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Differenzielle Modellierung infratentorieller Atrophiemuster bei Rasmussen Enzephalitis mittels struktureller und diffusionsgewichteter MRT
Get PDFDie Rasmussen Enzephalitis (RE) ist eine autoimmun-vermittelte Erkrankung des Gehirns, welche sich meist im Kindesalter erstmals manifestiert und neurologische Defizite sowie eine therapierefraktäre Epilepsie verursacht. Charakteristischerweise und aus bislang ungeklärten Gründen treten die entzündlichen Prozesse bei der RE streng unilateral auf, sodass die RE als eine unihemisphärische Erkrankung des Großhirns bekannt ist. Immer wieder zeigen sich jedoch auch im Kleinhirn Auffälligkeiten, welche erstaunlicherweise mal kontraläsional, mal ipsiläsional zur betroffenen Großhirnhemisphäre lokalisiert sind. Die Studie von Reiter et al. (2021) beleuchtet und untersucht erstmals systematisch infratentorielle Auffälligkeiten bei der RE. Mittels struktureller und diffusionsgewichteter MRT-Sequenzen einer vergleichsweise großen Kohorte von 57 Menschen mit RE und Kontrollpersonen gleichen Alters und Geschlechts wurden unterschiedliche zerebellare Atrophiemuster identifiziert und ätiologisch näher eingeordnet. Die Ergebnisse deuten darauf hin, dass bilateralen und kontraläsionalen Atrophiemustern sekundär-degenerative Mechanismen zugrunde liegen, während ipsiläsionale Atrophie Ausdruck einer primär-inflammatorischen infratentoriellen Erkrankungsmanifestation zu sein scheint. Die Arbeit schafft auf diese Weise ein Bewusstsein und eine Interpretationsgrundlage für infratentorielle Auffälligkeiten bei Menschen mit RE und erweitert das bestehende Erkrankungskonzept
Negotiating Citizenship(s) in Young Adult Speculative Novels
Get PDFThe major objective of this study is to analyse in which ways a selection of speculative novels for adolescent readers represent, interpret, shape and encode different forms of citizenship. In setting this focus, this study takes up the assumption that highly conventionalised genres are drawn on especially in historic moments in which a recourse to known formulae is perceived as helpful or necessary in order to make sense of collective experiences that are difficult to interpret or to encode social values and norms, both aspects that can be found in recent and ongoing debates about citizenship. The genres of dystopia and post-/disaster, as well as a further highly conventionalised genre that is of importance in the context of this study, the Bildungsroman, are often employed to represent and negotiate societal crisis in various ways, for example a crisis of conceptualising citizenship (as a form of belonging, as participation and representation and as responsibility), of national and international security or of ecological and climate crisis. Even adolescence itself is constructed as a time of crisis (cf. Kristeva, “The Adolescent Novel” 9). Differing dimensions of citizenship, such as political, cultural or ecological, and the ways in which they are threatened, contested and negotiated are intricately connected to all of these crises. The main assumption of this study is that in the selected novels, citizenship positions are interrogated and challenged but also reaffirmed and that this occurs through the challenging of or compliance with genre conventions relating to aspects of space and memory. This study seeks to determine in how far the treatment of such conventions is relevant for the characters’, and by extension the adolescent readers’, movement towards enfranchisement and which forms of enfranchisement are imagined as necessary or possible at all, i.e. which ‘spaces’ are opened up (or closed down) for the performance of (differing kinds of) citizenship. Furthermore, this study examines to which extent the ideologies of citizenship provided for adolescent readers in these novels remain steeped in “patriotic senses of national particularity” as “[h]istorically [cultivated by] the Rights of Man and Bildung”, thus having rendered these concepts complicit “with nationalism and colonialism” (Slaughter, “Enabling Fictions” 55), or whether genre hybridisation in these novels manages to create an “impure […] genre […] that represents resistance to a hegemonic ideology” (Baccolini, “Gender and Genre” 18). A genre-theoretical provides a concise outline of the most relevant ‘genres’ or forms of writing in relation to the novels to be discussed. The emphasis is placed on explaining the discursive functions of these categories, especially with regards to adolescence and aspects of citizenship, but also at this point important notions of space and/or memory are addressed. With a view to the many female protagonists in the novels under discussion, this presentation of the generic framework also briefly discusses issues around the construction of adolescent female identity. The textual analysis is divided into three major chapters, each examining distinct forms or ideologies of citizenship and their ties to specific generic traditions through the representation of a range of spatial and memory-related aspects and issues. Due to the thematic emphases of the selected novels, the focused citizenship categories are political, cultural and ecological citizenship
