TY - THES AB - In nature, different species find their niche in a range of environments, each with its unique characteristics. While some thrive in uniform (homogeneous) landscapes where environmental conditions stay relatively consistent across space, others traverse the complexities of spatially heterogeneous terrains. Comprehending how species are distributed and how they interact within these landscapes holds the key to gaining insights into their evolutionary dynamics while also informing conservation and management strategies. For species inhabiting heterogeneous landscapes, when the rate of dispersal is low compared to spatial fluctuations in selection pressure, localized adaptations may emerge. Such adaptation in response to varying selection strengths plays an important role in the persistence of populations in our rapidly changing world. Hence, species in nature are continuously in a struggle to adapt to local environmental conditions, to ensure their continued survival. Natural populations can often adapt in time scales short enough for evolutionary changes to influence ecological dynamics and vice versa, thereby creating a feedback between evolution and demography. The analysis of this feedback and the relative contributions of gene flow, demography, drift, and natural selection to genetic variation and differentiation has remained a recurring theme in evolutionary biology. Nevertheless, the effective role of these forces in maintaining variation and shaping patterns of diversity is not fully understood. Even in homogeneous environments devoid of local adaptations, such understanding remains elusive. Understanding this feedback is crucial, for example in determining the conditions under which extinction risk can be mitigated in peripheral populations subject to deleterious mutation accumulation at the edges of species’ ranges as well as in highly fragmented populations. In this thesis we explore both uniform and spatially heterogeneous metapopulations, investigating and providing theoretical insights into the dynamics of local adaptation in the latter and examining the dynamics of load and extinction as well as the impact of joint ecological and evolutionary (eco-evolutionary) dynamics in the former. The thesis is divided into 5 chapters. Chapter 1 provides a general introduction into the subject matter, clarifying concepts and ideas used throughout the thesis. In chapter 2, we explore how fast a species distributed across a heterogeneous landscape adapts to changing conditions marked by alterations in carrying capacity, selection pressure, and migration rate. In chapter 3, we investigate how migration selection and drift influences adaptation and the maintenance of variation in a metapopulation with three habitats, an extension of previous models of adaptation in two habitats. We further develop analytical approximations for the critical threshold required for polymorphism to persist. The focus of chapter 4 of the thesis is on understanding the interplay between ecology and evolution as coupled processes. We investigate how eco-evolutionary feedback between migration, selection, drift, and demography influences eco-evolutionary outcomes in marginal populations subject to deleterious mutation accumulation. Using simulations as well as theoretical approximations of the coupled dynamics of population size and allele frequency, we analyze how gene flow from a large mainland source influences genetic load and population size on an island (i.e., in a marginal population) under genetically realistic assumptions. Analyses of this sort are important because small isolated populations, are repeatedly affected by complex interactions between ecological and evolutionary processes, which can lead to their death. Understanding these interactions can therefore provide an insight into the conditions under which extinction risk can be mitigated in peripheral populations thus, contributing to conservation and restoration efforts. Chapter 5 extends the analysis in chapter 4 to consider the dynamics of load (due to deleterious mutation accumulation) and extinction risk in a metapopulation. We explore the role of gene flow, selection, and dominance on load and extinction risk and further pinpoint critical thresholds required for metapopulation persistence. Overall this research contributes to our understanding of ecological and evolutionary mechanisms that shape species’ persistence in fragmented landscapes, a crucial foundation for successful conservation efforts and biodiversity management. AU - Olusanya, Oluwafunmilola O ID - 14711 SN - 2663 - 337X TI - Local adaptation, genetic load and extinction in metapopulations ER - TY - THES AU - Chiossi, Heloisa ID - 14821 SN - 2663 - 337X TI - Adaptive hierarchical representations in the hippocampus ER - TY - THES AB - This thesis consists of four distinct pieces of work within theoretical biology, with two themes in common: the concept of optimization in biological systems, and the use of information-theoretic tools to quantify biological stochasticity and statistical uncertainty. Chapter 2 develops a statistical framework for studying biological systems which we believe to be optimized for a particular utility function, such as retinal neurons conveying information about visual stimuli. We formalize such beliefs as maximum-entropy Bayesian priors, constrained by the expected utility. We explore how such priors aid inference of system parameters with limited data and enable optimality hypothesis testing: is the utility higher than by chance? Chapter 3 examines the ultimate biological optimization process: evolution by natural selection. As some individuals survive and reproduce more successfully than others, populations evolve towards fitter genotypes and phenotypes. We formalize this as accumulation of genetic information, and use population genetics theory to study how much such information can be accumulated per generation and maintained in the face of random mutation and genetic drift. We identify the population size and fitness variance as the key quantities that control information accumulation and maintenance. Chapter 4 reuses the concept of genetic information from Chapter 3, but from a different perspective: we ask how much genetic information organisms actually need, in particular in the context of gene regulation. For example, how much information is needed to bind transcription factors at correct locations within the genome? Population genetics provides us with a refined answer: with an increasing population size, populations achieve higher fitness by maintaining more genetic information. Moreover, regulatory parameters experience selection pressure to optimize the fitness-information trade-off, i.e. minimize the information needed for a given fitness. This provides an evolutionary derivation of the optimization priors introduced in Chapter 2. Chapter 5 proves an upper bound on mutual information between a signal and a communication channel output (such as neural activity). Mutual information is an important utility measure for biological systems, but its practical use can be difficult due to the large dimensionality of many biological channels. Sometimes, a lower bound on mutual information is computed by replacing the high-dimensional channel outputs with decodes (signal estimates). Our result provides a corresponding upper bound, provided that the decodes are the maximum posterior estimates of the signal. AU - Hledik, Michal ID - 15020 KW - Theoretical biology KW - Optimality KW - Evolution KW - Information SN - 2663 - 337X TI - Genetic information and biological optimization ER - TY - THES AU - Chen, JingJing ID - 15101 SN - 2663 - 337X TI - Developmental transformation of nanodomain coupling between Ca2+ channels and release sensors at a central GABAergic synapse ER - TY - THES AB - Point sets, geometric networks, and arrangements of hyperplanes are fundamental objects in discrete geometry that have captivated mathematicians for centuries, if not millennia. This thesis seeks to cast new light on these structures by illustrating specific instances where a topological perspective, specifically through discrete Morse theory and persistent homology, provides valuable insights. At first glance, the topology of these geometric objects might seem uneventful: point sets essentially lack of topology, arrangements of hyperplanes are a decomposition of Rd, which is a contractible space, and the topology of a network primarily involves the enumeration of connected components and cycles within the network. However, beneath this apparent simplicity, there lies an array of intriguing structures, a small subset of which will be uncovered in this thesis. Focused on three case studies, each addressing one of the mentioned objects, this work will showcase connections that intertwine topology with diverse fields such as combinatorial geometry, algorithms and data structures, and emerging applications like spatial biology. AU - Cultrera di Montesano, Sebastiano ID - 15094 SN - 2663 - 337X TI - Persistence and Morse theory for discrete geometric structures ER - TY - THES AB - The process of detecting and evaluating sensory information to guide behaviour is termed perceptual decision-making (PDM), and is critical for the ability of an organism to interact with its external world. Individuals with autism, a neurodevelopmental condition primarily characterised by social and communication difficulties, frequently exhibit altered sensory processing and PDM difficulties are widely reported. Recent technological advancements have pushed forward our understanding of the genetic changes accompanying this condition, however our understanding of how these mutations affect the function of specific neuronal circuits and bring about the corresponding behavioural changes remains limited. Here, we use an innate PDM task, the looming avoidance response (LAR) paradigm, to identify a convergent behavioural abnormality across three molecularly distinct genetic mouse models of autism (Cul3, Setd5 and Ptchd1). Although mutant mice can rapidly detect threatening visual stimuli, their responses are consistently delayed, requiring longer to initiate an appropriate response than their wild-type siblings. Mutant animals show abnormal adaptation in both their stimulus- evoked escape responses and exploratory dynamics following repeated stimulus presentations. Similarly delayed behavioural responses are observed in wild-type animals when faced with more ambiguous threats, suggesting the mutant phenotype could arise from a dysfunction in the flexible control of this PDM process. Our knowledge of the core neuronal circuitry mediating the LAR facilitated a detailed dissection of the neuronal mechanisms underlying the behavioural impairment. In vivo extracellular recording revealed that visual responses were unaffected within a key brain region for the rapid processing of visual threats, the superior colliculus (SC), indicating that the behavioural delay was unlikely to originate from sensory impairments. Delayed behavioural responses were recapitulated in the Setd5 model following optogenetic stimulation of the excitatory output neurons of the SC, which are known to mediate escape initiation through the activation of cells in the underlying dorsal periaqueductal grey (dPAG). In vitro patch-clamp recordings of dPAG cells uncovered a stark hypoexcitability phenotype in two out of the three genetic models investigated (Setd5 and Ptchd1), that in Setd5, is mediated by the misregulation of voltage-gated potassium channels. Overall, our results show that the ability to use visual information to drive efficient escape responses is impaired in three diverse genetic mouse models of autism and that, in one of the models studied, this behavioural delay likely originates from differences in the intrinsic excitability of a key subcortical node, the dPAG. Furthermore, this work showcases the use of an innate behavioural paradigm to mechanistically dissect PDM processes in autism. AU - Burnett, Laura ID - 12716 SN - 2663-337X TI - To flee, or not to flee? Using innate defensive behaviours to investigate rapid perceptual decision-making through subcortical circuits in mouse models of autism ER - TY - THES AB - Understanding the mechanisms of learning and memory formation has always been one of the main goals in neuroscience. Already Pavlov (1927) in his early days has used his classic conditioning experiments to study the neural mechanisms governing behavioral adaptation. What was not known back then was that the part of the brain that is largely responsible for this type of associative learning is the cerebellum. Since then, plenty of theories on cerebellar learning have emerged. Despite their differences, one thing they all have in common is that learning relies on synaptic and intrinsic plasticity. The goal of my PhD project was to unravel the molecular mechanisms underlying synaptic plasticity in two synapses that have been shown to be implicated in motor learning, in an effort to understand how learning and memory formation are processed in the cerebellum. One of the earliest and most well-known cerebellar theories postulates that motor learning largely depends on long-term depression at the parallel fiber-Purkinje cell (PC-PC) synapse. However, the discovery of other types of plasticity in the cerebellar circuitry, like long-term potentiation (LTP) at the PC-PC synapse, potentiation of molecular layer interneurons (MLIs), and plasticity transfer from the cortex to the cerebellar/ vestibular nuclei has increased the popularity of the idea that multiple sites of plasticity might be involved in learning. Still a lot remains unknown about the molecular mechanisms responsible for these types of plasticity and whether they occur during physiological learning. In the first part of this thesis we have analyzed the variation and nanodistribution of voltagegated calcium channels (VGCCs) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid type glutamate receptors (AMPARs) on the parallel fiber-Purkinje cell synapse after vestibuloocular reflex phase reversal adaptation, a behavior that has been suggested to rely on PF-PC LTP. We have found that on the last day of adaptation there is no learning trace in form of VGCCs nor AMPARs variation at the PF-PC synapse, but instead a decrease in the number of PF-PC synapses. These data seem to support the view that learning is only stored in the cerebellar cortex in an initial learning phase, being transferred later to the vestibular nuclei. Next, we have studied the role of MLIs in motor learning using a relatively simple and well characterized behavioral paradigm – horizontal optokinetic reflex (HOKR) adaptation. We have found behavior-induced MLI potentiation in form of release probability increase that could be explained by the increase of VGCCs at the presynaptic side. Our results strengthen the idea of distributed cerebellar plasticity contributing to learning and provide a novel mechanism for release probability increase. AU - Alcarva, Catarina ID - 12809 SN - 2663 - 337X TI - Plasticity in the cerebellum: What molecular mechanisms are behind physiological learning ER - TY - THES AB - During navigation, animals can infer the structure of the environment by computing the optic flow cues elicited by their own movements, and subsequently use this information to instruct proper locomotor actions. These computations require a panoramic assessment of the visual environment in order to disambiguate similar sensory experiences that may require distinct behavioral responses. The estimation of the global motion patterns is therefore essential for successful navigation. Yet, our understanding of the algorithms and implementations that enable coherent panoramic visual perception remains scarce. Here I pursue this problem by dissecting the functional aspects of interneuronal communication in the lobula plate tangential cell network in Drosophila melanogaster. The results presented in the thesis demonstrate that the basis for effective interpretation of the optic flow in this circuit are stereotyped synaptic connections that mediate the formation of distinct subnetworks, each extracting a particular pattern of global motion. Firstly, I show that gap junctions are essential for a correct interpretation of binocular motion cues by horizontal motion-sensitive cells. HS cells form electrical synapses with contralateral H2 neurons that are involved in detecting yaw rotation and translation. I developed an FlpStop-mediated mutant of a gap junction protein ShakB that disrupts these electrical synapses. While the loss of electrical synapses does not affect the tuning of the direction selectivity in HS neurons, it severely alters their sensitivity to horizontal motion in the contralateral side. These physiological changes result in an inappropriate integration of binocular motion cues in walking animals. While wild-type flies form a binocular perception of visual motion by non-linear integration of monocular optic flow cues, the mutant flies sum the monocular inputs linearly. These results indicate that rather than averaging signals in neighboring neurons, gap-junctions operate in conjunction with chemical synapses to mediate complex non-linear optic flow computations. Secondly, I show that stochastic manipulation of neuronal activity in the lobula plate tangential cell network is a powerful approach to study the neuronal implementation of optic flow-based navigation in flies. Tangential neurons form multiple subnetworks, each mediating course-stabilizing response to a particular global pattern of visual motion. Application of genetic mosaic techniques can provide sparse optogenetic activation of HS cells in numerous combinations. These distinct combinations of activated neurons drive an array of distinct behavioral responses, providing important insights into how visuomotor transformation is performed in the lobula plate tangential cell network. This approach can be complemented by stochastic silencing of tangential neurons, enabling direct assessment of the functional role of individual tangential neurons in the processing of specific visual motion patterns. Taken together, the findings presented in this thesis suggest that establishing specific activity patterns of tangential cells via stereotyped synaptic connectivity is a key to efficient optic flow-based navigation in Drosophila melanogaster. AU - Pokusaeva, Victoria ID - 12826 SN - 2663 - 337X TI - Neural control of optic flow-based navigation in Drosophila melanogaster ER - TY - THES AB - Most energy in humans is produced in form of ATP by the mitochondrial respiratory chain consisting of several protein assemblies embedded into lipid membrane (complexes I-V). Complex I is the first and the largest enzyme of the respiratory chain which is essential for energy production. It couples the transfer of two electrons from NADH to ubiquinone with proton translocation across bacterial or inner mitochondrial membrane. The coupling mechanism between electron transfer and proton translocation is one of the biggest enigma in bioenergetics and structural biology. Even though the enzyme has been studied for decades, only recent technological advances in cryo-EM allowed its extensive structural investigation. Complex I from E.coli appears to be of special importance because it is a perfect model system with a rich mutant library, however the structure of the entire complex was unknown. In this thesis I have resolved structures of the minimal complex I version from E. coli in different states including reduced, inhibited, under reaction turnover and several others. Extensive structural analyses of these structures and comparison to structures from other species allowed to derive general features of conformational dynamics and propose a universal coupling mechanism. The mechanism is straightforward, robust and consistent with decades of experimental data available for complex I from different species. Cyanobacterial NDH (cyanobacterial complex I) is a part of broad complex I superfamily and was studied as well in this thesis. It plays an important role in cyclic electron transfer (CET), during which electrons are cycled within PSI through ferredoxin and plastoquinone to generate proton gradient without NADPH production. Here, I solved structure of NDH and revealed additional state, which was not observed before. The novel “resting” state allowed to propose the mechanism of CET regulation. Moreover, conformational dynamics of NDH resembles one in complex I which suggest more broad universality of the proposed coupling mechanism. In summary, results presented here helped to interpret decades of experimental data for complex I and contributed to fundamental mechanistic understanding of protein function. AU - Kravchuk, Vladyslav ID - 12781 SN - 2663-337X TI - Structural and mechanistic study of bacterial complex I and its cyanobacterial ortholog ER - TY - THES AB - Deep learning has become an integral part of a large number of important applications, and many of the recent breakthroughs have been enabled by the ability to train very large models, capable to capture complex patterns and relationships from the data. At the same time, the massive sizes of modern deep learning models have made their deployment to smaller devices more challenging; this is particularly important, as in many applications the users rely on accurate deep learning predictions, but they only have access to devices with limited memory and compute power. One solution to this problem is to prune neural networks, by setting as many of their parameters as possible to zero, to obtain accurate sparse models with lower memory footprint. Despite the great research progress in obtaining sparse models that preserve accuracy, while satisfying memory and computational constraints, there are still many challenges associated with efficiently training sparse models, as well as understanding their generalization properties. The focus of this thesis is to investigate how the training process of sparse models can be made more efficient, and to understand the differences between sparse and dense models in terms of how well they can generalize to changes in the data distribution. We first study a method for co-training sparse and dense models, at a lower cost compared to regular training. With our method we can obtain very accurate sparse networks, and dense models that can recover the baseline accuracy. Furthermore, we are able to more easily analyze the differences, at prediction level, between the sparse-dense model pairs. Next, we investigate the generalization properties of sparse neural networks in more detail, by studying how well different sparse models trained on a larger task can adapt to smaller, more specialized tasks, in a transfer learning scenario. Our analysis across multiple pruning methods and sparsity levels reveals that sparse models provide features that can transfer similarly to or better than the dense baseline. However, the choice of the pruning method plays an important role, and can influence the results when the features are fixed (linear finetuning), or when they are allowed to adapt to the new task (full finetuning). Using sparse models with fixed masks for finetuning on new tasks has an important practical advantage, as it enables training neural networks on smaller devices. However, one drawback of current pruning methods is that the entire training cycle has to be repeated to obtain the initial sparse model, for every sparsity target; in consequence, the entire training process is costly and also multiple models need to be stored. In the last part of the thesis we propose a method that can train accurate dense models that are compressible in a single step, to multiple sparsity levels, without additional finetuning. Our method results in sparse models that can be competitive with existing pruning methods, and which can also successfully generalize to new tasks. AU - Peste, Elena-Alexandra ID - 13074 SN - 2663-337X TI - Efficiency and generalization of sparse neural networks ER - TY - THES AB - Pattern formation is of great importance for its contribution across different biological behaviours. During developmental processes for example, patterns of chemical gradients are established to determine cell fate and complex tissue patterns emerge to define structures such as limbs and vascular networks. Patterns are also seen in collectively migrating groups, for instance traveling waves of density emerging in moving animal flocks as well as collectively migrating cells and tissues. To what extent these biological patterns arise spontaneously through the local interaction of individual constituents or are dictated by higher level instructions is still an open question however there is evidence for the involvement of both types of process. Where patterns arise spontaneously there is a long standing interest in how far the interplay of mechanics, e.g. force generation and deformation, and chemistry, e.g. gene regulation and signaling, contributes to the behaviour. This is because many systems are able to both chemically regulate mechanical force production and chemically sense mechanical deformation, forming mechano-chemical feedback loops which can potentially become unstable towards spatio and/or temporal patterning. We work with experimental collaborators to investigate the possibility that this type of interaction drives pattern formation in biological systems at different scales. We focus first on tissue-level ERK-density waves observed during the wound healing response across different systems where many previous studies have proposed that patterns depend on polarized cell migration and arise from a mechanical flocking-like mechanism. By combining theory with mechanical and optogenetic perturbation experiments on in vitro monolayers we instead find evidence for mechanochemical pattern formation involving only scalar bilateral feedbacks between ERK signaling and cell contraction. We perform further modeling and experiment to study how this instability couples with polar cell migration in order to produce a robust and efficient wound healing response. In a following chapter we implement ERK-density coupling and cell migration in a 2D active vertex model to investigate the interaction of ERK-density patterning with different tissue rheologies and find that the spatio-temporal dynamics are able to both locally and globally fluidize a tissue across the solid-fluid glass transition. In a last chapter we move towards lower spatial scales in the context of subcellular patterning of the cell cytoskeleton where we investigate the transition between phases of spatially homogeneous temporal oscillations and chaotic spatio-temporal patterning in the dynamics of myosin and ROCK activities (a motor component of the actomyosin cytoskeleton and its activator). Experimental evidence supports an intrinsic chemical oscillator which we encode in a reaction model and couple to a contractile active gel description of the cell cortex. The model exhibits phases of chemical oscillations and contractile spatial patterning which reproduce many features of the dynamics seen in Drosophila oocyte epithelia in vivo. However, additional pharmacological perturbations to inhibit myosin contractility leaves the role of contractile instability unclear. We discuss alternative hypotheses and investigate the possibility of reaction-diffusion instability. AU - Boocock, Daniel R ID - 12964 SN - 2663-337X TI - Mechanochemical pattern formation across biological scales ER - TY - THES AB - High-performance semiconductors rely upon precise control of heat and charge transport. This can be achieved by precisely engineering defects in polycrystalline solids. There are multiple approaches to preparing such polycrystalline semiconductors, and the transformation of solution-processed colloidal nanoparticles is appealing because colloidal nanoparticles combine low cost with structural and compositional tunability along with rich surface chemistry. However, the multiple processes from nanoparticle synthesis to the final bulk nanocomposites are very complex. They involve nanoparticle purification, post-synthetic modifications, and finally consolidation (thermal treatments and densification). All these properties dictate the final material’s composition and microstructure, ultimately affecting its functional properties. This thesis explores the synthesis, surface chemistry and consolidation of colloidal semiconductor nanoparticles into dense solids. In particular, the transformations that take place during these processes, and their effect on the material’s transport properties are evaluated. AU - Calcabrini, Mariano ID - 12885 SN - 2663-337X TI - Nanoparticle-based semiconductor solids: From synthesis to consolidation ER - TY - THES AB - The tight spatiotemporal coordination of signaling activity determining embryo patterning and the physical processes driving embryo morphogenesis renders embryonic development robust, such that key developmental processes can unfold relatively normally even outside of the full embryonic context. For instance, embryonic stem cell cultures can recapitulate the hallmarks of gastrulation, i.e. break symmetry leading to germ layer formation and morphogenesis, in a very reduced environment. This leads to