@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},
}

@inproceedings{11839,
  abstract     = {It is a highly desirable property for deep networks to be robust against
small input changes. One popular way to achieve this property is by designing
networks with a small Lipschitz constant. In this work, we propose a new
technique for constructing such Lipschitz networks that has a number of
desirable properties: it can be applied to any linear network layer
(fully-connected or convolutional), it provides formal guarantees on the
Lipschitz constant, it is easy to implement and efficient to run, and it can be
combined with any training objective and optimization method. In fact, our
technique is the first one in the literature that achieves all of these
properties simultaneously. Our main contribution is a rescaling-based weight
matrix parametrization that guarantees each network layer to have a Lipschitz
constant of at most 1 and results in the learned weight matrices to be close to
orthogonal. Hence we call such layers almost-orthogonal Lipschitz (AOL).
Experiments and ablation studies in the context of image classification with
certified robust accuracy confirm that AOL layers achieve results that are on
par with most existing methods. Yet, they are simpler to implement and more
broadly applicable, because they do not require computationally expensive
matrix orthogonalization or inversion steps as part of the network
architecture. We provide code at https://github.com/berndprach/AOL.},
  author       = {Prach, Bernd and Lampert, Christoph},
  booktitle    = {Computer Vision – ECCV 2022},
  isbn         = {9783031198021},
  location     = {Tel Aviv, Israel},
  pages        = {350--365},
  publisher    = {Springer Nature},
  title        = {{Almost-orthogonal layers for efficient general-purpose Lipschitz networks}},
  doi          = {10.1007/978-3-031-19803-8_21},
  volume       = {13681},
  year         = {2022},
}

@inproceedings{11775,
  abstract     = {Quantitative monitoring can be universal and approximate: For every finite sequence of observations, the specification provides a value and the monitor outputs a best-effort approximation of it. The quality of the approximation may depend on the resources that are available to the monitor. By taking to the limit the sequences of specification values and monitor outputs, we obtain precision-resource trade-offs also for limit monitoring. This paper provides a formal framework for studying such trade-offs using an abstract interpretation for monitors: For each natural number n, the aggregate semantics of a monitor at time n is an equivalence relation over all sequences of at most n observations so that two equivalent sequences are indistinguishable to the monitor and thus mapped to the same output. This abstract interpretation of quantitative monitors allows us to measure the number of equivalence classes (or “resource use”) that is necessary for a certain precision up to a certain time, or at any time. Our framework offers several insights. For example, we identify a family of specifications for which any resource-optimal exact limit monitor is independent of any error permitted over finite traces. Moreover, we present a specification for which any resource-optimal approximate limit monitor does not minimize its resource use at any time. },
  author       = {Henzinger, Thomas A and Mazzocchi, Nicolas Adrien and Sarac, Naci E},
  booktitle    = {22nd International Conference on Runtime Verification},
  issn         = {0302-9743},
  location     = {Tbilisi, Georgia},
  pages        = {200--220},
  publisher    = {Springer Nature},
  title        = {{Abstract monitors for quantitative specifications}},
  doi          = {10.1007/978-3-031-17196-3_11},
  volume       = {13498},
  year         = {2022},
}

@article{10642,
  abstract     = {Based on a result by Yarotsky (J Stat Phys 118, 2005), we prove that localized but otherwise arbitrary perturbations of weakly interacting quantum spin systems with uniformly gapped on-site terms change the ground state of such a system only locally, even if they close the spectral gap. We call this a strong version of the local perturbations perturb locally (LPPL) principle which is known to hold for much more general gapped systems, but only for perturbations that do not close the spectral gap of the Hamiltonian. We also extend this strong LPPL-principle to Hamiltonians that have the appropriate structure of gapped on-site terms and weak interactions only locally in some region of space. While our results are technically corollaries to a theorem of Yarotsky, we expect that the paradigm of systems with a locally gapped ground state that is completely insensitive to the form of the Hamiltonian elsewhere extends to other situations and has important physical consequences.},
  author       = {Henheik, Sven Joscha and Teufel, Stefan and Wessel, Tom},
  issn         = {1573-0530},
  journal      = {Letters in Mathematical Physics},
  keywords     = {mathematical physics, statistical and nonlinear physics},
  number       = {1},
  publisher    = {Springer Nature},
  title        = {{Local stability of ground states in locally gapped and weakly interacting quantum spin systems}},
  doi          = {10.1007/s11005-021-01494-y},
  volume       = {112},
  year         = {2022},
}

