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Processes of political meaning-making and contentious positioning. Recent Romanian cycles of mass protest and their activists' motives and demands
No full textThe work investigates a series of mass protest outbreaks between 2012 and 2019 and the dynamics of a simultaneous civil society reconfiguration in Romania, using a political ethnography approach. It strives to make a methodological contribution, bridging interpretivist ethnography and questions of contentious politics, investigating the potential of political difference theories in that regard.
In one methodological and two empirical papers, it first conceptualizes the methodological principle of political sensibility (in parallel to the principles of ethnographic sensibility, when tackling specifically political questions). It then tests political difference theory categories (association/dissociation; acknowledging/acting), conceptualizing practices of political positioning; and practices of creating political spaces, as exemplified in the interactions with Romanian political activists.
Facing the complex contexts of protest outbreak as a disruption in contentious politics culture, the platformization of protest communication/organization/documentation, and the analytical framework of post-socialism, the work proposes to rethink some of the "classical" concepts of social movement studies. The latter oftentimes operate with presuppositions won in historical contexts of modern, western democracy, and therefore oftentimes do not suit post-modern, non-western societal realities. As the work shows, ontologically turned methodological and theoretical approaches do have potential for that endeavor
Bildung von Gasen und kurzkettigen organischen Säuren in Opalinuston bei erhöhten Temperaturen
No full textDue to their low permeability, high retention capability for radionuclides, and self-sealing of fractures by swelling, claystones have beneficial properties as natural barrier for high-level heat-emitting nuclear waste (HLW). Temperatures at the surface of HLW containers in claystone formations are expected to be in the range of 90–150 °C. Elevated temperatures can cause clay mineral transformation reactions reducing the radionuclide retention potential of the host rock.
In this thesis, the thermal transformation of organic matter in a host rock for HLW disposal, the Opalinus Clay (OPA; Mont Terri, St. Ursanne, Switzerland), was investigated in hydrous pyrolysis experiments at temperatures from 80–200 °C – and beyond. Geochemical reactions were monitored over periods of several weeks. The experiments demonstrated the generation of gaseous CO2 and C1–C4 hydrocarbons. CO2(g) was the dominant gas. Gas yields increased with increasing temperature. CO2(g) originated predominantly from the dissolution of carbonate mineral phases in the OPA sample material and, to a lesser extent, from the thermal transformation of OPA organic matter. Analyses of aqueous fluid samples showed the generation of LMWOA, predominantly acetate, followed by oxalate and formate. The yields of the acids increased with increasing temperature, with the exception of significantly lower quantities of oxalate and formate at temperatures ≥160 °C.
The application of kinetic data on thermal LMWOA decomposition (e.g., decarboxylation) from the literature demonstrated that simultaneous generation and decomposition reactions of LMWOA affect the prediction of gas generation (e.g., CO2(g) + CH4(g)) by decarboxylation.
It is concluded that the quantities of generated gases and LMWOA, when confronted with geochemical reactions decomposing and/or immobilizing some of them, are unlikely to affect the integrity and long-term safety of a HLW repository in the Opalinus Clay
Klimaprotest als Diskurs intervention, ziviler Widerstand und Debattenmotiv
No full textPublikation der U Bremen und U Wien internationalen Studierendenkonferenz »Debattieren, Opponieren, Protestieren – Interdisziplinäre Perspektiven auf sprachliche Praktiken des Widersprechens« 2023.102
Arctic Sea Ice property retrieval from synthetic aperture radar with deep learning methods
