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Landesrecht Brandenburg
(2024)
Die topaktuelle 27. Auflage mit den wichtigsten Vorschriften des Landes Brandenburg für Studium, Referendariat und juristische Praxis berücksichtigt u.a. Änderungen des Landeswahlgesetzes, des Polizei- und des Pressegesetzes, des Juristenausbildungsgesetzes und der Juristenausbildungsordnung sowie des Schiedsstellen-, Schlichtungs- und Gütestellengesetzes. Schaubilder verdeutlichen den Aufbau der Gerichtsbarkeit und der Verwaltung. Gliederungen und ein ausführliches Register führen schnell zur gesuchten Norm, die durchgängige Satznummerierung gewährleistet präzise Zitierfähigkeit. Die Sammlung ist in Brandenburg zu den Staatsexamina zugelassen.
It is a well-attested finding in head-initial languages that individuals with aphasia (IWA) have greater difficulties in comprehending object-extracted relative clauses (ORCs) as compared to subject-extracted relative clauses (SRCs). Adopting the linguistically based approach of Relativized Minimality (RM; Rizzi, 1990, 2004), the subject-object asymmetry is attributed to the occurrence of a Minimality effect in ORCs due to reduced processing capacities in IWA (Garraffa & Grillo, 2008; Grillo, 2008, 2009). For ORCs, it is claimed that the embedded subject intervenes in the syntactic dependency between the moved object and its trace, resulting in greater processing demands. In contrast, no such intervener is present in SRCs. Based on the theoretical framework of RM and findings from language acquisition (Belletti et al., 2012; Friedmann et al., 2009), it is assumed that Minimality effects are alleviated when the moved object and the intervening subject differ in terms of relevant syntactic features. For German, the language under investigation, the RM approach predicts that number (i.e., singular vs. plural) and the lexical restriction [+NP] feature (i.e., lexically restricted determiner phrases vs. lexically unrestricted pronouns) are considered relevant in the computation of Minimality. Greater degrees of featural distinctiveness are predicted to result in more facilitated processing of ORCs, because IWA can more easily distinguish between the moved object and the intervener.
This cumulative dissertation aims to provide empirical evidence on the validity of the RM approach in accounting for comprehension patterns during relative clause (RC) processing in German-speaking IWA. For that purpose, I conducted two studies including visual-world eye-tracking experiments embedded within an auditory referent-identification task to study the offline and online processing of German RCs. More specifically, target sentences were created to evaluate (a) whether IWA demonstrate a subject-object asymmetry, (b) whether dissimilarity in the number and/or the [+NP] features facilitates ORC processing, and (c) whether sentence processing in IWA benefits from greater degrees of featural distinctiveness. Furthermore, by comparing RCs disambiguated through case marking (at the relative pronoun or the following noun phrase) and number marking (inflection of the sentence-final verb), it was possible to consider the role of the relative position of the disambiguation point. The RM approach predicts that dissimilarity in case should not affect the occurrence of Minimality effects. However, the case cue to sentence interpretation appears earlier within RCs than the number cue, which may result in lower processing costs in case-disambiguated RCs compared to number-disambiguated RCs.
In study I, target sentences varied with respect to word order (SRC vs. ORC) and dissimilarity in the [+NP] feature (lexically restricted determiner phrase vs. pronouns as embedded element). Moreover, by comparing the impact of these manipulations in case- and number-disambiguated RCs, the effect of dissimilarity in the number feature was explored. IWA demonstrated a subject-object asymmetry, indicating the occurrence of a Minimality effect in ORCs. However, dissimilarity neither in the number feature nor in the [+NP] feature alone facilitated ORC processing. Instead, only ORCs involving distinct specifications of both the number and the [+NP] features were well comprehended by IWA. In study II, only temporarily ambiguous ORCs disambiguated through case or number marking were investigated, while controlling for varying points of disambiguation. There was a slight processing advantage of case marking as cue to sentence interpretation as compared to number marking.
