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Assessing ChatGPT’s Performance in Analyzing Students’ Sentiments: A Case Study in Course Feedback
(2024)
The emergence of large language models (LLMs) like ChatGPT has impacted fields such as education, transforming natural language processing (NLP) tasks like sentiment analysis. Transformers form the foundation of LLMs, with BERT, XLNet, and GPT as key examples. ChatGPT, developed by OpenAI, is a state-of-the-art model and its ability in natural language tasks makes it a potential tool in sentiment analysis. This thesis reviews current sentiment analysis methods and examines ChatGPT’s ability to analyze sentiments across three labels (Negative, Neutral, Positive) and five labels (Very Negative, Negative, Neutral, Positive, Very Positive) on a dataset of student course reviews. Its performance is compared with fine tuned state-of-the-art models like BERT, XLNet, bart-large-mnli, and RoBERTa-large-mnli using quantitative metrics. With the help of 7 prompting techniques which are ways to instruct ChatGPT, this work also analyzed how well it understands complex linguistic nuances in the given texts using qualitative metrics. BERT and XLNet outperform ChatGPT mainly due to their bidirectional nature, which allows them to understand the full context of a sentence, not just left to right. This, combined with fine-tuning, helps them capture patterns and nuances better. ChatGPT, as a general purpose, open-domain model, processes text unidirectionally, which can limit its context understanding. Despite this, ChatGPT performed comparably to XLNet and BERT in three-label scenarios and outperformed others. Fine-tuned models excelled in five label cases. Moreover, it has shown impressive knowledge of the language. Chain-of-Thought (CoT) was the most effective technique for prompting with step by step instructions. ChatGPT showed promising performance in correctness, consistency, relevance, and robustness, except for detecting Irony. As education evolves with diverse learning environments, effective feedback analysis becomes increasingly valuable. Addressing ChatGPT’s limitations and leveraging its strengths could enhance personalized learning through better sentiment analysis.
Exploring Academic Perspectives: Sentiments and Discourse on ChatGPT Adoption in Higher Education
(2024)
Artificial intelligence (AI) is becoming more widely used in a number of industries, including in the field of education. Applications of artificial intelligence (AI) are becoming crucial for schools and universities, whether for automated evaluation, smart educational systems, individualized learning, or staff support. ChatGPT, anAI-based chatbot, offers coherent and helpful replies based on analyzing large volumes of data. Integrating ChatGPT, a sophisticated Natural Language Processing (NLP) tool developed by OpenAI, into higher education has sparked significant interest and debate. Since the technology is already adapted by many students and teachers, this study delves into analyzing the sentiments expressed on university websites regarding ChatGPT integration into education by creating a comprehensive sentiment analysis framework using Hierarchical Residual RSigELU Attention Network (HR-RAN). The proposed framework addresses several challenges in sentiment analysis, such as capturing fine-grained sentiment nuances, including contextual information, and handling complex language expressions in university review data. The methodology involves several steps, including data collection from various educational websites, blogs, and news platforms. The data is preprocessed to handle emoticons, URLs, and tags and then, detect and remove sarcastic text using the eXtreme Learning Hyperband Network (XLHN). Sentences are then grouped based on similarity and topics are modeled using the Non-negative Term-Document Matrix Factorization (NTDMF) approach. Features, such as lexico-semantic, lexico structural, and numerical features are extracted. Dependency parsing and coreference resolution are performed to analyze grammatical structures and understand semantic relationships. Word embedding uses the Word2Vec model to capture semantic relationships between words. The preprocessed text and extracted features are inputted into the HR-RAN classifier to categorize sentiments as positive, negative, or neutral. The sentiment analysis results indicate that 74.8% of the sentiments towards ChatGPT in higher education are neutral, 21.5% are positive, and only 3.7% are negative. This suggests a predominant neutrality among users, with a significant portion expressing positive views and a very small percentage holding negative opinions. Additionally, the analysis reveals regional variations, with Canada showing the highest number of sentiments, predominantly neutral, followed by Germany, the UK, and the USA. The sentiment analysis results are evaluated based on various metrics, such as accuracy, precision, recall, F-measure, and specificity. Results indicate that the proposed framework outperforms conventional sentiment analysis models. The HR-RAN technique achieved a precision of 98.98%, recall of 99.23%, F-measure of 99.10%, accuracy of 98.88%, and specificity of 98.31%. Additionally, word clouds are generated to visually represent the most common terms within positive, neutral, and negative sentiments, providing a clear and immediate understanding of the key themes in the data. These findings can inform educators, administrators, and developers about the benefits and challenges of integrating ChatGPT into educational
settings, guiding improvements in educational practices and AI tool development.
Recent studies show that biofilm substances in contact with nanoplastics play an important role in the aggregation and sedimentation of nanoplastics. Consequences of these processes are changes in biofilm formation and stability and changes in the transport and fate of pollutants in the environment. Having a deeper understanding of the nanoplastics–biofilm interaction would help to evaluate the risks posed by uncontrolled nanoplastic pollution. These interactions are impacted by environmental changes due to climate change, such as, e.g., the acidification of surface waters. We apply fluorescence correlation spectroscopy (FCS) to investigate the pH-dependent aggregation tendency of non-functionalized polystyrene (PS) nanoparticles (NPs) due to intermolecular forces with model extracellular biofilm substances. Our biofilm model consists of bovine serum albumin (BSA), which serves as a representative for globular proteins, and the polysaccharide alginate, which is a main component in many biofilms, in solutions containing Na+ with an ionic strength being realistic for fresh-water conditions. Biomolecule concentrations ranging from 0.5 g/L up to at maximum 21 g/L are considered. We use non-functionalized PS NPs as representative for mostly negatively charged nanoplastics. BSA promotes NP aggregation through adsorption onto the NPs and BSA-mediated bridging. In BSA–alginate mixtures, the alginate hampers this interaction, most likely due to alginate–BSA complex formation. In most BSA–alginate mixtures as in alginate alone, NP aggregation is predominantly driven by weaker, pH-independent depletion forces. The stabilizing effect of alginate is only weakened at high BSA contents, when the electrostatic BSA–BSA attraction is not sufficiently screened by the alginate. This study clearly shows that it is crucial to consider correlative effects between multiple biofilm components to better understand the NP aggregation in the presence of complex biofilm substances. Single-component biofilm model systems based on comparing the total organic carbon (TOC) content of the extracellular biofilm substances, as usually considered, would have led to a misjudgment of the stability towards aggregation.
The goal of this PhD thesis is to investigate possibilities of using symbol elimination for solving problems over complex theories and analyze the applicability of such uniform approaches in different areas of application, such as verification, knowledge representation and graph theory. In the thesis we propose an approach to symbol elimination in complex theories that follows the general idea of combining hierarchical reasoning with symbol elimination in standard theories. We analyze how this general approach can be specialized and used in different areas of application.
