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白内障术后非感染性角膜溃疡的研究进展 被引量:3
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作者 何海龙 梁新童 +1 位作者 王进达 万修华 《国际眼科杂志》 CAS 北大核心 2020年第1期65-69,共5页
白内障术后非感染性角膜溃疡作为白内障术后一种罕见的并发症可能与患者的自身免疫情况以及神经营养性角膜上皮病变相关,风湿性疾病、动脉炎、干燥综合征、克罗恩病、结核病、非甾体类抗炎药物的使用等均是白内障术后发生角膜溃疡的高... 白内障术后非感染性角膜溃疡作为白内障术后一种罕见的并发症可能与患者的自身免疫情况以及神经营养性角膜上皮病变相关,风湿性疾病、动脉炎、干燥综合征、克罗恩病、结核病、非甾体类抗炎药物的使用等均是白内障术后发生角膜溃疡的高危因素。本文就白内障术后非感染性角膜溃疡的病例报道和临床表现、发生机制、预防以及处理原则进行综述。 展开更多
关键词 白内障 角膜溃疡 风湿性疾病
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两种Nd∶YAG激光后囊膜切开方式治疗后囊膜混浊的Meta分析
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作者 何海龙 常笛 +3 位作者 周春媛 王进达 曹凯 万修华 《国际眼科杂志》 CAS 北大核心 2020年第10期1764-1768,共5页
目的:系统评价两种Nd∶YAG激光后囊膜切开方式治疗白内障术后后囊膜混浊的效果与安全性,为临床实践中后囊膜切开方式的选择提供可靠依据。方法:计算机检索中文全文期刊数据库(CNKI)、万方数据库、维普数据库、PubMed、Medline、Cochrane... 目的:系统评价两种Nd∶YAG激光后囊膜切开方式治疗白内障术后后囊膜混浊的效果与安全性,为临床实践中后囊膜切开方式的选择提供可靠依据。方法:计算机检索中文全文期刊数据库(CNKI)、万方数据库、维普数据库、PubMed、Medline、Cochrane Library搜集不同Nd∶YAG激光后囊膜切开方式治疗后囊膜混浊的相关文章,检索时限定义为2000-01-01/2019-12-31,2位评价者独立进行文献检索、筛选、质量评价及数据提取,采用RevMan5.3软件进行Meta分析。以均值差(MD)与95%置信区间(CI)衡量计量资料的效应量,对术后最佳矫正视力(BCVA)、术后眼压、激光使用能量进行合并分析。以比值比(OR)衡量计数资料的效应量,对出现人工晶状体受损以及眼前黑影飘动的比例进行合并分析。结果:共纳入7篇研究,包括行Nd∶YAG激光圆形后囊膜切开和十字形后囊膜切开共计432眼。Meta分析结果显示:圆形后囊膜切开组和十字形后囊膜切开组患者术后BCVA无差异(MD=-0.01,95%CI:-0.03~0.01,P=0.32);术后眼压无差异(MD=-0.60,95%CI:-1.31~0.11,P=0.10);使用激光能量无差异(MD=18.82,95%CI:-11.88~49.51,P=0.23);晶状体受损率无差异(OR=0.97,95%CI:0.50~1.87,P=0.93);眼前黑影飘动发生率无差异(OR=2.88,95%CI:0.28~29.26,P=0.37)。结论:在白内障术后发生后囊膜混浊的患者行Nd∶YAG激光后囊膜切开治疗中,圆形后囊膜切开与十字形后囊膜切开在治疗效果与安全性方面均无明显差异。 展开更多
关键词 Nd∶YAG激光 后发性白内障 最佳矫正视力 眼压 并发症
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Enhanced detection of freeze‒thaw induced landslides in Zhidoi county(Tibetan Plateau,China)with Google Earth Engine and image fusion 被引量:1
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作者 Jia-Hui YANG Yan-Chen GAO +5 位作者 Lang JIA Wen-Juan WANG Qing-Bai WU Francis ZVOMUYA Miles DYCK hai-long he 《Advances in Climate Change Research》 SCIE CSCD 2024年第3期476-489,共14页
Freeze‒thaw induced landslides(FTILs)in grasslands on the Tibetan Plateau are a geological disaster leading to soil erosion.These landslides reduce biodiversity and intensify landscape fragmentation,which in turn are ... Freeze‒thaw induced landslides(FTILs)in grasslands on the Tibetan Plateau are a geological disaster leading to soil erosion.These landslides reduce biodiversity and intensify landscape fragmentation,which in turn are strengthen by the persistent climate change and increased anthropogenic activities.However,conventional techniques for mapping FTILs on a regional scale are impractical due to their labor-intensive,costly,and time-consuming nature.This study focuses on improving FTILs detection by implementing image fusion-based Google Earth Engine(GEE)and a random forest algorithm.Integration of multiple data sources,including texture features,index features,spectral features,slope,and vertical‒vertical polarization data,allow automatic detection of the spatial distribution characteristics of FTILs in Zhidoi county,which is located within the Qinghai‒Tibet Engineering Corridor(QTEC).We employed statistical techniques to elucidate the mechanisms influencing FTILs occurrence.The enhanced method identifies two schemes that achieve high accuracy using a smaller training sample(scheme A:94.1%;scheme D:94.5%)compared to other methods(scheme B:50.0%;scheme C:95.8%).This methodology is effective in generating accurate results using only~10%of the training sample size necessitated by other methods.The spatial distribution patterns of FTILs generated for 2021 are similar to those obtained using various other training sample sources,with a primary concentration observed along the central region traversed by the QTEC.The results highlight the slope as the most crucial feature in the fusion images,accounting for 93%of FTILs occurring on gentle slopes ranging from 0°to 14°.This study provides a theoretical framework and technological reference for the identification,monitoring,prevention and control of FTILs in grasslands.Such developments hold the potential to benefit the management of grassland ecosystem,reduce economic losses,and promote grassland sustainability. 展开更多
关键词 Permafrost degradation Random forest Thaw slump Spatial distribution Tibetan Plateau