Taken together, these findings suggest that the RM approach can only partially capture empirical data from German IWA. In processing complex syntactic structures, IWA are susceptible to the occurrence of the intervening subject in ORCs. The new findings reported in the thesis show that structural dissimilarity can modulate sentence comprehension in aphasia. Interestingly, IWA can override Minimality effects in ORCs and derive correct sentence meaning if the featural specifications of the constituents are maximally different, because they can more easily distinguish the moved object and the intervening subject given their reduced processing capacities. This dissertation presents new scientific knowledge that highlights how the syntactic theory of RM helps to uncover selective effects of morpho-syntactic features on sentence comprehension in aphasia, emphasizing the close link between assumptions from theoretical syntax and empirical research.
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.
The landscape of software self-adaptation is shaped in accordance with the need to cost-effectively achieve and maintain (software) quality at runtime and in the face of dynamic operation conditions. Optimization-based solutions perform an exhaustive search in the adaptation space, thus they may provide quality guarantees. However, these solutions render the attainment of optimal adaptation plans time-intensive, thereby hindering scalability. Conversely, deterministic rule-based solutions yield only sub-optimal adaptation decisions, as they are typically bound by design-time assumptions, yet they offer efficient processing and implementation, readability, expressivity of individual rules supporting early verification. Addressing the quality-cost trade-of requires solutions that simultaneously exhibit the scalability and cost-efficiency of rulebased policy formalism and the optimality of optimization-based policy formalism as explicit artifacts for adaptation. Utility functions, i.e., high-level specifications that capture system objectives, support the explicit treatment of quality-cost trade-off. Nevertheless, non-linearities, complex dynamic architectures, black-box models, and runtime uncertainty that makes the prior knowledge obsolete are a few of the sources of uncertainty and subjectivity that render the elicitation of utility non-trivial.
This thesis proposes a twofold solution for incremental self-adaptation of dynamic architectures. First, we introduce Venus, a solution that combines in its design a ruleand an optimization-based formalism enabling optimal and scalable adaptation of dynamic architectures. Venus incorporates rule-like constructs and relies on utility theory for decision-making. Using a graph-based representation of the architecture, Venus captures rules as graph patterns that represent architectural fragments, thus enabling runtime extensibility and, in turn, support for dynamic architectures; the architecture is evaluated by assigning utility values to fragments; pattern-based definition of rules and utility enables incremental computation of changes on the utility that result from rule executions, rather than evaluating the complete architecture, which supports scalability. Second, we introduce HypeZon, a hybrid solution for runtime coordination of multiple off-the-shelf adaptation policies, which typically offer only partial satisfaction of the quality and cost requirements. Realized based on meta-self-aware architectures, HypeZon complements Venus by re-using existing policies at runtime for balancing the quality-cost trade-off.
The twofold solution of this thesis is integrated in an adaptation engine that leverages state- and event-based principles for incremental execution, therefore, is scalable for large and dynamic software architectures with growing size and complexity. The utility elicitation challenge is resolved by defining a methodology to train utility-change prediction models. The thesis addresses the quality-cost trade-off in adaptation of dynamic software architectures via design-time combination (Venus) and runtime coordination (HypeZon) of rule- and optimization-based policy formalisms, while offering supporting mechanisms for optimal, cost-effective, scalable, and robust adaptation. The solutions are evaluated according to a methodology that is obtained based on our systematic literature review of evaluation in self-healing systems; the applicability and effectiveness of the contributions are demonstrated to go beyond the state-of-the-art in coverage of a wide spectrum of the problem space for software self-adaptation.
Sigmund Freud, the founder of psychoanalysis, began his intellectual life with the Jewish Bible and also ended it with it. He began by reading the Philippson Bible together, especially with his father Jacob Freud, and ended by studying the figure of Moses. This study systematically traces this preoccupation and shows that the Jewish Bible was a constant reference for Freud and determined his Jewish identity. This is shown by analysing family documents, religious instruction and references to the Bible in Freud's writings and correspondence.
