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| Open AccessMaterials informatics for self-assembly of functionalized organic precursors on metal surfaces
Bottom-up fabrication via on-surface molecular self-assembly is a useful way to make nanomaterials, but finding appropriate precursor molecules for a given structure remains a challenge. Here the authors present an informatics technique linking self-assembled structures with precursor properties, helping identify molecules for target nanomaterials.
- Daniel M. Packwood
- & Taro Hitosugi
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| Open AccessScalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
Artificial neural networks are artificial intelligence computing methods which are inspired by biological neural networks. Here the authors propose a method to design neural networks as sparse scale-free networks, which leads to a reduction in computational time required for training and inference.
- Decebal Constantin Mocanu
- , Elena Mocanu
- & Antonio Liotta
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| Open AccessEfficient and self-adaptive in-situ learning in multilayer memristor neural networks
Memristor-based neural networks hold promise for neuromorphic computing, yet large-scale experimental execution remains difficult. Here, Xia et al. create a multi-layer memristor neural network with in-situ machine learning and achieve competitive image classification accuracy on a standard dataset.
- Can Li
- , Daniel Belkin
- & Qiangfei Xia
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| Open AccessWhen optimization for governing human-environment tipping elements is neither sustainable nor safe
Economic optimization in environmental governance was criticized for delivering short-term gains at the expense of long-term environmental degradation. Here, the authors use a stylized model of human-environment tipping elements to show no paradigm guarantees fulfilling another paradigm.
- Wolfram Barfuss
- , Jonathan F. Donges
- & Jürgen Kurths
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| Open AccessInferring collective dynamical states from widely unobserved systems
From infectious diseases to brain activity, complex systems can be approximated using autoregressive models. Here, the authors show that incomplete sampling can bias estimates of the stability of such systems, and introduce a novel, unbiased metric for use in such situations.
- Jens Wilting
- & Viola Priesemann
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| Open AccessConcurrence of form and function in developing networks and its role in synaptic pruning
How structure and function coevolve in developing brains is little understood. Here, the authors study a coupled model of network development and memory, and find that due to the feedback networks with some initial memory capacity evolve into heterogeneous structures with high memory performance.
- Ana P. Millán
- , J. J. Torres
- & J Marro
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| Open AccessExploring patterns enriched in a dataset with contrastive principal component analysis
Dimensionality reduction and visualization methods lack a principled way of comparing multiple datasets. Here, Abid et al. introduce contrastive PCA, which identifies low-dimensional structures enriched in one dataset compared to another and enables visualization of dataset-specific patterns.
- Abubakar Abid
- , Martin J. Zhang
- & James Zou
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| Open AccessSignal and noise extraction from analog memory elements for neuromorphic computing
The application of resistive and phase-change memories in neuromorphic computation will require efficient methods to quantify device-to-device and switching variability. Here, the authors assess the impact of a broad range of device switching mechanisms using machine learning regression techniques.
- N. Gong
- , T. Idé
- & T. Ando
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| Open AccessBayesian model selection for complex dynamic systems
Systematic changes in stock market prices or in the migration behaviour of cancer cells may be hidden behind random fluctuations. Here, Mark et al. describe an empirical approach to identify when and how such real-world systems undergo systematic changes.
- Christoph Mark
- , Claus Metzner
- & Ben Fabry
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| Open AccessAerodynamic generation of electric fields in turbulence laden with charged inertial particles
How lightning occurs in dusty atmospheres remains largely unknown because of the complexity of the turbulent flows involved. Di Renzo and Urzay reveal a flow-driven mechanism of charge separation by simulating turbulence laden with hundreds of millions of electrically charged inertial particles.
- M. Di Renzo
- & J. Urzay
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| Open AccessVariation in Wolbachia effects on Aedes mosquitoes as a determinant of invasiveness and vectorial capacity
Wolbachia infection in mosquitoes reduces dengue virus spread under specific lab conditions, prompting its use in disease control. Here, King et al. show that Wolbachia increases mean and variance in mosquito susceptibility and explain how this affects Wolbachia invasion and dengue transmission.
- Jessica G. King
- , Caetano Souto-Maior
- & M. Gabriela M. Gomes
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Article
| Open AccessMulticomponent reactions provide key molecules for secret communication
Designing molecular keys and combining advanced encryption standard cryptography with molecular steganography is a secure way for encoding messages. Here, the authors use the Ugi four-component reaction of perfluorinated acids to create a library of 500,000 molecular keys for encryption and decryption.
