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In der Dissertation “Leben am und vom Rhein. Aspekte der Alltagsgeschichte in St. Goar und St. Goarshausen vom Späten Mittelalter bis zum Ende des 17. Jahrhunderts” untersucht der Autor Richard Lange die Historie “kleiner Leute” in zwei Städten am Mittelrhein.
Die Studie konzentriert sich dabei auf die Geschichte jener Berufe, die direkt vom Rhein abhängig waren, also in erster Linie auf das Zollpersonal, die Kranbediensteten sowie die Salmenfischer. Hinzu kommen einige weitere Berufszweige wie Treidler, Fährleute, Schiffsleute sowie Händler und Betreiber von Wirtshäusern.
Für all diese Gruppen wird, soweit anhand der Quellen möglich, der Alltag ihres Berufes nachgezeichnet. Auf diesem Wege wird versucht, das bunte Bild, das sich auf dem Rhein bisweilen bot, darzustellen und gleichzeitig aufzuzeigen, in welcher nicht zu unterschätzenden Weise der Rhein das ganze Leben in St. Goar und St. Goarshausen über die Jahrhunderte hinweg beeinflusste.
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.
Speziell in Anwendungen mit intensiver Temperatur- und Korrosionsbeanspruchung finden vermehrt Phosphate als sogenannte chemische Binder für Hochleistungskeramiken Verwendung. Konkret ist die Summe der Reaktionsverläufe während des Bindemechanismus in Folge einer thermisch-induzierten Aushärtung und somit die Wirkungsweise von Phosphatbindern prinzipiell innerhalb der Fachliteratur nicht eindeutig untersucht. Innerhalb dieser Arbeit wurden aufbauend auf einer umfangreichen strukturanalytischen Prüfungsanordnung (Festkörper-NMR, RBA, REM-EDX) einer exemplarischen phosphatgebundenen Al₂O₃-MgAl₂O₄-Hochtemperaturkeramikzusammensetzung unter Einbeziehung verschiedenartiger anorganischer Phosphate grundlegende Bindemechanismen charakterisiert. Mechanisch-physikochemische Eigenschaftsuntersuchungen (STA, Dilatometrie, DMA, KBF) deckten zudem den Einfluss der eingesetzten Phosphate auf die Eigenschaftsentwicklungen der Feuerfestkeramiken bezüglich des Abbindeverhaltens, der Biegefestigkeit sowie der thermischen Längenänderung auf, welche mit Strukturänderungen korreliert wurden. Es wurde gezeigt, dass sich Bindemechanismen bei Verwendung von Phosphaten temperaturgeleitet (20 °C ≤ T ≤ 1500 °C) grundsätzlich aus zwei parallel ablaufenden Reaktionsabfolgen zusammensetzen, wobei die sich entwickelnden Phosphatphasen innerhalb der Keramikmasse quantitativ und qualitativ bezüglich ihrer Bindewirkung bewertet wurden. Zum einen wurde die Bildung eines festigkeitssteigernden Bindenetzwerks aus Aluminiumphosphaten meist amorpher Struktur identifiziert und charakterisiert. Dieses bindungsfördernde, dreidimensionale Aluminiumphosphatnetzwerk baut sich innerhalb der Initialisierungs- und Vernetzungsphasen temperaturgeleitet kontinuierlich über multiple Vernetzungsreaktionen homogen auf. Zum anderen werden Reaktionsabfolgen durch parallel ablaufende Strukturumwandlungen nicht aktiv-bindender Phosphatspezies wie Magnesium-, Calcium- oder Zirkoniumphosphate ergänzt, welche lediglich thermische Umwandlungsreaktionen der Ausgangsphosphate darstellen. Vermehrt bei T > 800 °C geht das phosphatische Bindenetzwerk Festkörperreaktionen mit MgAl₂O₄ unter Ausbildung und Agglomeration von Magnesium-Orthophosphat-Sinterstrukturen ein. Die Bildung dieser niedrigschmelzenden Hochtemperaturphasen führt zu einem teilweisen Bruch des Bindenetzwerks.
