@article{17481,
  abstract     = {Phase-field models such as the Allen–Cahn equation may give rise to the formation and evolution of geometric shapes, a phenomenon that may be analyzed rigorously in suitable scaling regimes. In its sharp-interface limit, the vectorial Allen–Cahn equation with a potential with N≥3 distinct minima has been conjectured to describe the evolution of branched interfaces by multiphase mean curvature flow. In the present work, we give a rigorous proof for this statement in two and three ambient dimensions and for a suitable class of potentials: as long as a strong solution to multiphase mean curvature flow exists, solutions to the vectorial Allen–Cahn equation with well-prepared initial data converge towards multiphase mean curvature flow in the limit of vanishing interface width parameter ε↘0. We even establish the rate of convergence O(ε 
1/2
 ). Our approach is based on the gradient-flow structure of the Allen–Cahn equation and its limiting motion: building on the recent concept of “gradient-flow calibrations” for multiphase mean curvature flow, we introduce a notion of relative entropy for the vectorial Allen–Cahn equation with multi-well potential. This enables us to overcome the limitations of other approaches, e.g. avoiding the need for a stability analysis of the Allen–Cahn operator or additional convergence hypotheses for the energy at positive times.},
  author       = {Fischer, Julian L and Marveggio, Alice},
  issn         = {1873-1430},
  journal      = {Annales de l'Institut Henri Poincaré C},
  number       = {5},
  pages        = {1117--1178},
  publisher    = {EMS Press},
  title        = {{Quantitative convergence of the vectorial Allen–Cahn equation towards multiphase mean curvature flow}},
  doi          = {10.4171/AIHPC/109},
  volume       = {41},
  year         = {2024},
}

@article{15048,
  abstract     = {Embryogenesis results from the coordinated activities of different signaling pathways controlling cell fate specification and morphogenesis. In vertebrate gastrulation, both Nodal and BMP signaling play key roles in germ layer specification and morphogenesis, yet their interplay to coordinate embryo patterning with morphogenesis is still insufficiently understood. Here, we took a reductionist approach using zebrafish embryonic explants to study the coordination of Nodal and BMP signaling for embryo patterning and morphogenesis. We show that Nodal signaling triggers explant elongation by inducing mesendodermal progenitors but also suppressing BMP signaling activity at the site of mesendoderm induction. Consistent with this, ectopic BMP signaling in the mesendoderm blocks cell alignment and oriented mesendoderm intercalations, key processes during explant elongation. Translating these ex vivo observations to the intact embryo showed that, similar to explants, Nodal signaling suppresses the effect of BMP signaling on cell intercalations in the dorsal domain, thus allowing robust embryonic axis elongation. These findings suggest a dual function of Nodal signaling in embryonic axis elongation by both inducing mesendoderm and suppressing BMP effects in the dorsal portion of the mesendoderm.},
  author       = {Schauer, Alexandra and Pranjic-Ferscha, Kornelija and Hauschild, Robert and Heisenberg, Carl-Philipp J},
  issn         = {1477-9129},
  journal      = {Development},
  number       = {4},
  pages        = {1--18},
  publisher    = {Company of Biologists},
  title        = {{Robust axis elongation by Nodal-dependent restriction of BMP signaling}},
  doi          = {10.1242/dev.202316},
  volume       = {151},
  year         = {2024},
}

