@phdthesis{10727, abstract = {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.}, author = {Metzler, Sina}, issn = {2663-337X}, publisher = {Institute of Science and Technology Austria}, title = {{Pathogen-mediated sexual selection and immunization in ant colonies}}, doi = {10.15479/AT:ISTA:10727}, year = {2022}, } @phdthesis{10759, abstract = {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.}, author = {Rzadkowski, Wojciech}, issn = {2663-337X}, pages = {120}, publisher = {Institute of Science and Technology Austria}, title = {{Analytic and machine learning approaches to composite quantum impurities}}, doi = {10.15479/at:ista:10759}, year = {2022}, } @article{10787, abstract = {A species distributed across diverse environments may adapt to local conditions. We ask how quickly such a species changes its range in response to changed conditions. Szép et al. (Szép E, Sachdeva H, Barton NH. 2021 Polygenic local adaptation in metapopulations: a stochastic eco-evolutionary model. Evolution75, 1030–1045 (doi:10.1111/evo.14210)) used the infinite island model to find the stationary distribution of allele frequencies and deme sizes. We extend this to find how a metapopulation responds to changes in carrying capacity, selection strength, or migration rate when deme sizes are fixed. We further develop a ‘fixed-state’ approximation. Under this approximation, polymorphism is only possible for a narrow range of habitat proportions when selection is weak compared to drift, but for a much wider range otherwise. When rates of selection or migration relative to drift change in a single deme of the metapopulation, the population takes a time of order m−1 to reach the new equilibrium. However, even with many loci, there can be substantial fluctuations in net adaptation, because at each locus, alleles randomly get lost or fixed. Thus, in a finite metapopulation, variation may gradually be lost by chance, even if it would persist in an infinite metapopulation. When conditions change across the whole metapopulation, there can be rapid change, which is predicted well by the fixed-state approximation. This work helps towards an understanding of how metapopulations extend their range across diverse environments. This article is part of the theme issue ‘Species’ ranges in the face of changing environments (Part II)’.}, author = {Barton, Nicholas H and Olusanya, Oluwafunmilola O}, issn = {1471-2970}, journal = {Philosophical Transactions of the Royal Society B: Biological Sciences}, keywords = {General Agricultural and Biological Sciences, General Biochemistry, Genetics and Molecular Biology}, number = {1848}, publisher = {The Royal Society}, title = {{The response of a metapopulation to a changing environment}}, doi = {10.1098/rstb.2021.0009}, volume = {377}, year = {2022}, } @phdthesis{10799, abstract = {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.}, author = {Konstantinov, Nikola H}, isbn = {978-3-99078-015-2}, issn = {2663-337X}, keywords = {robustness, fairness, machine learning, PAC learning, adversarial learning}, pages = {176}, publisher = {Institute of Science and Technology Austria}, title = {{Robustness and fairness in machine learning}}, doi = {10.15479/at:ista:10799}, year = {2022}, } @article{10842, abstract = {We determine the unique factorization of some polynomials over a finite local commutative ring with identity explicitly. This solves and generalizes the main conjecture of Qian, Shi and Solé in [13]. We also give some applications to enumeration of certain generalized double circulant self-dual and linear complementary dual (LCD) codes over some finite rings together with an application in asymptotic coding theory.