39 research outputs found

    Neuromorphic Few-Shot Learning: Generalization in Multilayer Physical Neural Networks

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    Neuromorphic computing leverages the complex dynamics of physical systems for computation. The field has recently undergone an explosion in the range and sophistication of implementations, with rapidly improving performance. Neuromorphic schemes typically employ a single physical system, limiting the dimensionality and range of available dynamics - restricting strong performance to a few specific tasks. This is a critical roadblock facing the field, inhibiting the power and versatility of neuromorphic schemes. Here, we present a solution. We engineer a diverse suite of nanomagnetic arrays and show how tuning microstate space and geometry enables a broad range of dynamics and computing performance. We interconnect arrays in parallel, series and multilayered neural network architectures, where each network node is a distinct physical system. This networked approach grants extremely high dimensionality and enriched dynamics enabling meta-learning to be implemented on small training sets and exhibiting strong performance across a broad taskset. We showcase network performance via few-shot learning, rapidly adapting on-the-fly to previously unseen tasks

    A Collaborative Research Manifesto! An Early Career Response to Uncertainties

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    Social researchers have been adapting methods and practices in response to COVID-19. In the wake of these adaptations, but still in the midst of intersecting crises that the pandemic has exacerbated or shifted (e.g. health-social-political-economic), researchers face a future suffused with methodological uncertainties. This paper presents a Collaborative Research Manifesto that responds to this by promoting markers for mean-ingful collaborations in future research. The manifesto was co-written primarily through a series of workshops and events that were designed to identify challenges within, and potential for, collaborative research. Through this exploratory collaborative qualitative process, we highlight what the future of such research could look like and describe methodo-logical commitments that collaborative researchers should embody. The discussion draws on wider methodological literature to articulate the key role that ‘collaborative research’ can offer in uncertain times whilst being sensitive of the limitations of our assertive and radical programme

    A Riemannian Approach to Reduced Plate, Shell, and Rod Theories

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    We derive a dimensionally-reduced limit theory for an nn-dimensional nonlinear elastic body that is slender along kk dimensions. The starting point is to view an elastic body as an nn-dimensional Riemannian manifold together with a not necessarily isometric W1,2W^{1,2}-immersion in nn-dimensional Euclidean space. The equilibrium configuration is the immersion that minimizes the average discrepancy between the induced and intrinsic metrics. The dimensionally reduced limit theory views the elastic body as a kk-dimensional Riemannian manifold along with an isometric W2,2W^{2,2}-immersion in nn-dimensional Euclidean space and linear data in the normal directions. The equilibrium configuration minimizes a functional depending on the average covariant derivatives of the linear data. The dimensionally-reduced limit is obtained using a Γ\Gamma-convergence approach. The limit includes as particular cases plate, shell, and rod theories. It applies equally to "standard" elasticity and to "incompatible" elasticity, thus including as particular cases so-called non-Euclidean plate, shell, and rod theories.Comment: 61 pages, added references, fixed typo

    The state of the Martian climate

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    60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

    Lysyl-tRNA synthetase as a drug target in malaria and cryptosporidiosis

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    Malaria and cryptosporidiosis, caused by apicomplexan parasites, remain major drivers of global child mortality. New drugs for the treatment of malaria and cryptosporidiosis, in particular, are of high priority; however, there are few chemically validated targets. The natural product cladosporin is active against blood- and liver-stage; Plasmodium falciparum; and; Cryptosporidium parvum; in cell-culture studies. Target deconvolution in; P. falciparum; has shown that cladosporin inhibits lysyl-tRNA synthetase (; Pf; KRS1). Here, we report the identification of a series of selective inhibitors of apicomplexan KRSs. Following a biochemical screen, a small-molecule hit was identified and then optimized by using a structure-based approach, supported by structures of both; Pf; KRS1 and; C. parvum; KRS (; Cp; KRS). In vivo proof of concept was established in an SCID mouse model of malaria, after oral administration (ED; 90; = 1.5 mg/kg, once a day for 4 d). Furthermore, we successfully identified an opportunity for pathogen hopping based on the structural homology between; Pf; KRS1 and; Cp; KRS. This series of compounds inhibit; Cp; KRS and; C. parvum; and; Cryptosporidium hominis; in culture, and our lead compound shows oral efficacy in two cryptosporidiosis mouse models. X-ray crystallography and molecular dynamics simulations have provided a model to rationalize the selectivity of our compounds for; Pf; KRS1 and; Cp; KRS vs. (human); Hs; KRS. Our work validates apicomplexan KRSs as promising targets for the development of drugs for malaria and cryptosporidiosis

    The James Webb Space Telescope Mission

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    Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least 4m4m. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the 6.5m6.5m James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

    Genetic mechanisms of critical illness in COVID-19.

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    Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

    Audio Classification with Skyrmion Reservoirs

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    Physical reservoir computing is a computational paradigm that enables spatiotemporal pattern recognition to be performed directly in matter. The use of physical matter leads the way toward energy‐efficient devices capable of solving machine learning problems without having to build a system of millions of interconnected neurons. Proposed herein is a high‐performance “skyrmion mixture reservoir” that implements the reservoir computing model with multidimensional inputs. This implementation solves spoken digit classification tasks with an overall model accuracy of 97.4% and a < 1% word error ratethe best performance ever reported for in materio reservoir computers. Due to the quality of the results and the low‐power properties of magnetic texture reservoirs, it is evident that skyrmion fabrics are a compelling candidate for reservoir computing
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