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Pseudoentropic derivation of the regularized lattice Boltzmann method

Physical Review E 2019年第2期100卷 023302-023302页

作者： Andreas Krämer Dominik Wilde Knut Küllmer Dirk Reith Holger Foysi Institute of Technology Resource and Energy-efficient Engineering (TREE) Bonn-Rhein-Sieg University of Applied Sciences Grantham-Allee 20 53757 Sankt Augustin Germany National Heart Lung and Blood Institute National Institutes of Health Bethesda Maryland 20892 United States Department of Mechanical Engineering University of Siegen Paul-Bonatz-Straße 9-11 57076 Siegen-Weidenau Germany Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) Schloss Birlinghoven 53754 Sankt Augustin Germany

The lattice Boltzmann method (LBM) facilitates efficient simulations of fluid turbulence based on advection and collision of local particle distribution functions. To ensure stable simulations on underresolved grids, the collision operator must prevent drastic deviations from local equilibrium. This can be achieved by various methods, such as the multirelaxation time, entropic, quasiequilibrium, regularized, and cumulant schemes. Complementing a part of a unified theoretical framework of these schemes, the present work presents a derivation of the regularized lattice Boltzmann method (RLBM), which follows a recently introduced entropic multirelaxation time LBM by Karlin, Bösch, and Chikatamarla (KBC). It is shown that both methods can be derived by locally maximizing a quadratic Taylor expansion of the entropy function. While KBC expands around the local equilibrium distribution, the RLBM is recovered by expanding entropy around a global equilibrium. Numerical tests were performed to elucidate the role of pseudoentropy maximization in these models. Simulations of a two-dimensional shear layer show that the RLBM successfully reproduces the largest eddies even on a 16×16 grid, while the conventional LBM becomes unstable for grid resolutions of 128×128 and lower. The RLBM suppresses spurious vortices more effectively than KBC. In contrast, simulations of the three-dimensional Taylor-Green and Kida vortices show that KBC performs better in resolving small scale vortices, outperforming the RLBM by a factor of 1.8 in terms of the effective Reynolds number.

关键词： Flow instability Shear flows Turbulence

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DARE: A reflective platform designed to enable agile data-driven research on the cloud 15

DARE: A reflective platform designed to enable agile data-dr...

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15th IEEE International Conference on eScience, eScience 2019

作者： Klampanos, Iraklis Davvetas, Athanasios Gemund, Andre Atkinson, Malcolm Koukourikos, Antonis Filgueira, Rosa Krause, Amrey Spinuso, Alessandro Charalambidis, Angelos Magnoni, Federica Casarotti, Emanuele Page, Christian Lindner, Mike Ikonomopoulos, Andreas Karkaletsis, Vangelis Institute of Informatics and Telecommunications NCSR Demokritos Greece Fraunhofer Institute for Algorithms and Scientific Computing Germany School of Informatics University of Edinburgh United Kingdom EPCC University of Edinburgh United Kingdom Netherlands Istituto Nazionale Geofisica e Vulcanologia [INGV Italy Centre Europeen de Recherche et de Formation Avancee en Calcul Scientifique [CERFACS France Karlsruher Institut fur Technologie [KIT Germany Institute of Nuclear and Radiological Sciences and Technology Energy and Safety NCSR Demokritos Greece

ISBN: (纸本)9781728124513

The DARE platform has been designed to help research developers deliver user-facing applications and solutions over diverse underlying e-infrastructures, data and computational contexts. The platform is Cloud-ready, and relies on the exposure of APIs, which are suitable for raising the abstraction level and hiding complexity. At its core, the platform implements the cataloguing and execution of fine-grained and Python-based dispel4py workflows as services. Reflection is achieved via a logical knowledge base, comprising multiple internal catalogues, registries and semantics, while it supports persistent and pervasive data provenance. This paper presents design and implementation aspects of the DARE platform, as well as it provides directions for future development. © 2019 IEEE.