No full textCurrent climate models are not capturing the feedback mechanisms driving the accelerated warming of the Arctic. A central challenge is the sparsity of observations. Satellite-borne synthetic aperture radar (SAR) instruments have the capability of monitoring Earth's sea ice masses at high resolution, unhampered by cloud coverage or the Arctic night. The measurements are made at scales of 10's of metres whilst still covering the Arctic in a matter of days. However, interpreting the radar signal to retrieve relevant sea ice information is difficult because of the complex interactions of the ice with the electromagnetic radar signal. Conventional neural network algorithms leverage contextual image data to make accurate predictions of surface ice properties comparable to those made by human experts. They are, however, dependent on large amounts of high-quality ground truth that is rare in these regions. Thus, the full potential of the SAR data is yet to be unlocked. With the advent of the MOSAiC mission, large timeseries of SAR data and near-coincident ground measurements were acquired for the first time. This thesis uses the unique opportunity provided by these data to analyse the behaviour of deep learning models. Seven months of data from the campaign is classified and analysed, using newly developed techniques to enable robust predictions across the timeseries. Core features are identified to facilitate robust and high-resolution classification. The final challenge of ground truth sparsity is then overcome using innovative network configurations that enable the training of 99.99%$ of the model parameters without any ground truth data. The techniques open up sea ice property retrieval to big data technologies, relying only on the abundantly available SAR data. These techniques enable the extrapolation of sparse reference data to a large space of sea ice conditions and enable high resolution mapping of the Earth's region most affected by human-made climate change
Numerische Quantifizierung des Einflusses räumlich verteilter Out-of-Plane Welligkeiten auf die Materialfestigkeit von Faserverbundstrukturen mithilfe probabilistischer Verfahren
No full textFertigungsbedingte Fehler stellen seit jeher die Herstellung von Flugzeugstrukturen aus Kohlenstofffaser-verstärktem Kunststoff (CFK) vor immensen Herausforderungen, um den hohen Qualitätsanforderungen der Luftfahrt gerecht zu werden. Unerwünschte Faserauslenkungen im Verbundwerkstoff, auch als Welligkeiten bezeichnet, repräsentieren hierbei einen charakteristischen Fehlertyp. Um das veränderte Material- und Tragverhalten unter dem Einfluss von Welligkeiten adäquat bestimmen zu können, kommen seit einiger Zeit vermehrt numerische Berechnungsverfahren zum Einsatz. Trotz der Verfügbarkeit moderner Rechentechnik beschränkt sich die simulationsbasierte Untersuchung der Thematik aufgrund der Komplexität jedoch auf ausgewählte Geometrien.
Die vorliegende Arbeit stellt einen numerischen Bewertungsansatz vor, der die Vielzahl potentieller Welligkeitsgeometrien auf Beispiel von Out-of-Plane Effekten mithilfe einer nicht-deterministischen Berechnungsmethode abbildet. Zu diesem Zweck wird ein stochastisches Konzept auf Basis von Zufallsfeldern zur Geometrieparametrisierung beschrieben und diskutiert. Ergänzend dazu wird ein FEM-zentrierter Modellierungsansatz dargelegt, mit dem die Auswirkungen der Welligkeiten auf die Tragreserven des Materials strukturmechanisch untersucht werden können. Dies erfolgt mithilfe detaillierter Modelle der Einzellagen des Materialverbunds, mit denen belastungsabhängige Abminderungsfaktoren (KDF) zur Quantifizierung des Materialverhaltens bestimmt werden. Die KDF werden in der Arbeit anhand verschiedener Kriterien zur Charakterisierung des Versagensverhaltens im CFK-Verbund miteinander verglichen.
Der dargelegte probabilistische Berechnungsansatz wird zusätzlich anhand repräsentativer Laminatkonfigurationen am Beispiel der Druckfestigkeit Rx demonstriert und daraus resultierend statistische Verteilungen des KDF der Materialkenngröße ermittelt. Im Vergleich der KDF zeigen sich je nach betrachtetem Versagenskriterium größere Unterschiede, die weiterführende Untersuchungen im Kontext motivieren. Für einen praktischen Einsatz der Methode werden abschließend verschiedene Geometrie-basierte Metriken miteinander verglichen, anhand derer eine näherungsweise Bestimmung des KDF ermöglicht werden kann. In den Untersuchungen zeigte sich, dass der maximale Welligkeitsgradient aufgrund eines geringen Variationskoeffizients für Winkel bis etwa 19 Grad eine geeignete Ersatzgröße darstellt. Dies bietet das Potential für einen fertigungsbegleitenden Einsatz der Methode zur Bewertung realitätsnaher Welligkeitsdefekte
Complex algal polysaccharides as substrates for Maribacter strains
No full textMarine bacteria play a crucial role in global nutrient cycles, yet much remains to be
understood about their ecophysiological niches, metabolic dependencies, and the
functions of essential proteins. The research unit FOR 2406 Proteogenomics of
Marine Polysaccharide Utilization investigates the mechanisms behind bacterial
polysaccharide utilization during marine phytoplankton blooms. The focus is
particularly on the functional analyses of marine bacteria within the phylum
Bacteroidota.
