impact of linguistic salience was not replicated by means of an implicit visual cue (Study 2) shown to modulate word order preferences during sentence production. However, a gaze shift to a depicted referent as an indicator of shared attention eased sentence-initial processing similar to linguistic salience as revealed by reduced reading times (Study 3). Yet, this cue did not modulate the strong subject-antecedent preference during later pronoun resolution like linguistic salience. Taken together, these findings suggest a significant impact of linguistic and visual salience cues on sentence comprehension, which substantiates that both the information delivered via language and via the visual environment is integrated into the mental representation of the discourse; but, the way how salience is induced is crucial to its impact.
Since half a century, cytometry has been a major scientific discipline in the field of cytomics - the study of system’s biology at single cell level. It enables the investigation of physiological processes, functional characteristics and rare events with proteins by analysing multiple parameters on an individual cell basis. In the last decade, mass cytometry has been established which increased the parallel measurement to up to 50 proteins. This has shifted the analysis strategy from conventional consecutive manual gates towards multi-dimensional data processing. Novel algorithms have been developed to tackle these high-dimensional protein combinations in the data. They are mainly based on clustering or non-linear dimension reduction techniques, or both, often combined with an upstream downsampling procedure. However, these tools have obstacles either in comprehensible interpretability, reproducibility, computational complexity or in comparability between samples and groups.
To address this bottleneck, a reproducible, semi-automated cytometric data mining workflow PRI (pattern recognition of immune cells) is proposed which combines three main steps: i) data preparation and storage; ii) bin-based combinatorial variable engineering of three protein markers, the so called triploTs, and subsequent sectioning of these triploTs in four parts; and iii) deployment of a data-driven supervised learning algorithm, the cross-validated elastic-net regularized logistic regression, with these triploT sections as input variables. As a result, the selected variables from the models are ranked by their prevalence, which potentially have discriminative value. The purpose is to significantly facilitate the identification of meaningful subpopulations, which are most distinguish between two groups. The proposed workflow PRI is exemplified by a recently published public mass cytometry data set. The authors found a T cell subpopulation which is discriminative between effective and ineffective treatment of breast carcinomas in mice. With PRI, that subpopulation was not only validated, but was further narrowed down as a particular Th1 cell population. Moreover, additional insights of combinatorial protein expressions are revealed in a traceable manner. An essential element in the workflow is the reproducible variable engineering. These variables serve as basis for a clearly interpretable visualization, for a structured variable exploration and as input layers in neural network constructs.
PRI facilitates the determination of marker levels in a semi-continuous manner. Jointly with the combinatorial display, it allows a straightforward observation of correlating patterns, and thus, the dominant expressed markers and cell hierarchies. Furthermore, it enables the identification and complex characterization of discriminating subpopulations due to its reproducible and pseudo-multi-parametric pattern presentation. This endorses its applicability as a tool for unbiased investigations on cell subsets within multi-dimensional cytometric data sets.
The central motivation of the thesis was to provide possible solutions and concepts to improve the performance (e.g. activity and selectivity) of electrochemical N2 reduction reaction (NRR). Given that porous carbon-based materials usually exhibit a broad range of structural properties, they could be promising NRR catalysts. Therefore, the advanced design of novel porous carbon-based materials and the investigation of their application in electrocatalytic NRR including the particular reaction mechanisms are the most crucial points to be addressed. In this regard, three main topics were investigated. All of them are related to the functionalization of porous carbon for electrochemical NRR or other electrocatalytic reactions.
In chapter 3, a novel C-TixOy/C nanocomposite has been described that has been obtained via simple pyrolysis of MIL-125(Ti). A novel mode for N2 activation is achieved by doping carbon atoms from nearby porous carbon into the anion lattice of TixOy. By comparing the NRR performance of M-Ts and by carrying out DFT calculations, it is found that the existence of (O-)Ti-C bonds in C-doped TixOy can largely improve the ability to activate and reduce N2 as compared to unoccupied OVs in TiO2. The strategy of rationally doping heteroatoms into the anion lattice of transition metal oxides to create active centers may open many new opportunities beyond the use of noble metal-based catalysts also for other reactions that require the activation of small molecules as well.
In chapter 4, a novel catalyst construction composed of Au single atoms decorated on the surface of NDPCs was reported. The introduction of Au single atoms leads to active reaction sites, which are stabilized by the N species present in NDPCs. Thus, the interaction within as-prepared AuSAs-NDPCs catalysts enabled promising performance for electrochemical NRR. For the reaction mechanism, Au single sites and N or C species can act as Frustrated Lewis pairs (FLPs) to enhance the electron donation and back-donation process to activate N2 molecules. This work provides new opportunities for catalyst design in order to achieve efficient N2 fixation at ambient conditions by utilizing recycled electric energy.
The last topic described in chapter 5 mainly focused on the synthesis of dual heteroatom-doped porous carbon from simple precursors. The introduction of N and B heteroatoms leads to the construction of N-B motives and Frustrated Lewis pairs in a microporous architecture which is also rich in point defects. This can improve the strength of adsorption of different reactants (N2 and HMF) and thus their activation. As a result, BNC-2 exhibits a desirable electrochemical NRR and HMF oxidation performance. Gas adsorption experiments have been used as a simple tool to elucidate the relationship between the structure and catalytic activity. This work provides novel and deep insights into the rational design and the origin of activity in metal-free electrocatalysts and enables a physically viable discussion of the active motives, as well as the search for their further applications.
Throughout this thesis, the ubiquitous problems of low selectivity and activity of electrochemical NRR are tackled by designing porous carbon-based catalysts with high efficiency and exploring their catalytic mechanisms. The structure-performance relationships and mechanisms of activation of the relatively inert N2 molecules are revealed by either experimental results or DFT calculations. These fundamental understandings pave way for a future optimal design and targeted promotion of NRR catalysts with porous carbon-based structure, as well as study of new N2 activation modes.