关键词： Semantics

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RDM-stars as sources of fast radio bursts

arXiv

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arXiv 2018年

作者： Nikitin, Igor Fraunhofer Institute for Algorithms and Scientific Computing Schloss Birlinghoven Sankt Augustin53757 Germany

In this work we consider a recently formulated model of a black hole coupled with radially directed flows of dark matter (RDM-star). In this model, a cutoff by quantum gravity (QG) creates a core of Planck density, filled with a gas of Planck mass particles, inside the star. Further, in this model, a fast radio burst (FRB) can be generated via the following mechanism. An object of an asteroid mass falls onto an RDM-star. Due to large gravitational forces available in the interior, the RDM-star works as a powerful accelerator, boosting the nucleons composing the object to extremely high energies. Upon collision with the core, the nucleons enter in deeply inelastic reactions with the Planck particles composing the core. This process is followed by stimulated emission of highly energetic photons. On the way outside, these photons are subjected to a strong redshift factor, downscaling their frequencies to the radio diapason, as a result producing an FRB. A straightforward computation gives a characteristic upper FRB frequency of 0.6GHz. With attenuation factors, it is stretched to a range 0.35-8GHz, fitting well with the observable FRB frequencies. We also discuss the reconstruction of other FRB parameters in frames of the model. Copyright © 2018, The Authors. All rights reserved.

关键词： Stars

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Stability of white holes revisited

arXiv

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arXiv 2018年

作者： Nikitin, Igor Fraunhofer Institute for Algorithms and Scientific Computing Schloss Birlinghoven Sankt Augustin53757 Germany

It is shown that the models of white hole interacting with external matter can be made stable by introduction of a negative central mass. Similar results are obtained for the models of white hole, interacting with null shells, with radial flows of matter and with photon gas. In realistic models, a naked timelike singularity corresponding to the negative mass is hidden under a coat of positive mass, providing an extremely strong redshift for photons born in the Planck neighborhood of the singularity and observed at infinity, thereby realizing the principle of cosmic censorship in a relaxed form. Copyright © 2018, The Authors. All rights reserved.

关键词： Stars

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Motor-cognitive dual tasking in the clinical setting: a sensitive measure of functional impairment in early Alzheimer’s disease

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Alzheimer's & Dementia 2023年第S14期19卷

作者： Anna-Katharine Brem Gaetano Scebba Jelena Curcic Marijn Muurling Casper de Boer Neva Coello Alankar Atreya Pauline Conde Holger Fröhlich Margarita Grammatikopoulou Chris Hinds Ioulietta Lazarou Manuel Lentzen Vaibhav A Narayan Rouba Kozak Spiros Nikolopoulos Srinivasan Vairavan Pieter Jelle Visser Gayle Wittenberg Dag Aarsland RADAR-AD Consortium University Hospital of Old Age Psychiatry University of Bern Bern Switzerland King’s College London London United Kingdom Correspondece Novartis Institutes for BioMedical Research Basel Switzerland Alzheimer Center Amsterdam Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam Netherlands Alzheimer Center Amsterdam Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam Noord-Holland Netherlands University of Oxford Oxford United Kingdom Fraunhofer Institute for Algorithms and Scientific Computing SCAI Sankt Augustin Germany Centre for Research & Technology Hellas Thessaloniki Greece Davos Alzheimers Collaborative Wayne PA USA Novartis Cambridge MA USA Janssen Research and Development LLC Titusville NJ USA Alzheimer Center Amsterdam Department of Neurology Amsterdam University Medical Center Amsterdam Netherlands Maastricht University Maastricht Netherlands Stavanger University Hospital Stavanger Norway

Background Gait is a complex everyday activity that depends upon supraspinal activity and a host of cognitive functions such as attention and executive functions. As cognition declines in neurodegenerative diseases, the interaction and competition for neuronal resources during motor-cognitive dual-tasking (e.g., walking while talking) might be a sensitive measure of subtle functional impairments in early Alzheimer’s disease (AD). Here, we aim to identify gait deficits due to neuronal competition across the AD spectrum. Method This investigation is part of the ongoing Remote Assessment of Disease and Relapse – Alzheimer’s Disease (RADAR-AD) study. We attached three inertial measurement units (accelerometer and gyroscope) to both feet and one hip to assess dual task effects (DTE) assessing gait performance with/without concurrent serial subtraction-by-1 task in four groups: 1) amyloid negative healthy controls (HC, N = 59); and 2) amyloid positive preclinical AD (PreAD, N = 30); 3) prodromal AD (ProAD, N = 51); and 4) mild-to-moderate AD dementia (MildAD, N = 44) (Table 1). We furthermore investigated associations of DTE with observer-reported cognition. Result Group comparisons showed that dual-tasking induced lower cadence and increased stance, which were significantly different between HC and ProAD. Several DTE measures of variability differed significantly between PreAD and MildAD, with variability in the path length separating best between PreAD and ProAD (Table 2, Figure 1). DTE measures were associated with observer-rated divided attention only in the MildAD group. Conclusion Neuronal competition as assessed with motor-cognitive dual-tasking, specifically the DTE variability, might reflect functional deficits already in early AD, and could be a valuable additional measure to detect early impairments not captured by cognitive or motor tests alone. Future studies should implement an adaptive cognitive load to improve sensitivity/specificity in early AD stages and

