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Land use/cover change effects on floods with different return periods： a case study of Beijing, China

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Frontiers of Environmental Science & Engineering 2013年第5期7卷 769-776页

作者： yueling wang Xiaoliu YANG Key Laboratory of Water Cycle and Related Land Surface Processes Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China College of Urban and Environmental Sciences Peking University Beijing 100871 China

In this study, an approach integrating digital land use/cover change （LUCC） analysis, hydraulic model- ing and statistical methods was applied to quantify the effect of LUCC on floods in terms of inundation extent, flood arrival time and maximum water depth. The study took Beijing as an example and analyzed five specific floods with return periods of 20-year, 50-year, 100-year, 1000-year and 10000-year on the basis of LUCC over a nine-year period from 1996 to 2004. The analysis reveals that 1） during the period of analysis Beijing experienced unprecedented LUCC; 2） LUCC can affect inundation extent and flood arrival time, and floods with longer return periods are more influenced; 3） LUCC can affect maximum water depth and floods with shorter return periods are more influenced; and 4） LUCC is a major flood security stressor for Beijing. It warns that those cities having experienced rapid expansion during recent decades in China are in danger of more serious floods and recommends that their actual land use patterns should be carefully assessed considering flood security. This inte- grated approach is demonstrated to he a useful tool for joint assessment, planning and management of land and water.

关键词： inundation extent flood arrival time maximum water depth shallow flow model

Impact of environmental factors on water quality at multiple spatial scales and its spatial variation in Huai River Basin, China

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Science China Earth Sciences 2018年第1期61卷 82-92页

作者： XIA Jun wang LongFeng YU JingJie ZHAN CheSheng ZHANG YongYong QIAO YunFeng wang yueling Key Laboratory of Water Cycle & Related Land Surface Processes Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China University of Chinese Academy of Sciences Belting 100049 China State Key Laboratory of Water Resources & Hydropower Engineering Science Wuhan University Wuhan 430072 China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China

Quantitative assessment of water quality and its spatial variation identification, as well as the discernment of primary factors affecting water quality are in its urgent in water environment management. In this study, four key water quality indicators,namely, ammonia nitrogen(NH_4^+-N), permanganate index(COD_(Mn)), total phosphorus(TP) and total nitrogen(TN) at 71 sampling sites were selected to evaluate water quality and its spatial variation identification. More concerns were emphasized on the anthropogenic factors(land use pattern) and natural factors(river density, elevation and precipitation) to quantify the overall water quality variations at different spatial scales. Results showed that the Yi-Shu-Si River sub-basin had a better water quality status than the Huai River sub-basin. The moderate polluted area nearly distributed in the upper and middle reaches of the Shaying River and Guo River. The high cluster centers which were surrounded with COD_(Mn), NH_4^+-N, TN and TP mainly also distributed in the upper and middle reaches of the Shaying River and Guo River. Redundancy analysis showed that the 200 m buffer area acted as the most sensitive area, which was easily subjected to pollution. The precipitation was identified as the most important variables among all the studied hydrological units, followed by farmland, urban land or elevation. The point source pollution was still existed although the non-point source pollution was also identified. The urban surface runoff pollution was severer than farmland fertilizer loss at the sub-basin scale in flood season, while the farmland showed "small-scale" effects for explaining overall water quality variations. This research is helpful for identifying the overall water quality variations from the scale-process interactions and providing a scientific basis for pollution control and decision making for the Huai River Basin.

关键词： Fuzzy comprehensive assessment Environmental factors Moran's I Redundancy analysis Pearson's correlation analysis Huai River Basin

Water quality prediction based on sparse dataset using enhanced machine learning

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Environmental Science and Ecotechnology 2024年第4期20卷 218-228页

作者： Sheng Huang Jun Xia yueling wang Jiarui Lei Gangsheng wang State Key Laboratory of Water Resources Engineering and Management Wuhan UniversityWuhan 430072China Institute for Water-Carbon Cycles and Carbon Neutrality Wuhan UniversityWuhan 430072China Department of Civil and Environmental Engineering National University of Singapore117578 Singapore Key Laboratory of Water Cycle and Related Land Surface Processes Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China