questions on specific contributions of embryo-specific features, such as the presence of extraembryonic tissues, which are inherently involved in gastrulation in the full embryonic context. To address this, we established zebrafish embryonic explants without the extraembryonic yolk cell, an important player as a signaling source and for morphogenesis during gastrulation, as a model of ex vivo development. We found that dorsal-marginal determinants are required and sufficient in these explants to form and pattern all three germ layers. However, formation of tissues, which require the highest Nodal-signaling levels, is variable, demonstrating a contribution of extraembryonic tissues for reaching peak Nodal signaling levels. Blastoderm explants also undergo gastrulation-like axis elongation. We found that this elongation movement shows hallmarks of oriented mesendoderm cell intercalations typically associated with dorsal tissues in the intact embryo. These are disrupted by uniform upregulation of BMP signaling activity and concomitant explant ventralization, suggesting that tight spatial control of BMP signaling is a prerequisite for explant morphogenesis. This control is achieved by Nodal signaling, which is critical for effectively downregulating BMP signaling in the mesendoderm, highlighting that Nodal signaling is not only directly required for mesendoderm cell fate specification and morphogenesis, but also by maintaining low levels of BMP signaling at the dorsal side. Collectively, we provide insights into the capacity and organization of signaling and morphogenetic domains to recapitulate features of zebrafish gastrulation outside of the full embryonic context. AU - Schauer, Alexandra ID - 12891 SN - 2663 - 337X TI - Mesendoderm formation in zebrafish gastrulation: The role of extraembryonic tissues ER - TY - THES AB - About a 100 years ago, we discovered that our universe is inherently noisy, that is, measuring any physical quantity with a precision beyond a certain point is not possible because of an omnipresent inherent noise. We call this - the quantum noise. Certain physical processes allow this quantum noise to get correlated in conjugate physical variables. These quantum correlations can be used to go beyond the potential of our inherently noisy universe and obtain a quantum advantage over the classical applications. Quantum noise being inherent also means that, at the fundamental level, the physical quantities are not well defined and therefore, objects can stay in multiple states at the same time. For example, the position of a particle not being well defined means that the particle is in multiple positions at the same time. About 4 decades ago, we started exploring the possibility of using objects which can be in multiple states at the same time to increase the dimensionality in computation. Thus, the field of quantum computing was born. We discovered that using quantum entanglement, a property closely related to quantum correlations, can be used to speed up computation of certain problems, such as factorisation of large numbers, faster than any known classical algorithm. Thus began the pursuit to make quantum computers a reality. Till date, we have explored quantum control over many physical systems including photons, spins, atoms, ions and even simple circuits made up of superconducting material. However, there persists one ubiquitous theme. The more readily a system interacts with an external field or matter, the more easily we can control it. But this also means that such a system can easily interact with a noisy environment and quickly lose its coherence. Consequently, such systems like electron spins need to be protected from the environment to ensure the longevity of their coherence. Other systems like nuclear spins are naturally protected as they do not interact easily with the environment. But, due to the same reason, it is harder to interact with such systems. After decades of experimentation with various systems, we are convinced that no one type of quantum system would be the best for all the quantum applications. We would need hybrid systems which are all interconnected - much like the current internet where all sorts of devices can all talk to each other - but now for quantum devices. A quantum internet. Optical photons are the best contenders to carry information for the quantum internet. They can carry quantum information cheaply and without much loss - the same reasons which has made them the backbone of our current internet. Following this direction, many systems, like trapped ions, have already demonstrated successful quantum links over a large distances using optical photons. However, some of the most promising contenders for quantum computing which are based on microwave frequencies have been left behind. This is because high energy optical photons can adversely affect fragile low-energy microwave systems. In this thesis, we present substantial progress on this missing quantum link between microwave and optics using electrooptical nonlinearities in lithium niobate. The nonlinearities are enhanced by using resonant cavities for all the involved modes leading to observation of strong direct coupling between optical and microwave frequencies. With this strong coupling we are not only able to achieve almost 100\% internal conversion efficiency with low added noise, thus presenting a quantum-enabled transducer, but also we are able to observe novel effects such as cooling of a microwave mode using optics. The strong coupling regime also leads to direct observation of dynamical backaction effect between microwave and optical frequencies which are studied in detail here. Finally, we also report first observation of microwave-optics entanglement in form of two-mode squeezed vacuum squeezed 0.7dB below vacuum level. With this new bridge between microwave and optics, the microwave-based quantum technologies can finally be a part of a quantum network which is based on optical photons - putting us one step closer to a future with quantum internet. AU - Sahu, Rishabh ID - 13175 KW - quantum optics KW - electrooptics KW - quantum networks KW - quantum communication KW - transduction SN - 2663 - 337X TI - Cavity quantum electrooptics ER - TY - THES AB - About a 100 years ago, we discovered that our universe is inherently noisy, that is, measuring any physical quantity with a precision beyond a certain point is not possible because of an omnipresent inherent noise. We call this - the quantum noise. Certain physical processes allow this quantum noise to get correlated in conjugate physical variables. These quantum correlations can be used to go beyond the potential of our inherently noisy universe and obtain a quantum advantage over the classical applications. Quantum noise being inherent also means that, at the fundamental level, the physical quantities are not well defined and therefore, objects can stay in multiple states at the same time. For example, the position of a particle not being well defined means that the particle is in multiple positions at the same time. About 4 decades ago, we started exploring the possibility of using objects which can be in multiple states at the same time to increase the dimensionality in computation. Thus, the field of quantum computing was born. We discovered that using quantum entanglement, a property closely related to quantum correlations, can be used to speed up computation of certain problems, such as factorisation of large numbers, faster than any known classical algorithm. Thus began the pursuit to make quantum computers a reality. Till date, we have explored quantum control over many physical systems including photons, spins, atoms, ions and even simple circuits made up of superconducting material. However, there persists one ubiquitous theme. The more readily a system interacts with an external field or matter, the more easily we can control it. But this also means that such a system can easily interact with a noisy environment and quickly lose its coherence. Consequently, such systems like electron spins need to be protected from the environment to ensure the longevity of their coherence. Other systems like nuclear spins are naturally protected as they do not interact easily with the environment. But, due to the same reason, it is harder to interact with such systems. After decades of experimentation with various systems, we are convinced that no one type of quantum system would be the best for all the quantum applications. We would need hybrid systems which are all interconnected - much like the current internet where all sorts of devices can all talk to each other - but now for quantum devices. A quantum internet. Optical photons are the best contenders to carry information for the quantum internet. They can carry quantum information cheaply and without much loss - the same reasons which has made them the backbone of our current internet. Following this direction, many systems, like trapped ions, have already demonstrated successful quantum links over a large distances using optical photons. However, some of the most promising contenders for quantum computing which are based on microwave frequencies have been left behind. This is because high energy optical photons can adversely affect fragile low-energy microwave systems. In this thesis, we present substantial progress on this missing quantum link between microwave and optics using electrooptical nonlinearities in lithium niobate. The nonlinearities are enhanced by using resonant cavities for all the involved modes leading to observation of strong direct coupling between optical and microwave frequencies. With this strong coupling we are not only able to achieve almost 100\% internal conversion efficiency with low added noise, thus presenting a quantum-enabled transducer, but also we are able to observe novel effects such as cooling of a microwave mode using optics. The strong coupling regime also leads to direct observation of dynamical backaction effect between microwave and optical frequencies which are studied in detail here. Finally, we also report first observation of microwave-optics entanglement in form of two-mode squeezed vacuum squeezed 0.7dB below vacuum level. With this new bridge between microwave and optics, the microwave-based quantum technologies can finally be a part of a quantum network which is based on optical photons - putting us one step closer to a future with quantum internet. AU - Sahu, Rishabh ID - 12900 KW - quantum optics KW - electrooptics KW - quantum networks KW - quantum communication KW - transduction SN - 2663 - 337X TI - Cavity quantum electrooptics ER - TY - THES AB - Nonergodic systems, whose out-of-equilibrium dynamics fail to thermalize, provide a fascinating research direction both for fundamental reasons and for application in state of the art quantum devices. Going beyond the description of statistical mechanics, ergodicity breaking yields a new paradigm in quantum many-body physics, introducing novel phases of matter with no counterpart at equilibrium. In this Thesis, we address different open questions in the field, focusing on disorder-induced many-body localization (MBL) and on weak ergodicity breaking in kinetically constrained models. In particular, we contribute to the debate about transport in kinetically constrained models, studying the effect of $U(1)$ conservation and inversion-symmetry breaking in a family of quantum East models. Using tensor network techniques, we analyze the dynamics of large MBL systems beyond the limit of exact numerical methods. In this setting, we approach the debated topic of the coexistence of localized and thermal eigenstates separated by energy thresholds known as many-body mobility edges. Inspired by recent experiments, our work further investigates the localization of a small bath induced by the coupling to a large localized chain, the so-called MBL proximity effect. In the first Chapter, we introduce a family of particle-conserving kinetically constrained models, inspired by the quantum East model. The system we study features strong inversion-symmetry breaking, due to the nature of the correlated hopping. We show that these models host so-called quantum Hilbert space fragmentation, consisting of disconnected subsectors in an entangled basis, and further provide an analytical description of this phenomenon. We further probe its effect on dynamics of simple product states, showing revivals in fidelity and local observalbes. The study of dynamics within the largest subsector reveals an anomalous transient superdiffusive behavior crossing over to slow logarithmic dynamics at later times. This work suggests that particle conserving constrained models with inversion-symmetry breaking realize new universality classes of dynamics and invite their further theoretical and experimental studies. Next, we use kinetic constraints and disorder to design a model with many-body mobility edges in particle density. This feature allows to study the dynamics of localized and thermal states in large systems beyond the limitations of previous studies. The time-evolution shows typical signatures of localization at small densities, replaced by thermal behavior at larger densities. Our results provide evidence in favor of the stability of many-body mobility edges, which was recently challenged by a theoretical argument. To support our findings, we probe the mechanism proposed as a cause of delocalization in many-body localized systems with mobility edges suggesting its ineffectiveness in the model studied. In the last Chapter of this Thesis, we address the topic of many-body localization proximity effect. We study a model inspired by recent experiments, featuring Anderson localized coupled to a small bath of free hard-core bosons. The interaction among the two particle species results in non-trivial dynamics, which we probe using tensor network techniques. Our simulations show convincing evidence of many-body localization proximity effect when the bath is composed by a single free particle and interactions are strong. We furthter observe an anomalous entanglement dynamics, which we explain through a phenomenological theory. Finally, we extract highly excited eigenstates of large systems, providing supplementary evidence in favor of our findings. AU - Brighi, Pietro ID - 12732 SN - 2663-337X TI - Ergodicity breaking in disordered and kinetically constrained quantum many-body systems ER - TY - THES AB - During development, tissues undergo changes in size and shape to form functional organs. Distinct cellular processes such as cell division and cell rearrangements underlie tissue morphogenesis. Yet how the distinct processes are controlled and coordinated, and how they contribute to morphogenesis is poorly understood. In our study, we addressed these questions using the developing mouse neural tube. This epithelial organ transforms from a flat epithelial sheet to an epithelial tube while increasing in size and undergoing morpho-gen-mediated patterning. The extent and mechanism of neural progenitor rearrangement within the developing mouse neuroepithelium is unknown. To investigate this, we per-formed high resolution lineage tracing analysis to quantify the extent of epithelial rear-rangement at different stages of neural tube development. We quantitatively described the relationship between apical cell size with cell cycle dependent interkinetic nuclear migra-tions (IKNM) and performed high cellular resolution live imaging of the neuroepithelium to study the dynamics of junctional remodeling. Furthermore, developed a vertex model of the neuroepithelium to investigate the quantitative contribution of cell proliferation, cell differentiation and mechanical properties to the epithelial rearrangement dynamics and validated the model predictions through functional experiments. Our analysis revealed that at early developmental stages, the apical cell area kinetics driven by IKNM induce high lev-els of cell rearrangements in a regime of high junctional tension and contractility. After E9.5, there is a sharp decline in the extent of cell rearrangements, suggesting that the epi-thelium transitions from a fluid-like to a solid-like state. We found that this transition is regulated by the growth rate of the tissue, rather than by changes in cell-cell adhesion and contractile forces. Overall, our study provides a quantitative description of the relationship between tissue growth, cell cycle dynamics, epithelia rearrangements and the emergent tissue material properties, and novel insights on how epithelial cell dynamics influences tissue morphogenesis. AU - Bocanegra, Laura ID - 13081 SN - 2663 - 337X TI - Epithelial dynamics during mouse neural tube development ER - TY - THES AB - The extension of extremal combinatorics to the setting of exterior algebra is a work in progress that gained attention recently. In this thesis, we study the combinatorial structure of exterior algebra by introducing a dictionary that translates the notions from the set systems into the framework of exterior algebra. We show both generalizations of celebrated Erdös--Ko--Rado theorem and Hilton--Milner theorem to the setting of exterior algebra in the simplest non-trivial case of two-forms. AU - Köse, Seyda ID - 13331 SN - 2791-4585 TI - Exterior algebra and combinatorics ER - TY - THES AB - Animals exhibit a remarkable ability to learn and remember new behaviors, skills, and associations throughout their lifetime. These capabilities are made possible thanks to a variety of changes in the brain throughout adulthood, regrouped under the term "plasticity". Some cells in the brain —neurons— and specifically changes in the connections between neurons, the synapses, were shown to be crucial for the formation, selection, and consolidation of memories from past experiences. These ongoing changes of synapses across time are called synaptic plasticity. Understanding how a myriad of biochemical processes operating at individual synapses can somehow work in concert to give rise to meaningful changes in behavior is a fascinating problem and an active area of research. However, the experimental search for the precise plasticity mechanisms at play in the brain is daunting, as it is difficult to control and observe synapses during learning. Theoretical approaches have thus been the default method to probe the plasticity-behavior connection. Such studies attempt to extract unifying principles across synapses and model all observed synaptic changes using plasticity rules: equations that govern the evolution of synaptic strengths across time in neuronal network models. These rules can use many relevant quantities to determine the magnitude of synaptic changes, such as the precise timings of pre- and postsynaptic action potentials, the recent neuronal activity levels, the state of neighboring synapses, etc. However, analytical studies rely heavily on human intuition and are forced to make simplifying assumptions about plasticity rules. In this thesis, we aim to assist and augment human intuition in this search for plasticity rules. We explore whether a numerical approach could automatically discover the plasticity rules that elicit desired behaviors in large networks of interconnected neurons. This approach is dubbed meta-learning synaptic plasticity: learning plasticity rules which themselves will make neuronal networks learn how to solve a desired task. We first write all the potential plasticity mechanisms to consider using a single expression with adjustable parameters. We then optimize these plasticity parameters using evolutionary strategies or Bayesian inference on tasks known to involve synaptic plasticity, such as familiarity detection and network stabilization. We show that these automated approaches are powerful tools, able to complement established analytical methods. By comprehensively screening plasticity rules at all synapse types in realistic, spiking neuronal network models, we discover entire sets of degenerate plausible plasticity rules that reliably elicit memory-related behaviors. Our approaches allow for more robust experimental predictions, by abstracting out the idiosyncrasies of individual plasticity rules, and provide fresh insights on synaptic plasticity in spiking network models. AU - Confavreux, Basile J ID - 14422 SN - 2663 - 337X TI - Synapseek: Meta-learning synaptic plasticity rules ER - TY - THES AB - Superconductivity has many important applications ranging from levitating trains over qubits to MRI scanners. The phenomenon is successfully modeled by Bardeen-Cooper-Schrieffer (BCS) theory. From a mathematical perspective, BCS theory has been studied extensively for systems without boundary. However, little is known in the presence of boundaries. With the help of numerical methods physicists observed that the critical temperature may increase in the presence of a boundary. The goal of this thesis is to understand the influence of boundaries on the critical temperature in BCS theory and to give a first rigorous justification of these observations. On the way, we also study two-body Schrödinger operators on domains with boundaries and prove additional results for superconductors without boundary. BCS theory is based on a non-linear functional, where the minimizer indicates whether the system is superconducting or in the normal, non-superconducting state. By considering the Hessian of the BCS functional at the normal state, one can analyze whether the normal state is possibly a minimum of the BCS functional and estimate the critical temperature. The Hessian turns out to be a linear operator resembling a Schrödinger operator for two interacting particles, but with more complicated kinetic energy. As a first step, we study the two-body Schrödinger operator in the presence of boundaries. For Neumann boundary conditions, we prove that the addition of a boundary can create new eigenvalues, which correspond to the two particles forming a bound state close to the boundary. Second, we need to understand superconductivity in the translation invariant setting. While in three dimensions this has been extensively studied, there is no mathematical literature for the one and two dimensional cases. In dimensions one and two, we compute the weak coupling asymptotics of the critical temperature and the energy gap in the translation invariant setting. We also prove that their ratio is independent of the microscopic details of the model in the weak coupling limit; this property is referred to as universality. In the third part, we study the critical temperature of superconductors in the presence of boundaries. We start by considering the one-dimensional case of a half-line with contact interaction. Then, we generalize the results to generic interactions and half-spaces in one, two and three dimensions. Finally, we compare the critical temperature of a quarter space in two dimensions to the critical temperatures of a half-space and of the full space. AU - Roos, Barbara ID - 14374 SN - 2663 - 337X TI - Boundary superconductivity in BCS theory ER - TY - THES AB - Payment channel networks are a promising approach to improve the scalability bottleneck of cryptocurrencies. Two design principles behind payment channel networks are efficiency and privacy. Payment channel networks improve efficiency by allowing users to transact in a peer-to-peer fashion along multi-hop routes in the network, avoiding the lengthy process of consensus on the blockchain. Transacting over payment channel networks also improves privacy as these transactions are not broadcast to the blockchain. Despite the influx of recent protocols built on top of payment channel networks and their analysis, a common shortcoming of many of these protocols is that they typically focus only on either improving efficiency or privacy, but not both. Another limitation on the efficiency front is that the models used to model actions, costs and utilities of users are limited or come with unrealistic assumptions. This thesis aims to address some of the shortcomings of recent protocols and algorithms on payment channel networks, particularly in their privacy and efficiency aspects. We first present a payment route discovery protocol based on hub labelling and private information retrieval that hides the route query and is also efficient. We then present a rebalancing protocol that formulates the rebalancing problem as a linear program and solves the linear program using multiparty computation so as to hide the channel balances. The rebalancing solution as output by our protocol is also globally optimal. We go on to develop more realistic models of the action space, costs, and utilities of both existing and new users that want to join the network. In each of these settings, we also develop algorithms to optimise the utility of these users with good guarantees on the approximation and competitive ratios. AU - Yeo, Michelle X ID - 14506 SN - 2663 - 337X TI - Advances in efficiency and privacy in payment channel network analysis ER - TY - THES AB - Most motions of many-body systems at any scale in nature with sufficient degrees of freedom tend to be chaotic; reaching from the orbital motion of planets, the air currents in our atmosphere, down to the water flowing through our pipelines or the movement of a population of bacteria. To the observer it is therefore intriguing when a moving collective exhibits order. Collective motion of flocks of birds, schools of fish or swarms of self-propelled particles or robots have been studied extensively over the past decades but the mechanisms involved in the transition from chaos to order remain unclear. Here, the interactions, that in most systems give rise to chaos, sustain order. In this thesis we investigate mechanisms that preserve, destabilize or lead to the ordered state. We show that endothelial cells migrating in circular confinements transition to a collective rotating state and concomitantly synchronize the frequencies of nucleating actin waves within individual cells. Consequently, the frequency dependent cell migration speed uniformizes across the population. Complementary to the WAVE dependent nucleation of traveling actin waves, we show that in leukocytes the actin polymerization depending on WASp generates pushing forces locally at stationary patches. Next, in pipe flows, we study methods to disrupt the self–sustaining cycle of turbulence and therefore relaminarize the flow. While we find in pulsating flow conditions that turbulence emerges through a helical instability during the decelerating phase. Finally, we show quantitatively in brain slices of mice that wild-type control neurons can compensate the migratory deficits of a genetically modified neuronal sub–population in the developing cortex. AU - Riedl, Michael ID - 12726 SN - 2663-337X TI - Synchronization in collectively moving active matter ER - TY - THES AB - Most motions of many-body systems at any scale in nature with sufficient degrees of freedom tend to be chaotic; reaching from the orbital motion of planets, the air currents in our atmosphere, down to the water flowing through our pipelines or the movement of a population of bacteria. To the observer it is therefore intriguing when a moving collective exhibits order. Collective motion of flocks of birds, schools of fish or swarms of self-propelled particles or robots have been studied extensively over the past decades but the mechanisms involved in the transition from chaos to order remain unclear. Here, the interactions, that in most systems give rise to chaos, sustain order. In this thesis we investigate mechanisms that preserve, destabilize or lead to the ordered state. We show that endothelial cells migrating in circular confinements transition to a collective rotating state and concomitantly synchronize the frequencies of nucleating actin waves within individual cells. Consequently, the frequency dependent cell migration speed uniformizes across the population. Complementary to the WAVE dependent nucleation of traveling actin waves, we show that in leukocytes the actin polymerization depending on WASp generates pushing forces locally at stationary patches. Next, in pipe flows, we study methods to disrupt the self--sustaining cycle of turbulence and therefore relaminarize the flow. While we find in pulsating flow conditions that turbulence emerges through a helical instability during the decelerating phase. Finally, we show quantitatively in brain slices of mice that wild-type control neurons can compensate the migratory deficits of a genetically modified neuronal sub--population in the developing cortex. AU - Riedl, Michael ID - 14530 KW - Synchronization KW - Collective Movement KW - Active Matter KW - Cell Migration KW - Active Colloids SN - 2663 - 337X TI - Synchronization in collectively moving active matter ER - TY - THES AB - Superconductor-semiconductor heterostructures currently capture a significant amount of research interest and they serve as the physical platform in many proposals towards topological quantum computation. Despite being under extensive investigations, historically using transport techniques, the basic properties of the interface between the superconductor and the semiconductor remain to be understood. In this thesis, two separate studies on the Al-InAs heterostructures are reported with the first focusing on the physics of the material