@article{17458,
  abstract     = {Changes in gene dosage can have tremendous evolutionary potential (e.g. whole-genome duplications), but without compensatory mechanisms, they can also lead to gene dysregulation and pathologies. Sex chromosomes are a paradigmatic example of naturally occurring gene dosage differences and their compensation. In species with chromosome-based sex determination, individuals within the same population necessarily show ‘natural’ differences in gene dosage for the sex chromosomes. In this Review, we focus on the mammalian X chromosome and discuss recent new insights into the dosage-compensation mechanisms that evolved along with the emergence of sex chromosomes, namely X-inactivation and X-upregulation. We also discuss the evolution of the genetic loci and molecular players involved, as well as the regulatory diversity and potentially different requirements for dosage compensation across mammalian species.},
  author       = {Cecalev, Daniela and Vicoso, Beatriz and Galupa, Rafael},
  issn         = {1477-9129},
  journal      = {Development},
  number       = {15},
  publisher    = {Company of Biologists},
  title        = {{Compensation of gene dosage on the mammalian X}},
  doi          = {10.1242/dev.202891},
  volume       = {151},
  year         = {2024},
}

@misc{14926,
  author       = {Hauschild, Robert},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Matlab script for analysis of clone dispersal}},
  doi          = {10.15479/AT:ISTA:14926},
  year         = {2024},
}

@misc{22234,
  abstract     = {Lists of nontrivial integral points on some (families of) cubic surfaces. (2024-07-18)},
  author       = {Browning, Timothy D and Sutherland, Andrew},
  publisher    = {Göttingen Research Online Data},
  title        = {{Data and code for: Integral points on cubic surfaces: heuristics and numerics}},
  doi          = {10.25625/4FLFH8},
  year         = {2024},
}

@article{17457,
  abstract     = {Autoantibodies against the protein leucine-rich glioma inactivated 1 (LGI1) cause the most
common subtype of autoimmune encephalitis with predominant involvement of the limbic
system, associated with seizures and memory deficits. LGI1 and its receptor ADAM22 are part
of a transsynaptic protein complex that includes several proteins involved in presynaptic
neurotransmitter release and postsynaptic glutamate sensing. Autoantibodies against LGI1
increase excitatory synaptic strength, but studies that genetically disrupt the LGI1-ADAM22
complex report a reduction in postsynaptic glutamate receptor-mediated responses. Thus, the
mechanisms underlying the increased synaptic strength induced by LGI1 autoantibodies remain elusive, and the contributions of presynaptic molecules to the LGI1-transsynaptic complex remain unclear. We therefore investigated the presynaptic mechanisms that mediate
autoantibody-induced synaptic strengthening.},
  author       = {Ritzau-Jost, Andreas and Gsell, Felix and Sell, Josefine and Sachs, Stefan and Montanaro-Punzengruber, Jacqueline-Claire and Kirmann, Toni and Maaß, Sebastian and Irani, Sarosh R. and Werner, Christian and Geis, Christian and Sauer, Markus and Shigemoto, Ryuichi and Hallermann, Stefan},
  issn         = {2332-7812},
  journal      = {Neurology, Neuroimmunology & Neuroinflammation},
  number       = {5},
  pages        = {e200284},
  publisher    = {Wolters Kluwer},
  title        = {{LGI1 autoantibodies enhance synaptic transmission by presynaptic Kv1 loss and increased action potential broadening}},
  doi          = {10.1212/NXI.0000000000200284},
  volume       = {11},
  year         = {2024},
}

@unpublished{19063,
  abstract     = {Instruction-tuned Large Language Models (LLMs) show impressive results in numerous practical applications, but they lack essential safety features that are common in other areas of computer science, particularly an explicit separation of instructions and data. This makes them vulnerable to manipulations such as indirect prompt injections and generally unsuitable for safety-critical tasks. Surprisingly, there is currently no established definition or benchmark to quantify this phenomenon. In this work, we close this gap by introducing a formal measure for instruction-data separation and an empirical variant that is calculable from a model's outputs. We also present a new dataset, SEP, that allows estimating the measure for real-world models. Our results on various LLMs show that the problem of instruction-data separation is real: all models fail to achieve high separation, and canonical mitigation techniques, such as prompt engineering and fine-tuning, either fail to substantially improve separation or reduce model utility. The source code and SEP dataset are openly accessible at https://github.com/egozverev/Shold-It-Be-Executed-Or-Processed.
},
  author       = {Zverev, Egor and Abdelnabi, Sahar and Tabesh, Soroush and Fritz, Mario and Lampert, Christoph},
  booktitle    = {arXiv},
  title        = {{Can LLMs separate instructions from data? And what do we even mean by that?}},
  doi          = {10.48550/arXiv.2403.06833},
  year         = {2024},
}

