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This dissertation examines the impact of the type of referring expression on the acquisition of word order variation in German-speaking preschoolers. A puzzle in the area of language acquisition concerns the production-comprehension asymmetry for non-canonical sentences like "Den Affen fängt die Kuh." (“The monkey, the cow chases.”), that is, preschoolers usually have difficulties in accurately understanding non-canonical sentences approximately until age six (e.g., Dittmar et al., 2008) although they produce non-canonical sentences already around age three (e.g., Poeppel & Wexler, 1993; Weissenborn, 1990). This dissertation investigated the production and comprehension of non-canonical sentences to address this issue.
Three corpus analyses were conducted to investigate the impact of givenness, topic status and the type of referring expression on word order in the spontaneous speech of two- to four-year-olds and the child-directed speech produced by their mothers. The positioning of the direct object in ditransitive sentences was examined; in particular, sentences in which the direct object occurred before or after the indirect object in the sentence-medial positions and sentences in which it occurred in the sentence-initial position. The results reveal similar ordering patterns for children and adults. Word order variation was to a large extent predictable from the type of referring expression, especially with respect to the word order involving the sentence-medial positions. Information structure (e.g., topic status) had an additional impact only on word order variation that involved the sentence-initial position.
Two comprehension experiments were conducted to investigate whether the type of referring expression and topic status influences the comprehension of non-canonical transitive sentences in four- and five-year-olds. In the first experiment, the topic status of the one of the sentential arguments was established via a preceding context sentence, and in the second experiment, the type of referring expression for the sentential arguments was additionally manipulated by using either a full lexical noun phrase (NP) or a personal pronoun. The results demonstrate that children’s comprehension of non-canonical sentences improved when the topic argument was realized as a personal pronoun and this improvement was independent of the grammatical role of the arguments. However, children’s comprehension was not improved when the topic argument was realized as a lexical NP.
In sum, the results of both production and comprehension studies support the view that referring expressions may be seen as a sentence-level cue to word order and to the information status of the sentential arguments. The results highlight the important role of the type of referring expression on the acquisition of word order variation and indicate that the production-comprehension asymmetry is reduced when the type of referring expression is considered.
Light-triggered release of bioactive compounds from HA/PLL multilayer films for stimulation of cells
(2016)
The concept of targeting cells and tissues by controlled delivery of molecules is essential in the field of biomedicine. The layer-by-layer (LbL) technology for the fabrication of polymer multilayer films is widely implemented as a powerful tool to assemble tailor-made materials for controlled drug delivery. The LbL films can as well be engineered to act as mimics of the natural cellular microenvironment. Thus, due to the myriad possibilities such as controlled cellular adhesion and drug delivery offered by LbL films, it becomes easily achievable to direct the fate of cells by growing them on the films.
The aim of this work was to develop an approach for non-invasive and precise control of the presentation of bioactive molecules to cells. The strategy is based on employment of the LbL films, which function as support for cells and at the same time as reservoirs for bioactive molecules to be released in a controlled manner. UV light is used to trigger the release of the stored ATP with high spatio-temporal resolution. Both physico-chemical (competitive intermolecular interactions in the film) and biological aspects (cellular response and viability) are addressed in this study.
Biopolymers hyaluronic acid (HA) and poly-L-lysine (PLL) were chosen as the building blocks for the LbL film assembly. Poor cellular adhesion to native HA/PLL films as well as significant degradation by cells within a few days were shown. However, coating the films with gold nanoparticles not only improved cellular adhesion and protected the films from degradation, but also formed a size-exclusion barrier with adjustable cut-off in the size range of a few tens of kDa.
The films were shown to have high reservoir capacity for small charged molecules (reaching mM levels in the film). Furthermore, they were able to release the stored molecules in a sustained manner. The loading and release are explained by a mechanism based on interactions between charges of the stored molecules and uncompensated charges of the biopolymers in the film. Charge balance and polymer dynamics in the film play the pivotal role.
Finally, the concept of light-triggered release from the films has been proven using caged ATP loaded into the films from which ATP was released on demand. ATP induces a fast cellular response, i.e. increase in intracellular [Ca2+], which was monitored in real-time. Limitations of the cellular stimulation by the proposed approach are highlighted by studying the stimulation as a function of irradiation parameters (time, distance, light power). Moreover, caging molecules bind to the film stronger than ATP does, which opens new perspectives for the use of the most diverse chemical compounds as caging molecules.
