@inproceedings{18155, abstract = {We study the classical problem of verifying programs with respect to formal specifications given in the linear temporal logic (LTL). We first present novel sound and complete witnesses for LTL verification over imperative programs. Our witnesses are applicable to both verification (proving) and refutation (finding bugs) settings. We then consider LTL formulas in which atomic propositions can be polynomial constraints and turn our focus to polynomial arithmetic programs, i.e. programs in which every assignment and guard consists only of polynomial expressions. For this setting, we provide an efficient algorithm to automatically synthesize such LTL witnesses. Our synthesis procedure is both sound and semi-complete. Finally, we present experimental results demonstrating the effectiveness of our approach and that it can handle programs which were beyond the reach of previous state-of-the-art tools.}, author = {Chatterjee, Krishnendu and Goharshady, Amir Kafshdar and Goharshady, Ehsan and Karrabi, Mehrdad and Zikelic, Dorde}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, isbn = {9783031711619}, issn = {1611-3349}, location = {Milan, Italy}, pages = {600--619}, publisher = {Springer Nature}, title = {{Sound and complete witnesses for template-based verification of LTL properties on polynomial programs}}, doi = {10.1007/978-3-031-71162-6_31}, volume = {14933}, year = {2024}, } @inproceedings{18156, abstract = {Privately counting distinct elements in a stream is a fundamental data analysis problem with many applications in machine learning. In the turnstile model, Jain et al. [NeurIPS2023] initiated the study of this problem parameterized by the maximum flippancy of any element, i.e., the number of times that the count of an element changes from 0 to above 0 or vice versa. They give an item-level (ε,δ)-differentially private algorithm whose additive error is tight with respect to that parameterization. In this work, we show that a very simple algorithm based on the sparse vector technique achieves a tight additive error for item-level (ε,δ)-differential privacy and item-level ε-differential privacy with regards to a different parameterization, namely the sum of all flippancies. Our second result is a bound which shows that for a large class of algorithms, including all existing differentially private algorithms for this problem, the lower bound from item-level differential privacy extends to event-level differential privacy. This partially answers an open question by Jain et al. [NeurIPS2023].}, author = {Henzinger, Monika H and Sricharan, A. R. and Steiner, Teresa Anna}, booktitle = {International Conference on Approximation Algorithms for Combinatorial Optimization Problems }, isbn = {9783959773485}, issn = {1868-8969}, location = {London, United Kingdom}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik}, title = {{Private counting of distinct elements in the turnstile model and extensions}}, doi = {10.4230/LIPIcs.APPROX/RANDOM.2024.40}, volume = {317}, year = {2024}, } @article{18158, abstract = {We study the geometry of Poisson point processes from the point of view of optimal transport and Ricci lower bounds. We construct a Riemannian structure on the space of point processes and the associated distance W that corresponds to the Benamou–Brenier variational formula. Our main tool is a non-local continuity equation formulated with the difference operator. The closure of the domain of the relative entropy is a complete geodesic space, when endowed with W. The geometry of this non-local infinite-dimensional space is analogous to that of spaces with positive Ricci curvature. Among others: (a) the Ornstein–Uhlenbeck semi-group is the gradient flow of the relative entropy; (b) the Poisson space has an entropic Ricci curvature bounded from below by 1; (c) W satisfies an HWI inequality.