cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Feedback-Dominated Accretion Flows
Creators: name: Gilbaum, Shmuel
name: Stone, Nicholas C.
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: We present new two-fluid models of accretion disks in active galactic nuclei (AGNs) that aim to address the long-standing problem of Toomre instability in AGN outskirts. In the spirit of earlier works by Sirko & Goodman and others, we argue that Toomre instability is eventually self-regulated via feedback produced by fragmentation and its aftermath. Unlike past semianalytic models, which (i) adopt local prescriptions to connect star formation rates to heat feedback, and (ii) assume that AGN disks self-regulate to a star-forming steady state (with Toomre parameter Q=1), we find that feedback processes are both temporally and spatially nonlocal. The accumulation of many stellar-mass black holes (BHs) embedded in AGN gas eventually displaces radiation, winds and supernovae from massive stars as the dominant feedback source. The nonlocality of feedback heating, in combination with the need for heat to efficiently mix throughout the gas, gives rise to steady-state AGN solutions that can have Q>>1 and no ongoing star formation. We find self-consistent steady-state solutions in much of the parameter space of AGN mass and accretion rate. These solutions harbor large populations of embedded compact objects that may grow in mass by factors of a few over the AGN lifetime, including into the lower and upper mass gaps. These feedback-dominated AGN disks differ significantly in structure from commonly used 1D disk models, which has broad implications for gravitational-wave-source formation inside AGNs.
description: 26 pages, 18 figures, 4 appendices. Comments are welcome
Exploring the Sgr-Milky-Way-disc interaction using high resolution N-body simulations
Creators: name: Bennett, Morgan
name: Bovy, Jo
name: Hunt, Jason A. S.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: The ongoing merger of the Sagittarius (Sgr) dwarf galaxy with the Milky Way is believed to strongly affect the dynamics of the Milky Way's disc. We present a suite of 13 $N$-body simulations, with 500 million to 1 billion particles, modelling the interaction between the Sagittarius dwarf galaxy (Sgr) and the Galactic disc. To quantify the perturbation to the disc's structure and dynamics in the simulation, we compute the number count asymmetry and the mean vertical velocity in a solar-neighbourhood-like volume. We find that overall the trends in the simulations match those seen in a simple one-dimensional model of the interaction. We explore the effects of changing the mass model of Sgr, the orbital kinematics of Sgr, and the mass of the Milky Way halo. We find that none of the simulations match the observations of the vertical perturbation using Gaia Data Release 2. In the simulation which is the most similar, we find that the final mass of Sgr far exceeds the observed mass of the Sgr remnant, the asymmetry wavelength is too large, and the shape of the asymmetry doesn't match past $z \approx 0.7$ kpc. We therefore conclude that our simulations support the conclusion that Sgr alone could not have caused the observed perturbation to the solar neighbourhood.
description: ApJ, in press
Scalable Image Coding for Humans and Machines
Creators: name: Choi, Hyomin
name: Bajic, Ivan V.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Image and Video Processing (eess.IV)
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: At present, and increasingly so in the future, much of the captured visual content will not be seen by humans. Instead, it will be used for automated machine vision analytics and may require occasional human viewing. Examples of such applications include traffic monitoring, visual surveillance, autonomous navigation, and industrial machine vision. To address such requirements, we develop an end-to-end learned image codec whose latent space is designed to support scalability from simpler to more complicated tasks. The simplest task is assigned to a subset of the latent space (the base layer), while more complicated tasks make use of additional subsets of the latent space, i.e., both the base and enhancement layer(s). For the experiments, we establish a 2-layer and a 3-layer model, each of which offers input reconstruction for human vision, plus machine vision task(s), and compare them with relevant benchmarks. The experiments show that our scalable codecs offer 37%-80% bitrate savings on machine vision tasks compared to best alternatives, while being comparable to state-of-the-art image codecs in terms of input reconstruction.
description: Submitted for peer review to IEEE Transactions
Next-to SV resummed Drell-Yan cross section beyond leading-logarithm
Creators: name: Ajjath, A. H.
name: Mukherjee, Pooja
name: Ravindran, V.
name: Sankar, Aparna
name: Tiwari, Surabhi
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences

description: We present the resummed predictions for inclusive cross section for Drell-Yan (DY) production up to next-to-next-to leading logarithmic ($\rm \overline{ NNLL}$) accuracy taking into account both soft virtual (SV) and next-to SV (NSV) threshold logarithms. We restrict ourselves to resummed contributions only from quark anti-quark ($q \bar q$) initiated channels. The resummation is performed in Mellin-$N$ space. We derive the $N$-dependent coefficients and the $N$-independent constants to desired accuracy for our study. The resummed results are matched through the minimal prescription procedure with the fixed order results. We find that the resummation, taking into account the NSV terms, appreciably increases the cross section while decreasing the sensitivity to renormalisation scale. \textcolor{black}{We observe that, at 13 TeV LHC energies, the SV+NSV resummation at $\rm \overline{ NLL} (\rm \overline{NNLL})$ gives about 8\% (2\%) corrections respectively to the NLO (NNLO) results for the considered $Q$ range: 150-3500 GeV}. In addition, the absence of quark gluon initiated contributions to NSV part in the resummed terms leaves large factorisation scale dependence indicating their importance at NSV level. We also study the numerical impact of $N$-independent constants and explore the ambiguity involved in exponetiating them. Finally we present our predictions for the neutral Drell-Yan process at various center of mass of energies.
description: 60 pages, 13 Tables and 15 Figures
Vold-Kalman Filter Order tracking of Axle Box Accelerations for Railway Stiffness Assessment
Creators: name: Hoelzl, Cyprien
name: Dertimanis, Vasilis
name: Ancu, Lucian
name: Kollros, Aurelia
name: Chatzi, Eleni
Publisher: name: ETH Zurich
Year: 2022
Subjects: Vold-Kalman order tracking filter
Axle box accelerations
Dynamic track stiffness
Vehicle-track dynamics
Railway asset management
Condition monitoring