@article{15401,
  abstract     = {Amide-proton-detected magic-angle-spinning NMR of deuterated proteins has become a main technique in NMR-based structural biology. In standard deuteration protocols that rely on D2O-based culture media, non-exchangeable amide sites remain deuterated, making these sites unobservable. Here we demonstrate that proteins produced with a H2O-based culture medium doped with deuterated cell lysate allow scientists to overcome this “reprotonation bottleneck” while retaining a high level of deuteration (ca. 80 %) and narrow linewidths. We quantified coherence lifetimes of several proteins prepared with this labeling pattern over a range of magic-angle-spinning (MAS) frequencies (40–100 kHz). We demonstrate that under commonly used conditions (50–60 kHz MAS), the amide 1H linewidths with our labeling approach are comparable to those of perdeuterated proteins and better than those of protonated samples at 100 kHz. For three proteins in the 33–50 kDa size range, many previously unobserved amides become visible. We report how to prepare the deuterated cell lysate for our approach from fractions of perdeuterated cultures which are usually discarded, and we show that such media can be used identically to commercial media. The residual protonation of Hα sites allows for well-resolved Hα-detected spectra and Hα resonance assignment, exemplified by the de novo assignment of 168 Hα sites in a 39 kDa protein. The approach based on this H2O/cell-lysate deuteration and MAS frequencies compatible with 1.3 or 1.9 mm rotors presents a strong sensitivity benefit over 0.7 mm 100 kHz MAS experiments.},
  author       = {Napoli, Federico and Guan, Jia-Ying and Arnaud, Charles-Adrien and Macek, Pavel and Fraga, Hugo and Breyton, Cécile and Schanda, Paul},
  issn         = {2699-0016},
  journal      = {Magnetic Resonance},
  number       = {1},
  pages        = {33--49},
  publisher    = {Copernicus Publications},
  title        = {{Deuteration of proteins boosted by cell lysates: High-resolution amide and Ha magic-angle-spinning (MAS) NMR without the reprotonation bottleneck}},
  doi          = {10.5194/mr-5-33-2024},
  volume       = {5},
  year         = {2024},
}

@phdthesis{15094,
  abstract     = {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.

},
  author       = {Cultrera di Montesano, Sebastiano},
  issn         = {2663-337X},
  pages        = {108},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Persistence and Morse theory for discrete geometric structures}},
  doi          = {10.15479/at:ista:15094},
  year         = {2024},
}

@article{13182,
  abstract     = {We characterize critical points of 1-dimensional maps paired in persistent homology
geometrically and this way get elementary proofs of theorems about the symmetry
of persistence diagrams and the variation of such maps. In particular, we identify
branching points and endpoints of networks as the sole source of asymmetry and
relate the cycle basis in persistent homology with a version of the stable marriage
problem. Our analysis provides the foundations of fast algorithms for maintaining a
collection of sorted lists together with its persistence diagram.},
  author       = {Biswas, Ranita and Cultrera Di Montesano, Sebastiano and Edelsbrunner, Herbert and Saghafian, Morteza},
  issn         = {2367-1734},
  journal      = {Journal of Applied and Computational Topology},
  pages        = {1101--1119},
  publisher    = {Springer Nature},
  title        = {{Geometric characterization of the persistence of 1D maps}},
  doi          = {10.1007/s41468-023-00126-9},
  volume       = {8},
  year         = {2024},
}