motivated by the emergence of a new phase, the Bogoliubov-Fermi surface. The second focuses on a technological application, a gate-tunable Josephson parametric amplifier. In the first study, we investigate the hypothesized unconventional nature of the induced superconductivity at the interface between the Al thin film and the InAs quantum well. We embed a two-dimensional Al-InAs hybrid system in a resonant microwave circuit allowing measurements of change in inductance. The behaviour of the resonance in a range of temperature and in-plane magnetic field has been studied and compared with the theory of conventional s-wave superconductor and a two-component theory that includes both contribution of the $s$-wave pairing in Al and the intraband $p \pm ip$ pairing in InAs. Measuring the temperature dependence of resonant frequency, no discrepancy is found between data and the conventional theory. We observe the breakdown of superconductivity due to an applied magnetic field which contradicts the conventional theory. In contrast, the data can be captured quantitatively by fitting to a two-component model. We find the evidence of the intraband $p \pm ip$ pairing in the InAs and the emergence of the Bogoliubov-Fermi surfaces due to magnetic field with the characteristic value $B^* = 0.33~\mathrm{T}$. From the fits, the sheet resistance of Al, the carrier density and mobility in InAs are determined. By systematically studying the anisotropy of the circuit response, we find weak anisotropy for $B < B^*$ and increasingly strong anisotropy for $B > B^*$ resulting in a pronounced two-lobe structure in polar plot of frequency versus field angle. Strong resemblance between the field dependence of dissipation and superfluid density hints at a hidden signature of the Bogoliubov-Fermi surface that is burried in the dissipation data. In the second study, we realize a parametric amplifier with a Josephson field effect transistor as the active element. The device's modest construction consists of a gated SNS weak link embedded at the center of a coplanar waveguide resonator. By applying a gate voltage, the resonant frequency is field-effect tunable over a range of 2 GHz. Modelling the JoFET minimally as a parallel RL circuit, the dissipation introduced by the JoFET can be quantitatively related to the gate voltage. We observed gate-tunable Kerr nonlinearity qualitatively in line with expectation. The JoFET amplifier has 20 dB of gain, 4 MHz of instantaneous bandwidth, and a 1dB compression point of -125.5 dBm when operated at a fixed resonant frequency. In general, the signal-to-noise ratio is improved by 5-7 dB when the JoFET amplifier is activated compared. The noise of the measurement chain and insertion loss of relevant circuit elements are calibrated to determine the expected and the real noise performance of the JoFET amplifier. As a quantification of the noise performance, the measured total input-referred noise of the JoFET amplifier is in good agreement with the estimated expectation which takes device loss into account. We found that the noise performance of the device reported in this document approaches one photon of total input-referred added noise which is the quantum limit imposed in nondegenerate parametric amplifier. AU - Phan, Duc T ID - 14547 KW - superconductor-semiconductor KW - superconductivity KW - Al KW - InAs KW - p-wave KW - superconductivity KW - JPA KW - microwave SN - 2663 - 337X TI - Resonant microwave spectroscopy of Al-InAs ER - TY - THES AB - Females and males across species are subject to divergent selective pressures arising from di↵erent reproductive interests and ecological niches. This often translates into a intricate array of sex-specific natural and sexual selection on traits that have a shared genetic basis between both sexes, causing a genetic sexual conflict. The resolution of this conflict mostly relies on the evolution of sex-specific expression of the shared genes, leading to phenotypic sexual dimorphism. Such sex-specific gene expression is thought to evolve via modifications of the genetic networks ultimately linked to sex-determining transcription factors. Although much empirical and theoretical evidence supports this standard picture of the molecular basis of sexual conflict resolution, there still are a few open questions regarding the complex array of selective forces driving phenotypic di↵erentiation between the sexes, as well as the molecular mechanisms underlying sexspecific adaptation. I address some of these open questions in my PhD thesis. First, how do patterns of phenotypic sexual dimorphism vary within populations, as a response to the temporal and spatial changes in sex-specific selective forces? To tackle this question, I analyze the patterns of sex-specific phenotypic variation along three life stages and across populations spanning the whole geographical range of Rumex hastatulus, a wind-pollinated angiosperm, in the first Chapter of the thesis. Second, how do gene expression patterns lead to phenotypic dimorphism, and what are the molecular mechanisms underlying the observed transcriptomic variation? I address this question by examining the sex- and tissue-specific expression variation in newly-generated datasets of sex-specific expression in heads and gonads of Drosophila melanogaster. I additionally used two complementary approaches for the study of the genetic basis of sex di↵erences in gene expression in the second and third Chapters of the thesis. Third, how does intersex correlation, thought to be one of the main aspects constraining the ability for the two sexes to decouple, interact with the evolution of sexual dimorphism? I develop models of sex-specific stabilizing selection, mutation and drift to formalize common intuition regarding the patterns of covariation between intersex correlation and sexual dimorphism in the fourth Chapter of the thesis. Alltogether, the work described in this PhD thesis provides useful insights into the links between genetic, transcriptomic and phenotypic layers of sex-specific variation, and contributes to our general understanding of the dynamics of sexual dimorphism evolution. AU - Puixeu Sala, Gemma ID - 14058 SN - 2663-337X TI - The molecular basis of sexual dimorphism: Experimental and theoretical characterization of phenotypic, transcriptomic and genetic patterns of sex-specific adaptation ER - TY - THES AU - Sack, Stefan ID - 14622 SN - 2663 - 337X TI - Improving variational quantum algorithms: Innovative initialization techniques and extensions to qudit systems ER - TY - THES AU - Stopp, Julian A ID - 14697 SN - 2663 - 337X TI - Neutrophils on the hunt: Migratory strategies employed by neutrophils to fulfill their effector function ER - TY - THES AB - For self-incompatibility (SI) to be stable in a population, theory predicts that sufficient inbreeding depression (ID) is required: the fitness of offspring from self-mated individuals must be low enough to prevent the spread of self-compatibility (SC). Reviews of natural plant populations have supported this theory, with SI species generally showing high levels of ID. However, there is thought to be an under-sampling of self-incompatible taxa in the current literature. In this thesis, I study inbreeding depression in the SI plant species Antirrhinum majus using both greenhouse crosses and a large collected field dataset. Additionally, the gametophytic S-locus of A. majus is highly heterozygous and polymorphic, thus making assembly and discovery of S-alleles very difficult. Here, 206 new alleles of the male component SLFs are presented, along with a phylogeny showing the high conservation with alleles from another Antirrhinum species. Lastly, selected sites within the protein structure of SLFs are investigated, with one site in particular highlighted as potentially being involved in the SI recognition mechanism. AU - Arathoon, Louise S ID - 14651 SN - 2663 - 337X TI - Investigating inbreeding depression and the self-incompatibility locus of Antirrhinum majus ER - TY - THES AB - Stochastic systems provide a formal framework for modelling and quantifying uncertainty in systems and have been widely adopted in many application domains. Formal verification and control of finite state stochastic systems, a subfield of formal methods also known as probabilistic model checking, is well studied. In contrast, formal verification and control of infinite state stochastic systems have received comparatively less attention. However, infinite state stochastic systems commonly arise in practice. For instance, probabilistic models that contain continuous probability distributions such as normal or uniform, or stochastic dynamical systems which are a classical model for control under uncertainty, both give rise to infinite state systems. The goal of this thesis is to contribute to laying theoretical and algorithmic foundations of fully automated formal verification and control of infinite state stochastic systems, with a particular focus on systems that may be executed over a long or infinite time. We consider formal verification of infinite state stochastic systems in the setting of static analysis of probabilistic programs and formal control in the setting of controller synthesis in stochastic dynamical systems. For both problems, we present some of the first fully automated methods for probabilistic (a.k.a. quantitative) reachability and safety analysis applicable to infinite time horizon systems. We also advance the state of the art of probability 1 (a.k.a. qualitative) reachability analysis for both problems. Finally, for formal controller synthesis in stochastic dynamical systems, we present a novel framework for learning neural network control policies in stochastic dynamical systems with formal guarantees on correctness with respect to quantitative reachability, safety or reach-avoid specifications. AU - Zikelic, Dorde ID - 14539 SN - 2663 - 337X TI - Automated verification and control of infinite state stochastic systems ER - TY - THES AB - Within the human body, the brain exhibits the highest rate of energy consumption amongst all organs, with the majority of generated ATP being utilized to sustain neuronal activity. Therefore, the metabolism of the mature cerebral cortex is geared towards preserving metabolic homeostasis whilst generating significant amounts of energy. This requires a precise interplay between diverse metabolic pathways, spanning from a tissue-wide scale to the level of individual neurons. Disturbances to this delicate metabolic equilibrium, such as those resulting from maternal malnutrition or mutations affecting metabolic enzymes, often result in neuropathological variants of neurodevelopment. For instance, mutations in SLC7A5, a transporter of metabolically essential large neutral amino acids (LNAAs), have been associated with autism and microcephaly. However, despite recent progress in the field, the extent of metabolic restructuring that occurs within the developing brain and the corresponding alterations in nutrient demands during various critical periods remain largely unknown. To investigate this, we performed metabolomic profiling of the murine cerebral cortex to characterize the metabolic state of the forebrain at different developmental stages. We found that the developing cortex undergoes substantial metabolic reprogramming, with specific sets of metabolites displaying stage-specific changes. According to our observations, we determined a distinct temporal period in postnatal development during which the cortex displays heightened reliance on LNAAs. Hence, using a conditional knock-out mouse model, we deleted Slc7a5 in neural cells, allowing us to monitor the impact of a perturbed neuronal metabolic state across multiple developmental stages of corticogenesis. We found that manipulating the levels of essential LNAAs in cortical neurons in vivo affects one particular perinatal developmental period critical for cortical network refinement. Abnormally low intracellular LNAA levels result in cell-autonomous alterations in neuronal lipid metabolism, excitability, and survival during this particular time window. Although most of the effects of Slc7a5 deletion on neuronal physiology are transient, derailment of these processes during this brief but crucial window leads to long-term circuit dysfunction in mice. In conclusion, out data indicate that the cerebral cortex undergoes significant metabolic reorganization during development. This process involves the intricate integration of multiple metabolic pathways to ensure optimal neuronal function throughout different developmental stages. Our findings offer a paradigm for understanding how neurons synchronize the expression of nutrient-related genes with their activity to allow proper brain maturation. Further, our results demonstrate that disruptions in these precisely calibrated metabolic processes during critical periods of brain development may result in neuropathological outcomes in mice and in humans. AU - Knaus, Lisa ID - 13107 SN - 2663 - 337X TI - The metabolism of the developing brain : How large neutral amino acids modulate perinatal neuronal excitability and survival ER - TY - THES AB - Cell division in Escherichia coli is performed by the divisome, a multi-protein complex composed of more than 30 proteins. The divisome spans from the cytoplasm through the inner membrane to the cell wall and the outer membrane. Divisome assembly is initiated by a cytoskeletal structure, the so-called Z-ring, which localizes at the center of the E. coli cell and determines the position of the future cell septum. The Z-ring is composed of the highly conserved bacterial tubulin homologue FtsZ, which forms treadmilling filaments. These filaments are recruited to the inner membrane by FtsA, a highly conserved bacterial actin homologue. FtsA interacts with other proteins in the periplasm and thus connects the cytoplasmic and periplasmic components of the divisome. A previous model postulated that FtsA regulates maturation of the divisome by switching from an oligomeric, inactive state to a monomeric and active state. This model was based mostly on in vivo studies, as a biochemical characterization of FtsA has been hampered by difficulties in purifying the protein. Here, we studied FtsA using an in vitro reconstitution approach and aimed to answer two questions: (i) How are dynamics from cytoplasmic, treadmilling FtsZ filaments coupled to proteins acting in the periplasmic space and (ii) How does FtsA regulate the maturation of the divisome? We found that the cytoplasmic peptides of the transmembrane proteins FtsN and FtsQ interact directly with FtsA and can follow the spatiotemporal signal of FtsA/Z filaments. When we investigated the underlying mechanism by imaging single molecules of FtsNcyto, we found the peptide to interact transiently with FtsA. An in depth analysis of the single molecule trajectories helped to postulate a model where PG synthases follow the dynamics of FtsZ by a diffusion and capture mechanism. Following up on these findings we were interested in how the self-interaction of FtsA changes when it encounters FtsNcyto and if we can confirm the proposed oligomer-monomer switch. For this, we compared the behavior of the previously identified, hyperactive mutant FtsA R286W with wildtype FtsA. The mutant outperforms WT in mirroring and transmitting the spatiotemporal signal of treadmilling FtsZ filaments. Surprisingly however, we found that this was not due to a difference in the self-interaction strength of the two variants, but a difference in their membrane residence time. Furthermore, in contrast to our expectations, upon binding of FtsNcyto the measured self-interaction of FtsA actually increased. We propose that FtsNcyto induces a rearrangement of the oligomeric architecture of FtsA. In further consequence this change leads to more persistent FtsZ filaments which results in a defined signalling zone, allowing formation of the mature divisome. The observed difference between FtsA WT and R286W is due to the vastly different membrane turnover of the proteins. R286W cycles 5-10x faster compared to WT which allows to sample FtsZ filaments at faster frequencies. These findings can explain the observed differences in toxicity for overexpression of FtsA WT and R286W and help to understand how FtsA regulates divisome maturation. AU - Radler, Philipp ID - 14280 KW - Cell Division KW - Reconstitution KW - FtsZ KW - FtsA KW - Divisome KW - E.coli SN - 2663-337X TI - Spatiotemporal signaling during assembly of the bacterial divisome ER - TY - THES AB - Semiconductor-superconductor hybrid systems are the harbour of many intriguing mesoscopic phenomena. This material combination leads to spatial variations of the superconducting properties, which gives rise to Andreev bound states (ABSs). Some of these states might exhibit remarkable properties that render them highly desirable for topological quantum computing. The most prominent and hunted of such states are Majorana zero modes (MZMs), quasiparticles equals to their own quasiparticles that they follow non-abelian statistics. In this thesis, we first introduce the general framework of such hybrid systems and, then, we unveil a series of mesoscopic phenomena that we discovered. Firstly, we show tunneling spectroscopy experiments on full-shell nanowires (NWs) showing that unwanted quantum-dot states coupled to superconductors (Yu-Shiba-Rusinov states) can mimic MZMs signatures. Then, we introduce a novel protocol which allowed the integration of tunneling spectroscopy with Coulomb spectroscopy within the same device. Employing this approach on both full-shell NWs and partial-shell NWs, we demonstrated that longitudinally confined states reveal charge transport phenomenology similar to the one expected for MZMs. These findings shed light on the intricate interplay between superconductivity and quantum confinement, which brought us to explore another material platform, i.e. a two-dimensional Germanium hole gas. After developing a robust way to induce superconductivity in such system, we showed how to engineer the proximity effect and we revealed a superconducting hard gap. Finally, we created a superconducting radio frequency driven ideal diode and a generator of non-sinusoidal current-phase relations. Our results open the path for the exploration of protected superconducting qubits and more complex hybrid devices in planar Germanium, like Kitaev chains and hybrid qubit devices. AU - Valentini, Marco ID - 13286 SN - 2663 - 337X TI - Mesoscopic phenomena in hybrid semiconductor-superconductor nanodevices : From full-shell nanowires to two-dimensional hole gas in germanium ER - TY - THES AB - Social insects fight disease using their individual immune systems and the cooperative sanitary behaviors of colony members. These social defenses are well explored against externally-infecting pathogens, but little is known about defense strategies against internally-infecting pathogens, such as viruses. Viruses are ubiquitous and in the last decades it has become evident that also many ant species harbor viruses. We present one of the first studies addressing transmission dynamics and collective disease defenses against viruses in ants on a mechanistic level. I successfully established an experimental ant host – viral pathogen system as a model for the defense strategies used by social insects against internal pathogen infections, as outlined in the third chapter. In particular, we studied how garden ants (Lasius neglectus) defend themselves and their colonies against the generalist insect virus CrPV (cricket paralysis virus). We chose microinjections of virus directly into the ants’ hemolymph because it allowed us to use a defined exposure dose. Here we show that this is a good model system, as the virus is replicating and thus infecting the host. The ants mount a clear individual immune response against the viral infection, which is characterized by a specific siRNA pattern, namely siRNAs mapping against the viral genome with a peak of 21 and 22 bp long fragments. The onset of this immune response is consistent with the timeline of viral replication that starts already within two days post injection. The disease manifests in decreased survival over a course of two to three weeks. Regarding group living, we find that infected ants show a strong individual immune response, but that their course of disease is little affected by nestmate presence, as described in chapter four. Hence, we do not find social immunity in the context of viral infections in ants. Nestmates, however, can contract the virus. Using Drosophila S2R+ cells in culture, we showed that 94 % of the nestmates contract active virus within four days of social contact to an infected individual. Virus is transmitted in low doses, thus not causing disease transmission within the colony. While virus can be transmitted during short direct contacts, we also assume transmission from deceased ants and show that the nestmates’ immune system gets activated after contracting a low viral dose. We find considerable potential for indirect transmission via the nest space. Virus is shed to the nest, where it stays viable for one week and is also picked up by other ants. Apart from that, we want to underline the potential of ant poison as antiviral agent. We determined that ant poison successfully inactivates CrPV in vitro. However, we found no evidence for effective poison use to sanitize the nest space. On the other hand, local application of ant poison by oral poison uptake, which is part of the ants prophylactic behavioral repertoire, probably contributes to keeping the gut of each individual sanitized. We hypothesize that oral poison uptake might be the reason why we did not find viable virus in the trophallactic fluid. The fifth chapter encompasses preliminary data on potential social immunization. However, our experiments do not confirm an actual survival benefit for the nestmates upon pathogen challenge under the given experimental settings. Nevertheless, we do not want to rule out the possibility for nestmate immunization, but rather emphasize that considering different experimental timelines and viral doses would provide a multitude of options for follow-up experiments. In conclusion, we find that prophylactic individual behaviors, such as oral poison uptake, might play a role in preventing viral disease transmission. Compared to colony defense against external pathogens, internal pathogen infections require a stronger component of individual physiological immunity than behavioral social immunity, yet could still lead to collective protection. AU - Franschitz, Anna ID - 13984 SN - 2663 - 337X TI - Individual and social immunity against viral infections in ants ER - TY - THES AB - Morphogens are signaling molecules that are known for their prominent role in pattern formation within developing tissues. In addition to patterning, morphogens also control tissue growth. However, the underlying mechanisms are poorly understood. We studied the role of morphogens in regulating tissue growth in the developing vertebrate neural tube. In this system, opposing morphogen gradients of Shh and BMP establish the dorsoventral pattern of neural progenitor domains. Perturbations in these morphogen pathways result in alterations in tissue growth and cell cycle progression, however, it has been unclear what cellular process is affected. To address this, we analysed the rates of cell proliferation and cell death in mouse mutants in which signaling is perturbed, as well as in chick neural plate explants exposed to defined concentrations of signaling activators or inhibitors. Our results indicated that the rate of cell proliferation was not altered in these assays. By contrast, both the Shh and BMP signaling pathways had profound effects on neural progenitor survival. Our results indicate that these pathways synergise to promote cell survival within neural progenitors. Consistent with this, we found that progenitors within the intermediate region of the neural tube, where the combined levels of Shh and BMP are the lowest, are most prone to cell death when signaling activity is inhibited. In addition, we found that downregulation of Shh results in increased apoptosis within the roof plate, which is the dorsal source of BMP ligand production. This revealed a cross-interaction between the Shh and BMP morphogen signaling pathways that may be relevant for understanding how gradients scale in neural tubes with different overall sizes. We further studied the mechanism acting downstream of Shh in cell survival regulation using genetic and genomic approaches. We propose that Shh transcriptionally regulates a non-canonical apoptotic pathway. Altogether, our study points to a novel role of opposing morphogen gradients in tissue size regulation and provides new insights into complex interactions between Shh and BMP signaling gradients in the neural tube. AU - Kuzmicz-Kowalska, Katarzyna ID - 14323 SN - 2663 - 337X TI - Regulation of neural progenitor survival by Shh and BMP in the developing spinal cord ER - TY - THES AU - Hennessey-Wesen, Mike ID - 14641 KW - microfluidics KW - miceobiology KW - mutations KW - quorum sensing SN - 2663 - 337X TI - Adaptive mutation in E. coli modulated by luxS ER - TY - THES AB - This thesis concerns the application of variational methods to the study of evolution problems arising in fluid mechanics and in material sciences. The main focus is on weak-strong stability properties of some curvature driven interface evolution problems, such as the two-phase Navier–Stokes flow with surface tension and multiphase mean curvature flow, and on the phase-field approximation of the latter. Furthermore, we discuss a variational approach to the study of a class of doubly nonlinear wave equations. First, we consider the two-phase Navier–Stokes flow with surface tension within a bounded domain. The two fluids are immiscible and separated by a sharp interface, which intersects the boundary of the domain at a constant contact angle of ninety degree. We devise a suitable concept of varifolds solutions for the associated interface evolution problem and we establish a weak-strong uniqueness principle in case of a two dimensional ambient space. In order to focus on the boundary effects and on the singular geometry of the evolving domains, we work for simplicity in the regime of same viscosities for the two fluids. The core of the thesis consists in the rigorous proof of the convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow for a suitable class of multi- well potentials and for well-prepared initial data. We even establish a rate of convergence. Our relative energy approach relies on the concept of gradient-flow calibration for branching singularities in multiphase mean curvature flow and thus enables us to overcome the limitations of other approaches. To the best of the author’s knowledge, our result is the first quantitative and unconditional one available in the literature for the vectorial/multiphase setting. This thesis also contains a first study of weak-strong stability for planar multiphase mean curvature flow beyond the singularity resulting from a topology change. Previous weak-strong results are indeed limited to time horizons before the first topology change of the strong solution. We consider circular topology changes and we prove weak-strong stability for BV solutions to planar multiphase mean curvature flow beyond the associated singular times by dynamically adapting the strong solutions to the weak one by means of a space-time shift. In the context of interface evolution problems, our proofs for the main results of this thesis are based on the relative energy technique, relying on novel suitable notions of relative energy functionals, which in particular measure the interface error. Our statements follow from the resulting stability estimates for the relative energy associated to the problem. At last, we introduce a variational approach to the study of nonlinear evolution problems. This approach hinges on the minimization of a parameter dependent family of convex functionals over entire trajectories, known as Weighted Inertia-Dissipation-Energy (WIDE) functionals. We consider a class of doubly nonlinear wave equations and establish the convergence, up to subsequences, of the associated WIDE minimizers to a solution of the target problem as the parameter goes to zero. AU - Marveggio, Alice ID - 14587 SN - 2663 - 337X TI - Weak-strong stability and phase-field approximation of interface evolution problems in fluid mechanics and in material sciences ER - TY - THES AB - The extracellular matrix (ECM) is a hydrated and complex three-dimensional network consisting of proteins, polysaccharides, and water. It provides structural scaffolding for the cells embedded within it and is essential in regulating numerous physiological processes, including cell migration and proliferation, wound healing, and stem cell fate. Despite extensive study, detailed structural knowledge of ECM components in physiologically relevant conditions is still rudimentary. This is due to methodological limitations in specimen preparation protocols which are incompatible with keeping large samples, such as the ECM, in their native state for subsequent imaging. Conventional electron microscopy (EM) techniques rely on fixation, dehydration, contrasting, and