In der Dissertationsarbeit mit dem Titel „Eine Hypothese über die Grundlagen von Moral und einige Implikationen“ unternimmt die Autorin den Versuch, die anthropologischen Prämissen moralischen Handelns herauszuarbeiten. Es wird eine Hypothese aufgestellt und erläutert, die behauptet, dass moralisches Handeln nur dann verständlich wird, wenn der Handelnde erstens die Fähigkeit der Phantasie aufweist, zweitens auf Erfahrungen (mittels seines Gedächtnisses) zugreifen kann und durch Konversation mit anderen Personen interagierte und interagiert, denn nur auf der Basis dieser drei Grundlagen von Moral können sich diejenigen Fähigkeiten ent¬wickeln, die als Voraussetzungen moralischen Handeln gesehen werden müssen: Selbstbewusstsein, Freiheit, die Entwicklung eines Wir-Gefühls, die Genese eines moralischen Ideals und die Fähigkeit, sich im Entscheiden und Handeln nach diesem Ideal richten zu können. Außerdem werden in dieser Dissertation einige Implikationen dieser Hypothese auf individueller und zwischenmenschlicher Ebene diskutiert.
Medical imaging plays an important role in disease diagnosis, treatment planning, and clinical monitoring. One of the major challenges in medical image analysis is imbalanced training data, in which the class of interest is much rarer than the other classes. Canonical machine learning algorithms suppose that the number of samples from different classes in the training dataset is roughly similar or balance. Training a machine learning model on an imbalanced dataset can introduce unique challenges to the learning problem.
A model learned from imbalanced training data is biased towards the high-frequency samples. The predicted results of such networks have low sensitivity and high precision. In medical applications, the cost of misclassification of the minority class could be more than the cost of misclassification of the majority class. For example, the risk of not detecting a tumor could be much higher than referring to a healthy subject to a doctor. The current Ph.D. thesis introduces several deep learning-based approaches for handling class imbalanced problems for learning multi-task such as disease classification and semantic segmentation.
At the data-level, the objective is to balance the data distribution through re-sampling the data space: we propose novel approaches to correct internal bias towards fewer frequency samples. These approaches include patient-wise batch sampling, complimentary labels, supervised and unsupervised minority oversampling using generative adversarial networks for all.
On the other hand, at algorithm-level, we modify the learning algorithm to alleviate the bias towards majority classes. In this regard, we propose different generative adversarial networks for cost-sensitive learning, ensemble learning, and mutual learning to deal with highly imbalanced imaging data.
We show evidence that the proposed approaches are applicable to different types of medical images of varied sizes on different applications of routine clinical tasks, such as disease classification and semantic segmentation. Our various implemented algorithms have shown outstanding results on different medical imaging challenges.
Business process management (BPM) deals with modeling, executing, monitoring, analyzing, and improving business processes. During execution, the process communicates with its environment to get relevant contextual information represented as events. Recent development of big data and the Internet of Things (IoT) enables sources like smart devices and sensors to generate tons of events which can be filtered, grouped, and composed to trigger and drive business processes.
The industry standard Business Process Model and Notation (BPMN) provides several event constructs to capture the interaction possibilities between a process and its environment, e.g., to instantiate a process, to abort an ongoing activity in an exceptional situation, to take decisions based on the information carried by the events, as well as to choose among the alternative paths for further process execution. The specifications of such interactions are termed as event handling. However, in a distributed setup, the event sources are most often unaware of the status of process execution and therefore, an event is produced irrespective of the process being ready to consume it. BPMN semantics does not support such scenarios and thus increases the chance of processes getting delayed or getting in a deadlock by missing out on event occurrences which might still be relevant.
The work in this thesis reviews the challenges and shortcomings of integrating real-world events into business processes, especially the subscription management. The basic integration is achieved with an architecture consisting of a process modeler, a process engine, and an event processing platform. Further, points of subscription and unsubscription along the process execution timeline are defined for different BPMN event constructs. Semantic and temporal dependencies among event subscription, event occurrence, event consumption and event unsubscription are considered. To this end, an event buffer with policies for updating the buffer, retrieving the most suitable event for the current process instance, and reusing the event has been discussed that supports issuing of early subscription.
The Petri net mapping of the event handling model provides our approach with a translation of semantics from a business process perspective. Two applications based on this formal foundation are presented to support the significance of different event handling configurations on correct process execution and reachability of a process path. Prototype implementations of the approaches show that realizing flexible event handling is feasible with minor extensions of off-the-shelf process engines and event platforms.
Back pain is a problem in adolescent athletes affecting postural control which is an important requirement for physical and daily activities whether under static or dynamic conditions. One leg stance and star excursion balance postural control tests are effective in measuring static and dynamic postural control respectively. These tests have been used in individuals with back pain, athletes and non-athletes without first establishing their reliabilities. In addition to this, there is no published literature investigating dynamic posture in adolescent athletes with back pain using the star excursion balance test. Therefore, the aim of the thesis was to assess deficit in postural control in adolescent athletes with and without back pain using static (one leg stance test) and dynamic postural (SEBT) control tests.
Adolescent athletes with and without back pain participated in the study. Static and dynamic postural control tests were performed using one leg stance and SEBT respectively. The reproducibility of both tests was established. Afterwards, it was determined whether there was an association between static and dynamic posture using the measure of displacement of the centre pressure and reach distance respectively. Finally, it was investigated whether there was a difference in postural control in adolescent athletes with and without back pain using the one leg stance test and the SEBT.
Fair to excellent reliabilities was recorded for the static (one leg stance) and dynamic (star excursion balance) postural control tests in the subjects of interest. No association was found between variables of the static and dynamic tests for the adolescent athletes with and without back pain. Also, no statistically significant difference was obtained between adolescent athletics with and without back pain using the static and dynamic postural control test.
