Mathematics and computing

  • Article
    | Open Access

    Every year, hundreds of people die at sea because of vessel accidents, and a key challenge in reducing these fatalities is to make Search and Rescue (SAR) planning more efficient. Here, the authors uncover hidden flow features that attract floating objects, providing specific information for optimal SAR planning.

    • Mattia Serra
    • , Pratik Sathe
    • , Irina Rypina
    • , Anthony Kirincich
    • , Shane D. Ross
    • , Pierre Lermusiaux
    • , Arthur Allen
    • , Thomas Peacock
    •  & George Haller
  • Article
    | Open Access

    It is crucial yet challenging to identify cause-consequence relation in complex dynamical systems where direct causal links can mix with indirect ones. Leng et al. propose a data-driven model-independent method to distinguish direct from indirect causality and test its applicability to real-world data.

    • Siyang Leng
    • , Huanfei Ma
    • , Jürgen Kurths
    • , Ying-Cheng Lai
    • , Wei Lin
    • , Kazuyuki Aihara
    •  & Luonan Chen
  • Article
    | Open Access

    It is generally difficult to scale derived estimates and understand the accuracy across locations for passively-collected data sources, such as mobile phones and satellite imagery. Here the authors show that their trained deep learning models are able to explain 70% of the variation in ground-measured village wealth in held-out countries, outperforming previous benchmarks from high-resolution imagery with errors comparable to that of existing ground data.

    • Christopher Yeh
    • , Anthony Perez
    • , Anne Driscoll
    • , George Azzari
    • , Zhongyi Tang
    • , David Lobell
    • , Stefano Ermon
    •  & Marshall Burke
  • Article
    | Open Access

    Current machine learning classifiers have been applied to whole-genome sequencing data to identify determinants of antimicrobial resistance, but they lack interpretability. Here the authors present a metabolic machine learning classifier that uses flux balance analysis to estimate the biochemical effects of alleles.

    • Erol S. Kavvas
    • , Laurence Yang
    • , Jonathan M. Monk
    • , David Heckmann
    •  & Bernhard O. Palsson
  • Article
    | Open Access

    Electronic Health Records (EHR) are subject to noise, biases and missing data. Here, the authors present MixEHR, a multi-view Bayesian framework related to collaborative filtering and latent topic models for EHR data integration and modeling.

    • Yue Li
    • , Pratheeksha Nair
    • , Xing Han Lu
    • , Zhi Wen
    • , Yuening Wang
    • , Amir Ardalan Kalantari Dehaghi
    • , Yan Miao
    • , Weiqi Liu
    • , Tamas Ordog
    • , Joanna M. Biernacka
    • , Euijung Ryu
    • , Janet E. Olson
    • , Mark A. Frye
    • , Aihua Liu
    • , Liming Guo
    • , Ariane Marelli
    • , Yuri Ahuja
    • , Jose Davila-Velderrain
    •  & Manolis Kellis
  • Article
    | Open Access

    Designing deep learning inference hardware based on in-memory computing remains a challenge. Here, the authors propose a strategy to train ResNet-type convolutional neural networks which results in reduced accuracy loss when transferring weights to in-memory computing hardware based on phase-change memory.

    • Vinay Joshi
    • , Manuel Le Gallo
    • , Simon Haefeli
    • , Irem Boybat
    • , S. R. Nandakumar
    • , Christophe Piveteau
    • , Martino Dazzi
    • , Bipin Rajendran
    • , Abu Sebastian
    •  & Evangelos Eleftheriou
  • Article
    | Open Access

    Population structure enables emergence of cooperation among individuals, but the impact of the dynamic nature of real interaction networks is not understood. Here, the authors study the evolution of cooperation on temporal networks and find that temporality enhances the evolution of cooperation.