sectioning. This results in the alteration of a highly hydrated environment and the potential introduction of artifacts. Other structural biology techniques, such as nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography, allow high-resolution analysis of protein structures but only work on homogenous and purified samples, hence lacking contextual information. Currently, no approach exists for the ultrastructural and structural study of extracellular components under native conditions in a physiological, 3D environment. In this thesis, I have developed a workflow that allows for the ultrastructural analysis of the ECM in near-native conditions at molecular resolution. The developments I introduced include implementing a novel specimen preparation workflow for cell-derived matrices (CDMs) to render them compatible with ion-beam milling and subsequent high-resolution cryo-electron tomography (ET). To this end, I have established protocols to generate CDMs grown over several weeks on EM grids that are compatible with downstream cryo-EM sample preparation and imaging techniques. Characterization of these ECMs confirmed that they contain essential ECM components such as collagen I, collagen VI, and fibronectin I in high abundance and hence represent a bona fide biologically-relevant sample. I successfully optimized vitrification of these specimens by testing various vitrification techniques and cryoprotectants. In order to obtain high-resolution molecular insights into the ultrastructure and organization of CDMs, I established cryo-focused ion beam scanning electron microscopy (FIBSEM) on these challenging and complex specimens. I explored different approaches for the creation of thin cryo-lamellae by FIB milling and succeeded in optimizing the cryo-lift-out technique, resulting in high-quality lamellae of approximately 200 nm thickness. High-resolution Cryo-ET of these lamellae revealed for the first time the architecture of native CDM in the context of matrix-secreting cells. This allowed for the in situ visualization of fibrillar matrix proteins such as collagen, laying the foundation for future structural and ultrastructural characterization of these proteins in their near-native environment. In summary, in this thesis, I present a novel workflow that combines state-of-the-art cryo-EM specimen preparation and imaging technologies to permit characterization of the ECM, an important tissue component in higher organisms. This innovative and highly versatile workflow will enable addressing far-reaching questions on ECM architecture, composition, and reciprocal ECM-cell interactions. AU - Zens, Bettina ID - 12491 KW - cryo-EM KW - cryo-ET KW - FIB milling KW - method development KW - FIBSEM KW - extracellular matrix KW - ECM KW - cell-derived matrices KW - CDMs KW - cell culture KW - high pressure freezing KW - HPF KW - structural biology KW - tomography KW - collagen SN - 2663-337X TI - Ultrastructural characterization of natively preserved extracellular matrix by cryo-electron tomography ER - TY - THES AB - We introduce the notion of a Faustian interchange in a 1-parameter family of smooth functions to generalize the medial axis to critical points of index larger than 0. We construct and implement a general purpose algorithm for approximating such generalized medial axes. AU - Stephenson, Elizabeth R ID - 14226 SN - 2791-4585 TI - Generalizing medial axes with homology switches ER - TY - THES AB - The brain is an exceptionally sophisticated organ consisting of billions of cells and trillions of connections that orchestrate our cognition and behavior. To decode its complex connectivity, it is pivotal to disentangle its intricate architecture spanning from cm-sized circuits down to tens of nm-small synapses. To achieve this goal, I developed CATS – Comprehensive Analysis of nervous Tissue across Scales, a versatile toolbox for obtaining a holistic view of nervous tissue context with (superresolution) fluorescence microscopy. CATS combines comprehensive labeling of the extracellular space, that is compatible with chemical fixation, with information on molecular markers, superresolved data acquisition and machine-learning based data analysis for segmentation and synapse identification. I used CATS to analyze key features of nervous tissue connectivity, ranging from whole tissue architecture, neuronal in- and output-fields, down to synapse morphology. Focusing on the hippocampal circuitry, I quantified synaptic transmission properties of mossy fiber boutons and analyzed the connectivity pattern of dentate gyrus granule cells with CA3 pyramidal neurons. This shows that CATS is a viable tool to study hallmarks of neuronal connectivity with light microscopy. AU - Michalska, Julia M ID - 12470 SN - 2663-337X TI - A versatile toolbox for the comprehensive analysis of nervous tissue organization with light microscopy ER - TY - THES AB - All visual experiences of the vertebrates begin with light being converted into electrical signals by the eye retina. Retinal ganglion cells (RGCs) are the neurons of the innermost layer of the mammal retina, and they transmit visual information to the rest of the brain. It has been shown that RGCs vary in their morphology and genetic profiles, moreover they can be unambiguously grouped into subtypes that share the same morphological and/or molecular properties. However, in terms of RGCs function, it remains unclear how many distinct types there are and what response properties their typology relies on. Even given the recent studies that successfully classified RGCs in a patch of the retina [1] and in scotopic conditions [2], the question remains whether the found subtypes persist across the entire retina. In this work, using a novel imaging method, we show that, when sampled from a large portion of the retina, RGCs can not be clearly divided into functional subtypes. We found that in photopic conditions, which implies more prominent natural scene statistic differences across the visual field, response properties can be exhibited by cells differently depending on their location in the retina, which leads to formation of a gradient of features rather than distinct classes. This finding suggests that RGCs follow a global organization across the visual field of the animal, adapting each RGC subtype to the requirements imposed by the natural scene statistics. AU - Kirillova, Kseniia ID - 12531 SN - 2791-4585 TI - Panoramic functional gradients across the mouse retina ER - TY - THES AB - The evolutionary processes that brought about today’s plethora of living species and the many billions more ancient ones all underlie biology. Evolutionary pathways are neither directed nor deterministic, but rather an interplay between selection, migration, mutation, genetic drift and other environmental factors. Hybrid zones, as natural crossing experiments, offer a great opportunity to use cline analysis to deduce different evolutionary processes - for example, selection strength. Theoretical cline models, largely assuming uniform distribution of individuals, often lack the capability of incorporating population structure. Since in reality organisms mostly live in patchy distributions and their dispersal is hardly ever Gaussian, it is necessary to unravel the effect of these different elements of population structure on cline parameters and shape. In this thesis, I develop a simulation inspired by the A. majus hybrid zone of a single selected locus under frequency dependent selection. This simulation enables us to untangle the effects of different elements of population structure as for example a low-density center and long-range dispersal. This thesis is therefore a first step towards theoretically untangling the effects of different elements of population structure on cline parameters and shape. AU - Julseth, Mara ID - 12800 SN - 2791-4585 TI - The effect of local population structure on genetic variation at selected loci in the A. majus hybrid zone ER - TY - THES AU - Gnyliukh, Nataliia ID - 14510 KW - Clathrin-Mediated Endocytosis KW - vesicle scission KW - Dynamin-Related Protein 2 KW - SH3P2 KW - TPLATE complex KW - Total internal reflection fluorescence microscopy KW - Arabidopsis thaliana SN - 2663-337X TI - Mechanism of clathrin-coated vesicle formation during endocytosis in plants ER - TY - THES AB - Inverse design problems in fabrication-aware shape optimization are typically solved on discrete representations such as polygonal meshes. This thesis argues that there are benefits to treating these problems in the same domain as human designers, namely, the parametric one. One reason is that discretizing a parametric model usually removes the capability of making further manual changes to the design, because the human intent is captured by the shape parameters. Beyond this, knowledge about a design problem can sometimes reveal a structure that is present in a smooth representation, but is fundamentally altered by discretizing. In this case, working in the parametric domain may even simplify the optimization task. We present two lines of research that explore both of these aspects of fabrication-aware shape optimization on parametric representations. The first project studies the design of plane elastic curves and Kirchhoff rods, which are common mathematical models for describing the deformation of thin elastic rods such as beams, ribbons, cables, and hair. Our main contribution is a characterization of all curved shapes that can be attained by bending and twisting elastic rods having a stiffness that is allowed to vary across the length. Elements like these can be manufactured using digital fabrication devices such as 3d printers and digital cutters, and have applications in free-form architecture and soft robotics. We show that the family of curved shapes that can be produced this way admits geometric description that is concise and computationally convenient. In the case of plane curves, the geometric description is intuitive enough to allow a designer to determine whether a curved shape is physically achievable by visual inspection alone. We also present shape optimization algorithms that convert a user-defined curve in the plane or in three dimensions into the geometry of an elastic rod that will naturally deform to follow this curve when its endpoints are attached to a support structure. Implemented in an interactive software design tool, the rod geometry is generated in real time as the user edits a curve and enables fast prototyping. The second project tackles the problem of general-purpose shape optimization on CAD models using a novel variant of the extended finite element method (XFEM). Our goal is the decoupling between the simulation mesh and the CAD model, so no geometry-dependent meshing or remeshing needs to be performed when the CAD parameters change during optimization. This is achieved by discretizing the embedding space of the CAD model, and using a new high-accuracy numerical integration method to enable XFEM on free-form elements bounded by the parametric surface patches of the model. Our simulation is differentiable from the CAD parameters to the simulation output, which enables us to use off-the-shelf gradient-based optimization procedures. The result is a method that fits seamlessly into the CAD workflow because it works on the same representation as the designer, enabling the alternation of manual editing and fabrication-aware optimization at will. AU - Hafner, Christian ID - 12897 SN - 2663-337X TI - Inverse shape design with parametric representations: Kirchhoff Rods and parametric surface models ER - TY - THES AB - In this thesis, we study two of the most important questions in Arithmetic geometry: that of the existence and density of solutions to Diophantine equations. In order for a Diophantine equation to have any solutions over the rational numbers, it must have solutions everywhere locally, i.e., over R and over Qp for every prime p. The converse, called the Hasse principle, is known to fail in general. However, it is still a central question in Arithmetic geometry to determine for which varieties the Hasse principle does hold. In this work, we establish the Hasse principle for a wide new family of varieties of the form f(t) = NK/Q(x) ̸= 0, where f is a polynomial with integer coefficients and NK/Q denotes the norm form associated to a number field K. Our results cover products of arbitrarily many linear, quadratic or cubic factors, and generalise an argument of Irving [69], which makes use of the beta sieve of Rosser and Iwaniec. We also demonstrate how our main sieve results can be applied to treat new cases of a conjecture of Harpaz and Wittenberg on locally split values of polynomials over number fields, and discuss consequences for rational points in fibrations. In the second question, about the density of solutions, one defines a height function and seeks to estimate asymptotically the number of points of height bounded by B as B → ∞. Traditionally, one either counts rational points, or integral points with respect to a suitable model. However, in this thesis, we study an emerging area of interest in Arithmetic geometry known as Campana points, which in some sense interpolate between rational and integral points. More precisely, we count the number of nonzero integers z1, z2, z3 such that gcd(z1, z2, z3) = 1, and z1, z2, z3, z1 + z2 + z3 are all squareful and bounded by B. Using the circle method, we obtain an asymptotic formula which agrees in the power of B and log B with a bold new generalisation of Manin’s conjecture to the setting of Campana points, recently formulated by Pieropan, Smeets, Tanimoto and Várilly-Alvarado [96]. However, in this thesis we also provide the first known counterexamples to leading constant predicted by their conjecture. AU - Shute, Alec L ID - 12072 SN - 2663-337X TI - Existence and density problems in Diophantine geometry: From norm forms to Campana points ER - TY - THES AB - In this dissertation we study coboundary expansion of simplicial complex with a view of giving geometric applications. Our main novel tool is an equivariant version of Gromov's celebrated Topological Overlap Theorem. The equivariant topological overlap theorem leads to various geometric applications including a quantitative non-embeddability result for sufficiently thick buildings (which partially resolves a conjecture of Tancer and Vorwerk) and an improved lower bound on the pair-crossing number of (bounded degree) expander graphs. Additionally, we will give new proofs for several known lower bounds for geometric problems such as the number of Tverberg partitions or the crossing number of complete bipartite graphs. For the aforementioned applications one is naturally lead to study expansion properties of joins of simplicial complexes. In the presence of a special certificate for expansion (as it is the case, e.g., for spherical buildings), the join of two expanders is an expander. On the flip-side, we report quite some evidence that coboundary expansion exhibits very non-product-like behaviour under taking joins. For instance, we exhibit infinite families of graphs $(G_n)_{n\in \mathbb{N}}$ and $(H_n)_{n\in\mathbb{N}}$ whose join $G_n*H_n$ has expansion of lower order than the product of the expansion constant of the graphs. Moreover, we show an upper bound of $(d+1)/2^d$ on the normalized coboundary expansion constants for the complete multipartite complex $[n]^{*(d+1)}$ (under a mild divisibility condition on $n$). Via the probabilistic method the latter result extends to an upper bound of $(d+1)/2^d+\varepsilon$ on the coboundary expansion constant of the spherical building associated with $\mathrm{PGL}_{d+2}(\mathbb{F}_q)$ for any $\varepsilon>0$ and sufficiently large $q=q(\varepsilon)$. This disproves a conjecture of Lubotzky, Meshulam and Mozes -- in a rather strong sense. By improving on existing lower bounds we make further progress towards closing the gap between the known lower and upper bounds on the coboundary expansion constants of $[n]^{*(d+1)}$. The best improvements we achieve using computer-aided proofs and flag algebras. The exact value even for the complete $3$-partite $2$-dimensional complex $[n]^{*3}$ remains unknown but we are happy to conjecture a precise value for every $n$. %Moreover, we show that a previously shown lower bound on the expansion constant of the spherical building associated with $\mathrm{PGL}_{2}(\mathbb{F}_q)$ is not tight. In a loosely structured, last chapter of this thesis we collect further smaller observations related to expansion. We point out a link between discrete Morse theory and a technique for showing coboundary expansion, elaborate a bit on the hardness of computing coboundary expansion constants, propose a new criterion for coboundary expansion (in a very dense setting) and give one way of making the folklore result that expansion of links is a necessary condition for a simplicial complex to be an expander precise. AU - Wild, Pascal ID - 11777 SN - 2663-337X TI - High-dimensional expansion and crossing numbers of simplicial complexes ER - TY - THES AB - Although we often see studies focusing on simple or even discrete traits in studies of colouration, the variation of “appearance” phenotypes found in nature is often more complex, continuous and high-dimensional. Therefore, we developed automated methods suitable for large datasets of genomes and images, striving to account for their complex nature, while minimising human bias. We used these methods on a dataset of more than 20, 000 plant SNP genomes and corresponding fower images from a hybrid zone of two subspecies of Antirrhinum majus with distinctly coloured fowers to improve our understanding of the genetic nature of the fower colour in our study system. Firstly, we use the advantage of large numbers of genotyped plants to estimate the haplotypes in the main fower colour regulating region. We study colour- and geography-related characteristics of the estimated haplotypes and how they connect to their relatedness. We show discrepancies from the expected fower colour distributions given the genotype and identify particular haplotypes leading to unexpected phenotypes. We also confrm a signifcant defcit of the double recessive recombinant and quite surprisingly, we show that haplotypes of the most frequent parental type are much less variable than others. Secondly, we introduce our pipeline capable of processing tens of thousands of full fower images without human interaction and summarising each image into a set of informative scores. We show the compatibility of these machine-measured fower colour scores with the previously used manual scores and study impact of external efect on the resulting scores. Finally, we use the machine-measured fower colour scores to ft and examine a phenotype cline across the hybrid zone in Planoles using full fower images as opposed to discrete, manual scores and compare it with the genotypic cline. AU - Matejovicova, Lenka ID - 11128 SN - 2663-337X TI - Genetic basis of flower colour as a model for adaptive evolution ER - TY - THES AB - G protein-coupled receptors (GPCRs) respond to specific ligands and regulate multiple processes ranging from cell growth and immune responses to neuronal signal transmission. However, ligands for many GPCRs remain unknown, suffer from off-target effects or have poor bioavailability. Additional challenges exist to dissect cell-type specific responses when the same GPCR is expressed on several cell types within the body. Here, we overcome these limitations by engineering DREADD-based GPCR chimeras that selectively bind their agonist clozapine-N-oxide (CNO) and mimic a GPCR-of-interest in a desired cell type. We validated our approach with β2-adrenergic receptor (β2AR/ADRB2) and show that our chimeric DREADD-β2AR triggers comparable responses on second messenger and kinase activity, post-translational modifications, and protein-protein interactions. Since β2AR is also enriched in microglia, which can drive inflammation in the central nervous system, we expressed chimeric DREADD-β2AR in primary microglia and successfully recapitulate β2AR-mediated filopodia formation through CNO stimulation. To dissect the role of selected GPCRs during microglial inflammation, we additionally generated DREADD-based chimeras for microglia-enriched GPR65 and GPR109A/HCAR2. In a microglia cell line, DREADD-β2AR and DREADD-GPR65 both modulated the inflammatory response with a similar profile as endogenously expressed β2AR, while DREADD-GPR109A showed no impact. Our DREADD-based approach provides the means to obtain mechanistic and functional insights into GPCR signaling on a cell-type specific level. AU - Schulz, Rouven ID - 11945 SN - 2663-337X TI - Chimeric G protein-coupled receptors mimic distinct signaling pathways and modulate microglia function ER - TY - THES AB - The scope of this thesis is to study quantum systems exhibiting a continuous symmetry that is broken on the level of the corresponding effective theory. In particular we are going to investigate translation-invariant Bose gases in the mean field limit, effectively described by the Hartree functional, and the Fröhlich Polaron in the regime of strong coupling, effectively described by the Pekar functional. The latter is a model describing the interaction between a charged particle and the optical modes of a polar crystal. Regarding the former, we assume in addition that the particles in the gas are unconfined, and typically we will consider particles that are subject to an attractive interaction. In both cases the ground state energy of the Hamiltonian is not a proper eigenvalue due to the underlying translation-invariance, while on the contrary there exists a whole invariant orbit of minimizers for the corresponding effective functionals. Both, the absence of proper eigenstates and the broken symmetry of the effective theory, make the study significantly more involved and it is the content of this thesis to develop a frameworks which allows for a systematic way to circumvent these issues. It is a well-established result that the ground state energy of Bose gases in the mean field limit, as well as the ground state energy of the Fröhlich Polaron in the regime of strong coupling, is to leading order given by the minimal energy of the corresponding effective theory. As part of this thesis we identify the sub-leading term in the expansion of the ground state energy, which can be interpreted as the quantum correction to the classical energy, since the effective theories under consideration can be seen as classical counterparts. We are further going to establish an asymptotic expression for the energy-momentum relation of the Fröhlich Polaron in the strong coupling limit. In the regime of suitably small momenta, this asymptotic expression agrees with the energy-momentum relation of a free particle having an effectively increased mass, and we find that this effectively increased mass agrees with the conjectured value in the physics literature. In addition we will discuss two unrelated papers written by the author during his stay at ISTA in the appendix. The first one concerns the realization of anyons, which are quasi-particles acquiring a non-trivial phase under the exchange of two particles, as molecular impurities. The second one provides a classification of those vector fields defined on a given manifold that can be written as the gradient of a given functional with respect to a suitable metric, provided that some mild smoothness assumptions hold. This classification is subsequently used to identify those quantum Markov semigroups that can be written as a gradient flow of the relative entropy. AU - Brooks, Morris ID - 12390 SN - 2663-337X TI - Translation-invariant quantum systems with effectively broken symmetry ER - TY - THES AB - Metazoan development relies on the formation and remodeling of cell-cell contacts. The binding of adhesion receptors and remodeling of the actomyosin cell cortex at cell-cell interaction sites have been implicated in cell-cell contact formation. Yet, how these two processes functionally interact to drive cell-cell contact expansion and strengthening remains unclear. Here, we study how primary germ layer progenitor cells from zebrafish bind to supported lipid bilayers (SLB) functionalized with E-cadherin ectodomains as an assay system for monitoring cell-cell contact formation at high spatiotemporal resolution. We show that cell-cell contact formation represents a two-tiered process: E-cadherinmediated downregulation of the small GTPase RhoA at the forming contact leads to both depletion of Myosin-2 and decrease of F-actin. This is followed by centrifugal actin network flows at the contact triggered by a sharp gradient of Myosin-2 at the rim of the contact zone, with Myosin-2 displaying higher cortical localization outside than inside of the contact. These centrifugal cortical actin flows, in turn, not only further dilute the actin network at the contact disc, but also lead to an accumulation of both F-actin and Ecadherin at the contact rim. Eventually, this combination of actomyosin downregulation and flows at the contact contribute to the characteristic molecular organization implicated in contact formation and maintenance: depletion of cortical actomyosin at the contact disc, driving contact expansion by lowering interfacial tension at the contact, and accumulation of both E-cadherin and F-actin at the contact rim, mechanically linking the contractile cortices of the adhering cells. Thus, using a biomimetic assay, we exemplify how adhesion signaling and cell mechanics function together to modulate the spatial organization of cell-cell contacts. AU - Arslan, Feyza N ID - 12368 SN - 2663-337X TI - Remodeling of E-cadherin-mediated contacts via cortical flows ER - TY - THES AB - Deep learning has enabled breakthroughs in challenging computing problems and has emerged as the standard problem-solving tool for computer vision and natural language processing tasks. One exception to this trend is safety-critical tasks where robustness and resilience requirements contradict the black-box nature of neural networks. To deploy deep learning methods for these tasks, it is vital to provide guarantees on neural network agents' safety and robustness criteria. This can be achieved by developing formal verification methods to verify the safety and robustness properties of neural networks. Our goal is to design, develop and assess safety verification methods for neural networks to improve their reliability and trustworthiness in real-world applications. This thesis establishes techniques for the verification of compressed and adversarially trained models as well as the design of novel neural networks for verifiably safe decision-making. First, we establish the problem of verifying quantized neural networks. Quantization is a technique that trades numerical precision for the computational efficiency of running a neural network and is widely adopted in industry. We show that neglecting the reduced precision when verifying a neural network can lead to wrong conclusions about the robustness and safety of the network, highlighting that novel techniques for quantized network verification are necessary. We introduce several bit-exact verification methods explicitly designed for quantized neural networks and experimentally confirm on realistic networks that the network's robustness and other formal properties are affected by the quantization. Furthermore, we perform a case study providing evidence that adversarial training, a standard technique for making neural networks more robust, has detrimental effects on the network's performance. This robustness-accuracy tradeoff has been studied before regarding the accuracy obtained on classification datasets where each data point is independent of all other data points. On the other hand, we investigate the tradeoff empirically in robot learning settings where a both, a high accuracy and a high robustness, are desirable. Our results suggest that the negative side-effects of adversarial training outweigh its robustness benefits in practice. Finally, we consider the problem of verifying safety when running a Bayesian neural network policy in a feedback loop with systems over the infinite time horizon. Bayesian neural networks are probabilistic models for learning uncertainties in the data and are therefore often used on robotic and healthcare applications where data is inherently stochastic. We introduce a method for recalibrating Bayesian neural networks so that they yield probability distributions over safe decisions only. Our method learns a safety certificate that guarantees safety over the infinite time horizon to determine which decisions are safe in every possible state of the system. We demonstrate the effectiveness of our approach on a series of reinforcement learning benchmarks. AU - Lechner, Mathias ID - 11362 KW - neural networks KW - verification KW - machine learning SN - 978-3-99078-017-6 TI - Learning verifiable representations ER - TY - THES AB - The polaron model is a basic model of quantum field theory describing a single particle interacting with a bosonic field. It arises in many physical contexts. We are mostly concerned with models applicable in the context of an impurity atom in a Bose-Einstein condensate as well as the problem of electrons moving in polar