}, author = {Dello Schiavo, Lorenzo and Herry, Ronan and Suzuki, Kohei}, issn = {2270-518X}, journal = {Journal de l'Ecole Polytechnique - Mathematiques}, pages = {957--1010}, publisher = {Ecole Polytechnique}, title = {{Wasserstein geometry and Ricci curvature bounds for Poisson spaces}}, doi = {10.5802/jep.270}, volume = {11}, year = {2024}, } @inproceedings{18159, abstract = {Markov Decision Processes (MDPs) are a classical model for decision making in the presence of uncertainty. Often they are viewed as state transformers with planning objectives defned with respect to paths over MDP states. An increasingly popular alternative is to view them as distribution transformers, giving rise to a sequence of probability distributions over MDP states. For instance, reachability and safety properties in modeling robot swarms or chemical reaction networks are naturally defned in terms of probability distributions over states. Verifying such distributional properties is known to be hard and often beyond the reach of classical state-based verifcation techniques. In this work, we consider the problems of certifed policy (i.e. controller) verifcation and synthesis in MDPs under distributional reach-avoidance specifcations. By certifed we mean that, along with a policy, we also aim to synthesize a (checkable) certifcate ensuring that the MDP indeed satisfes the property. Thus, given the target set of distributions and an unsafe set of distributions over MDP states, our goal is to either synthesize a certifcate for a given policy or synthesize a policy along with a certifcate, proving that the target distribution can be reached while avoiding unsafe distributions. To solve this problem, we introduce the novel notion of distributional reach-avoid certifcates and present automated procedures for (1) synthesizing a certifcate for a given policy, and (2) synthesizing a policy together with the certifcate, both providing formal guarantees on certifcate correctness. Our experimental evaluation demonstrates the ability of our method to solve several non-trivial examples, including a multi-agent robot-swarm model, to synthesize certifed policies and to certify existing policies. }, author = {Akshay, S and Chatterjee, Krishnendu and Meggendorfer, Tobias and Zikelic, Dorde}, booktitle = {Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence}, isbn = {9781956792041}, issn = {1045-0823}, location = {Jeju, Korea}, pages = {3--12}, publisher = {International Joint Conferences on Artificial Intelligence}, title = {{Certified policy verification and synthesis for MDPs under distributional reach-avoidance properties}}, doi = {10.24963/ijcai.2024/1}, year = {2024}, } @inproceedings{18160, abstract = {Markov decision processes (MDPs) provide a standard framework for sequential decision making under uncertainty. However, MDPs do not take uncertainty in transition probabilities into account. Robust Markov decision processes (RMDPs) address this shortcoming of MDPs by assigning to each transition an uncertainty set rather than a single probability value. In this work, we consider polytopic RMDPs in which all uncertainty sets are polytopes and study the problem of solving long-run average reward polytopic RMDPs. We present a novel perspective on this problem and show that it can be reduced to solving long-run average reward turn-based stochastic games with finite state and action spaces. This reduction allows us to derive several important consequences that were hitherto not known to hold for polytopic RMDPs. First, we derive new computational complexity bounds for solving long-run average reward polytopic RMDPs, showing for the first time that the threshold decision problem for them is in NP∩CONP and that they admit a randomized algorithm with sub-exponential expected runtime. Second, we present Robust Polytopic Policy Iteration (RPPI), a novel policy iteration algorithm for solving long-run average reward polytopic RMDPs. Our experimental evaluation shows that RPPI is much more efficient in solving long-run average reward polytopic RMDPs compared to state-of-the-art methods based on value iteration. }, author = {Chatterjee, Krishnendu and Kafshdar Goharshadi, Ehsan and Karrabi, Mehrdad and Novotný, Petr and Zikelic, Dorde}, booktitle = {33rd International Joint Conference on Artificial Intelligence}, isbn = {9781956792041}, issn = {1045-0823}, location = {Jeju, South Korea}, pages = {6707--6715}, publisher = {International Joint Conferences on Artificial Intelligence}, title = {{Solving long-run average reward robust MDPs via stochastic games}}, doi = {10.24963/ijcai.2024/741}, year = {2024}, } @inbook{18167, abstract = {Holdase chaperones are essential in the mitochondrial membrane-protein biogenesis as they stabilize preproteins and keep them in an import-competent state as they travel through the aqueous cytosol and intermembrane space. The small TIM chaperones of the mitochondrial intermembrane space function within a fine balance of client promiscuity and high affinity binding, while being also able to release their client proteins without significant energy barrier to