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arXiv 2021年

作者： Wang, Jingwei Zepf, Matt Leng, Yuxin Li, Ruxin Rykovanov, Sergey G. Shanghai 201800 China Collaborative Innovation Center of IFSA Shanghai Jiao Tong University Shanghai 200240 China Helmholtz Institute Jena Fröbelstieg 3 Jena07743 Germany Faculty of Physics and Astronomy Friedrich-Schiller-Universität Jena Jena07743 Germany High Performance Computing and Big Data Laboratory Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow121205 Russia

In this Letter using three-dimensional particle-in-cell simulations and analytical considerations we demonstrate intense high-order plasma surface harmonics carrying a time-varying orbital angular momentum (OAM) - the self-torque. We show that by using two laser beams with different OAMs l1 and l2 and a certain delay between each other and shooting them obliquely on an overdense plasma target, one can generate harmonics with OAM spanning nl1 to nl2, where n is the order of the harmonic. Such intense self-torqued harmonics can offer new possibilities in ultrafast spectroscopy. © 2021, CC BY.

关键词： Harmonic analysis

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Almost affinely disjoint subspaces

arXiv

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arXiv 2020年

作者： Liu, Hedongliang Polianskii, Nikita Vorobyev, Ilya Wachter-Zeh, Antonia Technical University of Munich Institute for Communications Engineering Munich80333 Germany Skolkovo Institute of Science and Technology Center for Computational and Data-Intensive Science and Engineering Moscow121205 Russia

In this work, we introduce a natural notion concerning finite vector spaces. A family of k-dimensional subspaces of Fnq, which forms a partial spread, is called almost affinely disjoint if any (k + 1)-dimensional subspace containing a subspace from the family non-trivially intersects with only a few subspaces from the family. The central question discussed in the paper is the polynomial growth (in q) of the maximal cardinality of these families given the parameters k and n. For the cases k = 1 and k = 2, optimal families are constructed. For other settings, we find lower and upper bounds on the polynomial growth. Additionally, some connections with problems in coding theory are shown. © 2020, CC BY-NC-ND.

关键词： Vectors

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Complex diffusion-based kinetics of photoluminescence in semiconductor nanoplatelets

arXiv

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arXiv 2021年

作者： Kurilovich, Aleksandr A. Mantsevich, Vladimir N. Stevenson, Keith J. Chechkin, Aleksei V. Palyulin, Vladimir V. Center for Energy Science and Technology Skolkovo Institute of Science and Technology Moscow121205 Russia Semiconductors and Cryoelectronics & Quantum Technology Center Physics department Lomonosov Moscow State University Moscow119991 Russia Institute for Physics & Astronomy University of Potsdam Potsdam-GolmD-14476 Germany Akhiezer Institute for Theoretical Physics National Science Center Kharkov Institute of Physics and Technology Kharkov61108 Ukraine Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow121205 Russia

We present a diffusion-based simulation and theoretical models for explanation of photoluminescence (PL) emission intensity in semiconductor nanoplatelets. It is shown that the shape of PL intensity curves can be reproduced by the interplay of recombination, diffusion and trapping of excitons. The emission intensity at short times is purely exponential and is defined by recombination. At long times it is governed by the release of excitons from surface traps and is characterized by a power-law tail. We show that the crossover from one limit to another is controlled by diffusion properties. This intermediate region exhibits a rich behaviour depending on the value of diffusivity. Proposed approach reproduces all the features of experimental curves measured for different nanoplatelet systems. Copyright © 2021, The Authors. All rights reserved.

关键词： Diffusion

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Estimation of the Second Moment Based on Rounded data

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Journal of Mathematical sciences (United States) 2019年第6期237卷 819-825页

作者： Samsonov, S.V. Ushakov, N.G. Ushakov, V.G. Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow Russian Federation Department of Mathematical Sciences Norwegian University of Science and Technology Trondheim Norway Moscow State University Moscow Russian Federation

Sample moments are unbiased estimators of theoretical moments (if the latter exist). In practice, however, observations are rounded under registration, which leads to systematic errors. In [1–3] it was shown that random measurement errors can provide the reduction of rounding errors, when the expectation is estimated by the first sample moment. This gives a possibility to manage the rounding error of the result, if one can add some noise to observations before registration. Moreover, this error can be made arbitrarily small. Now we find conditions under which this takes place for the second moment. © 2019, Springer science+Business Media, LLC, part of Springer Nature.