Wild bees are essential for the pollination of wild and cultivated plants. However, within the
last decades, the increasing intensification of modern agriculture has led to both a reduction and fragmentation as well as a degradation of the habitats wild bees need. The resulting loss of pollinators and their pollination poses an immense challenge to global food production. To support wild bees, the availability of flowering resources is essential. However, the flowering period of each resource is temporally limited and has different effects on pollinators and their pollination, depending on the time of their flowering.
Therefore, to efficiently promote and manage wild bee pollinators in agricultural landscapes, we identified species-specific key floral resources of three selected wild bee species and their spatial and temporal availability (CHAPTERS 2, 3 & 4). We examined, which habitat types predominantly provide these resources (CHAPTERS 3 & 4). We also investigated whether floral resource maps based on the use of these key resources and their spatial and temporal availability explain the abundance and development of the selected wild bees (CHAPTERS 3 & 4) and pollination (CHAPTER 5) better than habitat maps, that only indirectly account for the availability of floral resources.
For each of the species studied, we were able to identify different key pollen sources, predominantly woody plants in the early season (April/May) and increasingly herbaceous plants in the later season (June/July; CHAPTERS 2, 3 & 4). The open woody semi-natural habitats of our agricultural landscapes provided about 75% of the floral resources for the buff-tailed bumblebees, 60% for the red mason bees, and 55% for the horned mason bees studied, although they accounted for only 3% of the area (CHAPTERS 3 & 4). In addition, fruit orchards provided about 35% of the floral resources for the horned mason bees on 4% of the landscape area (CHAPTER 3). We showed that both mason bee species benefited from the resource availability in the surrounding landscapes (CHAPTER 3). Yet this was not the case for the bumblebees (CHAPTER 4). Instead, the weight gain of their colonies, the number of developed queen cells and their colony survival were higher with increasing proximity to forests. The proximity to forests also had a positive effect on the mason bees studied (CHAPTER 3). In addition, the red mason bees benefited from herbaceous semi-natural habitats. The proportion of built-up areas had a negative effect on the horned mason bees, and the proportion of arable land on the red mason bees. The habitat maps explained horned mason bee abundances equally well as the floral resource maps, but red mason bee abundances were distinctly better explained by key floral resources. The pollination of field bean increased with higher proportions of early floral resources, whereas synchronous floral resources showed no measurable reduction in their pollination (CHAPTER 5). Habitat maps also explained field bean pollination better than floral resource maps. Here, pollination increased with increasing proportions of built-up areas in the landscapes and decreased with increasing proportions of arable land.
Our results highlight the importance of the spatio-temporal availability of certain key species as resource plants of wild bees in agricultural landscapes. They show that habitat maps are ahead of, or at least equal to, spatio-temporally resolved floral resource maps in predicting wild bee development and pollination. Nevertheless, floral resource maps allow us to draw more accurate conclusions between key floral resources and the organisms studied. The proximity to forest edges had a positive effect on each of the three wild bee species studied. However, besides pure food availability, other factors seem to co-determine the occurrence of wild bees in agricultural landscapes.
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.
As a multilingual system,Wikipedia provides many challenges for academics and engineers alike. One such challenge is cultural contextualisation of Wikipedia content, and the lack of approaches to effectively quantify it. Additionally, what seems to lack is the intent of establishing sound computational practices and frameworks for measuring cultural variations in the data. Current approaches seem to mostly be dictated by the data availability, which makes it difficult to apply them in other contexts. Another common drawback is that they rarely scale due to a significant qualitative or translation effort. To address these limitations, this thesis develops and tests two modular quantitative approaches. They are aimed at quantifying culture-related phenomena in systems which rely on multilingual user-generated content. In particular, they allow to: (1) operationalise a custom concept of culture in a system; (2) quantify and compare culture-specific content- or coverage biases in such a system; and (3) map a large scale landscape of shared cultural interests and focal points. Empirical validation of these approaches is split into two parts. First, an approach to mapping Wikipedia communities of shared co-editing interests is validated on two large Wikipedia datasets comprising multilateral geopolitical and linguistic editor communities. Both datasets reveal measurable clusters of consistent co-editing interest, and computationally confirm that these clusters correspond to existing colonial, religious, socio economic, and geographical ties. Second, an approach to quantifying content differences is validated on a multilingual Wikipedia dataset, and a multi-platform (Wikipedia and Encyclopedia Britannica) dataset. Both are limited to a selected knowledge domain of national history. This analysis allows, for the first time on the large scale, to quantify and visualise the distribution of historical focal points in the articles on national histories. All results are cross-validated either by domain experts, or external datasets.
