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- African Union (1)
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- Biochemie (1)
- Biochemistry (1)
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Since its establishment, the African Union (AU) has assumed an important role in matters of peace and security on the continent. This doctoral dissertation is dedicated to its conflict and crisis interventions and seeks to identify as well as subsequently explain the broader patterns that have emerged. The dissertation posits that neither the AU's regime-serving roots, which emphasize the primacy of incumbents' parochial interests, nor the AU's problem-solving commitment, which emphasizes the pursuit of its declared organizational mission, can convincingly explain these patterns on their own. Instead, we should understand the AU as being driven by two different logics of cooperation at the same time: a problem-solving and a regime-serving logic. Across its three constitutive articles, the dissertation makes empirical as well as theoretical contributions to the existing literature. Empirically, it offers a broad and systematic analysis of AU interventions over time, across different intervention types, and without bias towards high-profile cases. The novel dataset, on which the dissertation builds, constitutes the hitherto most comprehensive effort to capture the AU's responses to crises and conflicts. Theoretically, the dissertation develops a set of testable theory-driven expectations based on the notion of two different logics of cooperation. While identifiable in the literature on the AU and linking to broader existing debates on international cooperation, the dissertation breaks ground by clearly outlining the implications of each logic and bringing them together under a single theoretical framework. Jointly, the articles provided strong evidence that the AU is indeed driven by both a problem-solving and a regime-serving logic of cooperation, and that this serves as the foundation for explaining the AU's broader intervention patterns. This contributes not only to a better understanding of AU interventions but also has a chance to enrich other important debates, including the debates on African regionalism, comparative regionalism, and multilateral interventions.
Artificial intelligence, most prominently in the form of machine learning, is shaping up to be one of the most transformational technologies of the 21st century. Auditors are among the professions forecasted to be the most affected by artificial intelligence, as the profession encompasses many highly structured and repetitive tasks. Automating such tasks would naturally increase the efficiency of financial statement audits. By allowing auditors to focus on higher value-added tasks, and the capability to analyze large volumes of data at a fracture of the time a human would need, artificial intelligence would also benefit the effectiveness of auditing. Despite these benefits, to this day, the actual adoption of artificial intelligence in the audit domain remains rather limited. The audit profession is highly regulated and has to consider requirements regarding, e.g. the application of professional standards, codes of conduct, and data protection obligations. Hence, the question arises of how audit firms can be supported in their efforts to adopt artificial intelligence and how machine learning systems can be designed to comply with the specific demands of the audit domain. The goal of this dissertation is to better understand the adoption of artificial intelligence in the audit domain and to actively support the adoption of artificial intelligence in auditing based on this understanding. To this end, we employ a mixture of research methods. On the one hand, the research presented here adopts a qualitative approach, examining the adoption of artificial intelligence and other advanced analytical technologies of the audit domain through taxonomy development and grounded theory. The findings of these studies inspire the second stream of work within this dissertation, which adopts a quantitative and design-oriented approach: It focuses on using machine learning to extract information from invoices for tests of details. Tests of details are essential substantive audit procedures used in nearly every audit. This dissertation proposes a new machine learning model architecture for information extraction from invoices, compares different machine learning models, and proposes design principles for machine learning pipelines for an audit application addressing the test of details through action design research.
Mikroalgen können bei den internationalen Bemühungen zur Begrenzung der CO2-Emissionen einen wichtigen Beitrag leisten. In der Photosynthese der Mikroalgen wird das CO2 aus der Atmosphäre in Biomasse fixiert. Im Gegensatz zu Landpflanzen können Mikroalgen zudem exponentiell wachsen, haben geringere Anforderungen an die Wasserqualität und konkurrieren nicht mit Agrarflächen, die begrenzt und für die Nahrungsmittelsicherheit der Weltbevölkerung erforderlich sind. Die produzierte Mikroalgenbiomasse kann als regenerative Ressource zu Biokraftstoffen wie Biogas und Biodiesel umgewandelt und somit als Energieträger genutzt werden. Zudem können Mikroalgen auch bei der biotechnologischen Produktion kommerziell relevanter Wertstoffe wie Pigmenten und Omega-3-Fettsäuren für die Nahrungsmittelindustrie Anwendung finden. Mit dem Ziel der Steigerung dieser Wertstoffe stand die Untersuchung des Einflusses der Kultivierungsparameter Licht und Temperatur auf das Wachstum und die Zusammensetzung der Mikroalgenbiomasse im Mittelpunkt dieser Dissertation. Insbesondere der Einfluss unterschiedlicher Lichtspektren auf das Wachstum und die Wertstoffproduktion in Mikroalgen wurde detailliert untersucht. Zusätzlich wurde überprüft, ob sich die gewonnenen Erkenntnisse auch auf Landpflanzen übertragen lassen. Im Rahmen dieser Promotion wurde erstmals systematisch der Einfluss unterschiedlicher Temperaturen und Lichtspektren im zeitlichen Verlauf der Kultivierung auf Mikroalgen untersucht. Hierbei konnten distinkte Spektralbereiche sowie Temperaturen ermittelt werden, die für eine maximale Produktion von Biomasse und Pigmenten sowie einem maximalen Desaturierungsgrad der Fettsäuren erforderlich sind. Die in dieser Arbeit gewonnenen Erkenntnisse tragen zu einem besseren Verständnis der Biochemie von photosynthetischen Organismen bei.
The emergence of sustainability as a guiding principle for tourism development came along with needs to introduce instruments that can monitor the actual impacts of tourism. Sustainability assessments in tourism (SAT) have gained popularity in recent years with a range of measurement schemes being introduced for national and subnational tourism destinations. With the help of sustainability indicators these schemes intend to guide decision-makers in making better evidence-informed decisions and to improve the overall sustainability performance of tourism. With this dissertation, the author aims to contribute to a deeper understanding of the implementation and performance of sustainability assessments, by linking transformative needs of tourism with necessary assessment approaches that can serve as effective instruments for a shift towards a more sustainable tourism development. Thus, the research is part of recent efforts to establish profound and effective measurement approaches for sustainable tourism. The author employs a mixed-methods approach combining qualitative, quantitative, set-theoretic, and review methods, with the aim of maximising the validity of results. First, he explores the general progress and current state of research on sustainability assessments in tourism, with the intention to identify patterns, key elements and research gaps within assessment approaches This is followed by subsequent detailed analyses that examine specific environmental and socio-economic sustainability issues with the aim of providing conceptual, methodological and empirical solutions for assessing them in detail. The dissertation highlights that concrete assessment tools are needed for evidence-informed decision-making and the establishment of effective actions in destination management. The findings indicate that assessments will be more successful in terms of serving as tools for decision-making, if they tackle main drivers of change and encourage management or policymakers to take decisions that affect multiple sustainability issues. It also reviews different concepts and accounting principles and rises awareness of a cautious selection of methods and measurement approaches, as this may affect overall results. The thesis empirically evaluates and applies different measurement approaches in specific destinations, with the help of quantitative and qualitative data collection methodologies. In general, my thesis provides further clarification about key environmental and socio-economic measurement methodologies, which supports ongoing debates about sustainability impacts of tourism. Thus, the research contributes to knowledge, frameworks, methodologies and practical application for tourism governance and tourism sustainability science.