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Despite the significant presence of neuroactive substances in the environment, bioassays that allow to detect diverse groups of neuroactive mechanisms of action are not well developed and not properly integrated into environmental monitoring and chemical regulation. Therefore, there is a need to develop testing methods which are amenable for fast and high-throughput neurotoxicity testing. The overall goal of this thesis work is to develop a test method for the toxicological characterization and screening of neuroactive substances and their mixtures which could be used for prospective and diagnostic hazard assessment.
In this thesis, the behavior of zebrafish embryos was explored as a promising tool to distinguish between different neuroactive mechanisms of action. Recently, new behavioral tests have been developed including photomotor response (PMR), locomotor response (LMR) and spontaneous tail coiling (STC) tests. However, the experimental parameters of these tests lack consistency in protocols such as exposure time, imaging time, age of exposure, endpoint parameter etc. To understand how experimental parameters may influence the toxicological interpretation of behavior tests, a systematic review of existing behavioral assays was conducted in Chapter 2. Results show that exposure concentration and exposure duration highly influenced the comparability between different test methods and the spontaneous tail coiling (STC) test was selected for further testing based on its relative higher sensitivity and capacity to detect neuroactive substances (Chapter 2).
STC is the first observable motor activity generated by the developing neural network of the embryo which is assumed to occur as a result of the innervation of the muscle by the primary motor neurons. Therefore, STC could be a useful endpoint to detect effect on the muscle innervation and also the on the whole nervous system. Consequently, important parameters of the STC test were optimized and an automated workflow to evaluate the STC with the open access software KNIME® was developed (Chapter 3).
To appropriately interpret the observed effect of a single chemical and especially mixture effects, requires the understanding of toxicokinetics and biotransformation. Most importantly, the biotransformation capacity of zebrafish embryos might be limited and this could be a challenge for assessment of chemicals such as organophosphates which require a bioactivation step to effectively inhibit the acetylcholinesterase (AChE) enzyme. Therefore, the influence of the potential limited biotransformation on the toxicity pathway of a typical organophosphate, chlorpyrifos, was investigated in Chapter 5. Chlorpyrifos could not inhibit AChE and this was attributed to possible lack of biotransformation in 24 hpf embryos (Chapter 5).
Since neuroactive substances occur in the environment as mixtures, it is therefore more realistic to assess their combined effect rather than individually. Therefore, mixture toxicity was predicted using the concentration addition and independent action models. Result shows that mixtures of neuroactive substances with different mechanisms of action but similar effects can be predicted with concentration addition and independent action (Chapter 4). Apart
from being able to predict the combined effect of neuroactive substances for prospective risk assessment, it is also important to assess in retrospect the combined neurotoxic effect of environmental samples since neuroactive substances are the largest group of chemicals occurring in the environment. In Chapter 6, the STC test was found to be capable of detecting neurotoxic effects of a wastewater effluent sample. Hence, the STC test is proposed as an effect based tool for monitoring environmental acute and neurotoxic effects.
Overall, this thesis shows the utility and versatility of zebrafish embryo behavior testing for screening neuroactive substances and this allows to propose its use for prospective and diagnostic hazard assessment. This will enhance the move away from expensive and demanding animal testing. The information contained in this thesis is of great potential to provide precautionary solutions, not only for the exposure of humans to neuroactive chemicals but for the environment at large.
Die Raytracing-Beschleunigung durch dedizierte Datenstrukturen ist schon lange ein wichtiges Thema der Computergrafik. Im Allgemeinen werden dafür zwei unterschiedliche Ansätze vorgeschlagen: räumliche und richtungsbezogene Beschleunigungsstrukturen. Die vorliegende Arbeit stellt einen innovativen kombinierten Ansatz dieser beiden Bereiche vor, welcher weitere Beschleunigung der Strahlenverfolgung ermöglicht. Dazu werden moderne räumliche Datenstrukturen als Basisstrukturen verwendet und um vorberechnete gerichtete Sichtbarkeitsinformationen auf Basis von Schächten innerhalb einer originellen Struktur, dem Line Space, ergänzt.