Water quality in surface bodies remains a pressing issue *** some regions have rich water quality data,less attention is given to areas that lack sufficient ***,it is crucial to explore novel ways of managing source-oriented surface water pollution in scenarios with infrequent data collection such as weekly or *** we showed sparse-dataset-based prediction of water pollution using machine *** investigated the efficacy of a traditional Recurrent Neural Network alongside three Long Short-Term Memory(LSTM)models,integrated with the Load Estimator(LOADEST).The research was conducted at a river-lake confluence,an area with intricate hydrological *** found that the Self-Attentive LSTM(SA-LSTM)model outperformed the other three machine learning models in predicting water quality,achieving Nash-Sutcliffe Efficiency(NSE)scores of 0.71 for COD_(Mn)and 0.57 for NH_(3)N when utilizing LOADEST-augmented water quality data(referred to as the SA-LSTMLOADEST model).The SA-LSTM-LOADEST model improved upon the standalone SA-LSTM model by reducing the Root Mean Square Error(RMSE)by 24.6%for COD_(Mn)and 21.3%for NH_(3)***,the model maintained its predictive accuracy when data collection intervals were extended from weekly to ***,the SA-LSTM-LOADEST model demonstrated the capability to forecast pollution loads up to ten days in *** study shows promise for improving water quality modeling in regions with limited monitoring capabilities.

关键词： Water quality modeling Sparse measurement River-lake confluence Long short-term memory Load estimator Machine learning

SOX11 as a potential prognostic biomarker in hepatocellular carcinoma linked to immune infiltration and ferroptosis

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Chinese Journal of Cancer Research 2024年第4期36卷 378-397页

作者： Hongyu Chen Qiangguo Ao yueling wang Yue Qian Qingli Cheng Wei Zhang Department of Nephrology the Second Medical Center of PLA General HospitalNational Clinical Research Center for Geriatric DiseasesBeijing 100853China Clinical Laboratory the First Affiliated Hospital of Henan UniversityKaifeng 475000China Cell Biology Department Wuxi School of MedicineJiangnan UniversityWuxi 214122China Department of Pathogen Biology Guizhou Nursing Vocational CollegeGuiyang 550000China

Objective:SOX11 is expressed in numerous malignancies,including hepatocellular carcinomas(HCC),but its oncogenic function has not been ***,we performed a comprehensive bioinformatics analysis of the Liver Hepatocellular Carcinoma(LIHC)dataset to investigate the function of SOX11 in ***:SOX11 expression data from The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)were validated by immunohistochemistry(IHC).Co-expression,differential expression,and functional analyses utilized TCGA-LIHC,Timer 2.0,Metascape,GTEx,and LinkedOmics *** with immune infiltration,ferroptosis,and immune checkpoint genes were *** changes were explored via *** regression,receiver operating characteristic curve(ROC),Kaplan-Meier analysis,and nomogram modeling evaluated associations with HCC clinicopathological ***11’s impact on proliferation and migration was studied in HepG2 and HuH7 cell ***:SOX11 was significantly elevated in HCC tumors compared to ***11-associated genes exhibited differential expression in pathways involving extracellular membrane ion *** associations were found between SOX11 levels,immune infiltration,ferroptosis,and immune checkpoint genes in HCC ***11 levels correlated with HCC stage,histologic grade,and tumor status,and independently predicted overall and disease-specific ***11 expression effectively distinguished between tumor and normal liver *** correlations highlighted a significant relationship between SOX11 and ferroptosis-associated *** SOX11 levels in HepG2 and HuH7 cells resulted in reduced proliferation and ***:SOX11 was found to represent a promising biomarker within HCC diagnosis and prognosis together with being a possible drug-target.

关键词： SOX11 biomarker HCC prognosis genetic alterations tumor-immune infiltration ferroptosis

Effect of Three Gorges Dam on Poyang Lake water level at daily scale based on machine learning

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Journal of Geographical Sciences 2021年第11期31卷 1598-1614页

作者： HUANG Sheng XIA Jun ZENG Sidong wang yueling SHE Dunxian State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan UniversityWuhan 430072China Hubei Key Laboratory of Water System Science for Sponge City Construction Wuhan UniversityWuhan 430072China Key Laboratory of Water Cycle and Related Land Surface Processes Institute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China Chongqing Institute of Green and Intelligent Technology CASChongqing 400714China