description: Intelligent data-driven monitoring procedures hold enormous potential for ensuring safe operation and optimal management of the railway infrastructure in the face of increasing demands on cost and efficiency. Numerous studies have shown that the track stiffness is one of the main parameters influencing the evolution of degradation that drives maintenance processes. As such, the measurement of track stiffness is fundamental for characterizing the performance of the track in terms of deterioration rate and noise emission. This can be achieved via low-cost On Board Monitoring (OBM) sensing systems (i.e., axle-box accelerometers) that are mounted on in-service trains and enable frequent, real-time monitoring of the railway infrastructure network. Acceleration-based stiffness indicators have seldom been considered in monitoring applications. In this work, the use of a Vold-Kalman filter is proposed, for decomposing the signal into periodic wheel and track related excitation--response pairs functions. We demonstrate that these components are in turn correlated to operational conditions, such as wheel out-of-roundness and rail type. We further illustrate the relationship between the track stiffness, the measured wheel-rail forces and the sleeper passage amplitude, which can ultimately serve as an indicator for predictive track maintenance and prediction of track durability.
description: arXiv
A globally consistent approach for basic service disruptions after natural disasters
Creators: name: Mühlhofer, Evelyn
name: Koks, Elco
name: Sansavini, Giovanni
name: Bresch, David N.
Publisher: name: ETH Zurich
Year: 2022

description: Critical infrastructures (CIs) such as powerlines, roads, telecommunication and healthcare systems across the globe are more exposed than ever to the risks of extreme weather events in a changing climate. Damages to CIs often lead to failure cascades with catastrophic impacts in terms of people being cut off from basic service access. Yet, there is a gap between traditional CI failure models, operating often at local scales, with detailed proprietary, non-transferrable data, and the large scales and global occurrences of natural disasters.

We demonstrate a way to bridge those incompatibilities by linking a globally consistent and spatially explicit natural hazard risk modelling platform (CLIMADA) and a CI failure cascade model. The latter is built on publicly available infrastructure, end-user and supply data, and makes use of consistent and transferrable dependency heuristics between CIs to represent infrastructure systems at national scales for any place interest. Impacts are then spatially mapped in terms of people experiencing disruptions to basic service access.

With this approach, we aim to showcase how the interplay of available data and well-informed heuristics can allow large-scale impact models to produce consistent hot-spot analyses and rapid emergency assessments, which may then provide a starting point for more detailed, local studies.
description: EGUsphere
A Note on $h^{2,1}$ of Divisors of CY Fourfolds I
Creators: name: Kim, Manki
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: Algebraic Geometry (math.AG)
subject: FOS: Physical sciences
subject: FOS: Mathematics

description: In this note, we prove combinatorial formulas for $h^{2,1}$ of prime toric divisors in an arbitrary toric hypersurface Calabi-Yau fourfold $Y_4.$ We show that it is possible to find a toric hypersurface Calabi-Yau in which there are more than $h^{1,1}(Y_4)$ non-perturbative superpotential terms with trivial intermediate Jacobian. Hodge numbers of divisors in toric CICYs are the subjects of the part two.
description: v2. References added
KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics
Creators: name: Revach, Guy
name: Shlezinger, Nir
name: Ni, Xiaoyong
name: Escoriza, Adria Lopez
name: van Sloun, Ruud J. G.
name: Eldar, Yonina C.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Signal Processing (eess.SP)
subject: Machine Learning (cs.LG)
subject: Machine Learning (stat.ML)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences

description: State estimation of dynamical systems in real-time is a fundamental task in signal processing. For systems that are well-represented by a fully known linear Gaussian state space (SS) model, the celebrated Kalman filter (KF) is a low complexity optimal solution. However, both linearity of the underlying SS model and accurate knowledge of it are often not encountered in practice. Here, we present KalmanNet, a real-time state estimator that learns from data to carry out Kalman filtering under non-linear dynamics with partial information. By incorporating the structural SS model with a dedicated recurrent neural network module in the flow of the KF, we retain data efficiency and interpretability of the classic algorithm while implicitly learning complex dynamics from data. We demonstrate numerically that KalmanNet overcomes non-linearities and model mismatch, outperforming classic filtering methods operating with both mismatched and accurate domain knowledge.
description: Accepted for publication in IEEE Transactions on Signal Processing - TSP
Предикторы гипоксически-ишемической энцефалопатии у новорожденных детей
Creators: name: Сергеева В.А.
name: Александрович Ю.С.
name: Петренкова Н.С.
Publisher: name: Вестник анестезиологии и реаниматологии
Year: 2017
Subjects: НОВОРОЖДЕННЫЕ
ЦИТОКИНЫ
ИНТЕРЛЕЙКИН-8
ИНТЕРЛЕЙКИН-10
СИСТЕМНЫЙ ФЕТАЛЬНЫЙ ВОСПАЛИТЕЛЬНЫЙ ОТВЕТ
ГИПОКСИЧЕСКИ-ИШЕМИЧЕСКАЯ ЭНЦЕФАЛОПАТИЯ
NEWBORNS
CYTOKINES
INTERLEUKIN-8
INTERLEUKIN-10
SYSTEM FETAL INFLAMMATORY RESPONSE
HYPOXIC ISCHEMIC ENCEPHALOPATHY