关键词： Estimators Registration second moment Noise Systematic errors Error measure Moment of force Rounding error Tea random measurement

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Relativistic modified Bessel-Gaussian beam generated from plasma-based beam braiding

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Physical Review A 2021年第2期104卷 L021501-L021501页

作者： Bifeng Lei Daniel Seipt Mingyuan Shi Bin Liu Jingwei Wang Matt Zepf Sergey G. Rykovanov Helmholtz Institute Jena Fröbelstieg 3 07743 Jena Germany GSI Helmholtzzentrum für Schwerionenforschung GmbH Planckstrasse 1 64291 Darmstadt Germany Faculty of Physics and Astronomy Friedrich-Schiller-Universität Jena 07743 Jena Germany Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences 201800 Shanghai China Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow 121205 Russia

We theoretically and numerically demonstrate the generation of a relativistic modified Bessel-Gaussian beam (MBGB) via plasma-based beam braiding. It is realized by injecting several intense Gaussian pulses with well-designed offsets and angles into an underdense plasma channel which acts as a laser-pulse combiner via refractive coupling. The MBGB propagates stably in the plasma channel with a well-controlled orbital angular momentum of large value, exciting a twisted plasma wave. After leaving the plasma, it becomes unguided and survives in vacuum for at least hundreds of femtoseconds. This method is insensitive to the initial laser injection conditions and thus should be robust for experimental implementation. It provides an alternative approach in generating high-quality tunable intense optical vortex beams which are desired for various applications.

关键词： Laser driven electron acceleration Laser wakefield acceleration Laser-plasma interactions Plasma acceleration & new acceleration techniques

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No-Dealer: Byzantine Fault-Tolerant Random Number Generator

No-Dealer: Byzantine Fault-Tolerant Random Number Generator

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IEEE Conference on Computer Communications Workshops, INFOCOM Wksps

作者： Mikhail Krasnoselskii Grigorii Melnikov Yury Yanovich Moscow Russia Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology (Skoltech) Moscow Russia Laboratory of Data Mining and Predictive Modeling Institute for Information Transmission Problems (IITP RAS) Moscow Russia

The following topics are dealt with: learning (artificial intelligence); Internet of Things; mobile computing; cloud computing; cryptography; telecommunication traffic; data privacy; autonomous aerial vehicles; resour... 详细信息

ISBN: (数字)9781728186955

ISBN: (纸本)9781728186962

关键词： Fault tolerance Fault tolerant systems Protocols Peer-to-peer computing computational modeling Public key

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Dynamic prediction of mortality in COVID-19 patients in the intensive care unit: A retrospective multi-center cohort study

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Intelligence-Based Medicine 2022年 6卷 100071-100071页