Im Laufe der Arbeit werden neuartige Ansätze für die vorberechneten Sichtbarkeitsinformationen vorgeschlagen: ein binärer Wert, der angibt, ob ein Schacht leer oder gefüllt ist, sowie ein einzelner Vertreter, der als repräsentativer Kandidat die tatsächliche Oberfläche approximiert. Es wird gezeigt, wie der binäre Wert nachweislich in einer einfachen, aber effektiven Leerraumüberspringungs-Technik (Empty Space Skipping) genutzt wird, welche unabhängig von der tatsächlich verwendeten räumlichen Basisdatenstruktur einen Leistungsgewinn beim Raytracing von bis zu 40% ermöglicht. Darüber hinaus wird gezeigt, dass diese binären Sichtbarkeitsinformationen eine schnelle Technik zur Berechnung von weichen Schatten und Umgebungsverdeckung auf der Grundlage von Blockerapproximationen ergeben. Obwohl die Ergebnisse einen gewissen Ungenauigkeitsfehler enthalten, welcher auch dargestellt und diskutiert wird, zeigt sich, dass eine weitere Traversierungsbeschleunigung von bis zu 300% gegenüber der Basisstruktur erreicht wird. Als Erweiterung zu diesem Ansatz wird die repräsentative Kandidatenvorberechnung demonstriert, welche verwendet wird, um die indirekte Lichtberechnung durch die Integration von kaum wahrnehmbaren Bildfehlern signifikant zu beschleunigen. Schließlich werden Techniken vorgeschlagen und bewertet, die auf zweistufigen Strukturen und einer Nutzungsheuristik basieren. Diese reduzieren den Speicherverbrauch und die Approximationsfehler bei Aufrechterhaltung des Geschwindigkeitsgewinns und ermöglichen zusätzlich weitere Möglichkeiten mit Objektinstanziierungen und starren Transformationen.
Alle Beschleunigungs- und Speicherwerte sowie die Näherungsfehler werden gemessen, dargestellt und diskutiert. Insgesamt zeigt sich, dass durch den Line Space eine deutliche Erhöhung der Raytracing Leistung auf Kosten eines höheren Speicherverbrauchs und möglicher Annäherungsfehler erreicht wird. Die vorgestellten Ergebnisse zeigen damit die Leistungsfähigkeit des kombinierten Ansatzes und eröffnen weitere Möglichkeiten für zukünftige Arbeiten.
The stands surveyed are among the last closed canopy forests in Rwanda. Their exploration began in the early twentieth century and is still ongoing. Previous studies were mainly concerned with plant sociological issues and presented references to environmental factors in anecdotal form, at best using indirect ordination methods. The present study undertakes a classification of the vegetation with numerical methods and establishes quantitative relationships of the species’ distributional structure to environmental parameters using spatially explicit procedures. For this purpose, 94 samples were taken in 100 m² hexagonal plots. Of these, 70 samples are from Nyungwe, 14 are from Gishwati, and 10 are from Cyamudongo. Given the homogeneity of the terrain and vegetation, all vegetation types encountered, all types of stands, and all vegetation strata were included. The beta diversity is expressed by an average Bray-Curtis dissimilarity of 0.92, and in JOST’S (2007) numbers equivalents, 37.90 equally likely samples would be needed to represent the diversity encountered. Within the survey, 1198 species in 127 families were collected. Among the specimens are 6 local endemics and 40 Albertine Rift endemics. Resulting from UPGMA and FCM-NC, 20 to 40 plant communities were established depending on the level of resolution. It can be inferred by means of a Mantel correlogram that the mean zone of influence of a single vegetation stand, as sampled by a 100 m² plot in Nyungwe Forest, ranges between 0.016 and 3.42 km. Of the communities compiled using FCM-NC and UPGMA, 50% consist of individual samples. Beyond undersampling, natural small-scale discontinuities are reflected by this result. Partial db-RDA resulted in an explained variation of 9.60% and 14.41% for environmental and soil factors, respectively. Utilising variation partitioning analyses based on CCA and tb-RDA, between 21.70% and 37.80% of the variation in vegetation data could be explained. The spatially structured fraction of these parameters accounts for between 30.50% and 49.80% of the explained variation (100%). The purely environmental parameters account for a share of 10.30% to 16.30%, whereby the lower limit originates from the unimodal approach and has lost its statistical significance. The soil variables, also after partial analysis, account for a share of 19.00% to 35.70%. While the residual impact of the climatic parameters is hardly significant, the effect of the soil properties is prevalent. In general, the spatially structured fraction of the parameters is predominant here. While on the broad-scale climatic factors, the altitude a.s.l. and the geology are determining factors, some soil parameters and matrix components also show their impacts here. In the mid-range of the scale, it is the forest matrix, the soil types, and the geology that determine species distribution. While in the fine range of the scale, some unrecorded parameters seem to have an effect, there are also neutral processes that determine species composition.