the downstream insertases/translocases. The tendency of the preproteins to aggregate and the dynamic nature of the preprotein—chaperone complexes makes the preparation of these complexes challenging. Here we present two optimized methods for complex formation of highly hydrophobic precursor proteins and chaperones: a pull-down approach and an in-vitro translation strategy. In the former, attaching the client protein to an affinity resin keeps the individual client protein copies apart from each other and decreases the client self-aggregation probability, thereby favouring complex formation. In the latter approach, a purified chaperone, added to the cell-free protein synthesis, captures the nascent precursor protein. The choice of method will depend on the desired client-chaperone complex amount, or the need for specific labeling scheme.}, author = {Guillerm, Undina and Sučec, Iva and Schanda, Paul}, booktitle = {Methods in Enzymology}, issn = {0076-6879}, pages = {391--422}, publisher = {Elsevier}, title = {{Generation of TIM chaperone substrate complexes}}, doi = {10.1016/bs.mie.2024.07.051}, volume = {707}, year = {2024}, } @article{18168, abstract = {Despite the considerable interest in the recombinant production of synthetic spider silk fibers that possess mechanical properties similar to those of native spider silks, such as the cost-effectiveness, tunability, and scalability realization, is still lacking. To address this long-standing challenge, we have constructed an artificial spider silk gene using Golden Gate assembly for the recombinant bacterial production of dragline-mimicking silk, incorporating all the essential components: the N-terminal domain, a 33-residue-long major-ampullate-spidroin-inspired segment repeated 16 times, and the C-terminal domain (N16C). This designed silk-like protein was successfully expressed in Escherichia coli, purified, and cast into films from formic acid. We produced uniformly 13C–15N-labeled N16C films and employed solid-state magic-angle spinning nuclear magnetic resonance (NMR) for characterization. Thus, we could demonstrate that our bioengineered silk-like protein self-assembles into a film where, when hydrated, the solvent-exposed layer of the rigid, β-nanocrystalline polyalanine core undergoes a transition to an α-helical structure, gaining mobility to the extent that it fully dissolves in water and transforms into a highly dynamic random coil. This hydration-induced behavior induces chain dynamics in the glycine-rich amorphous soft segments on the microsecond time scale, contributing to the elasticity of the solid material. Our findings not only reveal the presence of structurally and dynamically distinct segments within the film’s superstructure but also highlight the complexity of the self-organization responsible for the exceptional mechanical properties observed in proteins that mimic dragline silk.}, author = {Wu, Dongqing and Koscic, Anamaria and Schneider, Sonja and Dubini, Romeo C. A. and Rodriguez Camargo, Diana C. and Schneider, Sabine and Rovo, Petra}, issn = {1526-4602}, journal = {Biomacromolecules}, number = {3}, pages = {1759--1774}, publisher = {American Chemical Society}, title = {{Unveiling the dynamic self-assembly of a recombinant dragline-silk-mimicking protein}}, doi = {10.1021/acs.biomac.3c01239}, volume = {25}, year = {2024}, } @article{18171, abstract = {Defense against pathogens and parasites requires substantial investment of energy and resources on part of the host. This makes the host immune function dependent on availability and accessibility of resources. A resource deprived host is therefore expected to be more susceptible to infections, although empirical results do not always align with this prediction. Limiting host access to resources can additionally impact within-host pathogen numbers, either directly by altering the amount of resources available to the pathogens for proliferation or indirectly by altering the efficiency of the host immune system. We tested for the effects of host starvation (complete deprivation of resources) on susceptibility to bacterial pathogens, and within-host pathogen proliferation, in Drosophila melanogaster females. Our results show that starvation increases post-infection mortality of the host, but in a pathogen-specific manner. This increase in mortality is always accompanied by increased within-host pathogen proliferation. We therefore propose that starvation compromises host resistance to bacterial infections in Drosophila melanogaster females thereby increasing susceptibility to infections.