Radar-Based Scene Understanding for Autonomous Vehicles
No full textAutonomous vehicles have the potential to revolutionize transportation by redmoving instance segmentation leverages the advantages of radar sensors and leads to exceptional results, the predictions are ideal for enhancing scene understanding further. We propose an algorithm to utilize moving instance predictions and reliably associate agents over time, including the tracking of distant objects thatucing accidents caused by human errors, improving efficiency, and enhancing mobility for everyone. Dynamic real-world environments impose several challenges, including varying lighting conditions, adverse weather, and interactions with diverse road users. Therefore, the reliable perception of the surroundings under changing conditions is a fundamental task for safe navigation in dynamic real-world environments. Common perception stacks of modern autonomous driving systems comprise different sensors, such as cameras, LiDARs, and radar sensors, to leverage the advantages and mitigate the limitations of the individual modalities. Cameras and LiDARs face limitations in adverse weather conditions, including rain, fog and snow. Therefore, radar sensors, which work under these conditions, are critical to enable safe mobility. Radar sensors provide sparse point clouds to locate and identify objects within the surroundings of the autonomous vehicle. Each point in the cloud also contains additional information, such as the Doppler velocity, which is the radial velocity of the object. Consequently, radar point clouds include relevant information to differentiate between moving and static instances within the environment. Dedicated algorithms capable of handling sparse and noisy radar point clouds are fundamental to extracting high-level information. The main contributions of this thesis are novel and impactful approaches that process radar point clouds to improve scene understanding of autonomous vehicles in real-world environments. We focus on several tasks that contribute to the perception and understanding of the environment. We start with semantic segmentation to extract information about the corresponding classes of objects in radar point clouds. In the second step, we propose a novel approach to address moving object segmentation, which benefits from the fact that a binary classification simplifies the overall segmentation compared to general semantic segmentation. The task is well suited for radar data because of the provided Doppler velocity. Based on the reliable segmentation of moving objects, we develop a novel algorithm for instance segmentation to distinguish individual objects within a scene. The resulting segmentation of moving instances improves scene understanding and includes knowledge about the number of agents. Since only comprise one point. We further use the predictions to predict the semantics of the individual instances. Hence, we propose a novel approach that predicts the semantic classes of the individual agents and utilizes the information to refine the instance assignment. In sum, our approaches show superior performance on various benchmarks, including diverse environments, and provide optimized modules to enhance scene understanding. All of our proposed approaches presented in this thesis were published in peer-reviewed conference papers and journal articles, contributing to the advancements of radar-based scene understanding in real-world environments.Autonome Fahrzeuge besitzen das Potenzial, den Verkehr grundlegend zu verändern. Sie werden Unfälle aufgrund menschlichen Versagens reduzieren und Mobilität für alle zugänglich machen. Allerdings stellen reale Umgebungen aufgrund von wechselnden Licht- und Wetterverhältnissen sowie komplexen Interaktionen mit Verkehrsteilnehmern eine große Herausforderung für autonome Fahrzeuge dar. Eine zuverlässige Wahrnehmung der Umgebung ist dabei eine wesentliche Grundlage für sichere autonome Fahrfunktionen. Intelligente Wahrnehmungssysteme autonomer Fahrzeuge umfassen verschiedene Sensoren wie Kameras, LiDAR-Scanner und Radarsensoren, um die Stärken der verschiedenen Modalitäten zu kombinieren. LiDAR-Scanner und Kameras stoßen bei widrigen Wetterbedingungen, wie