Enterprise collaboration platforms are increasingly gaining importance in organisations. Integrating groupware functionality and enterprise social software (ESS), they have substantially been transforming everyday work in organisations. While traditional collaboration systems have been studied in Computer Supported Cooperative Work (CSCW) for many years, the large-scale, infrastructural and heterogeneous nature of enterprise collaboration platforms remains uncharted. Enterprise collaboration platforms are embedded into organisations’ digital workplace and come with a high degree of complexity, ambiguity, and generativity. When introduced, they are empty shells with no pre-determined purposes of use. They afford interpretive flexibility, and thus are shaping and being shaped by and in their social context. Outcomes and benefits emerge and evolve over time in an open-ended process and as the digital platform is designed through use. In order to make the most of the platform and associated continuous digital transformation, organisations have to develop the necessary competencies and capabilities.
Extant literature on enterprise collaboration platforms has proliferated and provide valuable insights on diverse topics, such as implementation strategies, adoption hurdles, or collaboration use cases, however, they tend to disregard their evolvability and related multiple time frames and settings. Thus, this research aims to identify, investigate, and theorise the ways that enterprise collaboration platforms are changing over time and space and the ways that organisations build digital transformation capabilities. To address this research aim two different case study types are conducted: i) in-depth longitudinal qualitative case study, where case narratives and visualisations capturing hard-to-summarise complexities in the enterprise collaboration platform evolution are developed and ii) multiple-case studies to capture, investigate, and compare cross-case elements that contribute to the shaping of enterprise collaboration platforms in different medium-sized and large organisations from a range of industries. Empirical data is captured and investigated through a multi-method research design (incl. focus groups, surveys, in-depth interviews, literature reviews, qualitative content analysis, descriptive statistics) with shifting units of analysis. The findings reveal unique change routes with unanticipated outcomes and transformations, context-specific change strategies to deal with multiple challenges (e.g. GDPR, works council, developments in the technological field, competing systems, integration of blue-collar workers), co-existing platform uses, and various interacting actors from the immediate setting and broader context. The interpretation draws on information infrastructure (II) as a theoretical lens and related sociotechnical concepts and perspectives (incl. inscriptions, social worlds, biography of artefacts). Iteratively, a conceptual model of the building of digital transformation capabilities is developed, integrating the insights gained from the study of enterprise collaboration platform change and developed monitoring change tools (e.g. MoBeC framework). It assists researchers and practitioners in understanding the building of digital transformation capabilities from a theoretical and practical viewpoint and organisations implement the depicted knowledge in their unique digital transformation processes.
