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Showing 1–25 of 25 results
Advanced filters: Author: Steven L. Brunton Clear advanced filters
  • Reframing of arousal as a latent dynamical system can reconstruct multidimensional measurements of large-scale spatiotemporal brain dynamics on the timescale of seconds in mice.

    • Ryan V. Raut
    • Zachary P. Rosenthal
    • J. Nathan Kutz
    ResearchOpen Access
    Nature
    P: 1-8
  • It is often advantageous to transform a strongly nonlinear system into a linear one in order to simplify its analysis for prediction and control. Here the authors combine dynamical systems with deep learning to identify these hard-to-find transformations.

    • Bethany Lusch
    • J. Nathan Kutz
    • Steven L. Brunton
    ResearchOpen Access
    Nature Communications
    Volume: 9, P: 1-10
  • The huge amount of data generated in fields like neuroscience or finance calls for effective strategies that mine data to reveal underlying dynamics. Here Brunton et al.develop a data-driven technique to analyze chaotic systems and predict their dynamics in terms of a forced linear model.

    • Steven L. Brunton
    • Bingni W. Brunton
    • J. Nathan Kutz
    ResearchOpen Access
    Nature Communications
    Volume: 8, P: 1-9
  • Dynamics of type I interferon (IFN) following infection with SARS-CoV-2 are critical in determining disease severity in humans but have been difficult to model in mice. Here, infection of genetically diverse mice reveals how delayed or immediate IFN signaling coordinates antiviral immunity.

    • Shelly J. Robertson
    • Olivia Bedard
    • Sonja M. Best
    ResearchOpen Access
    Nature Communications
    Volume: 14, P: 1-13
  • Unlike ubiquitous axial-flow turbines, cross-flow turbines have rotation axes perpendicular to the flow they sit in. This study presents a control scheme that optimizes blade angular velocity as a function of blade position with no extra degrees of freedom, yielding a 59% increase in power output.

    • Benjamin Strom
    • Steven L. Brunton
    • Brian Polagye
    Research
    Nature Energy
    Volume: 2, P: 1-9
  • Solid organ transplant recipients are at increased risk of infectious disease and have unique molecular pathophysiology. Here the authors use host-microbe profiling to assess SARS-CoV-2 infection and immunity in solid organ transplant recipients, showing enhanced viral abundance, impaired clearance, and increased expression of innate immunity genes.

    • Harry Pickering
    • Joanna Schaenman
    • Charles R. Langelier
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-16
  • A global network of researchers was formed to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity; this paper reports 13 genome-wide significant loci and potentially actionable mechanisms in response to infection.

    • Mari E. K. Niemi
    • Juha Karjalainen
    • Chloe Donohue
    ResearchOpen Access
    Nature
    Volume: 600, P: 472-477
  • The dynamics of complex physical systems can be determined by the balance of a few dominant processes. Callaham et al. propose a machine learning approach for the identification of dominant regimes from experimental or numerical data with examples from turbulence, optics, neuroscience, and combustion.

    • Jared L. Callaham
    • James V. Koch
    • Steven L. Brunton
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-10
  • Post-acute sequelae of SARS-CoV-2 (PASC) is still not well understood. Here the authors provide patient reported outcomes from 590 hospitalized COVID-19 patients and show association of PASC with higher respiratory SARS-CoV-2 load and circulating antibody titers, and in some an elevation in circulating fibroblast growth factor 21.

    • Al Ozonoff
    • Naresh Doni Jayavelu
    • Nadine Rouphael
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-17
  • Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

    • Athanasios Kousathanas
    • Erola Pairo-Castineira
    • J. Kenneth Baillie
    ResearchOpen Access
    Nature
    Volume: 607, P: 97-103
  • An analysis of 24,202 critical cases of COVID-19 identifies potentially druggable targets in inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

    • Erola Pairo-Castineira
    • Konrad Rawlik
    • J. Kenneth Baillie
    ResearchOpen Access
    Nature
    Volume: 617, P: 764-768
  • The role of IgG glycosylation in the immune response has been studied, but less is known about IgM glycosylation. Here the authors characterize glycosylation of SARS-CoV-2 spike specific IgM and show that it correlates with COVID-19 severity and affects complement deposition.

    • Benjamin S. Haslund-Gourley
    • Kyra Woloszczuk
    • Mary Ann Comunale
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-19
  • Transonic buffet is a ubiquitous challenge in commercial aviation since it can result in catastrophic structural failure of the aircraft wings. Here, authors experimentally show that this critical aerodynamic phenomenon can be mitigated using a carefully designed porous trailing edge on the wing.

    • Esther Lagemann
    • Steven L. Brunton
    • Christian Lagemann
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-15
  • Three machine learning methods are developed for discovering physically meaningful dimensionless groups and scaling parameters from data, with the Buckingham Pi theorem as a constraint.

    • Joseph Bakarji
    • Jared Callaham
    • J. Nathan Kutz
    Research
    Nature Computational Science
    Volume: 2, P: 834-844
  • Machine learning has enabled major advances in the field of partial differential equations. This Review discusses some of these efforts and other ongoing challenges and opportunities for development.

    • Steven L. Brunton
    • J. Nathan Kutz
    Reviews
    Nature Computational Science
    Volume: 4, P: 483-494
  • Metalens with typical chromatic aberrations, when attached to the distal tip of a conventional endoscope, simultaneously encodes different depths into the RGB channels of a camera at the proximal end.

    • Aamod Shanker
    • Johannes E. Fröch
    • Arka Majumdar
    ResearchOpen Access
    Light: Science & Applications
    Volume: 13, P: 1-14
  • Quantifying the coupling underlying synchronization in forced turbulent oscillator flows through phase-amplitude reduction analysis is typically computationally demanding. Here, the authors propose a data-driven approach coupling Stuart-Landau oscillator models with unknown forcing dynamics and apply it to the study of the wake behind a D-shaped body subject to periodic blowing.

    • Benjamín Herrmann
    • Philipp Oswald
    • Steven L. Brunton
    ResearchOpen Access
    Communications Physics
    Volume: 3, P: 1-9
  • Recent advances in machine learning are enabling progress in several aspects of experimental fluid mechanics. This Perspective article focuses on augmenting the quality of measurement techniques, improving experimental design and enabling real-time estimation and control.

    • Ricardo Vinuesa
    • Steven L. Brunton
    • Beverley J. McKeon
    Reviews
    Nature Reviews Physics
    Volume: 5, P: 536-545
  • Modelling soft-robot deformations induced by actuators and interactions with the surrounding environment can enable full uptake of embodied intelligence. This Technical Review provides a concise guide to modelling approaches and computational strategies that can lead to model-informed design of embodied intelligent robots.

    • Gianmarco Mengaldo
    • Federico Renda
    • Cecilia Laschi
    Reviews
    Nature Reviews Physics
    Volume: 4, P: 595-610
  • Machine learning has been used to accelerate the simulation of fluid dynamics. However, despite the recent developments in this field, there are still challenges to be addressed by the community, a fact that creates research opportunities.

    • Ricardo Vinuesa
    • Steven L. Brunton
    Reviews
    Nature Computational Science
    Volume: 2, P: 358-366