Regen, Nebel oder Schnee, an ihre Grenzen. Radarsensoren hingegen behalten auch unter diesen Bedingungen ihre Funktionalität und sind daher für eine verlässliche Wahrnehmung der Umgebung entscheidend. Im Gegensatz zu hochauflösenden Lidar-Scannern und Kameras liefern sie jedoch spärliche Punktwolken und werden durch Mehrwegeausbreitung und Interferenzen erheblich beeinträchtigt. Allerdings liefern Radarsensoren auch Dopplergeschwindigkeiten, welche die Unterscheidung zwischen bewegten und statischen Objekten ermöglichen und damit zu einem verbesserten Verständnis der Umgebung beitragen. Das Ziel dieser Arbeit ist die Entwicklung neuer Ansätze, um das Szenenverständnis von autonomen Fahrzeugen auf Basis von Radar-Punktwolken in realen Umgebungen zu verbessern. Wir beginnen mit der semantischen Segmentierung, um Informationen über die Objektklassen in Radar-Punktwolken zu extrahieren. Neben den semantischen Informationen ist auch die Unterscheidung zwischen statischer Umgebung und bewegten Objekten für eine sichere Navigation unerlässlich. Daher entwickeln wir einen neuen Ansatz zur Segmentierung bewegter Objekte. Auf dieser Grundlage erarbeiten wir einen Algorithmus für die Erkennung von Instanzen, um individuelle Objekte innerhalb einer Szene zu unterscheiden. Die daraus resultierende Segmentierung bewegter Instanzen verbessert das Szenenverständnis und schließt das Wissen über die Anzahl der Verkehrsteilnehmer ein. Die Segmentierung bewegter Instanzen bildet einen idealen Ausgangspunkt, um das Szenenverständnis weiter zu verbessern. Wir extrahieren zusätzliche Merkmale sowie geometrische Beziehungen, um Instanzen über die Zeit zu assoziieren und zu verfolgen. Unsere Instanzzuordnung funktioniert auch bei der Verfolgung von weit entfernten Objekten zuverlässig. In einem weiteren Ansatz prädizieren wir die semantische Klasse der bewegten Instanzen. Wir entwickeln hierzu einen neuartigen Ansatz, der die semantischen Klassen der einzelnen Agenten vorhersagt und die Informationen zur Optimierung der Instanzzuweisung nutzt. Abschließend lässt sich festhalten, dass unsere Ansätze zu wesentlichen Fortschritten des Szenenverständnisses in verschiedenen Umgebungen beitragen. Die neuartigen Methoden sind entscheidend, um Radar-Punktwolken zuverlässig zu verarbeiten und lassen sich auf reale Daten übertragen. Alle in dieser Arbeit vorgestellten Ansätze wurden in begutachteten Konferenzbeiträgen und Zeitschriftenartikeln veröffentlicht und tragen zur Weiterentwicklung des radarbasierten Szenenverständnisses in realen Umgebungen bei
Detecting Superfluids, Exciting the Higgs Mode and Enhanced Cooling of Dimers in the BEC-BCS Crossover
Get PDFIn this thesis, the BEC-BCS crossover is experimentally investigated using a quantum simulator apparatus. We prepare a degenerate, interacting fermionic sample by cooling atoms in two of the lowest hyperfine states of 6Li in a crossed optical dipole trap. Interactions between the two states are controlled by means of a broad magnetic Feshbach resonance, and we adjust the samples' temperature and density by preciely tuning the trapping potential. This setup allows us to access and probe the entire BEC-BCS crossover.
A key property of the BEC-BCS crossover is the superfluid critical temperature, predicted to have a maximum on the BEC side of the strongly interacting regime. However, accurately measuring the critical temperature is challenging due to difficulties in determining a reliable temperature scale in the presence of strong interactions. In this thesis, we determine the critical temperature in the crossover with high accuracy by reconstructing the density distribution and incorporating interaction effects in the low-density wings when fitting to the virial expansion of the equation of state. This requires precise identification of the superfluid phase transition onset, for which we have developed two novel advanced image recognition techniques based on machine learning. Our improved methodology confirms, for the first time, an increase in the critical temperature from the BCS limit, extending beyond the unitarity point and approaching the BEC limit.
Crossing the superfluid phase transition is accompanied by spontaneous symmetry breaking, creating an energy landscape that supports two distinct excitation modes: the Goldstone and Higgs modes. Here, we probe the Higgs mode using two distinct excitation methods: a quench and a modulation of the interaction strength. This enables us to observe the Higgs mode throughout the crossover, revealing a gradual fading of the mode as it approaches the BEC regime, where particle-hole symmetry vanishes. Notably, we observe no temperature dependence of the Higgs mode, prompting further research.