}, author = {Köse, Seyda and Özbudak, Ferruh}, issn = {1936-2455}, journal = {Cryptography and Communications}, keywords = {Applied Mathematics, Computational Theory and Mathematics, Computer Networks and Communications}, number = {4}, pages = {933--948}, publisher = {Springer Nature}, title = {{Factorization of some polynomials over finite local commutative rings and applications to certain self-dual and LCD codes}}, doi = {10.1007/s12095-022-00557-8}, volume = {14}, year = {2022}, } @article{10850, abstract = {We study two interacting quantum particles forming a bound state in d-dimensional free space, and constrain the particles in k directions to (0, ∞)k ×Rd−k, with Neumann boundary conditions. First, we prove that the ground state energy strictly decreases upon going from k to k+1. This shows that the particles stick to the corner where all boundary planes intersect. Second, we show that for all k the resulting Hamiltonian, after removing the free part of the kinetic energy, has only finitely many eigenvalues below the essential spectrum. This paper generalizes the work of Egger, Kerner and Pankrashkin (J. Spectr. Theory 10(4):1413–1444, 2020) to dimensions d > 1.}, author = {Roos, Barbara and Seiringer, Robert}, issn = {0022-1236}, journal = {Journal of Functional Analysis}, keywords = {Analysis}, number = {12}, publisher = {Elsevier}, title = {{Two-particle bound states at interfaces and corners}}, doi = {10.1016/j.jfa.2022.109455}, volume = {282}, year = {2022}, } @article{10920, abstract = {The spin-orbit interaction permits to control the state of a spin qubit via electric fields. For holes it is particularly strong, allowing for fast all electrical qubit manipulation, and yet an in-depth understanding of this interaction in hole systems is missing. Here we investigate, experimentally and theoretically, the effect of the cubic Rashba spin-orbit interaction on the mixing of the spin states by studying singlet-triplet oscillations in a planar Ge hole double quantum dot. Landau-Zener sweeps at different magnetic field directions allow us to disentangle the effects of the spin-orbit induced spin-flip term from those caused by strongly site-dependent and anisotropic quantum dot g tensors. Our work, therefore, provides new insights into the hole spin-orbit interaction, necessary for optimizing future qubit experiments.}, author = {Jirovec, Daniel and Mutter, Philipp M. and Hofmann, Andrea C and Crippa, Alessandro and Rychetsky, Marek and Craig, David L. and Kukucka, Josip and Martins, Frederico and Ballabio, Andrea and Ares, Natalia and Chrastina, Daniel and Isella, Giovanni and Burkard, Guido and Katsaros, Georgios}, issn = {1079-7114}, journal = {Physical Review Letters}, number = {12}, publisher = {American Physical Society}, title = {{Dynamics of hole singlet-triplet qubits with large g-factor differences}}, doi = {10.1103/PhysRevLett.128.126803}, volume = {128}, year = {2022}, } @article{10925, abstract = {Direct numerical simulations (DNS) of turbulent channel flows up to Reτ≈1000 are conducted to investigate the three-dimensional (consisting of streamwise wavenumber, spanwise wavenumber and frequency) spectrum of wall pressure fluctuations. To develop a predictive model of the wavenumber–frequency spectrum from the wavenumber spectrum, the time decorrelation mechanisms of wall pressure fluctuations are investigated. It is discovered that the energy-containing part of the wavenumber–frequency spectrum of wall pressure fluctuations can be well predicted using a similar random sweeping model for streamwise velocity fluctuations. To refine the investigation, we further decompose the spectrum of the total wall pressure fluctuations into the autospectra of rapid and slow pressure fluctuations, and the cross-spectrum between them. We focus on evaluating the assumption applied in many predictive models, that is, the magnitude of the cross-spectrum is negligibly small. The present DNS shows that neglecting the cross-spectrum causes a maximum error up to 4.7 dB in the subconvective region for all Reynolds numbers under test. Our analyses indicate that the approximation of neglecting the cross-spectrum needs to be applied carefully in the investigations of acoustics at low Mach numbers, in which the subconvective components of wall pressure fluctuations make important contributions to the radiated acoustic power.