In the verification of parametric systems it is important to prove that certain safety properties hold. This can be done by showing that a property is an inductive invariant of the system, i.e. it holds in the initial state of the system and is invariant under updates of the system. Sometimes this is not the case for the condition itself, but for a stronger condition it is. In this thesis we propose a method for goal-directed invariant strengthening.
In knowledge representation we often have to deal with huge ontologies. Combining two ontologies usually leads to new consequences, some of which may be false or undesired. We are interested in finding explanations for such unwanted consequences. For this we propose a method for computing interpolants in the description logics EL and EL⁺, based on a translation to the theory of semilattices with monotone operators and a certain form of interpolation in this theory.
In wireless network theory one often deals with classes of geometric graphs in which the existence or non-existence of an edge between two vertices in a graph relies on properties on their distances to other nodes. One possibility to prove properties of those graphs or to analyze relations between the graph classes is to prove or disprove that one graph class is contained in the other. In this thesis we propose a method for checking inclusions between geometric graph classes.
In Geschäftsbeziehungen, z. B. im internationalen Eisenbahnverkehr, können große Datenmengen zwischen den beteiligten Parteien ausgetauscht werden. Für den Austausch solcher Daten wird erwartet, dass das Risiko betrogen zu werden, z. B. durch den Erhalt gefälschter Daten, marginal ist, als auch angemessene Kosten sowie ein vorhersehbarer Gewinn. Da die ausgetauschten Daten für wichtige Geschäftsentscheidungen verwendet werden können, besteht für eine Partei ein hoher Anreiz, die Daten zu ihren Gunsten zu manipulieren. Um diese Art von Manipulation zu unterbinden existieren Mechanismen zur Sicherstellung der Integrität und Authentizität der Daten. In Kombination mit einem Protokoll für einen fairen Austausch kann sichergestellt werden, dass die Integrität und Authentizität dieser Daten auch über einen Austausch mit einer anderen Partei hinweg erhalten bleibt. Gleichzeitig stellt ein solches Protokoll sicher, dass der Austausch der Daten nur bei gleichzeitigem Austausch mit der vereinbarten Gegenleistung, z. B. einer Bezahlung erfolgt, aber auch, dass die Bezahlung nur erfolgt, wenn die Integrität und Authentizität der Daten wie vorher vereinbart, gegeben ist. Um jedoch Fairness garantieren zu können, muss ein Fair Exchange Protokoll eine vertrauenswürdige dritte Partei einbeziehen. Um Betrug durch eine einzelne zentralisierte Partei zu vermeiden, die als vertrauenswürdige dritte Partei agiert, schlägt die aktuelle Forschung vor, die vertrauenswürdige dritte Partei zu dezentralisieren, indem z. B. ein Distributed Ledger-basiertes Fair-Exchange Protokoll verwendet wird. Bei der Bewertung der Fairness eines solchen Austauschs vernachlässigen die aktuellen Ansätze jedoch die Kosten, die den Parteien entstehen, die den Fair Exchange durchführen. Dies kann zu einer Verletzung der skizzierten Erwartung angemessener Kosten führen, insbesondere wenn Distributed Ledger beteiligt sind, deren Benutzung in der Regel mit nicht-vernachlässigbaren Kosten verbunden ist. Darüber hinaus ist die Geschwindigkeit typischer Distributed-Ledger-basierter Fair Exchange-Protokolle begrenzt, was einer breiten Verwendung im Wege steht.
Um diese Herausforderungen zu überwinden, stellen wir in dieser Arbeit die Grundlage für eine Datenaustauschplattform vor, die einen vollständig dezentralisierten Fair Exchange mit angemessenen Kosten und Geschwindigkeit ermöglicht. Als theoretische Grundlage führen wir das Konzept der cost fairness ein, die die Kosten für die Fairnessbewertung berücksichtigt, indem verlangt wird, dass eine Partei, die dem Fair Exchange-Protokoll folgt, niemals einseitige Nachteile erleidet. Wir weisen nach, dass cost fairness nicht mit typischen öffentlichen Distributed Ledgers erreicht werden kann, sondern maßgeschneiderte Distributed Ledger-Instanzen erfordert, die in der Regel nicht vollständig dezentralisiert sind. Wir zeigen jedoch, dass die meisten einseitigen Kosten durch Angriffe einer unehrlichen Partei im Rahmen einer Grieving Attack verursacht werden können. Um einen Fair Exchange zu angemessenen Kosten und Geschwindigkeit zu ermöglichen, stellen wir FairSCE vor, ein Distributed Ledger-basiertes Fair Exchange-Protokoll, welches Distributed Ledger State Channels verwendet und einen Mechanismus zum Schutz vor Grieving Attacks enthält, wodurch die möglichen einseitigen Kosten auf ein Minimum reduziert werden. Auf der Grundlage unserer Evaluation von FairSCE sind die Worst Case-Kosten für den Datenaustausch selbst bei Vorhandensein von böswilligen Parteien bekannt, was eine Abschätzung des möglichen Nutzens und damit eine vorläufige Schätzung des wirtschaftlichen Nutzens ermöglicht. Um eine eindeutige Bewertung der korrekten übertragenen Daten zu ermöglichen und gleichzeitig sensible Teile der Daten zu maskieren, stellen wir außerdem einen Ansatz für das Hashing hierarchisch strukturierter Daten vor, mit dem die Integrität und Authentizität der übertragenen Daten sichergestellt werden kann.
Well-being is essential for all people. Therefore, important factors influencing people’s well-being must be investigated. Well-being is multifaceted and defined as, for example, psychological, emotional, mental, physical, or social well-being. Here, we focus on psychological well-being. The study aimed to analyze different aspects of connectedness as potential predictors of psychological well-being. For this purpose, we conducted a study examining the psychological well-being of 184 participants (130 women, 54 men, age: M = 31.39, SD = 15.24) as well as their connectedness with oneself (self-love), with others (prosocialness), with nature (nature connectedness), and with the transcendent (spirituality). First, significant positive correlations appeared between psychological well-being and self-love, nature connectedness, and spirituality. Furthermore, correlations between the four aspects of connectedness were significant, except for the relationship between self-love and prosocialness. A regression analysis revealed that self-love and nature connectedness positively predicted participants’ psychological well-being, while spirituality and prosocialness did not explain any incremental variance. The strong relationship between self-love and well-being was partly mediated by nature connectedness. Hence, self love, understood as a positive attitude of self-kindness, should be considered in more detail to enhance psychological well-being. Besides this, a more vital connectedness to the surrounding nature could benefit people’s well-being.
