TY - THES AB - Modern computer vision systems heavily rely on statistical machine learning models, which typically require large amounts of labeled data to be learned reliably. Moreover, very recently computer vision research widely adopted techniques for representation learning, which further increase the demand for labeled data. However, for many important practical problems there is relatively small amount of labeled data available, so it is problematic to leverage full potential of the representation learning methods. One way to overcome this obstacle is to invest substantial resources into producing large labelled datasets. Unfortunately, this can be prohibitively expensive in practice. In this thesis we focus on the alternative way of tackling the aforementioned issue. We concentrate on methods, which make use of weakly-labeled or even unlabeled data. Specifically, the first half of the thesis is dedicated to the semantic image segmentation task. We develop a technique, which achieves competitive segmentation performance and only requires annotations in a form of global image-level labels instead of dense segmentation masks. Subsequently, we present a new methodology, which further improves segmentation performance by leveraging tiny additional feedback from a human annotator. By using our methods practitioners can greatly reduce the amount of data annotation effort, which is required to learn modern image segmentation models. In the second half of the thesis we focus on methods for learning from unlabeled visual data. We study a family of autoregressive models for modeling structure of natural images and discuss potential applications of these models. Moreover, we conduct in-depth study of one of these applications, where we develop the state-of-the-art model for the probabilistic image colorization task. AU - Kolesnikov, Alexander ID - 197 SN - 2663-337X TI - Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images ER - TY - THES AB - This thesis is concerned with the inference of current population structure based on geo-referenced genetic data. The underlying idea is that population structure affects its spatial genetic structure. Therefore, genotype information can be utilized to estimate important demographic parameters such as migration rates. These indirect estimates of population structure have become very attractive, as genotype data is now widely available. However, there also has been much concern about these approaches. Importantly, genetic structure can be influenced by many complex patterns, which often cannot be disentangled. Moreover, many methods merely fit heuristic patterns of genetic structure, and do not build upon population genetics theory. Here, I describe two novel inference methods that address these shortcomings. In Chapter 2, I introduce an inference scheme based on a new type of signal, identity by descent (IBD) blocks. Recently, it has become feasible to detect such long blocks of genome shared between pairs of samples. These blocks are direct traces of recent coalescence events. As such, they contain ample signal for inferring recent demography. I examine sharing of IBD blocks in two-dimensional populations with local migration. Using a diffusion approximation, I derive formulas for an isolation by distance pattern of long IBD blocks and show that sharing of long IBD blocks approaches rapid exponential decay for growing sample distance. I describe an inference scheme based on these results. It can robustly estimate the dispersal rate and population density, which is demonstrated on simulated data. I also show an application to estimate mean migration and the rate of recent population growth within Eastern Europe. Chapter 3 is about a novel method to estimate barriers to gene flow in a two dimensional population. This inference scheme utilizes geographically localized allele frequency fluctuations - a classical isolation by distance signal. The strength of these local fluctuations increases on average next to a barrier, and there is less correlation across it. I again use a framework of diffusion of ancestral lineages to model this effect, and provide an efficient numerical implementation to fit the results to geo-referenced biallelic SNP data. This inference scheme is able to robustly estimate strong barriers to gene flow, as tests on simulated data confirm. AU - Ringbauer, Harald ID - 200 SN - 2663-337X TI - Inferring recent demography from spatial genetic structure ER - TY - THES AB - The aim of this thesis was the development of new strategies for optical and optogenetic control of proliferative and pro-survival signaling, and characterizing them from the molecular mechanism up to cellular effects. These new light-based methods have unique features, such as red light as an activator, or the avoidance of gene delivery, which enable to overcome current limitations, such as light delivery to target tissues and feasibility as therapeutic approach. A special focus was placed on implementing these new light-based approaches in pancreatic β-cells, as β-cells are the key players in diabetes and especially their loss in number negatively affects disease progression. Currently no treatment options are available to compensate the lack of functional β-cells in diabetic patients. In a first approach, red-light-activated growth factor receptors, in particular receptor tyrosine kinases were engineered and characterized. Receptor activation with light allows spatio-temporal control compared to ligand-based activation, and especially red light