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| 1 | Shadow–highlight feature matching automatic small crater recognition using high-resolution digital orthophoto map from Chang’E Missions显示文摘This paper introduces a new method of small lunar craters’ automatic identification, using digital orthophoto map(DOM) data. The core of the approach is the fact that the lunar exploration DOM data reveal contrasting highlight and shadow characteristics of small craters under sunlight irradiation. This research effort combines image processing and mathematical modeling. Overall it proposes a new planetary data processing approach, to segment and extract the highlight and shadow regions of small craters,using the image gray frequency(IGF) statistical method.IGF can also be applied to identify the coupling relationships between small craters’ shape and their relative features. This paper presents the highlight and shadow pair matching(HSPM) model which manages to perform highprecision automatic recognition of small lunar craters.Testing was performed using the DOM data of Chang’E-2(CE-2). The results have shown that the proposed method has a high level of successful detection rate. The proposed methodology that uses DOM data can complement the drawbacks of the digital elevation model(DEM) that has a relatively high false detection rate. A hybrid fusion model(FUM) that combines both DOM and DEM data, was carried out to simultaneously identify small, medium, and large-sized craters. It has been proven that the FUM generally shows stronger recognition ability compared to previous approaches and it can be adapted for high precision identification of craters on the whole lunar surface.The results meet the requirements for a reliable and accurate exploration of the Moon and the planets. | Wei Zuo Chunlai Li Lingjie Yu Zhoubin Zhang Rongwu Wang Xingguo Zeng Yuxuan Liu Yaying Xiong | 2019 | Acta Geochimica2019，38，4： | 1 |
| 2 | Tributyltin causes generational neurodevelopmental toxicity and the protective effect of folic acid in zebrafish显示文摘Tributyltin(TBT),a common organotin environmental pollutant,may pose a threat to human development during critical early-life periods.We aimed to assess the neurodevelopmental intergenerational toxicity of early-life exposure to TBT and the protective effect of DNA methyl donor folic acid(FA).Specifically,after early-life exposure(1–21 days postfertilization,dpf)to TBT(0,1,10 and 100 ng/L),zebrafish(Danio rerio)were cultured in clean medium until sexual maturity.The exposed females were mated with unexposed males to produce embryos(F1).The F1 generation were cultured(4–120 hours post-fertilization,hpf)with and without 1 mmol/L FA.The neurotoxic effects of early-life TBT exposure for zebrafish and their offspring(F1)were significantly enhanced anxiety and reduced aggression,decreased gene expression of DNA methyltransferase in the brain and increased serotonin levels in the body.Moreover,the intergenerational neurodevelopmental toxicity,as manifested in the F1 generation,was attenuated by FA supplementation.In summary,early-life TBT exposure led to intergenerational neurodevelopmental deficits in zebrafish,and DNA methyl donors had a protective effect on F1 neurodevelopment,which can inform the prevention and treatment of intergenerational neurotoxicity due to organotin pollutants. | Haoxing Cai Naying Zheng Chen Tang Yuxuan Zhang Zhenghong Zuo Chengyong He | 2024 | Journal of Environmental Sciences2024，，3： | 0 |
| 3 | A review on ultra-small undoped MoS2 as advanced catalysts for renewable fuel production显示文摘Molybdenum disulfide(MoS2)has garnered significant attention in the field of catalysis due to the high density of active sites in its unique two-dimensional(2D)structure,which could be developed into numerous high-performance catalysts.The synthesis of ultra-small MoS2 particles(<10 nm)is highly desired in various experimental studies.The ultra-small structure could often lead to a distinct S-Mo coordination state and nonstoichiometric composition in MoSx,minimizing in-plane active sites of the 2D structure and making it probable to regulate the atomic and electronic structure of its intrinsic active sites on a large extent,especially in MoSx clusters.This article summarizes the recent progress of catalysis over ultra-small undoped MoS2 particles for renewable fuel production.Through a systematic review of their synthesis,structural,and spectral characteristics,as well as the relationship between their catalytic performance and inherent defects,we aim to provide insights into catalysis over this matrix that may potentially enable advancement in the development of high-performance MoS2-based catalysts for sustainable energy generation in the future. | Guoping Liu Lingling Ding Yuxuan Meng Ahmad Ali Guifu Zuo Xianguang Meng Kun Chang Oi Lun Li Jinhua Ye | 2024 | Carbon Energy2024，6，2： | 0 |