Finally, we present a novel cooling method for a strongly interacting Fermi gas on the BEC side of the crossover, where a composite dimer bound state exists. By applying a modulation of the magnetic field at frequencies close to, but higher than the bound state energy, we selectively dissociate and remove high-energy dimers from the trap, thus realising evaporative cooling of the sample. This method does not require any changes to the trapping potential and facilitates staying in the efficient runaway regime. We demonstrate cooling for a wide range of interactions on the BEC side of the crossover, achieving high efficiencies that match or exceed all previously reported forced evaporation cooling near Feshbach resonances
Ampulläre Adenome bei Patienten mit familiärer adenomatöser Polyposis (FAP): Biopsie, Management, Risikobewertung
Get PDFHintergrund
Bei familiärer adenomatöser Polyposis (FAP) ist das Duodenum nach dem Kolon die zweithäufigste Manifestationsstelle einer Polyposis. Die Papilla duodeni major ist dabei besonders häufig von Adenomen betroffen. Die Spigelman-Klassifikation als Goldstandard zur Beurteilung der duodenalen Polyposis und Festlegung von Vorsorgeintervallen bezieht die Papille jedoch nicht mit in die Bewertung ein.
Methoden
Daten von 213 Patienten wurden hinsichtlich Diagnostik, Management und Risikobewertung von Papillenadenomen ausgewertet. Es erfolgte die Implementierung eines alternativen Spigelman Scores, welcher die Papillenparameter inkludiert. Anschließend wurde ein Unterschied der Spigelman Stadien geprüft. Des Weiteren wurde ein Zusammenhang zwischen dem Auftreten von Papillenadenomen und verschiedenen patientenbezogenen und klinischen Parametern geprüft.
Ergebnisse
Papillenadenome treten mit hoher Prävalenz bei FAP-Patienten auf. Ihr Auftreten korrelierte signifikant mit der Polypen Anzahl im Duodenum. Routinemäßige Biopsien sind sicher. Auch makroskopisch unauffällige Schleimhaut kann Adenome bergen. Die Einbeziehung der Papillenparameter führte zu einem signifikanten Upgrade im Spigelman Stadium und beeinflusste Vorsorgeempfehlungen. Die Therapie von Papillenadenomen birgt ein hohes Komplikationsrisiko.
Zusammenfassung
Der Bewertung der Papille bei FAP-Patienten kommt eine besondere Bedeutung zu. Die alleinige Anwendung der Spigelman Klassifikation wird dieser nicht gerecht. Papillenadenome treten häufig auf. Die Diagnostik dieser ist risikoarm, während die Therapie von Papillenadenomen mit einem bedeutenden Komplikationsrisiko verbunden ist
The importance of edges in complex networks
No full textThe sun, the climate, world politics, the stock market, or the human brain, complex networked systems are deeply intertwined in the world we live in. Their dynamics, which include unexpected and catastrophic extreme events, can have tremendous impact on a single human or man-kind as a whole. Hence, studying these systems' dynamical phenomena as well as their properties is essential to improve our knowledge about them. Under the key premise that a complex system can be divided into interacting elementary units, the network ansatz poses a very useful and decisive approach to characterise the system. Associating network vertices with elementary units and network edges with interactions between them, this ansatz yields vast applicability to various natural or man-made systems. Even for those cases, where interactions have no structural correlate or cannot be inferred directly, utilizing time-series-analysis techniques to investigate the units' dynamics allows to characterize properties of interactions, like their strength, direction or even coupling functions, ultimately constituting a time-evolving functional network. Graph theory assesses networks as mathematical structures and provides a multitude of concepts and metrics to assess network characteristics from a global scale, viewing the network as a whole, over an intermediate scale, focusing on substructures in it, to a local scale, inspecting properties of single vertices and edges. Knowledge gained in this way about the properties of the network can then be related to properties of the investigated system and aid to understand its complex emergent global dynamics. While in many ways it is the intricate interplay of interactions between the systems' elements that dictates its properties and dynamics, the edges of networks and their properties have been vastly overlooked. Therefore in this thesis, we embarked on a more edge-centric approach to investigate complex systems utilizing the network ansatz. We developed novel concepts, advanced local network metrics, proposed novel edge-centric metrics and introduced network decomposition algorithms, set out to improve our understanding of real-world systems and their complex dynamics. We demonstrated the applicability