Human action recognition from a video has received growing attention in computer vision and has made significant progress in recent years. Action recognition is described as a requirement to decide which human actions appear in videos. The difficulties involved in distinguishing human actions are due to the high complexity of human behaviors as well as appearance variation, motion pattern variation, occlusions, etc. Many applications use human action recognition on captured video from cameras, resulting in video surveillance systems, health monitoring, human-computer interaction, and robotics. Action recognition based on RGB-D data has increasingly drawn more attention to it in recent years. RGB-D data contain color (Red, Green, and Blue (RGB)) and depth data that represent the distance from the sensor to every pixel in the object (object point). The main problem that this thesis deals with is how to automate the classification of specific human activities/actions through RGB-D data. The classification process of these activities utilizes a spatial and temporal structure of actions. Therefore, the goal of this work is to develop algorithms that can distinguish these activities by recognizing low-level and high-level activities of interest from one another. These algorithms are developed by introducing new features and methods using RGB-D data to enhance the detection and recognition of human activities. In this thesis, the most popular state-of-the-art techniques are reviewed, presented, and evaluated. From the literature review, these techniques are categorized into hand-crafted features and deep learning-based approaches. The proposed new action recognition framework is based on these two categories that are approved in this work by embedding novel methods for human action recognition. These methods are based on features extracted from RGB-D data that are
evaluated using machine learning techniques. The presented work of this thesis improves human action recognition in two distinct parts. The first part focuses on improving current successful hand-crafted approaches. It contributes into two significant areas of state-of-the-art: Execute the existing feature detectors, and classify the human action in the 3D spatio-temporal domains by testing a new combination of different feature representations. The contributions of this part are tested based on machine learning techniques that include unsupervised and supervised learning to evaluate this suitability for the task of human action recognition. A k-means clustering represents the unsupervised learning technique, while the supervised learning technique is represented by: Support Vector Machine, Random Forest, K-Nearest Neighbor, Naive Bayes, and Artificial Neural Networks classifiers. The second part focuses on studying the current deep-learning-based approach and how to use it with RGB-D data for the human action recognition task. As the first step of each contribution, an input video is analyzed as a sequence of frames. Then, pre-processing steps are applied to the video frames, like filtering and smoothing methods to remove the noisy data from each frame. Afterward, different motion detection and feature representation methods are used to extract features presented in each frame. The extracted features
are represented by local features, global features, and feature combination besides deep learning methods, e.g., Convolutional Neural Networks. The feature combination achieves an excellent accuracy performance that outperforms other methods on the same RGB-D datasets. All the results from the proposed methods in this thesis are evaluated based on publicly available datasets, which illustrate that using spatiotemporal features can improve the recognition accuracy. The competitive experimental results are achieved overall. In particular, the proposed methods can be better applied to the test set compared to the state-of-the-art methods using the RGB-D datasets.
Wildbienen sind unerlässlich für die Bestäubung von Wild- und Kulturpflanzen. Die zunehmende Intensivierung der Landwirtschaft führte jedoch sowohl zu einer Verringerung und Fragmentierung als auch zu einer Wertminderung der von ihnen benötigten Lebensräume innerhalb der letzten Jahrzehnte. Die damit einhergehenden Verluste von Bestäubern und ihrer Bestäubung stellt die weltweite Nahrungsmittelproduktion vor eine immense Herausforderung. Zur Förderung von Wildbienen ist die Verfügbarkeit von Blüteressourcen essentiell. Die Blühdauer einzelner Ressourcen ist jedoch zeitlich begrenzt und hat, je nach Blütezeitpunkt, unterschiedliche Effekte auf Bestäuber und deren Bestäubung.
Um Wildbienen als Bestäuber in Agrarlandschaften effizient fördern und nutzen zu können, identifizierten wir deshalb die artspezifischen Schlüsselressourcen dreier ausgewählter Wildbienen und deren räumliche und zeitliche Verfügbarkeit (KAPITEL 2, 3 & 4). Wir untersuchten, welche Habitatstypen diese Ressourcen überwiegend bereitstellen (KAPITEL 3 & 4). Wir untersuchten zudem, ob Blütenressourcenkarten, die auf der Nutzung dieser Schlüsselressourcen und deren räumlich zeitlicher Verfügbarkeit basieren, die Abundanzen und die Entwicklung der ausgewählten Wildbienen (KAPITEL 3 & 4) und die Bestäubung (KAPITEL 5) besser erklären als Habitatkarten, die die Verfügbarkeit von Blüteressourcen nur indirekt beschreiben.
