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This work addresses the challenge of calibrating multiple solid-state LIDAR systems. The study focuses on three different solid-state LIDAR sensors that implement different hardware designs, leading to distinct scanning patterns for each system. Consequently, detecting corresponding points between the point clouds generated by these LIDAR systems—as required for calibration—is a complex task. To overcome this challenge, this paper proposes a method that involves several steps. First, the measurement data are preprocessed to enhance its quality. Next, features are extracted from the acquired point clouds using the Fast Point Feature Histogram method, which categorizes important characteristics of the data. Finally, the extrinsic parameters are computed using the Fast Global Registration technique. The best set of parameters for the pipeline and the calibration success are evaluated using the normalized root mean square error. In a static real-world indoor scenario, a minimum root mean square error of 7 cm was achieved. Importantly, the paper demonstrates that the presented approach is suitable for online use, indicating its potential for real-time applications. By effectively calibrating the solid-state LIDAR systems and establishing point correspondences, this research contributes to the advancement of multi-LIDAR fusion and facilitates accurate perception and mapping in various fields such as autonomous driving, robotics, and environmental monitoring.
Focusing on the triangulation of detective fiction, masculinity studies and disability studies, "Investigating the Disabled Detective – Disabled Masculinity and Masculine Disability in Contemporary Detective Fiction" shows that disability challenges common ideals of (hegemonic) masculinity as represented in detective fiction. After a theoretical introduction to the relevant focal points of the three research fields, the dissertation demonstrates that even the archetypal detectives Dupin and Holmes undermine certain nineteenth-century masculine ideals with their peculiarities. Shifting to contemporary detective fiction and adopting a literary disability studies perspective, the dissertation investigates how male detectives with a form of neurodiversity or a physical impairment negotiate their masculine identity in light of their disability in private and professional contexts. It argues that the occupation as a detective supports the disabled investigator to achieve ‘masculine disability’. Inversing the term ‘disabled masculinity’, predominantly used in research, ‘masculine disability’ introduces a decisively gendered reading of neurodiversity and (acquired) physical impairment in contemporary detective fiction. The term implies that the disabled detective (re)negotiates his masculine identity by implementing the disability in his professional investigations and accepting it as an important, yet not defining, characteristic of his (gender) identity. By applying this approach to five novels from contemporary British and American detective fiction, the dissertation demonstrates that masculinity and disability do not negate each other, as commonly assumed. Instead, it emphasises that disability allows the detective, as much as the reader, to rethink masculinity.
Empirical studies in software engineering use software repositories as data sources to understand software development. Repository data is either used to answer questions that guide the decision-making in the software development, or to provide tools that help with practical aspects of developers’ everyday work. Studies are classified into the field of Empirical Software Engineering (ESE), and more specifically into Mining Software Repositories (MSR). Studies working with repository data often focus on their results. Results are statements or tools, derived from the data, that help with practical aspects of software development. This thesis focuses on the methods and high order methods used to produce such results. In particular, we focus on incremental methods to scale the processing of repositories, declarative methods to compose a heterogeneous analysis, and high order methods used to reason about threats to methods operating on repositories. We summarize this as technical and methodological improvements. We contribute the improvements to methods and high-order methods in the context of MSR/ESE to produce future empirical results more effectively. We contribute the following improvements. We propose a method to improve the scalability of functions that abstract over repositories with high revision count in a theoretically founded way. We use insights on abstract algebra and program incrementalization to define a core interface of highorder functions that compute scalable static abstractions of a repository with many revisions. We evaluate the scalability of our method by benchmarks, comparing a prototype with available competitors in MSR/ESE. We propose a method to improve the definition of functions that abstract over a repository with a heterogeneous technology stack, by using concepts from declarative logic programming and combining them with ideas on megamodeling and linguistic architecture. We reproduce existing ideas on declarative logic programming with languages close to Datalog, coming from architecture recovery, source code querying, and static program analysis, and transfer them from the analysis of a homogeneous to a heterogeneous technology stack. We provide a prove-of-concept of such method in a case study. We propose a high-order method to improve the disambiguation of threats to methods used in MSR/ESE. We focus on a better disambiguation of threats, operationalizing reasoning about them, and making the implications to a valid data analysis methodology explicit, by using simulations. We encourage researchers to accomplish their work by implementing ‘fake’ simulations of their MSR/ESE scenarios, to operationalize relevant insights about alternative plausible results, negative results, potential threats and the used data analysis methodologies. We prove that such way of simulation based testing contributes to the disambiguation of threats in published MSR/ESE research.
Predictive Process Monitoring is becoming more prevalent as an aid for organizations to support their operational processes. However, most software applications available today require extensive technical know-how by the operator and are therefore not suitable for most real-world scenarios. Therefore, this work presents a prototype implementation of a Predictive Process Monitoring dashboard in the form of a web application. The system is based on the PPM Camunda Plugin presented by Bartmann et al. (2021) and allows users to easily create metrics, visualizations to display these metrics, and dashboards in which visualizations can be arranged. A usability test is with test users of different computer skills is conducted to confirm the application’s user-friendliness.
Challenges of Implementing Innovation Strategies at Large Organizations: A case of Lotte Group
(2023)
For many decades, one of the most important focuses of research has been on determining whether or not there is a correlation between the size of an organization and its level of innovation. Unlike small companies, large companies often have well-established structure that are hard to change and change managements seems to be much more difficult especially related to innovation. Nevertheless, there are many examples to prove the opposites. Some large organization like Apple, Amazon... always show great innovation efforts and keep changing in a much positive way. Therefore, the aim of this thesis is to discuss of how large organization can be able to implement innovation when having much drawbacks compare to SMEs. Through the use of a qualitative research approach, researcher was able to explore essential information on the innovation strategies that large companies are using in order to innovate and how they could overcome existing challenges by studying the working process of Lotte Group – one of the biggest companies in Korea.
In the last decade, policy-makers around the world have turned their attention toward the creative industry as the economic engine and significant driver of employments. Yet, the literature suggests that creative workers are one of the most vulnerable work-forces of today’s economy. Because of the highly deregulated and highly individuated environment, failure or success are believed to be the byproduct of individual ability and commitment, rather than a structural or collective issue. This thesis taps into the temporal, spatial, and social resolution of digital behavioural data to show that there are indeed structural and historical issues that impact individuals’ and
groups’ careers. To this end, this thesis offers a computational social science research framework that brings together the decades-long theoretical and empirical knowledge of inequality studies, and computational methods that deal with the complexity and scale of digital data. By taking music industry and science as use cases, this thesis starts off by proposing a novel gender detection method that exploits image search and face-detection methods.
By analysing the collaboration patterns and citation networks of male and female computer scientists, it sheds lights on some of the historical biases and disadvantages that women face in their scientific career. In particular, the relation of scientific success and gender-specific collaboration patterns is assessed. To elaborate further on the temporal aspect of inequalities in scientific careers, this thesis compares the degree of vertical and horizontal inequalities among the cohorts of scientists that started their career at different point in time. Furthermore, the structural inequality in music industry is assessed by analyzing the social and cultural relations that breed from live performances and musics releases. The findings hint toward the importance of community belonging at different stages of artists’ careers. This thesis also quantifies some of the underlying mechanisms and processes of inequality, such as the Matthew Effect and the Hipster Paradox, in creative careers. Finally, this thesis argues that online platforms such as Wikipedia could reflect and amplify the existing biases.
The diversity within amphibian communities in cultivated areas in Rwanda and within two selected, taxonomically challenging groups, the genera Ptychadena and Hyperolius, were investigated in this thesis. The amphibian community of an agricultural wetland near Butare in southern Rwanda comprised 15 anuran species. Rarefaction and jackknife analyses corroborated that the complete current species richness of the assemblage had been recorded, and the results of acoustic niche analysis suggested species saturation of the community. Surveys at many other Rwandan localities showed that the species recorded in Butare are widespread in cultivated and pristine wetlands. The species were readily distinguishable using morphological, bioacoustic, and molecular (DNA barcoding) features, but only eight of the 15 species could be assigned unambiguously to nominal species. The remaining represented undescribed or currently unrecognized taxa, including three species of Hyperolius, two Phrynobatrachus species, one Ptychadena species, and one species of Amietia. The diversity of the Ridged Frogs in Rwanda was investigated in two studies (Chapters III and IV). Three species of Ptychadena were recorded in wetlands in the catchment of the Nile. They can be distinguished by morphological characters (morphometrics and qualitative features) as well as by their advertisement calls and genetics. The Rwandan species of the P. mascareniensis group was shown to differ from the topotypic population as well as from other genetic lineages in sub-Saharan Africa and an old available name, P. nilotica, was resurrected from synonymy for this lineage. Two further Ptychadena species were identified among voucher specimens from Rwanda deposited in the collection of the RMCA, P. chrysogaster and P. uzungwensis. Morphologically they can be unambiguously distinguished from each other and the three other Rwandan species. A key based on qualitative morphological characters was developed, which allows unequivocal identification of specimens of all species that have been recorded from Rwanda. DNA was isolated from a Rwandan voucher specimen of P. chrysogaster, and the genetic analysis corroborated the species" distinct status.
A species of Hyperolius collected in the Nyungwe National Park was compared to all other Rwandan species of the genus and to morphologically or genetically similar species from neighbouring countries. Its distinct taxonomic status was justified by morphological, bioacoustic, and molecular evidence and it was described as a new species, H. jackie. A species of the H. nasutus group collected at agricultural sites in Rwanda was described as a new species in the course of a revision of the species of the Hyperolius nasutus group. The group was shown to consist of 15 distinct species which can be distinguished from each other genetically, bioacoustically, and morphologically.
The aerial performance, i.e. parachuting, of the Disc-fingered Reed Frog, Hyperolius discodactylus, was described. It represents a novel observation of a behaviour that has been known from a number of Southeast Asian and Neotropical frog species. Parachuting frogs, including H. discodactylus, exhibit certain morphological characteristics and, while airborne, assume a distinct posture which is best-suited for maneuvering in the air. Another study on the species addressed the validity of the taxon H. alticola which had been considered either a synonym of H. discodactylus or a distinct species. Type material of both taxa was re-examined and the status of H. alticola reassessed using morphological data from historic and new collections, call recordings, and molecular data from animals collected on recent expeditions. A northern and a southern genetic clade were identified, a divide that is weakly supported by diverging morphology of the vouchers from the respective localities. No distinction in advertisement call features could be recovered to support this split and both genetic and morphological differences between the two geographic clades are marginal and not always congruent and more likely reflect population-level variation. Therefore it was concluded that H. alticola is not a valid taxon and should be treated as a synonym of H. discodactylus.
