@phdthesis{Zona2024,
  author    = {Zona, Carlotta Isabella},
  title     = {Visuo-linguistic integration for thematic-role assignment across speakers},
  doi       = {10.25932/publishup-63185},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-631857},
  school      = {Universit{\"a}t Potsdam},
  pages     = {147},
  year      = {2024},
  abstract  = {This dissertation examines the integration of incongruent visual-scene and morphological-case information ("cues") in building thematic-role representations of spoken relative clauses in German. Addressing the mutual influence of visual and linguistic processing, the Coordinated Interplay Account (CIA) describes a mechanism in two steps supporting visuo-linguistic integration (Knoeferle \& Crocker, 2006, Cog Sci). However, the outcomes and dynamics of integrating incongruent thematic-role representations from distinct sources have been investigated scarcely. Further, there is evidence that both second-language (L2) and older speakers may rely on non-syntactic cues relatively more than first-language (L1)/young speakers. Yet, the role of visual information for thematic-role comprehension has not been measured in L2 speakers, and only limitedly across the adult lifespan. Thematically unambiguous canonically ordered (subject-extracted) and noncanonically ordered (object-extracted) spoken relative clauses in German (see 1a-b) were presented in isolation and alongside visual scenes conveying either the same (congruent) or the opposite (incongruent) thematic relations as the sentence did. 1 a Das ist der Koch, der die Braut verfolgt. This is the.NOM cook who.NOM the.ACC bride follows This is the cook who is following the bride. b Das ist der Koch, den die Braut verfolgt. This is the.NOM cook whom.ACC the.NOM bride follows This is the cook whom the bride is following. The relative contribution of each cue to thematic-role representations was assessed with agent identification. Accuracy and latency data were collected post-sentence from a sample of L1 and L2 speakers (Zona \& Felser, 2023), and from a sample of L1 speakers from across the adult lifespan (Zona \& Reifegerste, under review). In addition, the moment-by-moment dynamics of thematic-role assignment were investigated with mouse tracking in a young L1 sample (Zona, under review). The following questions were addressed: (1) How do visual scenes influence thematic-role representations of canonical and noncanonical sentences? (2) How does reliance on visual-scene, case, and word-order cues vary in L1 and L2 speakers? (3) How does reliance on visual-scene, case, and word-order cues change across the lifespan? The results showed reliable effects of incongruence of visually and linguistically conveyed thematic relations on thematic-role representations. Incongruent (vs. congruent) scenes yielded slower and less accurate responses to agent-identification probes presented post-sentence. The recently inspected agent was considered as the most likely agent ~300ms after trial onset, and the convergence of visual scenes and word order enabled comprehenders to assign thematic roles predictively. L2 (vs. L1) participants relied more on word order overall. In response to noncanonical clauses presented with incongruent visual scenes, sensitivity to case predicted the size of incongruence effects better than L1-L2 grouping. These results suggest that the individual's ability to exploit specific cues might predict their weighting. Sensitivity to case was stable throughout the lifespan, while visual effects increased with increasing age and were modulated by individual interference-inhibition levels. Thus, age-related changes in comprehension may stem from stronger reliance on visually (vs. linguistically) conveyed meaning. These patterns represent evidence for a recent-role preference - i.e., a tendency to re-assign visually conveyed thematic roles to the same referents in temporally coordinated utterances. The findings (i) extend the generalizability of CIA predictions across stimuli, tasks, populations, and measures of interest, (ii) contribute to specifying the outcomes and mechanisms of detecting and indexing incongruent representations within the CIA, and (iii) speak to current efforts to understand the sources of variability in sentence comprehension.},
  language  = {en}
}
@phdthesis{Zhou2024,
  author    = {Zhou, Xiangqian},
  title     = {Modeling of spatially distributed nitrate transport to investigate the effects of drought and river restoration in the Bode catchment, Central Germany},
  doi       = {10.25932/publishup-62105},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-621059},