Flavobacteriia, a prominent class within the phylum Bacteroidota, are a significant
component of marine bacterioplankton. Free-living members of this class play a
pivotal role in the degradation of polysaccharides from lysed algae. They often
harbour carbohydrate-active enzymes within polysaccharide utilization loci, operon-
like genetic regions encoding proteins responsible for the hydrolysis and transport
of polysaccharides. Fierce competition among free-living bacteria has led to
genomic streamlining, typically focusing on a select few polysaccharides. In
contrast, particle-associated bacteria face diverse substrate challenges. Some
have the ability to sense and migrate toward nutrient sources, while others reside
attached to particulate organic matter (POM), resulting in larger genomes compared
to their free-living counterparts. Despite their ecological importance, polysaccharide
utilization by particle-associated bacteria has received limited attention.
Maribacter, observed in particle-associated fractions within marine systems,
represent a significant gap in physiological studies. To address this gap, we
employed proteomics to investigate the complexity of polysaccharide utilization
mechanisms in Maribacter
The Atlantic Meridional Overturning Circulation in the North Atlantic, focussing on 47°N - variability, trends, and meridional connectivity
No full textThe Atlantic Meridional Overturning Circulation (AMOC) plays a vital role in the climate of Europe and the North Atlantic region. Climate model studies project an AMOC decline in the 21st century. However, they disagree on the magnitude and timescales of the weakening. Thus, monitoring AMOC changes remains essential to provide benchmarks for assessing climate models and understanding the physical processes determining AMOC variability. In this thesis, basin-wide AMOC volume transports are calculated (1993-2018). Measurements from moored instruments of the NOAC array at 47°N are combined with hydrography and satellite altimetry. Variability, trends, and meridional connectivity with the RAPID array at 26°N are analyzed. The AMOC volume transport at 47°N exhibits a mean strength of 17.2 Sv and substantial variability on inter-annual and seasonal timescales but no significant long-term trend. The NOAC AMOC shows a significant correlation with the RAPID AMOC when the NOAC AMOC leads by about one year, indicating meridional connectivity. An analysis of the AMOC at the NOAC, RAPID, and OSNAP (52°N-60°N) lines in the high-resolution forced VIKING20X model simulation reveals a mean NOAC AMOC strength within the estimated error range of the NOAC observations. In disagreement with observations, the VIKING20X AMOC decreases after the mid-1990s until 2010 at all three array lines. This decrease coincides with a significant cooling and freshening in the subpolar North Atlantic. In agreement with observations, VIKING20X shows meridional connectivity between the NOAC and RAPID AMOC when the NOAC AMOC leads by about one year. This indicates a common mechanism, determining the meridional connectivity in observations and VIKING20X. An analysis of different ANHA model simulations with varying resolution underlines the importance of model resolution for accurately representing the AMOC mean strength and variability but also stresses the need for model improvements beyond resolution
Towards Comprehensive Magnetic Resonance Imaging of Heterogeneously Catalyzed Reactions using Methanation as Case Study
No full textDie Optimierung chemischer Reaktionen im Hinblick auf eine effizientere Energienutzung sowie die Einführung neuer Prozessrouten sind wichtige Faktoren, um das Ziel der Klimaneutralität in der chemischen Industrie erreichen zu können. Da chemische Reaktoren jedoch blickdicht und unzugänglich für viele Messmethoden sind, ist eine Bewertung der Effektivität verschiedener Optimierungsmaßnahmen nur schwer möglich. In dieser Arbeit wird eine neue Technik zur Untersuchung von Gasphasenprozessen in der katalytisch aktiven Zone eines chemischen Reaktors vorgestellt. Die Combined Temperature and Density (CTD)-Technik ist in der Lage, eine dreidimensionale Verteilung der Temperatur und der Moleküldichte zu messen, die zum Beispiel zur Lokalisierung von Hotspots in der katalytisch aktiven Zone verwendet werden kann. Die Methode wird auf die Methanisierungsreaktion unter Verwendung einer Saturation-Recovery-Sequenz angewandt, wobei die gleichzeitige Messung der Signalamplitude und der longitudinalen Relaxationszeit T1 ausgenutzt wird, um Informationen über Temperatur und Dichte von Methan direkt aus der Gasphase zu gewinnen. Die Unterschiede in der Temperatur- und Dichteverteilung lassen sich deutlich erkennen und ermöglichen so, die lokalen Reaktionslimitierungen zu identifizieren
Digital Labour Mirage: Dissecting Utopias in Africa's Gig Economy
No full textThis dissertation investigates the multifaceted impacts of digital platformisation on labour markets in Sub-Saharan Africa, with a focus on Rwanda, South Africa, and Zimbabwe. Through extensive qualitative analysis comprising over 60 semi-structured interviews, organizational documents, and ethnographic observations, the study reveals complex dynamics of dispossession and agency as African workers navigate emerging digital economies.