Main thesis contributions. This thesis: (1) presents an effort to formalise the process of measuring cultural variations in user-generated data; (2) introduces and tests two novel approaches to quantifying cultural contextualisation in multilingual data; (3) synthesises a valuable overview of literature on defining and quantifying culture; (4) provides important empirical insights on the effect of culture on Wikipedia content and coverage; demonstrates that Wikipedia is not contextfree, and these differences should not be treated as noise, but rather, as an important feature of the data. (5) makes practical service contributions through sharing data and visualisations.
This thesis addresses the reduced basis methods for parametrized quasilinear elliptic and parabolic partial differential equations with strongly monotone differential operator. It presents all of the ingredients of the reduced basis method: basis generation for reduced basis approximation, certification of the approximation error by suitable a-posteriori error control and an Offine-Online decomposition. The methodology is further applied to the magnetostatic and magnetoquasistatic approximations of Maxwell’s equations and its validity is confirmed by numerical examples.
The belief in a just world in face of injustice: victim, observer, and perpetrator perspectives
(2021)
Injustice happens every day either to us, to our neighbors, or people across the world. Yet, believing that the world is a fair place helps us to cope with this injustice and motivates us to behave fairly. Scholars have found that these functions that the belief in a just world (BJW) serves are crucial for maintaining mental health. However, the conditions under which BJW is functional and when people give up this belief are not well studied. The current dissertation aims to examine: when the BJW can be shattered, the role of the external world and other internal resources in face of injustice, and the role of BJW in predicting corrupt behavior. Three studies were conducted corresponding to each party of injustice: a victim, an observer, and a perpetrator.
Study 1 examined the effects of criminal victimization on BJW and buffering role of perceptions of justice in the criminal justice process. A cross-sectional study showed that victims of very severe crimes such as domestic violence and human trafficking had lower personal BJW than non-victims and victims of less severe crimes, and higher informational justice perceptions reduced the effect of victimization on the personal BJW. Study 2 aimed to test the changes in BJW after observing severe injustice. A longitudinal study showed that after observing school rampage attacks that happened at other schools, BJW of adolescent participants increased. Moreover, life satisfaction and perceived social support moderated the change of BJW. Study 3 examined relationships between BJW and corrupt behavior. A cross-sectional study showed that personal BJW can predict bribery behavior.
The findings of three studies provided evidence that BJW does not function in isolation. An external world and internal resources can reduce the threat of injustice on BJW. BJW plays an important role in predicting unfair behavior therefore authorities should aim to maintain the BJW of their citizens.
Graph-based data formats are flexible in representing data. In particular semantic data models, where the schema is part of the data, gained traction and commercial success in recent years. Semantic data models are also the basis for the Semantic Web - a Web of data governed by open standards in which computer programs can freely access the provided data. This thesis is concerned with the correctness of programs that access semantic data. While the flexibility of semantic data models is one of their biggest strengths, it can easily lead to programmers accidentally not accounting for unintuitive edge cases. Often, such exceptions surface during program execution as run-time errors or unintended side-effects. Depending on the exact condition, a program may run for a long time before the error occurs and the program crashes.