Für jede der untersuchten Arten konnten wir unterschiedliche, im frühen Saisonverlauf (April/Mai) überwiegend holzige im späteren Verlauf (Juni/Juli) auch zunehmend krautige, Schlüsselarten identifizieren (KAPITEL 2, 3 & 4). Die Wildobst- und Wildheckengehölze unserer Agrarlandschaften stellten rund 75% der Blütenressourcen für Erdhummeln, 60% für Rote Mauerbienen und 55% für Gehörnte Mauerbienen bereit, obwohl sie einen Flächenanteil von nur 3% ausmachten (KAPITEL 3 & 4). Obstplantagen stellten zusätzlich rund 35% des Blütenangebots für Gehörnte Mauerbienen auf 4% der Fläche bereit (KAPITEL 3). Wir konnten zeigen, dass beide Mauerbienenarten von der Ressourcenverfügbarkeit in den umliegenden Landschaften profitierten (KAPITEL 3). Bei Erdhummeln zeigte sich dieser Zusammenhang jedoch nicht (KAPITEL 4). Stattdessen waren die Gewichtszunahme ihrer Kolonien, die Anzahlen der darin ausgebildeten Königinnenzellen und die Überlebensdauer der Kolonie mit zunehmender Nähe zum Wald höher. Ebenfalls auf die beiden Mauerbienenarten wirkte sich die Waldnähe positiv aus (KAPITEL 3). Daneben profitierten Rote Mauerbienen durch krautige halbnatürliche Habitate. Nachteilig wirkten sich Siedlungsflächen auf die Gehörnten Mauerbienen, und Ackerland auf die Roten Mauerbienen aus. Habitatkarten erklärten die Abundanzen der Gehörnten Mauerbienen gleich gut wie Blütenressourcenkarten, jedoch wurden die Abundanzen der Roten Mauerbienen deutlich besser durch Schlüsselressourcen erklärt. Die Bestäubung der Ackerbohne erhöhte sich mit höheren Anteilen früher Blütenressourcen (KAPITEL 5). Dabei zeigte sich keine messbare Reduktion der Bestäubung durch gleichzeitig blühende Ressourcen. Habitatkarten erklärten die Bestäubung der Ackerbohne auch besser als Blütenressourcenkarten. Dabei nahm die Bestäubung mit zunehmenden Anteilen an Siedlungsflächen in den Landschaften zu und reduzierte sich mit zunehmenden Anteilen von Ackerland.
Unsere Ergebnisse verdeutlichen die Wichtigkeit der räumlich-zeitlichen Verfügbarkeit bestimmter Schlüsselarten als Ressourcenpflanzen von Wildbienen in Agrarlandschaften. Sie zeigen, dass Habitatkarten detaillierten Blütenressourcenkarten in der Vorhersage der Entwicklung von Wildbienen und deren Bestäubung voraus oder zumindest ebenbürtig sind. Dennoch ermöglichen es
Blütenressourcenkarten, genauere Schlüsse zwischen den einzelnen Ressourcen und den untersuchten Organismen zu ziehen. Die Nähe zu Waldrändern wirkte sich positiv auf jede der drei untersuchten Wildbienenarten aus. Neben der reinen Nahrungsverfügbarkeit scheinen jedoch weitere Faktoren das Vorkommen von Wildbienen in Agrarlandschaften mitzubestimmen.
Content and Language Integrated Learning (CLIL) has experienced growing importance in the last decades and an increasing number of schools have already implemented CLIL programmes or are planning to do so. Though the potentials of CLIL programmes are widely praised, first research results also raise doubts if CLIL students can live up to these high expectations. Both Fehling (2005) as well as Rumlich (2013; 2016), for example, found that CLIL programmes not inevitably show the expected results but that the CLIL students’ success might also be at least partially explained by other influences, such as the selection process of future CLIL students. Hence, CLIL students apparently fall short of the high expectations that are usually connected to the respective CLIL programmes and as this is mainly based on the unsatisfactory quality of these programmes, Rumlich concludes that “it is now high time to focus on the quality of CLIL provision” (Rumlich 2016: 452). He continues to explain that “the promises of CLIL do not materialise automatically owing to the fact that another language is used for learning in a non-language subject” (Rumlich 2016: 452). It must be assumed that the success of CLIL teaching also highly depends on the quality of the CLIL teachers.
In contrast to the continuously growing number of CLIL schools, however, the number of specifically trained CLIL teachers is comparably small. In Germany, CLIL teachers are not (yet) required to attend any special training in order to teach in a CLIL programme. Notwithstanding, is it sufficient for a CLIL teacher only to be trained in the content subject and the foreign language? Or does CLIL teaching require more than the sum of these two components? Do CLIL teachers need additional teaching competences to the ones of a content and a language teacher? In the light of the recent findings of CLIL programmes falling short of the high expectations, the answer to these questions must clearly be “Yes”. Hence, in order to appropriately train (future) CLIL teachers, special training programmes need to be developed which consider the teachers’ individual educational backgrounds, i.e. their qualifications as language and/or as content teachers and build up on these competences through adding the CLIL-specific teaching competences.