Employment of HA/PLL films as a nouvelle support for cellular growth and hosting of bioactive molecules, along with the possibility to stimulate individual cells using focused light renders this approach highly efficient and unique in terms of precision and spatio-temporal resolution among those previously described. With its high potential, the concept presented herein provides the foundation for the design of new intelligent materials for single cell studies, with the focus on tissue engineering, diagnostics, and other cell-based applications.
Recently, due to an increasing demand on functionality and flexibility, beforehand isolated systems have become interconnected to gain powerful adaptive Systems of Systems (SoS) solutions with an overall robust, flexible and emergent behavior. The adaptive SoS comprises a variety of different system types ranging from small embedded to adaptive cyber-physical systems. On the one hand, each system is independent, follows a local strategy and optimizes its behavior to reach its goals. On the other hand, systems must cooperate with each other to enrich the overall functionality to jointly perform on the SoS level reaching global goals, which cannot be satisfied by one system alone. Due to difficulties of local and global behavior optimizations conflicts may arise between systems that have to be solved by the adaptive SoS.
This thesis proposes a modeling language that facilitates the description of an adaptive SoS by considering the adaptation capabilities in form of feedback loops as first class entities. Moreover, this thesis adopts the Models@runtime approach to integrate the available knowledge in the systems as runtime models into the modeled adaptation logic. Furthermore, the modeling language focuses on the description of system interactions within the adaptive SoS to reason about individual system functionality and how it emerges via collaborations to an overall joint SoS behavior. Therefore, the modeling language approach enables the specification of local adaptive system behavior, the integration of knowledge in form of runtime models and the joint interactions via collaboration to place the available adaptive behavior in an overall layered, adaptive SoS architecture.
Beside the modeling language, this thesis proposes analysis rules to investigate the modeled adaptive SoS, which enables the detection of architectural patterns as well as design flaws and pinpoints to possible system threats. Moreover, a simulation framework is presented, which allows the direct execution of the modeled SoS architecture. Therefore, the analysis rules and the simulation framework can be used to verify the interplay between systems as well as the modeled adaptation effects within the SoS. This thesis realizes the proposed concepts of the modeling language by mapping them to a state of the art standard from the automotive domain and thus, showing their applicability to actual systems. Finally, the modeling language approach is evaluated by remodeling up to date research scenarios from different domains, which demonstrates that the modeling language concepts are powerful enough to cope with a broad range of existing research problems.
Investigation of the TCA cycle and glycolytic metabolons and their physiological impacts in plants
(2016)
The increase in atmospheric methane concentration, which is determined by an imbalance between its sources and sinks, has led to investigations of the methane cycle in various environments. Aquatic environments are of an exceptional interest due to their active involvement in methane cycling worldwide and in particular in areas sensitive to climate change. Furthermore, being connected with each other aquatic environments form networks that can be spread on vast areas involving marine, freshwater and terrestrial ecosystems. Thus, aquatic systems have a high potential to translate local or regional environmental and subsequently ecosystem changes to a bigger scale. Many studies neglect this connectivity and focus on individual aquatic or terrestrial ecosystems.
The current study focuses on environmental controls of the distribution and aerobic oxidation of methane at the example of two aquatic ecosystems. These ecosystems are Arctic fresh water bodies and the Elbe estuary which represent interfaces between freshwater-terrestrial and freshwater-marine environments, respectively.
Arctic water bodies are significant atmospheric sources of methane. At the same time the methane cycle in Arctic water bodies is strongly affected by the surrounding permafrost environment, which is characterized by high amounts of organic carbon. The results of this thesis indicate that the methane concentrations in Arctic lakes and streams substantially vary between each other being regulated by local landscape features (e.g. floodplain area) and the morphology of the water bodies (lakes, streams and river). The highest methane concentrations were detected in the lake outlets and in a floodplain lake complex. In contrast, the methane concentrations measured at different sites of the Lena River did not vary substantially. The lake complexes in comparison to the Lena River, thus, appear as more individual and heterogeneous systems with a pronounced imprint of the surrounding soil environment. Furthermore, connected with each other Arctic aquatic environments have a large potential to transport methane from methane-rich water bodies such as streams and floodplain lakes to aquatic environments relatively poor in methane such as the Lena River.
Estuaries represent hot spots of oceanic methane emissions. Also, estuaries are intermediate zones between methane-rich river water and methane depleted marine water. Substantiated through this thesis at the example of the Elbe estuary, the methane distribution in estuaries, however, cannot entirely be described by the conservative mixing model i.e. gradual decrease from the freshwater end-member to the marine water end-member. In addition to the methane-rich water from the Elbe River mouth substantial methane input occurs from tidal flats, areas of significant interaction between aquatic and terrestrial environments. Thus, this study demonstrates the complex interactions and their consequences for the methane distribution within estuaries. Also it reveals how important it is to investigate estuaries at larger spatial scales.