Examining the role of post-event processing in test anxiety—Pilot testing in three student samples
(2024)
This work investigates the occurrence of post-event processing (PEP) in the context of test anxiety; PEP involves rumination and self-critical thinking following an event and commonly observed in social anxiety. Three short-term longitudinal studies in student samples examined whether PEP occurs after exams and how it is associated with test anxiety. University students (N =35 in Study 1, N =146 in Study 2, and N =37 in Study 3) completed measures of trait and state test anxiety before an actual exam; PEP related to the exam was assessed at various time points afterward. Results revealed that PEP occurred to a meaningful extent after exam situations. Overall, it was positively associated with trait and state test anxiety, although some variations in the relations were found across the three studies. These findings underscore the relevance of PEP in the context of test anxiety, as PEP might contribute to maintaining test anxiety in the long term. Implications for future studies are discussed.
Die aus nachwachsenden Rohstoffen hergestellten biologisch abbaubaren Polymere Polymilchsäure (polylactic acid, PLA) und Polyhydroxybuttersäure (polyhydroxybutyrate, PHB) wurden im Rahmen dieser Arbeit mit hydrierten amorphen Kohlenstoffschichten (amorphous hydrogenated carbon, a-C:H) bei unterschiedlichen Winkeleinstellungen mit verschiedenen Dicken beschichtet. Ähnlich wie herkömmliche Polymere haben Biopolymere oft ungeeignete Oberflächeneigenschaften für industrielle Zwecke, z.B. eine geringe Härte. Für manche Anwendungen ist es daher notwendig und vorteilhaft, die Oberflächeneigenschaften von Biopolymeren unter Beibehaltung der Haupteigenschaften des Trägermaterials zu modifizieren. Eine geeignete Oberflächenmodifikation ist das Aufbringen von dünnen a-C:H Schichten. Ihre Eigenschaften hängen wesentlich vom sp²- und sp³-Hybridisierungsverhältnis der Kohlenstoffatome und dem Gehalt an Wasserstoffatomen ab. Das sp²/sp³-Verhältnis sollte in der vorliegenden Arbeit durch Variation der Beschichtungsgeometrie gesteuert werden. Da Beschichtungen bei 0°, direkt vor der Plasmaquelle, einen höheren Anteil an sp³ und indirekt (180°) beschichtete ein höheren Anteil an sp² aufweisen, wird in dieser Arbeit gezeigt, dass es möglich ist, das sp²/sp³ -Verhältnis zu kontrollieren. Dazu werden die einzelnen Proben in den Winkeln 0, 30, 60, 90, 120, 150 und 180° vor der Plasmaquelle platziert und mit einer Dauer von 2.5, 5.0, 7.5 und 10.0 Minuten beschichtet. Für den Winkeln 0° ergaben sich die Schichtdicken von 25, 50, 75 und 100 nm. Die a-C:H Schichten wurden alle mit Radiofrequenzplasma-unterstützter chemischer Gasphasenabscheidung und Acetylen als C und H Quelle abgeschieden, nachdem sie 10 Minuten lang mit einem Sauerstoffplasma vorbehandelt worden waren. Nach dieser O₂-Behandlung und der a-C:H Abscheidung werden die Oberflächen mit makroskopischen und mikroskopischen Messmethoden untersucht und die Daten anschließend analysiert. Die Oberflächenmorphologie wird mit Hilfe der Rasterelektronenmikroskopie und der Rasterkraftmikroskopie erfasst. Auf diese Weise können auch Informationen über die Stabilität der Schicht und die Oberflächenrauhigkeit gesammelt werden. Mit Kontaktwinkelmessungen (contact angle, CA) wird nicht nur die Benetzbarkeit, sondern auch die Kontaktwinkelhysterese durch Auf- und Abpumpen des Tropfenvolumens bestimmt. Durch Messung des CA von verschiedenen Flüssigkeiten und deren Vergleich werden die freie Oberflächenenergie (surface free energy, SFE) und ihre polaren und dispersiven Bestandteile bestimmt. Die Veränderungen der Barriereeigenschaften werden durch Wasserdampftransmissionstests (water vapor transmission rate, WVTR) überprüft. Die chemische Analyse der Oberfläche erfolgt zum einen durch Fourier-Transformations-Infrarotspektroskopie mit spiegelnder Reflexion und zum anderen durch Synchrotron unterstützte Techniken wie der Nahkanten-Röntgenabsorptionsfeinstruktur und der Röntgen-Photoelektronenspektroskopie. Bei der Analyse der Oberflächen nach der O₂ Behandlung, von der zunächst angenommen wurde, dass sie nur der Reinigung und Aktivierung der Oberfläche für die a-C:H Beschichtung dient, wurde festgestellt, dass die Veränderungen drastischer sind als ursprünglich angenommen. Wird PLA zum Beispiel bei 0° für 10 Minuten behandelt, steigt die Rauheit um das Fünffache. Mit zunehmendem Winkel verringert sich diese wieder, bis sie bei 180° wieder dem Ausgangswert entspricht. Bei PHB hingegen wird durchgehend ein ähnlicher Wert gemessen. Für beide Polymere lässt sich zeigen, dass der polare Anteil der SFE zunimmt. In der WVTR ist bei PLA eine Abnahme der Permeabilität und bei PHB ein Anstieg des Ausgangswertes zu beobachten. Die chemische Oberflächenanalyse zeigt, dass die O₂ Behandlung kaum Auswirkungen auf die Oberflächenbindungen hat. Insgesamt kann in dieser Arbeit gezeigt werden, dass sich die O₂ Behandlung auf die Eigenschaften der Oberfläche auswirkt und nicht ausschließlich als Reinigungs- und Aktivierungsprozess betrachtet werden kann. Bei direkter a-C:H Beschichtung (bei 0°) ist sowohl bei PLA als auch bei PHB ein Schichtversagen bei 10.0 Minuten aufgrund von Eigenspannung zu beobachten. Dies ist bei PHB in geringerem Maße auch bei 30° zu erkennen. Die Durchlässigkeit der Polymere wird bei einer fünf minütigen Beschichtung um 47% reduziert und auch die Schicht bei 10.0 Minuten führt diesen Effekt trotz auftretender Risse weiter. Die Aufbringung von a-C:H Schichten zeigt für beide Polymertypen bei direkter Beschichtung eine Dominanz von sp³-Bindungen. Mit zunehmendem Winkel nimmt diese ab und bei indirekten Beschichtungen werden sp²-Bindungen dominierend. Dieses Ergebnis ist für alle Schichtdicken ähnlich, nur der Winkel, bei dem der Wechsel der dominanten Bindung stattfindet, ist unterschiedlich. Es wird gezeigt, dass es möglich ist, die Oberflächeneigenschaften durch eine winkelabhängige Beschichtung zu steuern und somit das Verhältnis sp²/sp³ zu kontrollieren.