On the recognition of human activities and the evaluation of its imitation by robotic systems
(2023)
This thesis addresses the problem of action recognition through the analysis of human motion and the benchmarking of its imitation by robotic systems.
For our action recognition related approaches, we focus on presenting approaches that generalize well across different sensor modalities. We transform multivariate signal streams from various sensors to a common image representation. The action recognition problem on sequential multivariate signal streams can then be reduced to an image classification task for which we utilize recent advances in machine learning. We demonstrate the broad applicability of our approaches formulated as a supervised classification task for action recognition, a semi-supervised classification task for one-shot action recognition, modality fusion and temporal action segmentation.
For action classification, we use an EfficientNet Convolutional Neural Network (CNN) model to classify the image representations of various data modalities. Further, we present approaches for filtering and the fusion of various modalities on a representation level. We extend the approach to be applicable for semi-supervised classification and train a metric-learning model that encodes action similarity. During training, the encoder optimizes the distances in embedding space for self-, positive- and negative-pair similarities. The resulting encoder allows estimating action similarity by calculating distances in embedding space. At training time, no action classes from the test set are used.
Graph Convolutional Network (GCN) generalized the concept of CNNs to non-Euclidean data structures and showed great success for action recognition directly operating on spatio-temporal sequences like skeleton sequences. GCNs have recently shown state-of-the-art performance for skeleton-based action recognition but are currently widely neglected as the foundation for the fusion of various sensor modalities. We propose incorporating additional modalities, like inertial measurements or RGB features, into a skeleton-graph, by proposing fusion on two different dimensionality levels. On a channel dimension, modalities are fused by introducing additional node attributes. On a spatial dimension, additional nodes are incorporated into the skeleton-graph.
Transformer models showed excellent performance in the analysis of sequential data. We formulate the temporal action segmentation task as an object detection task and use a detection transformer model on our proposed motion image representations. Experiments for our action recognition related approaches are executed on large-scale publicly available datasets. Our approaches for action recognition for various modalities, action recognition by fusion of various modalities, and one-shot action recognition demonstrate state-of-the-art results on some datasets.
Finally, we present a hybrid imitation learning benchmark. The benchmark consists of a dataset, metrics, and a simulator integration. The dataset contains RGB-D image sequences of humans performing movements and executing manipulation tasks, as well as the corresponding ground truth. The RGB-D camera is calibrated against a motion-capturing system, and the resulting sequences serve as input for imitation learning approaches. The resulting policy is then executed in the simulated environment on different robots. We propose two metrics to assess the quality of the imitation. The trajectory metric gives insights into how close the execution was to the demonstration. The effect metric describes how close the final state was reached according to the demonstration. The Simitate benchmark can improve the comparability of imitation learning approaches.
FinTech is deemed to be an underexplored phenomenon even in academic and real environments. Among (1) “Sustainable FinTech” – the application of information technology as innovation in established financial services providers’ business operation; and (2) “Disruptive FinTech” – the provision of financial products and services by non-incumbents which in most cases are information technology entrepreneurs, the former receives more attention. In order to contribute to Disruptive FinTech category, the thesis strive to examine Entrepreneurial Strategy framework applied for technology players taking part in Vietnam financial market.
Digital Transformation Maturity of Vietnam Aviation Industry: The Effect of Organizational Readiness
(2023)
The paper studies the digital transformation maturity in the context of the aviation industry in Vietnam. Digital transformation can mean enhancing existing processes, finding new opportunities within existing business domains, or finding new opportunities outside existing business domains. In the era of post Covid-19, digital transformation will play a vital role in the recovery with the support from digital technology to leverage the communication and implementation of new projects or changes.
Digital transformation and digital transformation maturity sometimes are used indistinguishing, but they are two different definitions. This paper will further explain the differences and will apply digital transformation maturity as a scale for the digital transformation in the report.
Due to the lack of experiment in the relationship between digital transformation maturity and the organizational readiness, the study will explore four components of organizational readiness, including digital leadership, digital culture, digital capabilities, and digital partnering.
The paper is a study focusing on exploring which factors and examining the impact of those factors influencing the entrepreneurial intention among students in the Construction industry, specifically among students of Hanoi Construction University and Hanoi Architecture University. The study also mentions some solution of this findings for entrepreneurship in the Construction field in Vietnam that the author might think of based on this research work for future study. The Theory of planned behavior is used as the theoritical framework for this study. Both qualitative and quantitative methods are employed. The questionaire will be conducted among students of the two universities mentioned above. Then, an exploratory factor analysis (EFA) will performed to test the validity of the constructs. The research findings provide factors and their impact factors influencing the entrepreneurial intention and propose some solutions to improve the entrepreneurship in the Construction field in Vietnam.
Digital transformation is a prevailing trend in the world, especially in dynamic Asia. Vietnam has recorded remarkable changes in the economy as domestic enterprises have made new strides in the digital transformation process. MB Bank, one of the prestigious financial groups in Vietnam, also takes advantage of digital transformation to have the opportunity to break through to become a large-scale technology enterprise with many factors such as improving customer experience, increasing customer base and increasing customer satisfaction. enhance competitiveness, build trust and loyalty for customers. However, in the process of converting MB, there are also many challenges that require banks to have appropriate policies to handle. It can be said that MB Bank is a typical case study of digital transformation in the banking sector in Vietnam.
With the increasing importance and urgency of climate change, companies are challenged to contribute to sustainable development, especially by younger generations. However, existing corporate contributions have been criticized as insufficient, which could be particularly caused by a lack of employee engagement in corporate sustainability. In this context, gamification has been proposed and increasingly investigated in recent years as a promising, innovative tool to motivate sustainable employee behaviors in the workplace. However, there are few studies and applicable gamification solutions that address more than one specific sustainability issue and thus take a holistic perspective on sustainable behaviors in the workplace. Moreover, previous research lacks a comprehensive understanding of how different gamification elements elicit specific psychological effects, how these manifest in behavioral changes, and how these, in turn, cumulatively result in measurable corporate outcomes. The path from gamification as ”input” to corporate sustainability as ”output” thus remains unexplored.
This dissertation fills this gap by conceptualizing, designing, and evaluating a holistic gamified intervention that supports employees in various sustainable behaviors in their daily activities. The project uses a design science research approach that closely involves employees in the incremental development of the solution. As part of the iterative design process, this dissertation presents six studies to extend the theoretical understanding of gamification for sustainable employee behaviors. First, a comprehensive review of existing research on gamification for sustainable employee behavior is provided, analyzing gamification designs and results of previous studies and outlining an agenda for further research (Study 1). Theoretical foundations of research on gamification, serious games, and game-based learning (Study 2) and empirical design principles for gamification and persuasive systems (Study 3) are then systematically reviewed as a basis for the successful design of gamified applications. Subsequently, empirical studies explore employees’ motivations for sustainable behavior and illuminate their expectations for design features (Study 4), and identify contextual challenges and design dilemmas when implementing gamification in an organizational context (Study 5). Finally, a quantitative field study (Study 6) explores how different gamification designs influence sustainable employee behavior and corporate sustainability in organizations. Based on the findings, this dissertation presents a comprehensive framework of gamification for sustainable employee behavior that incorporates design, individual behavior, and organizational perspectives. Finally, building on these insights, it provides practical recommendations for designing gamification to encourage sustainable employee behavior at work.
Counts of SARS-CoV-2-related deaths have been key numbers for justifying severe political, social and economical measures imposed by authorities world-wide. A particular focus thereby was the concomitant excess mortality (EM), i.e. fatalities above the expected all-cause mortality (AM). Recent studies, inter alia by the WHO, estimated the SARS-CoV-2-related EM in Germany between 2020 and 2021 as high as 200 000. In this study, we attempt to scrutinize these numbers by putting them into the context of German AM since the year 2000. We propose two straightforward, age-cohort-dependent models to estimate German AM for the ‘Corona pandemic’ years, as well as the corresponding flu seasons, out of historic data. For Germany, we find overall negative EM of about −18 500 persons for the year 2020, and a minor positive EM of about 7000 for 2021, unveiling that officially reported EM counts are an exaggeration. In 2022, the EM count is about 41 200. Further, based on NAA-test-positive related death counts, we are able to estimate how many Germans have died due to rather than with CoViD-19; an analysis not provided by the appropriate authority, the RKI. Through 2020 and 2021 combined, our due estimate is at no more than 59 500. Varying NAA test strategies heavily obscured SARS-CoV-2-related EM, particularly within the second year of the proclaimed pandemic. We compensated changes in test strategies by assuming that age-cohort-specific NAA-conditional mortality rates during the first pandemic year reflected SARS-CoV-2-characteristic constants.
X-ray computer tomography (XRT) is a three-dimensional, nondestructive, and thus reproducible examination method that allows for the investigation of internal and external structures of objects. Due to its characteristics, the XRT technique has increasingly established itself as an alternative examination method and is also applied in the field of mineral processing. Within this work, XRT is used to investigate the influence of hydrochloric acid leaching of iron-rich bauxites on grain composition. Acid leaching is a promising method for the beneficiation of iron-rich bauxites for refractories. Many studies have already established that leaching with hydrochloric acid can reduce the Fe₂O₃ content in bauxites. However, apart from the influence of the leaching process on the composition of the bauxites, aspects such as the influence of the acid on the exact grain constitution or the porosity behavior have rarely been considered so far. To address these open questions, XRT analysis was used to examine and characterize various bauxites. By comparing identical grains before and after leaching, it was observed that in gibbsite bauxites the acid penetration is deeper, and the volume decreases significantly. In diasporic and boehmitic bauxites, clear leaching edges can be seen in which the iron content has been reduced.