Methane oxidation (MOX) rates are commonly correlated with methane concentrations. This was shown in previous research studies and was substantiated by the present thesis. In detail, the highest MOX rates in the Arctic water bodies were detected in methane-rich streams and in the floodplain area while in the Elbe estuary the highest MOX rates were observed at the coastal stations. However, in these bordering environments, MOX rates are affected not only via the regulation through methane concentrations. The MOX rates in the Arctic lakes were shown to be also dependent on the abundance and community composition of methane-oxidising bacteria (MOB), that in turn are controlled by local landscape features (regardless of the methane concentrations) and by the transport of MOB between neighbouring environments. In the Elbe estuary, the MOX rates in addition to the methane concentrations are largely affected by the salinity, which is in turn regulated by the mixing of fresh- and marine waters. The magnitude of the salinity impact on MOX rates thereby depends on the MOB community composition and on the rate of the salinity change.
This study extends our knowledge of environmental controls of methane distribution and aerobic methane oxidation in aquatic environments. It also illustrates how important it is to investigate complex ecosystems rather than individual ecosystems to better understand the functioning of whole biomes.
The energy sector is both affected by climate change and a key sector for climate protection measures. Energy security is the backbone of our modern society and guarantees the functioning of most critical infrastructure. Thus, decision makers and energy suppliers of different countries should be familiar with the factors that increase or decrease the susceptibility of their electricity sector to climate change. Susceptibility means socioeconomic and structural characteristics of the electricity sector that affect the demand for and supply of electricity under climate change. Moreover, the relevant stakeholders are supposed to know whether the given national energy and climate targets are feasible and what needs to be done in order to meet these targets. In this regard, a focus should be on the residential building sector as it is one of the largest energy consumers and therefore emitters of anthropogenic CO 2 worldwide.
This dissertation addresses the first aspect, namely the susceptibility of the electricity sector, by developing a ranked index which allows for quantitative comparison of the electricity sector susceptibility of 21 European countries based on 14 influencing factors. Such a ranking has not been completed to date. We applied a sensitivity analysis to test the relative effect of each influencing factor on the susceptibility index ranking. We also discuss reasons for the ranking position and thus the susceptibility of selected countries. The second objective, namely the impact of climate change on the energy demand of buildings, is tackled by means of a new model with which the heating and cooling energy demand of residential buildings can be estimated. We exemplarily applied the model to Germany and the Netherlands. It considers projections of future changes in population, climate and the insulation standards of buildings, whereas most of the existing studies only take into account fewer than three different factors that influence the future energy demand of buildings. Furthermore, we developed a comprehensive retrofitting algorithm with which the total residential building stock can be modeled for the first time for each year in the past and future.
The study confirms that there is no correlation between the geographical location of a country and its position in the electricity sector susceptibility ranking. Moreover, we found no pronounced pattern of susceptibility influencing factors between countries that ranked higher or lower in the index. We illustrate that Luxembourg, Greece, Slovakia and Italy are the countries with the highest electricity sector susceptibility. The electricity sectors of Norway, the Czech Republic, Portugal and Denmark were found to be least susceptible to climate change. Knowledge about the most important factors for the poor and good ranking positions of these countries is crucial for finding adequate adaptation measures to reduce the susceptibility of the electricity sector. Therefore, these factors are described within this study.
We show that the heating energy demand of residential buildings will strongly decrease in both Germany and the Netherlands in the future. The analysis for the Netherlands focused on the regional level and a finer temporal resolution which revealed strong variations in the future heating energy demand changes by province and by month. In the German study, we additionally investigated the future cooling energy demand and could demonstrate that it will only slightly increase up to the middle of this century. Thus, increases in the cooling energy demand are not expected to offset reductions in heating energy demand. The main factor for substantial heating energy demand reductions is the retrofitting of buildings. We are the first to show that the given German and Dutch energy and climate targets in the building sector can only be met if the annual retrofitting rates are substantially increased. The current rate of only about 1 % of the total building stock per year is insufficient for reaching a nearly zero-energy demand of all residential buildings by the middle of this century. To reach this target, it would need to be at least tripled. To sum up, this thesis emphasizes that country-specific characteristics are decisive for the electricity sector susceptibility of European countries. It also shows for different scenarios how much energy is needed in the future to heat and cool residential buildings. With this information, existing climate mitigation and adaptation measures can be justified or new actions encouraged.