description: Цель исследования: изучение содержания маркеров системного фетального воспалительного ответа и эндотелиальной дисфункции в пуповинной крови у доношенных новорожденных, перенесших интранатальную асфиксию. Материал и методы. В 1-ю группу включено 12 доношенных новорожденных, которые родились с оценкой по шкале Апгар на 1-й мин 5 баллов и менее, во 2-ю группу 12 детей с физиологическим течением раннего неонатального периода. Изучали содержание в пуповинной крови интерлейкина-8 (ИЛ-8), интерлейкина-10 (ИЛ-10), С-реактивного белка (СРБ), растворимой формы Е-селектина (sЕ-селектин) и молекулы межклеточной адгезии-1 (sICAM-1). Результаты. У матерей детей 1-й группы чаще, чем во 2-й группе, выявляли воспалительные изменения в плаценте (60 и 8%, p = 0,018) и наблюдали более высокий уровень СРБ (961 [520; 1 096] и 43 [33; 71] нг/мл, p < 0,06), ИЛ-8 (153 [53; 323] и 28 [22; 42] пг/мл, p = 0,001), ИЛ-10 (12,3 [7,5; 43,5] и 2,5 [1,9; 5,0] пг/мл, p < 0,001) и sICAM-1 (40 [33; 45] и 18 [17; 21] нг/мл, p < 0,06), который коррелировал с наличием воспалительных изменений в плаценте (r = 0,812, p = 0,028; r = 0,534, p < 0,001; r = 0,492, p = 0,034; r = 0,688, p = 0,089 для СРБ, ИЛ-8, ИЛ-10 и sICAM-1 соответственно). Кроме того, установлено, что оценка по шкале Апгар имела отрицательную корреляционную связь с уровнем ИЛ-8 (r = -0,453, p = 0,04 и r = -0,565, p = 0,008 на 1-й и 5-й мин соответственно); ИЛ-10 (r = -0,711, p < 0,001 и r = -0,727, p < 0,001 на 1-й и 5-й мин соответственно) и sICAM-1 (r = -0,796, p = 0,013 и r = -0,904, p = 0,002 на 1-й и 5-й мин соответственно). Выводы. Системный фетальный воспалительный ответ и сопряженная с ним эндотелиальная дисфункция могут создавать предпосылки для развития гипоксически-ишемической энцефалопатии и снижать эффективность проводимых при ней лечебных мероприятий.
A method to remove lower order contributions in multi-particle femtoscopic correlation functions
Creators: name: Del Grande, Raffaele
name: Šerkšnytė, Laura
name: Fabbietti, Laura
name: Sarti, Valentina Mantovani
name: Mihaylov, Dimitar
Publisher: name: arXiv
Year: 2021
Subjects: subject: Nuclear Theory (nucl-th)
subject: High Energy Physics - Experiment (hep-ex)
subject: High Energy Physics - Phenomenology (hep-ph)
subject: Nuclear Experiment (nucl-ex)
subject: FOS: Physical sciences

description: In recent years the femtoscopy technique has been used by the ALICE Collaboration in small colliding systems at the LHC to investigate the strong-interaction of hadron pairs in the low-energy regime. The extension of this technique to the study of many-body correlations aims to deliver in the next years the first experimental measurements of the genuine many-hadron interactions, provided that the contributions due to the lower order terms are properly accounted for. In this paper we present a method that allows to determine the residual lower order contributions to the three-body correlation functions, based on the cumulant decomposition approach and on kinematic transformations. A procedure to simulate genuine three-body correlations in three-baryon correlation functions is also developed. A qualitative study of the produced correlation signal is performed by varying the strength of the adopted three-body interaction model and comparisons with the expectations for the lower order contributions to the correlation function are shown. The method can be also applied to evaluate the combinatorial background in the two-body correlation functions, providing an improved statistical accuracy with respect to the standard techniques. The example of the contribution by the pK$^+$K$^-$ channel to the recently measured p$ϕ$ correlation is discussed.
Complexity and efficiency of minimum entropy production probability paths from quantum dynamical evolutions
Creators: name: Cafaro, Carlo
name: Ray, Shannon
name: Alsing, Paul M.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: We present an information geometric characterization of quantum driving schemes specified by su(2;C) time-dependent Hamiltonians in terms of both complexity and efficiency concepts. By employing a minimum action principle, the optimum path connecting initial and final states on the manifold in finite-time is the geodesic path between the two states. In particular, the total entropy production that occurs during the transfer is minimized along these optimum paths. For each optimum path that emerges from the given quantum driving scheme, we evaluate the so-called information geometric complexity (IGC) and our newly proposed measure of entropic efficiency constructed in terms of the constant entropy production rates that specify the entropy minimizing paths being compared. From our analytical estimates of complexity and efficiency, we provide a relative ranking among the driving schemes being investigated. Finally, we conclude by commenting on the fact that an higher entropic speed in quantum transfer processes seems to necessarily go along with a lower entropic efficiency together with a higher information geometric complexity.
description: 21 pages, 2 figures, 1 table
A Data-Directed Paradigm for BSM searches: the bump-hunting example
Creators: name: Volkovich, Sergey
name: Halevy, Federico De Vito
name: Bressler, Shikma
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Experiment (hep-ex)
subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: We propose a data-directed paradigm (DDP) to search for new physics. Focusing on the data without using simulations, exclusive selections which exhibit significant deviations from known properties of the standard model can be identified efficiently and marked for further study. Different properties can be exploited with the DDP. Here, the paradigm is demonstrated by combining the promising potential of neural networks (NN) with the common bump-hunting approach. Using the NN, the resource-consuming tasks of background and systematic uncertainty estimation are avoided, allowing rapid testing of many final states with only a minor degradation in the sensitivity to bumps relative to standard analysis methods.
title: 01_1379
Creators: name: Wesley Baldwin, John
name: Baldwin, John W.
Publisher: name: NAKALA - https://nakala.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2018
Subjects: subject: LaMOP
subject: Laboratoire de Médiévistique Occidentale de Paris