One leg stance test and SEBT can be used as measures of postural control in adolescent athletes with and without back pain. Although static and dynamic postural control might be related, adolescent athletes with and without back pain might be using different mechanisms in controlling their static and dynamic posture. Consequently, static and dynamic postural control in adolescent athletes with back pain was not different from those without back pain. These outcome measures might not be challenging enough to detect deficit in postural control in our study group of interest.
Ultrafast magnetisation dynamics have been investigated intensely for two decades. The recovery process after demagnetisation, however, was rarely studied experimentally and discussed in detail. The focus of this work lies on the investigation of the magnetisation on long timescales after laser excitation. It combines two ultrafast time resolved methods to study the relaxation of the magnetic and lattice system after excitation with a high fluence ultrashort laser pulse. The magnetic system is investigated by time resolved measurements of the magneto-optical Kerr effect. The experimental setup has been implemented in the scope of this work. The lattice dynamics were obtained with ultrafast X-ray diffraction. The combination of both techniques leads to a better understanding of the mechanisms involved in magnetisation recovery from a non-equilibrium condition. Three different groups of samples are investigated in this work: Thin Nickel layers capped with nonmagnetic materials, a continuous sample of the ordered L10 phase of Iron Platinum and a sample consisting of Iron Platinum nanoparticles embedded in a carbon matrix. The study of the remagnetisation reveals a general trend for all of the samples: The remagnetisation process can be described by two time dependences. A first exponential recovery that slows down with an increasing amount of energy absorbed in the system until an approximately linear time dependence is observed. This is followed by a second exponential recovery. In case of low fluence excitation, the first recovery is faster than the second. With increasing fluence the first recovery is slowed down and can be described as a linear function. If the pump-induced temperature increase in the sample is sufficiently high, a phase transition to a paramagnetic state is observed. In the remagnetisation process, the transition into the ferromagnetic state is characterised by a distinct transition between the linear and exponential recovery. From the combination of the transient lattice temperature Tp(t) obtained from ultrafast X-ray measurements and magnetisation M(t) gained from magneto-optical measurements we construct the transient magnetisation versus temperature relations M(Tp). If the lattice temperature remains below the Curie temperature the remagnetisation curve M(Tp) is linear and stays below the M(T) curve in equilibrium in the continuous transition metal layers. When the sample is heated above phase transition, the remagnetisation converges towards the static temperature dependence. For the granular Iron Platinum sample the M(Tp) curves for different fluences coincide, i.e. the remagnetisation follows a similar path irrespective of the initial laser-induced temperature jump.
In the era of social networks, internet of things and location-based services, many online services produce a huge amount of data that have valuable objective information, such as geographic coordinates and date time. These characteristics (parameters) in the combination with a textual parameter bring the challenge for the discovery of geospatiotemporal knowledge. This challenge requires efficient methods for clustering and pattern mining in spatial, temporal and textual spaces.
In this thesis, we address the challenge of providing methods and frameworks for geospatiotemporal data analytics. As an initial step, we address the challenges of geospatial data processing: data gathering, normalization, geolocation, and storage. That initial step is the basement to tackle the next challenge -- geospatial clustering challenge. The first step of this challenge is to design the method for online clustering of georeferenced data. This algorithm can be used as a server-side clustering algorithm for online maps that visualize massive georeferenced data. As the second step, we develop the extension of this method that considers, additionally, the temporal aspect of data. For that, we propose the density and intensity-based geospatiotemporal clustering algorithm with fixed distance and time radius.
Each version of the clustering algorithm has its own use case that we show in the thesis.
In the next chapter of the thesis, we look at the spatiotemporal analytics from the perspective of the sequential rule mining challenge. We design and implement the framework that transfers data into textual geospatiotemporal data - data that contain geographic coordinates, time and textual parameters. By this way, we address the challenge of applying pattern/rule mining algorithms in geospatiotemporal space. As the applicable use case study, we propose spatiotemporal crime analytics -- discovery spatiotemporal patterns of crimes in publicly available crime data.
The second part of the thesis, we dedicate to the application part and use case studies. We design and implement the application that uses the proposed clustering algorithms to discover knowledge in data. Jointly with the application, we propose the use case studies for analysis of georeferenced data in terms of situational and public safety awareness.
Due to advances in science and technology towards smaller and more powerful processing units, the fabrication of micrometer sized machines for different tasks becomes more and more possible. Such micro-robots could revolutionize medical treatment of diseases and shall support to work on other small machines. Nevertheless, scaling down robots and other devices is a challenging task and will probably remain limited in near future. Over the past decade the concept of bio-hybrid systems has proved to be a promising approach in order to advance the further development of micro-robots. Bio-hybrid systems combine biological cells with artificial components, thereby benefiting from the functionality of living biological cells. Cell-driven micro-transport is one of the most prominent applications in the emerging field of these systems. So far, micrometer sized cargo has been successfully transported by means of swimming bacterial cells. The potential of motile adherent cells as transport systems has largely remained unexplored.
This thesis concentrates on the social amoeba Dictyostelium discoideum as a potential candidate for an amoeboid bio-hybrid transport system. The use of this model organism comes with several advantages. Due to the unspecific properties of Dictyostelium adhesion, a wide range of different cargo materials can be used for transport. As amoeboid cells exceed bacterial cells in size by one order of magnitude, also the size of an object carried by a single cell can also be much larger for an amoeba. Finally it is possible to guide the cell-driven transport based on the chemotactic behavior of the amoeba. Since cells undergo a developmentally induced chemotactic aggregation, cargo could be assembled in a self-organized manner into a cluster. It is also possible to impose an external chemical gradient to guide the amoeboid transport system to a desired location.
To establish Dictyostelium discoideum as a possible candidate for bio-hybrid transport systems, this thesis will first investigate the movement of single cells. Secondly, the interaction of cargo and cells will be studied. Eventually, a conceptional proof will be conducted, that the cheomtactic behavior can be exploited either to transport a cargo self-organized or through an external chemical source.