}, author = {Yang, Bowen and Yang, Zixuan}, issn = {1469-7645}, journal = {Journal of Fluid Mechanics}, publisher = {Cambridge University Press}, title = {{On the wavenumber-frequency spectrum of the wall pressure fluctuations in turbulent channel flow}}, doi = {10.1017/jfm.2022.137}, volume = {937}, year = {2022}, } @misc{10934, abstract = {FtsA is crucial for assembly of the E. coli divisome, as it dynamically links cytoplasmic FtsZ filaments with transmembrane cell division proteins. FtsA allegedly initiates cell division by switching from an inactive polymeric to an active monomeric confirmation, which recruits downstream proteins and stabilizes FtsZ filaments. Here, we use biochemical reconstitution experiments combined with quantitative fluorescence microscopy to study divisome activation in vitro. We compare wildtype-FtsA with FtsA-R286W, a constantly active gain-of-function mutant and find that R286W outperforms the wildtype protein in replicating FtsZ treadmilling dynamics, stabilizing FtsZ filaments and recruiting FtsN. We attribute these differences to a faster membrane exchange of FtsA-R286W and its higher packing density below FtsZ filaments. Using FRET microscopy, we find that FtsN binding does not compete with, but promotes FtsA self-interaction. Our findings suggest a model where FtsA always forms dynamic polymers on the membrane, which re-organize during assembly and activation of the divisome. }, author = {Radler, Philipp}, keywords = {Bacterial cell division, in vitro reconstitution, FtsZ, FtsN, FtsA}, publisher = {Institute of Science and Technology Austria}, title = {{In vitro reconstitution of Escherichia coli divisome activation}}, doi = {10.15479/AT:ISTA:10934}, year = {2022}, } @phdthesis{11128, abstract = {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.}, author = {Matejovicova, Lenka}, isbn = {978-3-99078-016-9}, issn = {2663-337X}, pages = {112}, publisher = {Institute of Science and Technology Austria}, title = {{Genetic basis of flower colour as a model for adaptive evolution}}, doi = {10.15479/at:ista:11128}, year = {2022}, } @article{11135, abstract = {We consider a correlated NxN Hermitian random matrix with a polynomially decaying metric correlation structure. By calculating the trace of the moments of the matrix and using the summable decay of the cumulants, we show that its operator norm is stochastically dominated by one.}, author = {Reker, Jana}, issn = {2010-3271}, journal = {Random Matrices: Theory and Applications}, keywords = {Discrete Mathematics and Combinatorics, Statistics, Probability and Uncertainty, Statistics and Probability, Algebra and Number Theory}, number = {4}, publisher = {World Scientific}, title = {{On the operator norm of a Hermitian random matrix with correlated entries}}, doi = {10.1142/s2010326322500368}, volume = {11}, year = {2022}, } @phdthesis{11193, abstract = {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.}, author = {Wachner, Stephanie}, issn = {2663-337X}, pages = {170}, publisher = {Institute of Science and Technology Austria}, title = {{Transcriptional regulation by Dfos and BMP-signaling support tissue invasion of Drosophila immune cells}}, doi = {10.15479/at:ista:11193}, year = {2022}, } @phdthesis{11196, abstract = {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. }, author = {Kim, Olena}, issn = {2663-337X}, pages = {132}, publisher = {Institute of Science and Technology Austria}, title = {{Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses}}, doi = {10.15479/at:ista:11196}, year = {2022}, } @misc{11321, abstract = {Here are the research data underlying the publication "Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus" Further information are summed up in the README document. }, author = {Surendranadh, Parvathy and Arathoon, Louise S and Baskett, Carina and Field, David and Pickup, Melinda and Barton, Nicholas H}, publisher = {Institute of Science and Technology Austria}, title = {{Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus}}, doi = {10.15479/at:ista:11321}, year = {2022}, } @phdthesis{11362, abstract = {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.}, author = {Lechner, Mathias}, isbn = {978-3-99078-017-6}, keywords = {neural networks, verification, machine learning}, pages = {124}, publisher = {Institute of Science and Technology Austria}, title = {{Learning verifiable representations}}, doi = {10.15479/at:ista:11362}, year = {2022}, } @phdthesis{11388, abstract = {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.