  school      = {Universit{\"a}t Potsdam},
  pages     = {VIII, 168},
  year      = {2024},
  abstract  = {The European Water Framework Directive (WFD) has identified river morphological alteration and diffuse pollution as the two main pressures affecting water bodies in Europe at the catchment scale. Consequently, river restoration has become a priority to achieve the WFD's objective of good ecological status. However, little is known about the effects of stream morphological changes, such as re-meandering, on in-stream nitrate retention at the river network scale. Therefore, catchment nitrate modeling is necessary to guide the implementation of spatially targeted and cost-effective mitigation measures. Meanwhile, Germany, like many other regions in central Europe, has experienced consecutive summer droughts from 2015-2018, resulting in significant changes in river nitrate concentrations in various catchments. However, the mechanistic exploration of catchment nitrate responses to changing weather conditions is still lacking. Firstly, a fully distributed, process-based catchment Nitrate model (mHM-Nitrate) was used, which was properly calibrated and comprehensively evaluated at numerous spatially distributed nitrate sampling locations. Three calibration schemes were designed, taking into account land use, stream order, and mean nitrate concentrations, and they varied in spatial coverage but used data from the same period (2011-2019). The model performance for discharge was similar among the three schemes, with Nash-Sutcliffe Efficiency (NSE) scores ranging from 0.88 to 0.92. However, for nitrate concentrations, scheme 2 outperformed schemes 1 and 3 when compared to observed data from eight gauging stations. This was likely because scheme 2 incorporated a diverse range of data, including low discharge values and nitrate concentrations, and thus provided a better representation of within-catchment heterogenous. Therefore, the study suggests that strategically selecting gauging stations that reflect the full range of within-catchment heterogeneity is more important for calibration than simply increasing the number of stations. Secondly, the mHM-Nitrate model was used to reveal the causal relations between sequential droughts and nitrate concentration in the Bode catchment (3200 km2) in central Germany, where stream nitrate concentrations exhibited contrasting trends from upstream to downstream reaches. The model was evaluated using data from six gauging stations, reflecting different levels of runoff components and their associated nitrate-mixing from upstream to downstream. Results indicated that the mHM-Nitrate model reproduced dynamics of daily discharge and nitrate concentration well, with Nash-Sutcliffe Efficiency ≥ 0.73 for discharge and Kling-Gupta Efficiency ≥ 0.50 for nitrate concentration at most stations. Particularly, the spatially contrasting trends of nitrate concentration were successfully captured by the model. The decrease of nitrate concentration in the lowland area in drought years (2015-2018) was presumably due to (1) limited terrestrial export loading (ca. 40\% lower than that of normal years 2004-2014), and (2) increased in-stream retention efficiency (20\% higher in summer within the whole river network). From a mechanistic modelling perspective, this study provided insights into spatially heterogeneous flow and nitrate dynamics and effects of sequential droughts, which shed light on water-quality responses to future climate change, as droughts are projected to be more frequent. Thirdly, this study investigated the effects of stream restoration via re-meandering on in-stream nitrate retention at network-scale in the well-monitored Bode catchment. The mHM-Nitrate model showed good performance in reproducing daily discharge and nitrate concentrations, with median Kling-Gupta values of 0.78 and 0.74, respectively. The mean and standard deviation of gross nitrate retention efficiency, which accounted for both denitrification and assimilatory uptake, were 5.1 ± 0.61\% and 74.7 ± 23.2\% in winter and summer, respectively, within the stream network. The study found that in the summer, denitrification rates were about two times higher in lowland sub-catchments dominated by agricultural lands than in mountainous sub-catchments dominated by forested areas, with median ± SD of 204 ± 22.6 and 102 ± 22.1 mg N m-2 d-1, respectively. Similarly, assimilatory uptake rates were approximately five times higher in streams surrounded by lowland agricultural areas than in those in higher-elevation, forested areas, with median ± SD of 200 ± 27.1 and 39.1 ± 8.7 mg N m-2 d-1, respectively. Therefore, restoration strategies targeting lowland agricultural areas may have greater potential for increasing nitrate retention. The study also found that restoring stream sinuosity could increase net nitrate retention efficiency by up to 25.4 ± 5.3\%, with greater effects seen in small streams. These results suggest that restoration efforts should consider augmenting stream sinuosity to increase nitrate retention and decrease nitrate concentrations at the catchment scale.},