This thesis defines type systems that can detect and avoid such run-time errors based on schema languages available for the Semantic Web. In particular, this thesis uses the Web Ontology Language (OWL) and its theoretic underpinnings, i.e., description logics, as well as the Shapes Constraint Language (SHACL) to define type systems that provide type-safe data access to semantic data graphs. Providing a safe type system is an established methodology for proving the absence of run-time errors in programs without requiring execution. Both schema languages are based on possible world semantics but differ in the treatment of incomplete knowledge. While OWL allows for modelling incomplete knowledge through an open-world semantics, SHACL relies on a fixed domain and closed-world semantics. We provide the formal underpinnings for type systems based on each of the two schema languages. In particular, we base our notion of types on sets of values which allows us to specify a subtype relation based on subset semantics. In case of description logics, subsumption is a routine problem. For
the type system based on SHACL, we are able to translate it into a description
logic subsumption problem.
Enterprise Collaboration Systems (ECS) have become substantial for computer-mediated communication and collaboration among employees in organisations. As ECS combine features from social media and traditional groupware, a growing number of organisations implement ECS to facilitate collaboration among employees. Consequently, ECS form the core of the digital workplace. Thus, the activity logs of ECS are particularly valuable since they provide a unique opportunity for observing and analysing collaboration in the digital workplace.
Evidence from academia and practice demonstrates that there is no standardised approach for the analysis of ECS logs and that practitioners struggle with various barriers. Because current ECS analytics tools only provide basic features, academics and practitioners cannot leverage the full potential of the activity logs. As ECS activity logs are a valuable source for understanding collaboration in the digital workplace, new methods and metrics for their analysis are required. This dissertation develops Social Collaboration Analytics (SCA) as a method for measuring and analysing collaboration activities in ECS. To address the existing limitations in academia and practice and to contribute a method and structures for applying SCA in practice, this dissertation aims to answer two main research questions:
1. What are the current practices for measuring collaboration activities in Enterprise Collaboration Systems?
2. How can Social Collaboration Analytics be implemented in practice?
By answering the research questions, this dissertation seeks to (1) establish a broad thematic understanding of the research field of SCA and (2) to develop SCA as a structured method for analysing ac-tivity logs of ECS. As part of the first research question, this dissertation documents the status quo of SCA in the academic literature and practice. By answering the second research question, this dissertation contributes the SCA framework (SCAF), which guides the practical application of SCA. SCAF is the main contribution of this dissertation. The framework was developed based on findings from an analysis of 86 SCA studies, results from 6 focus groups and results from a survey among 27 ECS user companies. The phases of SCAF were derived from a comparison of established process models for data mining and business intelligence. The eight phases of the framework contain detailed descriptions, working steps, and guiding questions, which provide a step by step guide for the application of SCA in practice. Thus, academics and practitioners can benefit from using the framework.
The constant evaluation of the research outcomes in focus groups ensures both rigour and relevance. This dissertation employs a qualitative-dominant mixed-methods approach. As part of the university-industry collaboration initiative IndustryConnect, this research has access to more than 30 leading ECS user companies. Being built on a key case study and a series of advanced focus groups with representatives of user companies, this dissertation can draw from unique insights from practice as well as rich data with a longitudinal perspective.
The role of alternative resources for pollinators and aphid predators in agricultural landscapes
(2021)
The world wide decline of insects is often associated with loss of natural and semi-natural habitat caused by intensified land-use. Many insects provide important ecosystem services to agriculture, such as pest control or pollination. To efficiently promote insects on remaining semi-natural habitat we need precise knowledge of their requirements to non-crop habitat. This thesis focuses on identifying
the most important semi-natural habitats (forest edges, grasslands, and semi-open habitats) for pollinators and natural enemies of crop pests with respect to their food resource requirements. Special
attention is given to floral resources and their spatio-temporal distribution in agricultural landscapes.
Floral resource maps might get closer at characterizing landscapes the way they are experienced by insects compared to classical habitat maps. Performance of the two map types was compared on the prediction of wild bees and natural enemies that consume nectar and pollen, identifying habitats of special importance in the process. In wild bees, influences of spatio-temporal floral resource availability were analysed as well as habitat preferences of specific groups of bees. Understanding dietary needs of natural enemies of crop pests requires additional knowledge on prey use. To this end, ladybird gut contents have been analysed by means of high-throughput sequencing for insight into aphid prey-use.