crystals. The model has a simple structure in which the interaction of the particle with the field is given by a term linear in the field’s creation and annihilation operators. In this work, we investigate the properties of this model by providing rigorous estimates on various energies relevant to the problem. The estimates are obtained, for the most part, by suitable operator techniques which constitute the principal mathematical substance of the thesis. The first application of these techniques is to derive the polaron model rigorously from first principles, i.e., from a full microscopic quantum-mechanical many-body problem involving an impurity in an otherwise homogeneous system. We accomplish this for the N + 1 Bose gas in the mean-field regime by showing that a suitable polaron-type Hamiltonian arises at weak interactions as a low-energy effective theory for this problem. In the second part, we investigate rigorously the ground state of the model at fixed momentum and for large values of the coupling constant. Qualitatively, the system is expected to display a transition from the quasi-particle behavior at small momenta, where the dispersion relation is parabolic and the particle moves through the medium dragging along a cloud of phonons, to the radiative behavior at larger momenta where the polaron decelerates and emits free phonons. At the same time, in the strong coupling regime, the bosonic field is expected to behave purely classically. Accordingly, the effective mass of the polaron at strong coupling is conjectured to be asymptotically equal to the one obtained from the semiclassical counterpart of the problem, first studied by Landau and Pekar in the 1940s. For polaron models with regularized form factors and phonon dispersion relations of superfluid type, i.e., bounded below by a linear function of the wavenumbers for all phonon momenta as in the interacting Bose gas, we prove that for a large window of momenta below the radiation threshold, the energy-momentum relation at strong coupling is indeed essentially a parabola with semi-latus rectum equal to the Landau–Pekar effective mass, as expected. For the Fröhlich polaron describing electrons in polar crystals where the dispersion relation is of the optical type and the form factor is formally UV–singular due to the nature of the point charge-dipole interaction, we are able to give the corresponding upper bound. In contrast to the regular case, this requires the inclusion of the quantum fluctuations of the phonon field, which makes the problem considerably more difficult. The results are supplemented by studies on the absolute ground-state energy at strong coupling, a proof of the divergence of the effective mass with the coupling constant for a wide class of polaron models, as well as the discussion of the apparent UV singularity of the Fröhlich model and the application of the techniques used for its removal for the energy estimates. AU - Mysliwy, Krzysztof ID - 11473 SN - 2663-337X TI - Polarons in Bose gases and polar crystals: Some rigorous energy estimates ER - TY - THES AB - Because of the increasing popularity of machine learning methods, it is becoming important to understand the impact of learned components on automated decision-making systems and to guarantee that their consequences are beneficial to society. In other words, it is necessary to ensure that machine learning is sufficiently trustworthy to be used in real-world applications. This thesis studies two properties of machine learning models that are highly desirable for the sake of reliability: robustness and fairness. In the first part of the thesis we study the robustness of learning algorithms to training data corruption. Previous work has shown that machine learning models are vulnerable to a range of training set issues, varying from label noise through systematic biases to worst-case data manipulations. This is an especially relevant problem from a present perspective, since modern machine learning methods are particularly data hungry and therefore practitioners often have to rely on data collected from various external sources, e.g. from the Internet, from app users or via crowdsourcing. Naturally, such sources vary greatly in the quality and reliability of the data they provide. With these considerations in mind, we study the problem of designing machine learning algorithms that are robust to corruptions in data coming from multiple sources. We show that, in contrast to the case of a single dataset with outliers, successful learning within this model is possible both theoretically and practically, even under worst-case data corruptions. The second part of this thesis deals with fairness-aware machine learning. There are multiple areas where machine learning models have shown promising results, but where careful considerations are required, in order to avoid discrimanative decisions taken by such learned components. Ensuring fairness can be particularly challenging, because real-world training datasets are expected to contain various forms of historical bias that may affect the learning process. In this thesis we show that data corruption can indeed render the problem of achieving fairness impossible, by tightly characterizing the theoretical limits of fair learning under worst-case data manipulations. However, assuming access to clean data, we also show how fairness-aware learning can be made practical in contexts beyond binary classification, in particular in the challenging learning to rank setting. AU - Konstantinov, Nikola H ID - 10799 KW - robustness KW - fairness KW - machine learning KW - PAC learning KW - adversarial learning SN - 2663-337X TI - Robustness and fairness in machine learning ER - TY - THES AB - Plant growth and development is well known to be both, flexible and dynamic. The high capacity for post-embryonic organ formation and tissue regeneration requires tightly regulated intercellular communication and coordinated tissue polarization. One of the most important drivers for patterning and polarity in plant development is the phytohormone auxin. Auxin has the unique characteristic to establish polarized channels for its own active directional cell to cell transport. This fascinating phenomenon is called auxin canalization. Those auxin transport channels are characterized by the expression and polar, subcellular localization of PIN auxin efflux carriers. PIN proteins have the ability to dynamically change their localization and auxin itself can affect this by interfering with trafficking. Most of the underlying molecular mechanisms of canalization still remain enigmatic. What is known so far is that canonical auxin signaling is indispensable but also other non-canonical signaling components are thought to play a role. In order to shed light into the mysteries auf auxin canalization this study revisits the branches of auxin signaling in detail. Further a new auxin analogue, PISA, is developed which triggers auxin-like responses but does not directly activate canonical transcriptional auxin signaling. We revisit the direct auxin effect on PIN trafficking where we found that, contradictory to previous observations, auxin is very specifically promoting endocytosis of PIN2 but has no overall effect on endocytosis. Further, we evaluate which cellular processes related to PIN subcellular dynamics are involved in the establishment of auxin conducting channels and the formation of vascular tissue. We are re-evaluating the function of AUXIN BINDING PROTEIN 1 (ABP1) and provide a comprehensive picture about its developmental phneotypes and involvement in auxin signaling and canalization. Lastly, we are focusing on the crosstalk between the hormone strigolactone (SL) and auxin and found that SL is interfering with essentially all processes involved in auxin canalization in a non-transcriptional manner. Lastly we identify a new way of SL perception and signaling which is emanating from mitochondria, is independent of canonical SL signaling and is modulating primary root growth. AU - Gallei, Michelle C ID - 11626 SN - 2663-337X TI - Auxin and strigolactone non-canonical signaling regulating development in Arabidopsis thaliana ER - TY - THES AB - The complex yarn structure of knitted and woven fabrics gives rise to both a mechanical and visual complexity. The small-scale interactions of yarns colliding with and pulling on each other result in drastically different large-scale stretching and bending behavior, introducing anisotropy, curling, and more. While simulating cloth as individual yarns can reproduce this complexity and match the quality of real fabric, it may be too computationally expensive for large fabrics. On the other hand, continuum-based approaches do not need to discretize the cloth at a stitch-level, but it is non-trivial to find a material model that would replicate the large-scale behavior of yarn fabrics, and they discard the intricate visual detail. In this thesis, we discuss three methods to try and bridge the gap between small-scale and large-scale yarn mechanics using numerical homogenization: fitting a continuum model to periodic yarn simulations, adding mechanics-aware yarn detail onto thin-shell simulations, and quantitatively fitting yarn parameters to physical measurements of real fabric. To start, we present a method for animating yarn-level cloth effects using a thin-shell solver. We first use a large number of periodic yarn-level simulations to build a model of the potential energy density of the cloth, and then use it to compute forces in a thin-shell simulator. The resulting simulations faithfully reproduce expected effects like the stiffening of woven fabrics and the highly deformable nature and anisotropy of knitted fabrics at a fraction of the cost of full yarn-level simulation. While our thin-shell simulations are able to capture large-scale yarn mechanics, they lack the rich visual detail of yarn-level simulations. Therefore, we propose a method to animate yarn-level cloth geometry on top of an underlying deforming mesh in a mechanics-aware fashion in real time. Using triangle strains to interpolate precomputed yarn geometry, we are able to reproduce effects such as knit loops tightening under stretching at negligible cost. Finally, we introduce a methodology for inverse-modeling of yarn-level mechanics of cloth, based on the mechanical response of fabrics in the real world. We compile a database from physical tests of several knitted fabrics used in the textile industry spanning diverse physical properties like stiffness, nonlinearity, and anisotropy. We then develop a system for approximating these mechanical responses with yarn-level cloth simulation, using homogenized shell models to speed up computation and adding some small-but-necessary extensions to yarn-level models used in computer graphics. AU - Sperl, Georg ID - 12358 SN - 2663-337X TI - Homogenizing yarn simulations: Large-scale mechanics, small-scale detail, and quantitative fitting ER - TY - THES AB - In this Thesis, I study composite quantum impurities with variational techniques, both inspired by machine learning as well as fully analytic. I supplement this with exploration of other applications of machine learning, in particular artificial neural networks, in many-body physics. In Chapters 3 and 4, I study quasiparticle systems with variational approach. I derive a Hamiltonian describing the angulon quasiparticle in the presence of a magnetic field. I apply analytic variational treatment to this Hamiltonian. Then, I introduce a variational approach for non-additive systems, based on artificial neural networks. I exemplify this approach on the example of the polaron quasiparticle (Fröhlich Hamiltonian). In Chapter 5, I continue using artificial neural networks, albeit in a different setting. I apply artificial neural networks to detect phases from snapshots of two types physical systems. Namely, I study Monte Carlo snapshots of multilayer classical spin models as well as molecular dynamics maps of colloidal systems. The main type of networks that I use here are convolutional neural networks, known for their applicability to image data. AU - Rzadkowski, Wojciech ID - 10759 SN - 2663-337X TI - Analytic and machine learning approaches to composite quantum impurities ER - TY - THES AB - One of the fundamental questions in Neuroscience is how the structure of synapses and their physiological properties are related. While synaptic transmission remains a dynamic process, electron microscopy provides images with comparably low temporal resolution (Studer et al., 2014). The current work overcomes this challenge and describes an improved “Flash and Freeze” technique (Watanabe et al., 2013a; Watanabe et al., 2013b) to study synaptic transmission at the hippocampal mossy fiber-CA3 pyramidal neuron synapses, using mouse acute brain slices and organotypic slices culture. The improved method allowed for selective stimulation of presynaptic mossy fiber boutons and the observation of synaptic vesicle pool dynamics at the active zones. Our results uncovered several intriguing morphological features of mossy fiber boutons. First, the docked vesicle pool was largely depleted (more than 70%) after stimulation, implying that the docked synaptic vesicles pool and readily releasable pool are vastly overlapping in mossy fiber boutons. Second, the synaptic vesicles are skewed towards larger diameters, displaying a wide range of sizes. An increase in the mean diameter of synaptic vesicles, after single and repetitive stimulation, suggests that smaller vesicles have a higher release probability. Third, we observed putative endocytotic structures after moderate light stimulation, matching the timing of previously described ultrafast endocytosis (Watanabe et al., 2013a; Delvendahl et al., 2016). In addition, synaptic transmission depends on a sophisticated system of protein machinery and calcium channels (Südhof, 2013b), which amplifies the challenge in studying synaptic communication as these interactions can be potentially modified during synaptic plasticity. And although recent study elucidated the potential correlation between physiological and morphological properties of synapses during synaptic plasticity (Vandael et al., 2020), the molecular underpinning of it remains unknown. Thus, the presented work tries to overcome this challenge and aims to pinpoint changes in the molecular architecture at hippocampal mossy fiber bouton synapses during short- and long-term potentiation (STP and LTP), we combined chemical potentiation, with the application of a cyclic adenosine monophosphate agonist (i.e. forskolin) and freeze-fracture replica immunolabelling. This method allowed the localization of membrane-bound proteins with nanometer precision within the active zone, in particular, P/Q-type calcium channels and synaptic vesicle priming proteins Munc13-1/2. First, we found that the number of clusters of Munc13-1 in the mossy fiber bouton active zone increased significantly during STP, but decreased to lower than the control value during LTP. Secondly, although the distance between the calcium channels and Munc13-1s did not change after induction of STP, it shortened during the LTP phase. Additionally, forskolin did not affect Munc13-2 distribution during STP and LTP. These results indicate the existence of two distinct mechanisms that govern STP and LTP at mossy fiber bouton synapses: an increase in the readily realizable pool in the case of STP and a potential increase in release probability during LTP. “Flash and freeze” and functional electron microscopy, are versatile methods that can be successfully applied to intact brain circuits to study synaptic transmission even at the molecular level. AU - Kim, Olena ID - 11196 SN - 2663-337X TI - Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses ER - TY - THES AB - Social insects are a common model to study disease dynamics in social animals. Even though pathogens should thrive in social insect colonies as the hosts engage in frequent social interactions, are closely related and live in a pathogen-rich environment, disease outbreaks are rare. This is because social insects have evolved mechanisms to keep pathogens at bay – and fight disease as a collective. Social insect colonies are often viewed as “superorganisms” with division of labor between reproductive “germ-like” queens and males and “somatic” workers, which together form an interdependent reproductive unit that parallels a multicellular body. Superorganisms possess a “social immune system” that comprises of collective disease defenses performed by the workers - summarized as “social immunity”. In social groups immunization (reduced susceptibility to a parasite upon secondary exposure to the same parasite) can e.g. be triggered by social interactions (“social immunization”). Social immunization can be caused by (i) asymptomatic low-level infections that are acquired during caregiving to a contagious individual that can give an immune boost, which can induce protection upon later encounter with the same pathogen (active immunization) or (ii) by transfer of immune effectors between individuals (passive immunization). In the second chapter, I built up on a study that I co-authored that found that low-level infections can not only be protective, but also be costly and make the host more susceptible to detrimental superinfections after contact to a very dissimilar pathogen. I here now tested different degrees of phylogenetically-distant fungal strains of M. brunneum and M. robertsii in L. neglectus and can describe the occurrence of cross-protection of social immunization if the first and second pathogen are from the same level. Interestingly, low-level infections only provided protection when the first strain was less virulent than the second strain and elicited higher immune gene expression. In the third and fourth chapters, I expanded on the role of social immunity in sexual selection, a so far unstudied field. I used the fungus Metarhizium robertsii and the ant Cardiocondyla obscurior as a model, as in this species mating occurs in the presence of workers and can be studied under laboratory conditions. Before males mate with virgin queens in the nest they engage in fierce combat over the access to their mating partners. First, I focused on male-male competition in the third chapter and found that fighting with a contagious male is costly as it can lead to contamination of the rival, but that workers can decrease the risk of disease contraction by performing sanitary care. In the fourth chapter, I studied the effect of fungal infection on survival and mating success of sexuals (freshly emerged queens and males) and found that worker-performed sanitary care can buffer the negative effect that a pathogenic contagion would have on sexuals by spore removal from the exposed individuals. When social immunity was prevented and queens could contract spores from their mating partner, very low dosages led to negative consequences: their lifespan was reduced and they produced fewer offspring with poor immunocompetence compared to healthy queens. Interestingly, cohabitation with a late-stage infected male where no spore transfer was possible had a positive effect on offspring immunity – male offspring of mothers that apparently perceived an infected partner in their vicinity reacted more sensitively to fungal challenge than male offspring without paternal pathogen history. AU - Metzler, Sina ID - 10727 SN - 2663-337X TI - Pathogen-mediated sexual selection and immunization in ant colonies ER - TY - THES AB - As the overall global mean surface temperature is increasing due to climate change, plant adaptation to those stressful conditions is of utmost importance for their survival. Plants are sessile organisms, thus to compensate for their lack of mobility, they evolved a variety of mechanisms enabling them to flexibly adjust their physiological, growth and developmental processes to fluctuating temperatures and to survive in harsh environments. While these unique adaptation abilities provide an important evolutionary advantage, overall modulation of plant growth and developmental program due to non-optimal temperature negatively affects biomass production, crop productivity or sensitivity to pathogens. Thus, understanding molecular processes underlying plant adaptation to increased temperature can provide important resources for breeding strategies to ensure sufficient agricultural food production. An increase in ambient temperature by a few degrees leads to profound changes in organ growth including enhanced hypocotyl elongation, expansion of petioles, hyponastic growth of leaves and cotyledons, collectively named thermomorphogenesis (Casal & Balasubramanian, 2019). Auxin, one of the best-studied growth hormones, plays an essential role in this process by direct activation of transcriptional and non-transcriptional processes resulting in elongation growth (Majda & Robert, 2018).To modulate hypocotyl growth in response to high ambient temperature (hAT), auxin needs to be redistributed accordingly. PINs, auxin efflux transporters, are key components of the polar auxin transport (PAT) machinery, which controls the amount and direction of auxin translocated in the plant tissues and organs(Adamowski & Friml, 2015). Hence, PIN-mediated transport is tightly linked with thermo-morphogenesis, and interference with PAT through either chemical or genetic means dramatically affecting the adaptive responses to hAT. Intriguingly, despite the key role of PIN mediated transport in growth response to hAT, whether and how PINs at the level of expression adapt to fluctuation in temperature is scarcely understood. With genetic, molecular and advanced bio-imaging approaches, we demonstrate the role of PIN auxin transporters in the regulation of hypocotyl growth in response to hAT. We show that via adjustment of PIN3, PIN4 and PIN7 expression in cotyledons and hypocotyls, auxin distribution is modulated thereby determining elongation pattern of epidermal cells at hAT. Furthermore, we identified three Zinc-Finger (ZF) transcription factors as novel molecular components of the thermo-regulatory network, which through negative regulation of PIN transcription adjust the transport of auxin at hAT. Our results suggest that the ZF-PIN module might be a part of the negative feedback loop attenuating the activity of the thermo-sensing pathway to restrain exaggerated growth and developmental responses to hAT. AU - Artner, Christina ID - 11879 KW - high ambient temperature KW - auxin KW - PINs KW - Zinc-Finger proteins KW - thermomorphogenesis KW - stress SN - 2663-337X TI - Modulation of auxin transport via ZF proteins adjust plant response to high ambient temperature ER - TY - THES AB - AMPA receptors (AMPARs) mediate fast excitatory neurotransmission and their role is implicated in complex processes such as learning and memory and various neurological diseases. These receptors are composed of different subunits and the subunit composition can affect channel properties, receptor trafficking and interaction with other associated proteins. Using the high sensitivity SDS-digested freeze-fracture replica labeling (SDS-FRL) for electron microscopy I investigated the number, density, and localization of AMPAR subunits, GluA1, GluA2, GluA3, and GluA1-3 (panAMPA) in pyramidal cells in the CA1 area of mouse hippocampus. I have found that the immunogold labeling for all of these subunits in the postsynaptic sites was highest in stratum radiatum and lowest in stratum lacunosummoleculare. The labeling density for the all subunits in the extrasynaptic sites showed a gradual increase from the pyramidal cell soma towards the distal part of stratum radiatum. The densities of extrasynaptic GluA1, GluA2 and panAMPA labeling reached 10-15% of synaptic densities, while the ratio of extrasynaptic labeling for GluA3 was significantly lower compared than those for other subunits. The labeling patterns for GluA1, GluA2 and GluA1-3 are similar and their densities were higher in the periphery than center of synapses. In contrast, the GluA3- containing receptors were more centrally localized compared to the GluA1- and GluA2- containing receptors. The hippocampus plays a central role in learning and memory. Contextual learning has been shown to require the delivery of AMPA receptors to CA1 synapses in the dorsal hippocampus. However, proximodistal heterogeneity of this plasticity and particular contribution of different AMPA receptor subunits are not fully understood. By combining inhibitory avoidance task, a hippocampus-dependent contextual fear-learning paradigm, with SDS-FRL, I have revealed an increase in synaptic density specific to GluA1-containing AMPA receptors in the CA1 area. The intrasynaptic distribution of GluA1 also changed from the periphery to center-preferred pattern. Furthermore, this synaptic plasticity was evident selectively in stratum radiatum but not stratum oriens, and in the CA1 subregion proximal but not distal to CA2. These findings further contribute to our understanding of how specific hippocampal subregions and AMPA receptor subunits are involved in physiological learning. Although the immunolabeling results above shed light on subunit-specific plasticity in AMPAR distribution, no tools to visualize and study the subunit composition at the single channel level in situ have been available. Electron microscopy with conventional immunogold labeling approaches has limitations in the single channel analysis because of the large size of antibodies and steric hindrance hampering multiple subunit labeling of single channels. I managed to develop a new chemical labeling system using a short peptide tag and small synthetic probes, which form specific covalent bond with a cysteine residue in the tag fused to proteins of interest (reactive tag system). I additionally made substantial progress into adapting this system for AMPA receptor subunits. AU - Jevtic, Marijo ID - 11393 SN - 2663-337X TI - Contextual fear learning induced changes in AMPA receptor subtypes along the proximodistal axis in dorsal hippocampus ER - TY - THES AB - Recent substantial advances in the feld of superconducting circuits have shown its potential as a leading platform for future quantum computing. In contrast to classical computers based on bits that are represented by a single binary value, 0 or 1, quantum bits (or qubits) can be in a superposition of both. Thus, quantum computers can store and handle more information at the same time and a quantum advantage has already been demonstrated for two types of computational tasks. Rapid progress in academic and industry labs accelerates the development of superconducting processors which may soon fnd applications in complex computations, chemical simulations, cryptography, and optimization. Now that these machines are scaled up to tackle such problems the questions of qubit interconnects and networks becomes very relevant. How to route signals on-chip between diferent processor components? What is the most efcient way to entangle qubits? And how to then send and process entangled signals between distant cryostats hosting superconducting processors? In this thesis, we are looking for solutions to these problems by studying the collective behavior of superconducting qubit ensembles. We frst demonstrate on-demand tunable directional scattering of microwave photons from a pair of qubits in a waveguide. Such a device can route microwave photons on-chip with a high diode efciency. Then we focus on studying ultra-strong coupling regimes between light (microwave photons) and matter (superconducting qubits), a regime that could be promising for extremely fast multi-qubit entanglement generation. Finally, we show coherent pulse storage and periodic revivals in a fve qubit ensemble strongly coupled to a resonator. Such a reconfgurable storage device could be used as part of a quantum repeater that is needed for longer-distance quantum communication. The achieved high degree of control over multi-qubit ensembles highlights not only the beautiful physics of circuit quantum electrodynamics, it also represents the frst step toward new quantum simulation and communication methods, and certain techniques may also fnd applications in future superconducting quantum computing hardware. AU - Redchenko, Elena ID - 12366 SN - 2663-337X TI - Controllable states of superconducting Qubit ensembles ER - TY - THES AB - The ability to form and retrieve memories is central to survival. In mammals, the hippocampus is a brain region essential to the acquisition and consolidation of new memories. It is also involved in keeping track of one’s position in space and aids navigation. Although this space-memory has been a source of contradiction, evidence supports the view that the role of the hippocampus in navigation is memory, thanks to the formation of cognitive maps. First introduced by Tolman in 1948, cognitive maps are generally used to organize experiences in memory; however, the detailed mechanisms by which these maps are formed and stored are not yet agreed upon. Some influential theories describe this process as involving three fundamental steps: initial encoding by the hippocampus, interactions between the hippocampus and other cortical areas, and long-term extra-hippocampal consolidation. In this thesis, I will show how the investigation of