description: L'ensemble de ces notes ont été crée par John Baldwin lors d'une de ses premières périodes de résidence à Paris. Ces documents comprennent tous les magistri qu’il avait pu rencontrer dans ses sources. Aux XIIème et XIIIème siècles, les universités n'existant pas encore, le titre de magister s'il évoque certainement une compétence n'est pas rattaché de façon systématique au passage par les écoles. De surcroît, les magistris sont le plus souvent désignés par leur seul prénom. La lecture de ces données est donc difficile et suppose un long travail pour tenter d'identifier un individu auquel on pourrait rattacher plusieurs mentions. John Baldwin avait donc renoncé à utiliser ces données pour donner un prolongement à sa magnifique étude sur les gradués d'université et leur emploi par les Capétiens et les Plantagenêts. Néanmoins, il a conservé ces données et elles sont potentiellement très utile dans le cadre de Studium, comme le sont toutes les mentions dans les volumes des Fasti Ecclesiae Gallicanae de chanoines portant ce titre de magister sans autres précisions. L'ampleur des dépouillements rend ces données très utiles et nous devons une grande reconnaissance à John Baldwin pour avoir pris la peine de faire photocopier ses fiches et de nous les avoir transmises amicalement.
Les données ainsi que les images des fiches sont accessibles sur le site Internet à l'adresse suivante : http://studium-baldwin.lamop.fr/.
Les transcriptions des fiches ont été effectuées par des étudiants de Paris 1 Panthéon - Sorbonne mais elles n'ont pas été corrigées par la suite.
description: Relation: https://lamop.hypotheses.org/
title: 01_1355
Creators: name: Wesley Baldwin, John
name: Baldwin, John W.
Publisher: name: NAKALA - https://nakala.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2018
Subjects: subject: LaMOP
subject: Laboratoire de Médiévistique Occidentale de Paris

description: L'ensemble de ces notes ont été crée par John Baldwin lors d'une de ses premières périodes de résidence à Paris. Ces documents comprennent tous les magistri qu’il avait pu rencontrer dans ses sources. Aux XIIème et XIIIème siècles, les universités n'existant pas encore, le titre de magister s'il évoque certainement une compétence n'est pas rattaché de façon systématique au passage par les écoles. De surcroît, les magistris sont le plus souvent désignés par leur seul prénom. La lecture de ces données est donc difficile et suppose un long travail pour tenter d'identifier un individu auquel on pourrait rattacher plusieurs mentions. John Baldwin avait donc renoncé à utiliser ces données pour donner un prolongement à sa magnifique étude sur les gradués d'université et leur emploi par les Capétiens et les Plantagenêts. Néanmoins, il a conservé ces données et elles sont potentiellement très utile dans le cadre de Studium, comme le sont toutes les mentions dans les volumes des Fasti Ecclesiae Gallicanae de chanoines portant ce titre de magister sans autres précisions. L'ampleur des dépouillements rend ces données très utiles et nous devons une grande reconnaissance à John Baldwin pour avoir pris la peine de faire photocopier ses fiches et de nous les avoir transmises amicalement.
Les données ainsi que les images des fiches sont accessibles sur le site Internet à l'adresse suivante : http://studium-baldwin.lamop.fr/.
Les transcriptions des fiches ont été effectuées par des étudiants de Paris 1 Panthéon - Sorbonne mais elles n'ont pas été corrigées par la suite.
description: Relation: https://lamop.hypotheses.org/
Digital Transformations in Public International Law
Creators: name: Golia, Angelo Jr.
name: Kettemann, Matthias C.
name: Kunz, Raffaela
Publisher: name: ETH Zurich
Year: 2022

description: Beiträge zum ausländischen öffentlichen Recht und Völkerrecht, 317
description: ISSN:0172-4770
description: ISSN:0172-4770
description: ISBN:978-3-7560-0275-7
description: ISBN:978-3-7489-3163-8
Geometric Effects Position Renal Vesicles During Kidney Development
Creators: name: Mederacke, Malte
name: Conrad, Lisa
name: Vetter, Roman
name: Iber, Dagmar
Publisher: name: ETH Zurich
Year: 2022
Subjects: Renal vesicle
Nephron
Ureteric bud
Kidney development
Curvature
Cell aggregation
Reaction-diffusion model