and added value of these concepts and metrics, and gained vital insights about archetypical network topologies, spreading phenomena, as well as critical transitions and their entailed extreme events. On the prime example of a complex dynamical system, able to self-generate extreme events, the human epileptic brain, we elucidated vital aspects of network mechanisms involved in the generation of epileptic seizures, e.g. in revealing specific tipping elements and tipping subnetworks. This can ultimately aid in developing more refined approaches to characterize, predict and possibly even mitigate extreme events, such as epileptic seizures. We further revealed limitations of the network ansatz, and how this approach can aid in tackling fundamental challenges encountered especially when studying such real-world systems as the brain, included sampling issues and influences of endogenous and external driving forces. Employing the network ansatz and focusing on the intricate interplay of a complex networked system's interactions, provided considerable advances in understanding these systems and their dynamical phenomena, while also paving the way for future research by displaying the immense potential the network ansatz -- and especially the study of important edges -- can hold
Amtliche Bekanntmachungen, 55. Jahrgang, Nr. 20
No full textÄnderung und zugleich Außerkraftsetzung des Organisationsstatuts der zentralen wissenschaftlichen Einrichtung Forum Internationale Wissenschaft Bonn (fiw) der Rheinischen Friedrich-Wilhelms-Universität Bonn vom 11. April 202
Metabolomics biomarkers for diet and adiposity
Get PDFDiet is an important determinant of health and well-being. Epidemiologic studies link higher habitual intake of sweetened beverages (SBs), sweet and fatty snacks, and the broad range of ultra-processed foods (UPF) with an increased risk of obesity. Poor nutritional profiles, higher caloric intake, and energy imbalance are some of the proposed mechanisms, but other biological pathways underlying diet-related weight gain and regulation are not fully defined. Human metabolome provides a rich resource for understanding metabolic alterations associated with diet. Here, we conduct a literature review on biomarkers of SBs (study 1); investigate the metabolomic signatures of SBs and added sugar intake in children, adolescents, and young adults and their association with adiposity measures (study 2); investigate the reproducibility of urine biomarkers of sweet and fatty snacks across two independent cohorts (study 3); and investigate the metabolomic profiles of UPF intake in adolescents and young adults and their association with adiposity (study 4).
In study 1, we conducted a systematic review of the literature on biomarkers of SBs and their levels of validity. In study 2, we used 3 data sets across 3 age groups: children (3.0–10.3 y), adolescents (14.9–18.4 y), and young adults (18.0–21.9 y), from the DONALD cohort study. In study 3, we included the previously defined sample of children and children from an external cohort, the IDEFICS/I.Family cohort. In study 4, we included the adolescent and young adult analytic samples defined in study 2. We used untargeted metabolomics in urine and plasma across all studies and additionally conducted lipidomics on plasma. We applied multiple machine learning methods because of the high-dimensional data: the random forest, partial least squares, and LASSO for joint metabolite selection (study 2 and 3); particle swarm optimization and extreme gradient boosting for investigating metabolite data missing mechanisms (study 4); and robust sparse PCA for deriving metabolite patterns (study 4). We used linear and mixed effects for covariate adjustments (study 2-4).
We identified metabolomic signatures of SBs, added sugar, sweet and fatty snacks, and UPF intake in young individuals. Some of these metabolomic changes were related to adiposity measures and may be important research targets for better understanding of the mechanisms through which these foods contribute to weight gain and adiposity
Amtliche Bekanntmachungen, 55. Jahrgang, Nr. 30
No full textÄnderungsordnung zur und zugleich Neubekanntmachung der Evaluations- und Akkreditierungsordnung Studium und Lehre (EvAO) der Rheinischen Friedrich-Wilhelms-Universität Bonn vom 15. Mai 202
Amtliche Bekanntmachungen, 55. Jahrgang, Nr. 34
No full textAkkreditierungsbeschluss vom 20. Mai 2025 - Evangelische Religionslehre (Bachelorteilstudiengang für Lehramt an Berufskollegs) - Evangelische Religionslehre (Masterteilstudiengang für Lehramt an Berufskollegs) - Evangelische Religionslehre (Bachelorteilstudiengang für Lehramt an Gymnasien und Gesamtschulen) - Evangelische Religionslehre (Masterteilstudiengang für Lehramt an Gymnasien und Gesamtschulen) vom 23. Mai 202