cognitive maps of space helped to shed light on each of these three memory processes. The first study included in this thesis deals with the initial encoding of spatial memories in the hippocampus. Much is known about encoding at the level of single cells, but less about their co-activity or joint contribution to the encoding of novel spatial information. I will describe the structure of an interaction network that allows for efficient encoding of noisy spatial information during the first exploration of a novel environment. The second study describes the interactions between the hippocampus and the prefrontal cortex (PFC), two areas directly and indirectly connected. It is known that the PFC, in concert with the hippocampus, is involved in various processes, including memory storage and spatial navigation. Nonetheless, the detailed mechanisms by which PFC receives information from the hippocampus are not clear. I will show how a transient improvement in theta phase locking of PFC cells enables interactions of cell pairs across the two regions. The third study describes the learning of behaviorally-relevant spatial locations in the hippocampus and the medial entorhinal cortex. I will show how the accumulation of firing around goal locations, a correlate of learning, can shed light on the transition from short- to long-term spatial memories and the speed of consolidation in different brain areas. The studies included in this thesis represent the main scientific contributions of my Ph.D. They involve statistical analyses and models of neural responses of cells in different brain areas of rats executing spatial tasks. I will conclude the thesis by discussing the impact of the findings on principles of memory formation and retention, including the mechanisms, the speed, and the duration of these processes. AU - Nardin, Michele ID - 11932 SN - 2663-337X TI - On the encoding, transfer, and consolidation of spatial memories ER - TY - THES AB - Environmental cues influence the highly dynamic morphology of microglia. Strategies to characterize these changes usually involve user-selected morphometric features, which preclude the identification of a spectrum of context-dependent morphological phenotypes. Here, we develop MorphOMICs, a topological data analysis approach, which enables semiautomatic mapping of microglial morphology into an atlas of cue-dependent phenotypes, overcomes feature-selection bias and minimizes biological variability. First, with MorphOMICs we derive the morphological spectrum of microglia across seven brain regions during postnatal development and in two distinct Alzheimer’s disease degeneration mouse models. We uncover region-specific and sexually dimorphic morphological trajectories, with females showing an earlier morphological shift than males in the degenerating brain. Overall, we demonstrate that both long primary- and short terminal processes provide distinct insights to morphological phenotypes. Moreover, using machine learning to map novel condition on the spectrum, we observe that microglia morphologies reflect a dose-dependent adaptation upon ketamine anesthesia and do not recover to control morphologies. Next, we took advantage of MorphOMICs to build a high-resolution and layer-specific map of microglial morphological spectrum in the retina, covering postnatal development and rd10 degeneration. Here, following photoreceptor death, microglia assume an early developmentlike morphology. Finally, we map microglial morphology following optic nerve crush on the retinal spectrum and observe a layer- and sex-dependent response. Overall, MorphOMICs opens a new perspective to analyze microglial morphology across multiple conditions, and provides a novel tool to characterize microglial morphology beyond the traditionally dichotomized view of microglia. AU - Colombo, Gloria ID - 12378 SN - 2663-337X TI - MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes ER - TY - THES AB - In evolve and resequence experiments, a population is sequenced, subjected to selection and then sequenced again, so that genetic changes before and after selection can be observed at the genetic level. Here, I use these studies to better understand the genetic basis of complex traits - traits which depend on more than a few genes. In the first chapter, I discuss the first evolve and resequence experiment, in which a population of mice, the so-called "Longshanks" mice, were selected for tibia length while their body mass was kept constant. The full pedigree is known. We observed a selection response on all chromosomes and used the infinitesimal model with linkage, a model which assumes an infinite number of genes with infinitesimally small effect sizes, as a null model. Results implied a very polygenic basis with a few loci of major effect standing out and changing in parallel. There was large variability between the different chromosomes in this study, probably due to LD. In chapter two, I go on to discuss the impact of LD, on the variability in an allele-frequency based summary statistic, giving an equation based on the initial allele frequencies, average pairwise LD, and the first four moments of the haplotype block copy number distribution. I describe this distribution by referring back to the founder generation. I then demonstrate how to infer selection via a maximum likelihood scheme on the example of a single locus and discuss how to extend this to more realistic scenarios. In chapter three, I discuss the second evolve and resequence experiment, in which a small population of Drosophila melanogaster was selected for increased pupal case size over 6 generations. The experiment was highly replicated with 27 lines selected within family and a known pedigree. We observed a phenotypic selection response of over one standard deviation. I describe the patterns in allele frequency data, including allele frequency changes and patterns of heterozygosity, and give ideas for future work. AU - Belohlavy, Stefanie ID - 11388 SN - 978-3-99078-018-3 TI - The genetic basis of complex traits studied via analysis of evolve and resequence experiments ER - TY - THES AB - Detachment of the cancer cells from the bulk of the tumor is the first step of metastasis, which is the primary cause of cancer related deaths. It is unclear, which factors contribute to this step. Recent studies indicate a crucial role of the tumor microenvironment in malignant transformation and metastasis. Studying cancer cell invasion and detachments quantitatively in the context of its physiological microenvironment is technically challenging. Especially, precise control of microenvironmental properties in vivo is currently not possible. Here, I studied the role of microenvironment geometry in the invasion and detachment of cancer cells from the bulk with a simplistic and reductionist approach. In this approach, I engineered microfluidic devices to mimic a pseudo 3D extracellular matrix environment, where I was able to quantitatively tune the geometrical configuration of the microenvironment and follow tumor cells with fluorescence live imaging. To aid quantitative analysis I developed a widely applicable software application to automatically analyze and visualize particle tracking data. Quantitative analysis of tumor cell invasion in isotropic and anisotropic microenvironments showed that heterogeneity in the microenvironment promotes faster invasion and more frequent detachment of cells. These observations correlated with overall higher speed of cells at the edge of the bulk of the cells. In heterogeneous microenvironments cells preferentially passed through larger pores, thus invading areas of least resistance and generating finger-like invasive structures. The detachments occurred mostly at the tips of these structures. To investigate the potential mechanism, we established a two dimensional model to simulate active Brownian particles representing the cell nuclei dynamics. These simulations backed our in vitro observations without the need of precise fitting the simulation parameters. Our model suggests the importance of the pore heterogeneity in the direction perpendicular to the orientation of bias field (lateral heterogeneity), which causes the interface roughening. AU - Tasciyan, Saren ID - 12401 SN - 2663-337X TI - Role of microenvironment heterogeneity in cancer cell invasion ER - TY - THES AB - The infiltration of immune cells into tissues underlies the establishment of tissue-resident macrophages and responses to infections and tumors. However, the mechanisms immune cells utilize to collectively migrate through tissue barriers in vivo are not yet well understood. In this thesis, I describe two mechanisms that Drosophila immune cells (hemocytes) use to overcome the tissue barrier of the germband in the embryo. One strategy is the strengthening of the actin cortex through developmentally controlled transcriptional regulation induced by the Drosophila proto-oncogene family member Dfos, which I show in Chapter 2. Dfos induces expression of the tetraspanin TM4SF and the filamin Cher leading to higher levels of the activated formin Dia at the cortex and increased cortical F-actin. This enhanced cortical strength allows hemocytes to overcome the physical resistance of the surrounding tissue and translocate their nucleus to move forward. This mechanism affects the speed of migration when hemocytes face a confined environment in vivo. Another aspect of the invasion process is the initial step of the leading hemocytes entering the tissue, which potentially guides the follower cells. In Chapter 3, I describe a novel subpopulation of hemocytes activated by BMP signaling prior to tissue invasion that leads penetration into the germband. Hemocytes that are deficient in BMP signaling activation show impaired persistence at the tissue entry, while their migration speed remains unaffected. This suggests that there might be different mechanisms controlling immune cell migration within the confined environment in vivo, one of these being the general ability to overcome the resistance of the surrounding tissue and another affecting the order of hemocytes that collectively invade the tissue in a stream of individual cells. Together, my findings provide deeper insights into transcriptional changes in immune cells that enable efficient tissue invasion and pave the way for future studies investigating the early colonization of tissues by macrophages in higher organisms. Moreover, they extend the current view of Drosophila immune cell heterogeneity and point toward a potentially conserved role for canonical BMP signaling in specifying immune cells that lead the migration of tissue resident macrophages during embryogenesis. AU - Wachner, Stephanie ID - 11193 SN - 2663-337X TI - Transcriptional regulation by Dfos and BMP-signaling support tissue invasion of Drosophila immune cells ER - TY - THES AB - Autism spectrum disorders (ASDs) are a group of neurodevelopmental disorders characterized by behavioral symptoms such as problems in social communication and interaction, as well as repetitive, restricted behaviors and interests. These disorders show a high degree of heritability and hundreds of risk genes have been identifed using high throughput sequencing technologies. This genetic heterogeneity has hampered eforts in understanding the pathogenesis of ASD but at the same time given rise to the concept of convergent mechanisms. Previous studies have identifed that risk genes for ASD broadly converge onto specifc functional categories with transcriptional regulation being one of the biggest groups. In this thesis, I focus on this subgroup of genes and investigate the gene regulatory consequences of some of them in the context of neurodevelopment. First, we showed that mutations in the ASD and intellectual disability risk gene Setd5 lead to perturbations of gene regulatory programs in early cell fate specifcation. In addition, adult animals display abnormal learning behavior which is mirrored at the transcriptional level by altered activity dependent regulation of postsynaptic gene expression. Lastly, we link the regulatory function of Setd5 to its interaction with the Paf1 and the NCoR complex. Second, by modeling the heterozygous loss of the top ASD gene CHD8 in human cerebral organoids we demonstrate profound changes in the developmental trajectories of both inhibitory and excitatory neurons using single cell RNA-sequencing. While the former were generated earlier in CHD8+/- organoids, the generation of the latter was shifted to later times in favor of a prolonged progenitor expansion phase and ultimately increased organoid size. Finally, by modeling heterozygous mutations for four ASD associated chromatin modifers, ASH1L, KDM6B, KMT5B, and SETD5 in human cortical spheroids we show evidence of regulatory convergence across three of those genes. We observe a shift from dorsal cortical excitatory neuron fates towards partially ventralized cell types resembling cells from the lateral ganglionic eminence. As this project is still ongoing at the time of writing, future experiments will aim at elucidating the regulatory mechanisms underlying this shift with the aim of linking these three ASD risk genes through biological convergence. AU - Dotter, Christoph ID - 12364 SN - 2663-337X TI - Transcriptional consequences of mutations in genes associated with Autism Spectrum Disorder ER - TY - THES AB - In this thesis we study persistence of multi-covers of Euclidean balls and the geometric structures underlying their computation, in particular Delaunay mosaics and Voronoi tessellations. The k-fold cover for some discrete input point set consists of the space where at least k balls of radius r around the input points overlap. Persistence is a notion that captures, in some sense, the topology of the shape underlying the input. While persistence is usually computed for the union of balls, the k-fold cover is of interest as it captures local density, and thus might approximate the shape of the input better if the input data is noisy. To compute persistence of these k-fold covers, we need a discretization that is provided by higher-order Delaunay mosaics. We present and implement a simple and efficient algorithm for the computation of higher-order Delaunay mosaics, and use it to give experimental results for their combinatorial properties. The algorithm makes use of a new geometric structure, the rhomboid tiling. It contains the higher-order Delaunay mosaics as slices, and by introducing a filtration function on the tiling, we also obtain higher-order α-shapes as slices. These allow us to compute persistence of the multi-covers for varying radius r; the computation for varying k is less straight-foward and involves the rhomboid tiling directly. We apply our algorithms to experimental sphere packings to shed light on their structural properties. Finally, inspired by periodic structures in packings and materials, we propose and implement an algorithm for periodic Delaunay triangulations to be integrated into the Computational Geometry Algorithms Library (CGAL), and discuss the implications on persistence for periodic data sets. AU - Osang, Georg F ID - 9056 SN - 2663-337X TI - Multi-cover persistence and Delaunay mosaics ER - TY - THES AB - In the first part of the thesis we consider Hermitian random matrices. Firstly, we consider sample covariance matrices XX∗ with X having independent identically distributed (i.i.d.) centred entries. We prove a Central Limit Theorem for differences of linear statistics of XX∗ and its minor after removing the first column of X. Secondly, we consider Wigner-type matrices and prove that the eigenvalue statistics near cusp singularities of the limiting density of states are universal and that they form a Pearcey process. Since the limiting eigenvalue distribution admits only square root (edge) and cubic root (cusp) singularities, this concludes the third and last remaining case of the Wigner-Dyson-Mehta universality conjecture. The main technical ingredients are an optimal local law at the cusp, and the proof of the fast relaxation to equilibrium of the Dyson Brownian motion in the cusp regime. In the second part we consider non-Hermitian matrices X with centred i.i.d. entries. We normalise the entries of X to have variance N −1. It is well known that the empirical eigenvalue density converges to the uniform distribution on the unit disk (circular law). In the first project, we prove universality of the local eigenvalue statistics close to the edge of the spectrum. This is the non-Hermitian analogue of the TracyWidom universality at the Hermitian edge. Technically we analyse the evolution of the spectral distribution of X along the Ornstein-Uhlenbeck flow for very long time (up to t = +∞). In the second project, we consider linear statistics of eigenvalues for macroscopic test functions f in the Sobolev space H2+ϵ and prove their convergence to the projection of the Gaussian Free Field on the unit disk. We prove this result for non-Hermitian matrices with real or complex entries. The main technical ingredients are: (i) local law for products of two resolvents at different spectral parameters, (ii) analysis of correlated Dyson Brownian motions. In the third and final part we discuss the mathematically rigorous application of supersymmetric techniques (SUSY ) to give a lower tail estimate of the lowest singular value of X − z, with z ∈ C. More precisely, we use superbosonisation formula to give an integral representation of the resolvent of (X − z)(X − z)∗ which reduces to two and three contour integrals in the complex and real case, respectively. The rigorous analysis of these integrals is quite challenging since simple saddle point analysis cannot be applied (the main contribution comes from a non-trivial manifold). Our result improves classical smoothing inequalities in the regime |z| ≈ 1; this result is essential to prove edge universality for i.i.d. non-Hermitian matrices. AU - Cipolloni, Giorgio ID - 9022 SN - 2663-337X TI - Fluctuations in the spectrum of random matrices ER - TY - THES AB - The present thesis is concerned with the derivation of weak-strong uniqueness principles for curvature driven interface evolution problems not satisfying a comparison principle. The specific examples being treated are two-phase Navier-Stokes flow with surface tension, modeling the evolution of two incompressible, viscous and immiscible fluids separated by a sharp interface, and multiphase mean curvature flow, which serves as an idealized model for the motion of grain boundaries in an annealing polycrystalline material. Our main results - obtained in joint works with Julian Fischer, Tim Laux and Theresa M. Simon - state that prior to the formation of geometric singularities due to topology changes, the weak solution concept of Abels (Interfaces Free Bound. 9, 2007) to two-phase Navier-Stokes flow with surface tension and the weak solution concept of Laux and Otto (Calc. Var. Partial Differential Equations 55, 2016) to multiphase mean curvature flow (for networks in R^2 or double bubbles in R^3) represents the unique solution to these interface evolution problems within the class of classical solutions, respectively. To the best of the author's knowledge, for interface evolution problems not admitting a geometric comparison principle the derivation of a weak-strong uniqueness principle represented an open problem, so that the works contained in the present thesis constitute the first positive results in this direction. The key ingredient of our approach consists of the introduction of a novel concept of relative entropies for a class of curvature driven interface evolution problems, for which the associated energy contains an interfacial contribution being proportional to the surface area of the evolving (network of) interface(s). The interfacial part of the relative entropy gives sufficient control on the interface error between a weak and a classical solution, and its time evolution can be computed, at least in principle, for any energy dissipating weak solution concept. A resulting stability estimate for the relative entropy essentially entails the above mentioned weak-strong uniqueness principles. The present thesis contains a detailed introduction to our relative entropy approach, which in particular highlights potential applications to other problems in curvature driven interface evolution not treated in this thesis. AU - Hensel, Sebastian ID - 10007 SN - 2663-337X TI - Curvature driven interface evolution: Uniqueness properties of weak solution concepts ER - TY - THES AB - This PhD thesis is primarily focused on the study of discrete transport problems, introduced for the first time in the seminal works of Maas [Maa11] and Mielke [Mie11] on finite state Markov chains and reaction-diffusion equations, respectively. More in detail, my research focuses on the study of transport costs on graphs, in particular the convergence and the stability of such problems in the discrete-to-continuum limit. This thesis also includes some results concerning non-commutative optimal transport. The first chapter of this thesis consists of a general introduction to the optimal transport problems, both in the discrete, the continuous, and the non-commutative setting. Chapters 2 and 3 present the content of two works, obtained in collaboration with Peter Gladbach, Eva Kopfer, and Jan Maas, where we have been able to show the convergence of discrete transport costs on periodic graphs to suitable continuous ones, which can be described by means of a homogenisation result. We first focus on the particular case of quadratic costs on the real line and then extending the result to more general costs in arbitrary dimension. Our results are the first complete characterisation of limits of transport costs on periodic graphs in arbitrary dimension which do not rely on any additional symmetry. In Chapter 4 we turn our attention to one of the intriguing connection between evolution equations and optimal transport, represented by the theory of gradient flows. We show that discrete gradient flow structures associated to a finite volume approximation of a certain class of diffusive equations (Fokker–Planck) is stable in the limit of vanishing meshes, reproving the convergence of the scheme via the method of evolutionary Γ-convergence and exploiting a more variational point of view on the problem. This is based on a collaboration with Dominik Forkert and Jan Maas. Chapter 5 represents a change of perspective, moving away from the discrete world and reaching the non-commutative one. As in the discrete case, we discuss how classical tools coming from the commutative optimal transport can be translated into the setting of density matrices. In particular, in this final chapter we present a non-commutative version of the Schrödinger problem (or entropic regularised optimal transport problem) and discuss existence and characterisation of minimisers, a duality result, and present a non-commutative version of the well-known Sinkhorn algorithm to compute the above mentioned optimisers. This is based on a joint work with Dario Feliciangeli and Augusto Gerolin. Finally, Appendix A and B contain some additional material and discussions, with particular attention to Harnack inequalities and the regularity of flows on discrete spaces. AU - Portinale, Lorenzo ID - 10030 SN - 2663-337X TI - Discrete-to-continuum limits of transport problems and gradient flows in the space of measures ER - TY - THES AB - This work is concerned with two fascinating circuit quantum electrodynamics components, the Josephson junction and the geometric superinductor, and the interesting experiments that can be done by combining the two. The Josephson junction has revolutionized the field of superconducting circuits as a non-linear dissipation-less circuit element and is used in almost all superconducting qubit implementations since the 90s. On the other hand, the superinductor is a relatively new circuit element introduced as a key component of the fluxonium qubit in 2009. This is an inductor with characteristic impedance larger than the resistance quantum and self-resonance frequency in the GHz regime. The combination of these two elements can occur in two fundamental ways: in parallel and in series. When connected in parallel the two create the fluxonium qubit, a loop with large inductance and a rich energy spectrum reliant on quantum tunneling. On the other hand placing the two elements in series aids with the measurement of the IV curve of a single Josephson junction in a high impedance environment. In this limit theory predicts that the junction will behave as its dual element: the phase-slip junction. While the Josephson junction acts as a non-linear inductor the phase-slip junction has the behavior of a non-linear capacitance and can be used to measure new Josephson junction phenomena, namely Coulomb blockade of Cooper pairs and phase-locked Bloch oscillations. The latter experiment allows for a direct link between frequency and current which is an elusive connection in quantum metrology. This work introduces the geometric superinductor, a superconducting circuit element where the high inductance is due to the geometry rather than the material properties of the superconductor, realized from a highly miniaturized superconducting planar coil. These structures will be described and characterized as resonators and qubit inductors and progress towards the measurement of phase-locked Bloch oscillations will be presented. AU - Peruzzo, Matilda ID - 9920 KW - quantum computing KW - superinductor KW - quantum metrology SN - 2663-337X TI - Geometric superinductors and their applications in circuit quantum electrodynamics ER - TY - THES AB - Those who aim to devise new materials with desirable properties usually examine present methods first. However, they will find out that some approaches can exist only conceptually without high chances to become practically useful. It seems that a numerical technique called automatic differentiation together with increasing supply of computational accelerators will soon shift many methods of the material design from the category ”unimaginable” to the category ”expensive but possible”. Approach we suggest is not an exception. Our overall goal is to have an efficient and generalizable approach allowing to solve inverse design problems. In this thesis we scratch its surface. We consider jammed systems of identical particles. And ask ourselves how the shape of those particles (or the parameters codifying it) may affect mechanical properties of the system. An indispensable part of reaching the answer is an appropriate particle parametrization. We come up with a simple, yet generalizable and purposeful scheme for it. Using our generalizable shape parameterization, we simulate the formation of a solid composed of pentagonal-like particles and measure anisotropy in the resulting elastic response. Through automatic differentiation techniques, we directly connect the shape parameters with the elastic response. Interestingly, for our system we find that less isotropic particles lead to a more isotropic elastic response. Together with other results known about our method it seems that it can be successfully generalized for different inverse design problems. AU - Piankov, Anton ID - 10422 SN - 2791-4585 TI - Towards designer materials using customizable particle shape ER - TY - THES AB - Deep learning is best known for its empirical success across a wide range of applications spanning computer vision, natural language processing and speech. Of equal significance, though perhaps less known, are its ramifications for learning theory: deep networks have been observed to perform surprisingly well in the high-capacity regime, aka the overfitting or underspecified regime. Classically, this regime on the far right of the bias-variance curve is associated with poor generalisation; however, recent experiments with deep networks challenge this view. This thesis is devoted to investigating various aspects of underspecification in deep learning. First, we argue that deep learning models are underspecified on two levels: a) any given training dataset can be fit by many different functions, and b) any given function can be expressed by many different parameter configurations. We refer to the second kind of underspecification as parameterisation redundancy and we precisely characterise its extent. Second, we characterise the implicit criteria (the inductive bias) that guide learning in the underspecified regime. Specifically, we consider a nonlinear but tractable classification setting, and show that given the choice, neural networks learn classifiers with a large margin. Third, we consider learning scenarios where the inductive bias is not by itself sufficient to deal with underspecification. We then study different ways of ‘tightening the specification’: i) In the setting of representation learning with variational autoencoders, we propose a hand- crafted regulariser based on mutual information. ii) In the setting of binary classification, we consider soft-label (real-valued) supervision. We derive a generalisation bound for linear networks supervised in this way and verify that soft labels facilitate fast learning. Finally, we explore an application of soft-label supervision to the training of multi-exit models. AU - Bui Thi Mai, Phuong