Article

Open Access


Article
 Open AccessDiversity of mesoscale architecture in human and nonhuman connectomes
Mesoscale architecture of connectomes is usually modeled as segregated clusters and communities. Here the authors report that nonassortative communities are better able to capture the functional connectivity for some networks and offer measures of community diversity that predict cognitive performance.
 Richard F. Betzel
 , John D. Medaglia
 & Danielle S. Bassett

Article
 Open AccessA general and flexible method for signal extraction from singlecell RNAseq data
Singlecell RNA sequencing (scRNAseq) data provides information on transcriptomic heterogeneity within cell populations. Here, Risso et al develop ZINBWaVE for lowdimensional representations of scRNAseq data that account for zero inflation, overdispersion, and the count nature of the data.
 Davide Risso
 , Fanny Perraudeau
 & JeanPhilippe Vert

Article
 Open AccessCooperating with machines
Artificial intelligence is now superior to humans in many fully competitive games, such as Chess, Go, and Poker. Here the authors develop a machinelearning algorithm that can cooperate effectively with humans when cooperation is beneficial but nontrivial, something humans are remarkably good at.
 Jacob W. Crandall
 , Mayada Oudah
 & Iyad Rahwan

Article
 Open AccessAbrupt transitions in time series with uncertainties
Most time series techniques tend to ignore data uncertainties, which results in inaccurate conclusions. Here, Goswami et al. represent time series as a sequence of probability density functions, and reliably detect abrupt transitions by identifying communities in probabilistic recurrence networks.
 Bedartha Goswami
 , Niklas Boers
 & Jürgen Kurths

Article
 Open AccessOcean forecasting of mesoscale features can deteriorate by increasing model resolution towards the submesoscale
The degree to which increasing the resolution of ocean models to consider submesoscale dynamics will improve prediction of mesoscale features remains uncertain. Here, via data assimilation experiments, the authors show higher resolution models do not necessarily provide improved dynamical solutions.
 Paul A. Sandery
 & Pavel Sakov

Article
 Open AccessTo infinity and some glimpses of beyond
Certain physical problems such as the rupture of a thin sheet can be difficult to solve as computations breakdown at the point of rupture. Here the authors propose a regularization approach to overcome this breakdown which could help dealing with mathematical models that have finite time singularities.
 Panayotis G. Kevrekidis
 , Constantinos I. Siettos
 & Yannis G. Kevrekidis

Article
 Open AccessOscillators that sync and swarm
Collective selforganized behavior can be observed in a variety of systems such as colloids and microswimmers. Here O’Keeffe et al. propose a model of oscillators which move in space and tend to synchronize with neighboring oscillators and outline five types of collective selforganized states.
 Kevin P. O’Keeffe
 , Hyunsuk Hong
 & Steven H. Strogatz

Article
 Open AccessDevelopmental increases in white matter network controllability support a growing diversity of brain dynamics
Human brain development is characterized by an increased control of neural activity, but how this happens is not well understood. Here, authors show that white matter connectivity in 882 youth, aged 822, becomes increasingly specialized locally and is optimized for network control.
 Evelyn Tang
 , Chad Giusti
 & Danielle S. Bassett

Article
 Open AccessTemporal profiles of avalanches on networks
Cascade propagation models represent a range of processes on networks, such as powergrid blackouts and epidemic outbreaks. Here the authors investigate temporal profiles of avalanches and show how nonsymmetric average avalanche shapes can occur at criticality.
 James P. Gleeson
 & Rick Durrett

Article
 Open AccessTemporal correlation detection using computational phasechange memory
New computing paradigms, such as inmemory computing, are expected to overcome the limitations of conventional computing approaches. Sebastian et al. report a largescale demonstration of computational phase change memory (PCM) by performing highlevel computational primitives using one million PCM devices.
 Abu Sebastian
 , Tomas Tuma
 & Evangelos Eleftheriou

Article
 Open AccessPariah moonshine
Classifying groups is an important challenge in mathematics and has led to the identification of groups which do not belong to the main families. Here Duncan et al. introduce a type of moonshine which is a connection between these groups, number theory and potentially physics.
 John F. R. Duncan
 , Michael H. Mertens
 & Ken Ono

Article
 Open AccessModelling sequences and temporal networks with dynamic community structures
The description of temporal networks is usually simplified in terms of their dynamic community structures, whose identification however relies on a priori assumptions. Here the authors present a datadriven method that determines relevant timescales for the dynamics and uses it to identify communities.
 Tiago P. Peixoto
 & Martin Rosvall

