On biased compression for distributed learning - Beznosikov, Aleksandr; Horvath, Samuel; Richtarik, Peter; Safaryan, Mher (Journal of Machine Learning Research)
In the last few years, various communication compression techniques have emerged as an indispensable tool helping to alleviate the communication bottleneck in distributed learning. However, despite the fact biased compressors often show superior performance in practice when compared to the much more studied and understood unbiased compressors, very little is known about them. In this work we study three classes of biased compression operators, two of which are new, and their performance when applied to (stochastic) gradient descent and distributed (stochastic) gradient descent. We show for the first time that biased compressors can lead to linear convergence rates both in the single node and distributed settings. We prove that distributed compressed SGD method, employed with error feedback mechanism, enjoys the ergodic rate O(δLexp[−μKδL]+(C+δD)Kμ), where δ≥1 is a compression parameter which grows when more compression is applied, L and μ are the smoothness and strong convexity constants, C captures stochastic gradient noise (C=0 if full gradients are computed on each node) and D captures the variance of the gradients at the optimum (D=0 for over-parameterized models). Further, via a theoretical study of several synthetic and empirical distributions of communicated gradients, we shed light on why and by how much biased compressors outperform their unbiased variants. Finally, we propose several new biased compressors with promising theoretical guarantees and practical performance.

Shortest dominating set reconfiguration under token sliding - Křišťan, Jan Matyáš; Svoboda, Jakub (24th International Symposium on Fundamentals of Computation Theory)
In this paper, we present novel algorithms that efficiently compute a shortest reconfiguration sequence between two given dominating sets in trees and interval graphs under the TOKEN SLIDING model. In this problem, a graph is provided along with its two dominating sets, which can be imagined as tokens placed on vertices. The objective is to find a shortest sequence of dominating sets that transforms one set into the other, with each set in the sequence resulting from sliding a single token in the previous set. While identifying any sequence has been well studied, our work presents the first polynomial algorithms for this optimization variant in the context of dominating sets.

Proof of availability and retrieval in a modular blockchain architecture - Cohen, Shir; Goren, Guy; Kokoris Kogias, Eleftherios; Sonnino, Alberto; Spiegelman, Alexander (27th International Conference on Financial Cryptography and Data Security)
This paper explores a modular design architecture aimed at helping blockchains (and other SMR implementation) to scale to a very large number of processes. This comes in contrast to existing monolithic architectures that interleave transaction dissemination, ordering, and execution in a single functionality. To achieve this we first split the monolith to multiple layers which can use existing distributed computing primitives. The exact specifications of the data dissemination part are formally defined by the Proof of Availability & Retrieval (PoA &R) abstraction. Solutions to the PoA &R problem contain two related sub-protocols: one that “pushes” information into the network and another that “pulls” this information. Regarding the latter, there is a dearth of research literature which is rectified in this paper. We present a family of pulling sub-protocols and rigorously analyze them. Extensive simulations support the theoretical claims of efficiency and robustness in case of a very large number of players. Finally, actual implementation and deployment on a small number of machines (roughly the size of several industrial systems) demonstrates the viability of the architecture’s paradigm.

Connecting theory and experiment in cell and tissue mechanics - Schwayer, Cornelia; Brückner, David (Journal of Cell Science)
Understanding complex living systems, which are fundamentally constrained by physical phenomena, requires combining experimental data with theoretical physical and mathematical models. To develop such models, collaborations between experimental cell biologists and theoreticians are increasingly important but these two groups often face challenges achieving mutual understanding. To help navigate these challenges, this Perspective discusses different modelling approaches, including bottom-up hypothesis-driven and top-down data-driven models, and highlights their strengths and applications. Using cell mechanics as an example, we explore the integration of specific physical models with experimental data from the molecular, cellular and tissue level up to multiscale input. We also emphasize the importance of constraining model complexity and outline strategies for crosstalk between experimental design and model development. Furthermore, we highlight how physical models can provide conceptual insights and produce unifying and generalizable frameworks for biological phenomena. Overall, this Perspective aims to promote fruitful collaborations that advance our understanding of complex biological systems.
Keywords: Cell Biology

Learning control policies for stochastic systems with reach-avoid guarantees - Zikelic, Dorde; Lechner, Mathias; Henzinger, Thomas A; Chatterjee, Krishnendu (Proceedings of the 37th AAAI Conference on Artificial Intelligence)
We study the problem of learning controllers for discrete-time non-linear stochastic dynamical systems with formal reach-avoid guarantees. This work presents the first method for providing formal reach-avoid guarantees, which combine and generalize stability and safety guarantees, with a tolerable probability threshold p in [0,1] over the infinite time horizon. Our method leverages advances in machine learning literature and it represents formal certificates as neural networks. In particular, we learn a certificate in the form of a reach-avoid supermartingale (RASM), a novel notion that we introduce in this work. Our RASMs provide reachability and avoidance guarantees by imposing constraints on what can be viewed as a stochastic extension of level sets of Lyapunov functions for deterministic systems. Our approach solves several important problems -- it can be used to learn a control policy from scratch, to verify a reach-avoid specification for a fixed control policy, or to fine-tune a pre-trained policy if it does not satisfy the reach-avoid specification. We validate our approach on 3 stochastic non-linear reinforcement learning tasks.
Keywords: General Medicine

On kinetic constraints that catalysis imposes on elementary processes - Sakref, Yann; Muñoz Basagoiti, Maitane; Zeravcic, Zorana; Rivoire, Olivier (The Journal of Physical Chemistry B)
Catalysis, the acceleration of product formation by a substance that is left unchanged, typically results from multiple elementary processes, including diffusion of the reactants toward the catalyst, chemical steps, and release of the products. While efforts to design catalysts are often focused on accelerating the chemical reaction on the catalyst, catalysis is a global property of the catalytic cycle that involves all processes. These are controlled by both intrinsic parameters such as the composition and shape of the catalyst and extrinsic parameters such as the concentration of the chemical species at play. We examine here the conditions that catalysis imposes on the different steps of a reaction cycle and the respective role of intrinsic and extrinsic parameters of the system on the emergence of catalysis by using an approach based on first-passage times. We illustrate this approach for various decompositions of a catalytic cycle into elementary steps, including non-Markovian decompositions, which are useful when the presence and nature of intermediate states are a priori unknown. Our examples cover different types of reactions and clarify the constraints on elementary steps and the impact of species concentrations on catalysis.
Keywords: Materials Chemistry; Surfaces; Coatings and Films; Physical and Theoretical Chemistry

Nonadditivity in interactions between three membrane-wrapped colloidal spheres - Azadbakht, Ali; Meadowcroft, Billie; Majek, Juraj; Šarić, Anđela; Kraft, Daniela J. (Biophysical Journal)
Many cell functions require a concerted effort from multiple membrane proteins, for example, for signaling, cell division, and endocytosis. One contribution to their successful self-organization stems from the membrane deformations that these proteins induce. While the pairwise interaction potential of two membrane-deforming spheres has recently been measured, membrane-deformation-induced interactions have been predicted to be nonadditive, and hence their collective behavior cannot be deduced from this measurement. We here employ a colloidal model system consisting of adhesive spheres and giant unilamellar vesicles to test these predictions by measuring the interaction potential of the simplest case of three membrane-deforming, spherical particles. We quantify their interactions and arrangements and, for the first time, experimentally confirm and quantify the nonadditive nature of membrane-deformation-induced interactions. We furthermore conclude that there exist two favorable configurations on the membrane: (1) a linear and (2) a triangular arrangement of the three spheres. Using Monte Carlo simulations, we corroborate the experimentally observed energy minima and identify a lowering of the membrane deformation as the cause for the observed configurations. The high symmetry of the preferred arrangements for three particles suggests that arrangements of many membrane-deforming objects might follow simple rules.

Cover Picture: The rigid core and flexible surface of amyloid fibrils probed by Magic‐Angle‐Spinning NMR spectroscopy of aromatic residues - Becker, Lea Marie; Berbon, Mélanie; Vallet, Alicia; Grelard, Axelle; Morvan, Estelle; Bardiaux, Benjamin; Lichtenecker, Roman; Ernst, Matthias; Loquet, Antoine; Schanda, Paul (Angewandte Chemie International Edition)
Cover Page
Keywords: General Chemistry; Catalysis

On the rightmost eigenvalue of non-Hermitian random matrices - Cipolloni, Giorgio; Erdös, László; Schröder, Dominik J; Xu, Yuanyuan (The Annals of Probability)
We establish a precise three-term asymptotic expansion, with an optimal estimate of the error term, for the rightmost eigenvalue of an n×n random matrix with independent identically distributed complex entries as n tends to infinity. All terms in the expansion are universal.
Keywords: Statistics; Probability and Uncertainty; Statistics and Probability

Der starre Kern und die flexible Oberfläche von Amyloidfibrillen – Magic‐Angle‐Spinning NMR Spektroskopie von aromatischen Resten - Becker, Lea Marie; Berbon, Mélanie; Vallet, Alicia; Grelard, Axelle; Morvan, Estelle; Bardiaux, Benjamin; Lichtenecker, Roman; Ernst, Matthias; Loquet, Antoine; Schanda, Paul (Angewandte Chemie)
Aromatische Seitenketten sind wichtige Indikatoren für die Plastizität von Proteinen und bilden oft entscheidende Kontakte bei Protein‐Protein‐Wechselwirkungen. Wir untersuchten aromatische Reste in den beiden strukturell homologen cross‐β Amyloidfibrillen HET‐s und HELLF mit Hilfe eines spezifischen Ansatzes zur Isotopenmarkierung und Festkörper NMR mit Drehung am magischen Winkel. Das dynamische Verhalten der aromatischen Reste Phe und Tyr deutet darauf hin, dass der hydrophobe Amyloidkern starr ist und keine Anzeichen von “atmenden Bewegungen” auf einer Zeitskala von Hunderten von Millisekunden zeigt. Aromatische Reste, die exponiert an der Fibrillenoberfläche sitzen, haben zwar eine starre Ringachse, weisen aber Ringflips auf verschiedenen Zeitskalen von Nanosekunden bis Mikrosekunden auf. Unser Ansatz bietet einen direkten Einblick in die Bewegungen des hydrophoben Kerns und ermöglicht eine bessere Bewertung der Konformationsheterogenität, die aus einem NMR‐Strukturensemble einer solchen Cross‐β‐Amyloidstruktur hervorgeht.
Keywords: General Medicine

Mechanisms for the Self‐Organization of Tropical Deep Convection - Haerter, Jan O.; Muller, Caroline J (Clouds and Their Climatic Impacts)
Organization – or departure from a random pattern – in tropical deep convection is heavily studied due to its immediate relevance to climate sensitivity and extremes. Low-latitude convection has motivated numerical model idealizations, where the Coriolis force is removed and boundary conditions are simplified spatially and temporally. One of the most stunning aspects of such idealized simulated cloud organization is the spontaneous clumping of convection that can occur without any predetermining external perturbation, such as inhomogeneous surface boundary conditions or large-scale waves. Whereas individual convective rain cells measure only few kilometers in horizontal diameter, the clusters they form can often span hundreds or even thousands of kilometers. Hence, organization may emerge from the very small scales but can show effects at the synoptic scale. We refer to such emergent organization as convective self-organization. Convective self-organization thus features characteristics of emergence, such as non-trivial system-scale pattern formation or hysteresis. We summarize observational evidence for large-scale organization and briefly recap classical idealized modeling studies that yield convective self-aggregation – emergent organization under strongly idealized boundary conditions. We then focus on developing research, where temporal variation, such as the diurnal cycle, or two-way interactive surface properties yield distinct organizational modes. Convectively generated cold pools and mesoscale convective systems, both ubiquitous in nature, are thereby found to potentially play key roles in promoting – rather than suppressing – sustained system-scale organization.

Preparing Chaperone–Client Protein Complexes for Biophysical and Structural Studies - Sučec, I.; Schanda, Paul (Biophysics of Molecular Chaperones)
Understanding the mechanisms of chaperones at the atomic level generally requires producing chaperone–client complexes in vitro. This task comes with significant challenges, because one needs to find conditions in which the client protein is presented to the chaperone in a state that binds and at the same time avoid the pitfalls of protein aggregation that are often inherent to such states. The strategy differs significantly for different client proteins and chaperones, but there are common underlying principles. Here, we discuss these principles and deduce the strategies that can be successfully applied for different chaperone–client complexes. We review successful biochemical strategies applied to making the client protein “binding competent” and illustrate the different strategies with examples of recent biophysical and biochemical studies.

Probing Single Chaperone Substrates - Wruck, F.; Avellaneda Sarrió, Mario; Naqvi, M. M.; Koers, E. J.; Till, K.; Gross, L.; Moayed, F.; Roland, A.; Heling, L. W. H. J.; Mashaghi, A.; Tans, S. J. (Biophysics of Molecular Chaperones)
Regulating protein states is considered the core function of chaperones. However, despite their importance to all major cellular processes, the conformational changes that chaperones impart on polypeptide chains are difficult to study directly due to their heterogeneous, dynamic, and multi-step nature. Here, we review recent advances towards this aim using single-molecule manipulation methods, which are rapidly revealing new mechanisms of conformational control and helping to define a different perspective on the chaperone function.