Leichte Sprache (LS, easy-to-read German) is a simplified variety of German. It is used to provide barrier-free texts for a broad spectrum of people, including lowliterate individuals with learning difficulties, intellectual or developmental disabilities (IDD) and/or complex communication needs (CCN). In general, LS authors are proficient in standard German and do not belong to the aforementioned group of people. Our goal is to empower the latter to participate in written discourse themselves. This requires a special writing system whose linguistic support and ergonomic software design meet the target group’s specific needs. We present EasyTalk a system profoundly based on natural language processing (NLP) for assistive writing in an extended variant of LS (ELS). EasyTalk provides users with a personal vocabulary underpinned with customizable communication symbols and supports in writing at their individual level of proficiency through interactive user guidance. The system minimizes the grammatical knowledge needed to produce correct and coherent complex contents by intuitively formulating linguistic decisions. It provides easy dialogs for selecting options from a natural-language paraphrase generator, which provides context-sensitive suggestions for sentence components and correctly inflected word forms. In addition, EasyTalk reminds users to add text elements that enhance text comprehensibility in terms of audience design (e.g., time and place of an event) and improve text coherence (e.g., explicit connectors to express discourse-relations). To tailor the system to the needs of the target group, the development of EasyTalk followed the principles of human-centered design (HCD). Accordingly, we matured the system in iterative development cycles, combined with purposeful evaluations of specific aspects conducted with expert groups from the fields of CCN, LS, and IT, as well as L2 learners of the German language. In a final case study, members of the target audience tested the system in free writing sessions. The study confirmed that adults with IDD and/or CCN who have low reading, writing, and computer skills can write their own personal texts in ELS using EasyTalk. The positive feedback from all tests inspires future long-term studies with EasyTalk and further development of this prototypical system, such as the implementation of a so-called Schreibwerkstatt (writing workshop)
In the last years, the public interest in epidemiology and mathematical modeling of disease spread has increased - mainly caused by the COVID-19 pandemic, which has emphasized the urgent need for accurate and timely modelling of disease transmission. However, even prior to that, mathematical modelling has been used for describing the dynamics and spread of infectious diseases, which is vital for developing effective interventions and controls, e.g., for vaccination campaigns and social restrictions like lockdowns. The forecasts and evaluations provided by these models influence political actions and shape the measures implemented to contain the virus.
This research contributes to the understanding and control of disease spread, specifically for Dengue fever and COVID-19, making use of mathematical models and various data analysis techniques. The mathematical foundations of epidemiological modelling, as well as several concepts for spatio-temporal diffusion like ordinary differential equation (ODE) models, are presented, as well as an originally human-vector model for Dengue fever, and the standard (SEIR)-model (with the potential inclusion of an equation for deceased persons), which are suited for the description of COVID-19. Additionally, multi-compartment models, fractional diffusion models, partial differential equations (PDE) models, and integro-differential models are used to describe spatial propagation of the diseases.
We will make use of different optimization techniques to adapt the models to medical data and estimate the relevant parameters or finding optimal control techniques for containing diseases using both Metropolis and Lagrangian methods. Reasonable estimates for the unknown parameters are found, especially in initial stages of pandemics, when little to no information is available and the majority of the population has not got in contact with the disease. The longer a disease is present, the more complex the modelling gets and more things (vaccination, different types, etc.) appear and reduce the estimation and prediction quality of the mathematical models.
While it is possible to create highly complex models with numerous equations and parameters, such an approach presents several challenges, including difficulties in comparing and evaluating data, increased risk of overfitting, and reduced generalizability. Therefore, we will also consider criteria for model selection based on fit and complexity as well as the sensitivity of the model with respect to specific parameters. This also gives valuable information on which political interventions should be more emphasized for possible variations of parameter values.
Furthermore, the presented models, particularly the optimization using the Metropolis algorithm for parameter estimation, are compared with other established methods. The quality of model calculation, as well as computational effort and applicability, play a role in this comparison. Additionally, the spatial integro-differential model is compared with an established agent-based model. Since the macroscopic results align very well, the computationally faster integro-differential model can now be used as a proxy for the slower and non-traditionally optimizable agent-based model, e.g., in order to find an apt control strategy.
In a world where language defines the boundaries of one's understanding, the words of Austrian philosopher Ludwig Wittgenstein resonate profoundly. Wittgenstein's assertion that "Die Grenzen meine Sprache bedeuten die Grenzen meiner Welt" (Wittgenstein 2016: v. 5.6) underscores the vital role of language in shaping our perceptions. Today, in a globalized and interconnected society, fluency in foreign languages is indispensable for individual success. Education must break down these linguistic barriers, and one promising approach is the integration of foreign languages into content subjects.
Teaching content subjects in a foreign language, a practice known as Content Language Integrated Learning (CLIL), not only enhances language skills but also cultivates cognitive abilities and intercultural competence. This approach expands horizons and aligns with the core principles of European education (Leaton Gray, Scott & Mehisto 2018: 50). The Kultusministerkonferenz (KMK) recognizes the benefits of CLIL and encourages its implementation in German schools (cf. KMK 2013a).
With the rising popularity of CLIL, textbooks in foreign languages have become widely available, simplifying teaching. However, the appropriateness of the language used in these materials remains an unanswered question. If textbooks impose excessive linguistic demands, they may inadvertently limit students' development and contradict the goal of CLIL.
This thesis focuses on addressing this issue by systematically analyzing language requirements in CLIL teaching materials, emphasizing receptive and productive skills in various subjects based on the Common European Framework of Reference. The aim is to identify a sequence of subjects that facilitates students' language skill development throughout their school years. Such a sequence would enable teachers to harness the full potential of CLIL, fostering a bidirectional approach where content subjects facilitate language learning.
While research on CLIL is extensive, studies on language requirements for bilingual students are limited. This thesis seeks to bridge this gap by presenting findings for History, Geography, Biology, and Mathematics, allowing for a comprehensive understanding of language demands. This research endeavors to enrich the field of bilingual education and CLIL, ultimately benefiting the academic success of students in an interconnected world.
Potential impacts of invasive crayfish on native
benthic fish: shelter use and agonistic behaviour
(2023)
Spinycheek crayfish (Faxonius limosus) and signal crayfish (Pacifastacus leniusculus) are successful North American invasive crayfish species distributed throughout Europe. Both species compete with native benthic fish for shelter. In a laboratory approach, we assessed competition for shelter and antagonistic interactions between these invasive crayfish species and the native benthic fish species, stone loach (Barbatula barbatula) and bullhead (Cottus gobio). This allows for studying the potential impacts of invasive crayfish on native benthic fish. Spinycheek crayfish and signal crayfish were able to gain control of the shelter and could successfully displace both benthic fish species. For stone loach, the presence of crayfish significantly decreased their shelter use and caused several behavioural changes such as reduced activity and increased hiding behaviour outside the shelter. Although the shelter use by bullheads was not reduced, they displayed similar behavioural changes, if less intense. Invasive crayfish species showed remarkable combative interactions against both species of benthic fishes, evidenced by the high number of aggressive interactions, especially concerning stone loach. Our results highlight the pronounced dominance of invasive crayfish over benthic fish in terms of shelter competition and aggressive interactions under laboratory conditions, which consequently might promote the latter’s exposure to predation.
Increasingly, problematic smartphone use behavior (PSU) and excessive consumption are reported. In this study, an experiment was developed to investigate the influence of screen coloration using the grayscale setting on smartphone usage time in repeated measurements. We also investigated how individuals perceived suffering correlates with smartphone usage time and PSU, and whether differences exist by smartphone usage type (social, process, habitual). 240 subjects completed a questionnaire about smartphone usage time, PSU, perceived suffering, and smartphone usage types. Afterward, their smartphones were switched to grayscale setting for at least 24h, and thereafter 92 of these participants completed the second questionnaire. Analyses showed that grayscale setting decreases usage time and that there is a positive correlation between PSU, smartphone usage duration, and perceived suffering. The types of use (process and habitual) influence one’s perceived suffering. Thus, it shows that individuals are aware of their PSU and suffer from it. Using grayscale setting is effective in reducing smartphone use time.
Artificial neural networks is a popular field of research in artificial intelli-
gence. The increasing size and complexity of huge models entail certain
problems. The lack of transparency of the inner workings of a neural net-
work makes it difficult to choose efficient architectures for different tasks.
It proves to be challenging to solve these problems, and with a lack of in-
sightful representations of neural networks, this state of affairs becomes
entrenched. With these difficulties in mind a novel 3D visualization tech-
nique is introduced. Attributes for trained neural networks are estimated
by utilizing established methods from the area of neural network optimiza-
tion. Batch normalization is used with fine-tuning and feature extraction to
estimate the importance of different parts of the neural network. A combi-
nation of the importance values with various methods like edge bundling,
ray tracing, 3D impostor and a special transparency technique results in a
3D model representing a neural network. The validity of the extracted im-
portance estimations is demonstrated and the potential of the developed
visualization is explored.
The trends of industry 4.0 and the further enhancements toward an ever changing factory lead to more mobility and flexibility on the factory floor. With that higher need of mobility and flexibility the requirements on wireless communication rise. A key requirement in that setting is the demand for wireless Ultra-Reliability and Low Latency Communication (URLLC). Example use cases therefore are cooperative Automated Guided Vehicles (AGVs) and mobile robotics in general. Working along that setting this thesis provides insights regarding the whole network stack. Thereby, the focus is always on industrial applications. Starting on the physical layer, extensive measurements from 2 GHz to 6 GHz on the factory floor are performed. The raw data is published and analyzed. Based on that data an improved Saleh-Valenzuela (SV) model is provided. As ad-hoc networks are highly depended onnode mobility, the mobility of AGVs is modeled. Additionally, Nodal Encounter Patterns (NEPs) are recorded and analyzed. A method to record NEP is illustrated. The performance by means of latency and reliability are key parameters from an application perspective. Thus, measurements of those two parameters in factory environments are performed using Wireless Local Area Network (WLAN) (IEEE 802.11n), private Long Term Evolution (pLTE) and 5G. This showed auto-correlated latency values. Hence, a method to construct confidence intervals based on auto-correlated data containing rare events is developed. Subsequently, four performance improvements for wireless networks on the factory floor are proposed. Of those optimization three cover ad-hoc networks, two deal with safety relevant communication, one orchestrates the usage of two orthogonal networks and lastly one optimizes the usage of information within cellular networks.
Finally, this thesis is concluded by an outlook toward open research questions. This includes open questions remaining in the context of industry 4.0 and further the ones around 6G. Along the research topics of 6G the two most relevant topics concern the ideas of a network of networks and overcoming best-effort IP.
Harvesting Season?
(2022)
Efforts to induce customers to buy groceries through the Internet have existed for around twenty years. Early on, the market structures of the digital grocery trade were still strongly fragmented and poorly coordinated. Due to the technological advancement in the past decade, the digital purchase of groceries has become more attractive. The adoption rate of these services varies greatly between different regions. In Germany in particular, the digital grocery trade is stagnating at a comparatively low level. In this regard, this dissertation analyzes both the retail-side market structures and the expectations and obstacles of German consumers.
The year 2020 connotes a turning point for the online grocery trade, as daily routines such as grocery shopping were subject to strict regulations imparted at a governmental level in order to reduce COVID-19 infections. At the same time, despite this opportunity, the digital grocery trade has not yet established itself nationwide in Germany. This can be attributed to a lack of investments, but also to inadequate digitization measures. A stronger synchronization between the digital and stationary offer, better integration of digital food services at a regional level as well as adapted, target group-appropriate digital solutions for the efficient breakdown of usage barriers will benefit service usage. The importance of stable food chains and distribution channels was illustrated by the COVID-19 pandemic. Further research should help to develop the digital food trade into a stable and sustainable supplementation of the stationary store.