    • Aming Li
    • , Lei Zhou
    • , Qi Su
    • , Sean P. Cornelius
    • , Yang-Yu Liu
    • , Long Wang
    •  & Simon A. Levin
  • Article
    | Open Access

    To advance the design of soft robots, novel computational frameworks that accurately model the dynamics of soft material systems are required. Here, the authors report a numerical framework for studying locomotion in limbed soft robots that is based on the discrete elastic rods algorithm.

    • Weicheng Huang
    • , Xiaonan Huang
    • , Carmel Majidi
    •  & M. Khalid Jawed
  • Article
    | Open Access

    The demands on transportation systems continue to grow while the methods for analyzing and forecasting traffic conditions remain limited. Here the authors show a parameter-independent approach for an accurate description, identification and forecasting of spatio-temporal traffic patterns directly from data.

    • A. M. Avila
    •  & I. Mezić
  • Article
    | Open Access

    The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. In that context, the authors present a Deep Neural Network (DNN) that recognizes different abnormalities in ECG recordings which matches or outperform cardiology and emergency resident medical doctors.

    • Antônio H. Ribeiro
    • , Manoel Horta Ribeiro
    • , Gabriela M. M. Paixão
    • , Derick M. Oliveira
    • , Paulo R. Gomes
    • , Jéssica A. Canazart
    • , Milton P. S. Ferreira
    • , Carl R. Andersson
    • , Peter W. Macfarlane
    • , Wagner Meira Jr.
    • , Thomas B. Schön
    •  & Antonio Luiz P. Ribeiro
  • Article
    | Open Access

    Prostate specific antigen (PSA) is a biomarker for prostate cancer. Here, the authors develop a mathematical model where longitudinal changes in PSA levels predict responses to intermittent androgen deprivation in patients with prostate cancer.

    • Renee Brady-Nicholls
    • , John D. Nagy
    • , Travis A. Gerke
    • , Tian Zhang
    • , Andrew Z. Wang
    • , Jingsong Zhang
    • , Robert A. Gatenby
    •  & Heiko Enderling
  • Article
    | Open Access

    Phenomena like imitation, herding and positive feedbacks in the complex financial markets characterize the emergence of endogenous instabilities, which however is still understudied. Here the authors show that the graph-based approach is helpful to timely recognize phases of increasing instability that can drive the system to a new market configuration.

    • Alessandro Spelta
    • , Andrea Flori
    • , Nicolò Pecora
    • , Sergey Buldyrev
    •  & Fabio Pammolli
  • Article
    | Open Access

    Natural hazards can have huge impacts on individuals and societies, however, monitoring the economic recovery in the aftermath of extreme events remains a challenge. Here, the authors find that Facebook posting activity of small businesses can be used to monitor post-disaster economic recovery, and can allow local governments to better target distribution of resources.

    • Robert Eyre
    • , Flavia De Luca
    •  & Filippo Simini
  • Article
    | Open Access

    The authors propose a learning rule for a neuron model with dendrite. In their model, somatodendritic interaction implements self-supervised learning applicable to a wide range of sequence learning tasks, including spike pattern detection, chunking temporal input and blind source separation.

    • Toshitake Asabuki
    •  & Tomoki Fukai
  • Article
    | Open Access

    Multiple access channels model communication from multiple independent senders to a common receiver. By drawing a connection to the study of classical and quantum correlations using nonlocal games, Leditzky et al. reveal remarkably complex behaviour of the entanglement-assisted and unassisted information transmission capabilities of a multiple access channel.

    • Felix Leditzky
    • , Mohammad A. Alhejji
    • , Joshua Levin
    •  & Graeme Smith
  • Article
    | Open Access

    Polymer crosslinking in desalination membranes adds stability on the cost of molecular transportation rates through the membrane. Here the authors tailor crosslinking of desalination membranes to overcome the stability and transport trade-off, and demonstrate a pervaporation desalination thin-film composite membrane with high water flux.