  language  = {en}
}
@phdthesis{Wolf2024,
  author    = {Wolf, Alexander Karsten},
  title     = {Pfadbrechende und pfadbest{\"a}tigende Dienstleistungspotenziale in der deutschen Gesundheitswirtschaft durch Quantified-Self-Applikationen},
  doi       = {10.25932/publishup-65138},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-651384},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XIII, 666},
  year      = {2024},
  abstract  = {Quantified Self, die pro-aktive Selbstvermessung von Menschen, hat sich in den letzten Jahren von einer Nischenanwendung zu einem Massenph{\"a}nomen entwickelt. Dabei stehen den Nutzern heute vielf{\"a}ltige technische Unterst{\"u}tzungsm{\"o}glichkeiten, beispielsweise in Form von Smartphones, Fitness-Trackern oder Gesundheitsapps zur Verf{\"u}gung, welche eine ann{\"a}hernd l{\"u}ckenlose {\"U}berwachung unterschiedlicher Kontextfaktoren einer individuellen Lebenswirklichkeit erlauben. In der Folge widmet sich diese Arbeit unter anderem der Fragestellung, inwieweit diese intensive und eigen-initiierte Besch{\"a}ftigung, insbesondere mit gesundheitsbezogenen Daten, die weitgehend als objektiviert und damit belastbar gelten, die Gesundheitskompetenz derart aktiver Menschen erh{\"o}hen kann. Dar{\"u}ber hinaus werden Aspekte untersucht, inwieweit die neuen Technologien in der Lage sind, spezifische medizinische Erkenntnisse zu vertiefen und in der Konsequenz die daraus resultierenden Behandlungsprozesse zu ver{\"a}ndern. W{\"a}hrend der Ursprung des Quantified Self im 2. Gesundheitsmarkt liegt, geht die vorliegende Arbeit der Frage nach, welche strukturellen, personellen und prozessualen Ankn{\"u}pfungspunkte perspektivisch im 1. Gesundheitsmarkt existieren werden, wenn ein potentieller Patient in einer st{\"a}rker emanzipierten Weise den Wunsch versp{\"u}rt, oder eine entsprechende Forderung stellt, seine gesammelten Gesundheitsdaten in m{\"o}glichst umfassender Form in eine medizinische Behandlung zu integrieren. Dabei werden auf der einen Seite aktuelle Entwicklungen im 2. Gesundheitsmarkt untersucht, die gekennzeichnet sind von einer hohen Dynamik und einer großen Intransparenz. Auf der anderen Seite steht der als stark reguliert und wenig digitalisiert geltende 1. Gesundheitsmarkt mit seinen langen Entwicklungszyklen und ausgepr{\"a}gten Partikularinteressen der verschiedenen Stakeholder. In diesem Zuge werden aktuelle Entwicklungen des zugrunde liegenden Rechtsrahmens, speziell im Hinblick auf st{\"a}rker patientenzentrierte und digitalisierte Normen untersucht, wobei insbesondere das Digitale Versorgung Gesetz eine wichtige Rolle einnimmt. Ziel der Arbeit ist die st{\"a}rkere Durchdringung von Wechselwirkungen an der Schnittstelle zwischen den beiden Gesundheitsm{\"a}rkten in Bezug auf die Verwendung von Technologien der Selbstvermessung, um in der Folge zuk{\"u}nftige Gesch{\"a}ftspotentiale f{\"u}r existierende oder neu in den Markt dr{\"a}ngende Dienstleister zu eruieren. Als zentrale Methodik kommt hier eine Delphi-Studie zum Einsatz, die in einem interprofessionellen Ansatz versucht, ein Zukunftsbild dieser derzeit noch sehr jungen Entwicklungen f{\"u}r das Jahr 2030 aufzuzeigen. Eingebettet werden die Ergebnisse in die Untersuchung einer allgemeinen gesellschaftlichen Akzeptanz der skizzierten Ver{\"a}nderungen.},
  language  = {de}
}
@phdthesis{Wojcik2024,
  author    = {Wojcik, Laurie Anne Myriam},
  title     = {Beyond a single diversity facet: implications for the links between biodiversity, environmental changes and ecosystem functioning},
  doi       = {10.25932/publishup-64692},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-646925},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vi, 189},
  year      = {2024},
