Reservoir computing with the frequency, phase and amplitude of spin-torque nano-oscillators

Spin-torque nano-oscillators can emulate neurons at the nanoscale. Recent works show that the non-linearity of their oscillation amplitude can be leveraged to achieve waveform classification for an input signal encoded in the amplitude of the input voltage. Here we show that the frequency and the phase of the oscillator can also be used to recognize waveforms. For this purpose, we phase-lock the oscillator to the input waveform, which carries information in its modulated frequency. In this way we considerably decrease amplitude, phase and frequency noise. We show that this method allows classifying sine and square waveforms with an accuracy above 99% when decoding the output from the oscillator amplitude, phase or frequency. We find that recognition rates are directly related to the noise and non-linearity of each variable. These results prove that spin-torque nano-oscillators offer an interesting platform to implement different computing schemes leveraging their rich dynamical features

RF signal classification in hardware with an RF spintronic neural network

Extracting information from radiofrequency (RF) signals using artificial neural networks at low energy cost is a critical need for a wide range of applications. Here we show how to leverage the intrinsic dynamics of spintronic nanodevices called magnetic tunnel junctions to process multiple analogue RF inputs in parallel and perform synaptic operations. Furthermore, we achieve classification of RF signals with experimental data from magnetic tunnel junctions as neurons and synapses, with the same accuracy as an equivalent software neural network. These results are a key step for embedded radiofrequency artificial intelligence.Comment: 8 pages, 5 figure

Systematic experimental comparison of particle filtration efficiency test methods for commercial respirators and face masks

Respirators, medical masks, and barrier face coverings all filter airborne particles using similar physical principles. However, they are tested for certification using a variety of standardized test methods, creating challenges for the comparison of differently certified products. We have performed systematic experiments to quantify and understand the differences between standardized test methods for N95 respirators (NIOSH TEB-APR-STP-0059 under US 42 CFR 84), medical face masks (ASTM F2299/F2100), and COVID-19-related barrier face coverings (ASTM F3502-21). Our experiments demonstrate the role of face velocity, particle properties (mean size, size variability, electric charge, density, and shape), measurement techniques, and environmental preconditioning. The measured filtration efficiency was most sensitive to changes in face velocity and particle charge. Relative to the NIOSH method, users of the ASTM F2299/F2100 method have commonly used non-neutralized (highly charged) aerosols as well as smaller face velocities, each of which may result in approximately 10% higher measured filtration efficiencies. In the NIOSH method, environmental conditioning at elevated humidity increased filtration efficiency in some commercial samples while decreasing it in others, indicating that measurement should be performed both with and without conditioning. More generally, our results provide an experimental basis for the comparison of respirators certified under various international methods, including FFP2, KN95, P2, Korea 1st Class, and DS2.Comment: 34 pages, 8 figures, 3 table

Nanomagnetic intergrowths in Fe-Ni meteoritic metal: The potential for time-resolved records of planetesimal dynamo fields

Nanoscale intergrowths unique to the cloudy zones (CZs) of meteoritic metal display novel magnetic behaviour with the potential to reveal new insight into the early development of magnetic fields on protoplanetary bodies. The nanomagnetic state of the CZ within the Tazewell IIICD iron meteorite has been imaged using off-axis electron holography. The CZ is revealed to be a natural nanocomposite of magnetically hard islands of tetrataenite (ordered FeNi) embedded in a magnetically soft matrix of ordered Fe3Ni. In the remanent state, each tetrataenite island acts as a uniaxial single domain particle with its 001 magnetic easy axis oriented along one of three ?100? crystallographic directions of the parent taenite phase. Micromagnetic simulations demonstrate that switching occurs via the nucleation and propagation of domain walls through individual tetrataenite particles. The switching field (Hs) varies with the length scale of the matrix phase (Lm), with Hs \> 1 T for Lm \~{}10 nm (approaching the intrinsic switching field for isolated single domain tetrataenite) and 0.2 \< H s \< 0.6 T for Lm \~{}30 nm. The reduction in Hs with increasing Lc is caused by exchange coupling between the hard tetrataenite islands and the soft magnetic matrix, which lowers the critical field for domain wall nucleation, providing an explanation for previously observed coercivity variations throughout the {CZ.} Non-random distributions of the tetrataenite easy axes are observed locally throughout the {CZ}, suggesting a magnetic field could have been present during nanostructure formation. This observation demonstrates the potential for stable chemical transformation remanent magnetisation to be encoded by the nanostructure, with variations in the proportions of the six possible magnetisation states reflecting the intensity and relative direction of the magnetic fields present during cooling. According to recent cooling models, the cooling rate of meteoritic metal originating near the surface of differentiated planetesimals was such that the magnetic signal across the {CZ} could potentially record dynamo field intensity and direction variations over time (10{\textendash}100 Ma), which would enable events such as magnetic reversals and the decay of an asteroid dynamo to be observed

Multilayer spintronic neural networks with radio-frequency connections

Spintronic nano-synapses and nano-neurons perform complex cognitive computations with high accuracy thanks to their rich, reproducible and controllable magnetization dynamics. These dynamical nanodevices could transform artificial intelligence hardware, provided that they implement state-of-the art deep neural networks. However, there is today no scalable way to connect them in multilayers. Here we show that the flagship nano-components of spintronics, magnetic tunnel junctions, can be connected into multilayer neural networks where they implement both synapses and neurons thanks to their magnetization dynamics, and communicate by processing, transmitting and receiving radio frequency (RF) signals. We build a hardware spintronic neural network composed of nine magnetic tunnel junctions connected in two layers, and show that it natively classifies nonlinearly-separable RF inputs with an accuracy of 97.7%. Using physical simulations, we demonstrate that a large network of nanoscale junctions can achieve state-of the-art identification of drones from their RF transmissions, without digitization, and consuming only a few milliwatts, which is a gain of more than four orders of magnitude in power consumption compared to currently used techniques. This study lays the foundation for deep, dynamical, spintronic neural networks

The inner junction protein CFAP20 functions in motile and non-motile cilia and is critical for vision

Motile and non-motile cilia are associated with mutually-exclusive genetic disorders. Motile cilia propel sperm or extracellular fluids, and their dysfunction causes primary ciliary dyskinesia. Non-motile cilia serve as sensory/signalling antennae on most cell types, and their disruption causes single-organ ciliopathies such as retinopathies or multi-system syndromes. CFAP20 is a ciliopathy candidate known to modulate motile cilia in unicellular eukaryotes. We demonstrate that in zebrafish, cfap20 is required for motile cilia function, and in C. elegans, CFAP-20 maintains the structural integrity of non-motile cilia inner junctions, influencing sensory-dependent signalling and development. Human patients and zebrafish with CFAP20 mutations both exhibit retinal dystrophy. Hence, CFAP20 functions within a structural/functional hub centered on the inner junction that is shared between motile and non-motile cilia, and is distinct from other ciliopathy-associated domains or macromolecular complexes. Our findings suggest an uncharacterised pathomechanism for retinal dystrophy, and potentially for motile and non-motile ciliopathies in general

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London