Article
 Open AccessMergeable nervous systems for robots
Robots that can selfassemble into different morphologies are desired to perform tasks that require different physical capabilities. Mathews et al. design robots whose bodies and control systems can merge and split to form new robots that retain full sensorimotor control and act as a single entity.
 Nithin Mathews
 , Anders Lyhne Christensen
 & Marco Dorigo

Article
 Open AccessUnpredictability of escape trajectory explains predator evasion ability and microhabitat preference of desert rodents
Biomechanical understanding of animal gait and maneuverability has primarily been limited to species with more predictable, steadystate movement patterns. Here, the authors develop a method to quantify movement predictability, and apply the method to study escaperelated movement in several species of desert rodents.
 Talia Y. Moore
 , Kimberly L. Cooper
 & Ramanarayan Vasudevan

Article
 Open AccessAn autonomous organic reaction search engine for chemical reactivity
While automated reaction systems typically work for the synthesis of predefined molecules, automated systems to discover reactivity are more challenging. Here the authors report an autonomous organic reaction search engine that allows discovery of the most reactive pathways in a multireagent, multistep reaction system.
 Vincenza Dragone
 , Victor Sans
 & Leroy Cronin

Article
 Open AccessChaos as an intermittently forced linear system
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 datadriven 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

Article
 Open AccessAmazonian forestsavanna bistability and human impact
Deforestation and edge effects around cleared areas impact forest stability. Here, the authors examine human impacts on Amazonian forestsavanna bistability and show that tree cover bimodality is enhanced in regions close to human activities and is nearly absent in regions unaffected by human activities.
 Bert Wuyts
 , Alan R. Champneys
 & Joanna I. House

Article
 Open AccessQuantifying similarity of poregeometry in nanoporous materials
Pore structure plays an important role in dictating gas storage performance for nanoporous materials. Here, Smit and colleagues develop a topological approach to quantify pore structure similarity, and exploit the resulting descriptor to screen for materials that possess structural similarities with topperformers.
 Yongjin Lee
 , Senja D. Barthel
 & Berend Smit

Article
 Open AccessSelffolding origami at any energy scale
Origami is widely practiced in the design of foldable structures for smart applications and usually consists of stiff sheets that only deform along prescribed creases. Pinsonet al. take a statistical physics approach to design and characterize arbitrary patterns as a function of folding energy.
 Matthew B. Pinson
 , Menachem Stern
 & Arvind Murugan

Article
 Open AccessQuantum vertex model for reversible classical computing
Solutions of computations can be encoded in the ground state of manybody spin models. Here the authors show that solutions to generic reversible classical computations can be encoded in the ground state of a vertex model, which can be reached without finite temperature phase transitions.
 C. Chamon
 , E. R. Mucciolo
 & Z.C. Yang

Article
 Open AccessPointwise error estimates in localization microscopy
Superresolution localization microscopy produces biophysical information in the form of estimated positions of single molecules. Here, Lindénet al. estimate the uncertainty of single localizations, and show that this additional information can improve data analysis and localization precision.
 Martin Lindén
 , Vladimir Ćurić
 & Johan Elf

Article
 Open AccessActive matter logic for autonomous microfluidics
Active fluids consist of selfdriven particles that can drive spontaneous flow without the intervention of external forces. Here Woodhouseet al. show how to design logic circuits using this phenomenon in active fluid networks, which could be further exploited for autonomous microfluidic computing.
 Francis G. Woodhouse
 & Jörn Dunkel

Article
 Open AccessHuman seizures couple across spatial scales through travelling wave dynamics
The authors record both local and longrange neural activity during human epileptic seizures to study the underlying multiscale dynamics. They find that coupling of activity across spatial scales increases during seizures through propagating waves that are fit by a model that combines neural activity and potassium concentration dynamics.
 LE Martinet
 , G. Fiddyment
 & M. A. Kramer

Article
 Open AccessDynamics and universal scaling law in geometricallycontrolled sessile drop evaporation
Drop evaporation can be used as a fabrication technology for targeted particle deposition or microflow control, yet previous research is limited to spherical drops. Here, Sáenzet al. generalize the evaporation dynamics for arbitrary drop geometry and show its potential for more sophisticated control.
 P. J. Sáenz
 , A. W. Wray
 & K. Sefiane

Article
 Open AccessHidden topological constellations and polyvalent charges in chiral nematic droplets
Once a purely mathematical discipline, topology has become an essential tool to investigate physical phenomena such as topological states in liquid crystals. Posnjaket al. observe the existence of 3D point defects of higher than unit topological charge in thermally quenched chiral nematic droplets.
 Gregor Posnjak
 , Simon Čopar
 & Igor Muševič