作者： Smit, J.M. Krijthe, J.H. Endeman, H. Tintu, A.N. de Rijke, Y.B. Gommers, D.A.M.P.J. Cremer, O.L. Bosman, R.J. Rigter, S. Wils, E.-J. Frenzel, T. Dongelmans, D.A. De Jong, R. Peters, M.A.A. Kamps, M.J.A. Ramnarain, D. Nowitzky, R. Nooteboom, F.G.C.A. De Ruijter, W. Urlings-Strop, L.C. Smit, E.G.M. Mehagnoul-Schipper, D.J. Dormans, T. De Jager, C.P.C. Hendriks, S.H.A. Achterberg, S. Oostdijk, E. Reidinga, A.C. Festen-Spanjer, B. Brunnekreef, G.B. Cornet, A.D. Van den Tempel, W. Boelens, A.D. Koetsier, P. Lens, J.A. Faber, H.J. karakus, A. Entjes, R. De Jong, P. Rettig, T.C.D. Arbous, M.S. Lalisang, R.C.A. Tonutti, M. De Bruin, D.P. Elbers, P.W.G. Van Bommel, J. Reinders, M.J.T. Intensive Care Erasmus University Medical Center Rotterdam Netherlands Pattern Recognition & Bioinformatics Group EEMCS Delft University of Technology Delft Netherlands Clinical Chemistry Erasmus University Medical Center Rotterdam Netherlands Intensive Care UMC Utrecht Utrecht Netherlands Intensive Care OLVG Amsterdam Netherlands Anesthesiology and Intensive Care St. Antonius Hospital Nieuwegein Netherlands Intensive Care Franciscus Gasthuis Vlietland Rotterdam Netherlands Intensive Care Radboud University Medical Center Nijmegen Netherlands Intensive Care Amsterdam UMC Amsterdam Netherlands Intensive Care Bovenij Ziekenhuis Amsterdam Netherlands Intensive Care Canisius Wilhelmina Ziekenhuis Nijmegen Netherlands Intensive Care Catharina Ziekenhuis Eindhoven Eindhoven Netherlands Intensive Care ETZ Tilburg Tilburg Netherlands Intensive Care HagaZiekenhuis Den Haag Netherlands Intensive Care Laurentius Ziekenhuis Roermond Netherlands Intensive Care Northwest Clinics Alkmaar Netherlands Intensive Care Reinier de Graaf Gasthuis Delft Netherlands Intensive Care Spaarne Gasthuis Haarlem en Hoofddorp Netherlands Intensive Care VieCuri Medisch Centrum Venlo Netherlands Intensive Care Zuyderland MC Heerlen Netherlands Intensive Care Jeroen Bosch Ziekenhuis 's-Hertogenbosch Netherlands Intensive Care Albert Schweitzerziekenhuis Dordrecht Netherlands Intensive Care Haaglanden Medisch Centrum Den Haag Netherlands Intensive Care Maasstad Ziekenhuis Rotterdam Rotterdam Netherlands Intensive Care SEH BWC Martiniziekenhuis Groningen Netherlands Intensive Care Ziekenhuis Gelderse Vallei Ede Netherlands Intensive Care Ziekenhuisgroep Twente Almelo Netherlands Intensive Care Medisch Spectrum Twente Enschede Netherlands Intensive Care Ikazia Ziekenhuis Rotterdam Rotterdam Netherlands Anesthesiology Antonius Ziekenhuis Sneek Sneek Netherlands Intensive Care Medisch Centrum Leeuwarden Leeuwarden Netherlands Intensive Care IJsselland Zieke

Background: The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this work, we report on the development and validation of a dynamic mortality model specifically for critically ill COVID-19 patients and discuss its potential utility in the ICU. Methods: We collected electronic medical record (EMR) data from 3222 ICU admissions with a COVID-19 infection from 25 different ICUs in the Netherlands. We extracted daily observations of each patient and fitted both a linear (logistic regression) and non-linear (random forest) model to predict mortality within 24 h from the moment of prediction. Isotonic regression was used to re-calibrate the predictions of the fitted models. We evaluated the models in a leave-one-ICU-out (LOIO) cross-validation procedure. Results: The logistic regression and random forest model yielded an area under the receiver operating characteristic curve of 0.87 [0.85;0.88] and 0.86 [0.84;0.88], respectively. The recalibrated model predictions showed a calibration intercept of −0.04 [−0.12;0.04] and slope of 0.90 [0.85;0.95] for logistic regression model and a calibration intercept of −0.19 [−0.27;−0.10] and slope of 0.89 [0.84;0.94] for the random forest model. Discussion: We presented a model for dynamic mortality prediction, specifically for critically ill COVID-19 patients, which predicts near-term mortality rather than in-ICU mortality. The potential clinical utility of dynamic mortality models such as benchmarking, improving resource allocation and informing family members, as well as the development of models with more causal structure, should be topics for future research. © 2022 The Authors

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New bounds and generalizations of locally recoverable codes with availability

New bounds and generalizations of locally recoverable codes ...