Today’s agriculture heavily relies on pesticides to manage diverse pests and maximise crop yields. Despite elaborate regulation of pesticide use based on a complex environmental risk assessment (ERA) scheme, the widespread use of these biologically active compounds has been shown to be a threat to the environment. For surface waters, pesticide exposure has been observed to exceed safe concentration levels and negatively impact stream ecology leading to the question whether current ERA schemes ensure a sustainable use of pesticides. To answer this, the large-scale “Kleingewässer-Monitoring” (KgM) assessed the occurrence of pesticides and related effects in 124 streams throughout Germany, Central Europe, in 2018 and 2019.
Based on five scientific publications originating from the KgM, this thesis evaluated pesticide exposure in streams, ecological effects and the regulatory implications. More than 1,000 water samples were analysed for over 100 pesticide analytes to characterise occurrence patterns (publication 1). Measured concentrations and effects were used to validate the exposure and effect concentrations predicted in the ERA (publication 2). By jointly analysing real-world pesticide application data and measured pesticide mixtures in streams, the disregard of environmental pesticide mixtures in the ERA was evaluated (publication 3). The toxic potential of mixtures in stream water was additionally investigated using suspect screening for 395 chemicals and a battery of in-vitro bioassays (publication 4). Finally, the results from the KgM stream monitoring were used to assess the capability to identify pesticide risks in governmental monitoring programmes (publication 5).
The results of this thesis reveal the widespread occurrence of pesticides in non-target stream ecosystems. The water samples contained a variety of pesticides occurring in complex mixtures predominantly in short-term peaks after rainfall events (publications 1 & 4). Respective pesticide concentration maxima were linked to declines in vulnerable invertebrate species and exceeded regulatory acceptable concentrations in about 80% of agricultural streams, while these thresholds were still estimated partly insufficient to protect the invertebrate community (publication 2). The co-occurrence of pesticides in streams led to a risk underestimated in the single substance-oriented ERA by a factor of about 3.2 in realistic worst-case scenarios, which is further exacerbated by a high frequency at which non-target organism are exposed to pesticides (publication 3). Stream water samples taken after rainfall caused distinct effects in bioassays which were only explainable to a minor extent by the many analytes, indicating the relevance of unknown chemical or biological mixture components (publication 4). Finally, the regulatory monitoring of surface waters under the Water Framework Directive (WFD) was found to significantly underestimate pesticide risks, as about three quarters of critical pesticides and more than half of streams at risk were overlooked (publication 5).
Essentially, this thesis involves a new level of validation of the ERA of pesticides in aquatic ecosystems by assessing pesticide occurrence and environmental impacts at a scale so far unique. The overall results demonstrate that the current agricultural use of pesticides leads to significant impacts on stream ecology that go beyond the level tolerated under the ERA. This thesis identified the underestimation of pesticide exposure, the potential insufficiency of regulatory thresholds and the general inertia of the authorisation process as the main causes why the ERA fails to meet its objectives. To achieve a sustainable use of pesticides, the thesis proposes substantial refinements of the ERA. Adequate monitoring programmes such as the KgM, which go beyond current government monitoring efforts, will continue to be needed to keep pesticide regulators constantly informed of the validity of their prospective ERA, which will always be subject to uncertainty.
In the last decades, it became evident that the world is facing an unprecedented, human-induced global biodiversity crisis with amphibians being one of the most threatened species groups. About 41% of the amphibian species are classified as endangered by the IUCN, but even in amphibian species that are listed as "least concern", population declines can be observed on a local level. With land-use change and agrochemicals (i.e. pesticides), two of the main drivers for this amphibian decline are directly linked to intensive agriculture, which is the dominant landscape type in large parts of Europe. Thus, understanding the situation of amphibians in the agricultural landscape is crucial for conservation measures. In the present thesis, I investigated the effects of viticulture on amphibian populations around Landau in der Pfalz (Germany) in terms of habitat use, pesticide exposure, biometric traits as well as genetic and age structure. From the perspective of amphibians, land-use change means usually the destruction of habitats in agricultural landscapes, which often leads to landscape fragmentation. Thus, I followed the question if also vineyards lead to the fragmentation of the landscape and if pesticides that are frequently used in viticulture have to be considered as a factor too, so if there is a chemical landscape fragmentation. Using telemetry, I could show that common toads (Bufo bufo) can be found directly in vineyards, but that they tend to avoid them as habitat. Analysing the genetic structure of common frogs (Rana temporaria) revealed that vineyards have to be considered as a barrier for amphibians. To identify if pesticides contribute to the resulting landscape fragmentation, I conducted an arena choice experiment in the laboratory in which I found evidence for an avoidance of pesticide-contaminated soil. Such an avoidance could be one of the underlying reasons for a potential chemical landscape fragmentation. By combining telemetry data with information about pesticide applications from local wine growers, I could show that a large part of the common toads is likely to come in contact with pesticides. Further, I demonstrated that the agricultural landscape, probably due to the application of pesticides, can have negative effects on the reproduction capacity of common toads. By studying palmate newts (Lissotriton helveticus) I found that adult newts from agricultural ponds are smaller than those from forest ponds. As I did not find differences in the age structure and growth, these differences might be carry-over effects from earlier life stages. While agricultural ponds might be suitable habitats for adult palmate newts, the potential carry-over effect indicates suboptimal conditions for larvae and/or juveniles. I conclude that the best management measure for sustaining amphibians in the agricultural landscape would be a heterogeneous cultural landscape with a mosaic of different habitat patches that work without or at least a reduced amount of pesticides. Green corridors between populations and different habitats would allow migrating individuals to avoid agricultural and thus pesticide-contaminated areas. This would reduce the pesticide exposure risk of amphibians, while preventing the fragmentation of the landscape and thus the isolation of populations.
This thesis was motivated by the need to advance the knowledge on the variability and dynamics of energy fluxes in lakes and reservoirs, as well as about the physical processes that regulate the fluxes at both the air and water side of the air-water interface.
In the first part, I re-examine how mechanical energy, resulting from its major source – the vertical wind energy flux - distributes into the various types of water motions, including turbulent flows and surface and internal waves. Although only a small fraction of the wind energy flux from the atmosphere is transferred to the water, it is crucial for physical, biogeochemical and ecological processes in lentic ecosystems. Based on extensive air- and water-side measurements collected at two small water bodies (< 10 km2), we estimated the energy fluxes and energy content in surface and in internal waves. Overall, the estimated energy fluxes and energy content agree well with results reported for larger water bodies, suggesting that the energetics driving the water motions in enclosed basins is similar, independently of the basin size. Our findings highlight the importance of the surface waves that receive the largest fraction of the wind energy flux, which strongly nonlinearly increases for wind speeds exceeding 3 m s-1. We found that the existing parameterization of the wave height as a function of wind speed and fetch length did not reproduce the measured wave amplitude in lakes. On average, the highest energy content was observed in basin-scale internal waves, together with high-frequency internal waves exhibiting seasonal variability and varies among the aquatic systems. During our analysis, we discovered the diurnal variability of the energy dissipation rates in the studied lake, suggesting biogenic turbulence generation, which appears to be a widespread phenomenon in lakes and reservoirs.
In the second part of the thesis, I addressed current knowledge gaps related to the bulk transfer coefficients (also known as the drag coefficient, the Stanton number and the Dalton number), which are of a particular importance for the bulk estimation of the surface turbulent fluxes of momentum, sensible and latent heat in the atmospheric boundary layer. Their inaccurate representation may lead to significant errors in flux estimates, affecting, for example, the weather and climate predictions or estimations of the near-surface current velocities in lake hydrodynamic models. Although the bulk transfer coefficients have been extensively studied over the past several decades (mainly in marine and large-lake environments), there has been no systematic analysis of measurements obtained at lakes of different size. A significant increase of the transfer coefficients at low wind speeds (< 3 m s-1) has been observed in several studies, but, to date, it has remained unexplained. We evaluated
the bulk transfer coefficients using flux measurements from 31 lakes and reservoirs. The estimates were generally within the range reported in previous studies for large lakes and oceans. All transfer coefficients increased substantially at low wind speeds, which was found to be associated with the presence of gusts and capillary waves (except the Dalton number). We found that the Stanton number is systematically higher than the Dalton number. This challenges the assumption made in the Bowen-ratio method, which is widely used for estimating evaporation rates from micrometeorological measurements. We found that the variability of the transfer coefficients among the lakes could be associated with lake surface area. In flux parameterizations at lake surfaces, it is recommended to consider variations in the drag coefficient and the Stanton number due to wind gustiness and capillary wave roughness while the Dalton number could be considered as constant at all wind speeds.
In the third part of the thesis, I address the key drivers of the near-surface turbulence that control the gas exchange in a large regulated river. As all inland waters, rivers are an important natural source of greenhouse gases. The effects of the widespread alteration and regulation of river flow for human demands on gas exchange is largely unknown. In particular, the near-surface turbulence in regulated rivers has been rarely measured and its drivers have not been identified. While in lakes and reservoirs, near-surface turbulence is mainly related to atmospheric forcing, in shallow rivers and streams it is generated by bottom friction of the gravity-forced flow. The studied large regulated river represents a transition between these two cases. Atmospheric forcing and gravity were the dominant drivers of the near-surface turbulence for a similar fraction of the measurement period. Based on validated scalings, we derived a simple model for estimating the relative contributions of wind and bottom friction to near-surface turbulence in lotic ecosystems with different flow depths. Large diel variability in the near-surface energy dissipation rates due to flow regulation leads to the same variability in gas exchange. This suggests that estimates of gas fluxes from rivers are biased by measurements performed predominantly during daytime.
In addition, the novelty in all the analyses described above is the use of the turbulent surface fluxes measured directly by the eddy-covariance technique – at the moment of writing, the most advanced method. Overall, this thesis is of a potential interest for a broad range of scientific disciplines, including limnology, micrometeorology and open channel hydraulics.
Ponds in agricultural landscapes are often used by amphibians as breeding habitat. However, the characteristics of agricultural ponds and especially the surrounding area are usually said to be suboptimal for many amphibian species. Using suboptimal habitats might allow a species’ survival and reproduction, but can have negative consequences at the individual and population level. In the present study, we investigated Palmate Newt (Lissotriton helveticus) populations from an intensive wine-growing region in southern Germany and compared them with populations located in a nearby forested area in terms of biometric traits, age and genetic structure. By analyzing over 900 adult newts from 11 ponds, we could show that newts reproducing in forest ponds were larger than newts reproducing in agricultural ponds. We did not find differences in the newt age and growth rate between habitat types. Therefore, differences in the body size of newts might already existed in larvae and/or juveniles, what might be related to a lower habitat quality for larvae and/or juveniles in the agricultural landscape. Body mass, body condition and sexual dimorphic traits (length of the caudal filament and max. height of the tail) correlated with body size, but no additional effect of the habitat type was found. The analysis of microsatellites revealed a higher genetic diversity in forest ponds. However, no clear sign of inbreeding was observed in any agricultural population, suggesting some degree of gene flow between them. We conclude, that agricultural ponds can be suitable habitats for the Palmate Newt and that conservation effort should aim to preserve them. The observed effects on body size indicate the need to increase the quality of the aquatic and terrestrial habitat for early life stages of this newt species in agricultural landscapes.