Article
 Open AccessPathways towards instability in financial networks
The spread of instabilities in financial systems, similarly to ecosystems, is influenced by topological features of the underlying network structures. Here the authors show, independently of specific financial models, that market integration and diversification can drive the system towards instability.
 Marco Bardoscia
 , Stefano Battiston
 & Guido Caldarelli

Article
 Open AccessLocal selfuniformity in photonic networks
The interaction between photonic bandgap materials and light is largely determined by the wavelengthscale material structure. Here, Sellerset al. develop a new metric of network structural order and demonstrate its connection to the photonic bandgap of an amorphous gyroid network.
 Steven R. Sellers
 , Weining Man
 & Marian Florescu

Article
 Open AccessUnravelling raked linear dunes to explain the coexistence of bedforms in complex dunefields
Raked linear dunes are a rare dune type, but the mechanisms for growth have not been constrained. Here, the authors show that a tridirectional wind regime is required to enable this extremely rare dune type to develop, where the raked pattern may develop preferentially on the leeward side.
 Ping Lü
 , Clément Narteau
 & Sylvain Courrech du Pont

Article
 Open AccessLocal dimensionality determines imaging speed in localization microscopy
Localisation microscopy enables nanometrescale imaging of biological samples, but the method is too slow to use on dynamic systems. Here, the authors develop a mathematical model that optimises the number of frames required and estimates the maximum speed for superresolution imaging.
 Patrick FoxRoberts
 , Richard Marsh
 & Susan Cox

Article
 Open AccessQuantumchemical insights from deep tensor neural networks
Machine learning is an increasingly popular approach to analyse data and make predictions. Here the authors develop a ‘deep learning’ framework for quantitative predictions and qualitative understanding of quantummechanical observables of chemical systems, beyond properties trivially contained in the training data.
 Kristof T. Schütt
 , Farhad Arbabzadah
 & Alexandre Tkatchenko

Article
 Open AccessQuantification of network structural dissimilarities
Identifying and quantifying dissimilarities among graphs is a problem of practical importance, but current approaches are either limited or computationally demanding. Here, the authors propose an efficiently computable measure for network comparison that can identify structural topological differences.
 Tiago A. Schieber
 , Laura Carpi
 & Martín G. Ravetti

Article
 Open AccessRegulation of persistent sodium currents by glycogen synthase kinase 3 encodes daily rhythms of neuronal excitability
It is not clear how circadian biochemical cascades are encoded into neural electrical signals. Here, using a combination of electrophysiology and modelling approaches in mice, the authors show activation of glycogen synthase kinase 3 modulates neural activity in the suprachiasmatic nuclei via regulation of the persistent sodium current, INaP.
 Jodi R. Paul
 , Daniel DeWoskin
 & Karen L. Gamble

Article
 Open AccessCompetition among networks highlights the power of the weak
Network science and game theory have been traditionally combined to analyse interactions between nodes of a network. Here, the authors model competition for importance among networks themselves, and reveal dominance of the underdogs in the fate of networksofnetworks.
 Jaime Iranzo
 , Javier M. Buldú
 & Jacobo Aguirre

Article
 Open AccessUnsupervised vectorbased classification of singlemolecule charge transport data
The stochastic nature of singlemolecule charge transport measurements requires collection of large data sets to capture their full complexity. Here, the authors adopt strategies from machine learning for the unsupervised classification of singlemolecule charge transport data without a prioriassumptions.
 Mario Lemmer
 , Michael S. Inkpen
 & Tim Albrecht

Article
 Open AccessThe backtracking survey propagation algorithm for solving random KSAT problems
The Ksatisfability problem is a combinatorial discrete optimization problem, which for K=3 is NPcomplete, and whose random formulation is of interest for understanding computational complexity. Here, the authors introduce the backtracking survey propagation algorithm for studying it for K=3 and K=4.
 Raffaele Marino
 , Giorgio Parisi
 & Federico RicciTersenghi

Article
 Open AccessUnsupervised learning in probabilistic neural networks with multistate metaloxide memristive synapses
Artificial neural networks exhibit learning abilities and can perform tasks which are tricky for conventional computing systems, such as pattern recognition. Here, Serb et al. show experimentally that memristor arrays can learn reversibly from noisy data thanks to sophisticated learning rules.
 Alexander Serb
 , Johannes Bill
 & Themis Prodromakis

Article
 Open AccessTerahertz timegated spectral imaging for content extraction through layered structures
Terahertz radiation may be used to nondestructively detect and study defects and structures within materials. Here the authors use terahertz timegated spectral imaging to extract occluded text from paper pages with subwavelength spacing.
 Albert RedoSanchez
 , Barmak Heshmat
 & Ramesh Raskar