Results showed, that wild bees were predicted better by floral resource maps compared to classical habitat maps. Forest edge area, as well as floral resources in forest edges had positive effects on abundance and diversity of rare bees and important crop pollinators. Similar patterns were retained for grassland diversity. Especially early floral resources seemed to have positive effects on wild bees. Crops and fruit trees produced a resource pulse in April that exceeded floral resource availability in May and June by tenfold. Most floral resources in forest edges appeared early in the season, with the highest floral density per area. Grasslands provided the lowest amount of floral resources but highest diversity, which was evenly distributed over the season.
Despite natural enemies need for floral resources, classical habitat maps performed better at predicting natural enemies of crop pests compared to floral resource maps. Classical habitat maps revealed a positive effect of forest edge habitat on the abundance of pest enemies, which translated into improved aphid control. Results from gut content analysis reveal high portions of pest aphid species and nettle aphids as well as a broader insight into prey spectra retained from ladybirds collected from sticky traps compared to individuals collected by hand. The aphid specific primer designed for this purpose will be helpful for identifying aphid consumption by ladybirds in future studies.
Findings of this thesis show the potential of floral resource maps for understanding interactions of wild bees and the landscape but also indicate that natural enemies are limited by other resources. I would like to highlight the positive effects of forest edges for different groups of bees as well as natural enemies and their performance on pest control.
The Stereotype Content Modell (SCM; Fiske et al., 2002) proposes two fundamental dimensions of social evaluation: Warmth, or the intentions of the target, and Competence, or the ability to enact these intentions. The practical applications of the SCM are very broad and have led to an assumption of universality of warmth and competence as fundamental dimensions of social evaluation.
This thesis has identified five mainly methodological shortcomings of the current SCM research and literature: (I) An insufficient initial scale development; (II) the usage of varying warmth and competence scales without sufficient scale property assessment in later research; (III) the dominant application of first-generation analytical approaches; (IV) the insufficient definition and empirical proof for the SCM’s assumption of universality; and (V) the limited application of the SCM for some social targets. These shortcomings were addressed in four article manuscripts strictly following open science recommendations.
Manuscript # 1 re-analysed published research using English SCM measures to investigate the measurement properties of the used warmth and competence scales. It reported the scales’ reliability, dimensionality and comparability across targets as well as the indicator-based parameter performance in a (multiple group) confirmatory factor analysis framework. The findings indicate that about two thirds of all re-analysed scales do not show the theoretically expected warmth and competence dimensionality. Moreover, only about eleven per cent allowed meaningful mean value comparisons between targets. Manuscript # 2 presents a replication of Manuscript # 1 in the national and language of German(y) generating virtually identical results as Manuscript # 1 did. Manuscript # 3 investigated the stereotype content of refugee subgroups in Germany. We showed that refugees was generally perceived unfavourably in terms of warmth and competence, but that the stereotype content varied based on the refugees’ geographic origin, religious affiliation, and flight motive. These results were generated using a reliability-corrected approach to compare mean values named alignment optimisation procedure. Manuscript # 4 developed and tested a high-performing SCM scale assessing occupational stereotypes a number of exploratory and confirmatory factor analyses.
There has been little research on out-of-school places of learning and their effec-tiveness in the context of ESD education measures. With the help of a multi-stage analysis, this study identifies out-of-school places of learning with reference to the ESD education concept in the Rhineland-Palatinate study area. To this end, qualita-tive literature analyses were first used to generate ESD criteria, which were opera-tionalised as a methodological instrument in the form of an ESD checklist for out-of-school places of learning. The data obtained in this way provide the basis for the creation of a geographically oriented learning location database with ESD refer-ence. A cartographic visualisation of the data results in a spatial distribution pattern: Thus, there are districts and cities that are well supplied with ESD learning loca-tions, but also real ESD learning location deserts where there is a need to catch up. Furthermore, there is an accumulation of ESD learning sites in areas close to for-ests.