  abstract  = {Human activities modify nature worldwide via changes in the environment, biodiversity and the functioning of ecosystems, which in turn disrupt ecosystem services and feed back negatively on humans. A pressing challenge is thus to limit our impact on nature, and this requires detailed understanding of the interconnections between the environment, biodiversity and ecosystem functioning. These three components of ecosystems each include multiple dimensions, which interact with each other in different ways, but we lack a comprehensive picture of their interconnections and underlying mechanisms. Notably, diversity is often viewed as a single facet, namely species diversity, while many more facets exist at different levels of biological organisation (e.g. genetic, phenotypic, functional, multitrophic diversity), and multiple diversity facets together constitute the raw material for adaptation to environmental changes and shape ecosystem functioning. Consequently, investigating the multidimensionality of ecosystems, and in particular the links between multifaceted diversity, environmental changes and ecosystem functions, is crucial for ecological research, management and conservation. This thesis aims to explore several aspects of this question theoretically. I investigate three broad topics in this thesis. First, I focus on how food webs with varying levels of functional diversity across three trophic levels buffer environmental changes, such as a sudden addition of nutrients or long-term changes (e.g. warming or eutrophication). I observed that functional diversity generally enhanced ecological stability (i.e. the buffering capacity of the food web) by increasing trophic coupling. More precisely, two aspects of ecological stability (resistance and resilience) increased even though a third aspect (the inverse of the time required for the system to reach its post-perturbation state) decreased with increasing functional diversity. Second, I explore how several diversity facets served as a raw material for different sources of adaptation and how these sources affected multiple ecosystem functions across two trophic levels. Considering several sources of adaptation enabled the interplay between ecological and evolutionary processes, which affected trophic coupling and thereby ecosystem functioning. Third, I reflect further on the multifaceted nature of diversity by developing an index K able to quantify the facet of functional diversity, which is itself multifaceted. K can provide a comprehensive picture of functional diversity and is a rather good predictor of ecosystem functioning. Finally I synthesise the interdependent mechanisms (complementarity and selection effects, trophic coupling and adaptation) underlying the relationships between multifaceted diversity, ecosystem functioning and the environment, and discuss the generalisation of my findings across ecosystems and further perspectives towards elaborating an operational biodiversity-ecosystem functioning framework for research and conservation.},
  language  = {en}
}
@phdthesis{WindirschWoiwode2024,
  author    = {Windirsch-Woiwode, Torben},
  title     = {Permafrost carbon stabilisation by recreating a herbivore-driven ecosystem},
  doi       = {10.25932/publishup-62424},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-624240},
  school      = {Universit{\"a}t Potsdam},
  pages     = {X, 104, A-57},
  year      = {2024},
  abstract  = {With Arctic ground as a huge and temperature-sensitive carbon reservoir, maintaining low ground temperatures and frozen conditions to prevent further carbon emissions that contrib-ute to global climate warming is a key element in humankind's fight to maintain habitable con-ditions on earth. Former studies showed that during the late Pleistocene, Arctic ground condi-tions were generally colder and more stable as the result of an ecosystem dominated by large herbivorous mammals and vast extents of graminoid vegetation - the mammoth steppe. Characterised by high plant productivity (grassland) and low ground insulation due to animal-caused compression and removal of snow, this ecosystem enabled deep permafrost aggrad-ation. Now, with tundra and shrub vegetation common in the terrestrial Arctic, these effects are not in place anymore. However, it appears to be possible to recreate this ecosystem local-ly by artificially increasing animal numbers, and hence keep Arctic ground cold to reduce or-ganic matter decomposition and carbon release into the atmosphere. By measuring thaw depth, total organic carbon and total nitrogen content, stable carbon iso-tope ratio, radiocarbon age, n-alkane and alcohol characteristics and assessing dominant vegetation types along grazing intensity transects in two contrasting Arctic areas, it was found that recreating conditions locally, similar to the mammoth steppe, seems to be possible. For permafrost-affected soil, it was shown that intensive grazing in direct comparison to non-grazed areas reduces active layer depth and leads to higher TOC contents in the