Publications by authors named "Fuxiang Huang"

Foundation model, trained on a diverse range of data and adaptable to a myriad of tasks, is advancing healthcare. It fosters the development of healthcare artificial intelligence (AI) models tailored to the intricacies of the medical field, bridging the gap between limited AI models and the varied nature of healthcare practices. The advancement of a healthcare foundation model (HFM) brings forth tremendous potential to augment intelligent healthcare services across a broad spectrum of scenarios.

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Droplets that can be steered and rebound off surfaces are fundamentally interesting and important due to their promising potential in numerous applications, such as anti-icing and -fogging, spray coating, and self-cleaning. Heterogeneous wettability surfaces have been shown to be an effective means of droplet manipulation. This paper combines numerical simulation with theoretical analysis to investigate the dynamics of two droplets training impacting on and bouncing off a heterogeneous surface (superhydrophobic substrate decorated with a hydrophilic strip).

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Unsupervised domain adaptation (UDA) intends to transfer knowledge from a labeled source domain to an unlabeled target domain. Many current methods focus on learning feature representations that are both discriminative for classification and invariant across domains by simultaneously optimizing domain alignment and classification tasks. However, these methods often overlook a crucial challenge: the inherent conflict between these two tasks during gradient-based optimization.

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Multimode emission of Mn for multimode fluorescence anticounterfeiting is achieved by cation site and interstitial occupancy in CaMgGeO. The rings in CaMgGeO have a significant distortion for Mn ions to enter the ring interstitials with a luminescence center at 665 nm, which is supported by XRD refinement results and first-principles calculations. The interstitial Mn ion has good thermal stability with an activation energy of 0.

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Learning to hash has been widely applied for image retrieval due to the low storage and high retrieval efficiency. Existing hashing methods assume that the distributions of the retrieval pool (i.e.

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Existing hashing methods have yielded significant performance in image and multimedia retrieval, which can be categorized into two groups: shallow hashing and deep hashing. However, there still exist some intrinsic limitations among them. The former generally adopts a one-step strategy to learn the hashing codes for discovering the discriminative binary feature, but the latent discriminative information in the learned hashing codes is not well exploited.

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Data from an in situ monitoring network and five ozone sondes are analysed during August of 2012, and a high tropospheric ozone episode is observed around the 8th of AUG. The Community Multi-scale Air Quality (CMAQ) model and its process analysis tool were used to study factors and mechanisms for high ozone mixing ratio at different levels of ozone vertical profiles. A sensitive scenario without chemical initial and boundary conditions (ICBCs) from MOZART4-GEOS5 was applied to study the impact of stratosphere-troposphere exchange (STE) on vertical ozone.

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We report a high-performance amorphous Indium-Gallium-Zinc-Oxide (a-IGZO) thin-film transistor (TFT) with new copper-chromium (Cu-Cr) alloy source/drain electrodes. The TFT shows a high mobility of 39.4 cm 2 ·V - 1 ·s - 1 a turn-on voltage of -0.

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