Publications by authors named "Xiangxiang Fan"

Article Synopsis
  • This study introduces a deep-learning denoising method that transforms fiber-optic sensor spectra into 2D images and uses a Cycle-GAN model to improve signal quality.
  • It demonstrates significant improvements in signal-to-noise ratio (SNR), root mean square error (RMSE), and high correlation with original signals compared to traditional denoising methods like wavelet transform and empirical mode decomposition.
  • The proposed algorithm successfully reduces noise across different fiber-optic sensors and shows excellent linearity in temperature response, making fiber-optic sensing more effective for various research and industrial applications.
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The recovery phase of mangrove seedlings in coastal wetland ecosystems can be negatively affected by exposure to external pollutants. This study aimed to investigate the impact of microplastics (MPs) influx, specifically polystyrene (PS) and polymethyl methacrylate (PMMA), on the growth of Aegiceras corniculatum seedlings and their accumulation of heavy metals (HMs). PS and PMMA significantly increased HMs accumulation (up to 21.

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CoO is a P-type metal-oxide semiconductor which can realize acetone detection at a lower temperature, but the lower working temperature brings the enhanced humidity effect. In order to solve the problem of a CoO gas sensor being easily affected by humidity, an acetone-sensing material of CoO mixed with Pr/Zn was prepared by electrospray in this work. The optimal working temperature of Pr/Zn-CoO is 160 °C, and the detection limit can reach 1 ppm.

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Pure NiO nanofibers and the InO-NiO one-dimensional heterogeneous nanofibers were prepared by electrospinning, and the gas sensing properties to acetone were also investigated. Material characterization proved that the heterogeneous nanofibers were composed of InO and NiO, and the nanofibers exhibited an enhanced sensitivity to acetone. At the optimal working temperature, the response of InO-NiO nanofibers to 50 ppm acetone was more than 10 times higher than that of pure NiO nanofibers.

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