Leitfaden für die Erstellung von kommunalen Aktionsplänen zur Steigerung der urbanen Klimaresilienz
(2024)
Die durch Klimaveränderungen hervorgerufenen Auswirkungen auf Menschen und Umwelt werden immer offensichtlicher: Neben der gesundheitlichen Gefährdung durch Hitzewellen, die deutschlandweit seit einigen Jahren eine steigende Rate an Todes- und Krankheitsfällen zur Folge hat sind in den letzten Jahren zunehmend Starkniederschläge und daraus resultierenden Überschwemmungen bzw. Sturzfluten aufgetreten. Diese ziehen zum Teil immensen wirtschaftlichen Schäden, aber auch Beeinträchtigungen für die menschliche Gesundheit – sowohl physisch als auch psychisch – sowie gar Todesopfer nach sich. Es ist davon auszugehen, dass diese Extremwetterereignisse zukünftiger noch häufiger auftreten werden.
Um die Bevölkerung besser vor den Folgen dieser Wetterextreme zu schützen, sind neben Klimaschutzmaßnahmen auch Vorsorge- und Anpassungsmaßnahmen zur Steigerung der kommunalen Klimaresilienz dringend notwendig. Dazu bedarf es einerseits einer Auseinandersetzung mit den eigenen kommunalen Risiken und daraus resultierenden Handlungsbedarfen, und andererseits eines interdisziplinären, querschnittsorientierten und prozessorientierten Planens und Handelns. Aktionspläne sollen diese beiden Aspekte bündeln.
In den letzten Jahren sind einige kommunale und kommunenübergreifende (Hitze-) aufgestellt worden. Diese unterscheiden sich jedoch in ihrem Inhalt und Umfang zum Teil erheblich. Mit dem vorliegenden Leitfaden soll eine effektive Hilfestellung geschaffen werden, um Kommunen bzw. die kommunale Verwaltung auf dem Weg zum eigenen Aktionsplan zu unterstützt. Dabei fokussiert der Leitfaden auf die Herausforderungen, die sich durch vermehrte Hitze- und Starkregenereignisse ergeben. Er stützt sich auf schon vorhandene Arbeitshilfen, Handlungsempfehlungen, Leitfäden und weitere Hinweise und verweist an vielen Stellen auch darauf. So soll ein praxistauglicher Leitfaden entstehen, der flexibel anwendbar ist. Mit Hilfe des vorliegenden Leitfadens können Kommunen ihre Aktivitäten auf Hitze oder Starkregen fokussieren oder einen umfassenden Aktionsplan für beide Themenbereiche erstellen.
Concepts and techniques for 3D-embedded treemaps and their application to software visualization
(2024)
This thesis addresses concepts and techniques for interactive visualization of hierarchical data using treemaps. It explores (1) how treemaps can be embedded in 3D space to improve their information content and expressiveness, (2) how the readability of treemaps can be improved using level-of-detail and degree-of-interest techniques, and (3) how to design and implement a software framework for the real-time web-based rendering of treemaps embedded in 3D. With a particular emphasis on their application, use cases from software analytics are taken to test and evaluate the presented concepts and techniques.
Concerning the first challenge, this thesis shows that a 3D attribute space offers enhanced possibilities for the visual mapping of data compared to classical 2D treemaps. In particular, embedding in 3D allows for improved implementation of visual variables (e.g., by sketchiness and color weaving), provision of new visual variables (e.g., by physically based materials and in situ templates), and integration of visual metaphors (e.g., by reference surfaces and renderings of natural phenomena) into the three-dimensional representation of treemaps.
For the second challenge—the readability of an information visualization—the work shows that the generally higher visual clutter and increased cognitive load typically associated with three-dimensional information representations can be kept low in treemap-based representations of both small and large hierarchical datasets. By introducing an adaptive level-of-detail technique, we cannot only declutter the visualization results, thereby reducing cognitive load and mitigating occlusion problems, but also summarize and highlight relevant data. Furthermore, this approach facilitates automatic labeling, supports the emphasis on data outliers, and allows visual variables to be adjusted via degree-of-interest measures.