In this thesis the possibilities for real-time visualization of OpenVDB
files are investigated. The basics of OpenVDB, its possibilities, as well
as NanoVDB and its GPU port, were studied. A system was developed
using PNanoVDB, the graphics API port of OpenVDB. Techniques were
explored to improve and accelerate a single ray approach of ray tracing.
To prove real-time capability, two single scattering approaches were
also implemented. One of these was selected, further investigated and
optimized to achieve interactive real-time rendering.
It is important to give artists immediate feedback on their adjustments, as
well as the possibility to change all parameters to ensure a user friendly
creation process.
In addition to the optical rendering, corresponding benchmarks were
collected to compare different improvement approaches and to prove
their relevance. Attention was paid to the rendering times and memory
consumption on the GPU to ensure optimal use. A special focus, when
rendering OpenVDB files, was put on the integrability and extensibility of
the program to allow easy integration into an existing real-time renderer
like U-Render.
This dissertation is dedicated to a new concept for capturing renunciation-oriented attitudes and beliefs — sufficiency orientation. Sufficiency originates in the interdisciplinary sustain-ability debate. In contrast to efficiency and consistency, sufficiency considers human behaviour as the cause of socio-ecological crises and strives for a reduction in consumption respecting the planetary boundaries. The present work places sufficiency in a psychological research context and explores it qualitatively and quantitatively. On the basis of five manuscripts, the overarching question pursued is to what extent sufficiency orientation contributes to socio-ecological transformation. Based on one qualitative study and five further quantitative studies, sufficiency orientation is investigated in different behavioural contexts that are of particular importance with regard to CO2 emissions. In addition, sufficiency orientation is linked to a wider range of psychologically relevant theories that help gain an overview of correlates and possible causes for the development of a sufficiency orientation.
Manuscript 1 uses expert interviews (N = 21) to develop a heuristic framework on a transformation towards societal sufficiency orientation including barriers and enablers, as well as ambiguities on such a change. The derived elements are interpreted in the light of the leverage points approach. This framework can serve as a heuristic for future research and to develop measures concerning sufficiency orientation.
As part of an online study (N = 648), Manuscript 2 examines the extent to which sufficiency orientation can be embedded in classic models for explaining pro-environmental intentions and behaviour (Theory of Planned Behaviour, Norm Activation Model), and showed a significant contribution to the explanation of intentions and behaviour in the field of plastic consumption.
Manuscript 3 reports two framing experiments (Study 1, N = 123, Study 2, N = 330) to investigate how pro-social justice sensitivity contributes to making sufficiency orientation more salient and promoting it. While sufficiency orientation and pro-social facets of justice sensitivity were positively related to each other, there was no effect of the framing intervention in the hypothesised direction. The results indicate that justice-related information at least in the presented manner is more likely to generate reactance.
Manuscript 4 presents an online study (N = 317) and targets the importance of sufficiency orientation for predicting actual greenhouse gas emissions in relation to flight behav-iour and policy support for the decarbonisation of mobility. In addition, the connection between sufficiency orientation and global identity is examined. It turns out that sufficiency orientation is superior to global identity in predicting actual emissions and decarbonisation policies. Contrary to expectations, sufficiency orientation and the form of global identity operationalised in the presented study shows a positive correlation and are compatible.
Manuscript 5 reports a reflective diary intervention (N = 252) that should lead to a short- and long-term increase in sufficiency orientation by satisfying basic psychological needs through induced self-reflection. For both groups with or without the intervention, sufficiency orientation increased slightly but significantly. Although no specific effect of the manipulation was found, basic psychological need satisfaction turns out to be the largest predictor for sufficiency orientation. Subjective well-being is positively associated with sufficiency orientation, while time affluence shows no clear associations in the study.
Overall, the results highlight the relevance of sufficiency orientation in relation to socio-ecological transformation and actual behavioural change. Sufficiency orientation is related to low-emission behaviour and support for political measures to decarbonize infrastructures. These results contribute to the discussion on the intention-behaviour gap in regard to impact-relevant behaviour, i.e. behaviour producing high emissions. The present findings suggest, that sufficiency orientation could be related to a strong intention-behavioural consistency. However, further research is needed to validate these results and improve the measurement of sufficiency orientation. Furthermore, the studies provided insights on correlates of sufficiency orientation: justice sensitivity, global identity, subjective well-being and left-wing liberal political ideologies are all found to be positively related to sufficiency orien-tation. Moreover, basic psychological need satisfaction was identified as a potential mechanism that can support the emergence of sufficiency orientation, however, causality remains unclear. From these findings, the work derives practical implications how to possibly strengthen sufficiency orientation on the micro, meso and macro levels of society.
Taken together, the dissertation provides important insights into a new and still developing concept, and shows its connectivity to psychological theories. However, future research is required in order to grasp more precisely the complexity of sufficiency orientation and to understand origins and predictors of sufficiency orientation. This work contributes to the interdisciplinary debate on socio-ecological transformation and points out that sufficiency orientation can serve to a future worth living as being related to reduced consumption.
Social networks are ubiquitous structures that we generate and enrich every-day while connecting with people through social media platforms, emails, and any other type of interaction. While these structures are intangible to us, they carry important information. For instance, the political leaning of our friends can be a proxy to identify our own political preferences. Similarly, the credit score of our friends can be decisive in the approval or rejection of our own loans. This explanatory power is being leveraged in public policy, business decision-making and scientific research because it helps machine learning techniques to make accurate predictions. However, these generalizations often benefit the majority of people who shape the general structure of the network, and put in disadvantage under-represented groups by limiting their resources and opportunities. Therefore it is crucial to first understand how social networks form to then verify to what extent their mechanisms of edge formation contribute to reinforce social inequalities in machine learning algorithms.
To this end, in the first part of this thesis, I propose HopRank and Janus two methods to characterize the mechanisms of edge formation in real-world undirected social networks. HopRank is a model of information foraging on networks. Its key component is a biased random walker based on transition probabilities between k-hop neighborhoods. Janus is a Bayesian framework that allows to identify and rank plausible hypotheses of edge formation in cases where nodes possess additional information. In the second part of this thesis, I investigate the implications of these mechanisms - that explain edge formation in social networks - on machine learning. Specifically, I study the influence of homophily, preferential attachment, edge density, fraction of inorities, and the directionality of links on both performance and bias of collective classification, and on the visibility of minorities in top-k ranks. My findings demonstrate a strong correlation between network structure and machine learning outcomes. This suggests that systematic discrimination against certain people can be: (i) anticipated by the type of network, and (ii) mitigated by connecting strategically in the network.
This study examines the contribution of saving and credit cooperatives (SACCOS) on the improvement of members‘ socio economic development in Rwanda: Opportunities and challenges‖, Evidence from Umwalimu SACCO- Huye District‖. The appearance of saving and credit cooperatives or credit unions has been known as remedy for social ills rooted in poverty because of its efficiency in loans or credits dispensation, social equality for enhancement and reduction of poverty amongst low income earners. Therefore, millions and millions of poor people and non-bankable in developing countries (or third world countries) have been provided access to formal financial services through saving and credit cooperatives‘ programs.
The targeted population concerned by the study was 1,940 members of USACCO from which a sample of 92 respondents was purposively selected. The study has adopted a combination of correlation and descriptive research design. It has employed both quantitative and qualitative approaches. The study used both primary and secondary data. The primary data was collected using questionnaire and interview and, while secondary data was collected using documentations techniques whereby, Manual of procedures and Credit policies of USACCO and financial reports have been consulted. The analysis of data was done using SPSS version 21. The data was presented in form of tables, charts and graphs designed by SPSS v. 21. The bio-characteristics of respondents showed that, the majority of respondents were women with 55.4%, majority of respondents‘ age is between 26 to 45 years Furthermore, and majority 77.20% of respondents were married. 100% of respondents attended school, where the majority of respondents attended secondary school with certificate A2.
The study has revealed that Umwalimu SACCO services offered to its members have a positive effect on the improvement of members‘ welfare. It was found that USACCO services have slightly affected income level of members, assets acquired, access to education and medical care as well as small income generating activities established by members in Huye District. The analysis of data also revealed that there are some variables which have effected USACCO members‘ socio-economic status, these were listed as: Education background of a member, number of dependents, the occupation of a member, and number of loans got from USACCO, government programs against teachers‘ welfare, and membership duration played very important role on the improvement of standard living of teachers. All these variables were found to have positive effects on teachers‘ socio-economic status, except the family size of respondents.
In addition, the findings showed that, the majority of respondents confirmed that, they did not find opportunities to save with other financial institutions, and other respondents did not have access to loan from other financial institutions due to complicated loan requirements. In addition, after they
have joined USACCO, their deplorable status somewhat changed, both socially and economically which has contributed to the improvement of their welfare. Therefore, the study testified that, the welfare of USACCO members in terms of assets acquired, income increased was improved compared to situation before joining USACCO. The study concludes that ―the level of improvement of living conditions of teachers depends largely to the level of loan granted by USACCO to teachers and membership duration. If the level of teachers‘ loan and saving increases, there will be also improvement of teachers‘ wellbeing‖ and finally, USACCO financial service is a veritable instrument for better improvement of economic and social conditions of teachers. The study recommends that, USACCO should provide frequent and regular trainings on business management game to their members. This could help members for good management of their loans and reducing loan defaulters‘ cases observed at USACCO. Challenges observed were lack of physical collateral security required by USACCO, complicated loan requirements terms and conditions and insufficient trainings on business management game.
Instructor feedback on written assignments is one of the most important elements in the writing process, especially for students writing in English as a foreign language. However, students are often critical of both the amount and quality of the feedback they receive. In order to better understand what makes feedback effective, this study explored the nature of students’ assessments of the educational alliance, and how their receptivity to, perceptions of, and decisions about using their instructors’ feedback differed depending on how strong they believed the educational alliance to be. This exploratory case study found that students not only assessed the quality of the educational alliance based on goal compatibility, task relevance, and teacher effectiveness, but that there was also a reciprocal relationship between these elements. Furthermore, students’ perceptions of the educational alliance directly influenced how they perceived the feedback, which made the instructor’s choice of feedback method largely irrelevant. Stronger educational alliances resulted in higher instances of critical engagement, intrinsic motivation, and feelings of self-efficacy. The multidirectional influence of goal, task, and bond mean that instructors who want to maximize their feedback efforts need to attend to all three.
