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Free, publicly-accessible full text available January 1, 2023
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Distributed model training suffers from communication bottlenecks due to frequent model updates transmitted across compute nodes. To alleviate these bottlenecks, practitioners use gradient compression techniques like sparsification, quantization, or low-rank updates. The techniques usually require choosing a static compression ratio, often requiring users to balance the trade-off between model accuracy and per-iteration speedup. In this work, we show that such performance degradation due to choosing a high compression ratio is not fundamental. An adaptive compression strategy can reduce communication while maintaining final test accuracy. Inspired by recent findings on critical learning regimes, in which small gradient errors can have irrecoverablemore »
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Antimicrobial resistance is a well-documented public health concern. The role that drinking water distribution pipes have as sources of antibiotic resistance genes (ARGs) is not well known. Metals are a known stressor for antibiotic resistance development, implying that aging metal-pipe infrastructure could be a source of ARGs. The objective of this study was to determine if ARGs, metal resistance genes (MRGs), and intI 1 were pervasive across various pipe biofilm sample types (biomass surfaces, pipe surfaces, corrosion tubercles, and under corrosion tubercles) and if the resistance genes associated with particular microbial taxa. Eight sample types in triplicate ( n =more »
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Free, publicly-accessible full text available November 1, 2022
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Electron microscopy (EM) enables the reconstruction of neural circuits at the level of individual synapses, which has been transformative for scientific discoveries. However, due to the complex morphology, an accurate reconstruction of cortical axons has become a major challenge. Worse still, there is no publicly available large-scale EM dataset from the cortex that provides dense ground truth segmentation for axons, making it difficult to develop and evaluate large-scale axon reconstruction methods. To address this, we introduce the AxonEM dataset, which consists of two 30x30x30 cubic mm EM image volumes from the human and mouse cortex, respectively. We thoroughly proofread overmore »