Therefore, this thesis aims at developing a German Framework for CLIL Teacher Education, which considers both the already published, theory-based standards of CLIL teacher education as well as the practical perspective of experienced CLIL teachers in Germany. This German Framework for CLIL Teacher Education classifies the different teaching competences, which are derived from integrating the theoretical and the practical perspective on CLIL teacher education, with regard to the three different competence areas, i.e. the general teaching competence, the language teaching competence and the subject teaching competence and is hence adaptable to different CLIL settings and educational backgrounds. In addition to developing this German Framework for CLIL Teacher Education, which provides the content of future CLIL teacher education programmes, this thesis discusses different forms of structurally implementing CLIL teacher education programmes in the existing structures of teacher education in Germany. This is achieved through analysing the current state of the art of CLIL teacher education at German universities and systematising the different forms of implementing these training programmes in the prevailing educational structures. Building on these first two steps, in the third and final step, this thesis develops a CLIL teacher education programme at a German university that is based on the results and elements of the German Framework for CLIL Teacher Education as well as the state of the art of CLIL teacher education in Germany. Thus, this thesis is allocated at the intersection between foreign language teaching as well as teacher education and is structured in eleven chapters.
Als mehrsprachiges System stelltWikipedia viele Herausforderungen sowohl an Akademiker als auch an Ingenieure. Eine dieser Herausforderungen ist die kulturelle Kontextualisierung der Wikipedia-Inhalte und der Mangel an Ansätzen zu ihrer effektiven Quantifizierung. Außerdem scheint es an der Absicht zu fehlen, solide Berechnungspraktiken und Rahmenbedingungen für die Messung kultureller Variationen in dem Datenmaterial zu schaffen. Die derzeitigen Ansätze scheinen hauptsächlich von der Datenverfügbarkeit diktiert zu werden, was ihre Anwendung in anderen Kontexten erschwert. Ein weiterer häufiger Nachteil ist, dass sie aufgrund eines erheblichen qualitativen oder Übersetzungsaufwands selten skalieren. Um diesen Einschränkungen zu begegnen, werden in dieser Arbeit zwei modulare quantitative Ansätze entwickelt und getestet. Sie zielen darauf ab, kulturbezogene Phänomene in Systemen zu quantifizieren, die auf mehrsprachigem, nutzergeneriertem Inhalt beruhen. Insbesondere
ermöglichen sie es: (1) einen benutzerdefinierten Kulturbegriff in einem System zu operationalisieren; (2) kulturspezifische Inhalts- oder Abdeckungsverzerrungen in einem solchen System zu quantifizieren und zu vergleichen; und (3) eine großräumige Landschaft mit gemeinsamen kulturellen Interessen und Schwerpunkten abzubilden. Die empirische Validierung dieser Ansätze ist in zwei Teile gegliedert. Erstens wird ein Ansatz zur Kartierung von Wikipedia-Gemeinschaften mit gemeinsamen redaktionellen Interessen auf zwei großenWikipedia Datensätzen validiert, die multilaterale geopolitische und sprachliche Redakteursgemeinschaften umfassen. Beide Datensätze zeigen messbare Cluster von konsistenten Mitredaktionsinteressen und bestätigen rechnerisch, dass diese Cluster mit bestehenden kolonialen, religiösen, sozioökonomischen und geographischen Bindungen übereinstimmen.
Zweitens wird ein Ansatz zur Quantifizierung von Inhaltsunterschieden anhand eines mehrsprachigen Wikipedia-Datensatzes und eines Multiplattform-Datensatzes (Wikipedia und Encyclopedia Britannica) validiert. Beide sind auf einen ausgewählten Wissensbereich der Nationalgeschichte beschränkt. Diese Analyse ermöglicht es erstmals im großen Maßstab, die Verteilung der historischen Schwerpunkte in den Artikeln zur Nationalgeschichte zu quantifizieren und zu visualisieren. Alle Ergebnisse werden entweder von Fachexperten oder von externen Datensätzen kreuzvalidiert. Die wichtigsten Beiträge der Dissertation. Diese Dissertation: (1) stellt einen Versuch dar, den Prozess der Messung kultureller Variationen in nutzergeneriertem Datenmaterial zu formalisieren; (2) stellt zwei neue Ansätze zur Quantifizierung der kulturellen Kontextualisierung in mehrsprachigem Datenmaterial vor und testet sie; (3) schafft einen wertvollen Überblick über die Literatur zur Definition und Quantifizierung von Kultur; (4) liefert wichtige empirische Erkenntnisse über die Wirkung von Kultur auf den Inhalt und die Abdeckung von Wikipedia; zeigt, dass Wikipedia nicht kontextfrei ist, und dass diese Unterschiede nicht als Rauschen, sondern als ein wichtiges Merkmal des Datenmaterials behandelt werden sollten. (5) leistet einen praktischen Beitrag durch das Teilen von Datenmaterial und Visualisierungen.