ID - 9418 SN - 2663-337X TI - Underspecification in deep learning ER - TY - THES AB - The design and verification of concurrent systems remains an open challenge due to the non-determinism that arises from the inter-process communication. In particular, concurrent programs are notoriously difficult both to be written correctly and to be analyzed formally, as complex thread interaction has to be accounted for. The difficulties are further exacerbated when concurrent programs get executed on modern-day hardware, which contains various buffering and caching mechanisms for efficiency reasons. This causes further subtle non-determinism, which can often produce very unintuitive behavior of the concurrent programs. Model checking is at the forefront of tackling the verification problem, where the task is to decide, given as input a concurrent system and a desired property, whether the system satisfies the property. The inherent state-space explosion problem in model checking of concurrent systems causes naïve explicit methods not to scale, thus more inventive methods are required. One such method is stateless model checking (SMC), which explores in memory-efficient manner the program executions rather than the states of the program. State-of-the-art SMC is typically coupled with partial order reduction (POR) techniques, which argue that certain executions provably produce identical system behavior, thus limiting the amount of executions one needs to explore in order to cover all possible behaviors. Another method to tackle the state-space explosion is symbolic model checking, where the considered techniques operate on a succinct implicit representation of the input system rather than explicitly accessing the system. In this thesis we present new techniques for verification of concurrent systems. We present several novel POR methods for SMC of concurrent programs under various models of semantics, some of which account for write-buffering mechanisms. Additionally, we present novel algorithms for symbolic model checking of finite-state concurrent systems, where the desired property of the systems is to ensure a formally defined notion of fairness. AU - Toman, Viktor ID - 10199 KW - concurrency KW - verification KW - model checking SN - 2663-337X TI - Improved verification techniques for concurrent systems ER - TY - THES AB - Many security definitions come in two flavors: a stronger “adaptive” flavor, where the adversary can arbitrarily make various choices during the course of the attack, and a weaker “selective” flavor where the adversary must commit to some or all of their choices a-priori. For example, in the context of identity-based encryption, selective security requires the adversary to decide on the identity of the attacked party at the very beginning of the game whereas adaptive security allows the attacker to first see the master public key and some secret keys before making this choice. Often, it appears to be much easier to achieve selective security than it is to achieve adaptive security. A series of several recent works shows how to cleverly achieve adaptive security in several such scenarios including generalized selective decryption [Pan07][FJP15], constrained PRFs [FKPR14], and Yao’s garbled circuits [JW16]. Although the above works expressed vague intuition that they share a common technique, the connection was never made precise. In this work we present a new framework (published at Crypto ’17 [JKK+17a]) that connects all of these works and allows us to present them in a unified and simplified fashion. Having the framework in place, we show how to achieve adaptive security for proxy re-encryption schemes (published at PKC ’19 [FKKP19]) and provide the first adaptive security proofs for continuous group key agreement protocols (published at S&P ’21 [KPW+21]). Questioning optimality of our framework, we then show that currently used proof techniques cannot lead to significantly better security guarantees for "graph-building" games (published at TCC ’21 [KKPW21a]). These games cover generalized selective decryption, as well as the security of prominent constructions for constrained PRFs, continuous group key agreement, and proxy re-encryption. Finally, we revisit the adaptive security of Yao’s garbled circuits and extend the analysis of Jafargholi and Wichs in two directions: While they prove adaptive security only for a modified construction with increased online complexity, we provide the first positive results for the original construction by Yao (published at TCC ’21 [KKP21a]). On the negative side, we prove that the results of Jafargholi and Wichs are essentially optimal by showing that no black-box reduction can provide a significantly better security bound (published at Crypto ’21 [KKPW21c]). AU - Klein, Karen ID - 10035 SN - 2663-337X TI - On the adaptive security of graph-based games ER - TY - THES AB - The scalability of concurrent data structures and distributed algorithms strongly depends on reducing the contention for shared resources and the costs of synchronization and communication. We show how such cost reductions can be attained by relaxing the strict consistency conditions required by sequential implementations. In the first part of the thesis, we consider relaxation in the context of concurrent data structures. Specifically, in data structures such as priority queues, imposing strong semantics renders scalability impossible, since a correct implementation of the remove operation should return only the element with highest priority. Intuitively, attempting to invoke remove operations concurrently creates a race condition. This bottleneck can be circumvented by relaxing semantics of the affected data structure, thus allowing removal of the elements which are no longer required to have the highest priority. We prove that the randomized implementations of relaxed data structures provide provable guarantees on the priority of the removed elements even under concurrency. Additionally, we show that in some cases the relaxed data structures can be used to scale the classical algorithms which are usually implemented with the exact ones. In the second part, we study parallel variants of the stochastic gradient descent (SGD) algorithm, which distribute computation among the multiple processors, thus reducing the running time. Unfortunately, in order for standard parallel SGD to succeed, each processor has to maintain a local copy of the necessary model parameter, which is identical to the local copies of other processors; the overheads from this perfect consistency in terms of communication and synchronization can negate the speedup gained by distributing the computation. We show that the consistency conditions required by SGD can be relaxed, allowing the algorithm to be more flexible in terms of tolerating quantized communication, asynchrony, or even crash faults, while its convergence remains asymptotically the same. AU - Nadiradze, Giorgi ID - 10429 SN - 2663-337X TI - On achieving scalability through relaxation ER - TY - THES AB - This thesis is the result of the research carried out by the author during his PhD at IST Austria between 2017 and 2021. It mainly focuses on the Fröhlich polaron model, specifically to its regime of strong coupling. This model, which is rigorously introduced and discussed in the introduction, has been of great interest in condensed matter physics and field theory for more than eighty years. It is used to describe an electron interacting with the atoms of a solid material (the strength of this interaction is modeled by the presence of a coupling constant α in the Hamiltonian of the system). The particular regime examined here, which is mathematically described by considering the limit α →∞, displays many interesting features related to the emergence of classical behavior, which allows for a simplified effective description of the system under analysis. The properties, the range of validity and a quantitative analysis of the precision of such classical approximations are the main object of the present work. We specify our investigation to the study of the ground state energy of the system, its dynamics and its effective mass. For each of these problems, we provide in the introduction an overview of the previously known results and a detailed account of the original contributions by the author. AU - Feliciangeli, Dario ID - 9733 SN - 2663-337X TI - The polaron at strong coupling ER - TY - THES AB - Blood – this is what animals use to heal wounds fast and efficient. Plants do not have blood circulation and their cells cannot move. However, plants have evolved remarkable capacities to regenerate tissues and organs preventing further damage. In my PhD research, I studied the wound healing in the Arabidopsis root. I used a UV laser to ablate single cells in the root tip and observed the consequent wound healing. Interestingly, the inner adjacent cells induced a division plane switch and subsequently adopted the cell type of the killed cell to replace it. We termed this form of wound healing “restorative divisions”. This initial observation triggered the questions of my PhD studies: How and why do cells orient their division planes, how do they feel the wound and why does this happen only in inner adjacent cells. For answering these questions, I used a quite simple experimental setup: 5 day - old seedlings were stained with propidium iodide to visualize cell walls and dead cells; ablation was carried out using a special laser cutter and a confocal microscope. Adaptation of the novel vertical microscope system made it possible to observe wounds in real time. This revealed that restorative divisions occur at increased frequency compared to normal divisions. Additionally, the major plant hormone auxin accumulates in wound adjacent cells and drives the expression of the wound-stress responsive transcription factor ERF115. Using this as a marker gene for wound responses, we found that an important part of wound signalling is the sensing of the collapse of the ablated cell. The collapse causes a radical pressure drop, which results in strong tissue deformations. These deformations manifest in an invasion of the now free spot specifically by the inner adjacent cells within seconds, probably because of higher pressure of the inner tissues. Long-term imaging revealed that those deformed cells continuously expand towards the wound hole and that this is crucial for the restorative division. These wound-expanding cells exhibit an abnormal, biphasic polarity of microtubule arrays before the division. Experiments inhibiting cell expansion suggest that it is the biphasic stretching that induces those MT arrays. Adapting the micromanipulator aspiration system from animal scientists at our institute confirmed the hypothesis that stretching influences microtubule stability. In conclusion, this shows that microtubules react to tissue deformation and this facilitates the observed division plane switch. This puts mechanical cues and tensions at the most prominent position for explaining the growth and wound healing properties of plants. Hence, it shines light onto the importance of understanding mechanical signal transduction. AU - Hörmayer, Lukas ID - 9992 SN - 2663-337X TI - Wound healing in the Arabidopsis root meristem ER - TY - THES AB - Cytoplasmic reorganizations are essential for morphogenesis. In large cells like oocytes, these reorganizations become crucial in patterning the oocyte for later stages of embryonic development. Ascidians oocytes reorganize their cytoplasm (ooplasm) in a spectacular manner. Ooplasmic reorganization is initiated at fertilization with the contraction of the actomyosin cortex along the animal-vegetal axis of the oocyte, driving the accumulation of cortical endoplasmic reticulum (cER), maternal mRNAs associated to it and a mitochondria-rich subcortical layer – the myoplasm – in a region of the vegetal pole termed contraction pole (CP). Here we have used the species Phallusia mammillata to investigate the changes in cell shape that accompany these reorganizations and the mechanochemical mechanisms underlining CP formation. We report that the length of the animal-vegetal (AV) axis oscillates upon fertilization: it first undergoes a cycle of fast elongation-lengthening followed by a slow expansion of mainly the vegetal pole (VP) of the cell. We show that the fast oscillation corresponds to a dynamic polarization of the actin cortex as a result of a fertilization-induced increase in cortical tension in the oocyte that triggers a rupture of the cortex at the animal pole and the establishment of vegetal-directed cortical flows. These flows are responsible for the vegetal accumulation of actin causing the VP to flatten. We find that the slow expansion of the VP, leading to CP formation, correlates with a relaxation of the vegetal cortex and that the myoplasm plays a role in the expansion. We show that the myoplasm is a solid-like layer that buckles under compression forces arising from the contracting actin cortex at the VP. Straightening of the myoplasm when actin flows stops, facilitates the expansion of the VP and the CP. Altogether, our results present a previously unrecognized role for the myoplasm in ascidian ooplasmic segregation. AU - Caballero Mancebo, Silvia ID - 9623 SN - 2663-337X TI - Fertilization-induced deformations are controlled by the actin cortex and a mitochondria-rich subcortical layer in ascidian oocytes ER - TY - THES AB - Quantum information and computation has become a vast field paved with opportunities for researchers and investors. As large multinational companies and international funds are heavily investing in quantum technologies it is still a question which platform is best suited for the task of realizing a scalable quantum processor. In this work we investigate hole spins in Ge quantum wells. These hold great promise as they possess several favorable properties: a small effective mass, a strong spin-orbit coupling, long relaxation time and an inherent immunity to hyperfine noise. All these characteristics helped Ge hole spin qubits to evolve from a single qubit to a fully entangled four qubit processor in only 3 years. Here, we investigated a qubit approach leveraging the large out-of-plane g-factors of heavy hole states in Ge quantum dots. We found this qubit to be reproducibly operable at extremely low magnetic field and at large speeds while maintaining coherence. This was possible because large differences of g-factors in adjacent dots can be achieved in the out-of-plane direction. In the in-plane direction the small g-factors, on the other hand, can be altered very effectively by the confinement potentials. Here, we found that this can even lead to a sign change of the g-factors. The resulting g-factor difference alters the dynamics of the system drastically and produces effects typically attributed to a spin-orbit induced spin-flip term. The investigations carried out in this thesis give further insights into the possibilities of holes in Ge and reveal new physical properties that need to be considered when designing future spin qubit experiments. AU - Jirovec, Daniel ID - 10058 KW - qubits KW - quantum computing KW - holes SN - 2663-337X TI - Singlet-Triplet qubits and spin-orbit interaction in 2-dimensional Ge hole gases ER - TY - THES AB - Accumulation of interstitial fluid (IF) between embryonic cells is a common phenomenon in vertebrate embryogenesis. Unlike other model systems, where these accumulations coalesce into a large central cavity – the blastocoel, in zebrafish, IF is more uniformly distributed between the deep cells (DC) before the onset of gastrulation. This is likely due to the presence of a large extraembryonic structure – the yolk cell (YC) at the position where the blastocoel typically forms in other model organisms. IF has long been speculated to play a role in tissue morphogenesis during embryogenesis, but direct evidence supporting such function is still sparse. Here we show that the relocalization of IF to the interface between the YC and DC/epiblast is critical for axial mesendoderm (ME) cell protrusion formation and migration along this interface, a key process in embryonic axis formation. We further demonstrate that axial ME cell migration and IF relocalization engage in a positive feedback loop, where axial ME migration triggers IF accumulation ahead of the advancing axial ME tissue by mechanically compressing the overlying epiblast cell layer. Upon compression, locally induced flow relocalizes the IF through the porous epiblast tissue resulting in an IF accumulation ahead of the leading axial ME. This IF accumulation, in turn, promotes cell protrusion formation and migration of the leading axial ME cells, thereby facilitating axial ME extension. Our findings reveal a central role of dynamic IF relocalization in orchestrating germ layer morphogenesis during gastrulation. AU - Huljev, Karla ID - 9397 SN - 2663-337X TI - Coordinated spatiotemporal reorganization of interstitial fluid is required for axial mesendoderm migration in zebrafish gastrulation ER - TY - THES AB - Left-right asymmetries can be considered a fundamental organizational principle of the vertebrate central nervous system. The hippocampal CA3-CA1 pyramidal cell synaptic connection shows an input-side dependent asymmetry where the hemispheric location of the presynaptic CA3 neuron determines the synaptic properties. Left-input synapses terminating on apical dendrites in stratum radiatum have a higher density of NMDA receptor subunit GluN2B, a lower density of AMPA receptor subunit GluA1 and smaller areas with less often perforated PSDs. On the other hand, left-input synapses terminating on basal dendrites in stratum oriens have lower GluN2B densities than right-input ones. Apical and basal synapses further employ different signaling pathways involved in LTP. SDS-digested freeze-fracture replica labeling can visualize synaptic membrane proteins with high sensitivity and resolution, and has been used to reveal the asymmetry at the electron microscopic level. However, it requires time-consuming manual demarcation of the synaptic surface for quantitative measurements. To facilitate the analysis of replica labeling, I first developed a software named Darea, which utilizes deep-learning to automatize this demarcation. With Darea I characterized the synaptic distribution of NMDA and AMPA receptors as well as the voltage-gated Ca2+ channels in CA1 stratum radiatum and oriens. Second, I explored the role of GluN2B and its carboxy-terminus in the establishment of input-side dependent hippocampal asymmetry. In conditional knock-out mice lacking GluN2B expression in CA1 and GluN2B-2A swap mice, where GluN2B carboxy-terminus was exchanged to that of GluN2A, no significant asymmetries of GluN2B, GluA1 and PSD area were detected. We further discovered a previously unknown functional asymmetry of GluN2A, which was also lost in the swap mouse. These results demonstrate that GluN2B carboxy-terminus plays a critical role in normal formation of input-side dependent asymmetry. AU - Kleindienst, David ID - 9562 SN - 2663-337X TI - 2B or not 2B: Hippocampal asymmetries mediated by NMDA receptor subunit GluN2B C-terminus and high-throughput image analysis by Deep-Learning ER - TY - THES AB - In this thesis, we consider several of the most classical and fundamental problems in static analysis and formal verification, including invariant generation, reachability analysis, termination analysis of probabilistic programs, data-flow analysis, quantitative analysis of Markov chains and Markov decision processes, and the problem of data packing in cache management. We use techniques from parameterized complexity theory, polyhedral geometry, and real algebraic geometry to significantly improve the state-of-the-art, in terms of both scalability and completeness guarantees, for the mentioned problems. In some cases, our results are the first theoretical improvements for the respective problems in two or three decades. AU - Goharshady, Amir Kafshdar ID - 8934 SN - 2663-337X TI - Parameterized and algebro-geometric advances in static program analysis ER - TY - THES AB - Bacteria-host interactions represent a continuous trade-off between benefit and risk. Thus, the host immune response is faced with a non-trivial problem – accommodate beneficial commensals and remove harmful pathogens. This is especially difficult as molecular patterns, such as lipopolysaccharide or specific surface organelles such as pili, are conserved in both, commensal and pathogenic bacteria. Type 1 pili, tightly regulated by phase variation, are considered an important virulence factor of pathogenic bacteria as they facilitate invasion into host cells. While invasion represents a de facto passive mechanism for pathogens to escape the host immune response, we demonstrate a fundamental role of type 1 pili as active modulators of the innate and adaptive immune response. AU - Tomasek, Kathrin ID - 10307 SN - 2663-337X TI - Pathogenic Escherichia coli hijack the host immune response ER - TY - THES AB - Nitrogen is an essential macronutrient determining plant growth, development and affecting agricultural productivity. Root, as a hub that perceives and integrates local and systemic signals on the plant’s external and endogenous nitrogen resources, communicates with other plant organs to consolidate their physiology and development in accordance with actual nitrogen balance. Over the last years, numerous studies demonstrated that these comprehensive developmental adaptations rely on the interaction between pathways controlling nitrogen homeostasis and hormonal networks acting globally in the plant body. However, molecular insights into how the information about the nitrogen status is translated through hormonal pathways into specific developmental output are lacking. In my work, I addressed so far poorly understood mechanisms underlying root-to-shoot communication that lead to a rapid re-adjustment of shoot growth and development after nitrate provision. Applying a combination of molecular, cell, and developmental biology approaches, genetics and grafting experiments as well as hormonal analytics, I identified and characterized an unknown molecular framework orchestrating shoot development with a root nitrate sensory system. AU - Abualia, Rashed ID - 10303 SN - 2663-337X TI - Role of hormones in nitrate regulated growth ER - TY - THES AB - The brain is one of the largest and most complex organs and it is composed of billions of neurons that communicate together enabling e.g. consciousness. The cerebral cortex is the largest site of neural integration in the central nervous system. Concerted radial migration of newly born cortical projection neurons, from their birthplace to their final position, is a key step in the assembly of the cerebral cortex. The cellular and molecular mechanisms regulating radial neuronal migration in vivo are however still unclear. Recent evidence suggests that distinct signaling cues act cell-autonomously but differentially at certain steps during the overall migration process. Moreover, functional analysis of genetic mosaics (mutant neurons present in wild-type/heterozygote environment) using the MADM (Mosaic Analysis with Double Markers) analyses in comparison to global knockout also indicate a significant degree of non-cell-autonomous and/or community effects in the control of cortical neuron migration. The interactions of cell-intrinsic (cell-autonomous) and cell-extrinsic (non-cell-autonomous) components are largely unknown. In part of this thesis work we established a MADM-based experimental strategy for the quantitative analysis of cell-autonomous gene function versus non-cell-autonomous and/or community effects. The direct comparison of mutant neurons from the genetic mosaic (cell-autonomous) to mutant neurons in the conditional and/or global knockout (cell-autonomous + non-cell-autonomous) allows to quantitatively analyze non-cell-autonomous effects. Such analysis enable the high-resolution analysis of projection neuron migration dynamics in distinct environments with concomitant isolation of genomic and proteomic profiles. Using these experimental paradigms and in combination with computational modeling we show and characterize the nature of non-cell-autonomous effects to coordinate radial neuron migration. Furthermore, this thesis discusses recent developments in neurodevelopment with focus on neuronal polarization and non-cell-autonomous mechanisms in neuronal migration. AU - Hansen, Andi H ID - 9962 KW - Neuronal migration KW - Non-cell-autonomous KW - Cell-autonomous KW - Neurodevelopmental disease SN - 2663-337X TI - Cell-autonomous gene function and non-cell-autonomous effects in radial projection neuron migration ER - TY - THES AB - Plant motions occur across a wide spectrum of timescales, ranging from seed dispersal through bursting (milliseconds) and stomatal opening (minutes) to long-term adaptation of gross architecture. Relatively fast motions include water-driven growth as exemplified by root cell expansion under abiotic/biotic stresses or during gravitropism. A showcase is a root growth inhibition in 30 seconds triggered by the phytohormone auxin. However, the cellular and molecular mechanisms are still largely unknown. This thesis covers the studies about this topic as follows. By taking advantage of microfluidics combined with live imaging, pharmaceutical tools, and transgenic lines, we examined the kinetics of and causal relationship among various auxininduced rapid cellular changes in root growth, apoplastic pH, cytosolic Ca2+, cortical microtubule (CMT) orientation, and vacuolar morphology. We revealed that CMT reorientation and vacuolar constriction are the consequence of growth itself instead of responding directly to auxin. In contrast, auxin induces apoplast alkalinization to rapidly inhibit root growth in 30 seconds. This auxin-triggered apoplast alkalinization results from rapid H+- influx that is contributed by Ca2+ inward channel CYCLIC NUCLEOTIDE-GATED CHANNEL 14 (CNGC14)-dependent Ca2+ signaling. To dissect which auxin signaling mediates the rapid apoplast alkalinization, we combined microfluidics and genetic engineering to verify that TIR1/AFB receptors conduct a non-transcriptional regulation on Ca2+ and H+ -influx. This non-canonical pathway is mostly mediated by the cytosolic portion of TIR1/AFB. On the other hand, we uncovered, using biochemical and phospho-proteomic analysis, that auxin cell surface signaling component TRANSMEMBRANE KINASE 1 (TMK1) plays a negative role during auxin-trigger apoplast alkalinization and root growth inhibition through directly activating PM H+ -ATPases. Therefore, we discovered that PM H+ -ATPases counteract instead of mediate the auxintriggered rapid H+ -influx, and that TIR1/AFB and TMK1 regulate root growth antagonistically. This opposite effect of TIR1/AFB and TMK1 is consistent during auxin-induced hypocotyl elongation, leading us to explore the relation of two signaling pathways. Assisted with biochemistry and fluorescent imaging, we verified for the first time that TIR1/AFB and TMK1 can interact with each other. The ability of TIR1/AFB binding to membrane lipid provides a basis for the interaction of plasma membrane- and cytosol-localized proteins. Besides, transgenic analysis combined with genetic engineering and biochemistry showed that vi they do function in the same pathway. Particularly, auxin-induced TMK1 increase is TIR1/AFB dependent, suggesting TIR1/AFB regulation on TMK1. Conversely, TMK1 also regulates TIR1/AFB protein levels and thus auxin canonical signaling. To follow the study of rapid growth regulation, we analyzed another rapid growth regulator, signaling peptide RALF1. We showed that RALF1 also triggers a rapid and reversible growth inhibition caused by H + influx, highly resembling but not dependent on auxin. Besides, RALF1 promotes auxin biosynthesis by increasing expression of auxin biosynthesis enzyme YUCCAs and thus induces auxin signaling in ca. 1 hour, contributing to the sustained RALF1-triggered growth inhibition. These studies collectively contribute to understanding rapid regulation on plant cell growth, novel auxin signaling pathway as well as auxin-peptide crosstalk. AU - Li, Lanxin ID - 10083 SN - 2663-337X TI - Rapid cell growth regulation in Arabidopsis ER - TY - THES AB - Indirect reciprocity in evolutionary game theory is a prominent mechanism for explaining the evolution of cooperation among unrelated individuals. In contrast to direct reciprocity, which is based on individuals meeting repeatedly, and conditionally cooperating by using their own experiences, indirect reciprocity is based on individuals’ reputations. If a player helps another, this increases the helper’s public standing, benefitting them in the future. This lets cooperation in the population emerge without individuals having to meet more than once. While the two modes of reciprocity are intertwined, they are difficult to compare. Thus, they are usually studied in isolation. Direct reciprocity can maintain cooperation with simple strategies, and is robust against noise even when players do not remember more than their partner’s last action. Meanwhile, indirect reciprocity requires its successful strategies, or social norms, to be more complex. Exhaustive search previously identified eight such norms, called the “leading eight”, which excel at maintaining cooperation. However, as the first result of this thesis, we show that the leading eight break down once we remove the fundamental assumption that information is synchronized and public, such that everyone agrees on reputations. Once we consider a more realistic scenario of imperfect information, where reputations are private, and individuals occasionally misinterpret or miss observations, the leading eight do not promote cooperation anymore. Instead, minor initial disagreements can proliferate, fragmenting populations into subgroups. In a next step, we consider ways to mitigate this issue. We first explore whether introducing “generosity” can stabilize cooperation when players use the leading eight strategies in noisy environments. This approach of modifying strategies to include probabilistic elements for coping with errors is known to work well in direct reciprocity. However, as we show here, it fails for the more complex norms of indirect reciprocity. Imperfect information still prevents cooperation from evolving. On the other hand, we succeeded to show in this thesis that modifying the leading eight to use “quantitative assessment”, i.e. tracking reputation scores on a scale beyond good and bad, and making overall judgments of others based on a threshold, is highly successful, even when noise increases in the environment. Cooperation can flourish when reputations are more nuanced, and players have a broader understanding what it means to be “good.” Finally, we present a single theoretical framework that unites the two modes of reciprocity despite their differences. Within this framework, we identify a novel simple and successful strategy for indirect reciprocity, which can cope with noisy environments and has an analogue in direct reciprocity. We can also analyze decision making when different sources of information are available. Our results help highlight that for sustaining cooperation, already the most simple rules of reciprocity can be sufficient. AU - Schmid, Laura ID - 10293 SN - 2663-337X TI - Evolution of cooperation via (in)direct reciprocity under imperfect information ER - TY - THES AB - Plants maintain the capacity to develop new organs e.g. lateral roots post-embryonically throughout their whole life and thereby flexibly adapt to ever-changing environmental conditions. Plant hormones auxin and cytokinin are the main regulators of the lateral root organogenesis. Additionally to their solo activities, the interaction between auxin and cytokinin plays crucial role in fine-tuning of lateral root development and growth. In particular, cytokinin modulates auxin distribution within the developing lateral root by affecting the endomembrane trafficking of auxin transporter PIN1 and promoting its vacuolar degradation (Marhavý et al., 2011, 2014). This effect is independent of transcription and translation. Therefore, it suggests novel, non-canonical cytokinin activity occuring possibly on the posttranslational level. Impact of cytokinin and other plant hormones on auxin transporters (including PIN1) on the posttranslational level is described in detail in the introduction part of this thesis in a form of a review (Semeradova et al., 2020). To gain insights into the molecular machinery underlying cytokinin effect on the endomembrane trafficking in the plant cell, in particular on the PIN1 degradation, we conducted two large proteomic screens: 1) Identification of cytokinin binding proteins using chemical proteomics. 