@article{14826,
  abstract     = {The plant-signaling molecule auxin triggers fast and slow cellular responses across land plants and algae. The nuclear auxin pathway mediates gene expression and controls growth and development in land plants, but this pathway is absent from algal sister groups. Several components of rapid responses have been identified in Arabidopsis, but it is unknown if these are part of a conserved mechanism. We recently identified a fast, proteome-wide phosphorylation response to auxin. Here, we show that this response occurs across 5 land plant and algal species and converges on a core group of shared targets. We found conserved rapid physiological responses to auxin in the same species and identified rapidly accelerated fibrosarcoma (RAF)-like protein kinases as central mediators of auxin-triggered phosphorylation across species. Genetic analysis connects this kinase to both auxin-triggered protein phosphorylation and rapid cellular response, thus identifying an ancient mechanism for fast auxin responses in the green lineage.},
  author       = {Kuhn, Andre and Roosjen, Mark and Mutte, Sumanth and Dubey, Shiv Mani and Carrillo Carrasco, Vanessa Polet and Boeren, Sjef and Monzer, Aline and Koehorst, Jasper and Kohchi, Takayuki and Nishihama, Ryuichi and Fendrych, Matyas and Sprakel, Joris and Friml, Jiří and Weijers, Dolf},
  issn         = {1097-4172},
  journal      = {Cell},
  keywords     = {General Biochemistry, Genetics and Molecular Biology},
  number       = {1},
  pages        = {130--148.e17},
  publisher    = {Elsevier},
  title        = {{RAF-like protein kinases mediate a deeply conserved, rapid auxin response}},
  doi          = {10.1016/j.cell.2023.11.021},
  volume       = {187},
  year         = {2024},
}

@inproceedings{18702,
  abstract     = {In this work we prove lower bounds on the (communication) cost of maintaining a shared key among a dynamic group of users. Being “dynamic” means one can add and remove users from the group. This captures important protocols like multicast encryption (ME) and continuous group-key agreement (CGKA), which is the primitive underlying many group messaging applications. We prove our bounds in a combinatorial setting where the state of the protocol progresses in rounds. The state of the protocol in each round is captured by a set system, with each of its elements specifying a set of users who share a secret key. We show this combinatorial model implies bounds in symbolic models for ME and CGKA that capture, as building blocks, PRGs, PRFs, dual PRFs, secret sharing, and symmetric encryption in the setting of ME, and PRGs, PRFs, dual PRFs, secret sharing, public-key encryption, and key-updatable public-key encryption in the setting of CGKA. The models are related to the ones used by Micciancio and Panjwani (Eurocrypt’04) and Bienstock et al. (TCC’20) to analyze ME and CGKA, respectively. We prove – using the Bollobás’ Set Pairs Inequality – that the cost (number of uploaded ciphertexts) for replacing a set of d users in a group of size n is Ω(dln(n/d)). Our lower bound is asymptotically tight and both improves on a bound of Ω(d) by Bienstock et al. (TCC’20), and generalizes a result by Micciancio and Panjwani (Eurocrypt’04), who proved a lower bound of Ω(log(n)) for d=1. },
  author       = {Anastos, Michael and Auerbach, Benedikt and Baig, Mirza Ahad and Cueto Noval, Miguel and Kwan, Matthew Alan and Pascual Perez, Guillermo and Pietrzak, Krzysztof Z},
  booktitle    = {22nd International Conference on Theory of Cryptography},
  isbn         = {9783031780103},
  issn         = {1611-3349},
  location     = {Milan, Italy},
  pages        = {413--443},
  publisher    = {Springer Nature},
  title        = {{The cost of maintaining keys in dynamic groups with applications to multicast encryption and group messaging}},
  doi          = {10.1007/978-3-031-78011-0_14},
  volume       = {15364},
  year         = {2024},
}