    • Yun Long Xue
    • , Jin Huang
    • , Cher Hon Lau
    • , Bing Cao
    •  & Pei Li
  • Article
    | Open Access

    Unconventional computing architectures might outperform current ones, but their realization has been limited to solving simple specific problems. Here, a network of interconnected Belousov-Zhabotinski reactions, operated by independent magnetic stirrers, performs encoding/decoding operations and data storage.

    • Juan Manuel Parrilla-Gutierrez
    • , Abhishek Sharma
    • , Soichiro Tsuda
    • , Geoffrey J. T. Cooper
    • , Gerardo Aragon-Camarasa
    • , Kevin Donkers
    •  & Leroy Cronin
  • Article
    | Open Access

    Understanding the underlying mechanisms behind the successes of deep networks remains a challenge. Here, the author demonstrates an implicit regularization in training deep networks, showing that the control of complexity in the training is hidden within the optimization technique of gradient descent.

    • Tomaso Poggio
    • , Qianli Liao
    •  & Andrzej Banburski
  • Article
    | Open Access

    Models of emerging epidemics can be exceedingly helpful in planning the response, but early on model selection is a difficult task. Here, the authors explore the joint contribution of age stratification and household structure on epidemic spread, and provides a rule of thumb to guide model choice.

    • Lorenzo Pellis
    • , Simon Cauchemez
    • , Neil M. Ferguson
    •  & Christophe Fraser
  • Article
    | Open Access

    It is hard to design quantum neural networks able to work with quantum data. Here, the authors propose a noise-robust architecture for a feedforward quantum neural network, with qudits as neurons and arbitrary unitary operations as perceptrons, whose training procedure is efficient in the number of layers.

    • Kerstin Beer
    • , Dmytro Bondarenko
    • , Terry Farrelly
    • , Tobias J. Osborne
    • , Robert Salzmann
    • , Daniel Scheiermann
    •  & Ramona Wolf
  • Article
    | Open Access

    Small non-polymeric molecules have tremendous structural diversity that can be used to represent information. Here the authors encode data in synthesized libraries of Ugi products.

    • Christopher E. Arcadia
    • , Eamonn Kennedy
    • , Joseph Geiser
    • , Amanda Dombroski
    • , Kady Oakley
    • , Shui-Ling Chen
    • , Leonard Sprague
    • , Mustafa Ozmen
    • , Jason Sello
    • , Peter M. Weber
    • , Sherief Reda
    • , Christopher Rose
    • , Eunsuk Kim
    • , Brenda M. Rubenstein
    •  & Jacob K. Rosenstein
  • Article
    | Open Access

    The physical limits and reliability of PCR-based random access of DNA encoded data is unknown. Here the authors demonstrate reliable file recovery from as few as ten copies per sequence, providing a data density limit of 17 exabytes per gram.

    • Lee Organick
    • , Yuan-Jyue Chen
    • , Siena Dumas Ang
    • , Randolph Lopez
    • , Xiaomeng Liu
    • , Karin Strauss
    •  & Luis Ceze
  • Article
    | Open Access

    Chronic lymphocytic leukemia is an indolent disease, and many patients succumb to infection rather than the direct effects of the disease. Here, the authors use medical records and machine learning to predict the patients that may be at risk of infection, which may enable a change in the course of their treatment.

    • Rudi Agius
    • , Christian Brieghel
    • , Michael A. Andersen
    • , Alexander T. Pearson
    • , Bruno Ledergerber
    • , Alessandro Cozzi-Lepri
    • , Yoram Louzoun
    • , Christen L. Andersen
    • , Jacob Bergstedt
    • , Jakob H. von Stemann
    • , Mette Jørgensen
    • , Man-Hung Eric Tang
    • , Magnus Fontes
    • , Jasmin Bahlo
    • , Carmen D. Herling
    • , Michael Hallek
    • , Jens Lundgren
    • , Cameron Ross MacPherson
    • , Jan Larsen
    •  & Carsten U. Niemann
  • Article
    | Open Access

    Here, the authors meta-analyze clinical trials comparing adjuvanted and non-adjuvanted influenza vaccines in children and find that oil-in-water emulsion adjuvant improves the efficacy of inactivated influenza vaccines in healthy immunologically naive children.