Reducing gender bias in STEM is key to generating more equality and contributing to a more balanced workforce in this field. Spatial ability and its components are cognitive processes crucial to success in STEM education and careers. Significant gender differences have consistently been found in mental rotation (MR), the ability to mentally transform two- and three-dimensional objects. The aim of this pilot study is to examine factors in psychological assessment which may contribute to gender differences in MR performance. Moreover, findings will inform the development of the new approaches to assessment using computer adaptive testing (CAT). (1) Background: The study examines the impact of emotional regulation on MR performance in primary school children whose mean age was 9.28 years old. (2) Methods: Skin conductance was measured to assess the impact of emotional reactivity (ER) on performance during an MR task. (3) Results: Patterns of ER influence response time (RT) on specific items in the task. (4) Conclusions: Identifying the effects of emotional arousal and issues of test construction such as stereotyped stimuli and item difficulty in tests of spatial ability warrants ongoing investigation. It is vital to ensure that these factors do not compromise the accurate measurement of performance and inadvertently contribute to the gender gap in STEM.
The title compound, [Fe(C5H5)(C21H24NO2)], which is produced by the oxidation of 1-(4-tert-butylphenyl)-2-ethyl-3-ferrocenylpyrrole, crystallizes as a racemic mixture in the centrosymmetric space group P21/n. The central heterocyclic pyrrole ring system subtends dihedral angles of 13.7 (2)° with respect to the attached cyclopentadienyl ring and of 43.6 (7)° with the major component of the disordered phenyl group bound to the N atom. The 4-tert-butylphenyl group, as well as the non-substituted Cp ring are disordered with s.o.f. values of 0.589 (16) and 0.411 (16), respectively. In the crystal, molecules with the same absolute configuration are linked into infinite chains along the b-axis direction by O—H···O hydrogen bonds between the hydroxy substituent and the carbonyl O atom of the adjacent molecule.
Herein, the particle size distributions (PSDs) and shape analysis of in vivo bioproduced particles from aqueous Au3+ and Eu3+ solutions by the cyanobacterium Anabaena sp. are examined in detail at the nanoscale. Generally, biosynthesis is affected by numerous parameters. Therefore, it is challenging to find the key set points for generating tailored nanoparticles (NPs). PSDs and shape analysis of the Au and Eu-NPs were performed with ImageJ using high-resolution transmission electron microscopy (HR-TEM) images. As the HR-TEM image analysis reflects only a fraction of the detected NPs within the cells, additional PSDs of the complete cell were performed to determine the NP count and to evaluate the different accuracies. Furthermore, local PSDs were carried out at five randomly selected locations within a single cell to identify local hotspots or agglomerations. The PSDs show that particle size depends mainly on contact time, while the particle shape is hardly affected. The particles formed are distributed quite evenly within the cells. HR-PSDs for Au-NPs show an average equivalent circular diameter (ECD) of 8.4 nm (24 h) and 7.2 nm (51 h). In contrast, Eu-NPs preferably exhibit an average ECD of 10.6 nm (10 h) and 12.3 nm (244 h). Au-NPs are classified predominantly as “very round” with an average reciprocal aspect ratio (RAR) of ~0.9 and a Feret major axis ratio (FMR) of ~1.17. Eu-NPs mainly belong to the “rounded” class with a smaller RAR of ~0.6 and a FMR of ~1.3. These results show that an increase in contact time is not accompanied by an average particle growth for Au-NPs, but by a doubling of the particle number. Anabaena sp. is capable of biosorbing and bioreducing dissolved Au3+ and Eu3+ ions from aqueous solutions, generating nano-sized Au and Eu particles, respectively. Therefore, it is a low-cost, non-toxic and effective candidate for a rapid recovery of these sought-after metals via the bioproduction of NPs with defined sizes and shapes, providing a high potential for scale-up.
How to begin? This short question addresses a problem that is anything but simple, especially when regarding something as sophisticated and multilayered as musical theatre. However, scholars of this vast research area have mostly neglected this question so far. This study analyses and compares the initial sections of late Victorian popular musical theatre and is therefore a contribution to several fields of research: the analysis of initial sections of musical theatre in general, the analysis of the music of popular musical theatre in particular, and therefore operetta studies. The 1890s are especially interesting times for popular musical theatre in London: The premiered works include the last collaborations of Gilbert and Sullivan as well as offshoots of Savoy opera; but the so-called ‘naughty nineties’ also saw the emergence of a new genre, musical comedy, which captured the late Victorian zeitgeist like no other. This new form of theatrical entertainment was carefully and consciously constructed and promoted as modern and fashionable, walking a fine line between respectability and mildly risqué excitement.
Because a deep understanding of the developments and new tendencies concerning popular musical theatre in the 1890s is crucial in order to interpret differences as well as similarities, the analyses of the opening numbers are preceded by a detailed discussion of the relevant genres: comic opera, musical comedy, musical play and operetta. Since the producers of the analysed works wanted to distance themselves from former and supposedly old-fashioned traditions, this book also considers influences from their British predecessors, but also from Viennese operetta and French opéra bouffe.
Coat color and pattern are a distinguished feature in mammalian carnivores, shaped by climatic cycles and habitat type. It can be expressed in various ways, such as gradients, polymorphisms, and rare color variants. Although natural selection explains much of the phenotypic variation found in the wild, genetic drift and heterozygote deficiency, as prominent in small and fragmented populations, may also affect phenotypic variability through the fixation of recessive alleles. The aim of this study was to test whether rare color variants in the wild could relate to a deficiency of heterozygotes, resulting from habitat fragmentation and small population size. We present an overview of all rare color variants in the order Carnivora, and compiled demographic and genetic data of the populations where they did and did not occur, to test for significant correlations. We also tested how phylogeny and body weight influenced the presence of color variants with phylogenetic generalized linear mixed models (PGLMMs). We found 40 color-variable species and 59 rare color variants. In 17 variable phenotypic populations for which genetic diversity was available, the average AR was 4.18, HO = 0.59, and HE= 0.66, and FIS= 0.086. We found that variable populations displayed a significant reduction in heterozygosity and allelic richness compared to non-variable populations across species. We also found a significant negative correlation between population size and inbreeding coefficients. Therefore, it is possible that small effective size had phenotypic consequences on the extant populations. The high frequency of the rare color variants (averaging 20%) also implies that genetic drift is locally overruling natural selection in small effective populations. As such, rare color variants could be added to the list of phenotypic consequences of inbreeding in the wild.