@article{17373,
  abstract     = {Scanning Kelvin probe microscopy (SKPM) is a powerful technique for investigating the electrostatic properties of material surfaces, enabling the imaging of variations in work function, topology, surface charge density, or combinations thereof. Regardless of the underlying signal source, SKPM results in a voltage image, which is spatially distorted due to the finite size of the probe, long-range electrostatic interactions, mechanical and electrical noise, and the finite response time of the electronics. In order to recover the underlying signal, it is necessary to deconvolve the measurement with an appropriate point spread function (PSF) that accounts the aforementioned distortions, but determining this PSF is difficult. Here, we describe how such PSFs can be determined experimentally and show how they can be used to recover the underlying information of interest. We first consider the physical principles that enable SKPM and discuss how these affect the system PSF. We then show how one can experimentally measure PSFs by looking at well-defined features, and that these compare well to simulated PSFs, provided scans are performed extremely slowly and carefully. Next, we work at realistic scan speeds and show that the idealized PSFs fail to capture temporal distortions in the scan direction. While simulating PSFs for these situations would be quite challenging, we show that measuring PSFs with similar scan conditions works well. Our approach clarifies the basic principles and inherent challenges to SKPM measurements and gives practical methods to improve results.},
  author       = {Lenton, Isaac C and Pertl, Felix and Shafeek, Lubuna B and Waitukaitis, Scott R},
  issn         = {1089-7550},
  journal      = {Journal of Applied Physics},
  number       = {4},
  publisher    = {AIP Publishing},
  title        = {{Beyond the blur: Using experimentally determined point spread functions to improve scanning Kelvin probe imaging}},
  doi          = {10.1063/5.0215151},
  volume       = {136},
  year         = {2024},
}

@inbook{17425,
  abstract     = {Mosaic Analysis with Double Markers (MADM) is a powerful genetic method typically used for lineage tracing and to disentangle cell autonomous and tissue-wide roles of candidate genes with single cell resolution. Given the relatively sparse labeling, depending on which of the 19 MADM chromosomes one chooses, the MADM approach represents the perfect opportunity for cell morphology analysis. Various MADM studies include reports of morphological anomalies and phenotypes in the central nervous system (CNS). MADM for any candidate gene can easily incorporate morphological analysis within the experimental workflow. Here, we describe the methods of morphological cell analysis which we developed in the course of diverse recent MADM studies. This chapter will specifically focus on methods to quantify aspects of the morphology of neurons and astrocytes within the CNS, but these methods can broadly be applied to any MADM-labeled cells throughout the entire organism. We will cover two analyses—soma volume and dendrite characterization—of physical characteristics of pyramidal neurons in the somatosensory cortex, and two analyses—volume and Sholl analysis—of astrocyte morphology.},
  author       = {Miranda, Osvaldo and Cheung, Giselle T and Hippenmeyer, Simon},
  booktitle    = {Neuronal Morphogenesis},
  editor       = {Toyooka, Kazuhito},
  isbn         = {9781071639689},
  issn         = {1940-6029},
  pages        = {283--299},
  publisher    = {Springer Nature},
  title        = {{Morphological Analysis of Neurons and Glia Using Mosaic Analysis with Double Markers}},
  doi          = {10.1007/978-1-0716-3969-6_19},
  volume       = {2831},
  year         = {2024},
}