active layer soil. For soil only frozen on top in winter, an increase of TOC with grazing intensity could not be found, most likely because of confounding factors such as vertical water and carbon movement, which is not possible with an impermeable layer in permafrost. In both areas, high animal activity led to a vegetation transformation towards species-poor graminoid-dominated landscapes with less shrubs. Lipid biomarker analysis revealed that, even though the available organic material is different between the study areas, in both permafrost-affected and sea-sonally frozen soils the organic material in sites affected by high animal activity was less de-composed than under less intensive grazing pressure. In conclusion, high animal activity af-fects decomposition processes in Arctic soils and the ground thermal regime, visible from reduced active layer depth in permafrost areas. Therefore, grazing management might be utilised to locally stabilise permafrost and reduce Arctic carbon emissions in the future, but is likely not scalable to the entire permafrost region.},
  language  = {en}
}
@phdthesis{Vitagliano2024,
  author    = {Vitagliano, Gerardo},
  title     = {Modeling the structure of tabular files for data preparation},
  doi       = {10.25932/publishup-62435},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-624351},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ii, 114},
  year      = {2024},
  abstract  = {To manage tabular data files and leverage their content in a given downstream task, practitioners often design and execute complex transformation pipelines to prepare them. The complexity of such pipelines stems from different factors, including the nature of the preparation tasks, often exploratory or ad-hoc to specific datasets; the large repertory of tools, algorithms, and frameworks that practitioners need to master; and the volume, variety, and velocity of the files to be prepared. Metadata plays a fundamental role in reducing this complexity: characterizing a file assists end users in the design of data preprocessing pipelines, and furthermore paves the way for suggestion, automation, and optimization of data preparation tasks. Previous research in the areas of data profiling, data integration, and data cleaning, has focused on extracting and characterizing metadata regarding the content of tabular data files, i.e., about the records and attributes of tables. Content metadata are useful for the latter stages of a preprocessing pipeline, e.g., error correction, duplicate detection, or value normalization, but they require a properly formed tabular input. Therefore, these metadata are not relevant for the early stages of a preparation pipeline, i.e., to correctly parse tables out of files. In this dissertation, we turn our focus to what we call the structure of a tabular data file, i.e., the set of characters within a file that do not represent data values but are required to parse and understand the content of the file. We provide three different approaches to represent file structure, an explicit representation based on context-free grammars; an implicit representation based on file-wise similarity; and a learned representation based on machine learning. In our first contribution, we use the grammar-based representation to characterize a set of over 3000 real-world csv files and identify multiple structural issues that let files deviate from the csv standard, e.g., by having inconsistent delimiters or containing multiple tables. We leverage our learnings about real-world files and propose Pollock, a benchmark to test how well systems parse csv files that have a non-standard structure, without any previous preparation. We report on our experiments on using Pollock to evaluate the performance of 16 real-world data management systems. Following, we characterize the structure of files implicitly, by defining a measure of structural similarity for file pairs. We design a novel algorithm to compute this measure, which is based on a graph representation of the files' content. We leverage this algorithm and propose Mondrian, a graphical system to assist users in identifying layout templates in a dataset, classes of files that have the same structure, and therefore can be prepared by applying the same preparation pipeline. Finally, we introduce MaGRiTTE, a novel architecture that uses self-supervised learning to automatically learn structural representations of files in the form of vectorial embeddings at three different levels: cell level, row level, and file level. We experiment with the application of structural embeddings for several tasks, namely dialect detection, row classification, and data preparation efforts estimation. Our experimental results show that structural metadata, either identified explicitly on parsing grammars, derived implicitly as file-wise similarity, or learned with the help of machine learning architectures, is fundamental to automate several tasks, to scale up preparation to large quantities of files, and to provide repeatable preparation pipelines.},