Frailty and sarcopenia share some underlying characteristics like loss of muscle mass, low muscle strength, and low physical performance. Imaging parameters and functional examinations mainly assess frailty and sarcopenia criteria; however, these measures can have limitations in clinical settings. Therefore, finding suitable biomarkers that reflect a catabolic muscle state e.g. an elevated muscle protein turnover as suggested in frailty, are becoming more relevant concerning frailty diagnosis and risk assessment.
3-Methylhistidine (3-MH) and its ratios 3-MH-to-creatinine (3-MH/Crea) and 3 MH-to-estimated glomerular filtration rate (3-MH/eGFR) are under discussion as possible biomarkers for muscle protein turnover and might support the diagnosis of frailty. However, there is some skepticism about the reliability of 3-MH measures since confounders such as meat and fish intake might influence 3-MH plasma concentrations. Therefore, the influence of dietary habits and an intervention with white meat on plasma 3-MH was determined in young and healthy individuals. In another study, the cross-sectional associations of plasma 3-MH, 3-MH/Crea and 3-MH/eGFR with the frailty status (robust, pre-frail and frail) were investigated.
Oxidative stress (OS) is a possible contributor to frailty development, and high OS levels as well as low micronutrient levels are associated with the frailty syndrome. However, data on simultaneous measures of OS biomarkers together with micronutrients are lacking in studies including frail, pre-frail and robust individuals. Therefore, cross-sectional associations of protein carbonyls (PrCarb), 3-nitrotyrosine (3-NT) and several micronutrients with the frailty status were determined.
A validated UPLC-MS/MS (ultra-performance liquid chromatography tandem mass spectrometry) method for the simultaneous quantification of 3-MH and 1-MH (1 methylhistidine, as marker for meat and fish consumption) was presented and used for further analyses. Omnivores showed higher plasma 3-MH and 1-MH concentrations than vegetarians and a white meat intervention resulted in an increase in plasma 3-MH, 3 MH/Crea, 1-MH and 1-MH/Crea in omnivores. Elevated 3-MH and 3-MH/Crea levels declined significantly within 24 hours after this white meat intervention. Thus, 3-MH and 3-MH/Crea might be used as biomarker for muscle protein turnover when subjects did not consume meat 24 hours prior to blood samplings.
Plasma 3-MH, 3-MH/Crea and 3-MH/eGFR were higher in frail individuals than in robust individuals. Additionally, these biomarkers were positively associated with frailty in linear regression models, and higher odds to be frail were found for every increase in 3 MH and 3-MH/eGFR quintile in multivariable logistic regression models adjusted for several confounders. This was the first study using 3-MH/eGFR and it is concluded that plasma 3-MH, 3-MH/Crea and 3-MH/eGFR might be used to identify frail individuals or individuals at higher risk to be frail, and that there might be threshold concentrations or ratios to support these diagnoses.
Higher vitamin D3, lutein/zeaxanthin, γ-tocopherol, α-carotene, β-carotene, lycopene and β-cryptoxanthin concentrations and additionally lower PrCarb concentrations were found in robust compared to frail individuals in multivariate linear models. Frail subjects had higher odds to be in the lowest than in the highest tertile for vitamin D3 α-tocopherol, α-carotene, β-carotene, lycopene, lutein/zeaxanthin, and β cryptoxanthin, and had higher odds to be in the highest than in the lowest tertile for PrCarb than robust individuals in multivariate logistic regression models. Thus, a low micronutrient together with a high PrCarb status is associated with pre-frailty and frailty.
The increasing age of worldwide population is a major contributor for the rising prevalence of major pathologies and disease, such as type 2 diabetes, mediated by massive insulin resistance and a decline in functional beta-cell mass, highly associated with an elevated incidence of obesity. Thus, the impact of aging under physiological conditions and in combination with diet-induced metabolic stress on characteristics of pancreatic islets and beta-cells, with the focus on functionality and structural integrity, were investigated in the present dissertation.
Primarily induced by malnutrition due to chronic and excess intake of high caloric diets, containing large amounts of carbohydrates and fats, obesity followed by systemic inflammation and peripheral insulin resistance occurs over time, initiating metabolic stress conditions. Elevated insulin demands initiate an adaptive response by beta-cell mass expansion due to increased proliferation, but prolonged stress conditions drive beta-cell failure and loss. Aging has been also shown to affect beta-cell functionality and morphology, in particular by proliferative limitations. However, most studies in rodents were performed under beta-cell challenging conditions, such as high-fat diet interventions. Thus, in the first part of the thesis (publication I), a characterization of age-related alterations on pancreatic islets and beta-cells was performed by using plasma samples and pancreatic tissue sections of standard diet-fed C57BL/6J wild-type mice in several age groups (2.5, 5, 10, 15 and 21 months).
Aging was accompanied by decreased but sustained islet proliferative potential as well as an induction of cellular senescence. This was associated with a progressive islet expansion to maintain normoglycemia throughout lifespan. Moreover, beta-cell function and mass were not impaired although the formation and accumulation of AGEs occurred, located predominantly in the islet vasculature, accompanied by an induction of oxidative and nitrosative (redox) stress.
The nutritional behavior throughout human lifespan; however, is not restricted to a balanced diet. This emphasizes the significance to investigate malnutrition by the intake of high-energy diets, inducing metabolic stress conditions that synergistically with aging might amplify the detrimental effects on endocrine pancreas. Using diabetes-prone NZO mice aged 7 weeks, fed a dietary regimen of carbohydrate restriction for different periods (young mice - 11 weeks, middle-aged mice - 32 weeks) followed by a carbohydrate intervention for 3 weeks, offered the opportunity to distinguish the effects of diet-induced metabolic stress in different ages on the functionality and integrity of pancreatic islets and their beta-cells (publication II, manuscript).