exhibits deeper tissue penetration than other wavelengths of the visible spectrum. Red-light-activated receptor tyrosine kinases robustly activated major growth factor related signaling pathways with a high temporal resolution. Moreover, the remote activation of the proliferative MAPK/Erk pathway by red-light-activated receptor tyrosine kinases in a pancreatic β-cell line was also achieved, through one centimeter thick mouse tissue. Although red-light-activated receptor tyrosine kinases are particularly attractive for applications in animal models due to the deep tissue penetration of red light, a drawback, especially with regard to translation into humans, is the requirement of gene therapy. In a second approach an endogenous light-sensitive mechanism was identified and its potential to promote proliferative and pro-survival signals was explored, towards light-based tissue regeneration without the need for gene transfer. Blue-green light illumination was found to be sufficient for the activation of proliferation and survival promoting signaling pathways in primary pancreatic murine and human islets. Blue-green light also led to an increase in proliferation of primary islet cells, an effect which was shown to be mostly β-cell specific in human islets. Moreover, it was demonstrated that this approach of pancreatic β-cell expansion did not have any negative effect on the β-cell function, in particular on their insulin secretion capacity. In contrast, a trend for enhanced insulin secretion under high glucose conditions after illumination was detected. In order to unravel the detailed characteristics of this endogenous light-sensitive mechanism, the precise light requirements were determined. In addition, the expression of light sensing proteins, OPN3 and rhodopsin, was detected. The observed effects were found to be independent of handling effects such as temperature differences and cytochrome c oxidase dependent ATP increase, but they were found to be enhanced through the knockout of OPN3. The exact mechanism of how islets cells sense light and the identity of the photoreceptor remains unknown. Summarized two new light-based systems with unique features were established that enable the activation of proliferative and pro-survival signaling pathways. While red-light-activated receptor tyrosine kinases open a new avenue for optogenetics research, by allowing non-invasive control of signaling in vivo, the identified endogenous light-sensitive mechanism has the potential to be the basis of a gene therapy-free therapeutical approach for light-based β-cell expansion. AU - Gschaider-Reichhart, Eva ID - 418 SN - 2663-337X TI - Optical and optogenetic control of proliferation and survival ER - TY - THES AB - In this thesis we will discuss systems of point interacting fermions, their stability and other spectral properties. Whereas for bosons a point interacting system is always unstable this ques- tion is more subtle for a gas of two species of fermions. In particular the answer depends on the mass ratio between these two species. Most of this work will be focused on the N + M model which consists of two species of fermions with N, M particles respectively which interact via point interactions. We will introduce this model using a formal limit and discuss the N + 1 system in more detail. In particular, we will show that for mass ratios above a critical one, which does not depend on the particle number, the N + 1 system is stable. In the context of this model we will prove rigorous versions of Tan relations which relate various quantities of the point-interacting model. By restricting the N + 1 system to a box we define a finite density model with point in- teractions. In the context of this system we will discuss the energy change when introducing a point-interacting impurity into a system of non-interacting fermions. We will see that this change in energy is bounded independently of the particle number and in particular the bound only depends on the density and the scattering length. As another special case of the N + M model we will show stability of the 2 + 2 model for mass ratios in an interval around one. Further we will investigate a different model of point interactions which was discussed before in the literature and which is, contrary to the N + M model, not given by a limiting procedure but is based on a Dirichlet form. We will show that this system behaves trivially in the thermodynamic limit, i.e. the free energy per particle is the same as the one of the non-interacting system. AU - Moser, Thomas ID - 52 SN - 2663-337X TI - Point interactions in systems of fermions ER - TY - THES AB - A qubit, a unit of quantum information, is essentially any quantum mechanical two-level system which can be coherently controlled. Still, to be used for computation, it has to fulfill criteria. Qubits, regardless of the system in which they are realized, suffer from decoherence. This leads to loss of the information stored in the qubit. The upper bound of the time scale on which decoherence happens is set by the spin relaxation time. In this thesis I studied a two-level system consisting of a Zeeman-split hole spin confined in a quantum dot formed in a Ge hut wire. Such Ge hut wires have emerged as a promising material system for the realization of spin qubits, due to the combination of two significant properties: long spin coherence time as expected for group IV semiconductors due to the low hyperfine interaction and a strong valence band spin-orbit coupling. Here, I present how to