A guideline-based explorative interview with two ESD experts provides additional insights into the question of how ESD has been implemented in the federal state of Rhineland-Palatinate, the extent to which there is a need for optimisation, and which continuing measures are being taken for ESD outside schools within the framework of Agenda 2030.
In addition, a quantitative questionnaire study was carried out with 1358 pupils at 30 out-of-school places of learning after participation in an educational measure, in which environmental awareness, attitudes towards environmental behaviour and local learning were also considered. By including non-ESD learning locations, a comparative study on the effectiveness of ESD learning locations became possible. The statistical data evaluation leads to a variety of interesting results. Contra-intuitively, for instance, the type of learning location (ESD or non-ESD learning lo-cation) is not a significant predictor for the environmental awareness and environ-mental behaviour of the surveyed students, whereas communication structures within educational measures at extracurricular learning locations, the multimediality and action orientation and the duration of educational measures have a significant influence.
Keywords: extracurricular learning locations, education for sustainable develop-ment (ESD), ESD criteria, learning location landscape Rhineland-Palatinate, ESD learning locations, environmental awareness, environmental behaviour.
Demografische und gesellschaftliche Wandlungsprozesse drohen die informelle Pflege als tragende Säule des Pflegesystems in Deutschland zunehmend zu erodieren. Während einerseits die Zahl an Pflegebedürftigen zukünftig ansteigen wird, nimmt andererseits die Zahl derer, die Pflegetätigkeiten übernehmen könnten ab. Zudem werden Frauen, die heute noch die Hauptlast der Pflegeverantwortung tragen, in Zukunft vermehrt erwerbstätig sein.
Vor diesem Hintergrund ergibt sich folgendes Problemfeld: Bei der Übernahme von informellen Pflegeaufgaben entsteht häufig ein Vereinbarkeitsproblem zwischen Pflege- und Erwerbstätigkeit. Pflegende reduzieren deshalb nicht selten ihre Erwerbsarbeitszeit oder geben die berufliche Tätigkeit ganz auf. Im Kontext des deutschen Sozialversicherungssystems bedeutet das, dass sich informell Pflegende erhöhten sozialen Risiken aussetzen, wenn sie ihre Erwerbs- und Verdienstpotenziale am Arbeitsmarkt nicht vollumfänglich ausschöpfen. Ferner entstehen indirekte Kosten beim Fiskus, die auf verringerte Einkommensteuer- und Sozialversicherungsbeiträge und/oder erhöhte Transferleistungen zurückzuführen sind. Diese sogenannten fiskalischen Kosten wurden im wissenschaftlichen und gesellschaftspolitischen Diskurs bisher jedoch nur unzureichend berücksichtigt.
Demnach ist das Ziel der vorliegenden Arbeit, die fiskalischen Kosten aufgrund informeller Pflege im deutschen Wohlfahrtsstaat empirisch zu prognostizieren. Dazu werden zunächst die Auswirkungen einer Pflegeübernahme auf das Arbeitsangebot evaluiert und dann in ein Steuer- und Sozialversicherungsmodell überführt, um so die fiskalischen Kosten aufgrund informeller Pflege zu quantifizieren. Mithilfe eines dynamischen Populationsmodells erfolgt abschließend die empirische Prognose der fiskalischen Kosten.
Im Ergebnis zeigt sich, dass beim Fiskus erhebliche (Mehr-)kosten durch informelle Pflege in Form von entgangenen Einkommensteuer- und Sozialversicherungsbeiträgen und/oder erhöhte Transferleistungen entstehen. Darüberhinaus ist die informelle Pflegeerbringung von Frauen aus staatlicher Perspektive kostengünstiger als die von Männern.
Scientific and public interest in epidemiology and mathematical modelling of disease spread has increased significantly due to the current COVID-19 pandemic. Political action is influenced by forecasts and evaluations of such models and the whole society is affected by the corresponding countermeasures for containment. But how are these models structured?