The production of isolated metallic nanoparticles with multifunctionalized properties, such as size and shape, is crucial for biomedical, photocatalytic, and energy storage or remediation applications. This study investigates the initial particle formations of gold nanoparticles (AuNPs) bioproduced in the cyanobacteria Anabaena sp. using high-resolution transmission electron microscopy images for digital image analysis. The developed method enabled the discovery of cerium nanoparticles (CeNPs), which were biosynthesized in the cyanobacteria Calothrix desertica. The particle size distributions for AuNPs and CeNPs were analyzed. After 10 h, the average equivalent circular diameter for AuNPs was 4.8 nm, while for CeNPs, it was approximately 5.2 nm after 25 h. The initial shape of AuNPs was sub-round to round, while the shape of CeNPs was more roundish due to their amorphous structure and formation restricted to heterocysts. The local PSDs indicate that the maturation of AuNPs begins in the middle of vegetative cells and near the cell membrane, compared to the other regions of the cell.
X-ray computed tomography (XRT) is a three-dimensional (3D), non-destructive, and reproducible investigation method capable of visualizing and examining internal and external structures of components independent of the material and geometry. In this work, XRT with its unique abilities complements conventionally utilized examination methods for the investigation of microstructure weakening induced by hydrogen corrosion and furthermore provides a new approach to corrosion research. The motivation for this is the current inevitable transformation to hydrogen-based steel production. Refractories of the system Al2O3-SiO2 are significant as lining materials. Two exemplary material types A and B, which differ mainly in their Al2O3:SiO2 ratio, are examined here using XRT. Identical samples of the two materials are measured, analyzed, and then compared before and after hydrogen attack. In this context, hydrogen corrosion-induced porosity and its spatial distribution and morphology are investigated. The results show that sample B has an higher resistance to hydrogen-induced attack than sample A. Furthermore, the 3D-representation revealed a differential porosity increase within the microstructure.
This thesis explores and examines the effectiveness and efficacy of traditional machine learning (ML), advanced neural networks (NN) and state-of-the-art deep learning (DL) models for identifying mental distress indicators from the social media discourses based on Reddit and Twitter as they are immensely used by teenagers. Different NLP vectorization techniques like TF-IDF, Word2Vec, GloVe, and BERT embeddings are employed with ML models such as Decision Tree (DT), Random Forest (RF), Logistic Regression (LR) and Support Vector Machine (SVM) followed by NN models such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) to methodically analyse their impact as feature representation of models. DL models such as BERT, DistilBERT, MentalRoBERTa and MentalBERT are end-to-end fine tuned for classification task. This thesis also compares different text preprocessing techniques such as tokenization, stopword removal and lemmatization to assess their impact on model performance. Systematic experiments with different configuration of vectorization and preprocessing techniques in accordance with different model types and categories have been implemented to find the most effective configurations and to gauge the strengths, limitations, and capability to detect and interpret the mental distress indicators from the text. The results analysis reveals that MentalBERT DL model significantly outperformed all other model types and categories due to its specific pretraining on mental data as well as rigorous end-to-end fine tuning gave it an edge for detecting nuanced linguistic mental distress indicators from the complex contextual textual corpus. This insights from the results acknowledges the ML and NLP technologies high potential for developing complex AI systems for its intervention in the domain of mental health analysis. This thesis lays the foundation and directs the future work demonstrating the need for collaborative approach of different domain experts as well as to explore next generational large language models to develop robust and clinically approved mental health AI systems.
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.
Empirische Studien in der Softwaretechnik verwenden Software Repositories als Datenquellen, um die Softwareentwicklung zu verstehen. Repository-Daten werden entweder verwendet, um Fragen zu beantworten, die die Entscheidungsfindung in der Softwareentwicklung leiten, oder um Werkzeuge bereitzustellen, die bei praktischen Aspekten der Entwicklung helfen. Studien werden in die Bereiche Empirical Software Engineering (ESE) und Mining Software Repositories (MSR) eingeordnet. Häufig konzentrieren sich Studien, die mit Repository-Daten arbeiten, auf deren Ergebnisse. Ergebnisse sind aus den Daten abgeleitete Aussagen oder Werkzeuge, die bei der Softwareentwicklung helfen. Diese Dissertation konzentriert sich hingegen auf die Methoden und High-Order-Methoden, die verwendet werden, um solche Ergebnisse zu erzielen. Insbesondere konzentrieren wir uns auf inkrementelle Methoden, um die Verarbeitung von Repositories zu skalieren, auf deklarative Methoden, um eine heterogene Analyse durchzuführen, und auf High-Order-Methoden, die verwendet werden, um Bedrohungen für Methoden, die auf Repositories arbeiten, zu operationalisieren. Wir fassen dies als technische und methodische Verbesserungen zusammen um zukünftige empirische Ergebnisse effektiver zu produzieren. Wir tragen die folgenden Verbesserungen bei. Wir schlagen eine Methode vor, um die Skalierbarkeit von Funktionen, welche über Repositories mit hoher Revisionszahl abstrahieren, auf theoretisch fundierte Weise zu verbessern. Wir nutzen Erkenntnisse aus abstrakter Algebra und Programminkrementalisierung, um eine Kernschnittstelle von Funktionen höherer Ordnung zu definieren, die skalierbare statische Abstraktionen eines Repositorys mit vielen Revisionen berechnen. Wir bewerten die Skalierbarkeit unserer Methode durch Benchmarks, indem wir einen Prototyp mit MSR/ESE Wettbewerbern vergleichen. Wir schlagen eine Methode vor, um die Definition von Funktionen zu verbessern, die über ein Repository mit einem heterogenen Technologie-Stack abstrahieren, indem Konzepte aus der deklarativen Logikprogrammierung verwendet werden, und mit Ideen zur Megamodellierung und linguistischen Architektur kombiniert werden. Wir reproduzieren bestehende Ideen zur deklarativen Logikprogrammierung mit Datalog-nahen Sprachen, die aus der Architekturwiederherstellung, der Quellcodeabfrage und der statischen Programmanalyse stammen, und übertragen diese aus der Analyse eines homogenen auf einen heterogenen Technologie-Stack. Wir liefern einen Proof-of-Concept einer solchen Methode in einer Fallstudie. Wir schlagen eine High-Order-Methode vor, um die Disambiguierung von Bedrohungen für MSR/ESE Methoden zu verbessern. Wir konzentrieren uns auf eine bessere Disambiguierung von Bedrohungen durch Simulationen, indem wir die Argumentation über Bedrohungen operationalisieren und die Auswirkungen auf eine gültige Datenanalysemethodik explizit machen. Wir ermutigen Forschende, „gefälschte“ Simulationen ihrer MSR/ESE-Szenarien zu erstellen, um relevante Erkenntnisse über alternative plausible Ergebnisse, negative Ergebnisse, potenzielle Bedrohungen und die verwendeten Datenanalysemethoden zu operationalisieren. Wir beweisen, dass eine solche Art des simulationsbasierten Testens zur Disambiguierung von Bedrohungen in der veröffentlichten MSR/ESE-Forschung beiträgt.