@article{10623,
  abstract     = {We investigate the BCS critical temperature Tc in the high-density limit and derive an asymptotic formula, which strongly depends on the behavior of the interaction potential V on the Fermi-surface. Our results include a rigorous confirmation for the behavior of Tc at high densities proposed by Langmann et al. (Phys Rev Lett 122:157001, 2019) and identify precise conditions under which superconducting domes arise in BCS theory.},
  author       = {Henheik, Sven Joscha},
  issn         = {1572-9656},
  journal      = {Mathematical Physics, Analysis and Geometry},
  keywords     = {geometry and topology, mathematical physics},
  number       = {1},
  publisher    = {Springer Nature},
  title        = {{The BCS critical temperature at high density}},
  doi          = {10.1007/s11040-021-09415-0},
  volume       = {25},
  year         = {2022},
}

@phdthesis{12072,
  abstract     = {In this thesis, we study two of the most important questions in Arithmetic geometry: that of the existence and density of solutions to Diophantine equations. In order for a Diophantine equation to have any solutions over the rational numbers, it must have solutions everywhere locally, i.e., over R and over Qp for every prime p. The converse, called the Hasse principle, is known to fail in general. However, it is still a central question in Arithmetic geometry to determine for which varieties the Hasse principle does hold. In this work, we establish the Hasse principle for a wide new family of varieties of the form f(t) = NK/Q(x) ̸= 0, where f is a polynomial with integer coefficients and NK/Q denotes the norm
form associated to a number field K. Our results cover products of arbitrarily many linear, quadratic or cubic factors, and generalise an argument of Irving [69], which makes use of the beta sieve of Rosser and Iwaniec. We also demonstrate how our main sieve results can be applied to treat new cases of a conjecture of Harpaz and Wittenberg on locally split values of polynomials over number fields, and discuss consequences for rational points in fibrations.
In the second question, about the density of solutions, one defines a height function and seeks to estimate asymptotically the number of points of height bounded by B as B → ∞. Traditionally, one either counts rational points, or
integral points with respect to a suitable model. However, in this thesis, we study an emerging area of interest in Arithmetic geometry known as Campana points, which in some sense interpolate between rational and integral points.
More precisely, we count the number of nonzero integers z1, z2, z3 such that gcd(z1, z2, z3) = 1, and z1, z2, z3, z1 + z2 + z3 are all squareful and bounded by B. Using the circle method, we obtain an asymptotic formula which agrees in
the power of B and log B with a bold new generalisation of Manin’s conjecture to the setting of Campana points, recently formulated by Pieropan, Smeets, Tanimoto and Várilly-Alvarado [96]. However, in this thesis we also provide the first known counterexamples to leading constant predicted by their conjecture. },
  author       = {Shute, Alec L},
  isbn         = {978-3-99078-023-7},
  issn         = {2663-337X},
  pages        = {208},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Existence and density problems in Diophantine geometry: From norm forms to Campana points}},
  doi          = {10.15479/at:ista:12072},
  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},
}

@inproceedings{11476,
  abstract     = {Messaging platforms like Signal are widely deployed and provide strong security in an asynchronous setting. It is a challenging problem to construct a protocol with similar security guarantees that can efficiently scale to large groups. A major bottleneck are the frequent key rotations users need to perform to achieve post compromise forward security.

In current proposals – most notably in TreeKEM (which is part of the IETF’s Messaging Layer Security (MLS) protocol draft) – for users in a group of size n to rotate their keys, they must each craft a message of size log(n) to be broadcast to the group using an (untrusted) delivery server.