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Towards an improved prediction of soil-freezing characteristic curve based on extreme gradient boosting model
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作者 Kai-Qi Li hai-long he 《Geoscience Frontiers》 SCIE CAS CSCD 2024年第6期229-243,共15页
As an essential property of frozen soils,change of unfrozen water content(UWC)with temperature,namely soil-freezing characteristic curve(SFCC),plays significant roles in numerous physical,hydraulic and mechanical proc... As an essential property of frozen soils,change of unfrozen water content(UWC)with temperature,namely soil-freezing characteristic curve(SFCC),plays significant roles in numerous physical,hydraulic and mechanical processes in cold regions,including the heat and water transfer within soils and at the land–atmosphere interface,frost heave and thaw settlement,as well as the simulation of coupled thermo-hydro-mechanical interactions.Although various models have been proposed to estimate SFCC,their applicability remains limited due to their derivation from specific soil types,soil treatments,and test devices.Accordingly,this study proposes a novel data-driven model to predict the SFCC using an extreme Gradient Boosting(XGBoost)model.A systematic database for SFCC of frozen soils compiled from extensive experimental investigations via various testing methods was utilized to train the XGBoost model.The predicted soil freezing characteristic curves(SFCC,UWC as a function of temperature)from the well-trained XGBoost model were compared with original experimental data and three conventional models.The results demonstrate the superior performance of the proposed XGBoost model over the traditional models in predicting SFCC.This study provides valuable insights for future investigations regarding the SFCC of frozen soils. 展开更多
关键词 Soil freezing characteristic curve(SFCC) Soil temperature Unfrozen water content XGBoost model Machine Learning Feature importance
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Realizing high thermoelectric performance of Cu and Ce co-doped p-type polycrystalline SnSe via inducing nanoprecipitation arrays 被引量:3
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作者 Yi QIN Tao XIONG +7 位作者 Jian-feng ZHU Yan-ling YANG Hong-rui REN hai-long he Chun-ping NIU Xiao-han LI Me-qian XIE Ting ZHAO 《Journal of Advanced Ceramics》 SCIE EI CAS CSCD 2022年第11期1671-1686,共16页
Thermoelectric(TE)performance of polycrystalline stannous selenide(SnSe)has been remarkably promoted by the strategies of energy band,defect engineering,etc.However,due to the intrinsic insufficiencies of phonon scatt... Thermoelectric(TE)performance of polycrystalline stannous selenide(SnSe)has been remarkably promoted by the strategies of energy band,defect engineering,etc.However,due to the intrinsic insufficiencies of phonon scattering and carrier concentration,it is hard to simultaneously realize the regulations of electrical and thermal transport properties by one simple approach.Herein,we develop Cu and Ce co-doping strategy that can not only greatly reduce lattice thermal conductivity but also improve the electrical transport properties.In this strategy,the incorporated Cu and Ce atoms could induce high-density SnSe_(2) nanoprecipitation arrays on the surface of SnSe microplate,and produce dopant atom point defects and dislocations in its interior,which form multi-scale phonon scattering synergy,thereby presenting an ultralow thermal conductivity of 0.275 W·m^(−1)·K^(−1) at 786 K.Meanwhile,density functional theory(DFT)calculations,carrier concentration,and mobility testing reveal that more extra hole carriers and lower conducting carrier scattering generate after Cu and Ce co-doping,thereby improving the electrical conductivity.The co-doped Sn_(0.98)Cu_(0.01)Ce_(0.01)Se bulk exhibits an excellent ZT value up to~1.2 at 786 K and a high average ZT value of 0.67 from 300 to 786 K.This work provides a simple and convenient strategy of enhancing the TE performance of polycrystalline SnSe. 展开更多
关键词 polycrystalline stannous selenide(SnSe) Cu and Ce co-doping NANOPRECIPITATION ultralow thermal conductivity thermoelectric(TE)performance
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