Ubiquity of bound states for the strongly coupled polaron - Mitrouskas, David Johannes; Seiringer, Robert (Pure and Applied Analysis)
Abstract We study the spectrum of the Fröhlich Hamiltonian for the polaron at fixed total momentum. We prove the existence of excited eigenvalues between the ground state energy and the essential spectrum at strong coupling. In fact, our main result shows that the number of excited energy bands diverges in the strong coupling limit. To prove this we derive upper bounds for the min-max values of the corresponding fiber Hamiltonians and compare them with the bottom of the essential spectrum, a lower bound on which was recently obtained by Brooks and Seiringer (Comm. Math. Phys. 404:1 (2023), 287–337). The upper bounds are given in terms of the ground state energy band shifted by momentum-independent excitation energies determined by an effective Hamiltonian of Bogoliubov type.
Keywords: General Medicine

Entangling microwaves and telecom wavelength light - Sahu, Rishabh; Qiu, Liu; Hease, William J; Arnold, Georg M; Minoguchi, Yuri; Rabl, Peter; Fink, Johannes M (Frontiers in Optics + Laser Science 2023)
We entangled microwave and optical photons for the first time as verified by a measured two-mode vacuum squeezing of 0.7 dB. This electro-optic entanglement is the key resource needed to connect cryogenic quantum circuits.

Constructing Hamilton cycles and perfect matchings efficiently - Anastos, Michael (Proceedings of the 12th European Conference on Combinatorics, Graph Theory and Applications)
Starting with the empty graph on $[n]$, at each round, a set of $K=K(n)$ edges is presented chosen uniformly at random from the ones that have not been presented yet. We are then asked to choose at most one of the presented edges and add it to the current graph. Our goal is to construct a Hamiltonian graph with $(1+o(1))n$ edges within as few rounds as possible. We show that in this process, one can build a Hamiltonian graph of size $(1+o(1))n$ in $(1+o(1))(1+(\log n)/2K) n$ rounds w.h.p. The case $K=1$ implies that w.h.p. one can build a Hamiltonian graph by choosing $(1+o(1))n$ edges in an online fashion as they appear along the first $(0.5+o(1))n\log n$ rounds of the random graph process. This answers a question of Frieze, Krivelevich and Michaeli. Observe that the number of rounds is asymptotically optimal as the first $0.5n\log n$ edges do not span a Hamilton cycle w.h.p. The case $K=Θ(\log n)$ implies that the Hamiltonicity threshold of the corresponding Achlioptas process is at most $(1+o(1))(1+(\log n)/2K) n$. This matches the $(1-o(1))(1+(\log n)/2K) n$ lower bound due to Krivelevich, Lubetzky and Sudakov and resolves the problem of determining the Hamiltonicity threshold of the Achlioptas process with $K=Θ(\log n)$. We also show that in the above process one can construct a graph $G$ that spans a matching of size $\lfloor V(G)/2) \rfloor$ and $(0.5+o(1))n$ edges within $(1+o(1))(0.5+(\log n)/2K) n$ rounds w.h.p. Our proof relies on a robust Hamiltonicity property of the strong $4$-core of the binomial random graph which we use as a black-box. This property allows it to absorb paths covering vertices outside the strong $4$-core into a cycle.

Measuring spontaneous charging of single aerosol particles - Stöllner, Andrea; Lenton, Isaac C; Muller, Caroline J; Waitukaitis, Scott R (EGU General Assembly 2023)

Complex vaccination strategies prevent the emergence of vaccine resistance - Rella, Simon; Kulikova, Y; Minnegalieva, Aygul; Kondrashov, Fyodor (European Journal of Public Health)
Keywords: Public Health; Environmental and Occupational Health

Intensification mechanisms of tropical cyclones - Polesello, Andrea; Muller, Caroline J; Pasquero, Claudia; Meroni, Agostino N. (EGU General Assembly 2023)

PCBend: Light up your 3D shapes with foldable circuit boards - Freire, Marco; Bhargava, Manas; Schreck, Camille; Hugron, Pierre-Alexandre; Bickel, Bernd; Lefebvre, Sylvain (Transactions on Graphics)
We propose a computational design approach for covering a surface with individually addressable RGB LEDs, effectively forming a low-resolution surface screen. To achieve a low-cost and scalable approach, we propose creating designs from flat PCB panels bent in-place along the surface of a 3D printed core. Working with standard rigid PCBs enables the use of established PCB manufacturing services, allowing the fabrication of designs with several hundred LEDs. Our approach optimizes the PCB geometry for folding, and then jointly optimizes the LED packing, circuit and routing, solving a challenging layout problem under strict manufacturing requirements. Unlike paper, PCBs cannot bend beyond a certain point without breaking. Therefore, we introduce parametric cut patterns acting as hinges, designed to allow bending while remaining compact. To tackle the joint optimization of placement, circuit and routing, we propose a specialized algorithm that splits the global problem into one sub-problem per triangle, which is then individually solved. Our technique generates PCB blueprints in a completely automated way. After being fabricated by a PCB manufacturing service, the boards are bent and glued by the user onto the 3D printed support. We demonstrate our technique on a range of physical models and virtual examples, creating intricate surface light patterns from hundreds of LEDs.
Keywords: PCB design and layout; Mesh geometry models

Distinct functions of TIR1 and AFB1 receptors in auxin signalling. - Chen, Huihuang; Li, Lanxin; Zou, Minxia; Qi, Linlin; Friml, Jiří (Molecular Plant)
Auxin is the major plant hormone regulating growth and development (Friml, 2022). Forward genetic approaches in the model plant Arabidopsis thaliana have identified major components of auxin signalling and established the canonical mechanism mediating transcriptional and thus developmental reprogramming. In this textbook view, TRANSPORT INHIBITOR RESPONSE 1 (TIR1)/AUXIN-SIGNALING F-BOX (AFBs) are auxin receptors, which act as F-box subunits determining the substrate specificity of the Skp1-Cullin1-F box protein (SCF) type E3 ubiquitin ligase complex. Auxin acts as a “molecular glue” increasing the affinity between TIR1/AFBs and the Aux/IAA repressors. Subsequently, Aux/IAAs are ubiquitinated and degraded, thus releasing auxin transcription factors from their repression making them free to mediate transcription of auxin response genes (Yu et al., 2022). Nonetheless, accumulating evidence suggests existence of rapid, non-transcriptional responses downstream of TIR1/AFBs such as auxin-induced cytosolic calcium (Ca2+) transients, plasma membrane depolarization and apoplast alkalinisation, all converging on the process of root growth inhibition and root gravitropism (Li et al., 2022). Particularly, these rapid responses are mostly contributed by predominantly cytosolic AFB1, while the long-term growth responses are mediated by mainly nuclear TIR1 and AFB2-AFB5 (Li et al., 2021; Prigge et al., 2020; Serre et al., 2021). How AFB1 conducts auxin-triggered rapid responses and how it is different from TIR1 and AFB2-AFB5 remains elusive. Here, we compare the roles of TIR1 and AFB1 in transcriptional and rapid responses by modulating their subcellular localization in Arabidopsis and by testing their ability to mediate transcriptional responses when part of the minimal auxin circuit reconstituted in yeast.

douglastome/dynamic-engrams: Dynamic and selective engrams emerge with memory consolidation - Feitosa Tomé, Douglas
Code and data necessary to reproduce the simulations and data analyses reported in our manuscript: Tomé, D.F., Zhang, Y., Aida, T., Mosto, O., Lu, Y., Chen, M., Sadeh, S., Roy, D. S., Clopath, C. Dynamic and selective engrams emerge with memory consolidation. 2023.

Superconductivity from a melted insulator in Josephson junction arrays - Mukhopadhyay, Soham; Senior, Jorden L; Saez Mollejo, Jaime; Puglia, Denise; Zemlicka, Martin; Fink, Johannes M; Higginbotham, Andrew P (Nature Physics)
Arrays of Josephson junctions are governed by a competition between superconductivity and repulsive Coulomb interactions, and are expected to exhibit diverging low-temperature resistance when interactions exceed a critical level. Here we report a study of the transport and microwave response of Josephson arrays with interactions exceeding this level. Contrary to expectations, we observe that the array resistance drops dramatically as the temperature is decreased—reminiscent of superconducting behaviour—and then saturates at low temperature. Applying a magnetic field, we eventually observe a transition to a highly resistive regime. These observations can be understood within a theoretical picture that accounts for the effect of thermal fluctuations on the insulating phase. On the basis of the agreement between experiment and theory, we suggest that apparent superconductivity in our Josephson arrays arises from melting the zero-temperature insulator.
Keywords: General Physics and Astronomy

Tale of cAMP as a second messenger in auxin signaling and beyond - Qi, Linlin; Friml, Jiří (New Phytologist)
The 3′,5′-cyclic adenosine monophosphate (cAMP) is a versatile second messenger in many mammalian signaling pathways. However, its role in plants remains not well-recognized. Recent discovery of adenylate cyclase (AC) activity for transport inhibitor response 1/auxin-signaling F-box proteins (TIR1/AFB) auxin receptors and the demonstration of its importance for canonical auxin signaling put plant cAMP research back into spotlight. This insight briefly summarizes the well-established cAMP signaling pathways in mammalian cells and describes the turbulent and controversial history of plant cAMP research highlighting the major progress and the unresolved points. We also briefly review the current paradigm of auxin signaling to provide a background for the discussion on the AC activity of TIR1/AFB auxin receptors and its potential role in transcriptional auxin signaling as well as impact of these discoveries on plant cAMP research in general.

Control of tissue dimensions in the developing neural tube and somites - Minchington, Thomas; Rus, Stefanie; Kicheva, Anna (Current Opinion in Systems Biology)
Despite its fundamental importance for development, the question of how organs achieve their correct size and shape is poorly understood. This complex process requires coordination between the generation of cell mass and the morphogenetic mechanisms that sculpt tissues. These processes are regulated by morphogen signalling pathways and mechanical forces. Yet, in many systems, it is unclear how biochemical and mechanical signalling are quantitatively interpreted to determine the behaviours of individual cells and how they contribute to growth and morphogenesis at the tissue scale. In this review, we discuss the development of the vertebrate neural tube and somites as an example of the state of knowledge, as well as the challenges in understanding the mechanisms of tissue size control in vertebrate organogenesis. We highlight how the recent advances in stem cell differentiation and organoid approaches can be harnessed to provide new insights into this question.

Reaction-diffusion equations with transport noise and critical superlinear diffusion: Local well-posedness and positivity - Agresti, Antonio; Veraar, Mark (Journal of Differential Equations)
In this paper we consider a class of stochastic reaction-diffusion equations. We provide local well-posedness, regularity, blow-up criteria and positivity of solutions. The key novelties of this work are related to the use transport noise, critical spaces and the proof of higher order regularity of solutions – even in case of non-smooth initial data. Crucial tools are Lp(Lp)-theory, maximal regularity estimates and sharp blow-up criteria. We view the results of this paper as a general toolbox for establishing global well-posedness for a large class of reaction-diffusion systems of practical interest, of which many are completely open. In our follow-up work [8], the results of this paper are applied in the specific cases of the Lotka-Volterra equations and the Brusselator model.

Iterated medial triangle subdivision in surfaces of constant curvature - Brunck, Florestan R (Discrete and Computational Geometry)
Consider a geodesic triangle on a surface of constant curvature and subdivide it recursively into four triangles by joining the midpoints of its edges. We show the existence of a uniform δ>0 such that, at any step of the subdivision, all the triangle angles lie in the interval (δ,π−δ) . Additionally, we exhibit stabilising behaviours for both angles and lengths as this subdivision progresses.

Codes for the Z-channel - Polyanskii, Nikita; Zhang, Yihan (IEEE Transactions on Information Theory)
This paper is a collection of results on combinatorial properties of codes for the Z-channel . A Z-channel with error fraction τ takes as input a length- n binary codeword and injects in an adversarial manner up to n τ asymmetric errors, i.e., errors that only zero out bits but do not flip 0’s to 1’s. It is known that the largest ( L - 1)-list-decodable code for the Z-channel with error fraction τ has exponential size (in n ) if τ is less than a critical value that we call the ( L - 1)- list-decoding Plotkin point and has constant size if τ is larger than the threshold. The ( L -1)-list-decoding Plotkin point is known to be L -1/L-1 – L -L/ L-1 , which equals 1/4 for unique-decoding with L -1 = 1. In this paper, we derive various results for the size of the largest codes above and below the list-decoding Plotkin point. In particular, we show that the largest ( L -1)-list-decodable code ε-above the Plotkin point, for any given sufficiently small positive constant ε > 0, has size Θ L (ε -3/2 ) for any L - 1 ≥ 1. We also devise upper and lower bounds on the exponential size of codes below the list-decoding Plotkin point.