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.
Künstliche neuronale Netze sind ein beliebtes Forschungsgebiet der künst-
lichen Intelligenz. Die zunehmende Größe und Komplexität der riesigen
Modelle bringt gewisse Probleme mit sich. Die mangelnde Transparenz
der inneren Abläufe eines neuronalen Netzes macht es schwierig, effiziente
Architekturen für verschiedene Aufgaben auszuwählen. Es erweist sich als
herausfordernd, diese Probleme zu lösen. Mit einem Mangel an aufschluss-
reichen Darstellungen neuronaler Netze verfestigt sich dieser Zustand. Vor
dem Hintergrund dieser Schwierigkeiten wird eine neuartige Visualisie-
rungstechnik in 3D vorgestellt. Eigenschaften für trainierte neuronale Net-
ze werden unter Verwendung etablierter Methoden aus dem Bereich der
Optimierung neuronaler Netze berechnet. Die Batch-Normalisierung wird
mit Fine-tuning und Feature Extraction verwendet, um den Einfluss der Be-
standteile eines neuronalen Netzes abzuschätzen. Eine Kombination dieser
Einflussgrößen mit verschiedenen Methoden wie Edge-bundling, Raytra-
cing, 3D-Impostor und einer speziellen Transparenztechnik führt zu einem
3D-Modell, das ein neuronales Netz darstellt. Die Validität der ermittelten
Einflusswerte wird demonstriert und das Potential der entwickelten Visua-
lisierung untersucht.
Leichte Sprache (LS) ist eine vereinfachte Varietät des Deutschen in der barrierefreie Texte für ein breites Spektrum von Menschen, einschließlich gering literalisierten Personen mit Lernschwierigkeiten, geistigen oder entwicklungsbedingten Behinderungen (IDD) und/oder komplexen Kommunikationsbedürfnissen (CCN), bereitgestellt werden. LS-Autor*innen sind i.d.R. der deutschen Standardsprache mächtig und gehören nicht der genannten Personengruppe an. Unser Ziel ist es, diese zu befähigen, selbst am schriftlichen Diskurs teilzunehmen. Hierfür bedarf es eines speziellen Schreibsystems, dessen linguistische Unterstützung und softwareergonomische Gestaltung den spezifischen Bedürfnissen der Zielgruppe gerecht wird. EasyTalk ist ein System basierend auf computerlinguistischer Verarbeitung natürlicher Sprache (NLP) für assistives Schreiben in einer erweiterten Variante von LS (ELS). Es stellt den Nutzenden ein personalisierbares Vokabular mit individualisierbaren Kommunikationssymbolen zur Verfügung und unterstützt sie entsprechend ihres persönlichen Fähigkeitslevels durch interaktive Benutzerführung beim Schreiben. Intuitive Formulierungen für linguistische Entscheidungen minimieren das erforderliche grammatikalische Wissen für die Erstellung korrekter und kohärenter komplexer Inhalte. Einfache Dialoge kommunizieren mit einem natürlichsprachlichen Paraphrasengenerator, der kontextsensitiv Vorschläge für Satzkomponenten und korrekt flektierte Wortformen bereitstellt. Außerdem regt EasyTalk die Nutzer*innen an, Textelemente hinzuzufügen, welche die Verständlichkeit des Textes für dessen Leserschaft fördern (z.B. Zeit- und Ortsangaben) und die Textkohärenz verbessern (z.B. explizite Diskurskonnektoren). Um das System auf die Bedürfnisse der Zielgruppe zuzuschneiden, folgte die Entwicklung von EasyTalk den Grundsätzen der menschzentrierten Gestaltung (UCD). Entsprechend wurde das System in iterativen Entwicklungszyklen ausgereift, kombiniert mit gezielten Evaluierungen bestimmter Aspekte durch Gruppen von Expert*innen aus den Bereichen CCN, LS und IT sowie L2-Lernende der deutschen Sprache. Eine Fallstudie, in welcher Mitglieder der Zielgruppe das freie Schreiben mit dem System testeten, bestätigte, dass Erwachsene mit geringen Lese-, Schreib- und Computerfähigkeiten mit IDD und/oder CCN mit EasyTalk eigene persönliche Texte in ELS verfassen können. Das positive Feedback aller Tests inspiriert Langzeitstudien mit EasyTalk und die Weiterentwicklung des prototypischen Systems, wie z.B. die Implementierung einer s.g. Schreibwerkstatt.
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.
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.
Durch die zunehmende Wichtigkeit und Dringlichkeit des Klimawandels sind Unternehmen aufgefordert, einen Beitrag zu nachhaltiger Entwicklung zu leisten, insbesondere durch die jüngeren Generationen. Bisherige Beiträge von Unternehmen werden jedoch als unzureichend kritisiert, was insbesondere am mangelnden Engagement der Mitarbeiterinnen und Mitarbeiter für Nachhaltigkeit in Unternehmen liegen könnte. In diesem Zusammenhang wurde in den letzten Jahren Gamification als ein vielversprechendes, innovatives Tool um nachhaltige Verhaltensweisen der Mitarbeiterinnen und Mitarbeiter am Arbeitsplatz zu motivieren, vorgeschlagen und zunehmend erforscht. Es gibt jedoch nur wenige Studien und anwendbare Gamification-Lösungen, die mehr als ein spezifisches Nachhaltigkeitsthema behandeln und somit eine ganzheitliche Perspektive auf nachhaltige Verhaltensweisen am Arbeitsplatz einnehmen. Darüber hinaus mangelt es bisheriger Forschung an einem umfassenden Verständnis dafür, wie verschiedene Gamification-Elemente spezifische psychologische Effekte hervorrufen, wie sich diese in Verhaltensänderungen manifestieren und wie diese wiederum kumulativ in messbaren Unternehmensergebnissen resultieren. Der Weg von Gamification als ”Input” zu unternehmerischer Nachhaltigkeit als ”Output” ist also bislang unerforscht.