    • Yu-Ju Lin
    • , Chiao-Ni Wen
    • , Ying-Ying Lin
    • , Wen-Chi Hsieh
    • , Chia-Chen Chang
    • , Yi-Hsuan Chen
    • , Chian-Hui Hsu
    • , Yun-Jui Shih
    • , Chang-Hsun Chen
    •  & Chi-Tai Fang
  • Perspective
    | Open Access

    Artificial intelligence (AI) is becoming more and more common in people’s lives. Here, the authors use an expert elicitation method to understand how AI may affect the achievement of the Sustainable Development Goals.

    • Ricardo Vinuesa
    • , Hossein Azizpour
    • , Iolanda Leite
    • , Madeline Balaam
    • , Virginia Dignum
    • , Sami Domisch
    • , Anna Felländer
    • , Simone Daniela Langhans
    • , Max Tegmark
    •  & Francesco Fuso Nerini
  • Article
    | Open Access

    DNA strand displacement reactions can be difficult to scale up for computational tasks. Here the authors develop DNA switching circuits that achieve high-speed computing with fewer molecules.

    • Fei Wang
    • , Hui Lv
    • , Qian Li
    • , Jiang Li
    • , Xueli Zhang
    • , Jiye Shi
    • , Lihua Wang
    •  & Chunhai Fan
  • Article
    | Open Access

    The use of machine learning for identifying small molecules through their retention time’s predictions has been challenging so far. Here the authors combine a large database of liquid chromatography retention time with a deep learning approach to enable accurate metabolites’s identification.

    • Xavier Domingo-Almenara
    • , Carlos Guijas
    • , Elizabeth Billings
    • , J. Rafael Montenegro-Burke
    • , Winnie Uritboonthai
    • , Aries E. Aisporna
    • , Emily Chen
    • , H. Paul Benton
    •  & Gary Siuzdak
  • Article
    | Open Access

    Aggregation of matter, common in stratified fluid systems, is essential to the carbon cycle and ocean ecology. Although the current understanding of aggregation involves only collision and adhesion, here Camassa et al. reveal a self-assembly phenomenon arising solely from diffusion-induced flows.

    • Roberto Camassa
    • , Daniel M. Harris
    • , Robert Hunt
    • , Zeliha Kilic
    •  & Richard M. McLaughlin
  • Article
    | Open Access

    Technologies for acquiring explainable features from medical images need further development. Here, the authors report a deep learning based automated acquisition of explainable features from pathology images, and show a higher accuracy of their method as compared to pathologist based diagnosis of prostate cancer recurrence.

    • Yoichiro Yamamoto
    • , Toyonori Tsuzuki
    • , Jun Akatsuka
    • , Masao Ueki
    • , Hiromu Morikawa
    • , Yasushi Numata
    • , Taishi Takahara
    • , Takuji Tsuyuki
    • , Kotaro Tsutsumi
    • , Ryuto Nakazawa
    • , Akira Shimizu
    • , Ichiro Maeda
    • , Shinichi Tsuchiya
    • , Hiroyuki Kanno
    • , Yukihiro Kondo
    • , Manabu Fukumoto
    • , Gen Tamiya
    • , Naonori Ueda
    •  & Go Kimura
  • Article
    | Open Access

    Relapse, reinfection and recrudescence can all cause recurrent infection after treatment of Plasmodium vivax malaria in endemic areas, but are difficult to distinguish. Here the authors show that they can be differentiated probabilistically and thereby demonstrate the high efficacy of primaquine treatment in preventing relapse.