Chemical inhibition of Arabidopsis PIN-FORMED auxin transporters by the anti-inflammatory drug naproxen - Xia, Jing; Kong, Mengjuan; Yang, Zhisen; Sun, Lianghanxiao; Peng, Yakun; Mao, Yanbo; Wei, Hong; Ying, Wei; Gao, Yongxiao; Friml, Jiří; Weng, Jianping; Liu, Xin; et al. (Plant Communications)
The phytohormone auxin plays central roles in many growth and developmental processes in plants. Development of chemical tools targeting the auxin pathway is useful for both plant biology and agriculture. Here we reveal that naproxen, a synthetic compound with anti-inflammatory activity in humans, acts as an auxin transport inhibitor targeting PIN-FORMED (PIN) transporters in plants. Physiological experiments indicate that exogenous naproxen treatment affects pleiotropic auxin-regulated developmental processes. Additional cellular and biochemical evidence indicates that naproxen suppresses auxin transport, specifically PIN-mediated auxin efflux. Moreover, biochemical and structural analyses confirm that naproxen binds directly to PIN1 protein via the same binding cavity as the indole-3-acetic acid substrate. Thus, by combining cellular, biochemical, and structural approaches, this study clearly establishes that naproxen is a PIN inhibitor and elucidates the underlying mechanisms. Further use of this compound may advance our understanding of the molecular mechanisms of PIN-mediated auxin transport and expand our toolkit in auxin biology and agriculture.

Unconventional colloidal aggregation in chiral bacterial baths - Grober, Daniel; Palaia, Ivan; Ucar, Mehmet C; Hannezo, Edouard B; Šarić, Anđela; Palacci, Jérémie A (Nature Physics)
When in equilibrium, thermal forces agitate molecules, which then diffuse, collide and bind to form materials. However, the space of accessible structures in which micron-scale particles can be organized by thermal forces is limited, owing to the slow dynamics and metastable states. Active agents in a passive fluid generate forces and flows, forming a bath with active fluctuations. Two unanswered questions are whether those active agents can drive the assembly of passive components into unconventional states and which material properties they will exhibit. Here we show that passive, sticky beads immersed in a bath of swimming Escherichia coli bacteria aggregate into unconventional clusters and gels that are controlled by the activity of the bath. We observe a slow but persistent rotation of the aggregates that originates in the chirality of the E. coli flagella and directs aggregation into structures that are not accessible thermally. We elucidate the aggregation mechanism with a numerical model of spinning, sticky beads and reproduce quantitatively the experimental results. We show that internal activity controls the phase diagram and the structure of the aggregates. Overall, our results highlight the promising role of active baths in designing the structural and mechanical properties of materials with unconventional phases.

The Dean-Kawasaki equation and the structure of density fluctuations in systems of diffusing particles - Cornalba, Federico; Fischer, Julian L (Archive for Rational Mechanics and Analysis)
The Dean–Kawasaki equation—a strongly singular SPDE—is a basic equation of fluctuating hydrodynamics; it has been proposed in the physics literature to describe the fluctuations of the density of N independent diffusing particles in the regime of large particle numbers N≫1. The singular nature of the Dean–Kawasaki equation presents a substantial challenge for both its analysis and its rigorous mathematical justification. Besides being non-renormalisable by the theory of regularity structures by Hairer et al., it has recently been shown to not even admit nontrivial martingale solutions. In the present work, we give a rigorous and fully quantitative justification of the Dean–Kawasaki equation by considering the natural regularisation provided by standard numerical discretisations: We show that structure-preserving discretisations of the Dean–Kawasaki equation may approximate the density fluctuations of N non-interacting diffusing particles to arbitrary order in N−1 (in suitable weak metrics). In other words, the Dean–Kawasaki equation may be interpreted as a “recipe” for accurate and efficient numerical simulations of the density fluctuations of independent diffusing particles.

Into the unknown: Active monitoring of neural networks (extended version) - Kueffner, Konstantin; Lukina, Anna; Schilling, Christian; Henzinger, Thomas A (International Journal on Software Tools for Technology Transfer)
Neural-network classifiers achieve high accuracy when predicting the class of an input that they were trained to identify. Maintaining this accuracy in dynamic environments, where inputs frequently fall outside the fixed set of initially known classes, remains a challenge. We consider the problem of monitoring the classification decisions of neural networks in the presence of novel classes. For this purpose, we generalize our recently proposed abstraction-based monitor from binary output to real-valued quantitative output. This quantitative output enables new applications, two of which we investigate in the paper. As our first application, we introduce an algorithmic framework for active monitoring of a neural network, which allows us to learn new classes dynamically and yet maintain high monitoring performance. As our second application, we present an offline procedure to retrain the neural network to improve the monitor’s detection performance without deteriorating the network’s classification accuracy. Our experimental evaluation demonstrates both the benefits of our active monitoring framework in dynamic scenarios and the effectiveness of the retraining procedure.

Protein dynamics detected by magic-angle spinning relaxation dispersion NMR - Napoli, Federico; Becker, Lea Marie; Schanda, Paul (Current Opinion in Structural Biology)
Magic-angle spinning (MAS) nuclear magnetic resonance (NMR) is establishing itself as a powerful method for the characterization of protein dynamics at the atomic scale. We discuss here how R1ρ MAS relaxation dispersion NMR can explore microsecond-to-millisecond motions. Progress in instrumentation, isotope labeling, and pulse sequence design has paved the way for quantitative analyses of even rare structural fluctuations. In addition to isotropic chemical-shift fluctuations exploited in solution-state NMR relaxation dispersion experiments, MAS NMR has a wider arsenal of observables, allowing to see motions even if the exchanging states do not differ in their chemical shifts. We demonstrate the potential of the technique for probing motions in challenging large enzymes, membrane proteins, and protein assemblies.

A combinatorial cut-toggling algorithm for solving Laplacian linear systems - Henzinger, Monika H; Jin, Billy; Peng, Richard; Williamson, David P. (Algorithmica)
Over the last two decades, a significant line of work in theoretical algorithms has made progress in solving linear systems of the form Lx=b, where L is the Laplacian matrix of a weighted graph with weights w(i,j)>0 on the edges. The solution x of the linear system can be interpreted as the potentials of an electrical flow in which the resistance on edge (i, j) is 1/w(i, j). Kelner et al. (in: Proceedings of the 45th Annual ACM Symposium on the Theory of Computing, pp 911–920, 2013. https://doi.org/10.1145/2488608.2488724) give a combinatorial, near-linear time algorithm that maintains the Kirchoff Current Law, and gradually enforces the Kirchoff Potential Law by updating flows around cycles (cycle toggling). In this paper, we consider a dual version of the algorithm that maintains the Kirchoff Potential Law, and gradually enforces the Kirchoff Current Law by cut toggling: each iteration updates all potentials on one side of a fundamental cut of a spanning tree by the same amount. We prove that this dual algorithm also runs in a near-linear number of iterations. We show, however, that if we abstract cut toggling as a natural data structure problem, this problem can be reduced to the online vector–matrix-vector problem, which has been conjectured to be difficult for dynamic algorithms (Henzinger et al., in: Proceedings of the 47th Annual ACM Symposium on the Theory of Computing, pp 21–30, 2015. https://doi.org/10.1145/2746539.2746609). The conjecture implies that the data structure does not have an O(n1−ϵ) time algorithm for any ϵ>0, and thus a straightforward implementation of the cut-toggling algorithm requires essentially linear time per iteration. To circumvent the lower bound, we batch update steps, and perform them simultaneously instead of sequentially. An appropriate choice of batching leads to an O˜(m1.5) time cut-toggling algorithm for solving Laplacian systems. Furthermore, we show that if we sparsify the graph and call our algorithm recursively on the Laplacian system implied by batching and sparsifying, we can reduce the running time to O(m1+ϵ) for any ϵ>0. Thus, the dual cut-toggling algorithm can achieve (almost) the same running time as its primal cycle-toggling counterpart.

Derivations and KMS-symmetric quantum Markov semigroups - Vernooij, Matthijs; Wirth, Melchior (Communications in Mathematical Physics)
We prove that the generator of the L2 implementation of a KMS-symmetric quantum Markov semigroup can be expressed as the square of a derivation with values in a Hilbert bimodule, extending earlier results by Cipriani and Sauvageot for tracially symmetric semigroups and the second-named author for GNS-symmetric semigroups. This result hinges on the introduction of a new completely positive map on the algebra of bounded operators on the GNS Hilbert space. This transformation maps symmetric Markov operators to symmetric Markov operators and is essential to obtain the required inner product on the Hilbert bimodule.

Beyond pulsed inhibition: Alpha oscillations modulate attenuation and amplification of neural activity in the awake resting state - Lombardi, Fabrizio; Herrmann, Hans J.; Parrino, Liborio; Plenz, Dietmar; Scarpetta, Silvia; Vaudano, Anna Elisabetta; De Arcangelis, Lucilla; Shriki, Oren (Cell Reports)
Alpha oscillations are a distinctive feature of the awake resting state of the human brain. However, their functional role in resting-state neuronal dynamics remains poorly understood. Here we show that, during resting wakefulness, alpha oscillations drive an alternation of attenuation and amplification bouts in neural activity. Our analysis indicates that inhibition is activated in pulses that last for a single alpha cycle and gradually suppress neural activity, while excitation is successively enhanced over a few alpha cycles to amplify neural activity. Furthermore, we show that long-term alpha amplitude fluctuations—the “waxing and waning” phenomenon—are an attenuation-amplification mechanism described by a power-law decay of the activity rate in the “waning” phase. Importantly, we do not observe such dynamics during non-rapid eye movement (NREM) sleep with marginal alpha oscillations. The results suggest that alpha oscillations modulate neural activity not only through pulses of inhibition (pulsed inhibition hypothesis) but also by timely enhancement of excitation (or disinhibition).

Genetic insights into the age-specific biological mechanisms governing human ovarian aging - Ojavee, Sven E.; Darrous, Liza; Patxot, Marion; Läll, Kristi; Fischer, Krista; Mägi, Reedik; Kutalik, Zoltan; Robinson, Matthew Richard (American Journal of Human Genetics)
There is currently little evidence that the genetic basis of human phenotype varies significantly across the lifespan. However, time-to-event phenotypes are understudied and can be thought of as reflecting an underlying hazard, which is unlikely to be constant through life when values take a broad range. Here, we find that 74% of 245 genome-wide significant genetic associations with age at natural menopause (ANM) in the UK Biobank show a form of age-specific effect. Nineteen of these replicated discoveries are identified only by our modeling framework, which determines the time dependency of DNA-variant age-at-onset associations without a significant multiple-testing burden. Across the range of early to late menopause, we find evidence for significantly different underlying biological pathways, changes in the signs of genetic correlations of ANM to health indicators and outcomes, and differences in inferred causal relationships. We find that DNA damage response processes only act to shape ovarian reserve and depletion for women of early ANM. Genetically mediated delays in ANM were associated with increased relative risk of breast cancer and leiomyoma at all ages and with high cholesterol and heart failure for late-ANM women. These findings suggest that a better understanding of the age dependency of genetic risk factor relationships among health indicators and outcomes is achievable through appropriate statistical modeling of large-scale biobank data.

Arithmetic and metric aspects of open de Rham spaces - Hausel, Tamás; Wong, Michael Lennox; Wyss, Dimitri (Proceedings of the London Mathematical Society)
In this paper, we determine the motivic class — in particular, the weight polynomial and conjecturally the Poincaré polynomial — of the open de Rham space, defined and studied by Boalch, of certain moduli spaces of irregular meromorphic connections on the trivial rank bundle on P1. The computation is by motivic Fourier transform. We show that the result satisfies the purity conjecture, that is, it agrees with the pure part of the conjectured mixed Hodge polynomial of the corresponding wild character variety. We also identify the open de Rham spaces with quiver varieties with multiplicities of Yamakawa and Geiss–Leclerc–Schröer. We finish with constructing natural complete hyperkähler metrics on them, which in the four-dimensional cases are expected to be of type ALF.

Stretching the limits of extracellular signal-related kinase (ERK) signaling — Cell mechanosensing to ERK activation - Hirashima, Tsuyoshi; Hino, Naoya; Aoki, Kazuhiro; Matsuda, Michiyuki (Current Opinion in Cell Biology)
Extracellular signal-regulated kinase (ERK) has been recognized as a critical regulator in various physiological and pathological processes. Extensive research has elucidated the signaling mechanisms governing ERK activation via biochemical regulations with upstream molecules, particularly receptor tyrosine kinases (RTKs). However, recent advances have highlighted the role of mechanical forces in activating the RTK–ERK signaling pathways, thereby opening new avenues of research into mechanochemical interplay in multicellular tissues. Here, we review the force-induced ERK activation in cells and propose possible mechanosensing mechanisms underlying the mechanoresponsive ERK activation. We conclude that mechanical forces are not merely passive factors shaping cells and tissues but also active regulators of cellular signaling pathways controlling collective cell behaviors.

