The development of efficient, durable, and affordable electrocatalysts is critical for the advancement of a hydrogen economy, particularly in alkaline media. In this study, we propose CoCrFeNi and CoCrFeNiMo high entropy alloys (HEAs) powders as bifunctional electrocatalysts for the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER). While there is a performance gap compared to Pt/C, the prepared samples exhibit relatively good electro-catalytic activity with overpotentials of 156.7 mV and 160.5 mV for HER at 10 mA cm À 2 in a 1.0 M KOH solution, respectively. Notably, the CoCrFeNiMo catalyst demonstrates significantly higher OER activity than commercial RuO 2 with an overpotential of 390 mV at 50 mA cm À 2 , and delivers a cell voltage of 1.86 V at a current density of 10 mA cm À 2 for water splitting.

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：Targeting negative effects such as clarity and contrast degradation and color distortion of images acquired in hazy weather，underwater，and in nighttime environments，a two-stage image restoration meth• od using an improved atmospheric scattering model is proposed. A global compensation coefficient is intro• duced into the traditional atmospheric scattering model to obtain an improved atmospheric scattering mod• el；the two-stage image restoration method based on this model consists of two stages. First，a degraded image is fed to the improved atmospheric scattering model to obtain a coarse restored image. The gray• scale world algorithm is then used to determine the albedo of this coarse restored image. Second，the albe• do and output image of the first stage are fed to the improved atmospheric scattering model to obtain the fi• nal restored image. Experimental results indicate that the proposed method can avoid the problems of color 文章编号 1004-924X (2022)18-2267-13 收稿日期： 2022-04-21； 修订日期： 2022-06-02. 基金项目： 国家自然科学基金项目(No. 61705127， No. U2033218) 第 30 卷 光学 精密工程 distortion and dark tones in the restored images and has good applicability. The method can effectively achieve image dehazing，underwater image restoration，and night image enhancement. The proposed method achieves excellent results in both quantitative and qualitative experiments compared with state-ofthe-art methods.