    • Aimee R. Taylor
    • , James A. Watson
    • , Cindy S. Chu
    • , Kanokpich Puaprasert
    • , Jureeporn Duanguppama
    • , Nicholas P. J. Day
    • , Francois Nosten
    • , Daniel E. Neafsey
    • , Caroline O. Buckee
    • , Mallika Imwong
    •  & Nicholas J. White
  • Perspective
    | Open Access

    Recent research in motor neuroscience has focused on optimal feedback control of single, simple tasks while robotics and AI are making progress towards flexible movement control in complex environments employing hierarchical control strategies. Here, the authors argue for a return to hierarchical models of motor control in neuroscience.

    • Josh Merel
    • , Matthew Botvinick
    •  & Greg Wayne
  • Article
    | Open Access

    t-SNE is widely used for dimensionality reduction and visualization of high-dimensional single-cell data. Here, the authors introduce a protocol to help avoid common shortcomings of t-SNE, for example, enabling preservation of the global structure of the data.

    • Dmitry Kobak
    •  & Philipp Berens
  • Article
    | Open Access

    Reconstructing system dynamics on complex high-dimensional energy landscapes from static experimental snapshots remains challenging. Here, the authors introduce a framework to infer the essential dynamics of physical and biological systems without need for time-dependent measurements.

    • Philip Pearce
    • , Francis G. Woodhouse
    • , Aden Forrow
    • , Ashley Kelly
    • , Halim Kusumaatmaja
    •  & Jörn Dunkel
  • Article
    | Open Access

    Network properties can be modified when they interact with other networks, yet most previous results have focused on equilibrium states exclusively. Here the authors introduce a framework to examine the out-of-equilibrium dynamics of evolutionary processes to mimic real-world interconnected networks.

    • Javier M. Buldú
    • , Federico Pablo-Martí
    •  & Jacobo Aguirre
  • Article
    | Open Access

    People are able to mentally time travel to distant memories and reflect on the consequences of those past events. Here, the authors show how a mechanism that connects learning from delayed rewards with memory retrieval can enable AI agents to discover links between past events to help decide better courses of action in the future.

    • Chia-Chun Hung
    • , Timothy Lillicrap
    • , Josh Abramson
    • , Yan Wu
    • , Mehdi Mirza
    • , Federico Carnevale
    • , Arun Ahuja
    •  & Greg Wayne
  • Article
    | Open Access

    Methods for dilation are currently limited to specific shapes and curvatures, with the potential for some of the structure's shape to encroach onto the final dilated volume. Here, the authors develop a method for creating dilational structures from arbitrary surfaces that avoids volume encroachment.

    • Freek G. J. Broeren
    • , Werner W. P. J. van de Sande
    • , Volkert van der Wijk
    •  & Just L. Herder
  • Article
    | Open Access

    The spatial structure of a population is often critical for the evolution of cooperation. Here, Allen and colleagues show that when spatial structure is represented by an isothermal graph, the effective number of neighbors per individual determines whether or not cooperation can evolve.

    • Benjamin Allen
    • , Gabor Lippner
    •  & Martin A. Nowak
  • Article
    | Open Access

    Theories state that transitions between extreme waves are allowed but experimental confirmations are lacking because of lack of control strategies. Here, the authors propose and experimentally report, for the first time, the use of topological indices to control the generation of extreme waves.

    • Giulia Marcucci
    • , Davide Pierangeli
    • , Aharon J. Agranat
    • , Ray-Kuang Lee
    • , Eugenio DelRe
    •  & Claudio Conti
  • Article
    | Open Access

    Is there an optimum difficulty level for training? In this paper, the authors show that for the widely-used class of stochastic gradient-descent based learning algorithms, learning is fastest when the accuracy during training is 85%.

    • Robert C. Wilson
    • , Amitai Shenhav
    • , Mark Straccia
    •  & Jonathan D. Cohen
  • Article
    | Open Access

    The use of single-photon data has been limited by time-consuming reconstruction algorithms. Here, the authors combine statistical models and computational tools known from computer graphics and show real-time reconstruction of moving scenes.