Successive vertex orderings of fully regular graphs - Fang, Lixing; Huang, Hao; Pach, János; Tardos, Gábor; Zuo, Junchi (Journal of Combinatorial Theory. Series A)
A graph G=(V, E) is called fully regular if for every independent set I c V, the number of vertices in V\I that are not connected to any element of I depends only on the size of I. A linear ordering of the vertices of G is called successive if for every i, the first i vertices induce a connected subgraph of G. We give an explicit formula for the number of successive vertex orderings of a fully regular graph. As an application of our results, we give alternative proofs of two theorems of Stanley and Gao & Peng, determining the number of linear edge orderings of complete graphs and complete bipartite graphs, respectively, with the property that the first i edges induce a connected subgraph. As another application, we give a simple product formula for the number of linear orderings of the hyperedges of a complete 3-partite 3-uniform hypergraph such that, for every i, the first i hyperedges induce a connected subgraph. We found similar formulas for complete (non-partite) 3-uniform hypergraphs and in another closely related case, but we managed to verify them only when the number of vertices is small.

Formal radical deoxyfluorination of oxalate-activated alcohols triggered by the selectfluor-DMAP charge-transfer complex - Baunis, Haralds; Pieber, Bartholomäus (European Journal of Organic Chemistry)
We present a photon- and metal-free approach for the radical fluorination of aliphatic oxalate-activated alcohols. The method relies on the spontaneous generation of the N-(chloromethyl)triethylenediamine radical dication, a potent single electron oxidant, from Selectfluor and 4-(dimethylamino)pyridine. The protocol is easily scalable and provides the desired fluorinated products within only a few minutes reaction time.

A simple approach to Lieb-Thirring type inequalities - Seiringer, Robert; Solovej, Jan Philip (Journal of Functional Analysis)
In [10] Nam proved a Lieb–Thirring Inequality for the kinetic energy of a fermionic quantum system, with almost optimal (semi-classical) constant and a gradient correction term. We present a stronger version of this inequality, with a much simplified proof. As a corollary we obtain a simple proof of the original Lieb–Thirring inequality.

Polycrystalline phases grown in-situ engendering unique mechanism of charge storage in polyaniline-graphite composite - Mahato, Neelima; Singh, Saurabh; Faisal, Mohammad; Sreekanth, T. V.M.; Majumder, Sutripto; Yoo, Kisoo; Kim, Jonghoon (Synthetic Metals)
We report on a simple surfactant/template free chemical route for the synthesis of semi-polycrystalline polyaniline-graphite (SPani-graphite) composite and its application as an electroactive material in electrochemical charge storage. The synthesized material exhibits well-defined poly-crystallographic lattices in high resolution transmission electron micrographs and sharp peaks in x-ray diffraction spectra suggesting crystalline nature of the material. The specific capacitance computed from the galvanostatic charge-discharge (GCD) data obtained from 3-electrode cell configuration using 1 M aq. Na2SO4 as an electrolyte was 111.4 F g−1 at a current density of 0.1 A g−1 which rises to 269 F g−1 at an elevated current density of 1.0 A g−1. A similar pattern of increase in the specific capacitance values with an increase in the current density was observed in the results obtained from 2-electrode symmetric device configuration using polymer gel electrolyte (xanthan gum in 1 M aq. Na2SO4). The specific capacitance computed from the GCD data obtained from the device configuration was 20 F g−1 at the current density of 1.0 A g−1. The device delivers an energy density of 1.7 Wh kg−1 and a power density of 2.48 kWh kg−1 at an applied current density of 0.5 A g−1 suggesting an excellent rate capability and power management. In addition, the device exhibits ⁓92 % specific capacitance retention up to 8000 continuous GCD cycles and ⁓80 % coulombic efficiency up to 10,000 continuous GCD cycles indicating excellent cycling stability. The unique feature of increasing specific capacitance with respect to applied current density is attributed to the presence of semi-polycrystalline phases in the SPani-graphite matrix. The material behaves as a surface redox supercapacitor and its unique mechanism of charge storage is discussed in detail in the article.

Weakly weighted generalised quasi-metric spaces and semilattices - Castellano, Ilaria; Giordano Bruno, Anna; Zava, Nicolò (Theoretical Computer Science)
Motivated by recent applications to entropy theory in dynamical systems, we generalise notions introduced by Matthews and define weakly weighted and componentwise weakly weighted (generalised) quasi-metrics. We then systematise and extend to full generality the correspondences between these objects and other structures arising in theoretical computer science and dynamics. In particular, we study the correspondences with weak partial metrics and, if the underlying space is a semilattice, with invariant (generalised) quasi-metrics satisfying the descending path condition, and with strictly monotone semi(-co-)valuations. We conclude discussing, for endomorphisms of generalised quasi-metric semilattices, a generalisation of both the known intrinsic semilattice entropy and the semigroup entropy.

BAX activation in mouse retinal ganglion cells occurs in two temporally and mechanistically distinct steps - Maes, Margaret E; Donahue, Ryan J.; Schlamp, Cassandra L.; Marola, Olivia J.; Libby, Richard T.; Nickells, Robert W. (Molecular Neurodegeneration)
Background: Pro-apoptotic BAX is a central mediator of retinal ganglion cell (RGC) death after optic nerve damage. BAX activation occurs in two stages including translocation of latent BAX to the mitochondrial outer membrane (MOM) and then permeabilization of the MOM to facilitate the release of apoptotic signaling molecules. As a critical component of RGC death, BAX is an attractive target for neuroprotective therapies and an understanding of the kinetics of BAX activation and the mechanisms controlling the two stages of this process in RGCs is potentially valuable in informing the development of a neuroprotective strategy. Methods: The kinetics of BAX translocation were assessed by both static and live-cell imaging of a GFP-BAX fusion protein introduced into RGCs using AAV2-mediated gene transfer in mice. Activation of BAX was achieved using an acute optic nerve crush (ONC) protocol. Live-cell imaging of GFP-BAX was achieved using explants of mouse retina harvested 7 days after ONC. Kinetics of translocation in RGCs were compared to GFP-BAX translocation in 661W tissue culture cells. Permeabilization of GFP-BAX was assessed by staining with the 6A7 monoclonal antibody, which recognizes a conformational change in this protein after MOM insertion. Assessment of individual kinases associated with both stages of activation was made using small molecule inhibitors injected into the vitreous either independently or in concert with ONC surgery. The contribution of the Dual Leucine Zipper-JUN-N-Terminal Kinase cascade was evaluated using mice with a double conditional knock-out of both Mkk4 and Mkk7. Results: ONC induces the translocation of GFP-BAX in RGCs at a slower rate and with less intracellular synchronicity than 661W cells, but exhibits less variability among mitochondrial foci within a single cell. GFP-BAX was also found to translocate in all compartments of an RGC including the dendritic arbor and axon. Approximately 6% of translocating RGCs exhibited retrotranslocation of BAX immediately following translocation. Unlike tissue culture cells, which exhibit simultaneous translocation and permeabilization, RGCs exhibited a significant delay between these two stages, similar to detached cells undergoing anoikis. Translocation, with minimal permeabilization could be induced in a subset of RGCs using an inhibitor of Focal Adhesion Kinase (PF573228). Permeabilization after ONC, in a majority of RGCs, could be inhibited with a broad spectrum kinase inhibitor (sunitinib) or a selective inhibitor for p38/MAPK14 (SB203580). Intervention of DLK-JNK axis signaling abrogated GFP-BAX translocation after ONC. Conclusions: A comparison between BAX activation kinetics in tissue culture cells and in cells of a complex tissue environment shows distinct differences indicating that caution should be used when translating findings from one condition to the other. RGCs exhibit both a delay between translocation and permeabilization and the ability for translocated BAX to be retrotranslocated, suggesting several stages at which intervention of the activation process could be exploited in the design of a therapeutic strategy.

Microwave-optics entanglement via cavity optomagnomechanics - Fan, Zhi Yuan; Qiu, Liu; Gröblacher, Simon; Li, Jie (Laser and Photonics Reviews)
Microwave-optics entanglement is a vital component for building hybrid quantum networks. Here, a new mechanism for preparing stationary entanglement between microwave and optical cavity fields in a cavity optomagnomechanical system is proposed. It consists of a magnon mode in a ferrimagnetic crystal that couples directly to a microwave cavity mode via the magnetic dipole interaction and indirectly to an optical cavity through the deformation displacement of the crystal. The mechanical displacement is induced by the magnetostrictive force and coupled to the optical cavity via radiation pressure. Both the opto- and magnomechanical couplings are dispersive. Magnon–phonon entanglement is created via magnomechanical parametric down-conversion, which is further distributed to optical and microwave photons via simultaneous optomechanical beamsplitter interaction and electromagnonic state-swap interaction, yielding stationary microwave-optics entanglement. The microwave-optics entanglement is robust against thermal noise, which will find broad potential applications in quantum networks and quantum information processing with hybrid quantum systems.

Spinal cords: Symphonies of interneurons across species - Wilson, Alexia C; Sweeney, Lora Beatrice Jaeger (Frontiers in Neural Circuits)
Vertebrate movement is orchestrated by spinal inter- and motor neurons that, together with sensory and cognitive input, produce dynamic motor behaviors. These behaviors vary from the simple undulatory swimming of fish and larval aquatic species to the highly coordinated running, reaching and grasping of mice, humans and other mammals. This variation raises the fundamental question of how spinal circuits have changed in register with motor behavior. In simple, undulatory fish, exemplified by the lamprey, two broad classes of interneurons shape motor neuron output: ipsilateral-projecting excitatory neurons, and commissural-projecting inhibitory neurons. An additional class of ipsilateral inhibitory neurons is required to generate escape swim behavior in larval zebrafish and tadpoles. In limbed vertebrates, a more complex spinal neuron composition is observed. In this review, we provide evidence that movement elaboration correlates with an increase and specialization of these three basic interneuron types into molecularly, anatomically, and functionally distinct subpopulations. We summarize recent work linking neuron types to movement-pattern generation across fish, amphibians, reptiles, birds and mammals.

Evaluating memory properties in convection schemes using idealised tests - Hwong, Yi-Ling; Colin, Maxime; Aglas, Philipp; Muller, Caroline J; Sherwood, Steven (EGU General Assembly 2023)

Extreme precipitation in tropical squall lines - Abramian, Sophie; Muller, Caroline J; Risi, Camille (EGU General Assembly 2023)

Fast symbolic algorithms for mega-regular games under strong transition fairness - Banerjee, Tamajit; Majumdar, Rupak; Mallik, Kaushik; Schmuck, Anne-Kathrin; Soudjani, Sadegh (TheoretiCS)
We consider fixpoint algorithms for two-player games on graphs with $ω$-regular winning conditions, where the environment is constrained by a strong transition fairness assumption. Strong transition fairness is a widely occurring special case of strong fairness, which requires that any execution is strongly fair with respect to a specified set of live edges: whenever the source vertex of a live edge is visited infinitely often along a play, the edge itself is traversed infinitely often along the play as well. We show that, surprisingly, strong transition fairness retains the algorithmic characteristics of the fixpoint algorithms for $ω$-regular games -- the new algorithms have the same alternation depth as the classical algorithms but invoke a new type of predecessor operator. For Rabin games with $k$ pairs, the complexity of the new algorithm is $O(n^{k+2}k!)$ symbolic steps, which is independent of the number of live edges in the strong transition fairness assumption. Further, we show that GR(1) specifications with strong transition fairness assumptions can be solved with a 3-nested fixpoint algorithm, same as the usual algorithm. In contrast, strong fairness necessarily requires increasing the alternation depth depending on the number of fairness assumptions. We get symbolic algorithms for (generalized) Rabin, parity and GR(1) objectives under strong transition fairness assumptions as well as a direct symbolic algorithm for qualitative winning in stochastic $ω$-regular games that runs in $O(n^{k+2}k!)$ symbolic steps, improving the state of the art. Finally, we have implemented a BDD-based synthesis engine based on our algorithm. We show on a set of synthetic and real benchmarks that our algorithm is scalable, parallelizable, and outperforms previous algorithms by orders of magnitude.

Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels - Bombari, Simone; Kiyani, Shayan; Mondelli, Marco (Proceedings of the 40th International Conference on Machine Learning)
Machine learning models are vulnerable to adversarial perturbations, and a thought-provoking paper by Bubeck and Sellke has analyzed this phenomenon through the lens of over-parameterization: interpolating smoothly the data requires significantly more parameters than simply memorizing it. However, this "universal" law provides only a necessary condition for robustness, and it is unable to discriminate between models. In this paper, we address these gaps by focusing on empirical risk minimization in two prototypical settings, namely, random features and the neural tangent kernel (NTK). We prove that, for random features, the model is not robust for any degree of over-parameterization, even when the necessary condition coming from the universal law of robustness is satisfied. In contrast, for even activations, the NTK model meets the universal lower bound, and it is robust as soon as the necessary condition on over-parameterization is fulfilled. This also addresses a conjecture in prior work by Bubeck, Li and Nagaraj. Our analysis decouples the effect of the kernel of the model from an "interaction matrix", which describes the interaction with the test data and captures the effect of the activation. Our theoretical results are corroborated by numerical evidence on both synthetic and standard datasets (MNIST, CIFAR-10).