- Andreas C. Boukis
- , Kevin Reiter
- & Michael A. R. Meier
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Article
| Open AccessSnap evaporation of droplets on smooth topographies
Droplet evaporation control has applications in inkjet printing and surface patterning. Here, the authors show that on slippery curved substrates droplets evaporate by slowly retracting and then suddenly snapping, which can be exploited to design surfaces that control an evaporation sequence.
- Gary G. Wells
- , Élfego Ruiz-Gutiérrez
- & Rodrigo Ledesma-Aguilar
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| Open AccessInstability of expanding bacterial droplets
Sokolov et al. have previously shown how bacteria are expelled in response to a rotating microparticle. Here the authors find that when the microparticle is spun at much higher rotation rates bacteria are trapped around it and then are expelled radially upon rotation cessation in an explosion-like manner.
- Andrey Sokolov
- , Leonardo Dominguez Rubio
- & Igor S. Aranson
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| Open AccessMemory effects can make the transmission capability of a communication channel uncomputable
In information theory one is interested in how much information can be reliably sent over noisy communication channels. Here the authors show that for channels with memory the optimal rate of information transmission is uncomputable.
- David Elkouss
- & David Pérez-García
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| Open AccessToward a universal decoder of linguistic meaning from brain activation
Previous work decoding linguistic meaning from imaging data has generally been limited to a small number of semantic categories. Here, authors show that a decoder trained on neuroimaging data of single concepts sampling the semantic space can robustly decode meanings of semantically diverse new sentences with topics not encountered during training.
- Francisco Pereira
- , Bin Lou
- & Evelina Fedorenko
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| Open AccessInput–output maps are strongly biased towards simple outputs
Algorithmic information theory measures the complexity of strings. Here the authors provide a practical bound on the probability that a randomly generated computer program produces a given output of a given complexity and apply this upper bound to RNA folding and financial trading algorithms.
- Kamaludin Dingle
- , Chico Q. Camargo
- & Ard A. Louis
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| Open AccessGeneralized leaky integrate-and-fire models classify multiple neuron types
Simplified neuron models, such as generalized leaky integrate-and-fire (GLIF) models, are extensively used in network modeling. Here the authors systematically generate and compare GLIF models of varying complexity for their ability to classify cell types in the Allen Cell Types Database and faithfully reproduce spike trains.
- Corinne Teeter
- , Ramakrishnan Iyer
- & Stefan Mihalas
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| Open AccessDirect measurement of superdiffusive energy transport in disordered granular chains
Wave propagation is often nonlinear in character, yet the interplay between disorder and nonlinearity remains elusive. Kim et al. use experiments and corroborating numerical simulations to investigate this phenomenon and demonstrate superdiffusive energy transport in disordered granular chains.
- Eunho Kim
- , Alejandro J. Martínez
- & Jinkyu Yang
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| Open AccessAbsence of warmth permits epigenetic memory of winter in Arabidopsis
Plants use multiple cues to monitor seasonal temperatures. Here, the authors show that Arabidopsis requires not only prolonged cold, but the absence of temperature spikes above 15 °C to epigenetically silence FLC during winter.
- Jo Hepworth
- , Rea L. Antoniou-Kourounioti
- & Caroline Dean
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| Open AccessStatistical modeling of RNA structure profiling experiments enables parsimonious reconstruction of structure landscapes
Different experimental and computational approaches can be used to study RNA structures. Here, the authors present a computational method for data-directed reconstruction of complex RNA structure landscapes, which predicts a parsimonious set of co-existing structures and estimates their abundances from structure profiling data.
- Hua Li
- & Sharon Aviran
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| Open AccessOptimal compressed representation of high throughput sequence data via light assembly
Increase in high throughput sequencing (HTS) data warrants compression methods to facilitate better storage and communication. Here, Ginart et al. introduce Assembltrie, a reference-free compression tool which is guaranteed to achieve optimality for error-free reads.
- Antonio A. Ginart
- , Joseph Hui
- & David N. Tse
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| Open AccessCrosstalk in concurrent repeated games impedes direct reciprocity and requires stronger levels of forgiveness
Social interactions among people are often repeated, and yet it is assumed that simultaneous interactions are independent from one another. Here, Reiter and colleagues describe a conceptual framework where an action in one game can influence the decision in another.