The growing numbers of breeding rooks (Corvus frugilegus) in the city of Landau (Rhineland- Palatinate, Germany) increase the potential for conflict between rooks and humans, which is mainly associated with noise and faeces. Therefore, the aim of this work is a better understanding of the breeding tree selection of the rook in order to develop options for action and management in the future.
Part I of this thesis provides general background information on the rook and includes mapping of the rookeries in the Anterior Palatinate and South Palatinate including Landau in the year 2020. That mapping revealed that the number of rural colonies has decreased, while the number of urban colonies has increased in the study area in the last few years. In line with current literature, tree species and tree size were important criteria for breeding tree selection. However, the mapping showed that additional factors must be important as well.
Therefore, as rooks seem to often breed along traffic axes, Part II of this thesis examines how temperature, artificial light and noise, which are all linked to traffic axes, affect the breeding tree selection of the rook in the city of Landau. The following three hypotheses are developed: (1) manually selected breeding trees (Bm) have a warmer microclimate than manually selected non-breeding trees (Nm) or randomly selected non-breeding trees (Nr), (2) Bm are exposed to a higher light level than Nm or Nr and (3) Bm are exposed to a higher noise level than Nm or Nr. To test these hypotheses, 15 Bm, 13 Nm and 16 Nr are investigated.
The results show that Bm were exposed to more noise than both types of non-breeding trees (μBm, noise = 36.52481 dB, μNm, noise = 31.27229 dB, μNr, noise = 29.17417 dB) where the difference between Bm and Nr was significant. In addition, there was a tendency for Bm to be exposed to less light (μBm, light = 0.356 lx) than Nm (μNm, light = 0.4107692 lx) and significantly less light than Nr (μNr, light = 1.995 lx), while temperature did not differ between the groups (μBm, temp = 16.90549 °C, μNm, temp = 16.93118 °C, μNr, temp = 17.28639 °C).
This study shows for the first time that rooks prefer trees which are exposed to low light levels and high noise levels, i.e. more intense traffic noise, for breeding. It can only be speculated that the cause of this is lower enemy pressure at such sites. The fact that temperature does not seem to have any influence on breeding tree selection may be due to only small temperature differences at nest height, which might be compensated by breeding behaviour. Consequently, in the long term one management approach could be to divert traffic from inner-city areas, especially schools and hospitals, to bypasses. If tree genera suitable for rooks, such as plane trees, are planted along the bypasses, those sites could provide suitable alternative habitats to inner-city breeding locations, which become less attractive for breeding due to noise reduction. In the short term in addition to locally implemented repellent measures the most effective approach is to strengthen rook acceptance among the population. However, further research is needed to verify the results of this thesis and to gain further insights into rook breeding site selection in order to develop effective management measures.
The presented study was motivated by the dynamic phenomena observed in basic catalytic surface reactions, especially by bi- and tristability, and the interactions between these stable states. In this regard, three reaction-diffusion models were developed and examined using bifurcation theory and numerical simulations.
A first model was designed to extend the bistable CO oxidation on Ir(111) to include hydrogen and its oxidation. The differential equation system was analyzed within the framework of bifurcation theory, revealing three branches of stable solutions.
One state is characterized by high formation rates (upper rate state, UR), while the other two branches display low formation rates (lower rate (LR) \& very low rate (VLR) states).
The overlapping branches form the shape of a `swallowtail', the curve of saddle-node bifurcations forming two cusps. Increasing the temperature leads to a subsequent unfolding and hence decreases the system complexity.
A series of numerical simulations representing possible experiments was conducted to illustrate the experimental accessibility (or the lack) of said states. Relaxation experiments show partially long decay times. Quasistatic scanning illustrates the existence of all three states within the tristable regime and their respective conversion once crossing a fold.
A first attempt regarding the state dominance in reaction-diffusion fronts was done. While UR seems to dominate in 1D, a 2D time-evolution shows that LR invades the interphase between UR and VLR.
Subsequently, a generic monospecies mock model was used for the comprehensive study of reaction-diffusion fronts. A quintic polynomial as reaction term was chosen, derived by the sixth-order potential associated with the `butterfly bifurcation'. This ensures up to three stable solutions($u_{0}$,$u_{1}$,$u_{2}$), depending on the four-dimensional parameter space.
The model was explored extensively, identifying regions with similar behaviors.
A term for the front velocity connecting two stable states was derived, depending only on the relative difference of the states' potential wells.
Equipotential curves were found, where the front velocity vanishes of a given front. Numerical simulations on a two-dimensional, finite disk using a triangulated mesh supported these findings.
Additionally, the front-splitting instability was observed for certain parameters. The front solution $u_{02}$ becomes unstable and divides into $u_{01}$ and $u_{12}$, exhibiting different front velocities. A good estimate for the limit of the front splitting region was given and tested using time evolutions.
Finally, the established mock model was modified from continuous to discrete space, utilizing a simple domain in 1D and three different lattices in 2D (square, hexagonal, triangular).
For low diffusivities or large distances between coupling nodes, fronts can become pinned, if the parameters are within range of the equipotential lines. This phenomenon is known as propagation failure and its extent in parameter space was explored in 1D. In 2D, an estimate was given for remarkable front orientations respective to the lattice using a pseudo-2D approximation. Near the pinning region, front velocities differ significantly from the continuous expectation as the shape of the curve potential becomes significant. Factors that decide the size and shape of the pinning regions are the coupling strength, the lattice, the front orientation relative to the lattice, and the front itself. The bifurcation diagram shows a snaking curve in the pinning region, each alternating branch representing a stable or unstable frozen front solution. Numerical simulations supported the observations concerning propagation failure and lattice dependence.
Furthermore, the influence of front orientation on the front velocity was explored in greater detail, showing that fronts with certain lattice-dependent orientations are more or less prone to propagation failure. This leads to the possibility of pattern formation, reflecting the lattice geometry. An attempt to quantify the front movement depending on angular front orientation has shown reasonable results and good agreement with the pseudo-2D approach.
Abstract for the print-book: Walden, R. (2008). Architectural Psychology: School, University Campus, and Office Building of the Future. Lengerich: Pabst Science Publishers (in German). The need for display of self in architecture and for users' self-regulation of stress factors, which demonstrate that users crave individual control of their environment (cf. Flammer, 1990; Burger, 1992) motivated this study to use the concept of environmental control as a central criterion for the evaluation of built environment. It was applied to three case studies: a school, a university campus, and an office building. Advantages and disadvantages of the data- gathering methods of architectural Programming, User-Needs Analysis, and Post-Occupancy Evaluation were analyzed to highlight their significance in terms of Building Performance Evaluation as described by Preiser and Sc hramm (1997, 2005). The “Koblenz Architecture Questionnaire” was used as an instrument for assessing the built environment of the three case studies, and the study reports selected findings from these questionnaires. The investigation seeks to determine the effect of architecture - especially buildings' provisions for user control of environmental conditions - on user performance (cf. BOSTI studies, 1984, 2001) in three innovative buildings: the Waldorf School in Cologne, the new campus for the University in Koblenz, and the Office Tower of the Deutsche Post World Net AG in Bonn. Performance is measured in terms of (1) Lear ning and Work Efficiency, (2) Well-being, (3) Environmental Control, (4) Social Behavior (the latter just for the school project), and by means of 21 and 16 additional psychological criteria for success of the organization in the cases of the university and the office building, respectively. The study aims, among other things, at reassessing the theoretical concept of 'environmental control' and at making recommendations for both improvement of existing buildings and the design of new projects. Two central questions are: In User-Needs Analysis, what is the difference between the assessment of a building for its current use and its estimated performance in future? Do certain architectural features influence user assessments on the given performance criteria? In the studies, three mapping sentences were developed according to the 'facet approach' (Borg, 1996) as well as two systems to judge the quality of school and office buildings. Using these systems, information was obtained in all three studies to construct questionnaires. In the school study, teachers were asked 139 questions, pupils 86 questions. Responses were obtained from 26 teachers and 122 pupils. For the university, 147 students and 28 faculty members responded to 203 questions. For the office building, 56 student-experts were asked 254 questions. Characteristics of the built environment were rated using the following scale: +2 ☺☺ (very good “at present”, and accordingly very important “in the future”) down to –2 // (very bad “at present”, and very unimportant “in the future”). A general finding was a high and significant co rrelation between the responses for the three main performance criteria in all three case studies, especially for the 'importance for the future' aspect. This supports the conclusion that a perception of higher degree of environmental control by users will lead to an increased sense of well-being and consequently, there will also be a higher expectation of improved work or learning efficiency 'in the future'. The three studies further show for example that users in all three environments desire 'retreat opportunities' which may take the form of student offices in schools, niches and small group seating in classrooms, and sheltered seating in outdoor areas and work tables in the cafeteria for the university. For the offices, users wanted more visual privacy (less transparent office partitions in Combi Offices) for less visual control of their activities by supervisors and co-workers. The relationships found by the studies between the responses on the central performance criteria and the spatial characteristics of the three buildings support the contention that focused improvements in the built environment, especially with respect to features that enhance user control of environmental conditions, will influence users’ well-being as well as work performance and work or learning efficiency in a positive way.
Agricultural plastic covers made from polyethylene (PE) and polypropylene (PP) provide increased yields and an improved crop quality. However, such covers are suspected of partially breaking down into smaller debris and thereby contributing to soil pollution with microplastics. To scrutinize this, we randomly sampled 240 topsoil cores (0–5 cm) from eight fields which were covered with fleeces, perforated foils, and plastic mulches for less than 2 years. Samples from the field periphery (50 m perimeter) served as a reference. Visual plastic debris > 2 mm was analyzed by Fourier transform infrared spectroscopy. Smaller, soil-associated plastic debris was dispersed from 50 g of fine soil (≤ 2 mm) using sodium hexametaphosphate solution and density-separated with saturated NaCl solution. The collected PE, PP, and polystyrene (PS) debris was selectively dissolved in a mixture of 1,2,4-trichlorobenzene and p-xylene at 150 °C and quantified by pyrolysis–gas chromatography–mass spectrometry (Py-GC/MS). We counted six PE and PS fragments > 2 mm in two out of eight fields. By contrast, Py-GC/MS detected PE, PP, and PS contents in the fine soil of six fields (6 % of all samples). In three fields, PE levels of 3–35 mg kg−1 were potentially associated with the use of thinner and less durable perforated foils (40 µm thickness). This was slightly more pronounced at field edges where the plastic covers are turned and weighed down. By contrast, 50 µm thick PE films were not shown to emit any plastic debris. PP contents of 5–10 mg kg−1 were restricted to single observations in the field centers of three sites. At one site, we found expanded PS particles > 2 mm that concurred with elevated PS levels (8–19 mg kg−1) in the fine soil. Both PP and PS were distributed indistinctly across sites so that their source remained unresolved. In addition, the extent to which plastic contents of up to 7 mg kg−1 in the field periphery of some sites were attributed to wind drift from the covered fields or from external sources needs to be investigated in future studies. Our results suggest that the short-term use of thicker and more durable plastic covers should be preferred over thinner or perforated films to limit plastic emissions and accumulation in soil.