Deep neural collapse is provably optimal for the deep unconstrained features model - Súkeník, Peter; Mondelli, Marco; Lampert, Christoph (37th Annual Conference on Neural Information Processing Systems)
Neural collapse (NC) refers to the surprising structure of the last layer of deep neural networks in the terminal phase of gradient descent training. Recently, an increasing amount of experimental evidence has pointed to the propagation of NC to earlier layers of neural networks. However, while the NC in the last layer is well studied theoretically, much less is known about its multi-layered counterpart - deep neural collapse (DNC). In particular, existing work focuses either on linear layers or only on the last two layers at the price of an extra assumption. Our paper fills this gap by generalizing the established analytical framework for NC - the unconstrained features model - to multiple non-linear layers. Our key technical contribution is to show that, in a deep unconstrained features model, the unique global optimum for binary classification exhibits all the properties typical of DNC. This explains the existing experimental evidence of DNC. We also empirically show that (i) by optimizing deep unconstrained features models via gradient descent, the resulting solution agrees well with our theory, and (ii) trained networks recover the unconstrained features suitable for the occurrence of DNC, thus supporting the validity of this modeling principle.

Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence - Wu, Diyuan; Kungurtsev, Vyacheslav; Mondelli, Marco (Transactions on Machine Learning Research)
The stochastic heavy ball method (SHB), also known as stochastic gradient descent (SGD) with Polyak's momentum, is widely used in training neural networks. However, despite the remarkable success of such algorithm in practice, its theoretical characterization remains limited. In this paper, we focus on neural networks with two and three layers and provide a rigorous understanding of the properties of the solutions found by SHB: (i) stability after dropping out part of the neurons, (ii) connectivity along a low-loss path, and (iii) convergence to the global optimum. To achieve this goal, we take a mean-field view and relate the SHB dynamics to a certain partial differential equation in the limit of large network widths. This mean-field perspective has inspired a recent line of work focusing on SGD while, in contrast, our paper considers an algorithm with momentum. More specifically, after proving existence and uniqueness of the limit differential equations, we show convergence to the global optimum and give a quantitative bound between the mean-field limit and the SHB dynamics of a finite-width network. Armed with this last bound, we are able to establish the dropout-stability and connectivity of SHB solutions.

Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer - Shaw, Thomas; Buri, Pascal; McCarthy, Michael; Miles, Evan; Pellicciotti, Francesca
GLACIER METEOROLOGICAL DATA SWISS ALPS -2022

The metabolism of the developing brain : How large neutral amino acids modulate perinatal neuronal excitability and survival - Knaus, Lisa
Within the human body, the brain exhibits the highest rate of energy consumption amongst all organs, with the majority of generated ATP being utilized to sustain neuronal activity. Therefore, the metabolism of the mature cerebral cortex is geared towards preserving metabolic homeostasis whilst generating significant amounts of energy. This requires a precise interplay between diverse metabolic pathways, spanning from a tissue-wide scale to the level of individual neurons. Disturbances to this delicate metabolic equilibrium, such as those resulting from maternal malnutrition or mutations affecting metabolic enzymes, often result in neuropathological variants of neurodevelopment. For instance, mutations in SLC7A5, a transporter of metabolically essential large neutral amino acids (LNAAs), have been associated with autism and microcephaly. However, despite recent progress in the field, the extent of metabolic restructuring that occurs within the developing brain and the corresponding alterations in nutrient demands during various critical periods remain largely unknown. To investigate this, we performed metabolomic profiling of the murine cerebral cortex to characterize the metabolic state of the forebrain at different developmental stages. We found that the developing cortex undergoes substantial metabolic reprogramming, with specific sets of metabolites displaying stage-specific changes. According to our observations, we determined a distinct temporal period in postnatal development during which the cortex displays heightened reliance on LNAAs. Hence, using a conditional knock-out mouse model, we deleted Slc7a5 in neural cells, allowing us to monitor the impact of a perturbed neuronal metabolic state across multiple developmental stages of corticogenesis. We found that manipulating the levels of essential LNAAs in cortical neurons in vivo affects one particular perinatal developmental period critical for cortical network refinement. Abnormally low intracellular LNAA levels result in cell-autonomous alterations in neuronal lipid metabolism, excitability, and survival during this particular time window. Although most of the effects of Slc7a5 deletion on neuronal physiology are transient, derailment of these processes during this brief but crucial window leads to long-term circuit dysfunction in mice. In conclusion, out data indicate that the cerebral cortex undergoes significant metabolic reorganization during development. This process involves the intricate integration of multiple metabolic pathways to ensure optimal neuronal function throughout different developmental stages. Our findings offer a paradigm for understanding how neurons synchronize the expression of nutrient-related genes with their activity to allow proper brain maturation. Further, our results demonstrate that disruptions in these precisely calibrated metabolic processes during critical periods of brain development may result in neuropathological outcomes in mice and in humans.

Large neutral amino acid levels tune perinatal neuronal excitability and survival - Knaus, Lisa; Basilico, Bernadette; Malzl, Daniel; Gerykova Bujalkova, Maria; Smogavec, Mateja; Schwarz, Lena A.; Gorkiewicz, Sarah; Amberg, Nicole; Pauler, Florian; Knittl-Frank, Christian; Tassinari, Marianna; Maulide, Nuno; et al. (Cell)
Little is known about the critical metabolic changes that neural cells have to undergo during development and how temporary shifts in this program can influence brain circuitries and behavior. Inspired by the discovery that mutations in SLC7A5, a transporter of metabolically essential large neutral amino acids (LNAAs), lead to autism, we employed metabolomic profiling to study the metabolic states of the cerebral cortex across different developmental stages. We found that the forebrain undergoes significant metabolic remodeling throughout development, with certain groups of metabolites showing stage-specific changes, but what are the consequences of perturbing this metabolic program? By manipulating Slc7a5 expression in neural cells, we found that the metabolism of LNAAs and lipids are interconnected in the cortex. Deletion of Slc7a5 in neurons affects the postnatal metabolic state, leading to a shift in lipid metabolism. Additionally, it causes stage- and cell-type-specific alterations in neuronal activity patterns, resulting in a long-term circuit dysfunction.
Keywords: General Biochemistry; Genetics and Molecular Biology

Radio frequency driven superconducting diode and parity conserving Cooper pair transport in a two-dimensional germanium hole gas - Valentini, Marco; Sagi, Oliver; Baghumyan, Levon; Gijsel, Thijs de; Jung, Jason; Calcaterra, Stefano; Ballabio, Andrea; Servin, Juan Aguilera; Aggarwal, Kushagra; Janik, Marian; Adletzberger, Thomas; Souto, Rubén Seoane; et al. (arXiv)
Superconductor/semiconductor hybrid devices have attracted increasing interest in the past years. Superconducting electronics aims to complement semiconductor technology, while hybrid architectures are at the forefront of new ideas such as topological superconductivity and protected qubits. In this work, we engineer the induced superconductivity in two-dimensional germanium hole gas by varying the distance between the quantum well and the aluminum. We demonstrate a hard superconducting gap and realize an electrically and flux tunable superconducting diode using a superconducting quantum interference device (SQUID). This allows to tune the current phase relation (CPR), to a regime where single Cooper pair tunneling is suppressed, creating a $ \sin \left( 2 φ \right)$ CPR. Shapiro experiments complement this interpretation and the microwave drive allows to create a diode with $ ≈ 100 %$ efficiency. The reported results open up the path towards monolithic integration of spin qubit devices, microwave resonators and (protected) superconducting qubits on a silicon technology compatible platform.
Keywords: Mesoscale and Nanoscale Physics

Image retrieval outperforms diffusion models on data augmentation - Burg, Max; Wenzel, Florian; Zietlow, Dominik; Horn, Max; Makansi, Osama; Locatello, Francesco; Russell, Chris (Journal of Machine Learning Research)
Many approaches have been proposed to use diffusion models to augment training datasets for downstream tasks, such as classification. However, diffusion models are themselves trained on large datasets, often with noisy annotations, and it remains an open question to which extent these models contribute to downstream classification performance. In particular, it remains unclear if they generalize enough to improve over directly using the additional data of their pre-training process for augmentation. We systematically evaluate a range of existing methods to generate images from diffusion models and study new extensions to assess their benefit for data augmentation. Personalizing diffusion models towards the target data outperforms simpler prompting strategies. However, using the pre-training data of the diffusion model alone, via a simple nearest-neighbor retrieval procedure, leads to even stronger downstream performance. Our study explores the potential of diffusion models in generating new training data, and surprisingly finds that these sophisticated models are not yet able to beat a simple and strong image retrieval baseline on simple downstream vision tasks.

Multi-view causal representation learning with partial observability - Yao, Dingling; Xu, Danru; Lachapelle, Sébastien; Magliacane, Sara; Taslakian, Perouz; Martius, Georg; Kügelgen, Julius von; Locatello, Francesco (arXiv)
We present a unified framework for studying the identifiability of representations learned from simultaneously observed views, such as different data modalities. We allow a partially observed setting in which each view constitutes a nonlinear mixture of a subset of underlying latent variables, which can be causally related. We prove that the information shared across all subsets of any number of views can be learned up to a smooth bijection using contrastive learning and a single encoder per view. We also provide graphical criteria indicating which latent variables can be identified through a simple set of rules, which we refer to as identifiability algebra. Our general framework and theoretical results unify and extend several previous works on multi-view nonlinear ICA, disentanglement, and causal representation learning. We experimentally validate our claims on numerical, image, and multi-modal data sets. Further, we demonstrate that the performance of prior methods is recovered in different special cases of our setup. Overall, we find that access to multiple partial views enables us to identify a more fine-grained representation, under the generally milder assumption of partial observability.

Latent space translation via semantic alignment - Maiorca, Valentino; Moschella, Luca; Norelli, Antonio; Fumero, Marco; Locatello, Francesco; Rodolà, Emanuele (arXiv)
While different neural models often exhibit latent spaces that are alike when exposed to semantically related data, this intrinsic similarity is not always immediately discernible. Towards a better understanding of this phenomenon, our work shows how representations learned from these neural modules can be translated between different pre-trained networks via simpler transformations than previously thought. An advantage of this approach is the ability to estimate these transformations using standard, well-understood algebraic procedures that have closed-form solutions. Our method directly estimates a transformation between two given latent spaces, thereby enabling effective stitching of encoders and decoders without additional training. We extensively validate the adaptability of this translation procedure in different experimental settings: across various trainings, domains, architectures (e.g., ResNet, CNN, ViT), and in multiple downstream tasks (classification, reconstruction). Notably, we show how it is possible to zero-shot stitch text encoders and vision decoders, or vice-versa, yielding surprisingly good classification performance in this multimodal setting.

Grounded object centric learning - Kori, Avinash; Locatello, Francesco; Ribeiro, Fabio De Sousa; Toni, Francesca; Glocker, Ben (arXiv)
The extraction of modular object-centric representations for downstream tasks is an emerging area of research. Learning grounded representations of objects that are guaranteed to be stable and invariant promises robust performance across different tasks and environments. Slot Attention (SA) learns object-centric representations by assigning objects to slots, but presupposes a single distribution from which all slots are randomly initialised. This results in an inability to learn specialized slots which bind to specific object types and remain invariant to identity-preserving changes in object appearance. To address this, we present Conditional Slot Attention (CoSA) using a novel concept of Grounded Slot Dictionary (GSD) inspired by vector quantization. Our proposed GSD comprises (i) canonical object-level property vectors and (ii) parametric Gaussian distributions, which define a prior over the slots. We demonstrate the benefits of our method in multiple downstream tasks such as scene generation, composition, and task adaptation, whilst remaining competitive with SA in popular object discovery benchmarks.

Sample complexity bounds for score-matching: Causal discovery and generative modeling - Zhu, Zhenyu; Locatello, Francesco; Cevher, Volkan (arXiv)
This paper provides statistical sample complexity bounds for score-matching and its applications in causal discovery. We demonstrate that accurate estimation of the score function is achievable by training a standard deep ReLU neural network using stochastic gradient descent. We establish bounds on the error rate of recovering causal relationships using the score-matching-based causal discovery method of Rolland et al. [2022], assuming a sufficiently good estimation of the score function. Finally, we analyze the upper bound of score-matching estimation within the score-based generative modeling, which has been applied for causal discovery but is also of independent interest within the domain of generative models.

Assumption violations in causal discovery and the robustness of score matching - Montagna, Francesco; Mastakouri, Atalanti A.; Eulig, Elias; Noceti, Nicoletta; Rosasco, Lorenzo; Janzing, Dominik; Aragam, Bryon; Locatello, Francesco (arXiv)
When domain knowledge is limited and experimentation is restricted by ethical, financial, or time constraints, practitioners turn to observational causal discovery methods to recover the causal structure, exploiting the statistical properties of their data. Because causal discovery without further assumptions is an ill-posed problem, each algorithm comes with its own set of usually untestable assumptions, some of which are hard to meet in real datasets. Motivated by these considerations, this paper extensively benchmarks the empirical performance of recent causal discovery methods on observational i.i.d. data generated under different background conditions, allowing for violations of the critical assumptions required by each selected approach. Our experimental findings show that score matching-based methods demonstrate surprising performance in the false positive and false negative rate of the inferred graph in these challenging scenarios, and we provide theoretical insights into their performance. This work is also the first effort to benchmark the stability of causal discovery algorithms with respect to the values of their hyperparameters. Finally, we hope this paper will set a new standard for the evaluation of causal discovery methods and can serve as an accessible entry point for practitioners interested in the field, highlighting the empirical implications of different algorithm choices.