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A Graph-Theoretic Approach to the Train Marshalling Problem

A Graph-Theoretic Approach to the Train Marshalling Problem

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Federated Conference on Computer Science and Information Systems

作者： Jens Dorpinghaus Rainer Schrader Fraunhofer Institute for Algorithms and Scientific Computing Schloss Birlinghoven Institut fur Informatik Universitat zu Koln

ISBN: (纸本)9781538623718

Rearranging cars of an incoming train in a hump yard is a widely discussed topic. We focus on the train marshalling problem where the incoming cars of a train are distributed to a certain number of sorting tracks. When pulled out again to build the outgoing train, cars sharing the same destination should appear consecutively. The goal is to minimize the number of sorting tracks. We suggest a graph-theoretic approach for this NP-complete problem. The idea is to partition an associated directed graph into what we call pseudochains of minimum length. We describe a greedy-type heuristic to solve the partitioning problem which, on random instances, performs better than the known heuristics for the train marshalling problem.

关键词： TRAIN Cars on-the-job training particle tracks Track tracks Tracks Heuristics REARRANGING grade Nondeterministic polynomial-time hard PULL-OUT

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A representer theorem for deep kernel learning

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The Journal of Machine Learning Research 2019年第1期20卷

作者： Bastian Bohn Christian Rieger Michael Griebel Institute for Numerical Simulation University of Bonn Bonn Germany Institute for Numerical Simulation University of Bonn Bonn Germany and Fraunhofer Center for Machine Learning Fraunhofer Institute for Algorithms and Scientific Computing SCAI Sankt Augustin Germany

In this paper we provide a finite-sample and an infinite-sample representer theorem for the concatenation of (linear combinations of) kernel functions of reproducing kernel Hilbert spaces. These results serve as mathematical foundation for the analysis of machine learning algorithms based on compositions of functions. As a direct consequence in the finite-sample case, the corresponding infinite-dimensional minimization problems can be recast into (nonlinear) finite-dimensional minimization problems, which can be tackled with nonlinear optimization algorithms. Moreover, we show how concatenated machine learning problems can be reformulated as neural networks and how our representer theorem applies to a broad class of state-of-the-art deep learning methods.

关键词： artificial neural networks deep kernel learning multilayer kernel regularized least-squares regression representer theorem

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App-based augmented reality to assess cognitive impairment in early Alzheimer’s disease

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Alzheimer's & Dementia 2023年第S14期19卷

作者： Anna-Katharine Brem Marijn Muurling Casper de Boer Jelena Curcic Alankar Atreya Neva Coello Pauline Conde Holger Fröhlich Margarita Grammatikopoulou Chris Hinds Ioulietta Lazarou Manuel Lentzen Robbert Harms Maximilian Bügler Vaibhav A Narayan Rouba Kozak Spiros Nikolopoulos Srinivasan Vairavan Pieter Jelle Visser Gayle Wittenberg Dag Aarsland RADAR-AD Consortium King’s College London London United Kingdom University Hospital of Old Age Psychiatry University of Bern Bern Switzerland Correspondece Alzheimer Center Amsterdam Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam Netherlands Alzheimer Center Amsterdam Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam Noord-Holland Netherlands Novartis Institutes for BioMedical Research Basel Switzerland University of Oxford Oxford United Kingdom Fraunhofer Institute for Algorithms and Scientific Computing SCAI Sankt Augustin Germany Centre for Research & Technology Hellas Thessaloniki Greece Altoida Inc. Washington DC USA Davos Alzheimers Collaborative Wayne PA USA Novartis Cambridge MA USA Janssen Research and Development LLC Titusville NJ USA Alzheimer Center Amsterdam Department of Neurology Amsterdam University Medical Center Amsterdam Netherlands Maastricht University Maastricht Netherlands Stavanger University Hospital Stavanger Norway