- Johannes G. Reiter
- , Christian Hilbe
- & Martin A. Nowak
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| Open AccessMatched asymptotic solution for crease nucleation in soft solids
Our understanding of material instabilities in soft solids remains elusive mainly due to the mathematical challenges in capturing localised phenomena within nonlinear elastic materials. Ciarletta develops an analytical theory to describe the nucleation threshold of creases in agreement with experiments.
- P. Ciarletta
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| Open AccessPractical device-independent quantum cryptography via entropy accumulation
The security of DIQKD is difficult to prove, as one needs to take into account every possible attack strategy. Here, the authors develop a method to determine the entropy of a system as the sum of the entropies of its parts. Applied to DIQKD, this implies that it suffices to consider i.i.d. attacks.
- Rotem Arnon-Friedman
- , Frédéric Dupuis
- & Thomas Vidick
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| Open AccessDiversity of meso-scale architecture in human and non-human connectomes
Meso-scale architecture of connectomes is usually modeled as segregated clusters and communities. Here the authors report that non-assortative 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
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| Open AccessA general and flexible method for signal extraction from single-cell RNA-seq data
Single-cell RNA sequencing (scRNA-seq) data provides information on transcriptomic heterogeneity within cell populations. Here, Risso et al develop ZINB-WaVE for low-dimensional representations of scRNA-seq data that account for zero inflation, over-dispersion, and the count nature of the data.
- Davide Risso
- , Fanny Perraudeau
- & Jean-Philippe Vert
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| 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 machine-learning 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
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| 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
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| 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
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| 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
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| Open AccessOscillators that sync and swarm
Collective self-organized 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 self-organized states.
- Kevin P. O’Keeffe
- , Hyunsuk Hong
- & Steven H. Strogatz
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| 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 8-22, becomes increasingly specialized locally and is optimized for network control.
- Evelyn Tang
- , Chad Giusti
- & Danielle S. Bassett
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| Open AccessTemporal profiles of avalanches on networks
Cascade propagation models represent a range of processes on networks, such as power-grid 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
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| Open AccessTemporal correlation detection using computational phase-change memory
New computing paradigms, such as in-memory computing, are expected to overcome the limitations of conventional computing approaches. Sebastian et al. report a large-scale demonstration of computational phase change memory (PCM) by performing high-level computational primitives using one million PCM devices.
- Abu Sebastian
- , Tomas Tuma
- & Evangelos Eleftheriou
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| 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
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| 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 data-driven method that determines relevant timescales for the dynamics and uses it to identify communities.
- Tiago P. Peixoto
- & Martin Rosvall
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| Open AccessMergeable nervous systems for robots
Robots that can self-assemble 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
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| 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, steady-state movement patterns. Here, the authors develop a method to quantify movement predictability, and apply the method to study escape-related movement in several species of desert rodents.
- Talia Y. Moore
- , Kimberly L. Cooper
- & Ramanarayan Vasudevan
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| Open AccessAn autonomous organic reaction search engine for chemical reactivity
While automated reaction systems typically work for the synthesis of pre-defined 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 multi-reagent, multistep reaction system.
- Vincenza Dragone
- , Victor Sans
- & Leroy Cronin
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| 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 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
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| Open AccessAmazonian forest-savanna bistability and human impact
Deforestation and edge effects around cleared areas impact forest stability. Here, the authors examine human impacts on Amazonian forest-savanna 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
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| Open AccessQuantifying similarity of pore-geometry 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 top-performers.
- Yongjin Lee
- , Senja D. Barthel
- & Berend Smit
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| Open AccessSelf-folding 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
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| Open AccessQuantum vertex model for reversible classical computing
Solutions of computations can be encoded in the ground state of many-body 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
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| Open AccessPointwise error estimates in localization microscopy
Super-resolution 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
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| Open AccessActive matter logic for autonomous microfluidics
Active fluids consist of self-driven 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
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| Open AccessHuman seizures couple across spatial scales through travelling wave dynamics
The authors record both local and long-range neural activity during human epileptic seizures to study the underlying multi-scale 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.
- L-E Martinet
- , G. Fiddyment
- & M. A. Kramer
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| Open AccessDynamics and universal scaling law in geometrically-controlled 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