description: During kidney development, reciprocal signalling between the epithelium and the mesenchyme coordinates nephrogenesis with branching morphogenesis of the collecting ducts. The mechanism that positions the renal vesicles, and thus the nephrons, relative to the branching ureteric buds has remained elusive. By combining computational modelling and experiments, we show that geometric effects concentrate the key regulator, WNT9b, at the junctions between parent and daughter branches where renal vesicles emerge, despite its uniform expression in the ureteric epithelium. This curvature effect might be a general paradigm to create non-uniform signalling in development.
description: bioRxiv
Aligning Distant Sequences to Graphs using Long Seed Sketches
Creators: name: Joudaki, Amir
name: Meterez, Alexandru
name: Mustafa, Harun
name: Koerkamp, Ragnar Groot
name: Kahles, André
name: Rätsch, Gunnar
Publisher: name: ETH Zurich
Year: 2022
Subjects: sequence-to-graph alignment
tensor sketching
tensor embedding

description: Sequence-to-graph alignment is an important step in applications such as variant genotyping, read error correction and genome assembly. When a query sequence requires a substantial number of edits to align, approximate alignment tools that follow the seed-and-extend approach require shorter seeds to get any matches. However, in large graphs with high variation, relying on a shorter seed length leads to an exponential increase in spurious matches. We propose a novel seeding approach relying on long inexact matches instead of short exact matches. We demonstrate experimentally that our approach achieves a better time-accuracy trade-off in settings with up to a 25% mutation rate.We achieve this by sketching a subset of graph nodes and storing them in a K-nearest neighbor index. While sketches are more robust to indels, finding the nearest neighbor of a sketch in a high-dimensional space is more computationally challenging than finding exact seeds. We demonstrate that if we store sketch vectors in a K-nearest neighbor index, we can circumvent the curse of dimensionality. Our long sketch-based seed scheme contrasts existing approaches and highlights the important role that tensor sketching can play in bioinformatics applications. Our proposed seeding method and implementation have several advantages: i) We empirically show that our method is efficient and scales to graphs with 1 billion nodes, with time and memory requirements for preprocessing growing linearly with graph size and query time growing quasi-logarithmically with query length. ii) For queries with an edit distance of 25% relative to their length, on the 1 billion node graph, longer sketch-based seeds yield a 4 increase in recall compared to exact seeds. iii) Conceptually, our seeder can be incorporated into other aligners, proposing a novel direction for sequence-to-graph alignment.The implementation is available at: https://github.com/ratschlab/tensor-sketch-alignment.Competing Interest StatementThe authors have declared no competing interest.
description: bioRxiv
First results on QCD+QED with C* boundary conditions
Creators: name: Bushnaq, Lucius
name: Campos, Isabel
name: Catillo, Marco
name: Cotellucci, Alessandro
name: Dale, Madeleine
name: Fritzsch, Patrick
name: Lücke, Jens
name: Marinkovic, Marina
name: Patella, Agostino
name: Tantalo, Nazario
Publisher: name: ETH Zurich
Year: 2022

description: Accounting for isospin-breaking corrections is critical for achieving subpercent precision in lattice computations of hadronic observables. A way to include QED and strong-isospin-breaking corrections in lattice QCD calculations is to impose C⋆ boundary conditions in space. Here, we demonstrate the computation of a selection of meson and baryon masses on two QCD and five QCD+QED gauge ensembles in this setup, which preserves locality, gauge and translational invariance all through the calculation. The generation of the gauge ensembles is performed for two volumes, and three different values of the renormalized fine-structure constant at the U-symmetric point, corresponding to the SU(3)-symmetric QCD in the two ensembles where the electromagnetic coupling is turned off. We also present our tuning strategy and, to the extent possible, a cost analysis of the simulations with C⋆ boundary conditions.
description: arXiv
Primate pre-arcuate cortex actively maintains persistent representations of saccades from plans to outcomes
Creators: name: Calangiu, Ioana
name: Kollmorgen, Sepp
name: Reppas, John
name: Mante, Valerio
Publisher: name: ETH Zurich
Year: 2022

description: Dorso-lateral prefrontal cortex is thought to contribute to adaptive behavior by integrating temporally dispersed, behaviorally-relevant factors. Past work has revealed a variety of neural representations preceding actions, which are involved in internal processes like planning, working memory and covert attention. Task-related activity following actions has often been reported, but so far lacks a clear interpretation. We leveraged modified versions of classic oculomotor paradigms and population recordings to show that post-saccadic activity is a dominant signal in dorso-lateral prefrontal cortex that is distinct from pre-saccadic activity. Unlike pre-saccadic activity, post-saccadic activity occurs after each saccade, although its strength and duration are modulated by task context and expected rewards. In contrast to representations preceding actions, which appear to be mixed randomly across neurons, post-saccadic activity results in representations that are highly structured at the single-neuron and population level. Overall, the properties of post-saccadic activity are consistent with those of an action memory, an internal process with a possible role in learning and updating spatial representations.
description: bioRxiv
A new theoretical framework jointly explains behavioral and neural variability across subjects performing flexible decision-making
Creators: name: Pagan, Marino
name: Tang, Vincent D.
name: Aoi, Mikio C.
name: Pillow, Jonathan W.
name: Mante, Valerio
name: Sussillo, David
name: Brody, Carlos D.
Publisher: name: ETH Zurich
Year: 2022