Interestingly, while young NZO mice exhibited massive hyperglycemia in response to diet-induced metabolic stress accompanied by beta-cell dysfunction and apoptosis, middle-aged animals revealed only moderate hyperglycemia by the maintenance of functional beta-cells. The loss of functional beta-cell mass in islets of young mice was associated with reduced expression of PDX1 transcription factor, increased endocrine AGE formation and related redox stress as well as TXNIP-dependent induction of the mitochondrial death pathway. Although the amounts of secreted insulin and the proliferative potential were comparable in both age groups, islets of middle-aged mice exhibited sustained PDX1 expression, almost regular insulin secretory function, increased capacity for cell cycle progression as well as maintained redox potential.
The results of the present thesis indicate a loss of functional beta-cell mass in young diabetes-prone NZO mice, occurring by redox imbalance and induction of apoptotic signaling pathways. In contrast, aging under physiological conditions in C57BL/6J mice and in combination with diet-induced metabolic stress in NZO mice does not appear to have adverse effects on the functionality and structural integrity of pancreatic islets and beta-cells, associated with adaptive responses on changing metabolic demands. However, considering the detrimental effects of aging, it has to be assumed that the compensatory potential of mice might be exhausted at a later point of time, finally leading to a loss of functional beta-cell mass and the onset and progression of type 2 diabetes.
The polygenic, diabetes-prone NZO mouse is a suitable model for the investigation of human obesity-associated type 2 diabetes. However, mice at advanced age attenuated the diabetic phenotype or do not respond to the dietary stimuli. This might be explained by the middle age of mice, corresponding to the human age of about 38-40 years, in which the compensatory mechanisms of pancreatic islets and beta cells towards metabolic stress conditions are presumably more active.
Analysis of supramolecular assemblies of NE81, the first lamin protein in a non-metazoan organism
(2019)
Nuclear lamins are nucleus-specific intermediate filaments forming a network located at the inner nuclear membrane of the nuclear envelope. They form the nuclear lamina together with proteins of the inner nuclear membrane regulating nuclear shape and gene expression, among others. The amoebozoan Dictyostelium NE81 protein is a suitable candidate for an evolutionary conserved lamin protein in this non-metazoan organism. It shares the domain organization of metazoan lamins and is fulfilling major lamin functions in Dictyostelium. Moreover, field-emission scanning electron microscopy (feSEM) images of NE81 expressed on Xenopus oocytes nuclei revealed filamentous structures with an overall appearance highly reminiscent to that of metazoan Xenopus lamin B2. For the classification as a lamin-like or a bona fide lamin protein, a better understanding of the supramolecular NE81 structure was necessary. Yet, NE81 carrying a large N-terminal GFP-tag turned out as unsuitable source for protein isolation and characterization; GFP-NE81 expressed in Dictyostelium NE81 knock-out cells exhibited an abnormal distribution, which is an indicator for an inaccurate assembly of GFP-tagged NE81. Hence, a shorter 8×HisMyc construct was the tag of choice to investi-gate formation and structure of NE81 assemblies. One strategy was the structural analysis of NE81 in situ at the outer nuclear membrane in Dictyostelium cells; NE81 without a func-tional nuclear localization signal (NLS) forms assemblies at the outer face of the nucleus. Ultrastructural feSEM pictures of NE81ΔNLS nuclei showed a few filaments of the expected size but no repetitive filamentous structures. The former strategy should also be established for metazoan lamins in order to facilitate their structural analysis. However, heterologously expressed Xenopus and C. elegans lamins showed no uniform localization at the outer nucle-ar envelope of Dictyostelium and hence, no further ultrastructural analysis was undertaken. For in vitro assembly experiments a Dictyostelium mutant was generated, expressing NE81 without the NLS and the membrane-anchoring isoprenylation site (HisMyc-NE81ΔNLSΔCLIM). The cytosolic NE81 clusters were soluble at high ionic strength and were purified from Dictyostelium extracts using Ni-NTA Agarose. Widefield immunofluorescence microscopy, super-resolution light microscopy and electron microscopy images of purified NE81 showed its capability to form filamentous structures at low ionic strength, as described previously for metazoan lamins. Introduction of a phosphomimetic point mutation (S122E) into the CDK1-consensus sequence of NE81 led to disassembled NE81 protein in vivo, which could be reversibly stimulated to form supramolecular assemblies by blue light exposure.
The results of this work reveal that NE81 has to be considered a bona fide lamin, since it is able to form filamentous assemblies. Furthermore, they highlight Dictyostelium as a non-mammalian model organism with a well-characterized nuclear envelope containing all rele-vant protein components known in animal cells.
Introduction: Cystic fibrosis (CF) is a genetic disease which disrupts the function of an epithelial surface anion channel, CFTR (cystic fibrosis transmembrane conductance regulator). Impairment to this channel leads to inflammation and infection in the lung causing the majority of morbidity and mortality. However, CF is a multiorgan disease affecting many tissues, including vascular smooth muscle. Studies have revealed young people with cystic fibrosis lacking inflammation and infection still demonstrate vascular endothelial dysfunction, measured per flow-mediated dilation (FMD). In other disease cohorts, i.e. diabetic and obese, endurance exercise interventions have been shown improve or taper this impairment. However, long-term exercise interventions are risky, as well as costly in terms of time and resources. Nevertheless, emerging research has correlated the acute effects of exercise with its long-term benefits and advocates the study of acute exercise effects on FMD prior to longitudinal studies. The acute effects of exercise on FMD have previously not been examined in young people with CF, but could yield insights on the potential benefits of long-term exercise interventions.