Background Augmented reality apps merge real world with virtual experiences and can be used to remotely assess complex instrumental activities of daily living (iADL) that are affected early in Alzheimer’s disease (AD). Our aim was to compare standard clinical measures with an augmented reality app to assess iADL that are related to memory and spatial navigation in early AD and its feasibility in the home-setting. Method We administered an augmented reality app (Altoida Inc., Washington DC, USA) in an on-going cross-sectional study (RADAR-AD: Remote Assessment of Disease and Relapse – Alzheimer’s Disease) in three groups: 1) amyloid negative healthy controls (HC, N = 49); and amyloid positive 2) preclinical AD (PreAD, N = 17); and 3) prodromal AD (ProAD, N = 29) (Table 1). Altoida’s research algorithm DNS-MCI (Digital Neuro Signature) produces the outcome of a machine learning model trained to identify cognitively normal individuals from those with cognitive impairment). DNS-MCI reflects performance in app-based tasks assessing memory and visuo-spatial function (placing and finding virtual objects, fire drill simulation) further including attention and motor performance (reaction time, finger tapping, navigational trajectory). At baseline, app-based tasks were performed in the clinic together with a standard neuropsychological assessment and iADL questionnaires (Figure 1). Participants were furthermore given the option of using Altoida in the home environment. Result The DNS-MCI score could significantly distinguish HC and PreAD participants from the ProAD group and was correlated with all neuropsychological tests and iADL questionnaires (Figures 1 and 2). Participants used the app on average 3-4 times at home (Table 1). Baseline in-clinic assessments were strongly correlated with at-home assessments (r = 0.53, p <.001). Conclusion App-based augmented reality tasks are applicable in the home setting and successful in capturing cognitive impairment in early AD. Future

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Perspectives on adaptive dynamical systems

arXiv

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arXiv 2023年

作者： Sawicki, Jakub Berner, Rico Loos, Sarah A.M. Anvari, Mehrnaz Bader, Rolf Barfuss, Wolfram Botta, Nicola Brede, Nuria Franović, Igor Gauthier, Daniel J. Goldt, Sebastian Hajizadeh, Aida Hövel, Philipp Karin, Omer Lorenz-Spreen, Philipp Miehl, Christoph Mölter, Jan Olmi, Simona Schöll, Eckehard Seif, Alireza Tass, Peter A. Volpe, Giovanni Yanchuk, Serhiy Kurths, Jürgen Potsdam Institute for Climate Impact Research Telegrafenberg Potsdam14473 Germany Fachhochschule Nordwestschweiz FHNW Leonhardsstrasse 6 Basel4009 Switzerland Department of Physics Humboldt-Universität zu Berlin Newtonstraße 15 Berlin12489 Germany DAMTP University of Cambridge Wilberforce Road CambridgeCB3 0WA United Kingdom Fraunhofer Institute for Algorithms and Scientific Computing Schloss Birlinghoven Sankt-Augustin53757 Germany Institute of Systematic Musicology University of Hamburg Germany Transdisciplinary Research Area: Sustainable Futures University of Bonn Bonn53113 Germany University of Bonn Bonn53113 Germany Department of Computer Science and Engineering Chalmers University of Technology Göteborg412 96 Sweden Department of Computer Science University of Potsdam An der Bahn 2 Potsdam14476 Germany Scientific Computing Laboratory Center for the Study of Complex Systems Institute of Physics Belgrade University of Belgrade Pregrevica 118 Belgrade11080 Serbia The Ohio State University Department of Physics and Electrical and Computer Engineering 191 West Woodruff Ave ColumbusOH43210 United States ResCon Technologies LLC 1275 Kinnear Rd. Suite 239 ColumbusOH43212 United States Trieste Italy Research Group Comparative Neuroscience Leibniz Institute for Neurobiology Magdeburg Germany Theoretical Physics Saarland University Saarbrücken66123 Germany Center for Biophysics Saarland University Saarbrücken66123 Germany Department of Mathematics Imperial College London United Kingdom Center for Adaptive Rationality Max Planck Institute for Human Development Lentzeallee 94 Berlin14195 Germany Max Planck Institute for Brain Research Max-von-Laue-Straße 4 Frankfurt am Main60438 Germany Technical University of Munich School of Life Sciences Alte Akademie 8 Freising85354 Germany Department of Mathematics School of Computation Information and Technology Technical University of Munich Boltzmannstraße 3 Garching bei München8574

Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems like the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges, and give perspectives on future research directions, looking to inspire interdisciplinary approaches. Copyright © 2023, The Authors. All rights reserved.