Diese Dissertation schließt diese Lücke, indem eine ganzheitliche gamifizierte Intervention konzipiert, gestaltet und evaluiert wird, die Mitarbeiterinnen und Mitarbeiter bei verschiedenen nachhaltigen Verhaltensweisen in ihren täglichen Aktivitäten unterstützt. Das Projekt verwendet einen designwissenschaftlichen Forschungsansatz, der die Mitarbeiterinnen und Mitarbeiter eng in die schrittweise Entwicklung der Lösung einbezieht. Als Teil des iterativen Designprozesses werden in dieser Dissertation sechs Studien vorgestellt, um das theoretische Verständnis von Gamification für nachhaltige Verhaltensweisen von Mitarbeiterinnen und Mitarbeitern zu erweitern. Zunächst wird ein umfassender Überblick über die bestehende Forschung zu Gamification für nachhaltiges Mitarbeiterverhalten gegeben, wobei Gamification-Designs und Ergebnisse früherer Studien analysiert und eine Agenda für die weitere Forschung aufgezeigt werden (Studie 1). Danach werden theoretische Grundlagen der Forschung zu Gamification, Serious Games und Game-based Learning (Studie 2) und empirische Gestaltungsprinzipien
für Gamification und persuasive Systeme (Studie 3) als Basis für die erfolgreiche Gestaltung gamifizierter Anwendungen systematisch untersucht. Anschließend werden in empirischen Studien Motivationen der Mitarbeiterinnen und Mitarbeiter für nachhaltiges Verhalten erforscht und ihre Erwartungen an Gestaltungsmerkmale beleuchtet (Studie 4) sowie kontextuelle Herausforderungen und Gestaltungsdilemmata bei der Implementierung von Gamification in einem organisatorischen Kontext aufgezeigt (Studie 5). Schließlich wird in einer quantitativen Feldstudie (Studie 6) untersucht, wie verschiedene Gamification-Designs nachhaltiges Mitarbeiterverhalten und unternehmerische Nachhaltigkeitskennzahlen in Organisationen beeinflussen. Basierend auf den Ergebnissen wird in dieser Dissertation ein umfassendes Framework für Gamification für nachhaltiges Mitarbeiterverhalten präsentiert, welches Design-, individuelle Verhaltens- und Unternehmensperspektiven einbezieht. Schließlich werden darauf aufbauend praktische Empfehlungen für die Gestaltung von Gamification zur Förderung nachhaltigen Mitarbeiterverhaltens am Arbeitsplatz präsentiert.
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.
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.
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.
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.
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.
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.
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.
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.
Die Aufmerksamkeit politischer Entscheidungsträger weltweit richtet sich in den letzten 10 Jahren verstärkt auf die Kreativwirtschaft als signifikanter Wachstums- und Beschäftigungsmotor in Städten. Die Literatur zeigt jedoch, dass Kreativschaffende zu den gefährdetsten Arbeitskräften in der heutigen Wirtschaft gehören. Aufgrund des enorm deregulierten und stark individualisierten Umfelds werden Misserfolg oder Erfolg eher individuellen Fähigkeiten und Engagement zugeschrieben und strukturelle oder kollektive Aspekte vernachlässigt. Diese Arbeit widmet sich zeitlichen, räumlichen und sozialen Aspekten digitaler behavioraler Daten, um zu zeigen, dass es tatsächlich strukturelle und historische Faktoren gibt, die sich auf die Karrieren von Individuen und Gruppen auswirken. Zu diesem Zweck bietet die Arbeit einen computergestützten, sozialwissenschaftlichen Forschungsrahmen, der das theoretische und empirisches Wissen aus jahrelanger Forschung zu Ungleichheit mit computergestützten Methoden zum Umgang mit komplexen und umfangreichen digitalen Daten verbindet. Die Arbeit beginnt mit der Darlegung einer neuartigen Methode zur Geschlechtererkennung, welche sich Image Search und Gesichtserkennungsmethoden bedient. Die Analyse der kollaborativen Verhaltensweisen sowie der Zitationsnetzwerke männlicher und weiblicher Computerwissenschaftler*innen verdeutlicht einige der historischen Bias und Nachteile, welchen Frauen in ihren wissenschaftlichen Karrieren begegnen. Zur weiterfuhrenden Elaboration der zeitlichen Aspekte von Ungleichheit, wird der Anteil vertikaler und horizontaler Ungleichheit in unterschiedlichen Kohorten von Wissenschaftler*innen untersucht, die ihre Karriere zu unterschiedlichen Zeitpunkten begonnen haben. Im Weiteren werden einige der zugrunde liegenden Mechanismen und Prozesse von Ungleichheit in kreativen Berufen analysiert, wie der Matthew-Effekt und das Hipster-Paradoxon. Schließlich zeigt diese Arbeit auf, dass Online-Plattformen wie Wikipedia bestehenden Bias reflektieren sowie verstärken können.
Predictive Process Monitoring setzt sich als Hilfsmittel zur Unterstützung der betrieblichen Abläufe in Unternehmen immer mehr durch Die meisten heute verfüg-baren Softwareanwendungen erfordern jedoch ein umfangreiches technisches Know-how des Betreibers und sind daher für die meisten realen Szenarien nicht geeignet. Daher wird in dieser Arbeit eine prototypische Implementierung eines Predictive Process Monitoring Dashboards in Form einer Webanwendung vorgestellt. Das System basiert auf dem von Bartmann et al. (2021) vorgestellten PPM-Camunda-Plugin und ermöglicht es dem Benutzer, auf einfache Weise Metriken, Visualisierungen zur Darstellung dieser Metriken und Dashboards, in denen die Visualisierungen angeordnet werden können, zu erstellen. Ein Usability-Test mit Testnutzern mit unterschiedlichen Computerkenntnissen wird durchgeführt, um die Benutzerfreundlichkeit der Anwendung zu bestätigen.
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.