The aims of these studies were to 1) develop and test the reliability of the FMD method and its applicability to study acute exercise effects; 2) compare baseline FMD and the acute exercise effect on FMD between young people with and without CF; and 3) explore associations between the acute effects of exercise on FMD and demographic characteristics, physical activity levels, lung function, maximal exercise capacity or inflammatory hsCRP levels.
Methods: Thirty young volunteers (10 people with CF, 10 non-CF and 10 non-CF active matched controls) between the ages of 10 and 30 years old completed blood draws, pulmonary function tests, maximal exercise capacity tests and baseline FMD measurements, before returning approximately 1 week later and performing a 30-min constant load training at 75% HRmax. FMD measurements were taken prior, immediately after, 30 minutes after and 1 hour after constant load training. ANOVAs and repeated measures ANOVAs were employed to explore differences between groups and timepoints, respectively. Linear regression was implemented and evaluated to assess correlations between FMD and demographic characteristics, physical activity levels, lung function, maximal exercise capacity or inflammatory hsCRP levels. For all comparisons, statistical significance was set at a p-value of α < 0.05.
Results: Young people with CF presented with decreased lung function and maximal exercise capacity compared to matched controls. Baseline FMD was also significantly decreased in the CF group (CF: 5.23% v non-CF: 8.27% v non-CF active: 9.12%). Immediately post-training, FMD was significantly attenuated (approximately 40%) in all groups with CF still demonstrating the most minimal FMD. Follow-up measurements of FMD revealed a slow recovery towards baseline values 30 min post-training and improvements in the CF and non-CF active groups 60 min post-training. Linear regression exposed significant correlations between maximal exercise capacity (VO2 peak), BMI and FMD immediately post-training.
Conclusion: These new findings confirm that CF vascular endothelial dysfunction can be acutely modified by exercise and will aid in underlining the importance of exercise in CF populations. The potential benefits of long-term exercise interventions on vascular endothelial dysfunction in young people with CF warrants further investigation.
Die vorliegende Forschungsarbeit untersucht den Umgang mit Dilemmata von Topmanagern. Dilemmata sind ein alltägliches Geschäft im Topmanagement. Die entsprechenden Akteure sind daher immer wieder mit diesen konfrontiert und mit ihnen umzugehen, gehört gewissermaßen zu ihrer Berufsbeschreibung. Hinzu kommen Dilemmata im nicht direkt geschäftlichen Bereich, wie zum Beispiel jene zwischen Familien- und Arbeitszeit. Doch stellt dieses Feld ein kaum untersuchtes Forschungsgebiet dar. Während Dilemmata in anderen Bereichen eine zunehmende Aufmerksamkeit erfuhren, wurden deren Besonderheiten im Topmanagement genauso wenig differenziert betrachtet wie zugehörige Umgangsweisen. Theorie und Praxis stellen bezüglich Dilemmata von Topmanagern vor allem einen Gegensatz dar, beziehungsweise fehlt es an einer theoretischen Fundierung der Empirie. Diesem Umstand wird mittels dieser Studie begegnet. Auf der Grundlage einer differenzierten und breiten Erfassung von Theorien zu Dilemmata, so diese auch noch nicht auf Topmanager bezogen wurden, und einer empirischen Erhebung, die im Mittelpunkt dieser Arbeit stehen, soll das Feld Dilemmata von Topmanagern der Forschung geöffnet werden. Empirische Grundlage sind vor allem narrative Interviews mit Topmanagern über ihre Dilemmata-Wahrnehmung, ausgemachte Ursachen, Umgangsweisen und Resultate. Dies erlaubt es, Topmanagertypen sowie Dilemmata-Arten, mit denen sie konfrontiert sind oder waren, analytisch herauszuarbeiten. Angesichts der Praxisrelevanz von Dilemmata von Topmanagern wird jedoch nicht nur ein theoretisches Modell zu dieser Thematik erarbeitet, es werden auch Reflexionen auf die Praxis in Form von Handlungsempfehlungen vorgenommen. Schließlich gilt es, die allgemeine Theorie zu Dilemmata, ohne konkreten Bezug zu Topmanagern, mit den theoretischen Erkenntnissen dieser Studie auf empirischer Basis zu kontrastieren. Dabei wird im Rahmen der empirischen Erfassung und Auswertung dem Ansatz der Grounded-Theory-Methodologie gefolgt.
Im Rahmen dieser Dissertation konnten neue Kalium- und Natrium-Ionen Fluoreszenzfarbstoffe von der Klasse der Fluoroionophore synthetisiert und charakterisiert werden. Sie bestehen aus einem N Phenylazakronenether als Ionophor und unterschiedlichen Fluorophoren und sind über einen π-konjugierten 1,2,3-Triazol-1,4-diyl Spacer verbunden. Dabei lag der Fokus während ihrer Entwicklung darauf, diese in ihrer Sensitivität, Selektivität und in ihren photophysikalischen Eigenschaften so zu funktionalisieren, dass sie für intra- bzw. extrazelluläre Konzentrationsbestimmungen geeignet sind.
Durch Variation der in ortho Position der N-Phenylazakronenether befindlichen Alkoxy-Gruppen und der fluorophoren Gruppe der Fluoroionophore konnte festgestellt werden, dass die Sensitivität und Selektivität für Kalium- bzw. Natrium-Ionen jeweils durch eine bestimmte Isomerie der 1,2,3-Triazol-1,4-diyl-Einheit erhöht wird. Des Weiteren wurde gezeigt, dass durch eine erhöhte Einschränkung der N,N-Diethylamino-Gruppe des Fluorophors eine Steigerung der Fluoreszenzquantenausbeute und eine Verschiebung des Emissionsmaximums auf über 500 nm erreicht werden konnte. Die Einführung einer Isopropoxy-Gruppe an einem N-Phenylaza-[18]krone-6-ethers resultierte dabei in einem hoch selektiven Kalium-Ionen Fluoroionophor und ermöglichte eine in vitro Überwachung von 10 – 80 mM Kalium-Ionen. Die Substitution einer Methoxy-Gruppe an einem N-Phenylaza-[15]krone-5-ether kombiniert mit unterschiedlich N,N-Diethylamino-Coumarinen lieferte hingegen zwei Natrium-Ionen Fluoroionophore, die für die Überwachung von intra- bzw. extrazellulären Natrium-Ionen Konzentrationen geeignet sind.