Article
 Open AccessCapacity estimates for optical transmission based on the nonlinear Fourier transform
Optical fibres enable highspeed communication over long distances, but traditional systems are limited by nonlinear optical effects. Here, the authors quantify the increase in capacity that is made possible by using an alternative approach that uses a nonlinear Fourier transform.
 Stanislav A. Derevyanko
 , Jaroslaw E. Prilepsky
 & Sergei K. Turitsyn

Article
 Open AccessPrediction of allosteric sites and mediating interactions through bondtobond propensities
Allostery is a key molecular mechanism underpinning control and modulation in a variety of cellular processes. Here, the authors present a method that can be used to predict allosteric sites and the mediating interactions that connect them to the active site of the protein.
 B. R. C. Amor
 , M. T. Schaub
 & M. Barahona

Article
 Open AccessThermodynamics of freezing and melting
Melting is a classic firstorder phase transition, but an accurate thermodynamic description is still lacking. Here, Pedersen et al. develop a theory, validated by simulations of the LennardJones system, for the melting thermodynamics applicable to all systems characterized by hidden scale invariance.
 Ulf R. Pedersen
 , Lorenzo Costigliola
 & Jeppe C. Dyre

Article
 Open AccessVortex knots in tangled quantum eigenfunctions
Strings or long chains are prone to knotting. Here, the authors demonstrate that the vortex structure of quantum wavefunctions, such as that in a simple harmonic oscillator, can also contain knots, whose topological complexity can be a descriptor of the spatial order of the system.
 Alexander J. Taylor
 & Mark R. Dennis

Article
 Open AccessFaulttolerant error correction with the gauge color code
Construction of a scalable quantum computer requires errorcorrecting codes to overcome the errors introduced by noise. Here, the authors develop a decoding algorithm for the gauge color code, and obtain its threshold values when physical errors and measurement faults are included.
 Benjamin J. Brown
 , Naomi H. Nickerson
 & Dan E. Browne

Article
 Open AccessToughness and strength of nanocrystalline graphene
Graphene is known to be a remarkably strong material, but it can often contain defects. Here, the authors use largescale simulations and continuum modelling to show that the statistical variation in toughness and strength of polycrystalline graphene can be understood with 'weakestlink' statistics.
 Ashivni Shekhawat
 & Robert O. Ritchie

Article
 Open AccessSpatiotemporal propagation of cascading overload failures in spatially embedded networks
Overload failures propagate through hidden functional dependencies across networked systems. Here, the authors study the spatiotemporal propagation behaviour of cascading overload failures, and find that they spread radially from their origin with an approximately constant velocity.
 Jichang Zhao
 , Daqing Li
 & Shlomo Havlin

Article
 Open AccessAn eventbased architecture for solving constraint satisfaction problems
Constraint satisfaction problems are typically solved using conventional von Neumann computing architectures, which are however illsuited to solving them. Here, the authors present a prototype for an eventbased architecture that yield state of the art performance on random SAT problems.
 Hesham Mostafa
 , Lorenz K. Müller
 & Giacomo Indiveri

Article
 Open AccessThe minimal work cost of information processing
Irreversible computation cannot be performed without a work cost, and energy dissipation imposes limitations on devices' performances. Here the authors show that the minimal work requirement of logical operations is given by the amount of discarded information, measured by entropy.
 Philippe Faist
 , Frédéric Dupuis
 & Renato Renner

Article
 Open AccessChemical reaction mechanisms in solution from brute force computational Arrhenius plots
Obtaining activation entropies and enthalpies of a reaction is important for distinguishing between alternative reaction mechanisms. Here the authors use computational methods to accurately obtain the enthalpic/entropic components of the activation free energy for hydrolytic deamination reactions.
 Masoud Kazemi
 & Johan Åqvist

Article 
Ranking in interconnected multilayer networks reveals versatile nodes
A challenging problem is to identify the most central agents in interconnected multilayer networks. Here, De Domenico et al. present a mathematical framework to calculate centrality in such networks—versatility—and rank nodes accordingly.
 Manlio De Domenico
 , Albert SoléRibalta
 & Alex Arenas

Article 
A Bayesian modelling framework for tornado occurrences in North America
Tornadoes are one of nature’s most hazardous phenomena, yet prognostic tools for tornado occurrence are lacking. Here, the authors use Bayesian inference techniques to evaluate the spatiotemporal relationship between atmospheric variables and tornado activity in North America.
 Vincent Y.S. Cheng
 , George B. Arhonditsis
 & Heather Auld