Filtern
Erscheinungsjahr
Dokumenttyp
- Dissertation (249)
- Masterarbeit (91)
- Ausgabe (Heft) zu einer Zeitschrift (84)
- Bachelorarbeit (45)
- Diplomarbeit (27)
- Wissenschaftlicher Artikel (22)
- Studienarbeit (11)
- Konferenzveröffentlichung (10)
- Habilitation (4)
- Sonstiges (2)
Sprache
- Englisch (547) (entfernen)
Schlagworte
- Pestizid (8)
- Pflanzenschutzmittel (6)
- Software Engineering (6)
- Internet of Things (5)
- Biodiversität (4)
- Bluetooth (4)
- Bodenchemie (4)
- Landwirtschaft (4)
- Semantic Web (4)
- ecotoxicology (4)
Institut
- Fachbereich 4 (116)
- Institut für Informatik (83)
- Fachbereich 7 (78)
- Institut für Wirtschafts- und Verwaltungsinformatik (53)
- Institut für Computervisualistik (52)
- Institute for Web Science and Technologies (50)
- Institut für Management (30)
- Institut für Integrierte Naturwissenschaften, Abt. Biologie (24)
- Institut für Umweltwissenschaften (23)
- Fachbereich 8 (20)
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.
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 the last years, the public interest in epidemiology and mathematical modeling of disease spread has increased - mainly caused by the COVID-19 pandemic, which has emphasized the urgent need for accurate and timely modelling of disease transmission. However, even prior to that, mathematical modelling has been used for describing the dynamics and spread of infectious diseases, which is vital for developing effective interventions and controls, e.g., for vaccination campaigns and social restrictions like lockdowns. The forecasts and evaluations provided by these models influence political actions and shape the measures implemented to contain the virus.
This research contributes to the understanding and control of disease spread, specifically for Dengue fever and COVID-19, making use of mathematical models and various data analysis techniques. The mathematical foundations of epidemiological modelling, as well as several concepts for spatio-temporal diffusion like ordinary differential equation (ODE) models, are presented, as well as an originally human-vector model for Dengue fever, and the standard (SEIR)-model (with the potential inclusion of an equation for deceased persons), which are suited for the description of COVID-19. Additionally, multi-compartment models, fractional diffusion models, partial differential equations (PDE) models, and integro-differential models are used to describe spatial propagation of the diseases.
We will make use of different optimization techniques to adapt the models to medical data and estimate the relevant parameters or finding optimal control techniques for containing diseases using both Metropolis and Lagrangian methods. Reasonable estimates for the unknown parameters are found, especially in initial stages of pandemics, when little to no information is available and the majority of the population has not got in contact with the disease. The longer a disease is present, the more complex the modelling gets and more things (vaccination, different types, etc.) appear and reduce the estimation and prediction quality of the mathematical models.
While it is possible to create highly complex models with numerous equations and parameters, such an approach presents several challenges, including difficulties in comparing and evaluating data, increased risk of overfitting, and reduced generalizability. Therefore, we will also consider criteria for model selection based on fit and complexity as well as the sensitivity of the model with respect to specific parameters. This also gives valuable information on which political interventions should be more emphasized for possible variations of parameter values.
Furthermore, the presented models, particularly the optimization using the Metropolis algorithm for parameter estimation, are compared with other established methods. The quality of model calculation, as well as computational effort and applicability, play a role in this comparison. Additionally, the spatial integro-differential model is compared with an established agent-based model. Since the macroscopic results align very well, the computationally faster integro-differential model can now be used as a proxy for the slower and non-traditionally optimizable agent-based model, e.g., in order to find an apt control strategy.
In a world where language defines the boundaries of one's understanding, the words of Austrian philosopher Ludwig Wittgenstein resonate profoundly. Wittgenstein's assertion that "Die Grenzen meine Sprache bedeuten die Grenzen meiner Welt" (Wittgenstein 2016: v. 5.6) underscores the vital role of language in shaping our perceptions. Today, in a globalized and interconnected society, fluency in foreign languages is indispensable for individual success. Education must break down these linguistic barriers, and one promising approach is the integration of foreign languages into content subjects.
Teaching content subjects in a foreign language, a practice known as Content Language Integrated Learning (CLIL), not only enhances language skills but also cultivates cognitive abilities and intercultural competence. This approach expands horizons and aligns with the core principles of European education (Leaton Gray, Scott & Mehisto 2018: 50). The Kultusministerkonferenz (KMK) recognizes the benefits of CLIL and encourages its implementation in German schools (cf. KMK 2013a).
With the rising popularity of CLIL, textbooks in foreign languages have become widely available, simplifying teaching. However, the appropriateness of the language used in these materials remains an unanswered question. If textbooks impose excessive linguistic demands, they may inadvertently limit students' development and contradict the goal of CLIL.
This thesis focuses on addressing this issue by systematically analyzing language requirements in CLIL teaching materials, emphasizing receptive and productive skills in various subjects based on the Common European Framework of Reference. The aim is to identify a sequence of subjects that facilitates students' language skill development throughout their school years. Such a sequence would enable teachers to harness the full potential of CLIL, fostering a bidirectional approach where content subjects facilitate language learning.
While research on CLIL is extensive, studies on language requirements for bilingual students are limited. This thesis seeks to bridge this gap by presenting findings for History, Geography, Biology, and Mathematics, allowing for a comprehensive understanding of language demands. This research endeavors to enrich the field of bilingual education and CLIL, ultimately benefiting the academic success of students in an interconnected world.
Potential impacts of invasive crayfish on native
benthic fish: shelter use and agonistic behaviour
(2023)
Spinycheek crayfish (Faxonius limosus) and signal crayfish (Pacifastacus leniusculus) are successful North American invasive crayfish species distributed throughout Europe. Both species compete with native benthic fish for shelter. In a laboratory approach, we assessed competition for shelter and antagonistic interactions between these invasive crayfish species and the native benthic fish species, stone loach (Barbatula barbatula) and bullhead (Cottus gobio). This allows for studying the potential impacts of invasive crayfish on native benthic fish. Spinycheek crayfish and signal crayfish were able to gain control of the shelter and could successfully displace both benthic fish species. For stone loach, the presence of crayfish significantly decreased their shelter use and caused several behavioural changes such as reduced activity and increased hiding behaviour outside the shelter. Although the shelter use by bullheads was not reduced, they displayed similar behavioural changes, if less intense. Invasive crayfish species showed remarkable combative interactions against both species of benthic fishes, evidenced by the high number of aggressive interactions, especially concerning stone loach. Our results highlight the pronounced dominance of invasive crayfish over benthic fish in terms of shelter competition and aggressive interactions under laboratory conditions, which consequently might promote the latter’s exposure to predation.
Increasingly, problematic smartphone use behavior (PSU) and excessive consumption are reported. In this study, an experiment was developed to investigate the influence of screen coloration using the grayscale setting on smartphone usage time in repeated measurements. We also investigated how individuals perceived suffering correlates with smartphone usage time and PSU, and whether differences exist by smartphone usage type (social, process, habitual). 240 subjects completed a questionnaire about smartphone usage time, PSU, perceived suffering, and smartphone usage types. Afterward, their smartphones were switched to grayscale setting for at least 24h, and thereafter 92 of these participants completed the second questionnaire. Analyses showed that grayscale setting decreases usage time and that there is a positive correlation between PSU, smartphone usage duration, and perceived suffering. The types of use (process and habitual) influence one’s perceived suffering. Thus, it shows that individuals are aware of their PSU and suffer from it. Using grayscale setting is effective in reducing smartphone use time.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.