The third challenge is addressed by developing a real-time rendering framework with WebGL and accumulative multi-frame rendering. The framework removes hardware constraints and graphics API requirements, reduces interaction response times, and simplifies high-quality rendering. At the same time, the implementation effort for a web-based deployment of treemaps is kept reasonable.
The presented visualization concepts and techniques are applied and evaluated for use cases in software analysis. In this domain, data about software systems, especially about the state and evolution of the source code, does not have a descriptive appearance or natural geometric mapping, making information visualization a key technology here. In particular, software source code can be visualized with treemap-based approaches because of its inherently hierarchical structure. With treemaps embedded in 3D, we can create interactive software maps that visually map, software metrics, software developer activities, or information about the evolution of software systems alongside their hierarchical module structure.
Discussions on remaining challenges and opportunities for future research for 3D-embedded treemaps and their applications conclude the thesis.
Das in diesem Beitrag vorgestellte Projektseminarkonzept reagiert auf eine wahrgenommene Distanz und Unsicherheit Studierender im Fach Lebensgestaltung-Ethik-Religionskunde gegenüber religionsbezogenen Themen. Mittels verschiedener Strategien wurde, ausgehend von der Conceptual Change-Forschung, zur Wahrnehmung und Reflexion des eigenen kulturellen Standortes und der eigenen Konzepte in Bezug auf Religion(en) angeregt. Ihren Lernprozess haben die Studierenden in Arbeitsjournaleinträgen festgehalten. Diese Einträge wurden wiederum mittels einer qualitative Inhaltsanalyse untersucht. Nach der Darstellung der dabei erhobenen religions- und unterrichtsbezogenen Vorstellungen der Studierenden werden im Beitrag Anregungen gegeben, inwiefern die analysierten Befunde als Grundlage für die Verbesserung der Hochschullehre im Fachbereich dienen können.
Organic-inorganic hybrids based on P3HT and mesoporous silicon for thermoelectric applications
(2024)
This thesis presents a comprehensive study on synthesis, structure and thermoelectric transport properties of organic-inorganic hybrids based on P3HT and porous silicon. The effect of embedding polymer in silicon pores on the electrical and thermal transport is studied. Morphological studies confirm successful polymer infiltration and diffusion doping with roughly 50% of the pore space occupied by conjugated polymer. Synchrotron diffraction experiments reveal no specific ordering of the polymer inside the pores. P3HT-pSi hybrids show improved electrical transport by five orders of magnitude compared to porous silicon and power factor values comparable or exceeding other P3HT-inorganic hybrids. The analysis suggests different transport mechanisms in both materials. In pSi, the transport mechanism relates to a Meyer-Neldel compansation rule. The analysis of hybrids' data using the power law in Kang-Snyder model suggests that a doped polymer mainly provides charge carriers to the pSi matrix, similar to the behavior of a doped semiconductor. Heavily suppressed thermal transport in porous silicon is treated with a modified Landauer/Lundstrom model and effective medium theories, which reveal that pSi agrees well with the Kirkpatrick model with a 68% percolation threshold. Thermal conductivities of hybrids show an increase compared to the empty pSi but the overall thermoelectric figure of merit ZT of P3HT-pSi hybrid exceeds both pSi and P3HT as well as bulk Si.
The present paper proposes a novel approach for equilibrium selection in the infinitely repeated prisoner’s dilemma where players can communicate before choosing their strategies. This approach yields a critical discount factor that makes different predictions for cooperation than the usually considered sub-game perfect or risk dominance critical discount factors. In laboratory experiments, we find that our factor is useful for predicting cooperation. For payoff changes where the usually considered factors and our factor make different predictions, the observed cooperation is consistent with the predictions based on our factor.