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作者： Kruglik, Stanislav Nazirkhanova, Kamilla Frolov, Alexey Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow121205 Russia Department of Radio Engineering and Cybernetics Moscow Institute of Physics and Technology Moscow141701 Russia

We investigate the distance properties of linear locally recoverable codes (LRC codes) with all-symbol locality and availability. New upper and lower bounds on the minimum distance of such codes are derived. The upper bound is based on the shortening method and generalized Hamming weights that are fundamental parameters of any linear codes with many useful applications. This bound improves existing upper bounds. To reduce the gap in between upper and lower bounds, we do not restrict the alphabet size and propose explicit constructions of codes with locality and availability via rank-metric codes. The first construction relies on expander graphs and is better in low rate region. The second construction utilizes the LRC codes developed by Wang et al. as inner codes and is better in high rate region. We also suggest one possible generalization of LRC codes in which the recovering sets can intersect in a small number of coordinates. This feature allows us to increase the achievable code rate and still meet load balancing requirements. We derive upper and lower bounds on the parameters of such codes and present explicit constructions of codes with such a property. © 1963-2012 IEEE.

关键词： Fault tolerance

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Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats (vol 16, 585, 2025)

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NATURE COMMUNICATIONS 2025年第1期16卷 1-15页

作者： Steinfeldt, Jakob Wild, Benjamin Buergel, Thore Pietzner, Maik Upmeier zu Belzen, Julius Vauvelle, Andre Hegselmann, Stefan Denaxas, Spiros Hemingway, Harry Langenberg, Claudia Landmesser, Ulf Deanfield, John Eils, Roland Department of Cardiology Angiology and Intensive Care Medicine Deutsches Herzzentrum der Charité (DHZC) Berlin Germany Charité – Universitätsmedizin Berlin corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin Klinik/Centrum Berlin Germany Computational Medicine Berlin Institute of Health (BIH) Charite - University Medicine Berlin Berlin Germany Friede Springer Cardiovascular Prevention Center@Charite Charite - University Medicine Berlin Berlin Germany Institute of Cardiovascular Sciences University College London London UK Berlin Institute of Health (BIH) Charite - University Medicine Berlin Berlin Germany DZHK (German Centre for Cardiovascular Research) Partner Site Berlin Berlin Berlin Germany MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK Precision Health University Research Institute Queen Mary University of London and Barts NHS Trust London UK Center for Digital Health Berlin Institute of Health (BIH) Charite - University Medicine Berlin Berlin Germany Health Data Science Unit Heidelberg University Hospital and BioQuant Heidelberg Germany Institute of Health Informatics University College London London UK British Heart Foundation Data Science Centre London UK Health Data Research UK London UK National Institute for Health Research Biomedical Research Centre at University College London Hospitals London UK Institute for Medical Engineering and Science Massachusetts Institute of Technology Massachusetts USA Pattern Recognition and Image Analysis Lab University of Münster Münster Germany

The COVID-19 pandemic exposed a global deficiency of systematic, data-driven guidance to identify high-risk individuals. Here, we illustrate the utility of routinely recorded medical history to predict the risk for 1741 diseases across clinical specialties and support the rapid response to emerging health threats such as COVID-19. We developed a neural network to learn from health records of 502,489 UK Biobank participants. Importantly, we observed discriminative improvements over basic demographic predictors for 1546 (88.8%) endpoints. After transferring the unmodified risk models to the All of US cohort, we replicated these improvements for 1115 (78.9%) of 1414 investigated endpoints, demonstrating generalizability across healthcare systems and historically underrepresented groups. Ultimately, we showed how this approach could have been used to identify individuals vulnerable to severe COVID-19. Our study demonstrates the potential of medical history to support guidance for emerging pandemics by systematically estimating risk for thousands of diseases at once at minimal cost.

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Optimal multistage group testing algorithm for 3 defectives

arXiv

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arXiv 2020年

作者： Vorobyev, Ilya Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow127051 Russia Advanced Combinatorics and Complex Networks Lab Moscow Institute of Physics and Technology Dolgoprudny141701 Russia

Group testing is a well-known search problem that consists in detecting of s defective members of a set of t samples by carrying out tests on properly chosen subsets of samples. In classical group testing the goal is to find all defective elements by using the minimal possible number of tests in the worst case. In this work, a multistage group testing problem is considered. Our goal is to construct a multistage search procedure, having asymptotically the same number of tests as an adaptive one. We propose a new approach to designing multistage algorithms, which allows us to construct a 5-stage algorithm for finding 3 defectives with the optimal number 3 log2 t(1 + o(1)) of *** Codes 68R05 Copyright © 2020, The Authors. All rights reserved.

关键词： Well testing

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