description: The ability to flexibly select and accumulate relevant information to form decisions, while ignoring irrelevant information, is a fundamental component of higher cognition. Yet its neural mechanisms remain unclear. Here we demonstrate that, under assumptions supported by both monkey and rat data, the space of possible network mechanisms to implement this ability is spanned by the combination of three different components, each with specific behavioral and anatomical implications. We further show that existing electrophysiological and modeling data are compatible with the full variety of possible combinations of these components, suggesting that different individuals could use different component combinations. To study variations across subjects, we developed a rat task requiring context-dependent evidence accumulation, and trained many subjects on it. Our task delivers sensory evidence through pulses that have random but precisely known timing, providing high statistical power to characterize each individual’s neural and behavioral responses. Consistent with theoretical predictions, neural and behavioral analysis revealed remarkable heterogeneity across rats, despite uniformly good task performance. The theory further predicts a specific link between behavioral and neural signatures, which was robustly supported in the data. Our results provide a new experimentally-supported theoretical framework to analyze biological and artificial systems performing flexible decision-making tasks, and open the door to the study of individual variability in neural computations underlying higher cognition.
description: bioRxiv
Packaging, containerization, and virtualization of computational omics methods: Advances, challenges, and opportunities
Creators: name: Alser, Mohammed
name: Waymost, Sharon
name: Ayyala, Ram
name: Lawlor, Brendan
name: Abdill, Richard J.
name: Rajkumar, Neha
name: LaPierre, Nathan
name: Brito, Jaqueline
name: Ribeiro-dos-Santos, Andre M.
name: Firtina, Can
name: Almadhoun, Nour
name: Sarwal, Varuni
name: Eskin, Eleazar
name: Hu, Qiyang
name: Strong, Derek
name: Kim, Byoung-Do
name: Abedalthagafi, Malak S.
name: Mutlu, Onur
name: Mangul, Serghei
Publisher: name: ETH Zurich
Year: 2022
Subjects: Genomics (q-bio.GN)
Distributed, Parallel, and Cluster Computing (cs.DC)
Software Engineering (cs.SE)
Applications (stat.AP)
FOS: Biological sciences
FOS: Computer and information sciences

description: Omics software tools have reshaped the landscape of modern biology and become an essential component of biomedical research. The increasing dependence of biomedical scientists on these powerful tools creates a need for easier installation and greater usability. Packaging, virtualization, and containerization are different approaches to satisfy this need by wrapping omics tools in additional software that makes the omics tools easier to install and use. Here, we systematically review practices across prominent packaging, virtualization, and containerization platforms. We outline the challenges, advantages, and limitations of each approach and some of the most widely used platforms from the perspectives of users, software developers, and system administrators. We also propose principles to make packaging, virtualization, and containerization of omics software more sustainable and robust to increase the reproducibility of biomedical and life science research.
description: arXiv
TuRaN: True Random Number Generation Using Supply Voltage Underscaling in SRAMs
Creators: name: Yüksel, İsmail Emir
name: Olgun, Ataberk
name: Salami, Behzad
name: Bostancı, F. Nisa
name: Tuğrul, Yahya Can
name: Yağlıkçı, A. Giray
name: Mansouri Ghiasi, Nika
name: Mutlu, Onur
name: Ergin, Oğuz
Publisher: name: ETH Zurich
Year: 2022
Subjects: Hardware Architecture (cs.AR)
Cryptography and Security (cs.CR)
FOS: Computer and information sciences

description: Prior works propose SRAM-based TRNGs that extract entropy from SRAM arrays. SRAM arrays are widely used in a majority of specialized or general-purpose chips that perform the computation to store data inside the chip. Thus, SRAM-based TRNGs present a low-cost alternative to dedicated hardware TRNGs. However, existing SRAM-based TRNGs suffer from 1) low TRNG throughput, 2) high energy consumption, 3) high TRNG latency, and 4) the inability to generate true random numbers continuously, which limits the application space of SRAM-based TRNGs. Our goal in this paper is to design an SRAM-based TRNG that overcomes these four key limitations and thus, extends the application space of SRAM-based TRNGs. To this end, we propose TuRaN, a new high-throughput, energy-efficient, and low-latency SRAM-based TRNG that can sustain continuous operation. TuRaN leverages the key observation that accessing SRAM cells results in random access failures when the supply voltage is reduced below the manufacturer-recommended supply voltage. TuRaN generates random numbers at high throughput by repeatedly accessing SRAM cells with reduced supply voltage and post-processing the resulting random faults using the SHA-256 hash function. To demonstrate the feasibility of TuRaN, we conduct SPICE simulations on different process nodes and analyze the potential of access failure for use as an entropy source. We verify and support our simulation results by conducting real-world experiments on two commercial off-the-shelf FPGA boards. We evaluate the quality of the random numbers generated by TuRaN using the widely-adopted NIST standard randomness tests and observe that TuRaN passes all tests. TuRaN generates true random numbers with (i) an average (maximum) throughput of 1.6Gbps (1.812Gbps), (ii) 0.11nJ/bit energy consumption, and (iii) 278.46us latency.
description: arXiv
Empowering Data Centers for Next Generation Trusted Computing
Creators: name: Dhar, Aritra
name: Sridhara, Supraja
name: Shinde, Shweta
name: Capkun, Srdjan
name: Andri, Renzo
Publisher: name: ETH Zurich
Year: 2022