| 4 | Building Better Full Manganese‑Based Cathode Materialsfor Next‑Generation Lithium‑Ion Batteries显示文摘Lithium-manganese-oxides have been exploited as promising cathode materials for many years due to their environmental friendliness,resource abundance and low biotoxicity.Nevertheless,inevitable problems,such as Jahn-Teller distortion,manganese dissolution and phase transition,still frustrate researchers;thus,progress in full manganese-based cathode materials(FMCMs)has been relatively slow and limited in recent decades.Recently,with the fast growth of vehicle electrification and large-scale energy-storage grids,there has been an urgent demand to develop novel FMCMs again;actually,new waves of research based on FMCMs are being created.Herein,we systematically review the history of FMCMs,correctly describe their structures,evaluate the advantages and challenges,and discuss the resolution strategies and latest developments.Additionally,beyond FMCMs,a profound discussion of current controversial issues,such as oxygen redox reaction,voltage decay and voltage hysteresis in Li_(2)MnO_(3)-based cathode materials,is also presented.This review summarizes the effectively optimized approaches and offers a few new possible enhancement methods from the perspective of the electronic-coordination-crystal structure for building better FMCMs for next-generation lithium-ion batteries. | Jin Song Hangchao Wang Yuxuan Zuo Kun Zhang Tonghuan Yang Yali Yang Chuan Gao Tao Chen Guang Feng Zewen Jiang Wukun Xiao Tie Luo Dingguo Xia | 2023 | Electrochemical Energy Reviews2023，6，1： | 0 |
| 5 | Physics-informed deep learning for fringe pattern analysis显示文摘Recently,deep learning has yielded transformative success across optics and photonics,especially in optical metrology.Deep neural networks (DNNs) with a fully convolutional architecture (e.g.,U-Net and its derivatives) have been widely implemented in an end-to-end manner to accomplish various optical metrology tasks,such as fringe denoising,phase unwrapping,and fringe analysis.However,the task of training a DNN to accurately identify an image-to-image transform from massive input and output data pairs seems at best naive,as the physical laws governing the image formation or other domain expertise pertaining to the measurement have not yet been fully exploited in current deep learning practice.To this end,we introduce a physics-informed deep learning method for fringe pattern analysis (PI-FPA) to overcome this limit by integrating a lightweight DNN with a learning-enhanced Fourier transform profilometry (Le FTP) module.By parameterizing conventional phase retrieval methods,the Le FTP module embeds the prior knowledge in the network structure and the loss function to directly provide reliable phase results for new types of samples,while circumventing the requirement of collecting a large amount of high-quality data in supervised learning methods.Guided by the initial phase from Le FTP,the phase recovery ability of the lightweight DNN is enhanced to further improve the phase accuracy at a low computational cost compared with existing end-to-end networks.Experimental results demonstrate that PI-FPA enables more accurate and computationally efficient single-shot phase retrieval,exhibiting its excellent generalization to various unseen objects during training.The proposed PI-FPA presents that challenging issues in optical metrology can be potentially overcome through the synergy of physics-priors-based traditional tools and data-driven learning approaches,opening new avenues to achieve fast and accurate single-shot 3D imaging. | Wei Yin Yuxuan Che Xinsheng Li Mingyu Li Yan Hu Shijie Feng Edmund Y.Lam Qian Chen Chao Zuo | 2024 | Opto-Electronic Advances2024，7，1： | 0 |
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