This thesis explores a 3D object detection and pose estimation approach based on the point pair features method presented by Drost et. al. [Dro+10]. While pose estimation methods have shown good improvements, they still remain a crucial problem on the computer vision field. In this work, we implemented a program that takes point cloud scenes as input and returns the detected object with their estimated pose. The program fully covers an object detection pipeline by processing 3D models during an offline phase, extracting their point pair features and creating a global descriptor out of them. During an online phase, the same features are extracted from a point cloud scene and are matched to the model features. After the voting scheme, potential poses of the object are retrieved. The poses end being clustered together and post-processed to finally deliver a result. The program was tested using simulated and real data. We evaluate these tests and present the final results, by discussing the achieved accuracy of the detections and the estimated poses.
These proceedings contain 6 papers presented at the 1st Interdisciplinary Conference on Gamification and Entrepreneurship (StartPlay) 2022. The conference was held at the University of Koblenz-Landau in Koblenz, Germany, on August 05-06, 2022.
Game-Balance Simulation as a Tool for the Evaluation of
Systematically Designed Gamification Strategies
Authors: David Kessing, Manuel Löwer
A Canvas Framework for Gameful Design Concepts
Authors: Max Höllen, Thomas Voit
Gamified Sustainable Entrepreneurship Education –
A digital Educational Escape Room for economy classes
in German High Schools
Authors: Jürgen Frentz, Marie Tuchscherer, Claudia Wiepcke
Playing Positive Psychology: The Development of a
Positive-Psychological Board Game for Team Building
Authors: Leonie Kloep, Anna-Lena Helten, Corinna Peifer
Gamification Design for Goal Activation and Goal Striving
in Digital Marketing and Innovation Management
Authors: Jenny V. Bittner, Christian Wellmann
Gamification of Assembly Routines: Planned User Study
Evaluating a Level System with Customized Feedback
Elements
Authors: Jessica Ulmer, Sebastian Braun, Jörg Wollert
This study was conducted in Nyungwe National Park (NNP); a biodiversity hotspot Mountain rainforest of high conservation importance in Central Africa, but with little knowledge of its insect communities including butterflies, good indicators of climate change, and forest ecosystem health. The study aimed at availing baseline data on butterfly species diversity and distribution in NNP, for future use in monitoring climate change-driven shifts and the effects of forest fragmentation on the biodiversity of Nyungwe. Butterflies were collected seasonally using fruit-baited traps and hand nets along elevational transects spanning from 1700 m up to 2950 m of altitude. Two hundred forty-two species including 28 endemics to the Albertine Rift and 18 potential local climate change indicators were documented. Species richness and abundance declined with increasing elevation and higher seasonal occurrence was observed during the dry season. This was the first study on the spatial and temporal distribution of butterflies in NNP and further studies could be conducted to add more species and allow a depth understanding of the ecology of Nyungwe butterflies.
Semantic Web technologies have been recognized to be key for the integration of distributed and heterogeneous data sources on the Web, as they provide means to define typed links between resources in a dynamic manner and following the principles of dataspaces. The widespread adoption of these technologies in the last years led to a large volume and variety of data sets published as machine-readable RDF data, that once linked constitute the so-called Web of Data. Given the large scale of the data, these links are typically generated by computational methods that given a set of RDF data sets, analyze their content and identify the entities and schema elements that should be connected via the links. Analogously to any other kind of data, in order to be truly useful and ready to be consumed, links need to comply with the criteria of high quality data (e.g., syntactically and semantically accurate, consistent, up-to-date). Despite the progress in the field of machine learning, human intelligence is still essential in the quest for high quality links: humans can train algorithms by labeling reference examples, validate the output of algorithms to verify their performance on a data set basis, as well as augment the resulting set of links. Humans —especially expert humans, however, have limited availability. Hence, extending data quality management processes from data owners/publishers to a broader audience can significantly improve the data quality management life cycle.
Recent advances in human computation and peer-production technologies opened new avenues for human-machine data management techniques, allowing to involve non-experts in certain tasks and providing methods for cooperative approaches. The research work presented in this thesis takes advantage of such technologies and investigates human-machine methods that aim at facilitating link quality management in the Semantic Web. Firstly, and focusing on the dimension of link accuracy, a method for crowdsourcing ontology alignment is presented. This method, also applicable to entities, is implemented as a complement to automatic ontology alignment algorithms. Secondly, novel measures for the dimension of information gain facilitated by the links are introduced. These entropy-centric measures provide data managers with information about the extent the entities in the linked data set gain information in terms of entity description, connectivity and schema heterogeneity. Thirdly, taking Wikidata —the most successful case of a linked data set curated, linked and maintained by a community of humans and bots— as a case study, we apply descriptive and predictive data mining techniques to study participation inequality and user attrition. Our findings and method can help community managers make decisions on when/how to intervene with user retention plans. Lastly, an ontology to model the history of crowd contributions across marketplaces is presented. While the field of human-machine data management poses complex social and technical challenges, the work in this thesis aims to contribute to the development of this still emerging field.
Men are currently underrepresented in traditionally female care-oriented (communal) engagement such as taking parental leave, whereas they are overrepresented in traditionally male (agentic) engagement such as breadwinning or leadership. We examined to what extent different prototypical representations of men affect men’s self-reported parental leave-taking intentions and more generally the future they can imagine for themselves with regard to work and care roles (i.e., their possible selves). We expected prototypes of men that combine the two basic stereotype dimensions of agency and communion to increase men’s communal intentions. In two experiments (N1 = 132, N2 = 233), we presented male participants with contrived newspaper articles that described the ideal man of today with varying degrees of agency and communion (between-subjects design with four conditions; combined agentic and communal vs. agentic vs. communal vs. control condition). Results of Experiment 1 were in line with the main hypothesis that especially presenting a combination of agency and communion increases men’s expectations for communal engagement: As compared to a control condition, men expected more to engage in caretaking in the future, reported higher parental leave-taking intentions, and tended to expect taking longer parental leave. Experiment 2 only partially replicated these findings, namely for parental leave-taking intentions. Both experiments additionally provided initial evidence for a contrast effect in that an exclusive focus on agency also increased men’s self-reported parental leave-taking intentions compared to the control condition. Yet, exclusively emphasizing communion in prototypes of men did not affect men’s communal intentions, which were high to begin with. We further did not find evidence for preregistered mechanisms. We discuss conditions and explanations for the emergence of these mixed effects as well as implications for the communication of gendered norms and barriers to men’s communal engagement more broadly.
Social media provides a powerful way for people to share opinions and sentiments about a specific topic, allowing others to benefit from these thoughts and feelings. This procedure generates a huge amount of unstructured data, such as texts, images, and references that are constantly increasing through daily comments to related discussions. However, the vast amount of unstructured data presents risks to the information-extraction process, and so decision making becomes highly challenging. This is because data overload may cause the loss of useful data due to its inappropriate presentation and its accumulation. To this extent, this thesis contributed to the field of analyzing and detecting feelings in images and texts. And that by extracting the feelings and opinions hidden in a huge collection of image data and texts on social networks After that, these feelings are classified into positive, negative, or neutral, according to the features of the classified data. The process of extracting these feelings greatly helps in decision-making processes on various topics as will be explained in the first chapter of the thesis. A system has been built that can classify the feelings inherent in the images and texts on social media sites, such as people’s opinions about products and companies, personal posts, and general messages. This thesis begins by introducing a new method of reducing the dimension of text data based on data-mining approaches and then examines the sentiment based on neural and deep neural network classification algorithms. Subsequently, in contrast to sentiment analysis research in text datasets, we examine sentiment expression and polarity classification within and across image datasets by building deep neural networks based on the attention mechanism.
Background. Agricultural plastic mulches offer great benefits such as higher yields and lower pesticide use. Yet, plastic mulches may disintegrate over time and fragment into smaller debris. Such plastic debris is expected to remain in the field after removal of the plastic mulch and thus contributes to soil contamination with plastics.
Method. To investigate this, we collected soil samples at 0–10 cm and 10–40 cm depth from three fields covered with black mulch film for three consecutive years. Three fields without any reported plastic use served as control. Visual plastic debris > 1 cm (macroplastics) was collected from the soil surface. Mesoplastics between 2 mm and 1 cm were density separated from the sampled soil using saturated NaCl solution and analyzed by Fourier-transform infrared spectroscopy. Debris ≤ 2 mm (microplastics) was dispersed from 50 g soil using sodium hexametaphosphate solution followed by the aforementioned density separation. The separated polyethylene (PE), polypropylene (PP), and polystyrene (PS) were quantified via solvent-based pyrolysis–gas chromatography/mass spectrometry (Py–GC/MS).
Results. With 89–206 fragments ha−1, the majority of macroplastics were located in fields previously covered with mulch films. 80% of the collected specimen were identified as black PE film. The number of mesoplastics in plastic-mulched soil was 2.3 particles kg−1, while only 1.0 particles kg−1 were found in the reference fields. Py–GC/MS revealed microplastic levels of up to 13 mg kg−1. The PE content was significantly higher in plastic-mulched fields than in reference fields.
Discussion. Although the identified plastic levels are lower than those reported in comparable studies, our results still suggest that plastic mulching functions as a source of plastic debris in agricultural systems. Due to its severely restricted degradability, these plastics are likely to accumulate in soil in the long term and further fragment into smaller and smaller debris.
Manmade dams have been constructed from centuries for multiple purposes, and in the past decades they have been constructed in a fast pace, with the hotspot in tropical and subtropical regions. However, studies that explore hydrodynamics in these areas are scarce and biased to the rich literature available for temperate regions. Lakes and reservoirs have the same controlling mechanisms for physical processes and primary production, hence, analyses that were initially conceptualized for lakes are frequently applied for reservoirs. Nevertheless, longitudinal gradients in reservoirs challenges the application of these approaches.