}, author = {Basu, Aabeer and Singh, Aparajita and Sehgal, Suhaas and Madaan, Tanvi and Prasad, Nagaraj Guru}, issn = {1096-0805}, journal = {Journal of Invertebrate Pathology}, number = {11}, publisher = {Elsevier}, title = {{Starvation increases susceptibility to bacterial infection and promotes systemic pathogen proliferation in Drosophila melanogaster females}}, doi = {10.1016/j.jip.2024.108209}, volume = {207}, year = {2024}, } @article{18172, abstract = {Red Giant stars host solar-like oscillations which have mixed character, being sensitive to conditions both in the outer convection zone and deep within the interior. The properties of these modes are sensitive to both core rotation and magnetic fields. While asteroseismic studies of the former have been done on a large scale, studies of the latter are currently limited to tens of stars. We aim to produce the first large catalogue of both magnetic and rotational perturbations. We jointly constrain these parameters by devising an automated method for fitting the power spectra directly. We successfully apply the method to 302 low-luminosity red giants. We find a clear bimodality in core rotation rate. The primary peak is at δνrot = 0.32 μHz, and the secondary at δνrot = 0.47 μHz. Combining our results with literature values, we find that the percentage of stars rotating much more rapidly than the population average increases with evolutionary state. We measure magnetic splittings of 2σ significance in 23 stars. While the most extreme magnetic splitting values appear in stars with masses > 1.1M⊙, implying they formerly hosted a convective core, a small but statistically significant magnetic splitting is measured at lower masses. Asymmetry between the frequencies of a rotationally split multiplet has previously been used to diagnose the presence of a magnetic perturbation. We find that of the stars with a significant detection of magnetic perturbation, 43\% do not show strong asymmetry. We find no strong evidence of correlation between the rotation and magnetic parameters.}, author = {Hatt, Emily J. and Ong, J. M.Joel and Nielsen, Martin B. and Chaplin, William J. and Davies, Guy R. and Deheuvels, Sébastien and Ballot, Jérôme and Li, Gang and Bugnet, Lisa Annabelle}, issn = {1365-2966}, journal = {Monthly Notices of the Royal Astronomical Society}, number = {2}, pages = {1060--1076}, publisher = {Oxford University Press}, title = {{Asteroseismic signatures of core magnetism and rotation in hundreds of low-luminosity red giants}}, doi = {10.1093/mnras/stae2053}, volume = {534}, year = {2024}, } @article{18174, abstract = {We investigate the phase ordering (pattern formation) of systems of two-dimensional core–shell particles using Monte Carlo (MC) computer simulations and classical density functional theory (DFT). The particles interact via a pair potential having a hard core and a repulsive square shoulder. Our simulations show that on cooling, the liquid state structure becomes increasingly characterized by long wavelength density modulations and on further cooling forms a variety of other phases, including clustered, striped, and other patterned phases. In DFT, the hard core part of the potential is treated using either fundamental measure theory or a simple local density approximation, whereas the soft shoulder is treated using the random phase approximation. The different DFTs are benchmarked using large-scale grand-canonical-MC and Gibbs-ensemble-MC simulations, demonstrating their predictive capabilities and shortcomings. We find that having the liquid state static structure factor S(k) for wavenumber k is sufficient to identify the Fourier modes governing both the liquid and solid phases. This allows us to identify from easier-to-obtain liquid state data the wavenumbers relevant to the periodic phases and to predict roughly where in the phase diagram these patterned phases arise.}, author = {Wassermair, Michael and Kahl, Gerhard and Roth, Roland and Archer, Andrew J.