}, author = {Belohlavy, Stefanie}, isbn = {978-3-99078-018-3}, pages = {98}, publisher = {Institute of Science and Technology Austria}, title = {{The genetic basis of complex traits studied via analysis of evolve and resequence experiments}}, doi = {10.15479/at:ista:11388}, year = {2022}, } @phdthesis{11393, abstract = {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.}, author = {Jevtic, Marijo}, issn = {2663-337X}, pages = {108}, publisher = {Institute of Science and Technology Austria}, title = {{Contextual fear learning induced changes in AMPA receptor subtypes along the proximodistal axis in dorsal hippocampus}}, doi = {10.15479/at:ista:11393}, year = {2022}, } @article{11403, author = {Stöllner, Andrea}, issn = {2662-138X}, journal = {Nature Reviews Earth and Environment}, number = {6}, pages = {360}, publisher = {Springer Nature}, title = {{Measuring airborne nanoplastics using aerosol physics}}, doi = {10.1038/s43017-022-00302-y}, volume = {3}, year = {2022}, } @article{11411, abstract = {Many studies have quantified the distribution of heterozygosity and relatedness in natural populations, but few have examined the demographic processes driving these patterns. In this study, we take a novel approach by studying how population structure affects both pairwise identity and the distribution of heterozygosity in a natural population of the self-incompatible plant Antirrhinum majus. Excess variance in heterozygosity between individuals is due to identity disequilibrium, which reflects the variance in inbreeding between individuals; it is measured by the statistic g2. We calculated g2 together with FST and pairwise relatedness (Fij) using 91 SNPs in 22,353 individuals collected over 11 years. We find that pairwise Fij declines rapidly over short spatial scales, and the excess variance in heterozygosity between individuals reflects significant variation in inbreeding. Additionally, we detect an excess of individuals with around half the average heterozygosity, indicating either selfing or matings between close relatives. We use 2 types of simulation to ask whether variation in heterozygosity is consistent with fine-scale spatial population structure. First, by simulating offspring using parents drawn from a range of spatial scales, we show that the known pollen dispersal kernel explains g2. Second, we simulate a 1,000-generation pedigree using the known dispersal and spatial distribution and find that the resulting g2 is consistent with that observed from the field data. In contrast, a simulated population with uniform density underestimates g2, indicating that heterogeneous density promotes identity disequilibrium. Our study shows that heterogeneous density and leptokurtic dispersal can together explain the distribution of heterozygosity.}, author = {Surendranadh, Parvathy and Arathoon, Louise S and Baskett, Carina and Field, David and Pickup, Melinda and Barton, Nicholas H}, issn = {1943-2631}, journal = {Genetics}, number = {3}, publisher = {Oxford University Press}, title = {{Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus}}, doi = {10.1093/genetics/iyac083}, volume = {221}, year = {2022}, } @article{11438, abstract = {Lasers with well-controlled relative frequencies are indispensable for many applications in science and technology. We present a frequency-offset locking method for lasers based on beat-frequency discrimination utilizing hybrid electronic LC filters. The method is specifically designed for decoupling the tightness of the lock from the broadness of its capture range. The presented demonstration locks two free-running diode lasers at 780 nm with a 5.5-GHz offset. It displays an offset frequency instability below 55 Hz for time scales in excess of 1000 s and a minimum of 12 Hz at 10-s averaging. The performance is complemented with a 190-MHz lock-capture range, a tuning range of up to 1 GHz, and a frequency ramp agility of 200kHz/μs.}, author = {Li, Vyacheslav and Diorico, Fritz R and Hosten, Onur}, issn = {2331-7019}, journal = {Physical Review Applied}, keywords = {General Physics and Astronomy}, number = {5}, publisher = {American Physical Society}, title = {{Laser frequency-offset locking at 10-Hz-level instability using hybrid electronic filters}}, doi = {10.1103/physrevapplied.17.054031}, volume = {17}, year = {2022}, }