Leveraging sparse and shared feature activations for disentangled representation learning - Fumero, Marco; Wenzel, Florian; Zancato, Luca; Achille, Alessandro; Rodolà, Emanuele; Soatto, Stefano; Schölkopf, Bernhard; Locatello, Francesco (arXiv)
Recovering the latent factors of variation of high dimensional data has so far focused on simple synthetic settings. Mostly building on unsupervised and weakly-supervised objectives, prior work missed out on the positive implications for representation learning on real world data. In this work, we propose to leverage knowledge extracted from a diversified set of supervised tasks to learn a common disentangled representation. Assuming each supervised task only depends on an unknown subset of the factors of variation, we disentangle the feature space of a supervised multi-task model, with features activating sparsely across different tasks and information being shared as appropriate. Importantly, we never directly observe the factors of variations but establish that access to multiple tasks is sufficient for identifiability under sufficiency and minimality assumptions. We validate our approach on six real world distribution shift benchmarks, and different data modalities (images, text), demonstrating how disentangled representations can be transferred to real settings.

Rotating features for object discovery - Löwe, Sindy; Lippe, Phillip; Locatello, Francesco; Welling, Max (arXiv)
The binding problem in human cognition, concerning how the brain represents and connects objects within a fixed network of neural connections, remains a subject of intense debate. Most machine learning efforts addressing this issue in an unsupervised setting have focused on slot-based methods, which may be limiting due to their discrete nature and difficulty to express uncertainty. Recently, the Complex AutoEncoder was proposed as an alternative that learns continuous and distributed object-centric representations. However, it is only applicable to simple toy data. In this paper, we present Rotating Features, a generalization of complex-valued features to higher dimensions, and a new evaluation procedure for extracting objects from distributed representations. Additionally, we show the applicability of our approach to pre-trained features. Together, these advancements enable us to scale distributed object-centric representations from simple toy to real-world data. We believe this work advances a new paradigm for addressing the binding problem in machine learning and has the potential to inspire further innovation in the field.

Object-centric multiple object tracking - Zhao, Zixu; Wang, Jiaze; Horn, Max; Ding, Yizhuo; He, Tong; Bai, Zechen; Zietlow, Dominik; Carl-Johann Simon-Gabriel, Carl-Johann Simon-Gabriel; Shuai, Bing; Tu, Zhuowen; Brox, Thomas; Schiele, Bernt; et al. (arXiv)
Unsupervised object-centric learning methods allow the partitioning of scenes into entities without additional localization information and are excellent candidates for reducing the annotation burden of multiple-object tracking (MOT) pipelines. Unfortunately, they lack two key properties: objects are often split into parts and are not consistently tracked over time. In fact, state-of-the-art models achieve pixel-level accuracy and temporal consistency by relying on supervised object detection with additional ID labels for the association through time. This paper proposes a video object-centric model for MOT. It consists of an index-merge module that adapts the object-centric slots into detection outputs and an object memory module that builds complete object prototypes to handle occlusions. Benefited from object-centric learning, we only require sparse detection labels (0%-6.25%) for object localization and feature binding. Relying on our self-supervised Expectation-Maximization-inspired loss for object association, our approach requires no ID labels. Our experiments significantly narrow the gap between the existing object-centric model and the fully supervised state-of-the-art and outperform several unsupervised trackers.

Shortcuts for causal discovery of nonlinear models by score matching - Montagna, Francesco; Noceti, Nicoletta; Rosasco, Lorenzo; Locatello, Francesco (arXiv)
The use of simulated data in the field of causal discovery is ubiquitous due to the scarcity of annotated real data. Recently, Reisach et al., 2021 highlighted the emergence of patterns in simulated linear data, which displays increasing marginal variance in the casual direction. As an ablation in their experiments, Montagna et al., 2023 found that similar patterns may emerge in nonlinear models for the variance of the score vector $\nabla \log p_{X}$, and introduced the ScoreSort algorithm. In this work, we formally define and characterize this score-sortability pattern of nonlinear additive noise models. We find that it defines a class of identifiable (bivariate) causal models overlapping with nonlinear additive noise models. We theoretically demonstrate the advantages of ScoreSort in terms of statistical efficiency compared to prior state-of-the-art score matching-based methods and empirically show the score-sortability of the most common synthetic benchmarks in the literature. Our findings remark (1) the lack of diversity in the data as an important limitation in the evaluation of nonlinear causal discovery approaches, (2) the importance of thoroughly testing different settings within a problem class, and (3) the importance of analyzing statistical properties in causal discovery, where research is often limited to defining identifiability conditions of the model.

Unsupervised open-vocabulary object localization in videos - Fan, Ke; Bai, Zechen; Xiao, Tianjun; Zietlow, Dominik; Horn, Max; Zhao, Zixu; Carl-Johann Simon-Gabriel, Carl-Johann Simon-Gabriel; Shou, Mike Zheng; Locatello, Francesco; Schiele, Bernt; Brox, Thomas; Zhang, Zheng; et al. (arXiv)
In this paper, we show that recent advances in video representation learning and pre-trained vision-language models allow for substantial improvements in self-supervised video object localization. We propose a method that first localizes objects in videos via a slot attention approach and then assigns text to the obtained slots. The latter is achieved by an unsupervised way to read localized semantic information from the pre-trained CLIP model. The resulting video object localization is entirely unsupervised apart from the implicit annotation contained in CLIP, and it is effectively the first unsupervised approach that yields good results on regular video benchmarks.

A sparsity principle for partially observable causal representation learning - Xu, Danru; Yao, Dingling; Lachapelle, Sebastien; Taslakian, Perouz; von Kügelgen, Julius; Locatello, Francesco; Magliacane, Sara (Causal Representation Learning Workshop at NeurIPS 2023)
Causal representation learning (CRL) aims at identifying high-level causal variables from low-level data, e.g. images. Current methods usually assume that all causal variables are captured in the high-dimensional observations. In this work, we focus on learning causal representations from data under partial observability, i.e., when some of the causal variables are not observed in the measurements, and the set of masked variables changes across the different samples. We introduce some initial theoretical results for identifying causal variables under partial observability by exploiting a sparsity regularizer, focusing in particular on the linear and piecewise linear mixing function case. We provide a theorem that allows us to identify the causal variables up to permutation and element-wise linear transformations in the linear case and a lemma that allows us to identify causal variables up to linear transformation in the piecewise case. Finally, we provide a conjecture that would allow us to identify the causal variables up to permutation and element-wise linear transformations also in the piecewise linear case. We test the theorem and conjecture on simulated data, showing the effectiveness of our method.

Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise - Fu, Teng; Liu, YuHao; Barbier, Jean; Mondelli, Marco; Liang, ShanSuo; Hou, TianQi (Proceedings of 2023 IEEE International Symposium on Information Theory)
We study the performance of a Bayesian statistician who estimates a rank-one signal corrupted by non-symmetric rotationally invariant noise with a generic distribution of singular values. As the signal-to-noise ratio and the noise structure are unknown, a Gaussian setup is incorrectly assumed. We derive the exact analytic expression for the error of the mismatched Bayes estimator and also provide the analysis of an approximate message passing (AMP) algorithm. The first result exploits the asymptotic behavior of spherical integrals for rectangular matrices and of low-rank matrix perturbations; the second one relies on the design and analysis of an auxiliary AMP. The numerical experiments show that there is a performance gap between the AMP and Bayes estimators, which is due to the incorrect estimation of the signal norm.

Dynamics and proliferation of turbulent stripes in plane-Poiseuille and plane-Couette flows - Marensi, Elena; Yalniz, Gökhan; Hof, Björn (Journal of Fluid Mechanics)
The first long-lived turbulent structures observable in planar shear flows take the form of localized stripes, inclined with respect to the mean flow direction. The dynamics of these stripes is central to transition, and recent studies proposed an analogy to directed percolation where the stripes’ proliferation is ultimately responsible for the turbulence becoming sustained. In the present study we focus on the internal stripe dynamics as well as on the eventual stripe expansion, and we compare the underlying mechanisms in pressure- and shear-driven planar flows, respectively, plane-Poiseuille and plane-Couette flow. Despite the similarities of the overall laminar–turbulence patterns, the stripe proliferation processes in the two cases are fundamentally different. Starting from the growth and sustenance of individual stripes, we find that in plane-Couette flow new streaks are created stochastically throughout the stripe whereas in plane-Poiseuille flow streak creation is deterministic and occurs locally at the downstream tip. Because of the up/downstream symmetry, Couette stripes, in contrast to Poiseuille stripes, have two weak and two strong laminar turbulent interfaces. These differences in symmetry as well as in internal growth give rise to two fundamentally different stripe splitting mechanisms. In plane-Poiseuille flow splitting is connected to the elongational growth of the original stripe, and it results from a break-off/shedding of the stripe's tail. In plane-Couette flow splitting follows from a broadening of the original stripe and a division along the stripe into two slimmer stripes.
Keywords: turbulence; transition to turbulence; patterns

To DISP or not? The far‐reaching reaction mechanisms underpinning Lithium‐air batteries - Jethwa, Rajesh B; Mondal, Soumyadip; Pant, Bhargavi; Freunberger, Stefan Alexander (Angewandte Chemie International Edition)
The short history of research on Li-O2 batteries has seen a remarkable number of mechanistic U-turns over the years. From the initial use of carbonate electrolytes, that were then found to be entirely unsuitable, to the belief that (su)peroxide was solely responsible for degradation, before the more reactive singlet oxygen was found to form, to the hypothesis that capacity depends on a competing surface/solution mechanism before a practically exclusive solution mechanism was identified. Herein, we argue for an ever-fresh look at the reported data without bias towards supposedly established explanations. We explain how the latest findings on rate and capacity limits, as well as the origin of side reactions, are connected via the disproportionation (DISP) step in the (dis)charge mechanism. Therefrom, directions emerge for the design of electrolytes and mediators on how to suppress side reactions and to enable high rate and high reversible capacity.
Keywords: General Chemistry; Catalysis

Lattice expansion enables interstitial doping to achieve a high average ZT in n‐type PbS - Liu, Zhengtao; Hong, Tao; Xu, Liqing; Wang, Sining; Gao, Xiang; Chang, Cheng; Ding, Xiangdong; Xiao, Yu; Zhao, Li‐Dong (Interdisciplinary Materials)
Lead sulfide (PbS) presents large potential in thermoelectric application due to its earth-abundant S element. However, its inferior average ZT (ZTave) value makes PbS less competitive with its analogs PbTe and PbSe. To promote its thermoelectric performance, this study implements strategies of continuous Se alloying and Cu interstitial doping to synergistically tune thermal and electrical transport properties in n-type PbS. First, the lattice parameter of 5.93 Å in PbS is linearly expanded to 6.03 Å in PbS0.5Se0.5 with increasing Se alloying content. This expanded lattice in Se-alloyed PbS not only intensifies phonon scattering but also facilitates the formation of Cu interstitials. Based on the PbS0.6Se0.4 content with the minimal lattice thermal conductivity, Cu interstitials are introduced to improve the electron density, thus boosting the peak power factor, from 3.88 μW cm−1 K−2 in PbS0.6Se0.4 to 20.58 μW cm−1 K−2 in PbS0.6Se0.4−1%Cu. Meanwhile, the lattice thermal conductivity in PbS0.6Se0.4−x%Cu (x = 0–2) is further suppressed due to the strong strain field caused by Cu interstitials. Finally, with the lowered thermal conductivity and high electrical transport properties, a peak ZT ~1.1 and ZTave ~0.82 can be achieved in PbS0.6Se0.4 − 1%Cu at 300–773K, which outperforms previously reported n-type PbS.

Parakeet: Practical key transparency for end-to-end eEncrypted messaging - Malvai, Harjasleen; Kokoris Kogias, Eleftherios; Sonnino, Alberto; Ghosh, Esha; Oztürk, Ercan; Lewi, Kevin; Lawlor, Sean (Proceedings of the 2023 Network and Distributed System Security Symposium)
Encryption alone is not enough for secure end-to end encrypted messaging: a server must also honestly serve public keys to users. Key transparency has been presented as an efficient solution for detecting (and hence deterring) a server that attempts to dishonestly serve keys. Key transparency involves two major components: (1) a username to public key mapping, stored and cryptographically committed to by the server, and, (2) an outof-band consistency protocol for serving short commitments to users. In the setting of real-world deployments and supporting production scale, new challenges must be considered for both of these components. We enumerate these challenges and provide solutions to address them. In particular, we design and implement a memory-optimized and privacy-preserving verifiable data structure for committing to the username to public key store. To make this implementation viable for production, we also integrate support for persistent and distributed storage. We also propose a future-facing solution, termed “compaction”, as a mechanism for mitigating practical issues that arise from dealing with infinitely growing server data structures. Finally, we implement a consensusless solution that achieves the minimum requirements for a service that consistently distributes commitments for a transparency application, providing a much more efficient protocol for distributing small and consistent commitments to users. This culminates in our production-grade implementation of a key transparency system (Parakeet) which we have open-sourced, along with a demonstration of feasibility through our benchmarks.