In larger groups, having users sequentially rotate their keys requires too much bandwidth (or takes too long), so variants allowing any T≤n users to simultaneously rotate their keys in just 2 communication rounds have been suggested (e.g. “Propose and Commit” by MLS). Unfortunately, 2-round concurrent updates are either damaging or expensive (or both); i.e. they either result in future operations being more costly (e.g. via “blanking” or “tainting”) or are costly themselves requiring Ω(T) communication for each user [Bienstock et al., TCC’20].

In this paper we propose CoCoA; a new scheme that allows for T concurrent updates that are neither damaging nor costly. That is, they add no cost to future operations yet they only require Ω(log2(n)) communication per user. To circumvent the [Bienstock et al.] lower bound, CoCoA increases the number of rounds needed to complete all updates from 2 up to (at most) log(n); though typically fewer rounds are needed.

The key insight of our protocol is the following: in the (non-concurrent version of) TreeKEM, a delivery server which gets T concurrent update requests will approve one and reject the remaining T−1. In contrast, our server attempts to apply all of them. If more than one user requests to rotate the same key during a round, the server arbitrarily picks a winner. Surprisingly, we prove that regardless of how the server chooses the winners, all previously compromised users will recover after at most log(n) such update rounds.

To keep the communication complexity low, CoCoA is a server-aided CGKA. That is, the delivery server no longer blindly forwards packets, but instead actively computes individualized packets tailored to each user. As the server is untrusted, this change requires us to develop new mechanisms ensuring robustness of the protocol.},
  author       = {Alwen, Joël and Auerbach, Benedikt and Cueto Noval, Miguel and Klein, Karen and Pascual Perez, Guillermo and Pietrzak, Krzysztof Z and Walter, Michael},
  booktitle    = {Advances in Cryptology – EUROCRYPT 2022},
  isbn         = {9783031070846},
  issn         = {1611-3349},
  location     = {Trondheim, Norway},
  pages        = {815–844},
  publisher    = {Springer Nature},
  title        = {{CoCoA: Concurrent continuous group key agreement}},
  doi          = {10.1007/978-3-031-07085-3_28},
  volume       = {13276},
  year         = {2022},
}

@article{9311,
  abstract     = {Partially observable Markov decision processes (POMDPs) are standard models for dynamic systems with probabilistic and nondeterministic behaviour in uncertain environments. We prove that in POMDPs with long-run average objective, the decision maker has approximately optimal strategies with finite memory. This implies notably that approximating the long-run value is recursively enumerable, as well as a weak continuity property of the value with respect to the transition function. },
  author       = {Chatterjee, Krishnendu and Saona Urmeneta, Raimundo J and Ziliotto, Bruno},
  issn         = {1526-5471},
  journal      = {Mathematics of Operations Research},
  keywords     = {Management Science and Operations Research, General Mathematics, Computer Science Applications},
  number       = {1},
  pages        = {100--119},
  publisher    = {Institute for Operations Research and the Management Sciences},
  title        = {{Finite-memory strategies in POMDPs with long-run average objectives}},
  doi          = {10.1287/moor.2020.1116},
  volume       = {47},
  year         = {2022},
}

@article{11448,
  abstract     = {Studies of protein fitness landscapes reveal biophysical constraints guiding protein evolution and empower prediction of functional proteins. However, generalisation of these findings is limited due to scarceness of systematic data on fitness landscapes of proteins with a defined evolutionary relationship. We characterized the fitness peaks of four orthologous fluorescent proteins with a broad range of sequence divergence. While two of the four studied fitness peaks were sharp, the other two were considerably flatter, being almost entirely free of epistatic interactions. Mutationally robust proteins, characterized by a flat fitness peak, were not optimal templates for machine-learning-driven protein design – instead, predictions were more accurate for fragile proteins with epistatic landscapes. Our work paves insights for practical application of fitness landscape heterogeneity in protein engineering.},
  author       = {Gonzalez Somermeyer, Louisa and Fleiss, Aubin and Mishin, Alexander S and Bozhanova, Nina G and Igolkina, Anna A and Meiler, Jens and Alaball Pujol, Maria-Elisenda and Putintseva, Ekaterina V and Sarkisyan, Karen S and Kondrashov, Fyodor},
  issn         = {2050-084X},
  journal      = {eLife},
  keywords     = {General Immunology and Microbiology, General Biochemistry, Genetics and Molecular Biology, General Medicine, General Neuroscience},
  publisher    = {eLife Sciences Publications},
  title        = {{Heterogeneity of the GFP fitness landscape and data-driven protein design}},
  doi          = {10.7554/elife.75842},
  volume       = {11},
  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 Publishing},
  title        = {{On the operator norm of a Hermitian random matrix with correlated entries}},
  doi          = {10.1142/s2010326322500368},
  volume       = {11},
  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},
}