Lake water level is an essential indicator of environmental changes caused by natural and human *** water level of Poyang Lake,the largest freshwater lake in China,has exhibited a dramatic variation for the past few years,especially after the completion of the Three Gorges Dam(TGD).However,there is a lack of more accurate assessment of the effect of the TGD on the Poyang Lake water level(PLWL)at finer temporal scales(e.g.,the daily scale).Here,we used three machine learning models,namely,an Artificial Neural Network(ANN),a Nonlinear Autoregressive model with exogenous input(NARX),and a Gated Recurrent Unit(GRU),to simulate the daily lake level during *** found that machine learning models with historical memory(i.e.,the GRU model)are more suitable for simulating the PLWL under the influence of the *** GRU-based results show that the lake level is significantly affected by the TGD regulation in the different operation stages and in different *** the TGD has had a slight but not very significant impact on the yearly decline of the PLWL,the blocking or releasing of water at the TGD at certain moments has caused large changes in the lake *** machine-learning-based study sheds light on the interactions between Poyang Lake and the Yangtze River regulated by the TGD.

关键词： water level Poyang Lake machine learning Three Gorges Dam Yangtze River

宁南黄土区中庄小流域土壤密度坡面变化及尺度效应

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水土保持研究 2025年第2期32卷 72-82页

作者：韩新生许浩刘广全安钰董立国王月玲万海霞郭永忠宁夏农林科学院、林业与草地生态研究所、宁夏防沙治沙与水土保持重点实验室、宁夏生态修复与多功能林业综合研究中心银川750002 中国水利水电科学研究院流域水循环模拟与调控国家重点实验室北京100038

[目的]分析土壤密度在坡面上的变化特征及尺度效应,探讨土壤密度坡面尺度转换路径,为精准监测土壤密度、科学评价土壤功能、指导土壤资源管理提供理论依据。[方法]在宁夏南部半干旱黄土丘陵区中庄小流域,选择3个退耕还林还草后的典型坡... 详细信息

[目的]分析土壤密度在坡面上的变化特征及尺度效应,探讨土壤密度坡面尺度转换路径,为精准监测土壤密度、科学评价土壤功能、指导土壤资源管理提供理论依据。[方法]在宁夏南部半干旱黄土丘陵区中庄小流域,选择3个退耕还林还草后的典型坡面,按坡位从上至下设置了5个样地,调查各样地的植被类型、土地利用、立地条件等,采用环刀法分层测定了200 cm深度的土壤密度。[结果]在东坡、西坡、南坡,土壤密度随土层加深基本表现为线性增加,土层每加深10 cm土壤密度平均增加0.0062,0.0036,0.0075 g/cm^(3),其原因为植被根系、土壤有机质、压实作用的土层差异。在0—200 cm土层,东坡和南坡土壤密度坡面均值均为1.22 g/cm^(3),低于西坡(1.26 g/cm^(3))。3个坡面土壤密度的坡面变化存在差异,东坡、西坡、南坡沿坡变化表现为逐渐增加或先增后减、先升后降、先降后升,整体上为坡面下部大于上部,主要原因包括植被类型、土地利用、人类活动、恢复年限等坡面差异。以离坡顶水平距离增加100 m土壤密度坡面滑动平均值的变化量评价坡面尺度效应,0—200 cm土层的平均土壤密度坡面尺度效应在东坡为0.032(g/cm^(3))/100 m,在西坡为0.024(g/cm^(3))/100 m(离坡顶0—250 m)和-0.007(g/cm^(3))/100 m(离坡顶250—329 m),在南部为-0.011(g/cm^(3))/100 m(离坡顶0—140 m)和0.018(g/cm^(3))/100 m(离坡顶140—368 m)。构建3个坡面不同坡位样地各土层的土壤密度与坡面均值的比值随离坡顶水平距离增加而变化的关系式(R2>0.80,p<0.0001),且基于拟合关系式预测的土壤密度坡面均值的相对误差均小于2.5%,藉此可由任一坡位样地土壤密度测定值准确便捷地估算坡面均值。[结论]半干旱黄土区土壤密度坡面变化和坡位差异明显,且植被类型、人为干扰、土地利用等对土壤密度坡面分布格局影响较大,未来应加强主要作用因子对土壤密度坡面变化及尺度效应的贡献研究。