In den letzten Jahrzehnten wurde deutlich, dass die Welt mit einer beispiellosen, vom Menschen verursachten Biodiversitätskrise konfrontiert ist. Eine der am stärksten bedrohten Artengruppen stellen dabei die Amphibien dar, so gelten laut IUCN 41% der Amphibienarten als gefährdet. Jedoch können selbst bei Arten die als "least concern" klassifiziert sind Populationsrückgänge auf lokaler Ebene beobachtet werden. Mit einer veränderten Landnutzung und dem Einsatz von Pestiziden sind zwei der Hauptursachen für diese Gefährdung direkt mit intensiver Landwirtschaft verbunden. Daher ist das Wissen um die Situation von Amphibien in der Agrarlandschaft von entscheidender Bedeutung für Schutzmaßnahmen. In der vorliegenden Arbeit wurden Amphibienpopulationen in der durch Weinbau geprägten Gegend um Landau in der Pfalz (Deutschland) im Hinblick auf Lebensraumnutzung, Pestizidexposition, biometrische Merkmale sowie der Alters- und genetischer Populationsstruktur untersucht. Da Agrarflächen oft zur Fragmentierung von Landschaften führen, ging ich der Frage nach ob dies auch auf Weinberge zutrifft und ob eingesetzte Pestizide zur Fragmentierung beitragen, ob also eine chemische Landschaftsfragmentierung vorliegt. Durch die Telemetrierung von Erdkröten (Bufo bufo) konnte ich zeigen, dass diese Art direkt in Weinbergen gefunden werden kann, diese aber generell eher meidet. Die Analyse der genetischen Struktur von Grasfröschen (Rana temporaria) ergab, dass Weinberge als Barriere für Amphibien anzusehen sind. Um herauszufinden, ob Pestizide zu der daraus resultierenden Landschaftsfragmentierung beitragen, führte ich einen Wahlversuch im Labor durch, bei dem ich ein Vermeidungsverhalten gegenüber kontaminierten Böden fand, was zu einer chemischen Landschaftsfragmentierung führen könnte. Durch die Kombination von Telemetriedaten mit Daten über Pestizidanwendungen von lokalen Winzern konnte ich zeigen, dass ein großer Teil der Erdkröten mit Pestiziden in Kontakt kommt. Außerdem konnte gezeigt werden, dass sich die Agrarlandschaft und hier wahrscheinlich Pestizide negativ auf die Fortpflanzungsfähigkeit von Erdkröten auswirkt. Bei der Untersuchung von Fadenmolchen (Lissotriton helveticus) stellte ich fest, dass adulte Molche aus Gewässern in der Agrarlandschaft kleiner sind als Individuen aus Gewässern im Wald. Da kein Unterschied in der Altersstruktur festgestellt werden konnte, könnten diese Größenunterschiede auf suboptimale Bedingungen für Larven und/oder Jungtiere hindeuten, wenngleich Gewässer in der Agrarlandschaft geeignete Lebensräume für adulte Teichmolche sein könnten. Ich komme zu dem Schluss, dass die beste Maßnahme zum Schutz von Amphibien in der Agrarlandschaft eine heterogene Kulturlandschaft mit einem Mosaik aus verschiedenen Lebensräumen wäre, die ohne oder zumindest mit weniger Pestiziden auskommt. Grüne Korridore zwischen Populationen und Teillebensräumen würden es wandernden Individuen ermöglichen, landwirtschaftliche und damit pestizidbelastete Flächen zu vermeiden. Dies würde das Risiko der Pestizidexposition von Amphibien verringern und gleichzeitig die Fragmentierung der Landschaft und damit die Isolation von Populationen verhindern.
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.
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.
Binnengewässer spielen eine aktive Rolle im globalen Kohlenstoffkreislauf. Sie nehmen Kohlenstoff von stromaufwärts gelegenen Landmassen auf und transportieren ihn stromabwärts, bis er schließlich den Ozean erreicht. Auf diesem Weg sind vielfältige Prozesse zu beobachten, die zu einer (dauerhaften) Rückhaltung des Kohlenstoffs durch Einlagerung in Sedimenten sowie zu direkter Emission in die Atmosphäre führen. Es ist dringend notwendig diese Kohlenstoffflüsse und ihre anthropogene Veränderung zu quantifizieren. In diesem Zusammenhang muss die Aufmerksamkeit auf ein weit verbreitetes Merkmal von Gewässern gerichtet werden: ihre teilweise Austrocknung. Dies führt dazu, dass ehemals überschwemmte Sedimente in direkten Kontakt mit der Atmosphäre gelangen, genannt „dry inland waters“. Ein Merkmal der „dry inland waters“ sind überproportional hohe Kohlendioxid (CO2)-Emissionen. Diese Erkenntnis beruhte jedoch bisher auf lokalen Fallstudien, und es fehlt an Wissen über die globale Verbreitung und die grundlegenden Mechanismen dieser Emissionen. Vor diesem Hintergrund zielt diese Arbeit darauf ab, das Ausmaß und die Mechanismen der Kohlenstoffemissionen der „dry inland waters“ auf globaler und lokaler Ebene besser zu verstehen und die Auswirkungen von „dry inland waters“ auf den globalen Kohlenstoffkreislauf zu bewerten. Die spezifischen Forschungsfragen dieser Arbeit lauteten: (1) Wie fügen sich gasförmige Kohlenstoffemissionen von „dry inland waters“ in den globalen Kohlenstoffkreislauf und in die globalen Treibhausgasbudgets ein? (2) Welche Auswirkungen haben saisonale und langfristige Austrocknung auf den Kohlenstoffkreislauf von Gewässern? Diese Arbeit hat gezeigt, dass „dry inland waters“im globalen Maßstab unverhältnismäßig große Mengen an CO2 emittieren und dass diese Emissionen in allen Ökosystemen vergleichbaren Mechanismen folgen. Die Quantifizierung der globalen Wasserstandsschwankungen in Stauseen und die globale Berechnung der Kohlenstoffflüsse legen nahe, dass Stauseen mehr Kohlenstoff freisetzen als sie in den Sedimenten einlagern, was das derzeitige Verständnis von Stauseen als Nettokohlenstoffsenken in Frage stellt. Auf lokaler Ebene hat diese Arbeit gezeigt, dass sowohl die heterogenen Emissionsmuster verschiedener typischer Uferbereiche als auch die saisonalen Schwankungen der Kohlenstoffemissionen aus der „drawdown area“ berücksichtigt werden müssen. Darüber hinaus hat diese Arbeit gezeigt, dass die Remobilisierung von Kohlenstoff aus den Sedimenten bei dauerhafter Austrocknung von Gewässern die beobachteten Emissionsraten erklären kann, was die Hypothese einer positiven Rückkopplung zwischen Klimawandel und der Austrocknung von Gewässern unterstützt. Insgesamt unterstreicht die vorliegende Arbeit die Bedeutung der Emissionen aus trockenen Gewässerbereichen für den globalen Kohlenstoffkreislauf von Gewässern.
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.
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
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.
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.
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.
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.
Objectives: Crayfish plague disease, caused by the oomycete pathogen Aphanomyces astaci represents one of the greatest risks for the biodiversity of the freshwater crayfish. This data article covers the de novo transcriptome assembly and annotation data of the noble crayfish and the marbled crayfish challenged with Ap. astaci. Following the controlled infection experiment (Francesconi et al. in Front Ecol Evol, 2021, https://doi.org/10.3389/fevo.2021.647037), we conducted a differential gene expression analysis described in (Boštjančić et al. in BMC Genom, 2022, https://doi.org/10.1186/s12864-022-08571-z) Data description: In total, 25 noble crayfish and 30 marbled crayfish were selected. Hepatopancreas tissue was isolated, followed by RNA sequencing using the Illumina NovaSeq 6000 platform. Raw data was checked for quality with FastQC, adapter and quality trimming were conducted using Trimmomatic followed by de novo assembly with Trinity. Assembly quality was assessed with BUSCO, at 93.30% and 93.98% completeness for the noble crayfish and the marbled crayfish, respectively. Transcripts were annotated using the Dammit! pipeline and assigned to KEGG pathways. Respective transcriptome and raw datasets may be reused as the reference transcriptome assemblies for future expression studies.