@article{11732,
  abstract     = {We study the BCS energy gap Ξ in the high–density limit and derive an asymptotic formula, which strongly depends on the strength of the interaction potential V on the Fermi surface. In combination with the recent result by one of us (Math. Phys. Anal. Geom. 25, 3, 2022) on the critical temperature Tc at high densities, we prove the universality of the ratio of the energy gap and the critical temperature.},
  author       = {Henheik, Sven Joscha and Lauritsen, Asbjørn Bækgaard},
  issn         = {1572-9613},
  journal      = {Journal of Statistical Physics},
  keywords     = {Mathematical Physics, Statistical and Nonlinear Physics},
  publisher    = {Springer Nature},
  title        = {{The BCS energy gap at high density}},
  doi          = {10.1007/s10955-022-02965-9},
  volume       = {189},
  year         = {2022},
}

@article{11660,
  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 collections of interrelated sorted lists together with their persistence diagrams. },
  author       = {Biswas, Ranita and Cultrera di Montesano, Sebastiano and Edelsbrunner, Herbert and Saghafian, Morteza},
  journal      = {LIPIcs},
  publisher    = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik},
  title        = {{A window to the persistence of 1D maps. I: Geometric characterization of critical point pairs}},
  year         = {2022},
}

@article{11658,
  abstract     = {The depth of a cell in an arrangement of n (non-vertical) great-spheres in Sd is the number of great-spheres that pass above the cell. We prove Euler-type relations, which imply extensions of the classic Dehn–Sommerville relations for convex polytopes to sublevel sets of the depth function, and we use the relations to extend the expressions for the number of faces of neighborly polytopes to the number of cells of levels in neighborly arrangements.},
  author       = {Biswas, Ranita and Cultrera di Montesano, Sebastiano and Edelsbrunner, Herbert and Saghafian, Morteza},
  journal      = {Leibniz International Proceedings on Mathematics},
  publisher    = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik},
  title        = {{Depth in arrangements: Dehn–Sommerville–Euler relations with applications}},
  year         = {2022},
}

@article{12291,
  abstract     = {The phytohormone auxin triggers transcriptional reprogramming through a well-characterized perception machinery in the nucleus. By contrast, mechanisms that underlie fast effects of auxin, such as the regulation of ion fluxes, rapid phosphorylation of proteins or auxin feedback on its transport, remain unclear1,2,3. Whether auxin-binding protein 1 (ABP1) is an auxin receptor has been a source of debate for decades1,4. Here we show that a fraction of Arabidopsis thaliana ABP1 is secreted and binds auxin specifically at an acidic pH that is typical of the apoplast. ABP1 and its plasma-membrane-localized partner, transmembrane kinase 1 (TMK1), are required for the auxin-induced ultrafast global phospho-response and for downstream processes that include the activation of H+-ATPase and accelerated cytoplasmic streaming. abp1 and tmk mutants cannot establish auxin-transporting channels and show defective auxin-induced vasculature formation and regeneration. An ABP1(M2X) variant that lacks the capacity to bind auxin is unable to complement these defects in abp1 mutants. These data indicate that ABP1 is the auxin receptor for TMK1-based cell-surface signalling, which mediates the global phospho-response and auxin canalization.},
  author       = {Friml, Jiří and Gallei, Michelle C and Gelová, Zuzana and Johnson, Alexander J and Mazur, Ewa and Monzer, Aline and Rodriguez Solovey, Lesia and Roosjen, Mark and Verstraeten, Inge and Živanović, Branka D. and Zou, Minxia and Fiedler, Lukas and Giannini, Caterina and Grones, Peter and Hrtyan, Mónika and Kaufmann, Walter and Kuhn, Andre and Narasimhan, Madhumitha and Randuch, Marek and Rýdza, Nikola and Takahashi, Koji and Tan, Shutang and Teplova, Anastasiia and Kinoshita, Toshinori and Weijers, Dolf and Rakusová, Hana},
  issn         = {1476-4687},
  journal      = {Nature},
  number       = {7927},
  pages        = {575--581},
  publisher    = {Springer Nature},
  title        = {{ABP1–TMK auxin perception for global phosphorylation and auxin canalization}},
  doi          = {10.1038/s41586-022-05187-x},
  volume       = {609},
  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},
}