fabricate quantum dot devices suitable for electrical transport measurements. Coupled quantum dot devices allowed the realization of a charge sensor, which is electrostatically and tunnel coupled to a quantum dot. By integrating the charge sensor into a radio-frequency reflectometry setup, I performed for the first time single-shot readout measurements of hole spins and extracted the hole spin relaxation times in Ge hut wires. AU - Vukušić, Lada ID - 69 SN - 2663-337X TI - Charge sensing and spin relaxation times of holes in Ge hut wires ER - TY - THES AB - Neuronal networks in the brain consist of two main types of neuron, glutamatergic principal neurons and GABAergic interneurons. Although these interneurons only represent 10–20% of the whole population, they mediate feedback and feedforward inhibition and are involved in the generation of high-frequency network oscillations. A hallmark functional property of GABAergic interneurons, especially of the parvalbumin‑expressing (PV+) subtypes, is the speed of signaling at their output synapse across species and brain regions. Several molecular and subcellular factors may underlie the submillisecond signaling at GABAergic synapses. Such as the selective use of P/Q type Ca2+ channels and the tight coupling between Ca2+ channels and Ca2+ sensors of exocytosis. However, whether the molecular identity of the release sensor contributes to these signaling properties remains unclear. Besides, these interneurons are mainly show depression in response to train of stimuli. How could they keep sufficient release to control the activity of postsynaptic principal neurons during high network activity, is largely elusive. For my Ph.D. work, we firstly examined the Ca2+ sensor of exocytosis at the GABAergic basket cell (BC) to Purkinje cell (PC) synapse in the cerebellum. Immunolabeling suggested that BC terminals selectively expressed synaptotagmin 2 (Syt2), whereas synaptotagmin 1 (Syt1) was enriched in excitatory terminals. Genetic elimination of Syt2 reduced action potential-evoked release to ~10% compared to the wild-type control, identifying Syt2 as the major Ca2+ sensor at BC‑PC synapses. Differential adenovirus-mediated rescue revealed Syt2 triggered release with shorter latency and higher temporal precision, and mediated faster vesicle pool replenishment than Syt1. Furthermore, deletion of Syt2 severely reduced and delayed disynaptic inhibition following parallel fiber stimulation. Thus, the selective use of Syt2 as the release sensor at BC–PC synapse ensures fast feedforward inhibition in cerebellar microcircuits. Additionally, we tested the function of another synaptotagmin member, Syt7, for inhibitory synaptic transmission at the BC–PC synapse. Syt7 is thought to be a Ca2+ sensor that mediates asynchronous transmitter release and facilitation at synapses. However, it is strongly expressed in fast-spiking, PV+ GABAergic interneurons and the output synapses of these neurons produce only minimal asynchronous release and show depression rather than facilitation. How could Syt7, a facilitation sensor, contribute to the depressed inhibitory synaptic transmission needs to be further investigated and understood. Our results indicated that at the BC–PC synapse, Syt7 contributes to asynchronous release, pool replenishment and facilitation. In combination, these three effects ensure efficient transmitter release during high‑frequency activity and guarantee frequency independence of inhibition. Taken together, our results confirmed that Syt2, which has the fastest kinetic properties among all synaptotagmin members, is mainly used by the inhibitory BC‑PC synapse for synaptic transmission, contributing to the speed and temporal precision of transmitter release. Furthermore, we showed that Syt7, another highly expressed synaptotagmin member in the output synapses of cerebellar BCs, is used for ensuring efficient inhibitor synaptic transmission during high activity. AU - Chen, Chong ID - 324 SN - 2663-337X TI - Synaptotagmins ensure speed and efficiency of inhibitory neurotransmitter release ER - TY - THES AB - Function and activity of biomolecules often depend on their spatial arrangement. The method introduced here allows genetically encoding the spatial arrangement of proteins and DNA. The approach relies on staple proteins that fold double-stranded DNA into user-defined shapes. This thesis describes the development of staple proteins based on the DNA recognition of TAL effectors and presents experimentally derived rules for designing a variety of self-assembling nanoscale shapes featuring structural motifs such as curvature, vertices, corners, and multilayer helix packing. AU - Praetorius, Florian M ID - 14306 TI - Genetically encoding the spatial arrangement of DNA and proteins in self-assembling nanostructures ER - TY - THES AB - Consortial subscription contracts regulate the digital access to publications between publishers and scientific libraries. However, since a couple of years the tendency towards a freely accessible publishing (Open Access) intensifies. As a consequence of this trend the contractual relationship between licensor and licensee is gradually changing as well: More and more contracts exercise influence on open access publishing. The present study attempts to compare Austrian examples of consortial licence contracts, which include components of open access. It describes the difference between pure subscription contracts and differing innovative deals including open access components. Thereby it becomes obvious that for the