@phdthesis{17465,
  abstract     = {In the modern age of machine learning, artificial neural networks have become an integral part
of many practical systems. One of the key ingredients of the success of the deep learning
approach is recent computational advances which allowed the training of models with billions
of parameters on large-scale data. Such over-parameterized and data-hungry regimes pose a
challenge for the theoretical analysis of modern models since “classical” statistical wisdom
is no longer applicable. In this view, it is paramount to extend or develop new machinery
that will allow tackling the neural network analysis under new challenging asymptotic regimes,
which is the focus of this thesis.
Large neural network systems are usually optimized via “local” search algorithms, such
as stochastic gradient descent (SGD). However, given the high-dimensional nature of the
parameter space, it is a priori not clear why such a crude “local” approach works so remarkably
well in practice. We take a step towards demystifying this phenomenon by showing that
the landscape of the SGD training dynamics exhibits a few beneficial properties for the
optimization. First, we show that along the SGD trajectory an over-parameterized network
is dropout stable. The emergence of dropout stability allows to conclude that the minima
found by SGD are connected via a continuous path of small loss. This in turn means that
the high-dimensional landscape of the neural network optimization problem is provably not so
unfavourable to gradient-based training, due to mode connectivity. Next, we show that SGD
for an over-parameterized network tends to find solutions that are functionally more “simple”.
This in turn means that the SGD minima are more robust, since a less complicated solution
will less likely overfit the data. More formally, for a prototypical example of a wide two-layer
ReLU network on a 1d regression task we show that the SGD algorithm is implicitly selective in
its choice of an interpolating solution. Namely, at convergence the neural network implements
a piece-wise linear function with the number of linear regions depending only on the amount
of training data. This is in contrast to a “smooth”-like behaviour which one would expect
given such a severe over-parameterization of the model.
Diverging from the generic supervised setting of classification and regression problems, we
analyze an auto-encoder model that is commonly used for representation learning and data
compression. Despite the wide applicability of the auto-encoding paradigm, the theoretical
understanding of their behaviour is limited even in the simplistic shallow case. The related
work is restricted to extreme asymptotic regimes in which the auto-encoder is either severely
over-parameterized or under-parameterized. In contrast, we provide a tight characterization
for the 1-bit compression of Gaussian signals in the challenging proportional regime, i.e., the
input dimension and the size of the compressed representation obey the same asymptotics.
We also show that gradient-based methods are able to find a globally optimal solution and
that the predictions made for Gaussian data extrapolate beyond - to the case of compression
of natural images. Next, we relax the Gaussian assumption and study more structured input
sources. We show that the shallow model is sometimes agnostic to the structure of the data
vii
which results in a Gaussian-like behaviour. We prove that making the decoding component
slightly less shallow is already enough to escape the “curse” of Gaussian performance.
},
  author       = {Shevchenko, Aleksandr},
  issn         = {2663-337X},
  pages        = {232},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{High-dimensional limits in artificial neural networks}},
  doi          = {10.15479/at:ista:17465},
  year         = {2024},
}

@inproceedings{17469,
  abstract     = {Autoencoders are a prominent model in many empirical branches of machine learning and lossy data compression. However, basic theoretical questions remain unanswered even in a shallow two-layer setting. In particular, to what degree does a shallow autoencoder capture the structure of the underlying data distribution? For the prototypical case of the 1-bit compression of sparse Gaussian data, we prove that gradient descent converges to a solution that completely disregards the sparse structure of the input. Namely, the performance of the algorithm is the same as if it was compressing a Gaussian source - with no sparsity. For general data distributions, we give evidence of a phase transition phenomenon in the shape of the gradient descent minimizer, as a function of the data sparsity: below the critical sparsity level, the minimizer is a rotation taken uniformly at random (just like in the compression of non-sparse data); above the critical sparsity, the minimizer is the identity (up to a permutation). Finally, by exploiting a connection with approximate message passing algorithms, we show how to improve upon Gaussian performance for the compression of sparse data: adding a denoising function to a shallow architecture already reduces the loss provably, and a suitable multi-layer decoder leads to a further improvement. We validate our findings on image datasets, such as CIFAR-10 and MNIST.},
  author       = {Kögler, Kevin and Shevchenko, Aleksandr and Hassani, Hamed and Mondelli, Marco},
  booktitle    = {Proceedings of the 41st International Conference on Machine Learning},
  location     = {Vienna, Austria},
  pages        = {24964--25015},
  publisher    = {ML Research Press},
  title        = {{Compression of structured data with autoencoders: Provable benefit of nonlinearities and depth}},
  volume       = {235},
  year         = {2024},
}