Diese Arbeit befasst sich mit den reduzierten Basismethoden für parametrisierte quasilineare elliptische und parabolische partielle Differentialgleichungen mit stark monotonem Differentialoperator. Es werden alle Bestandteile der Methode mit reduzierter Basis vorgestellt: Basisgenerierung für reduzierte Approximation, Zertifizierung des Approximationsfehlers durch geeignete a-posteriori Fehlerkontrolle und Offine-Online-Zerlegung. Die Methodik wird ferner auf die magnetostatischen und magnetoquasistatischen Näherungen der Maxwellschen Gleichungen angewendet und ihre Gültigkeit wird durch numerische Beispiele bestätigt.
The belief in a just world in face of injustice: victim, observer, and perpetrator perspectives
(2021)
Jeden Tag geschieht uns, unseren Nachbarn oder Menschen auf der ganzen Welt Ungerechtigkeit. Doch der Glaube an eine gerechte Welt (GGW) hilft uns, mit dieser Ungerechtigkeit umzugehen, und motiviert uns, uns gerecht zu verhalten. Studien haben gezeigt, dass diese Funktionen, die der GGW erfüllt, für die Aufrechterhaltung der psychischen Gesundheit bedeutend sind. Die Bedingungen, unter denen der GGW funktioniert und wann Menschen diesen Glauben aufgeben, sind jedoch nicht gut untersucht. In der vorliegenden Dissertation wird untersucht, wann der GGW erschüttert werden kann, welche Rolle die Außenwelt und andere interne Ressourcen angesichts von Ungerechtigkeit spielen und welche Rolle der GGW bei der Vorhersage korrupten Verhaltens spielt. Es wurden drei Studien durchgeführt, die jeweils einer Seite der Ungerechtigkeit entsprechen: einem Opfer, einem Beobachter und einem Täter.
Studie 1 untersuchte die Auswirkungen einer kriminellen Viktimisierung auf den GGW und die schützende Rolle der Gerechtigkeitsvorstellungen im Strafrechtsprozess. Diese Studie zeigte, dass Opfer sehr schwerer Straftaten, wie häusliche Gewalt und Menschenhandel, einen niedrigeren persönlichen GGW aufwiesen als Nicht-Opfer und Opfer weniger schwerer Straftaten, und dass eine höhere Wahrnehmung der informationelle Gerechtigkeit die Auswirkungen der Viktimisierung auf den persönlichen GGW verringerte. Studie 2 hatte zum Ziel die Veränderungen des GGW nach der Beobachtung schwerer Ungerechtigkeit zu untersuchen. Diese Studie zeigte, dass der GGW der jugendlichen Teilnehmer nach der Beobachtung von Amokläufen an anderen Schulen anstieg. Außerdem beeinflussten Lebenszufriedenheit und wahrgenommene soziale Unterstützung die Veränderung der GGW. Studie 3 untersuchte die Beziehungen zwischen GGW und korruptem Verhalten. Eine Querschnittsstudie zeigte, dass der persönliche GGW das Korruptionsverhalten vorhersagen kann.
Die Ergebnisse der drei Studien haben gezeigt, dass GGW nicht isoliert betrachtet werden kann. Eine externe Welt und interne Ressourcen können die Bedrohung durch Ungerechtigkeit auf dem GGW reduzieren. Der GGW spielt eine wichtige Rolle bei der Vorhersage von ungerechtem Verhalten, weshalb die Behörden bestrebt sein sollten, den GGW ihrer Bürger zu erhalten.