Which methods can be used to apply them to the respective regions, based on real data sets? These questions are certainly not new. Mathematical modelling in epidemiology using differential equations has been researched for quite some time now and can be carried out mainly by means of numerical computer simulations. These models are constantly being refinded and adapted to corresponding diseases. However, it should be noted that the more complex a model is, the more unknown parameters are included. A meaningful data adaptation thus becomes very diffcult. The goal of this thesis is to design applicable models using the examples of COVID-19 and dengue, to adapt them adequately to real data sets and thus to perform numerical simulations. For this purpose, first the mathematical foundations are presented and a theoretical outline of ordinary differential equations and optimization is provided. The parameter estimations shall be performed by means of adjoint functions. This procedure represents a combination of static and dynamical optimization. The objective function corresponds to a least squares method with L2 norm which depends on the searched parameters. This objective function is coupled to constraints in the form of ordinary differential equations and numerically minimized, using Pontryagin's maximum (minimum) principle and optimal control theory. In the case of dengue, due to the transmission path via mosquitoes, a model reduction of an SIRUV model to an SIR model with time-dependent transmission rate is performed by means of time-scale separation. The SIRUV model includes uninfected (U) and infected (V ) mosquito compartments in addition to the susceptible (S), infected (I) and recovered (R) human compartments, known from the SIR model. The unknwon parameters of the reduced SIR model are estimated using data sets from Colombo (Sri Lanka) and Jakarta (Indonesia). Based on this parameter estimation the predictive power of the model is checked and evaluated. In the case of Jakarta, the model is additionally provided with a mobility component between the individual city districts, based on commuter data. The transmission rates of the SIR models are also dependent on meteorological data as correlations between these and dengue outbreaks have been demonstrated in previous data analyses. For the modelling of COVID-19 we use several SEIRD models which in comparison to the SIR model also take into account the latency period and the number of deaths via exposed (E) and deaths (D) compartments. Based on these models a parameter estimation with adjoint functions is performed for the location Germany. This is possible because since the beginning of the pandemic, the cumulative number of infected persons and deaths
are published daily by Johns Hopkins University and the Robert-Koch-Institute. Here, a SEIRD model with a time delay regarding the deaths proves to be particularly suitable. In the next step, this model is used to compare the parameter estimation via adjoint functions with a Metropolis algorithm. Analytical effort, accuracy and calculation speed are taken into account. In all data fittings, one parameter each is determined to assess the estimated number of unreported cases.
Identifizierung und Quantifizierung von Mikroplastik mittels quantitativer ¹H-NMR Spektroskopie
(2021)
Plastic, and so microplastics (MP), are globally present and represent an increasingly significant problem for the environment. In order to understand the distribution and impact of MP it is important to identify and quantify MP over a wide range of sizes and to ensure comparability of studies. However, comparability of studies is made difficult or even impossible by different MP concentration data. There still is a great need for research in the field of size-independent, quantitative analysis of MP in environmental samples, especially with regard to mass-based MP concentration information. Therefore, this thesis aims to utilize quantitative ¹H-NMR spectroscopy (qNMR) as an alternative method in MP analysis. The qNMR method is a size-independent, mass-based method which can be used as an alternative for MP analysis and has potential for routine analysis. The proof-of-concept was demonstrated for LDPE, PET and PS particles (Chapter 2). Additionally, PVC, PA, and ABS particles were tested to cover the most important polymer types for MP-analysis (Chapter 3). Moreover, using PET, PVC and PS as examples it was examined whether the qNMR method can also be transferred to the more cost-effective NoD method (Chapter 4). Results of method validation of both methods (1D and NoD) show that quantification using the qNMR method is not only possible in principle, but also shows high accuracy (88.0-110 %) and detection limits (1 – 84 µg) that lie within the environmentally relevant range. Furthermore, it was examined whether not only high-field instruments are suitable for MP analysis, but also benchtop devices (low-field instruments), which are much more cost-effective in purchase and maintenance. Increasing measurement times for PET and PS to 30 min and for PVC to 140 min, the lower measuring frequency especially concerning resolving capacity could be compensated (Chapter 4). To address the question of potential matrix effects of environmental samples, matrix effects and recovery rates of sample preparation procedures, which have been developed specifically for the application of the qNMR method were investigated using PET fibers as an example (Chapter 5). It could be shown that environmental matrices do not interfere with the quantitative analysis of MP using qNMR methods. Specific sample preparation methods developed for qNMR analysis can be used with recovery rates > 80 % for different environmental matrices (Chapter 5). Finally, first orienting investigations for the simultaneous determination of several polymer types in one sample are reported (Chapter 6).