evaluation of this licence contracts new methods are needed. An essential new element of such analyses is the evaluation of the open access publication numbers. So this study tries to carry out such publication analyses for Austrian open access deals focusing on quantitative questions: How does the number of publications evolve? How does the open access share change? Publications reports of the publishers and database queries from Scopus form the data basis. The analysis of the data points out that differing approaches of contracts result in highly divergent results: Particular deals can prioritize a saving in costs or else the increase of the open access rate. It is to be assumed that within the following years further numerous open access deals will be negotiated. The finding of this study shall provide guidance. AU - Villányi, Márton ID - 278 TI - Lizenzverträge mit Open-Access-Komponenten an österreichischen Bibliotheken ER - TY - THES AB - The eigenvalue density of many large random matrices is well approximated by a deterministic measure, the self-consistent density of states. In the present work, we show this behaviour for several classes of random matrices. In fact, we establish that, in each of these classes, the self-consistent density of states approximates the eigenvalue density of the random matrix on all scales slightly above the typical eigenvalue spacing. For large classes of random matrices, the self-consistent density of states exhibits several universal features. We prove that, under suitable assumptions, random Gram matrices and Hermitian random matrices with decaying correlations have a 1/3-Hölder continuous self-consistent density of states ρ on R, which is analytic, where it is positive, and has either a square root edge or a cubic root cusp, where it vanishes. We, thus, extend the validity of the corresponding result for Wigner-type matrices from [4, 5, 7]. We show that ρ is determined as the inverse Stieltjes transform of the normalized trace of the unique solution m(z) to the Dyson equation −m(z) −1 = z − a + S[m(z)] on C N×N with the constraint Im m(z) ≥ 0. Here, z lies in the complex upper half-plane, a is a self-adjoint element of C N×N and S is a positivity-preserving operator on C N×N encoding the first two moments of the random matrix. In order to analyze a possible limit of ρ for N → ∞ and address some applications in free probability theory, we also consider the Dyson equation on infinite dimensional von Neumann algebras. We present two applications to random matrices. We first establish that, under certain assumptions, large random matrices with independent entries have a rotationally symmetric self-consistent density of states which is supported on a centered disk in C. Moreover, it is infinitely often differentiable apart from a jump on the boundary of this disk. Second, we show edge universality at all regular (not necessarily extreme) spectral edges for Hermitian random matrices with decaying correlations. AU - Alt, Johannes ID - 149 SN - 2663-337X TI - Dyson equation and eigenvalue statistics of random matrices ER - TY - THES AB - Autism spectrum disorders (ASD) are a group of genetic disorders often overlapping with other neurological conditions. Despite the remarkable number of scientific breakthroughs of the last 100 years, the treatment of neurodevelopmental disorders (e.g. autism spectrum disorder, intellectual disability, epilepsy) remains a great challenge. Recent advancements in geno mics, like whole-exome or whole-genome sequencing, have enabled scientists to identify numerous mutations underlying neurodevelopmental disorders. Given the few hundred risk genes that were discovered, the etiological variability and the heterogeneous phenotypic outcomes, the need for genotype -along with phenotype- based diagnosis of individual patients becomes a requisite. Driven by this rationale, in a previous study our group described mutations, identified via whole - exome sequencing, in the gene BCKDK – encoding for a key regulator of branched chain amin o acid (BCAA) catabolism - as a cause of ASD. Following up on the role of BCAAs, in the study described here we show that the solute carrier transporter 7a5 (SLC7A5), a large neutral amino acid transporter localized mainly at the blood brain barrier (BBB), has an essential role in maintaining normal levels of brain BCAAs. In mice, deletion of Slc7a5 from the endothelial cells of the BBB leads to atypical brain amino acid profile, abnormal mRNA translation and severe neurolo gical abnormalities. Additionally, deletion of Slc7a5 from the neural progenitor cell population leads to microcephaly. Interestingly, we demonstrate that BCAA intracerebroventricular administration ameliorates abnormal behaviors in adult mutant mice. Furthermore, whole - exome sequencing of patients diagnosed with neurological dis o r ders helped us identify several patients with autistic traits, microcephaly and motor delay carrying deleterious homozygous mutations in the SLC7A5 gene. In conclusion, our data elucidate a neurological syndrome defined by SLC7A5 mutations and support an essential role for t he BCAA s in human bra in function. Together with r ecent studies (described in chapter two) that have successfully made the transition into clinical practice, our findings on the role of B CAAs might have a crucial impact on the development of novel individualized therapeutic strategies for ASD. AU - Tarlungeanu, Dora-Clara ID - 395 SN - 2663-337X TI - The branched chain amino acids in autism spectrum disorders ER -