    • Julián Tachella
    • , Yoann Altmann
    • , Nicolas Mellado
    • , Aongus McCarthy
    • , Rachael Tobin
    • , Gerald S. Buller
    • , Jean-Yves Tourneret
    •  & Stephen McLaughlin
  • Article
    | Open Access

    The brain can often continue to function despite lesions in many areas, but damage to particular locations may have serious effects. Here, the authors use the concept of Ollivier-Ricci curvature to investigate the robustness of brain networks.

    • Hamza Farooq
    • , Yongxin Chen
    • , Tryphon T. Georgiou
    • , Allen Tannenbaum
    •  & Christophe Lenglet
  • Article
    | Open Access

    Discovery of hybrid dynamical models for real-world cyber-physical systems remains a challenge. This paper proposes a general framework for automating mechanistic modeling of hybrid dynamical systems from observed data with low computational complexity and noise resilience.

    • Ye Yuan
    • , Xiuchuan Tang
    • , Wei Zhou
    • , Wei Pan
    • , Xiuting Li
    • , Hai-Tao Zhang
    • , Han Ding
    •  & Jorge Goncalves
  • Article
    | Open Access

    Viral assembly is a complex process that in tailed bacteriophages involves scaffolding proteins which coordinate assembly of the phage procapsid and are subsequently released during maturation. Here the authors reveal the conformational changes that accompany virion maturation, documenting how the dissociation of scaffold proteins and DNA packaging processes intersect.

    • Athanasios Ignatiou
    • , Sandrine Brasilès
    • , Mehdi El Sadek Fadel
    • , Jörg Bürger
    • , Thorsten Mielke
    • , Maya Topf
    • , Paulo Tavares
    •  & Elena V. Orlova
  • Article
    | Open Access

    Natural creatures, from fish to snake and birds, combine neural control, sensory feedback and compliant mechanics to operate across uncertain environments. Here the authors present a versatile modeling approach to the dynamic simulation of their architectures based on the assembly of Cosserat rods.

    • Xiaotian Zhang
    • , Fan Kiat Chan
    • , Tejaswin Parthasarathy
    •  & Mattia Gazzola
  • Article
    | Open Access

    The scale and dimensionality of imaging data means information is commonly overlooked. Here, using recurrent neural networks we understand temporal dependencies in hyperspectral imagery, enabling the observation of differences in ferroelectric switching mechanisms in PbZr0.2Ti0.8O3 thin films due to formation of charged domain walls.

    • Joshua C. Agar
    • , Brett Naul
    • , Shishir Pandya
    • , Stefan van der Walt
    • , Joshua Maher
    • , Yao Ren
    • , Long-Qing Chen
    • , Sergei V. Kalinin
    • , Rama K. Vasudevan
    • , Ye Cao
    • , Joshua S. Bloom
    •  & Lane W. Martin
  • Article
    | Open Access

    The extent to which brain structure and function are coupled remains a complex question. Here, the authors show that coupling strength between structural connectivity and functional activity can be quantified and reveals a cortical gradient spanning from lower-level sensory areas to high-level cognitive ones.

    • Maria Giulia Preti
    •  & Dimitri Van De Ville
  • Article
    | Open Access

    Though conductivity doping in organic semiconductors has been widely studied in organic electronics, a clear mechanistic picture that explains the phenomenon is still lacking. Here, the authors report a theoretical approach to elucidate the role of disorder compensation in doped organic materials.

    • Artem Fediai
    • , Franz Symalla
    • , Pascal Friederich
    •  & Wolfgang Wenzel
  • Article
    | Open Access

    The inverse DFT problem of mapping the ground-state density to its exchange correlation potential has been numerically challenging so far. Here, the authors propose an approach for an accurate solution to the inverse DFT problem, enabling the evaluation of exact exchange and correlation potential from an ab initio density.

    • Bikash Kanungo
    • , Paul M. Zimmerman
    •  & Vikram Gavini