2) Monitoring of proteomic and phosphoproteomic changes upon cytokinin treatment. In the first screen, we identified DYNAMIN RELATED PROTEIN 2A (DRP2A). We found that DRP2A plays a role in cytokinin regulated processes during the plant growth and that cytokinin treatment promotes destabilization of DRP2A protein. However, the role of DRP2A in the PIN1 degradation remains to be elucidated. In the second screen, we found VACUOLAR PROTEIN SORTING 9A (VPS9A). VPS9a plays crucial role in plant’s response to cytokin and in cytokinin mediated PIN1 degradation. Altogether, we identified proteins, which bind to cytokinin and proteins that in response to cytokinin exhibit significantly changed abundance or phosphorylation pattern. By combining information from these two screens, we can pave our way towards understanding of noncanonical cytokinin effects. AU - Semerádová, Hana ID - 10135 SN - 2663-337X TI - Molecular mechanisms of the cytokinin-regulated endomembrane trafficking to coordinate plant organogenesis ER - TY - THES AB - Most real-world flows are multiphase, yet we know little about them compared to their single-phase counterparts. Multiphase flows are more difficult to investigate as their dynamics occur in large parameter space and involve complex phenomena such as preferential concentration, turbulence modulation, non-Newtonian rheology, etc. Over the last few decades, experiments in particle-laden flows have taken a back seat in favour of ever-improving computational resources. However, computers are still not powerful enough to simulate a real-world fluid with millions of finite-size particles. Experiments are essential not only because they offer a reliable way to investigate real-world multiphase flows but also because they serve to validate numerical studies and steer the research in a relevant direction. In this work, we have experimentally investigated particle-laden flows in pipes, and in particular, examined the effect of particles on the laminar-turbulent transition and the drag scaling in turbulent flows. For particle-laden pipe flows, an earlier study [Matas et al., 2003] reported how the sub-critical (i.e., hysteretic) transition that occurs via localised turbulent structures called puffs is affected by the addition of particles. In this study, in addition to this known transition, we found a super-critical transition to a globally fluctuating state with increasing particle concentration. At the same time, the Newtonian-type transition via puffs is delayed to larger Reynolds numbers. At an even higher concentration, only the globally fluctuating state is found. The dynamics of particle-laden flows are hence determined by two competing instabilities that give rise to three flow regimes: Newtonian-type turbulence at low, a particle-induced globally fluctuating state at high, and a coexistence state at intermediate concentrations. The effect of particles on turbulent drag is ambiguous, with studies reporting drag reduction, no net change, and even drag increase. The ambiguity arises because, in addition to particle concentration, particle shape, size, and density also affect the net drag. Even similar particles might affect the flow dissimilarly in different Reynolds number and concentration ranges. In the present study, we explored a wide range of both Reynolds number and concentration, using spherical as well as cylindrical particles. We found that the spherical particles do not reduce drag while the cylindrical particles are drag-reducing within a specific Reynolds number interval. The interval strongly depends on the particle concentration and the relative size of the pipe and particles. Within this interval, the magnitude of drag reduction reaches a maximum. These drag reduction maxima appear to fall onto a distinct power-law curve irrespective of the pipe diameter and particle concentration, and this curve can be considered as the maximum drag reduction asymptote for a given fibre shape. Such an asymptote is well known for polymeric flows but had not been identified for particle-laden flows prior to this work. AU - Agrawal, Nishchal ID - 9728 KW - Drag Reduction KW - Transition to Turbulence KW - Multiphase Flows KW - particle Laden Flows KW - Complex Flows KW - Experiments KW - Fluid Dynamics SN - 2663-337X TI - Transition to turbulence and drag reduction in particle-laden pipe flows ER - TY - THES AB - This thesis is based on three main topics: In the first part, we study convergence of discrete gradient flow structures associated with regular finite-volume discretisations of Fokker-Planck equations. We show evolutionary I convergence of the discrete gradient flows to the L2-Wasserstein gradient flow corresponding to the solution of a Fokker-Planck equation in arbitrary dimension d >= 1. Along the argument, we prove Mosco- and I-convergence results for discrete energy functionals, which are of independent interest for convergence of equivalent gradient flow structures in Hilbert spaces. The second part investigates L2-Wasserstein flows on metric graph. The starting point is a Benamou-Brenier formula for the L2-Wasserstein distance, which is proved via a regularisation scheme for solutions of the continuity equation, adapted to the peculiar geometric structure of metric graphs. Based on those results, we show that the L2-Wasserstein space over a metric graph admits a gradient flow which may be identified as a solution of a Fokker-Planck equation. In the third part, we focus again on the discrete gradient flows, already encountered in the first part. We propose a variational structure which extends the gradient flow structure to Markov chains violating the detailed-balance conditions. Using this structure, we characterise contraction estimates for the discrete heat flow in terms of convexity of corresponding path-dependent energy functionals. In addition, we use this approach to derive several functional inequalities for said functionals. AU - Forkert, Dominik L ID - 7629 SN - 2663-337X TI - Gradient flows in spaces of probability measures for finite-volume schemes, metric graphs and non-reversible Markov chains ER - TY - THES AB - This thesis concerns itself with the interactions of evolutionary and ecological forces and the consequences on genetic diversity and the ultimate survival of populations. It is important to understand what signals processes leave on the genome and what we can infer from such data, which is usually abundant but noisy. Furthermore, understanding how and when populations adapt or go extinct is important for practical purposes, such as the genetic management of populations, as well as for theoretical questions, since local adaptation can be the first step toward speciation. In Chapter 2, we introduce the method of maximum entropy to approximate the demographic changes of a population in a simple setting, namely the logistic growth model with immigration. We show that this method is not only a powerful tool in physics but can be gainfully applied in an ecological framework. We investigate how well it approximates the real behavior of the system, and find that is does so, even in unexpected situations. Finally, we illustrate how it can model changing environments. In Chapter 3, we analyze the co-evolution of allele frequencies and population sizes in an infinite island model. We give conditions under which polygenic adaptation to a rare habitat is possible. The model we use is based on the diffusion approximation, considers eco-evolutionary feedback mechanisms (hard selection), and treats both drift and environmental fluctuations explicitly. We also look at limiting scenarios, for which we derive analytical expressions. In Chapter 4, we present a coalescent based simulation tool to obtain patterns of diversity in a spatially explicit subdivided population, in which the demographic history of each subpopulation can be specified. We compare the results to existing predictions, and explore the relative importance of time and space under a variety of spatial arrangements and demographic histories, such as expansion and extinction. In the last chapter, we give a brief outlook to further research. AU - Szep, Eniko ID - 8574 TI - Local adaptation in metapopulations ER - TY - THES AB - We study the interacting homogeneous Bose gas in two spatial dimensions in the thermodynamic limit at fixed density. We shall be concerned with some mathematical aspects of this complicated problem in many-body quantum mechanics. More specifically, we consider the dilute limit where the scattering length of the interaction potential, which is a measure for the effective range of the potential, is small compared to the average distance between the particles. We are interested in a setting with positive (i.e., non-zero) temperature. After giving a survey of the relevant literature in the field, we provide some facts and examples to set expectations for the two-dimensional system. The crucial difference to the three-dimensional system is that there is no Bose–Einstein condensate at positive temperature due to the Hohenberg–Mermin–Wagner theorem. However, it turns out that an asymptotic formula for the free energy holds similarly to the three-dimensional case. We motivate this formula by considering a toy model with δ interaction potential. By restricting this model Hamiltonian to certain trial states with a quasi-condensate we obtain an upper bound for the free energy that still has the quasi-condensate fraction as a free parameter. When minimizing over the quasi-condensate fraction, we obtain the Berezinskii–Kosterlitz–Thouless critical temperature for superfluidity, which plays an important role in our rigorous contribution. The mathematically rigorous result that we prove concerns the specific free energy in the dilute limit. We give upper and lower bounds on the free energy in terms of the free energy of the non-interacting system and a correction term coming from the interaction. Both bounds match and thus we obtain the leading term of an asymptotic approximation in the dilute limit, provided the thermal wavelength of the particles is of the same order (or larger) than the average distance between the particles. The remarkable feature of this result is its generality: the correction term depends on the interaction potential only through its scattering length and it holds for all nonnegative interaction potentials with finite scattering length that are measurable. In particular, this allows to model an interaction of hard disks. AU - Mayer, Simon ID - 7514 SN - 2663-337X TI - The free energy of a dilute two-dimensional Bose gas ER - TY - THES AB - Mrp (Multi resistance and pH adaptation) are broadly distributed secondary active antiporters that catalyze the transport of monovalent ions such as sodium and potassium outside of the cell coupled to the inward translocation of protons. Mrp antiporters are unique in a way that they are composed of seven subunits (MrpABCDEFG) encoded in a single operon, whereas other antiporters catalyzing the same reaction are mostly encoded by a single gene. Mrp exchangers are crucial for intracellular pH homeostasis and Na+ efflux, essential mechanisms for H+ uptake under alkaline environments and for reduction of the intracellular concentration of toxic cations. Mrp displays no homology to any other monovalent Na+(K+)/H+ antiporters but Mrp subunits have primary sequence similarity to essential redox-driven proton pumps, such as respiratory complex I and membrane-bound hydrogenases. This similarity reinforces the hypothesis that these present day redox-driven proton pumps are descended from the Mrp antiporter. The Mrp structure serves as a model to understand the yet obscure coupling mechanism between ion or electron transfer and proton translocation in this large group of proteins. In the thesis, I am presenting the purification, biochemical analysis, cryo-EM analysis and molecular structure of the Mrp complex from Anoxybacillus flavithermus solved by cryo-EM at 3.0 Å resolution. Numerous conditions were screened to purify Mrp to high homogeneity and to obtain an appropriate distribution of single particles on cryo-EM grids covered with a continuous layer of ultrathin carbon. A preferred particle orientation problem was solved by performing a tilted data collection. The activity assays showed the specific pH-dependent profile of secondary active antiporters. The molecular structure shows that Mrp is a dimer of seven-subunit protomers with 50 trans-membrane helices each. The dimer interface is built by many short and tilted transmembrane helices, probably causing a thinning of the bacterial membrane. The surface charge distribution shows an extraordinary asymmetry within each monomer, revealing presumable proton and sodium translocation pathways. The two largest and homologous Mrp subunits MrpA and MrpD probably translocate one proton each into the cell. The sodium ion is likely being translocated in the opposite direction within the small subunits along a ladder of charged and conserved residues. Based on the structure, we propose a mechanism were the antiport activity is accomplished via electrostatic interactions between the charged cations and key charged residues. The flexible key TM helices coordinate these electrostatic interactions, while the membrane thinning between the monomers enables the translocation of sodium across the charged membrane. The entire family of redox-driven proton pumps is likely to perform their mechanism in a likewise manner. AU - Steiner, Julia ID - 8353 SN - 2663-337X TI - Biochemical and structural investigation of the Mrp antiporter, an ancestor of complex I ER - TY - THES AB - The plant hormone auxin plays indispensable roles in plant growth and development. An essential level of regulation in auxin action is the directional auxin transport within cells. The establishment of auxin gradient in plant tissue has been attributed to local auxin biosynthesis and directional intercellular auxin transport, which both are controlled by various environmental and developmental signals. It is well established that asymmetric auxin distribution in cells is achieved by polarly localized PIN-FORMED (PIN) auxin efflux transporters. Despite the initial insights into cellular mechanisms of PIN polarization obtained from the last decades, the molecular mechanism and specific regulators mediating PIN polarization remains elusive. In this thesis, we aim to find novel players in PIN subcellular polarity regulation during Arabidopsis development. We first characterize the physiological effect of piperonylic acid (PA) on Arabidopsis hypocotyl gravitropic bending and PIN polarization. Secondly, we reveal the importance of SCFTIR1/AFB auxin signaling pathway in shoot gravitropism bending termination. In addition, we also explore the role of myosin XI complex, and actin cytoskeleton in auxin feedback regulation on PIN polarity. In Chapter 1, we give an overview of the current knowledge about PIN-mediated auxin fluxes in various plant tropic responses. In Chapter 2, we study the physiological effect of PA on shoot gravitropic bending. Our results show that PA treatment inhibits auxin-mediated PIN3 repolarization by interfering with PINOID and PIN3 phosphorylation status, ultimately leading to hyperbending hypocotyls. In Chapter 3, we provide evidence to show that the SCFTIR1/AFB nuclear auxin signaling pathway is crucial and required for auxin-mediated PIN3 repolarization and shoot gravitropic bending termination. In Chapter 4, we perform a phosphoproteomics approach and identify the motor protein Myosin XI and its binding protein, the MadB2 family, as an essential regulator of PIN polarity for auxin-canalization related developmental processes. In Chapter 5, we demonstrate the vital role of actin cytoskeleton in auxin feedback on PIN polarity by regulating PIN subcellular trafficking. Overall, the data presented in this PhD thesis brings novel insights into the PIN polar localization regulation that resulted in the (re)establishment of the polar auxin flow and gradient in response to environmental stimuli during plant development. AU - Han, Huibin ID - 8589 SN - 2663-337X TI - Novel insights into PIN polarity regulation during Arabidopsis development ER - TY - THES AB - In the thesis we focus on the interplay of the biophysics and evolution of gene regulation. We start by addressing how the type of prokaryotic gene regulation – activation and repression – affects spurious binding to DNA, also known as transcriptional crosstalk. We propose that regulatory interference caused by excess regulatory proteins in the dense cellular medium – global crosstalk – could be a factor in determining which type of gene regulatory network is evolutionarily preferred. Next,we use a normative approach in eukaryotic gene regulation to describe minimal non-equilibrium enhancer models that optimize so-called regulatory phenotypes. We find a class of models that differ from standard thermodynamic equilibrium models by a single parameter that notably increases the regulatory performance. Next chapter addresses the question of genotype-phenotype-fitness maps of higher dimensional phenotypes. We show that our biophysically realistic approach allows us to understand how the mechanisms of promoter function constrain genotypephenotype maps, and how they affect the evolutionary trajectories of promoters. In the last chapter we ask whether the intrinsic instability of gene duplication and amplification provides a generic alternative to canonical gene regulation. Using mathematical modeling, we show that amplifications can tune gene expression in many environments, including those where transcription factor-based schemes are hard to evolve or maintain. AU - Grah, Rok ID - 8155 SN - 2663-337X TI - Gene regulation across scales – how biophysical constraints shape evolution ER - TY - THES AB - Many methods for the reconstruction of shapes from sets of points produce ordered simplicial complexes, which are collections of vertices, edges, triangles, and their higher-dimensional analogues, called simplices, in which every simplex gets assigned a real value measuring its size. This thesis studies ordered simplicial complexes, with a focus on their topology, which reflects the connectedness of the represented shapes and the presence of holes. We are interested both in understanding better the structure of these complexes, as well as in developing algorithms for applications. For the Delaunay triangulation, the most popular measure for a simplex is the radius of the smallest empty circumsphere. Based on it, we revisit Alpha and Wrap complexes and experimentally determine their probabilistic properties for random data. Also, we prove the existence of tri-partitions, propose algorithms to open and close holes, and extend the concepts from Euclidean to Bregman geometries. AU - Ölsböck, Katharina ID - 7460 KW - shape reconstruction KW - hole manipulation KW - ordered complexes KW - Alpha complex KW - Wrap complex KW - computational topology KW - Bregman geometry SN - 2663-337X TI - The hole system of triangulated shapes ER - TY - THES AB - A search problem lies in the complexity class FNP if a solution to the given instance of the problem can be verified efficiently. The complexity class TFNP consists of all search problems in FNP that are total in the sense that a solution is guaranteed to exist. TFNP contains a host of interesting problems from fields such as algorithmic game theory, computational topology, number theory and combinatorics. Since TFNP is a semantic class, it is unlikely to have a complete problem. Instead, one studies its syntactic subclasses which are defined based on the combinatorial principle used to argue totality. Of particular interest is the subclass PPAD, which contains important problems like computing Nash equilibrium for bimatrix games and computational counterparts of several fixed-point theorems as complete. In the thesis, we undertake the study of averagecase hardness of TFNP, and in particular its subclass PPAD. Almost nothing was known about average-case hardness of PPAD before a series of recent results showed how to achieve it using a cryptographic primitive called program obfuscation. However, it is currently not known how to construct program obfuscation from standard cryptographic assumptions. Therefore, it is desirable to relax the assumption under which average-case hardness of PPAD can be shown. In the thesis we take a step in this direction. First, we show that assuming the (average-case) hardness of a numbertheoretic problem related to factoring of integers, which we call Iterated-Squaring, PPAD is hard-on-average in the random-oracle model. Then we strengthen this result to show that the average-case hardness of PPAD reduces to the (adaptive) soundness of the Fiat-Shamir Transform, a well-known technique used to compile a public-coin interactive protocol into a non-interactive one. As a corollary, we obtain average-case hardness for PPAD in the random-oracle model assuming the worst-case hardness of #SAT. Moreover, the above results can all be strengthened to obtain average-case hardness for the class CLS ⊆ PPAD. Our main technical contribution is constructing incrementally-verifiable procedures for computing Iterated-Squaring and #SAT. By incrementally-verifiable, we mean that every intermediate state of the computation includes a proof of its correctness, and the proof can be updated and verified in polynomial time. Previous constructions of such procedures relied on strong, non-standard assumptions. Instead, we introduce a technique called recursive proof-merging to obtain the same from weaker assumptions. AU - Kamath Hosdurg, Chethan ID - 7896 SN - 2663-337X TI - On the average-case hardness of total search problems ER - TY - THES AB - This thesis considers two examples of reconfiguration problems: flipping edges in edge-labelled triangulations of planar point sets and swapping labelled tokens placed on vertices of a graph. In both cases the studied structures – all the triangulations of a given point set or all token placements on a given graph – can be thought of as vertices of the so-called reconfiguration graph, in which two vertices are adjacent if the corresponding structures differ by a single elementary operation – by a flip of a diagonal in a triangulation or by a swap of tokens on adjacent vertices, respectively. We study the reconfiguration of one instance of a structure into another via (shortest) paths in the reconfiguration graph. For triangulations of point sets in which each edge has a unique label and a flip transfers the label from the removed edge to the new edge, we prove a polynomial-time testable condition, called the Orbit Theorem, that characterizes when two triangulations of the same point set lie in the same connected component of the reconfiguration graph. The condition was first conjectured by Bose, Lubiw, Pathak and Verdonschot. We additionally provide a polynomial time algorithm that computes a reconfiguring flip sequence, if it exists. Our proof of the Orbit Theorem uses topological properties of a certain high-dimensional cell complex that has the usual reconfiguration graph as its 1-skeleton. In the context of token swapping on a tree graph, we make partial progress on the problem of finding shortest reconfiguration sequences. We disprove the so-called Happy Leaf Conjecture and demonstrate the importance of swapping tokens that are already placed at the correct vertices. We also prove that a generalization of the problem to weighted coloured token swapping is NP-hard on trees but solvable in polynomial time on paths and stars. AU - Masárová, Zuzana ID - 7944 KW - reconfiguration KW - reconfiguration graph KW - triangulations KW - flip KW - constrained triangulations KW - shellability KW - piecewise-linear balls KW - token swapping KW - trees KW - coloured weighted token swapping SN - 2663-337X TI - Reconfiguration problems ER - TY - THES AB - One of the most striking hallmarks of the eukaryotic cell is the presence of intracellular vesicles and organelles. Each of these membrane-enclosed compartments has a distinct composition of lipids and proteins, which is essential for accurate membrane traffic and homeostasis. Interestingly, their biochemical identities are achieved with the help of small GTPases of the Rab family, which cycle between GDP- and GTP-bound forms on the selected membrane surface. While this activity switch is well understood for an individual protein, how Rab GTPases collectively transition between states to generate decisive signal propagation in space and time is unclear. In my PhD thesis, I present in vitro reconstitution experiments with theoretical modeling to systematically study a minimal Rab5 activation network from bottom-up. We find that positive feedback based on known molecular interactions gives rise to bistable GTPase activity switching on system’s scale. Furthermore, we determine that collective transition near the critical point is intrinsically stochastic and provide evidence that the inactive Rab5 abundance on the membrane can shape the network response. Finally, we demonstrate that collective switching can spread on the lipid bilayer as a traveling activation wave, representing a possible emergent activity pattern in endosomal maturation. Together, our findings reveal new insights into the self-organization properties of signaling networks away from chemical equilibrium. Our work highlights the importance of systematic characterization of biochemical systems in well-defined physiological conditions. This way, we were able to answer long-standing open questions in the field and close the gap between regulatory processes on a molecular scale and emergent responses on system’s level. AU - Bezeljak, Urban ID - 8341 SN - 2663-337X TI - In vitro reconstitution of a Rab activation switch ER -