}, issn = {1089-7690}, journal = {The Journal of chemical physics}, number = {12}, publisher = {AIP Publishing}, title = {{Fingerprints of ordered self-assembled structures in the liquid phase of a hard-core, square-shoulder system}}, doi = {10.1063/5.0226954}, volume = {161}, year = {2024}, } @inproceedings{18175, abstract = {Large-scale software repositories are a source of insights for software engineering. They offer an unmatched window into the software development process at scale. Their sheer number and size holds the promise of broadly applicable results. At the same time, that very size presents practical challenges for scaling tools and algorithms to millions of projects. A reasonable approach is to limit studies to representative samples of the population of interest. Broadly applicable conclusions can then be obtained by generalizing to the entire population. The contribution of this paper is a standardized experimental design methodology for choosing the inputs of studies working with large-scale repositories. We advocate for a methodology that clearly lays out what the population of interest is, how to sample it, and that fosters reproducibility. Along the way, we discourage researchers from using extrinsic attributes of projects such as stars, that measure some unclear notion of popularity.}, author = {Maj, Petr and Muroya Lei, Stefanie and Siek, Konrad and Di Grazia, Luca and Vitek, Jan}, booktitle = {38th European Conference on Object-Oriented Programming}, isbn = {9783959773416}, issn = {1868-8969}, location = {Vienna, Austria}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik}, title = {{The fault in our stars: Designing reproducible large-scale code analysis experiments}}, doi = {10.4230/LIPIcs.ECOOP.2024.27}, volume = {313}, year = {2024}, } @article{18176, abstract = {Introducing a class of SU(2) invariant quantum unitary circuits generating chiral transport, we examine the role of broken space-reflection and time-reversal symmetries on spin-transport properties. Upon adjusting parameters of local unitary gates, the dynamics can be either chaotic or integrable. The latter corresponds to a generalization of the space-time discretized (Trotterized) higher-spin quantum Heisenberg chain. We demonstrate that breaking of space-reflection symmetry results in a drift in the dynamical spin susceptibility. Remarkably, we find a universal drift velocity given by a simple formula, which, at zero average magnetization, depends only on the values of SU(2) Casimir invariants associated with local spins. In the integrable case, the drift velocity formula is confirmed analytically based on the exact solution of thermodynamic Bethe ansatz equations. Finally, by inspecting the large fluctuations of the time-integrated current between two halves of the system in stationary maximum-entropy states, we demonstrate violation of the Gallavotti-Cohen symmetry, implying that such states cannot be regarded as equilibrium ones. We show that the scaled cumulant generating function of the time-integrated current instead obeys a generalized fluctuation relation.}, author = {Zadnik, Lenart and Ljubotina, Marko and Krajnik, Žiga and Ilievski, Enej and Prosen, Tomaž}, issn = {2691-3399}, journal = {PRX Quantum}, number = {3}, publisher = {American Physical Society}, title = {{Quantum many-body spin ratchets}}, doi = {10.1103/PRXQuantum.5.030356}, volume = {5}, year = {2024}, } @inproceedings{18177, abstract = {Partially Specified Boolean Networks (PSBNs) represent a family of Boolean models resulting from possible interpretations of unknown update logics. Hybrid extension of CTL (HCTL) has the power to express complex dynamical phenomena, such as oscillations or stability. We present BNClassifier to classify Boolean Networks corresponding to a given PSBN according to criteria specified in HCTL. The implementation of the tool is fully symbolic (based on BDDs). The results are visualised using the machine-learning-based technology of decision trees.}, author = {Beneš, Nikola and Brim, Luboš and Huvar, Ondřej and Pastva, Samuel and Šafránek, David}, booktitle = {Computational Methods in Systems Biology}, isbn = {9783031716706}, issn = {1611-3349}, pages = {19--26}, publisher = {Springer Nature}, title = {{BNClassifier: Classifying boolean models by dynamic properties}}, doi = {10.1007/978-3-031-71671-3_2}, volume = {14971}, year = {2024}, } @article{18187, abstract = {Quasicrystals are ordered but not periodic, which makes them fascinating objects at the interface between order and disorder. Experiments with ultracold atoms zoom in on this interface by driving a quasicrystal and exploring its fractal properties.