  language  = {en}
}
@phdthesis{Taleb2024,
  author    = {Taleb, Aiham},
  title     = {Self-supervised deep learning methods for medical image analysis},
  doi       = {10.25932/publishup-64408},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-644089},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xii, 171},
  year      = {2024},
  abstract  = {Deep learning has seen widespread application in many domains, mainly for its ability to learn data representations from raw input data. Nevertheless, its success has so far been coupled with the availability of large annotated (labelled) datasets. This is a requirement that is difficult to fulfil in several domains, such as in medical imaging. Annotation costs form a barrier in extending deep learning to clinically-relevant use cases. The labels associated with medical images are scarce, since the generation of expert annotations of multimodal patient data at scale is non-trivial, expensive, and time-consuming. This substantiates the need for algorithms that learn from the increasing amounts of unlabeled data. Self-supervised representation learning algorithms offer a pertinent solution, as they allow solving real-world (downstream) deep learning tasks with fewer annotations. Self-supervised approaches leverage unlabeled samples to acquire generic features about different concepts, enabling annotation-efficient downstream task solving subsequently. Nevertheless, medical images present multiple unique and inherent challenges for existing self-supervised learning approaches, which we seek to address in this thesis: (i) medical images are multimodal, and their multiple modalities are heterogeneous in nature and imbalanced in quantities, e.g. MRI and CT; (ii) medical scans are multi-dimensional, often in 3D instead of 2D; (iii) disease patterns in medical scans are numerous and their incidence exhibits a long-tail distribution, so it is oftentimes essential to fuse knowledge from different data modalities, e.g. genomics or clinical data, to capture disease traits more comprehensively; (iv) Medical scans usually exhibit more uniform color density distributions, e.g. in dental X-Rays, than natural images. Our proposed self-supervised methods meet these challenges, besides significantly reducing the amounts of required annotations. We evaluate our self-supervised methods on a wide array of medical imaging applications and tasks. Our experimental results demonstrate the obtained gains in both annotation-efficiency and performance; our proposed methods outperform many approaches from related literature. Additionally, in case of fusion with genetic modalities, our methods also allow for cross-modal interpretability. In this thesis, not only we show that self-supervised learning is capable of mitigating manual annotation costs, but also our proposed solutions demonstrate how to better utilize it in the medical imaging domain. Progress in self-supervised learning has the potential to extend deep learning algorithms application to clinical scenarios.},
  language  = {en}
}
@phdthesis{Sun2024,
  author    = {Sun, Bowen},
  title     = {Energy losses in low-offset organic solar cells},
  doi       = {10.25932/publishup-62143},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-621430},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxi, 190},
  year      = {2024},
  abstract  = {Organic solar cells (OSCs) represent a new generation of solar cells with a range of captivating attributes including low-cost, light-weight, aesthetically pleasing appearance, and flexibility. Different from traditional silicon solar cells, the photon-electron conversion in OSCs is usually accomplished in an active layer formed by blending two kinds of organic molecules (donor and acceptor) with different energy levels together. The first part of this thesis focuses on a better understanding of the role of the energetic offset and each recombination channel on the performance of these low-offset OSCs. By combining advanced experimental techniques with optical and electrical simulation, the energetic offsets between CT and excitons, several important insights were achieved: 1. The short circuit current density and fill-factor of low-offset systems are largely determined by field-dependent charge generation in such low-offset OSCs. Interestingly, it is strongly evident that such field-dependent charge generation originates from a field-dependent exciton dissociation yield. 