One of the primary clinical observations for screening the infectious by the novel coronavirus is capturing a chest x-ray image. In most of the patients, a chest x-ray contains abnormalities, such as consolidation, wh...
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Super-resolution microscopy, or nanoscopy, enables the use of fluorescent-based molecular localization tools to study molecular structure at the nanoscale level in the intact cell, bridging the mesoscale gap to classi...
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In this paper, we propose two novel algorithms for histogram specification and quantile transformation of data without local information. These are core techniques that can serve as building blocks for applications th...
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We report an array-based smartphone sensor for multiplex detection and quantitation of lead and mercury ions in drinking water without the addition of any solution reagent. The detection limits for lead and mercury ar...
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In medical image analysis, the long-range spatial features are often not accurately obtained by the traditional convolutional neural networks. Hence, we propose a TransClaw U-Net network structure. The transformer par...
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In medical image analysis, the long-range spatial features are often not accurately obtained by the traditional convolutional neural networks. Hence, we propose a TransClaw U-Net network structure. The transformer part is added after three convolution operations to fuse shallow features extracted by convolution operations for maximally encoding the long-range spatial features between patches. The “Claw” in TransClaw U-net means that we add the bottom upsampling part to retain the deepest feature information for detail segmentation. In addition, the modified three-channel global attention mechanism to blend the outputs of three channels (the encoding part, the bottom upsampling part and the decoding part) to effectively extract image contours. The experimental results on Synapse Multi-organ Segmentation Dataset show that TransClaw U-Net performs better than other networks. The results of ablation experiments prove the effectiveness of the three improved components of the network and influence of input image size and skip-connection numbers on network performance. The source code will be publicly available once the paper is accepted.
Forecasting global foreign trade is essential for developing government trade policies and management strategies for multinational corporations. However, achieving an accurate trade forecast is challenging because of ...
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The localized release of energy at the surface of plasma-exposed materials plays a crucial role in many plasma-driven processes. Unfortunately, the interaction between low-temperature plasmas and surfaces is both poor...
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The localized release of energy at the surface of plasma-exposed materials plays a crucial role in many plasma-driven processes. Unfortunately, the interaction between low-temperature plasmas and surfaces is both poorly understood and difficult to characterize. Here, we use Raman thermometry to measure the temperature of graphene during plasma exposure. We observe a significant increase in the graphene temperature even for modest input plasma powers. These results suggest that two-dimensional materials are effective surface probes for the quantitative characterization of plasma-induced heating effects and for further investigation of the plasma-surface interaction.
To contain the spread of the virus and stop the overcrowding of hospitalized patients, the coronavirus pandemic crippled healthcare facilities, mandating lockdowns and promoting remote work. As a result, telehealth ha...
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The Mekong River Basin (MRB) is crucial for the livelihoods of over 60 million people across six Southeast Asian countries. Understanding long-term sediment changes is crucial for management and contingency plans, but...
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