Mathematical models of species dispersal and the resilience of metapopulations against habitat loss
(2021)
Habitat loss and fragmentation due to climate and land-use change are among the biggest threats to biodiversity, as the survival of species relies on suitable habitat area and the possibility to disperse between different patches of habitat. To predict and mitigate the effects of habitat loss, a better understanding of species dispersal is needed. Graph theory provides powerful tools to model metapopulations in changing landscapes with the help of habitat networks, where nodes represent habitat patches and links indicate the possible dispersal pathways between patches.
This thesis adapts tools from graph theory and optimisation to study species dispersal on habitat networks as well as the structure of habitat networks and the effects of habitat loss. In chapter 1, I will give an introduction to the thesis and the different topics presented in this thesis. Chapter 2 will then give a brief summary of tools used in the thesis.
In chapter 3, I present our model on possible range shifts for a generic species. Based on a graph-based dispersal model for a generic aquatic invertebrate with a terrestrial life stage, we developed an optimisation model that models dispersal directed to predefined habitat patches and yields a minimum time until these patches are colonised with respect to the given landscape structure and species dispersal capabilities. We created a time-expanded network based on the original habitat network and solved a mixed integer program to obtain the minimum colonisation time. The results provide maximum possible range shifts, and can be used to estimate how fast newly formed habitat patches can be colonised. Although being specific for this simulation model, the general idea of deriving a surrogate can in principle be adapted to other simulation models.
Next, in chapter 4, I present our model to evaluate the robustness of metapopulations. Based on a variety of habitat networks and different generic species characterised by their dispersal traits and habitat demands, we modeled the permanent loss of habitat patches and subsequent metapopulation dynamics. The results show that species with short dispersal ranges and high local-extinction risks are particularly vulnerable to the loss of habitat across all types of networks. On this basis, we then investigated how well different graph-theoretic metrics of habitat networks can serve as indicators of metapopulation robustness against habitat loss. We identified the clustering coefficient of a network as the only good proxy for metapopulation robustness across all types of species, networks, and habitat loss scenarios.
Finally, in chapter 5, I utilise the results obtained in chapter 4 to identify the areas in a network that should be improved in terms of restoration to maximise the metapopulation robustness under limited resources. More specifically, we exploit our findings that a network’s clustering coefficient is a good indicator for metapopulation robustness and develop two heuristics, a Greedy algorithm and a deducted Lazy Greedy algorithm, that aim at maximising the clustering coefficient of a network. Both algorithms can be applied to any network and are not specific to habitat networks only.
In chapter 6, I will summarize the main findings of this thesis, discuss their limitations and give an outlook of future research topics.
Overall this thesis develops frameworks to study the behaviour of habitat networks and introduces mathematical tools to ecology and thus narrows the gap between mathematics and ecology. While all models in this thesis were developed with a focus on aquatic invertebrates, they can easily be adapted to other metapopulations.
Within the field of Business Process Management, business rules are commonly used to model company decision logic and govern allowed company behavior. An exemplary business rule in the financial sector could be for example:
”A customer with a mental condition is not creditworthy”. Business rules are
usually created and maintained collaboratively and over time. In this setting,
modelling errors can occur frequently. A challenging problem in this context is
that of inconsistency, i.e., contradictory rules which cannot hold at the same
time. For instance, regarding the exemplary rule above, an inconsistency would
arise if a (second) modeller entered an additional rule: ”A customer with a mental condition is always creditworthy”, as the two rules cannot hold at the same
time. In this thesis, we investigate how to handle such inconsistencies in business
rule bases. In particular, we develop methods and techniques for the detection,
analysis and resolution of inconsistencies in business rule bases