@phdthesis{17881,
  abstract     = {This work can be broadly classified into the study of critical phenomena in a one dimensional
array of Josephson junctions. While we study quantum criticality when the array is in thermal
equilibrium at zero bias, the non-equilibrium study involves understanding the bistability of the
array at a critical non-zero bias. This work furthers our knowledge in understanding quantum
critical behaviour at finite temperatures in a one dimensional Josephson array, while also
establishing relaxation behaviour dual to that observed in a single Josephson junction.
Chapter 1 briefly introduces the model to understand superconductor-insulator phase transition
in a one dimensional Josephson array and points out the state of the field from where we
started our zero-bias experiments. In this context it discusses the phase-charge duality observed
in a Josephson array and its dual hysteretic behaviour to that of a single junction, setting the
ground for our non-equilibrium study of the array.
Chapter 2 shows the experimental setup and the chip layout of the device we measured.
In chapter 3 we show that, unlike the typical quantum-critical broadening scenario, in one dimensional Josephson arrays temperature dramatically shifts the critical region. This shift leads
to a regime of superconductivity at high temperature, arising from the melted zero-temperature
insulator. Our results quantitatively explain the low-temperature onset of superconductivity in
nominally insulating regimes, and the transition to the strongly insulating phase. We further
present, to our knowledge, the first understanding of the onset of anomalous-metallic resistance
saturation [30]. This work demonstrates a non-trivial interplay between thermal effects and
quantum criticality. A practical consequence is that, counterintuitively, the coherence of
high-impedance quantum circuits is expected to be stabilized by thermal fluctuations.
In chapter 4, we show relaxation oscillations in a current-biased one dimensional array of
Josephson junctions. These oscillations are well described by a circuit model, dual to the
ordinary Josephson relaxation oscillations [72]. Injection locking these oscillations results in
current plateaux. The relaxation step is found to obey a characteristic self-consistent relation,
suggesting that it is governed by overheating effects.
Chapter 5 describes the various checks and analysis we performed to support our conclusions
made in chapters 3 and 4.
Finally, chapter 6 describes the nanofabrication steps and the finite element electromagnetic
simulations we performed to fabricate our devices.},
  author       = {Mukhopadhyay, Soham},
  isbn         = {978-3-99078-043-5},
  issn         = {2663-337X},
  pages        = {82},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Thermal effects in one dimensional Josephson chains}},
  doi          = {10.15479/at:ista:17881},
  year         = {2024},
}

@unpublished{18057,
  abstract     = {We report relaxation oscillations in a one-dimensional array of Josephson
junctions. The oscillations are circuit-dual to those ordinarily observed in
single junctions. The dual circuit quantitatively accounts for temporal
dynamics of the array, including the dependence on biasing conditions.
Injection locking the oscillations results in well-developed current plateaux.
A thermal model explains the relaxation step of the oscillations.},
  author       = {Mukhopadhyay, Soham and Lancheros Naranjo, Diego A and Senior, Jorden L and Higginbotham, Andrew P},
  booktitle    = {arXiv},
  title        = {{Dual relaxation oscillations in a Josephson junction array}},
  doi          = {10.48550/arXiv.2408.07829},
  year         = {2024},
}

@article{17890,
  abstract     = {Our understanding of the molecular pathways that regulate oogenesis and define cellular identity in the Arthropod female reproductive system and the extent of their conservation is currently very limited. This is due to the focus on model systems, including Drosophila and Daphnia, which do not reflect the observed diversity of morphologies, reproductive modes, and sex chromosome systems. We use single-nucleus RNA and ATAC sequencing to produce a comprehensive single nucleus atlas of the adult Artemia franciscana female reproductive system. We map our data to the Fly Cell Atlas single-nucleus dataset of the Drosophila melanogaster ovary, shedding light on the conserved regulatory programs between the two distantly related Arthropod species. We identify the major cell types known to be present in the Artemia ovary, including germ cells, follicle cells, and ovarian muscle cells. Additionally, we use the germ cells to explore gene regulation and expression of the Z chromosome during meiosis, highlighting its unique regulatory dynamics and allowing us to explore the presence of meiotic sex chromosome silencing in this group.},
  author       = {Elkrewi, Marwan N and Vicoso, Beatriz},
  issn         = {1553-7404},
  journal      = {PLoS Genetics},
  number       = {8},
  publisher    = {Public Library of Science},
  title        = {{Single-nucleus atlas of the Artemia female reproductive system suggests germline repression of the Z chromosome}},
  doi          = {10.1371/journal.pgen.1011376},
  volume       = {20},
  year         = {2024},
}

