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您的检索式：作者名="Yuying Huo"
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| 1 | A 42-yr soil erosion record inferred from mineral magnetism of reservoir sediments in a small carbonate-rock catchment, Guizhou Plateau, southwest China显示文摘 | Hongya Wang Yuying Huo Lingyun Zeng Xiouqin Wu Yunlong Cai | 2008 | Journal of Paleolimnology2008，，3： | 1 |
| 2 | Hybrid energy harvesting systems for self-powered sustainable water purification by harnessing ambient energy显示文摘The development of self-powered water purification technologies for decentralized applications is crucial for ensuring the provision of drinking water in resource-limited regions. The elimination of the dependence on external energy inputs and the attainment of self-powered status significantly expands the applicability of the treatment system in real-world scenarios. Hybrid energy harvesters, which convert multiple ambient energies simultaneously, show the potential to drive self-powered water purification facilities under fluctuating actual conditions. Here, we propose recent advancements in hybrid energy systems that simultaneously harvest various ambient energies (e.g., photo irradiation, flow kinetic, thermal, and vibration) to drive water purification processes. The mechanisms of various energy harvesters and point-of-use water purification treatments are first outlined. Then we summarize the hybrid energy harvesters that can drive water purification treatment. These hybrid energy harvesters are based on the mechanisms of mechanical and photovoltaic, mechanical and thermal, and thermal and photovoltaic effects. This review provides a comprehensive understanding of the potential for advancing beyond the current state-of-the-art of hybrid energy harvester-driven water treatment processes. Future endeavors should focus on improving catalyst efficiency and developing sustainable hybrid energy harvesters to drive self-powered treatments under unstable conditions (e.g., fluctuating temperatures and humidity). | Zhengyang Huo Young Jun Kim Yuying Chen Tianyang Song Yang Yang Qingbin Yuan Sang Woo Kim | 2023 | Frontiers of Environmental Science & Engineering2023，17，10： | 0 |
| 3 | Integrating multi-modal information to detect spatial domains of spatial transcriptomics by graph attention network显示文摘Recent advances in spatially resolved transcriptomic technologies have enabled unprecedented opportunities to elucidate tissue architecture and function in situ.Spatial transcriptomics can provide multimodal and complementary information simultaneously,including gene expression profiles,spatial locations,and histology images.However,most existing methods have limitations in efficiently utilizing spatial information and matched high-resolution histology images.To fully leverage the multi-modal information,we propose a SPAtially embedded Deep Attentional graph Clustering(SpaDAC)method to identify spatial domains while reconstructing denoised gene expression profiles.This method can efficiently learn the low-dimensional embeddings for spatial transcriptomics data by constructing multi-view graph modules to capture both spatial location connectives and morphological connectives.Benchmark results demonstrate that SpaDAC outperforms other algorithms on several recent spatial transcriptomics datasets.SpaDAC is a valuable tool for spatial domain detection,facilitating the comprehension of tissue architecture and cellular microenvironment.The source code of SpaDAC is freely available at Github(http://gffzz188fe103f8f1460ascfuqv50qf0n660kb.ffgz.tsg.suse.edu.cn/huoyuying/SpaDAC.git). | Yuying Huo Yilang Guo Jiakang Wang Huijie Xue Yujuan Feng Weizheng Chen Xiangyu Li | 2023 | Journal of Genetics and Genomics2023，50，9： | 0 |
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