关键词： Dynamical systems

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Ten new insights in climate science 2024

One Earth

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One Earth 2025年第6期8卷 None页

作者： Schaeffer, Roberto Schipper, E. Lisa F. Ospina, Daniel Mirazo, Paula Alencar, Ane Anvari, Mehrnaz Artaxo, Paulo Biresselioglu, Mehmet Efe Blome, Tanja Boeckmann, Melanie Brink, Ebba Broadgate, Wendy Bustamante, Mercedes Cai, Wenju Canadell, Josep G. Cardinale, Roberto Chidichimo, Maria Paz Ditlevsen, Peter Eicker, Ursula Feron, Sarah Fikru, Mahelet G. Fuss, Sabine Gaye, Amadou T. Gustafsson, Örjan Harring, Niklas He, Cheng Hebden, Sophie Heilemann, Adrian Hirota, Marina Janardhanan, Nandakumar Juhola, Sirkku Jung, Tae Yong Kejun, Jiang Kilkiș, Şiir Kumarasinghe, Nilushi Lapola, David Lee, June-Yi Levis, Carolina Lusambili, Adelaide Maasakkers, Joannes D. MacIntosh, Claire Mahmood, Jemilah Mankin, Justin S. Marchegiani, Pía Martin, Maria Mukherji, Aditi Muñoz-Erickson, Tischa A. Niazi, Zeenat Nyangon, Joseph Pandipati, Santosh Perera, Amarasinghage T.D. Persad, Geeta Persson, Åsa Redman, Aaron Riipinen, Ilona Rockström, Johan Roffe, Sarah Roy, Joyashree Sakschewski, Boris Samset, Bjørn H. Schlosser, Peter Sharifi, Ayyoob Shih, Wan-Yu Sioen, Giles B. Sokona, Youba Stammer, Detlef Suk, Sunhee Thiam, Djiby Thompson, Vikki Tullos, Erin van Westen, René M. Vargas Falla, Ana Maria Vecellio, Daniel J. Worden, John Wu, Henry C. Xu, Chi Yang, Yang Zachariah, Mariam Zhang, Zhen Ziervogel, Gina Federal University of Rio de Janeiro Rio de Janeiro Brazil University of Bonn Bonn Germany Future Earth Secretariat Stockholm Sweden Arizona State University Tempe AZ United States Amazon Environmental Research Institute (IPAM) Brasilia Brazil Fraunhofer Institute for Algorithms and Scientific Computing SCAI St. Augustin Germany Potsdam Institute for Climate Impact Research (PIK) Potsdam Germany University of São Paulo São Paulo Brazil İzmir University of Economics İzmir Turkey Climate Service Center Germany (GERICS) Helmholtz-Zentrum Hereon Hamburg Germany University of Bremen Bremen Germany Lund University Lund Sweden University of Brasilia Brasilia Brazil Ocean University of China Qingdao China Xiamen University Xiamen China Commonwealth Scientific and Industrial Research Organisation (CSIRO) Environment Canberra ACT Australia University College London London United Kingdom National Scientific and Technical Research Council (CONICET) Buenos Aires Argentina National University of San Martin Buenos Aires Argentina University of Copenhagen Copenhagen Denmark Concordia University Montreal QC Canada University of Groningen Groningen Netherlands Missouri University of Science and Technology Rolla MO United States Mercator Research Institute on Global Commons and Climate Change (MCC) Berlin Germany Humboldt-University of Berlin Berlin Germany Cheikh Anta Diop University Dakar Senegal Stockholm University Stockholm Sweden University of Gothenburg Gothenburg Sweden Institute of Epidemiology Helmholtz Zentrum München—German Research Center for Environmental Health (GmbH) Neuherberg Germany European Space Agency (ESA) - European Centre for Space Applications and Telecommunications (ECSAT) Oxford United Kingdom Federal University of Santa Catarina Florianopolis Brazil Institute for Global Environmental Strategies (IGES) Hayama Japan University of Helsinki Helsinki Finland Yonsei University Graduate Seoul South Korea Chinese Academy of Macroeconomic

The years 2023 and 2024 were characterized by unprecedented warming across the globe, underscoring the urgency of climate action. Robust science advice for decision makers on subjects as complex as climate change requires deep cross- and interdisciplinary understanding. However, navigating the ever-expanding and diverse peer-reviewed literature on climate change is enormously challenging for individual researchers. We elicited expert input through an online questionnaire (188 respondents from 45 countries) and prioritized 10 key advances in climate-change research with high policy relevance. The insights span a wide range of areas, from changes in methane and aerosol emissions to the factors shaping citizens’ acceptance of climate policies. This synthesis and communications effort forms the basis for a science-policy report distributed to party delegations ahead of the 29th session of the Conference of the Parties (COP29) to inform their positions and arguments on critical issues, including heat-adaptation planning, comprehensive mitigation strategies, and strengthened governance in energy-transition minerals value chains. © 2025 The Authors

关键词： adaptation climate policy climate science governance just transition mitigation resilience science policy

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