@phdthesis{17119,
  abstract     = {Genomes are shaped by natural selection at the level of the organism, as genomic variants that
have a beneficial effect on the viability or fecundity of their carriers are on average expected
to be passed on to more offspring than less beneficial alleles. However, selection also favors
genomic variants that drive their own transmission to the next generation above the mendelian
expectation of 50 percent in heterozygotes, even if these self-promoting variants are less
beneficial to the organism than other variants at the same locus. Such variants, called meiotic
drivers, are found in diverse taxa, and often impose fitness costs on their host organisms. As
meiotic drivers often require multiple genes and sequences for transmission ratio distortion,
they are often found in regions of low recombination, such as inversions, which prevent their
recombination with the non-driving homologous regions. Reduced recombination rates are
expected to lead to the accumulation of deleterious mutations, which may affect hundreds
of genes trapped in the inversions of meiotic drivers. Although the observed fitness costs of
self-promoting haplotypes are thought to possibly reflect sequence degeneration, no study has
systematically investigated the level of degeneration on a meiotic driver. Further, the low
rates of recombination between driving and non-driving haplotypes have limited the power of
traditional genetic studies in uncovering the gene content of meiotic drivers, and made the
the identification of the genes causing transmission ratio distortion difficult.
After an introduction to meiotic drivers in Chapter 1, this thesis presents three studies that
make use of next generation sequencing data to characterize the sequence and expression
evolution of genes on the t-haplotype, a large and ancient meiotic driver in house mice that is
transmitted to up to 100% of the offspring in males heterozygous for it. Chapter 2 presents
a comprehensive assessment of the t-haplotype’s sequence evolution, which shows signs of
sequence degeneration counteracted by occasional recombination with the non-driving homolog
over large parts of the meiotic driver, proposing an explanation for its long-term survival.
Chapter 3 investigates the sequence and expression evolution of genes on the t-haplotype,
and finds widespread expression and copy number changes and signs of less efficient purifying
selection compared to the genes on the non-driving homolog. Further, this chapter finds
candidates for involvment in drive: two positively selected genes on the t-haplotype, and
the discovery of a t-specific gene duplicate, which was gained from another chromosome,
and which acquired novel sequence and testis-specific expression on the t-haplotype. Finally,
Chapter 4 provides unprecedented insights into the gene expression landscape in testes of
t-carrier mice, using single nucleus sequencing. Cell-resolved RNA-sequencing allows the
comparison of expression in spermatids carrying or not carrying the t-haplotype as well as the
timing of t-haplotype-induced expression changes along spermatogenesis. This study shows
the timing of previously found drive-associated genes, and uncovers novel candidate genes and
biological processes that may underlie the complex biology of transmission ratio distortion of
the t-haplotype. Chapter 5 synthesizes the findings of the three studies, and discusses them in
the context of the current state of meiotic drive research.},
  author       = {Kelemen, Réka K},
  isbn         = {978-3-99078-039-8},
  issn         = {2663-337X},
  keywords     = {meiotic driver, neofunctionalization, single nucleus sequencing},
  pages        = {105},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Characterizing the sequence and expression evolution of the t-haplotype, a model meiotic driver}},
  doi          = {10.15479/at:ista:17119},
  year         = {2024},
}