@phdthesis{11879,
  abstract     = {As the overall global mean surface temperature is increasing due to climate change, plant
adaptation to those stressful conditions is of utmost importance for their survival. Plants are
sessile organisms, thus to compensate for their lack of mobility, they evolved a variety of
mechanisms enabling them to flexibly adjust their physiological, growth and developmental
processes to fluctuating temperatures and to survive in harsh environments. While these unique
adaptation abilities provide an important evolutionary advantage, overall modulation of plant
growth and developmental program due to non-optimal temperature negatively affects biomass
production, crop productivity or sensitivity to pathogens. Thus, understanding molecular
processes underlying plant adaptation to increased temperature can provide important
resources for breeding strategies to ensure sufficient agricultural food production.
An increase in ambient temperature by a few degrees leads to profound changes in organ growth
including enhanced hypocotyl elongation, expansion of petioles, hyponastic growth of leaves and
cotyledons, collectively named thermomorphogenesis (Casal & Balasubramanian, 2019). Auxin,
one of the best-studied growth hormones, plays an essential role in this process by direct
activation of transcriptional and non-transcriptional processes resulting in elongation growth
(Majda & Robert, 2018).To modulate hypocotyl growth in response to high ambient temperature
(hAT), auxin needs to be redistributed accordingly. PINs, auxin efflux transporters, are key
components of the polar auxin transport (PAT) machinery, which controls the amount and
direction of auxin translocated in the plant tissues and organs(Adamowski & Friml, 2015). Hence,
PIN-mediated transport is tightly linked with thermo-morphogenesis, and interference with PAT
through either chemical or genetic means dramatically affecting the adaptive responses to hAT.
Intriguingly, despite the key role of PIN mediated transport in growth response to hAT, whether
and how PINs at the level of expression adapt to fluctuation in temperature is scarcely
understood.
With genetic, molecular and advanced bio-imaging approaches, we demonstrate the role of PIN
auxin transporters in the regulation of hypocotyl growth in response to hAT. We show that via
adjustment of PIN3, PIN4 and PIN7 expression in cotyledons and hypocotyls, auxin distribution is modulated thereby determining elongation pattern of epidermal cells at hAT. Furthermore, we
identified three Zinc-Finger (ZF) transcription factors as novel molecular components of the
thermo-regulatory network, which through negative regulation of PIN transcription adjust the
transport of auxin at hAT. Our results suggest that the ZF-PIN module might be a part of the
negative feedback loop attenuating the activity of the thermo-sensing pathway to restrain
exaggerated growth and developmental responses to hAT.},
  author       = {Artner, Christina},
  isbn         = {978-3-99078-022-0},
  issn         = {2663-337X},
  keywords     = {high ambient temperature, auxin, PINs, Zinc-Finger proteins, thermomorphogenesis, stress},
  pages        = {128},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Modulation of auxin transport via ZF proteins adjust plant response to high ambient temperature}},
  doi          = {10.15479/at:ista:11879},
  year         = {2022},
}