Phenotype control of partially specified boolean networks - Beneš, Nikola; Brim, Luboš; Pastva, Samuel; Šafránek, David; Šmijáková, Eva (21st International Conference on Computational Methods in Systems Biology)
Partially specified Boolean networks (PSBNs) represent a promising framework for the qualitative modelling of biological systems in which the logic of interactions is not completely known. Phenotype control aims to stabilise the network in states exhibiting specific traits. In this paper, we define the phenotype control problem in the context of asynchronous PSBNs and propose a novel semi-symbolic algorithm for solving this problem with permanent variable perturbations.

Universal Functionals in Density Functional Theory - Lewin, Mathieu; Lieb, Elliott H.; Seiringer, Robert (Density Functional Theory)
In this chapter we first review the Levy–Lieb functional, which gives the lowest kinetic and interaction energy that can be reached with all possible quantum states having a given density. We discuss two possible convex generalizations of this functional, corresponding to using mixed canonical and grand-canonical states, respectively. We present some recent works about the local density approximation, in which the functionals get replaced by purely local functionals constructed using the uniform electron gas energy per unit volume. We then review the known upper and lower bounds on the Levy–Lieb functionals. We start with the kinetic energy alone, then turn to the classical interaction alone, before we are able to put everything together. A later section is devoted to the Hohenberg–Kohn theorem and the role of many-body unique continuation in its proof.

The rigid core and flexible surface of amyloid fibrils probed by Magic‐Angle Spinning NMR of aromatic residues - Becker, Lea Marie; Berbon, Mélanie; Vallet, Alicia; Grelard, Axelle; Morvan, Estelle; Bardiaux, Benjamin; Lichtenecker, Roman; Ernst, Matthias; Loquet, Antoine; Schanda, Paul (Angewandte Chemie International Edition)
Aromatic side chains are important reporters of the plasticity of proteins, and often form important contacts in protein--protein interactions. By studying a pair of structurally homologous cross-β amyloid fibrils, HET-s and HELLF, with a specific isotope-labeling approach and magic-angle-spinning (MAS) NMR, we have characterized the dynamic behavior of Phe and Tyr aromatic rings to show that the hydrophobic amyloid core is rigid, without any sign of "breathing motions" over hundreds of milliseconds at least. Aromatic residues exposed at the fibril surface have a rigid ring axis but undergo ring flips, on a variety of time scales from ns to µs. Our approach provides direct insight into hydrophobic-core motions, enabling a better evaluation of the conformational heterogeneity generated from a NMR structural ensemble of such amyloid cross-β architecture.
Keywords: General Chemistry; Catalysis

Research data to: The rigid core and flexible surface of amyloid fibrils probed by magic-angle-spinning NMR spectroscopy of aromatic residues - Becker, Lea Marie; Schanda, Paul
Aromatic side chains are important reporters of the plasticity of proteins, and often form important contacts in protein–protein interactions. We studied aromatic residues in the two structurally homologous cross-β amyloid fibrils HET-s, and HELLF by employing a specific isotope-labeling approach and magic-angle-spinning NMR. The dynamic behavior of the aromatic residues Phe and Tyr indicates that the hydrophobic amyloid core is rigid, without any sign of "breathing motions" over hundreds of milliseconds at least. Aromatic residues exposed at the fibril surface have a rigid ring axis but undergo ring flips on a variety of time scales from nanoseconds to microseconds. Our approach provides direct insight into hydrophobic-core motions, enabling a better evaluation of the conformational heterogeneity generated from an NMR structural ensemble of such amyloid cross-β architecture.
Keywords: aromatic side chains; isotopic labeling; protein dynamics; ring flips; spin relaxation

Research data for the publication "Imaging brain tissue architecture across millimeter to nanometer scales" - Danzl, Johann G
Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here, we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease.

Chiral and nematic phases of flexible active filaments - Dunajova, Zuzana; Prats Mateu, Batirtze; Radler, Philipp; Lim, Keesiang; Brandis, Dörte; Velicky, Philipp; Danzl, Johann G; Wong, Richard W.; Elgeti, Jens; Hannezo, Edouard B; Loose, Martin
The emergence of large-scale order in self-organized systems relies on local interactions between individual components. During bacterial cell division, FtsZ -- a prokaryotic homologue of the eukaryotic protein tubulin -- polymerizes into treadmilling filaments that further organize into a cytoskeletal ring. In vitro, FtsZ filaments can form dynamic chiral assemblies. However, how the active and passive properties of individual filaments relate to these large-scale self-organized structures remains poorly understood. Here, we connect single filament properties with the mesoscopic scale by combining minimal active matter simulations and biochemical reconstitution experiments. We show that density and flexibility of active chiral filaments define their global order. At intermediate densities, curved, flexible filaments organize into chiral rings and polar bands. An effectively nematic organization dominates for high densities and for straight, mutant filaments with increased rigidity. Our predicted phase diagram captures these features quantitatively, demonstrating how the flexibility, density and chirality of active filaments affect their collective behaviour. Our findings shed light on the fundamental properties of active chiral matter and explain how treadmilling FtsZ filaments organize during bacterial cell division.

Chiral and nematic phases of flexible active filaments - Dunajova, Zuzana; Prats Mateu, Batirtze; Radler, Philipp; Lim, Keesiang; Brandis, Dörte; Velicky, Philipp; Danzl, Johann G; Wong, Richard W.; Elgeti, Jens; Hannezo, Edouard B; Loose, Martin (Nature Physics)
The emergence of large-scale order in self-organized systems relies on local interactions between individual components. During bacterial cell division, FtsZ—a prokaryotic homologue of the eukaryotic protein tubulin—polymerizes into treadmilling filaments that further organize into a cytoskeletal ring. In vitro, FtsZ filaments can form dynamic chiral assemblies. However, how the active and passive properties of individual filaments relate to these large-scale self-organized structures remains poorly understood. Here we connect single-filament properties with the mesoscopic scale by combining minimal active matter simulations and biochemical reconstitution experiments. We show that the density and flexibility of active chiral filaments define their global order. At intermediate densities, curved, flexible filaments organize into chiral rings and polar bands. An effectively nematic organization dominates for high densities and for straight, mutant filaments with increased rigidity. Our predicted phase diagram quantitatively captures these features, demonstrating how the flexibility, density and chirality of the active filaments affect their collective behaviour. Our findings shed light on the fundamental properties of active chiral matter and explain how treadmilling FtsZ filaments organize during bacterial cell division.

Imaging brain tissue architecture across millimeter to nanometer scales - Michalska, Julia M; Lyudchik, Julia; Velicky, Philipp; Korinkova, Hana; Watson, Jake; Cenameri, Alban; Sommer, Christoph M; Amberg, Nicole; Venturino, Alessandro; Roessler, Karl; Czech, Thomas; Höftberger, Romana; et al. (Nature Biotechnology)
Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease.

Spatiotemporal signaling during assembly of the bacterial divisome - Radler, Philipp
Cell division in Escherichia coli is performed by the divisome, a multi-protein complex composed of more than 30 proteins. The divisome spans from the cytoplasm through the inner membrane to the cell wall and the outer membrane. Divisome assembly is initiated by a cytoskeletal structure, the so-called Z-ring, which localizes at the center of the E. coli cell and determines the position of the future cell septum. The Z-ring is composed of the highly conserved bacterial tubulin homologue FtsZ, which forms treadmilling filaments. These filaments are recruited to the inner membrane by FtsA, a highly conserved bacterial actin homologue. FtsA interacts with other proteins in the periplasm and thus connects the cytoplasmic and periplasmic components of the divisome. A previous model postulated that FtsA regulates maturation of the divisome by switching from an oligomeric, inactive state to a monomeric and active state. This model was based mostly on in vivo studies, as a biochemical characterization of FtsA has been hampered by difficulties in purifying the protein. Here, we studied FtsA using an in vitro reconstitution approach and aimed to answer two questions: (i) How are dynamics from cytoplasmic, treadmilling FtsZ filaments coupled to proteins acting in the periplasmic space and (ii) How does FtsA regulate the maturation of the divisome? We found that the cytoplasmic peptides of the transmembrane proteins FtsN and FtsQ interact directly with FtsA and can follow the spatiotemporal signal of FtsA/Z filaments. When we investigated the underlying mechanism by imaging single molecules of FtsNcyto, we found the peptide to interact transiently with FtsA. An in depth analysis of the single molecule trajectories helped to postulate a model where PG synthases follow the dynamics of FtsZ by a diffusion and capture mechanism. Following up on these findings we were interested in how the self-interaction of FtsA changes when it encounters FtsNcyto and if we can confirm the proposed oligomer-monomer switch. For this, we compared the behavior of the previously identified, hyperactive mutant FtsA R286W with wildtype FtsA. The mutant outperforms WT in mirroring and transmitting the spatiotemporal signal of treadmilling FtsZ filaments. Surprisingly however, we found that this was not due to a difference in the self-interaction strength of the two variants, but a difference in their membrane residence time. Furthermore, in contrast to our expectations, upon binding of FtsNcyto the measured self-interaction of FtsA actually increased. We propose that FtsNcyto induces a rearrangement of the oligomeric architecture of FtsA. In further consequence this change leads to more persistent FtsZ filaments which results in a defined signalling zone, allowing formation of the mature divisome. The observed difference between FtsA WT and R286W is due to the vastly different membrane turnover of the proteins. R286W cycles 5-10x faster compared to WT which allows to sample FtsZ filaments at faster frequencies. These findings can explain the observed differences in toxicity for overexpression of FtsA WT and R286W and help to understand how FtsA regulates divisome maturation.
Keywords: Cell Division; Reconstitution; FtsZ; FtsA; Divisome; E.coli

Mesoscopic phenomena in hybrid semiconductor-superconductor nanodevices : From full-shell nanowires to two-dimensional hole gas in germanium - Valentini, Marco
Semiconductor-superconductor hybrid systems are the harbour of many intriguing mesoscopic phenomena. This material combination leads to spatial variations of the superconducting properties, which gives rise to Andreev bound states (ABSs). Some of these states might exhibit remarkable properties that render them highly desirable for topological quantum computing. The most prominent and hunted of such states are Majorana zero modes (MZMs), quasiparticles equals to their own quasiparticles that they follow non-abelian statistics. In this thesis, we first introduce the general framework of such hybrid systems and, then, we unveil a series of mesoscopic phenomena that we discovered. Firstly, we show tunneling spectroscopy experiments on full-shell nanowires (NWs) showing that unwanted quantum-dot states coupled to superconductors (Yu-Shiba-Rusinov states) can mimic MZMs signatures. Then, we introduce a novel protocol which allowed the integration of tunneling spectroscopy with Coulomb spectroscopy within the same device. Employing this approach on both full-shell NWs and partial-shell NWs, we demonstrated that longitudinally confined states reveal charge transport phenomenology similar to the one expected for MZMs. These findings shed light on the intricate interplay between superconductivity and quantum confinement, which brought us to explore another material platform, i.e. a two-dimensional Germanium hole gas. After developing a robust way to induce superconductivity in such system, we showed how to engineer the proximity effect and we revealed a superconducting hard gap. Finally, we created a superconducting radio frequency driven ideal diode and a generator of non-sinusoidal current-phase relations. Our results open the path for the exploration of protected superconducting qubits and more complex hybrid devices in planar Germanium, like Kitaev chains and hybrid qubit devices.

aggregation_data - Curk, Samo
This data repository underpins the paper, published in PNAS (doi pending) and bioarxiv (doi: https://doi.org/10.1101/2023.07.05.547777).

A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties - Majumdar, Rupak; Mallik, Kaushik; Rychlicki, Mateusz; Schmuck, Anne-Kathrin; Soudjani, Sadegh (35th International Conference on Computer Aided Verification)
We present a flexible and efficient toolchain to symbolically solve (standard) Rabin games, fair-adversarial Rabin games, and 2 1/2 license type-player Rabin games. To our best knowledge, our tools are the first ones to be able to solve these problems. Furthermore, using these flexible game solvers as a back-end, we implemented a tool for computing correct-by-construction controllers for stochastic dynamical systems under LTL specifications. Our implementations use the recent theoretical result that all of these games can be solved using the same symbolic fixpoint algorithm but utilizing different, domain specific calculations of the involved predecessor operators. The main feature of our toolchain is the utilization of two programming abstractions: one to separate the symbolic fixpoint computations from the predecessor calculations, and another one to allow the integration of different BDD libraries as back-ends. In particular, we employ a multi-threaded execution of the fixpoint algorithm by using the multi-threaded BDD library Sylvan, which leads to enormous computational savings.