The dissertation consists of three interconnected papers. The first examines Rwanda's strategic efforts to equip youth with digital skills, highlighting both opportunities and risks of exacerbating inequality. The second paper explores how algorithmic management systems undermine worker autonomy across platform sectors, while also uncovering instances of strategic resistance. The final paper develops a nuanced typology of five platform worker categories, illuminating varied experiences of precarity and capability.
Employing an integrated theoretical framework combining neo-Marxist and postcolonial perspectives, the analysis traces continuities between historical and contemporary regimes of accumulation that perpetuate asymmetric power relations. However, workers retain agency to contest constraints in innovative ways.
The findings challenge techno-optimistic narratives by revealing concrete policy actions needed to promote equity and sustainability in Africa's digital labour markets. By foregrounding marginalized voices, this study advances critical scholarship on decent digital work and provides an empirical foundation for governance reforms fostering human-centered technological transitions in the Global South
Real-time ship recognition and georeferencing for the improvement of maritime situational awareness
No full textIn an era where maritime infrastructures are paramount to societies, the need for advanced maritime situational awareness solutions has become increasingly important. Existing ship monitoring procedures, such as the Automatic Identification System (AIS), have limitations, suffer from delayed updates, and are vulnerable to cyberattacks. Other technologies, such as satellite imagery and radar, face challenges in real-time applications due to delays in acquiring and processing data. The use of optical camera systems and image processing can improve situational awareness, allowing real-time usage of maritime infrastructure footage. However, the number of video streams available poses a challenge for maritime operators, who could benefit from summarized spatial information of recognized ships, irrespective of their size and type, presented on a map in real-time. This motivates the development of automated ship recognition and georeferencing technologies. Moreover, the deployment of such camera systems, equipped with embedded devices, allows for local data processing on the edge to minimize network demand, reduce energy usage, decrease latency, cut costs, and enhance data protection. This thesis, integrating six of my publications, presents a comprehensive investigation into leveraging deep learning and computer vision to advance real-time ship recognition and georeferencing for the improvement of maritime situational awareness. I present a novel dataset for ship recognition and georeferencing, ShipSG, which facilitates the development and validation of recognition and georeferencing methodologies. The dataset contains 3,505 images and 11,625 ship masks with their corresponding class, geographic position, and length. Through a series of studies of state-of-the-art deep-learning-based object recognition algorithms, I introduce a custom real-time segmentation architecture, ScatYOLOv8+CBAM. This architecture was created and optimized for the NVIDIA Jetson AGX Xavier as an embedded system. ScatYOLOv8+CBAM incorporates the 2D scattering transform, a novel addition that enhances YOLOv8 in real-world applications such as ship segmentation. Additionally, the performance is further improved with the integration of attention mechanisms. The proposed architecture exceeds state-of-the-art methods by more than 5%, achieving a mean Average Precision (mAP) of 75.46%. The inference speed, once the customized architecture is deployed on the embedded system using TensorRT, is 25.3 ms per frame. Furthermore, I address the need for precision in recognizing small and distant ships and their real-time processing of full-resolution images on embedded systems with an enhanced slicing mechanism that performs batch inference and merges predictions, achieving mAP improvements ranging from 8% to 11%. The recognized ships are georeferenced using my proposed method, which automatically calculates the georeferencing pixel of the recognized ships and uses homographies to provide the geographic position of ships from single images without prior camera knowledge. In the quantitative analysis, the georeferencing method achieved a positioning error of 18 m ± 10 m for ranges inside the port basin (up to 400 m) and 44 m ± 27 m outside (from 400 m to 1200 m). The main findings reveal significant advancements in maritime situational awareness with the practical demonstration of the applicability of the methodologies in real-world scenarios, such as the detection of abnormal ship behavior, camera integrity assessment, and 3D reconstruction. The approach not only outperforms existing methods in terms of accuracy and processing speed but also provides a framework for seamlessly integrating recognized and georeferenced ships into real-time systems, enhancing operational effectiveness and decision-making for maritime authorities. The integration of these methodologies into embedded systems represents a pivotal advancement in the domain, offering a scalable and efficient solution for improving maritime situational awareness and response capabilities. This thesis contributes to the maritime computer vision field by establishing a benchmark for ship segmentation and georeferencing research, demonstrating the viability of deep-learning-based recognition and georeferencing methods for real-time maritime monitoring