In einem weiteren Schritt wurden N-Phenylaza-[18]krone-6-ether mit einem Fluorophor, basierend auf einem [1,3]-Dioxolo[4,5-f][1,3]benzodioxol-(DBD)-Grundgerüst, funktionalisiert. Die im Anschluss durchgeführten spektroskopischen Untersuchungen ergaben, dass die Isopropoxy-Gruppe in ortho Position des N-Phenylaza-[18]krone-6-ether in einen für extrazelluläre Kalium-Ionen Konzentrationen selektiven Fluoroionophor resultierte, der die Konzentrationsbestimmungen über die Fluoreszenzintensität und -lebensdauer ermöglicht.
In einem abschließenden Schritt konnte unter Verwendung eines Pyrens als fluorophore Gruppe ein weiterer für extrazelluläre Kalium-Ionen Konzentrationen geeigneter Fluoroionophor entwickelt werden. Die Bestimmung der Kalium-Ionen Konzentration erfolgte hierbei anhand der Fluoreszenzintensitätsverhältnisse bei zwei Emissionswellenlängen.
Insgesamt konnten 17 verschiedene neue Fluoroionophore für die Bestimmung von Kalium- bzw. Natrium-Ionen synthetisiert und charakterisiert werden. Sechs dieser neuen Moleküle ermöglichen in vitro Messungen der intra- oder extrazellulären Kalium- und Natrium-Ionen Konzentrationen und könnten zukünftig für in vivo Konzentrationsmessungen verwendet werden.
Cellulose derived polymers
(2019)
Plastics, such as polyethylene, polypropylene, and polyethylene terephthalate are part of our everyday lives in the form of packaging, household goods, electrical insulation, etc. These polymers are non-degradable and create many environmental problems and public health concerns. Additionally, these polymers are produced from finite fossils resources. With the continuous utilization of these limited resources, it is important to look towards renewable sources along with biodegradation of the produced polymers, ideally. Although many bio-based polymers are known, such as polylactic acid, polybutylene succinate adipate or polybutylene succinate, none have yet shown the promise of replacing conventional polymers like polyethylene, polypropylene and polyethylene terephthalate. Cellulose is one of the most abundant renewable resources produced in nature. It can be transformed into various small molecules, such as sugars, furans, and levoglucosenone. The aim of this research is to use the cellulose derived molecules for the synthesis of polymers.
Acid-treated cellulose was subjected to thermal pyrolysis to obtain levoglucosenone, which was reduced to levoglucosenol. Levoglucosenol was polymerized, for the first time, by ring-opening metathesis polymerization (ROMP) yielding high molar mass polymers of up to ~150 kg/mol. The poly(levoglucosenol) is thermally stable up to ~220 ℃, amorphous, and is exhibiting a relatively high glass transition temperature of ~100 ℃. The poly(levoglucosenol) can be converted to a transparent film, resembling common plastic, and was found to degrade in a moist acidic environment. This means that poly(levoglucosenol) may find its use as an alternative to conventional plastic, for instance, polystyrene.
Levoglucosenol was also converted into levoglucosenyl methyl ether, which was polymerized by cationic ring-opening metathesis polymerization (CROP). Polymers were obtained with molar masses up to ~36 kg/mol. These polymers are thermally stable up to ~220 ℃ and are semi-crystalline thermoplastics, having a glass transition temperature of ~35 ℃ and melting transition of 70-100 ℃. Additionally, the polymers underwent cross-linking, hydrogenation and thiol-ene click chemistry.
Risiken für Cyberressourcen können durch unbeabsichtigte oder absichtliche Bedrohungen entstehen. Dazu gehören Insider-Bedrohungen von unzufriedenen oder nachlässigen Mitarbeitern und Partnern, eskalierende und aufkommende Bedrohungen aus aller Welt, die stetige Weiterentwicklung der Angriffstechnologien und die Entstehung neuer und zerstörerischer Angriffe. Informationstechnik spielt mittlerweile in allen Bereichen des Lebens eine entscheidende Rolle, u. a. auch im Bereich des Militärs. Ein ineffektiver Schutz von Cyberressourcen kann hier Sicherheitsvorfälle und Cyberattacken erleichtern, welche die kritischen Vorgänge stören, zu unangemessenem Zugriff, Offenlegung, Änderung oder Zerstörung sensibler Informationen führen und somit die nationale Sicherheit, das wirtschaftliche Wohlergehen sowie die öffentliche Gesundheit und Sicherheit gefährden. Oftmals ist allerdings nicht klar, welche Bedrohungen konkret vorhanden sind und welche der kritischen Systemressourcen besonders gefährdet ist.
In dieser Dissertation werden verschiedene Analyseverfahren für Bedrohungen in militärischer Informationstechnik vorgeschlagen und in realen Umgebungen getestet. Dies bezieht sich auf Infrastrukturen, IT-Systeme, Netze und Anwendungen, welche Verschlusssachen (VS)/Staatsgeheimnisse verarbeiten, wie zum Beispiel bei militärischen oder Regierungsorganisationen. Die Besonderheit an diesen Organisationen ist das Konzept der Informationsräume, in denen verschiedene Datenelemente, wie z. B. Papierdokumente und Computerdateien, entsprechend ihrer Sicherheitsempfindlichkeit eingestuft werden, z. B. „STRENG GEHEIM“, „GEHEIM“, „VS-VERTRAULICH“, „VS-NUR-FÜR-DEN-DIENSTGEBRAUCH“ oder „OFFEN“.