description: Modern data centers have grown beyond CPU nodes to provide domain-specific accelerators such as GPUs and FPGAs to their customers. From a security standpoint, cloud customers want to protect their data. They are willing to pay additional costs for trusted execution environments such as enclaves provided by Intel SGX and AMD SEV. Unfortunately, the customers have to make a critical choice -- either use domain-specific accelerators for speed or use CPU-based confidential computing solutions. To bridge this gap, we aim to enable data-center scale confidential computing that expands across CPUs and accelerators. We argue that having wide-scale TEE-support for accelerators presents a technically easier solution, but is far away from being a reality. Instead, our hybrid design provides enclaved execution guarantees for computation distributed over multiple CPU nodes and devices with/without TEE support. Our solution scales gracefully in two dimensions -- it can handle a large number of heterogeneous nodes and it can accommodate TEE-enabled devices as and when they are available in the future. We observe marginal overheads of 0.42--8% on real-world AI data center workloads that are independent of the number of nodes in the data center. We add custom TEE support to two accelerators (AI and storage) and integrate it into our solution, thus demonstrating that it can cater to future TEE devices.
description: arXiv
SURVEY OF OLDER ROAD USERS BEHAVIOURAL & TRAVEL ISSUES
Creators: name: Nielsen, Sally
Publisher: name: Monash University
Year: 2016
Subjects: Uncategorized

description: Monash University Accident Research Centre - Report #57 - 1994Authors: B. Fildes, S. Lee, D. Kenny & W. Foddy
ResMiCo: increasing the quality of metagenome-assembled genomes with deep learning
Creators: name: Mineeva, Olga
name: Danciu, Daniel
name: Schölkopf, Bernhard
name: Ley, Ruth E.
name: Rätsch, Gunnar
name: Youngblut, Nicholas D.
Publisher: name: ETH Zurich
Year: 2022

description: The number of published metagenome assemblies is rapidly growing due to advances in sequencing technologies. However, sequencing errors, variable coverage, repetitive genomic regions, and other factors can produce misassemblies, which are challenging to detect for taxonomically novel genomic data. Assembly errors can affect all downstream analyses of the assemblies. Accuracy for the state of the art in reference-free misassembly prediction does not exceed an AUPRC of 0.57, and it is not clear how well these models generalize to real-world data. Here, we present the Residual neural network for Misassembled Contig identification (ResMiCo), a deep learning approach for reference-free identification of misassembled contigs. To develop ResMiCo, we first generated a training dataset of unprecedented size and complexity that can be used for further benchmarking and developments in the field. Through rigorous validation, we show that ResMiCo is substantially more accurate than the state of the art, and the model is robust to novel taxonomic diversity and varying assembly methods. ResMiCo estimated 4.7% misassembled contigs per metagenome across multiple real-world datasets. We demonstrate how ResMiCo can be used to optimize metagenome assembly hyperparameters to improve accuracy, instead of optimizing solely for contiguity. The accuracy, robustness, and ease-of-use of ResMiCo make the tool suitable for general quality control of metagenome assemblies and assembly methodology optimization.Author summary Metagenome assembly quality is fundamental to all downstream analyses of such data. The number of metagenome assemblies, especially metagenome-assembled genomes (MAGs), is rapidly increasing, but tools to assess the quality of these assemblies lack the accuracy needed for robust quality control. Moreover, existing models have been trained on datasets lacking complexity and realism, which may limit their generalization to novel data. Due to the limitations of existing models, most studies forgo such approaches and instead rely on CheckM to assess assembly quality, an approach that only utilizes a small portion of all genomic information and does not identify specific misassemblies. We harnessed existing large genomic datasets and high-performance computing to produce a training dataset of unprecedented size and complexity and thereby trained a deep learning model for predicting misassemblies that can robustly generalize to novel taxonomy and varying assembly methodologies.Competing Interest StatementThe authors have declared no competing interest.
description: bioRxiv
From Chinese Postman to Salesman and Beyond: Shortest Tour δ-Covering All Points on All Edges
Creators: name: Frei, Fabian
name: Ghazy, Ahmed
name: Hartmann, Tim
name: Hörsch, Florian
name: Marx, Dániel
Publisher: name: CISPA
Year: 2024

description: A well-studied continuous model of graphs, introduced by Dearing and Francis [Transportation Science, 1974], considers each edge as a continuous unit-length interval of points. For δ >= 0, we introduce the problem δ-Tour, where the objective is to find the shortest tour that comes within a distance of δ of every point on every edge. It can be observed that 0-Tour is essentially equivalent to the Chinese Postman Problem, which is solvable in polynomial time. In contrast, 1/2-Tour is essentially equivalent to the graphic Traveling Salesman Problem (TSP), which is NP-hard but admits a constant-factor approximation in polynomial time. We investigate δ-Tour for other values of δ, noting that the problem's behavior and the insights required to understand it differ significantly across various δ regimes.

First, we examine the approximability of the problem for every fixed δ > 0:
(1) For every fixed 0 < δ < 3/2, the problem δ-Tour admits a constant-factor approximation and is APX-hard, while for every fixed δ >= 3/2, the problem admits an O(log n)-approximation in polynomial time and has no polynomial-time o(log n)-approximation, unless P = NP.

When parameterizing by the minimum tour length, it is relatively easy to show that 3/2 is the threshold of fixed-parameter tractability:
(2) For every fixed 0 < δ < 3/2, the problem δ-Tour is fixed-parameter tractable (FPT) when parameterized by the minimum tour length, while it is W[2]-hard for every fixed δ >= 3/2.