}, author = {Leonard, Julian}, issn = {1745-2481}, journal = {Nature Physics}, number = {3}, pages = {351--352}, publisher = {Springer Nature}, title = {{A kicked quasicrystal}}, doi = {10.1038/s41567-023-02357-0}, volume = {20}, year = {2024}, } @article{18188, abstract = {New generations of ultracold-atom experiments are continually raising the demand for efficient solutions to optimal control problems. Here, we apply Bayesian optimization to improve a state-preparation protocol recently implemented in an ultracold-atom system to realize a two-particle fractional quantum Hall state. Compared to manual ramp design, we demonstrate the superior performance of our optimization approach in a numerical simulation – resulting in a protocol that is 10x faster at the same fidelity, even when taking into account experimentally realistic levels of disorder in the system. We extensively analyze and discuss questions of robustness and the relationship between numerical simulation and experimental realization, and how to make the best use of the surrogate model trained during optimization. We find that numerical simulation can be expected to substantially reduce the number of experiments that need to be performed with even the most basic transfer learning techniques. The proposed protocol and workflow will pave the way toward the realization of more complex many-body quantum states in experiments.}, author = {Blatz, Tizian and Kwan, Joyce and Leonard, Julian and Bohrdt, Annabelle}, issn = {2521-327X}, journal = {Quantum}, publisher = {Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften}, title = {{Bayesian optimization for robust state preparation in quantum many-body systems}}, doi = {10.22331/q-2024-06-27-1388}, volume = {8}, year = {2024}, } @unpublished{18202, abstract = {We report on adiabatic state preparation in the one-dimensional quantum Ising model using ultracold bosons in a tilted optical lattice. We prepare many-body ground states of controllable system sizes and observe enhanced fluctuations around the transition between paramagnetic and antiferromagnetic states, marking the precursor of quantum critical behavior. Furthermore, we find evidence for superpositions of domain walls and study their effect on the many-body ground state by measuring the populations of each spin configuration across the transition. These results shed new light on the effect of boundary conditions in finite-size quantum systems.}, author = {Kim, Sooshin and Lukin, Alexander and Rispoli, Matthew and Tai, M. Eric and Kaufman, Adam M. and Segura, Perrin and Li, Yanfei and Kwan, Joyce and Leonard, Julian and Brice Bakkali-Hassani, Brice Bakkali-Hassani and Greiner, Markus}, booktitle = {arXiv}, title = {{Adiabatic state preparation in a quantum Ising spin chain}}, doi = {10.48550/arXiv.2404.07481}, year = {2024}, } @article{18203, abstract = {Protein Data Bank (PDB) files list the relative spatial location of atoms in a protein structure as the final output of the process of fitting and refining to experimentally determined electron density measurements. Where experimental evidence exists for multiple conformations, atoms are modelled in alternate locations. Programs reading PDB files commonly ignore these alternate conformations by default leaving users oblivious to the presence of alternate conformations in the structures they analyze. This has led to underappreciation of their prevalence, under characterisation of their features and limited the accessibility to this high-resolution data representing structural ensembles. We have trawled PDB files to extract structural features of residues with alternately located atoms. The output includes the distance between alternate conformations and identifies the location of these segments within the protein chain and in proximity of all other atoms within a defined radius. This dataset should be of use in efforts to predict multiple structures from a single sequence and support studies investigating protein flexibility and the association with protein function.}, author = {Rosenberg, Aviv A. and Marx, Ailie and Bronstein, Alexander}, issn = {2052-4463}, journal = {Scientific Data}, publisher = {Springer Nature}, title = {{A dataset of alternately located segments in protein crystal structures}}, doi = {10.1038/s41597-024-03595-4}, volume = {11}, year = {2024}, } @article{18204, abstract = {Non-linear dynamical systems describe numerous real-world phenomena, ranging from the weather, to financial markets and disease progression. Individual systems may share substantial common information, for example patients’ anatomy. Lately, deep-learning has emerged as a leading method for data-driven modeling of non-linear dynamical systems. Yet, despite recent breakthroughs, prior works