Die Besonderheit dieser Arbeit ist der Zugang zu eingestuften Informationen aus verschiedenen Informationsräumen und der Prozess der Freigabe dieser. Jede in der Arbeit entstandene Veröffentlichung wurde mit Angehörigen in der Organisation besprochen, gegengelesen und freigegeben, so dass keine eingestuften Informationen an die Öffentlichkeit gelangen.
Die Dissertation beschreibt zunächst Bedrohungsklassifikationsschemen und Angreiferstrategien, um daraus ein ganzheitliches, strategiebasiertes Bedrohungsmodell für Organisationen abzuleiten. Im weiteren Verlauf wird die Erstellung und Analyse eines Sicherheitsdatenflussdiagramms definiert, welches genutzt wird, um in eingestuften Informationsräumen operationelle Netzknoten zu identifizieren, die aufgrund der Bedrohungen besonders gefährdet sind. Die spezielle, neuartige Darstellung ermöglicht es, erlaubte und verbotene Informationsflüsse innerhalb und zwischen diesen Informationsräumen zu verstehen.
Aufbauend auf der Bedrohungsanalyse werden im weiteren Verlauf die Nachrichtenflüsse der operationellen Netzknoten auf Verstöße gegen Sicherheitsrichtlinien analysiert und die Ergebnisse mit Hilfe des Sicherheitsdatenflussdiagramms anonymisiert dargestellt. Durch Anonymisierung der Sicherheitsdatenflussdiagramme ist ein Austausch mit externen Experten zur Diskussion von Sicherheitsproblematiken möglich.
Der dritte Teil der Arbeit zeigt, wie umfangreiche Protokolldaten der Nachrichtenflüsse dahingehend untersucht werden können, ob eine Reduzierung der Menge an Daten möglich ist. Dazu wird die Theorie der groben Mengen aus der Unsicherheitstheorie genutzt. Dieser Ansatz wird in einer Fallstudie, auch unter Berücksichtigung von möglichen auftretenden Anomalien getestet und ermittelt, welche Attribute in Protokolldaten am ehesten redundant sind.
Continuous insight into biological processes has led to the development of large-scale, mechanistic systems biology models of pharmacologically relevant networks. While these models are typically designed to study the impact of diverse stimuli or perturbations on multiple system variables, the focus in pharmacological research is often on a specific input, e.g., the dose of a drug, and a specific output related to the drug effect or response in terms of some surrogate marker.
To study a chosen input-output pair, the complexity of the interactions as well as the size of the models hinders easy access and understanding of the details of the input-output relationship.
The objective of this thesis is the development of a mathematical approach, in specific a model reduction technique, that allows (i) to quantify the importance of the different state variables for a given input-output relationship, and (ii) to reduce the dynamics to its essential features -- allowing for a physiological interpretation of state variables as well as parameter estimation in the statistical analysis of clinical data. We develop a model reduction technique using a control theoretic setting by first defining a novel type of time-limited controllability and observability gramians for nonlinear systems. We then show the superiority of the time-limited generalised gramians for nonlinear systems in the context of balanced truncation for a benchmark system from control theory.
The concept of time-limited controllability and observability gramians is subsequently used to introduce a state and time-dependent quantity called the input-response (ir) index that quantifies the importance of state variables for a given input-response relationship at a particular time.
We subsequently link our approach to sensitivity analysis, thus, enabling for the first time the use of sensitivity coefficients for state space reduction. The sensitivity based ir-indices are given as a product of two sensitivity coefficients. This allows not only for a computational more efficient calculation but also for a clear distinction of the extent to which the input impacts a state variable and the extent to which a state variable impacts the output.
The ir-indices give insight into the coordinated action of specific state variables for a chosen input-response relationship.
Our developed model reduction technique results in reduced models that still allow for a mechanistic interpretation in terms of the quantities/state variables of the original system, which is a key requirement in the field of systems pharmacology and systems biology and distinguished the reduced models from so-called empirical drug effect models. The ir-indices are explicitly defined with respect to a reference trajectory and thereby dependent on the initial state (this is an important feature of the measure). This is demonstrated for an example from the field of systems pharmacology, showing that the reduced models are very informative in their ability to detect (genetic) deficiencies in certain physiological entities. Comparing our novel model reduction technique to the already existing techniques shows its superiority.
The novel input-response index as a measure of the importance of state variables provides a powerful tool for understanding the complex dynamics of large-scale systems in the context of a specific drug-response relationship. Furthermore, the indices provide a means for a very efficient model order reduction and, thus, an important step towards translating insight from biological processes incorporated in detailed systems pharmacology models into the population analysis of clinical data.
This dissertation investigates the impact of the economic and fiscal crisis starting in 2008 on EU climate policy-making. While the overall number of adopted greenhouse gas emission reduction policies declined in the crisis aftermath, EU lawmakers decided to introduce new or tighten existing regulations in some important policy domains. Existing knowledge about the crisis impact on EU legislative decision-making cannot explain these inconsistencies. In response, this study develops an actor-centred conceptual framework based on rational choice institutionalism that provides a micro-level link to explain how economic crises translate into altered policy-making patterns. The core theoretical argument draws on redistributive conflicts, arguing that tensions between ‘beneficiaries’ and ‘losers’ of a regulatory initiative intensify during economic crises and spill over to the policy domain. To test this hypothesis and using social network analysis, this study analyses policy processes in three case studies: The introduction of carbon dioxide emission limits for passenger cars, the expansion of the EU Emissions Trading System to aviation, and the introduction of a regulatory framework for biofuels. The key finding is that an economic shock causes EU policy domains to polarise politically, resulting in intensified conflict and more difficult decision-making. The results also show that this process of political polarisation roots in the industry that is the subject of the regulation, and that intergovernmental bargaining among member states becomes more important, but also more difficult in times of crisis.