2. The reduced energetic offset was found to be accompanied by strongly enhanced bimolecular recombination coefficient, which cannot be explained solely by exciton repopulation from CT states. This implies the existence of another dark decay channel apart from CT. The second focus of the thesis was on the technical perspective. In this thesis, the influence of optical artifacts in differential absorption spectroscopy upon the change of sample configuration and active layer thickness was studied. It is exemplified and discussed thoroughly and systematically in terms of optical simulations and experiments, how optical artifacts originated from non-uniform carrier profile and interference can manipulate not only the measured spectra, but also the decay dynamics in various measurement conditions. In the end of this study, a generalized methodology based on an inverse optical transfer matrix formalism was provided to correct the spectra and decay dynamics manipulated by optical artifacts. Overall, this thesis paves the way for a deeper understanding of the keys toward higher PCEs in low-offset OSC devices, from the perspectives of both device physics and characterization techniques.},
  language  = {en}
}
@phdthesis{Stange2024,
  author    = {Stange, Maike},
  title     = {A study on Coronin-A and Aip1 function in motility of Dictyostelium discoideum and on Aip1 interchangeability between Dictyostelium discoideum and Arabidopsis thaliana},
  doi       = {10.25932/publishup-62856},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-628569},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiv, 168},
  year      = {2024},
  abstract  = {Actin is one of the most highly conserved proteins in eukaryotes and distinct actin-related proteins with filament-forming properties are even found in prokaryotes. Due to these commonalities, actin-modulating proteins of many species share similar structural properties and proposed functions. The polymerization and depolymerization of actin are critical processes for a cell as they can contribute to shape changes to adapt to its environment and to move and distribute nutrients and cellular components within the cell. However, to what extent functions of actin-binding proteins are conserved between distantly related species, has only been addressed in a few cases. In this work, functions of Coronin-A (CorA) and Actin-interacting protein 1 (Aip1), two proteins involved in actin dynamics, were characterized. In addition, the interchangeability and function of Aip1 were investigated in two phylogenetically distant model organisms. The flowering plant Arabidopsis thaliana (encoding two homologs, AIP1-1 and AIP1-2) and in the amoeba Dictyostelium discoideum (encoding one homolog, DdAip1) were chosen because the functions of their actin cytoskeletons may differ in many aspects. Functional analyses between species were conducted for AIP1 homologs as flowering plants do not harbor a CorA gene. In the first part of the study, the effect of four different mutation methods on the function of Coronin-A protein and the resulting phenotype in D. discoideum was revealed in two genetic knockouts, one RNAi knockdown and a sudden loss-of-function mutant created by chemical-induced dislocation (CID). The advantages and disadvantages of the different mutation methods on the motility, appearance and development of the amoebae were investigated, and the results showed that not all observed properties were affected with the same intensity. Remarkably, a new combination of Selection-Linked Integration and CID could be established. In the second and third parts of the thesis, the exchange of Aip1 between plant and amoeba was carried out. For A. thaliana, the two homologs (AIP1-1 and AIP1-2) were analyzed for functionality as well as in D. discoideum. In the Aip1-deficient amoeba, rescue with AIP1-1 was more effective than with AIP1-2. The main results in the plant showed that in the aip1-2 mutant background, reintroduced AIP1-2 displayed the most efficient rescue and A. thaliana AIP1-1 rescued better than DdAip1. The choice of the tagging site was important for the function of Aip1 as steric hindrance is a problem. The DdAip1 was less effective when tagged at the C-terminus, while the plant AIP1s showed mixed results depending on the tag position. In conclusion, the foreign proteins partially rescued phenotypes of mutant plants and mutant amoebae, despite the organisms only being very distantly related in evolutionary terms.},