On the other hand, if δ is considered to be part of the input, then an interesting nontrivial phenomenon appears when δ is a constant fraction of the number of vertices:
(3) If δ is part of the input, then the problem can be solved in time f(k) n^O(k), where k = ⌈n/δ⌉; however, assuming the Exponential-Time Hypothesis (ETH), there is no algorithm that solves the problem and runs in time f(k) n^o(k/log k).

Our techniques also yield APX-hardness as a new result for graphic TSP on cubic bipartite graphs.
Mutant SF3B1 promotes PDAC malignancy through TGF-β resistance
Creators: name: Simmler, Patrik T.
name: Mengis, Tamara
name: Lehmann, Kjong-Van
name: Kahles, André
name: Thomas, Tinu
name: Rätsch, Gunnar
name: Stoffel, Markus
name: Schwank, Gerald
Publisher: name: ETH Zurich
Year: 2022

description: The splicing factor SF3B1 is recurrently mutated in various tumors, including pancreatic ductal adenocarcinoma (PDAC). The impact of the hotspot mutation SF3B1K700E on the PDAC pathogenesis, however, remains elusive. Here, we demonstrate that Sf3b1K700E alone is insufficient to induce malignant transformation of the murine pancreas, but increases aggressiveness of PDAC if it co-occurs together with mutated KRAS and p53. We further demonstrate that SF3B1K700E reduces epithelial–mesenchymal transition (EMT) and confers resistance to TGF-β1-induced cell death, and provide evidence that this phenotype is in part mediated through aberrant splicing of Map3k7. Taken together, our work suggests that SF3B1K700E acts as an oncogenic driver in PDAC through enhancing resistance to the tumor suppressive effects of TGF-β.Competing Interest StatementThe authors have declared no competing interest.
description: bioRxiv
Entropy Maximization with Depth: A Variational Principle for Random Neural Networks
Creators: name: Joudaki, Amir
name: Daneshmand, Hadi
name: Bach, Francis
Publisher: name: ETH Zurich
Year: 2022

description: To understand the essential role of depth in neural networks, we investigate a variational principle for depth: Does increasing depth perform an implicit optimization for the representations in neural networks? We prove that random neural networks equipped with batch normalization maximize the differential entropy of representations with depth up to constant factors, assuming that the representations are contractive. Thus, representations inherently obey the principle of maximum entropy at initialization, in the absence of information about the learning task. Our variational formulation for neural representations characterizes the interplay between representation entropy and architectural components, including depth, width, and non-linear activations, thereby potentially inspiring the design of neural architectures.
description: arXiv
PAC-Bayesian Meta-Learning: From Theory to Practice
Creators: name: Rothfuss, Jonas
name: Josifoski, Martin
name: Fortuin, Vincent
name: Krause, Andreas
Publisher: name: ETH Zurich
Year: 2022

description: Meta-Learning aims to accelerate the learning on new tasks by acquiring useful inductive biases from related data sources. In practice, the number of tasks available for meta-learning is often small. Yet, most of the existing approaches rely on an abundance of meta-training tasks, making them prone to overfitting. How to regularize the meta-learner to ensure generalization to unseen tasks, is a central question in the literature. We provide a theoretical analysis using the PAC-Bayesian framework and derive the first bound for meta-learners with unbounded loss functions. Crucially, our bounds allow us to derive the PAC-optimal hyper-posterior (PACOH) - the closed-form-solution of the PAC-Bayesian meta-learning problem, thereby avoiding the reliance on nested optimization, giving rise to an optimization problem amenable to standard variational methods that scale well. Our experiments show that, when instantiating the PACOH with Gaussian processes and Bayesian Neural Networks as base learners, the resulting methods are more scalable, and yield state-of-the-art performance, both in terms of predictive accuracy and the quality of uncertainty estimates. Finally, thanks to the principled treatment of uncertainty, our meta-learners can also be successfully employed for sequential decision problems.
description: arXiv
Performance analysis of a hybrid agent for quantum-accessible reinforcement learning
Creators: name: Hamann, Arne
name: Wölk, Sabine
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: In the last decade quantum machine learning has provided fascinating and fundamental improvements to supervised, unsupervised and reinforcement learning. In reinforcement learning, a so-called agent is challenged to solve a task given by some environment. The agent learns to solve the task by exploring the environment and exploiting the rewards it gets from the environment. For some classical task environments, such as deterministic strictly epochal environments, an analogue quantum environment can be constructed which allows to find rewards quadratically faster by applying quantum algorithms. In this paper, we analytically analyze the behavior of a hybrid agent which combines this quadratic speedup in exploration with the policy update of a classical agent. This leads to a faster learning of the hybrid agent compared to the classical agent. We demonstrate that if the classical agent needs on average $\langle J \rangle$ rewards and $\langle T \rangle_c$ epochs to learn how to solve the task, the hybrid agent will take $\langle T \rangle_q \leq α\sqrt{\langle T \rangle_c \langle J \rangle}$ epochs on average. Here, $α$ denotes a constant which is independent of the problem size. Additionally, we prove that if the environment allows for maximally $α_o k_\text{max}$ sequential coherent interactions, e.g. due to noise effects, an improvement given by $\langle T \rangle_q \approx α_o\langle T \rangle_c/4 k_\text{max}$ is still possible.
description: 13 pages, 4 figures