Assessing memory in convection schemes using idealized tests - Hwong, Yi-Ling; Colin, M.; Aglas, Philipp; Muller, Caroline J; Sherwood, S. C. (Journal of Advances in Modeling Earth Systems)
Two assumptions commonly applied in convection schemes—the diagnostic and quasi-equilibrium assumptions—imply that convective activity (e.g., convective precipitation) is controlled only by the large-scale (macrostate) environment at the time. In contrast, numerical experiments indicate a “memory” or dependence of convection also on its own previous activity whereby subgrid-scale (microstate) structures boost but are also boosted by convection. In this study we investigated this memory by comparing single-column model behavior in two idealized tests previously executed by a cloud-resolving model (CRM). Conventional convection schemes that employ the diagnostic assumption fail to reproduce the CRM behavior. The memory-capable org and Laboratoire de Météorologie Dynamique Zoom cold pool schemes partially capture the behavior, but fail to fully exhibit the strong reinforcing feedbacks implied by the CRM. Analysis of this failure suggests that it is because the CRM supports a linear (or superlinear) dependence of the subgrid structure growth rate on the precipitation rate, while the org scheme assumes a sublinear dependence. Among varying versions of the org scheme, the growth rate of the org variable representing subgrid structure is strongly associated with memory strength. These results demonstrate the importance of parameterizing convective memory, and the ability of idealized tests to reveal shortcomings of convection schemes and constrain model structural assumptions.

Correct approximation of stationary distributions - Meggendorfer, Tobias (TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems)
A classical problem for Markov chains is determining their stationary (or steady-state) distribution. This problem has an equally classical solution based on eigenvectors and linear equation systems. However, this approach does not scale to large instances, and iterative solutions are desirable. It turns out that a naive approach, as used by current model checkers, may yield completely wrong results. We present a new approach, which utilizes recent advances in partial exploration and mean payoff computation to obtain a correct, converging approximation.

Data-assessing memory in convection schemes using idealized tests - Hwong, Yi-Ling; Colin, Maxime; Aglas, Philipp; Muller, Caroline J; Sherwood, Steven C.
This repository contains the data, scripts, WRF codes and files required to reproduce the results of the manuscript "Assessing Memory in Convection Schemes Using Idealized Tests" submitted to the Journal of Advances in Modeling Earth Systems (JAMES).

Artefact for: Correct Approximation of Stationary Distributions - Meggendorfer, Tobias
The software artefact to evaluate the approximation of stationary distributions implementation.

Lincheck: A practical framework for testing concurrent data structures on JVM - Koval, Nikita; Fedorov, Alexander; Sokolova, Maria; Tsitelov, Dmitry; Alistarh, Dan-Adrian (35th International Conference on Computer Aided Verification)
This paper presents Lincheck, a new practical and user-friendly framework for testing concurrent algorithms on the Java Virtual Machine (JVM). Lincheck provides a simple and declarative way to write concurrent tests: instead of describing how to perform the test, users specify what to test by declaring all the operations to examine; the framework automatically handles the rest. As a result, tests written with Lincheck are concise and easy to understand. The framework automatically generates a set of concurrent scenarios, examines them using stress-testing or bounded model checking, and verifies that the results of each invocation are correct. Notably, if an error is detected via model checking, Lincheck provides an easy-to-follow trace to reproduce it, significantly simplifying the bug investigation. To the best of our knowledge, Lincheck is the first production-ready tool on the JVM that offers such a simple way of writing concurrent tests, without requiring special skills or expertise. We successfully integrated Lincheck in the development process of several large projects, such as Kotlin Coroutines, and identified new bugs in popular concurrency libraries, such as a race in Java’s standard ConcurrentLinkedDeque and a liveliness bug in Java’s AbstractQueuedSynchronizer framework, which is used in most of the synchronization primitives. We believe that Lincheck can significantly improve the quality and productivity of concurrent algorithms research and development and become the state-of-the-art tool for checking their correctness.

Lincheck: A practical framework for testing concurrent data structures on JVM - Koval, Nikita; Fedorov, Alexander; Sokolova, Maria; Tsitelov, Dmitry; Alistarh, Dan-Adrian
Lincheck is a new practical and user-friendly framework for testing concurrent data structures on the Java Virtual Machine (JVM). It provides a simple and declarative way to write concurrent tests. Instead of describing how to perform the test, users specify what to test by declaring all the operations to examine; the framework automatically handles the rest. As a result, tests written with Lincheck are concise and easy to understand. The artifact presents a collection of Lincheck tests that discover new bugs in popular libraries and implementations from the concurrency literature -- they are listed in Table 1, Section 3. To evaluate the performance of Lincheck analysis, the collection of tests also includes those which check correct data structures and, thus, always succeed. Similarly to Table 2, Section 3, the experiments demonstrate the reasonable time to perform a test. Finally, Lincheck provides user-friendly output with an easy-to-follow trace to reproduce a detected error, significantly simplifying further investigation.

A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties - Majumdar, Rupak; Mallik, Kaushik; Rychlicki, Mateusz; Schmuck, Anne-Kathrin; Soudjani, Sadegh
This resource contains the artifacts for reproducing the experimental results presented in the paper titled "A Flexible Toolchain for Symbolic Rabin Games under Fair and Stochastic Uncertainties" that has been submitted in CAV 2023.

Compositional policy learning in stochastic control systems with formal guarantees - Zikelic, Dorde; Lechner, Mathias; Verma, Abhinav; Chatterjee, Krishnendu; Henzinger, Thomas A (37th Conference on Neural Information Processing Systems)
Reinforcement learning has shown promising results in learning neural network policies for complicated control tasks. However, the lack of formal guarantees about the behavior of such policies remains an impediment to their deployment. We propose a novel method for learning a composition of neural network policies in stochastic environments, along with a formal certificate which guarantees that a specification over the policy's behavior is satisfied with the desired probability. Unlike prior work on verifiable RL, our approach leverages the compositional nature of logical specifications provided in SpectRL, to learn over graphs of probabilistic reach-avoid specifications. The formal guarantees are provided by learning neural network policies together with reach-avoid supermartingales (RASM) for the graph’s sub-tasks and then composing them into a global policy. We also derive a tighter lower bound compared to previous work on the probability of reach-avoidance implied by a RASM, which is required to find a compositional policy with an acceptable probabilistic threshold for complex tasks with multiple edge policies. We implement a prototype of our approach and evaluate it on a Stochastic Nine Rooms environment.

A framework for grassroots research collaboration in machine learning and global health - Currin, Christopher; Asiedu , Mercy Nyamewaa; Fourie, Chris; Rosman, Benjamin; Turki, Houcemeddine; Lambebo Tonja, Atnafu; Abbott, Jade; Ajala, Marvellous; Adedayo, Sadiq Adewale; Emezue, Chris Chinenye; Machangara, Daphne (1st Workshop on Machine Learning & Global Health)
Traditional top-down approaches for global health have historically failed to achieve social progress (Hoffman et al., 2015; Hoffman & Røttingen, 2015). Recently, however, a more holistic, multi-level approach termed One Health (OH) (Osterhaus et al., 2020) is being adopted. Several sets of challenges have been identified for the implementation of OH (dos S. Ribeiro et al., 2019), including policy and funding, education and training, and multi-actor, multi-domain, and multi-level collaborations. These exist despite the increasing accessibility to knowledge and digital collaborative research tools through the internet. To address some of these challenges, we propose a general framework for grassroots community-based means of participatory research. Additionally, we present a specific roadmap to create a Machine Learning for Global Health community in Africa. The proposed framework aims to enable any small group of individuals with scarce resources to build and sustain an online community within approximately two years. We provide a discussion on the potential impact of the proposed framework for global health research collaborations.

Monitoring hyperproperties with prefix transducers - Chalupa, Marek; Henzinger, Thomas A (23nd International Conference on Runtime Verification)
Hyperproperties are properties that relate multiple execution traces. Previous work on monitoring hyperproperties focused on synchronous hyperproperties, usually specified in HyperLTL. When monitoring synchronous hyperproperties, all traces are assumed to proceed at the same speed. We introduce (multi-trace) prefix transducers and show how to use them for monitoring synchronous as well as, for the first time, asynchronous hyperproperties. Prefix transducers map multiple input traces into one or more output traces by incrementally matching prefixes of the input traces against expressions similar to regular expressions. The prefixes of different traces which are consumed by a single matching step of the monitor may have different lengths. The deterministic and executable nature of prefix transducers makes them more suitable as an intermediate formalism for runtime verification than logical specifications, which tend to be highly non-deterministic, especially in the case of asynchronous hyperproperties. We report on a set of experiments about monitoring asynchronous version of observational determinism.

QuePaxa: Escaping the tyranny of timeouts in consensus - Tennage, Pasindu; Basescu, Cristina; Kokoris Kogias, Eleftherios; Syta, Ewa; Jovanovic, Philipp; Estrada-Galinanes, Vero; Ford, Bryan (Proceedings of the 29th Symposium on Operating Systems Principles)
Leader-based consensus algorithms are fast and efficient under normal conditions, but lack robustness to adverse conditions due to their reliance on timeouts for liveness. We present QuePaxa, the first protocol offering state-of-the-art normal-case efficiency without depending on timeouts. QuePaxa uses a novel randomized asynchronous consensus core to tolerate adverse conditions such as denial-of-service (DoS) attacks, while a one-round-trip fast path preserves the normal-case efficiency of Multi-Paxos or Raft. By allowing simultaneous proposers without destructive interference, and using short hedging delays instead of conservative timeouts to limit redundant effort, QuePaxa permits rapid recovery after leader failure without risking costly view changes due to false timeouts. By treating leader choice and hedging delay as a multi-armed-bandit optimization, QuePaxa achieves responsiveness to prevalent conditions, and can choose the best leader even if the current one has not failed. Experiments with a prototype confirm that QuePaxa achieves normal-case LAN and WAN performance of 584k and 250k cmd/sec in throughput, respectively, comparable to Multi-Paxos. Under conditions such as DoS attacks, misconfigurations, or slow leaders that severely impact existing protocols, we find that QuePaxa remains live with median latency under 380ms in WAN experiments.

Unified treatment of contact, friction and shock-propagation in rigid body animation - Chen, Yi-Lu; Ly, Mickaël; Wojtan, Christopher J (Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation)

Monitoring hyperproperties with prefix transducers - Chalupa, Marek; Henzinger, Thomas A
This artifact aims to reproduce experiments from the paper Monitoring Hyperproperties With Prefix Transducers accepted at RV'23, and give further pointers to implementation of prefix transducers. It has two parts: a pre-compiled docker image and sources that one can use to compile (locally or in docker) the software and run the experiments.

Individual and social immunity against viral infections in ants - Franschitz, Anna
Social insects fight disease using their individual immune systems and the cooperative sanitary behaviors of colony members. These social defenses are well explored against externally-infecting pathogens, but little is known about defense strategies against internally-infecting pathogens, such as viruses. Viruses are ubiquitous and in the last decades it has become evident that also many ant species harbor viruses. We present one of the first studies addressing transmission dynamics and collective disease defenses against viruses in ants on a mechanistic level. I successfully established an experimental ant host – viral pathogen system as a model for the defense strategies used by social insects against internal pathogen infections, as outlined in the third chapter. In particular, we studied how garden ants (Lasius neglectus) defend themselves and their colonies against the generalist insect virus CrPV (cricket paralysis virus). We chose microinjections of virus directly into the ants’ hemolymph because it allowed us to use a defined exposure dose. Here we show that this is a good model system, as the virus is replicating and thus infecting the host. The ants mount a clear individual immune response against the viral infection, which is characterized by a specific siRNA pattern, namely siRNAs mapping against the viral genome with a peak of 21 and 22 bp long fragments. The onset of this immune response is consistent with the timeline of viral replication that starts already within two days post injection. The disease manifests in decreased survival over a course of two to three weeks. Regarding group living, we find that infected ants show a strong individual immune response, but that their course of disease is little affected by nestmate presence, as described in chapter four. Hence, we do not find social immunity in the context of viral infections in ants. Nestmates, however, can contract the virus. Using Drosophila S2R+ cells in culture, we showed that 94 % of the nestmates contract active virus within four days of social contact to an infected individual. Virus is transmitted in low doses, thus not causing disease transmission within the colony. While virus can be transmitted during short direct contacts, we also assume transmission from deceased ants and show that the nestmates’ immune system gets activated after contracting a low viral dose. We find considerable potential for indirect transmission via the nest space. Virus is shed to the nest, where it stays viable for one week and is also picked up by other ants. Apart from that, we want to underline the potential of ant poison as antiviral agent. We determined that ant poison successfully inactivates CrPV in vitro. However, we found no evidence for effective poison use to sanitize the nest space. On the other hand, local application of ant poison by oral poison uptake, which is part of the ants prophylactic behavioral repertoire, probably contributes to keeping the gut of each individual sanitized. We hypothesize that oral poison uptake might be the reason why we did not find viable virus in the trophallactic fluid. The fifth chapter encompasses preliminary data on potential social immunization. However, our experiments do not confirm an actual survival benefit for the nestmates upon pathogen challenge under the given experimental settings. Nevertheless, we do not want to rule out the possibility for nestmate immunization, but rather emphasize that considering different experimental timelines and viral doses would provide a multitude of options for follow-up experiments. In conclusion, we find that prophylactic individual behaviors, such as oral poison uptake, might play a role in preventing viral disease transmission. Compared to colony defense against external pathogens, internal pathogen infections require a stronger component of individual physiological immunity than behavioral social immunity, yet could still lead to collective protection.