Degradation of water quality in reservoirs is a major concern, and it is expected to be aggravated with climate change. Therefore, studies that explore mechanisms controlling water quality are essential for the maintenance of these systems, especially in tropical and subtropical regions. The aim of this thesis is to comprehend the role of hydrodynamic processes in the fate of nutrients in reservoirs and its implications on water quality, in a subtropical region. With focus on the relevance of different density current patterns. For that, analyses combining field measurements and numerical simulations were performed in a medium to small size subtropical drinking water reservoir for a complete seasonal cycle. Measurements were conducted combining several approaches: traditional sampling, sensors in high temporal and spatial resolution, and remote sensing. Besides, hydrodynamic models were set up and calibrated to reproduce observations, and to simulate scenarios that assisted on the analysis.
Results showed that different flow paths of density currents did not influence on phytoplankton dynamics. At the regions where the main nutrient supply was the river inflow (upstream), the density currents did not vary, the euphotic zone usually covered the entire depth, and vertical mixing was observed on a daily basis, turning the flow path of the density currents irrelevant. At downstream regions, the remobilization of nutrients in the sediment was the main source for primary production. Even though density currents had a seasonal pattern in the downstream region, thermal stratification conditions were the driver for variations in chlorophyll-a concentrations, with peaks after vertical mixing. This mechanism had in its favor the frequent anoxic conditions in the hypolimnion that enhanced the dissolution of reactive phosphorus from the sediment. Anoxic conditions were easily reached because the sediment in the downstream area was rich in organic matter. Phytoplankton produced in the upstream area was transported by the density currents, and for this reason, large concentrations of chl-a was observed below the euphotic zone. Further, the extensive measurements of temperature, and flow velocities, together with the hydrodynamic models, provided insights about the hydrodynamics of reservoirs. For instance, that the relevant processes occurred along the longitudinal, and mixing conditions varied along it. The relevance of inflow conditions regarding the presence of structures such as forebays and pre-dams, and the degree of stream shading in the catchment was assessed. And turbulence and internal waves had different features than the documented for high latitudes. Those findings can assist on the management of reservoirs, based on the comprehension of the physical processes.
Background: For over a century, scientists have studied host-pathogen interactions between the crayfish plague disease agent Aphanomyces astaci and freshwater crayfish. It has been hypothesised that North American crayfish hosts are disease-resistant due to the long-lasting coevolution with the pathogen. Similarly, the increasing number of latent infections reported in the historically sensitive European crayfish hosts seems to indicate that similar coevolutionary processes are occurring between European crayfish and A. astaci. Our current understanding of these host-pathogen interactions is largely focused on the innate immunity processes in the crayfish haemolymph and cuticle, but the molecular basis of the observed disease-resistance and susceptibility remain unclear. To understand how coevolution is shaping the host’s molecular response to the pathogen, susceptible native European noble crayfish and invasive disease-resistant marbled crayfish were challenged with two A. astaci strains of different origin: a haplogroup A strain (introduced to Europe at least 50 years ago, low virulence) and a haplogroup B strain (signal crayfish in lake Tahoe, USA, high virulence). Here, we compare the gene expression profiles of the hepatopancreas, an integrated organ of crayfish immunity and metabolism.
Results: We characterised several novel innate immune-related gene groups in both crayfish spe cies. Across allchallenge groups, we detected 412 differentially expressed genes (DEGs) in the noble crayfish, and 257 DEGs in the marbled crayfish. In the noble crayfish, a clear immune response was detected to the haplogroup B strain, but not to the haplogroup A strain. In contrast, in the marbled crayfish we detected an immune response to the haplogroup A strain, but not to the haplogroup B strain. Conclusions: We highlight the hepatopancreas as an important hub for the synthesis of immune molecules in the response to A. astaci. A clear distinction between the innate immune response in the marbled crayfish and the noble crayfish is the capability of the marbled crayfish to mobilise a higher variety of innate immune response effectors.
The use of agricultural plastic covers has become common practice for its agronomic benefits such as improving yields and crop quality, managing harvest times better, and increasing pesticide and water use efficiency. However, plastic covers are suspected of partially breaking down into smaller debris and thereby contributing to soil pollution with microplastics. A better understanding of the sources and fate of plastic debris in terrestrial systems has so far been hindered by the lack of adequate analytical techniques for the mass-based and polymer-selective quantification of plastic debris in soil. The aim of this dissertation was thus to assess, develop, and validate thermoanalytical methods for the mass-based quantification of relevant polymers in and around agricultural fields previously covered with fleeces, perforated foils, and plastic mulches. Thermogravimetry/mass spectrometry (TGA/MS) enabled direct plastic analyses of 50 mg of soil without any sample preparation. With polyethylene terephthalate (PET) as a preliminary model, the method limit of detection (LOD) was 0.7 g kg−1. But the missing chromatographic separation complicated the quantification of polymer mixtures. Therefore, a pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) method was developed that additionally exploited the selective solubility of polymers in specific solvents prior to analysis. By dissolving polyethylene (PE), polypropylene (PP), and polystyrene (PS) in a mixture of 1,2,4-trichlorobenzene and p-xylene after density separation, up to 50 g soil became amenable to routine plastic analysis. Method LODs were 0.7–3.3 mg kg−1, and the recovery of 20 mg kg−1 PE, PP, and PS from a reference loamy sand was 86–105%. In the reference silty clay, however, poor PS recoveries, potentially induced by the additional separation step, suggested a qualitative evaluation of PS. Yet, the new solvent-based Py-GC/MS method enabled a first exploratory screening of plastic-covered soil. It revealed PE, PP, and PS contents above LOD in six of eight fields (6% of all samples). In three fields, PE levels of 3–35 mg kg−1 were associated with the use of 40 μm thin perforated foils. By contrast, 50 μm PE films were not shown to induce plastic levels above LOD. PP and PS contents of 5–19 mg kg−1 were restricted to single observations in four fields and potentially originated from littering. The results suggest that the short-term use of thicker and more durable plastic covers should be preferred to limit plastic emissions and accumulation in soil. By providing mass-based information on the distribution of the three most common plastics in agricultural soil, this work may facilitate comparisons with modeling and effect data and thus contribute to a better risk assessment and regulation of plastics. However, the fate of plastic debris in the terrestrial environment remains incompletely understood and needs to be scrutinized in future, more systematic research. This should include the study of aging processes, the interaction of plastics with other organic and inorganic compounds, and the environmental impact of biodegradable plastics and nanoplastics.
For software engineers, conceptually understanding the tools they are using in the context of their projects is a daily challenge and a prerequisite for complex tasks. Textual explanations and code examples serve as knowledge resources for understanding software languages and software technologies. This thesis describes research on integrating and interconnecting
existing knowledge resources, which can then be used to assist with understanding and comparing software languages and software technologies on a conceptual level. We consider the following broad research questions that we later refine: What knowledge resources can be systematically reused for recovering structured knowledge and how? What vocabulary already exists in literature that is used to express conceptual knowledge? How can we reuse the
online encyclopedia Wikipedia? How can we detect and report on instances of technology usage? How can we assure reproducibility as the central quality factor of any construction process for knowledge artifacts? As qualitative research, we describe methodologies to recover knowledge resources by i.) systematically studying literature, ii.) mining Wikipedia, iii.) mining available textual explanations and code examples of technology usage. The theoretical findings are backed by case studies. As research contributions, we have recovered i.) a reference semantics of vocabulary for describing software technology usage with an emphasis on software languages, ii.) an annotated corpus of Wikipedia articles on software languages, iii.) insights into technology usage on GitHub with regard to a catalog of pattern and iv.) megamodels of technology usage that are interconnected with existing textual explanations and code examples.
The Coronavirus Pandemic has influenced the lives of many people. We analyzed the effects of physical activity and stress on students’ motivation during the Pandemic. Participants were 254 university students who reported their academic motivation, physical activity, general stress, the Coronavirus Pandemic strain, and their Coronavirus stress. Women reported higher levels of Coronavirus stress, general stress, and motivation. The Coronavirus stress was predicted by the strain of the Coronavirus Pandemic but not by physical activity. General stress and gender predicted mastery goals, and performance goals were predicted by general stress. Physical activity was not related to students’ motivation during the Pandemic. Higher levels of general stress were associated with higher academic motivation. Negative emotions like stress could have enhanced students’ motivation during uncertain times of the Pandemic. Moreover, a moderate stress level could be favorable for academic dedication and achievement.
To render the surface of a material capable of withstanding mechanical and electrochemical loads, and to perform well in service, the deposition of a thin film or coating is a solution. In this project, such a thin film deposition is carried out. The coating material chosen is titanium nitride (TiN) which is a ceramic material known to possess a high hardness (>10 GPa) as well as good corrosion resistance. The method of deposition selected is high power impulse magnetron sputtering (HiPIMS) that results in coatings with high quality and enhanced properties. Sputtering is a physical process that represents the removal or dislodgment of surface atoms by energetic particle bombardment. The term magnetron indicates that a magnetic field is utilized to increase the efficiency of the sputtering process. In HiPIMS, a high power is applied in pulses of low duty cycles to a cathode that is sputtered and that consists of the coating material. As result of the high power, the ionization of the sputtered material takes place giving the possibility to control these species with electric and magnetic field allowing thereby the improvement and tuning of coating properties. However, the drawback of HiPIMS is a low deposition rate.
In this project, it is demonstrated first that it is possible to deposit TiN coating using HiPIMS with an optimized deposition rate, by varying the magnetic field strength. It was found that low magnetic field strength (here 22mT) results in a deposition rate similar to that of conventional magnetron sputtering in which the average power is applied continuously, called also direct current magnetron sputtering (dcMS). The high deposition rate at low magnetic field strength was attributed to a reduction in the back attraction probability of the sputtered species. The magnetic field strength did not show noticeable influence on the mechanical properties. The proposed explanation was that the considered peak current density interval 1.22-1.72 A∙cm-2 does not exhibit dramatic changes in the plasma dynamics.
In a second part, using the optimized deposition rate, the optimized chemical composition of TiN was determined. It was shown that the chemical composition of TiN does not significantly influence the corrosion performance but impacts considerably the mechanical properties. It was also shown that the corrosion resistance of the coatings deposited using HiPIMS was higher than that of the coatings deposited using dcMS.
The third study was the effect of annealing post deposition on the properties of TiN coating deposited using HiPIMS. The hardness of the coatings showed a maximum at 400°C reaching 24.8 GPa. Above 400°C however, a lowering of the hardness was measured and was due to the oxidation of TiN which led to the formation of TiN-TiO2 composites with lower mechanical properties.
The coating microscopic properties such as crystal orientation, residual stresses, average grain size were determined from X-ray diffraction data and the roughness was measured using atomic force microscopy. These properties were found to vary with the magnetic field strength, the chemical composition as well as the annealing temperature.