  language  = {en}
}
@phdthesis{Stallasch2024,
  author    = {Stallasch, Sophie E.},
  title     = {Optimizing power analysis for randomized experiments: Design parameters for student achievement},
  doi       = {10.25932/publishup-62939},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-629396},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ix, 224},
  year      = {2024},
  abstract  = {Randomized trials (RTs) are promising methodological tools to inform evidence-based reform to enhance schooling. Establishing a robust knowledge base on how to promote student achievement requires sensitive RT designs demonstrating sufficient statistical power and precision to draw conclusive and correct inferences on the effectiveness of educational programs and innovations. Proper power analysis is therefore an integral component of any informative RT on student achievement. This venture critically hinges on the availability of reasonable input variance design parameters (and their inherent uncertainties) that optimally reflect the realities around the prospective RT—precisely, its target population and outcome, possibly applied covariates, the concrete design as well as the planned analysis. However, existing compilations in this vein show far-reaching shortcomings. The overarching endeavor of the present doctoral thesis was to substantively expand available resources devoted to tweak the planning of RTs evaluating educational interventions. At the core of this thesis is a systematic analysis of design parameters for student achievement, generating reliable and versatile compendia and developing thorough guidance to support apt power analysis to design strong RTs. To this end, the thesis at hand bundles two complementary studies which capitalize on rich data of several national probability samples from major German longitudinal large-scale assessments. Study I applied two- and three-level latent (covariate) modeling to analyze design parameters for a wide spectrum of mathematical-scientific, verbal, and domain-general achievement outcomes. Three vital covariate sets were covered comprising (a) pretests, (b) sociodemographic characteristics, and (c) their combination. The accumulated estimates were additionally summarized in terms of normative distributions. Study II specified (manifest) single-, two-, and three-level models and referred to influential psychometric heuristics to analyze design parameters and develop concise selection guidelines for covariate (a) types of varying bandwidth-fidelity (domain-identical, cross-domain, fluid intelligence pretests; sociodemographic characteristics), (b) combinations quantifying incremental validities, and (c) time lags of 1- to 7-year-lagged pretests scrutinizing validity degradation. The estimates for various mathematical-scientific and verbal achievement outcomes were meta-analytically integrated and employed in precision simulations. In doing so, Studies I and II addressed essential gaps identified in previous repertoires in six major dimensions: Taken together, this thesis accumulated novel design parameters and deliberate guidance for RT power analysis (1) tailored to four German student (sub)populations across the entire school career from Grade 1 to 12, (2) matched to 21 achievement (sub)domains, (3) adjusted for 11 covariate sets enriched by empirically supported guidelines, (4) adapted to six RT designs, (5) suitable for latent and manifest analysis models, (6) which were cataloged along with quantifications of their associated uncertainties. These resources are complemented by a plethora of illustrative application examples to gently direct psychological and educational researchers through pivotal steps in the process of RT design. The striking heterogeneity of the design parameter estimates across all these dimensions constitutes the overall, joint key result of Studies I and II. Hence, this work convincingly reinforces calls for a close match between design parameters and the specific peculiarities of the target RT's research context. All in all, the present doctoral thesis offers a—so far unique—nuanced and extensive toolkit to optimize power analysis for sound RTs on student achievement in the German (and similar) school context. It is of utmost importance that research does not tire to spawn robust evidence on what actually works to improve schooling. With this in mind, I hope that the emerging compendia and guidance contribute to the quality and rigor of our randomized experiments in psychology and education.},
  language  = {en}
}