关键词：土壤密度坡面变化尺度效应植被类型半干旱黄土区

Effect of aspirin alone or combined with cisplatin on human cervical carcinoma HeLa cells

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Journal of Medical Colleges of PLA(China) 2010年第1期25卷 11-18页

作者： wang yueling Zhao Hongmin Liu Lin wang Jiangfen Department of Obstetrics and Gynecology First Affiliated Hospital Medical College Xi 'an Jiaotong University Xi 'an 710061 China

Objective： To study the effect and mechanism of aspirin alone or combined with cisplatin （DDP） on human cervical carcinoma HeLa cells. Methods： HeLa cells were treated by different concentrations of aspirin, DDP alone or both. The inhibitory effect on cell growth was analyzed by MTT and colony-forming assay. Cell apoptosis was measured with flow cytometry. The mRNA levels ofBcl-2, Bax and NF-κB（P65） were studied by RT-PCR. Results： MTT assay showed that aspirin inhibited HeLa cell proliferation in a time-and dose-dependant maoner. Aspirin decreased clone numbers in colony formation assay. Aspirin also induced apoptosis of HeLa cells in a dose- and time-dependent manner as detected by flow cytometry. The inhibition effects on proliferation, colony formation and apoptosis were significantly enhanced when cells were treated with both aspirin and DDP. RT-PCR demonstrated that aspirin decreased the transcription of Bcl-2 and NF-κB, and increased expression of Bax gene. Conclusion： Aspirin can induce apoptosis in HeLa cells. Combination of aspirin and DDP displays a synergistic effect. The possible mechanism might be that aspirin downregulates the mRNA levels of Bcl-2 and NF-κB gene and upregulates the expression of Bax.

关键词： Aspirin Cisplatin HeLa cells Cervical carcinoma Apoptosis

Gradient decrease in telomerase and its RNA in progressive passage of human endometrial stromal stem cells

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Journal of Medical Colleges of PLA(China) 2011年第5期26卷 254-263页

作者： Yang Xinyuan wang Wei wang yueling Chen Wei Li Xu Department of Gynaecology and Obstetrics First Affiliated Hospital School of Medicine Xi＇an Jiaotong University Xi＇an 710061 China Department of Anesthesiology First Affiliated Hospital School of Medicine Xi＇an Jiaotong University Xi ＇an 710061 China Department of Clinical Laboratory First Affiliated Hospital School of Medicine Xi＇an Jiaotong University Xi ＇an710061 China

The purpose of this study was to explore the change of telomerase in passage from human endometrial stromal stem cells isolated from human *** activity of cultured endometrial stromal cells was assessed at mRNA and protein levels using RT-PCR and immunohistochemistry *** mRNA and protein levels were higher at early passages,and then had a gradually decreased trend of immunoreactive intensity and gradually weakened positive cells with progressive passage in endometrial stromal stem *** results suggest that telomerase is contributed to the insenecence of endometrial stem cell.

关键词： Endometrial stromal cell Telomerase Cell culture

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基于支持向量机与概率输出网的深度学习模型

系统工程理论与实践 2018年第8期38卷 2147-2154页

作者：刘涵王月岭王晓林艳艳西安理工大学自动化与信息工程学院

本文提出了基于支持向量机与概率输出网络的深度学习回归模型．该回归模型利用深度学习的深层结构，以及支持向量机的泛化能力、概率输出网络中的条件概率估计特点，建立了多层支持向量机的深度学习结构，避免了深度学习的参数选择问题... 详细信息

本文提出了基于支持向量机与概率输出网络的深度学习回归模型．该回归模型利用深度学习的深层结构，以及支持向量机的泛化能力、概率输出网络中的条件概率估计特点，建立了多层支持向量机的深度学习结构，避免了深度学习的参数选择问题．其中核参数的选择域呈网格状，通过求取输出对应卢分布的累积概率分布和经验累积概率分布的K-S检验，求取一致性的P值最大对应的核参数作为支持向量机模型的核参数．对应的输出为模型提取的特征，作为下一层的输入，直至模型达到结束条件为止．仿真实验通过三个标准的回归数据集证明了本文提出模型的有效性．

关键词：支持向量机概率输出网络深度学习 K-S检验