largely ignored the existence of shared information between different systems. However, such cases are quite common, for example, in medicine: we may wish to have a patient-specific model for some disease, but the data collected from a single patient is usually too small to train a deep-learning model. Hence, we must properly utilize data gathered from other patients. Here, we explicitly consider such cases by jointly modeling multiple systems. We show that the current single-system models consistently fail when trying to learn simultaneously from multiple systems. We suggest a framework for jointly approximating the Koopman operators of multiple systems, while intrinsically exploiting common information. We demonstrate how we can adapt to a new system using order-of-magnitude less new data and show the superiority of our model over competing methods, in terms of both forecasting ability and statistical fidelity, across chaotic, cardiac, and climate systems.}, author = {Elul, Yonatan and Rozenberg, Eyal and Boyarski, Amit and Yaniv, Yael and Schuster, Assaf and Bronstein, Alexander}, issn = {2399-3650}, journal = {Communications Physics}, publisher = {Springer Nature}, title = {{Data-driven modeling of interrelated dynamical systems}}, doi = {10.1038/s42005-024-01626-5}, volume = {7}, year = {2024}, } @article{18205, abstract = {We explore numerically an unsupervised, physics-informed, deep learning-based reconstruction technique for time-resolved imaging by multiplexed ptychography. In our method, the untrained deep learning model replaces the iterative algorithm’s update step, yielding superior reconstructions of multiple dynamic object frames compared to conventional methodologies. More precisely, we demonstrate improvements in image quality and resolution, while reducing sensitivity to the number of recorded frames, the mutual orthogonality of different probe modes, overlap between neighboring probe beams and the cutoff frequency of the ptychographic microscope – properties that are generally of paramount importance for ptychographic reconstruction algorithms.}, author = {Wengrowicz, Omri and Bronstein, Alexander and Cohen, Oren}, issn = {1094-4087}, journal = {Optics Express}, number = {6}, pages = {8791--8803}, publisher = {Optica Publishing Group}, title = {{Unsupervised physics-informed deep learning-based reconstruction for time-resolved imaging by multiplexed ptychography}}, doi = {10.1364/oe.515445}, volume = {32}, year = {2024}, } @inproceedings{18206, abstract = {In the context of in vitro fertilization (IVF), selecting embryos for transfer is critical in determining pregnancy outcomes, with implantation as the essential first milestone for a successful pregnancy. This study introduces the Bonna algorithm, an advanced deep-learning framework engineered to predict embryo implantation probabilities. The algorithm employs a sophisticated integration of machine-learning techniques, utilizing MobileNetV2 for pixel and context embedding, a custom Pix2Pix model for precise segmentation, and a Vision Transformer for additional depth in embedding. MobileNetV2 was chosen for its robust feature extraction capabilities, focusing on textures and edges. The custom Pix2Pix model is adapted for precise segmentation of significant biological features such as the zona pellucida and blastocyst cavity. The Vision Transformer adds a global perspective, capturing complex patterns not apparent in local image segments. Tested on a dataset of images of human blastocysts collected from Ukraine, Israel, and Spain, the Bonna algorithm was rigorously validated through 10-fold cross-validation to ensure its robustness and reliability. It demonstrates superior performance with a mean area under the receiver operating characteristic curve (AUC) of 0.754, significantly outperforming existing models. The study not only advances predictive accuracy in embryo selection but also highlights the algorithm’s clinical applicability due to reliable confidence reporting.}, author = {Rave, Gilad and Fordham, Daniel E. and Bronstein, Alexander and Silver, David H.}, booktitle = {First International Conference on Artificial Intelligence in Healthcare}, isbn = {9783031672842}, issn = {1611-3349}, location = {Swansea, United Kingdom}, pages = {160--171}, publisher = {Springer Nature}, title = {{Enhancing predictive accuracy in embryo implantation: The Bonna algorithm and its clinical implications}}, doi = {10.1007/978-3-031-67285-9_12}, volume = {14976}, year = {2024}, }