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Numerical Approaches to Identification of Characteristic Soil Layers in an Urban Environment

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Pedosphere 2008年第3期18卷 335-343页

作者： YUAN Da-gang zhang gan-lin GONG Zi-Tong State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of SciencesNanjing 210008 （China） Graduate School of the Chinese Academy of Sciences Beijing 100049 （China） College of Resource and Environmental Sciences Sichuan Agricultural University Ya＇an 625014 （China）

Pedogenetic soil horizons are one of the fundamental building blocks of modern soil classification; however, in soils of urban areas which are often strongly disturbed by human activities, horizons are difficult to distinguish but substitutive morphological layers may be identified. To identify the characteristic soil layers in an urban environment, 224 soil layers of 36 in-situ pedons were examined and described in urban and suburban Nanjing, and 27 variables were extracted for multivariate analysis. Three groups and six subdivisions were identified by TwoStep cluster analysis combined with hierarchical cluster analysis based on factor scores. Soil forming factors and soil forming processes could be interpreted from the principal component analysis （PCA） of variables, cluster analysis of soil layers, and discriminant analysis of soil layer groups and their subdivisions. Parent materials, moisture regimes, organic matter accumulation, and especially nutrient accumulation were the main causes of characteristic soil layer formations. The numerical approaches used in this study were useful tools for characteristic soil layer identification of urban soils.

关键词： characteristic soil layer multivariate analysis numerical soil classification urban soils

两样本孟德尔随机化分析炎性因子与前列腺癌因果关系

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中华男科学杂志 2024年第7期30卷 588-596页

作者：曾银张甘霖郭军杨梦萍韩强杨国旺首都医科大学附属北京中医医院北京100010 中国中医科学院西苑医院男科北京100091 北京中医药大学第三临床医学院北京100029

目的:采用两样本孟德尔随机化方法来评估91种炎性因子与前列腺癌的潜在因果关系。方法:选取91种炎性因子的全基因组关联分析(GWAS)汇总统计数据(n=14824)结合FinnGen最新第9版数据库中选取前列腺癌作为结局进行孟德尔随机化分析。通过... 详细信息

目的:采用两样本孟德尔随机化方法来评估91种炎性因子与前列腺癌的潜在因果关系。方法:选取91种炎性因子的全基因组关联分析(GWAS)汇总统计数据(n=14824)结合FinnGen最新第9版数据库中选取前列腺癌作为结局进行孟德尔随机化分析。通过逆方差加权法(IVW)、MR-Egger回归、简单中位数法(SM)、加权中位数法(WM)、加权中值法(WME)等回归模型的OR值和95%CI评估炎性因子与前列腺癌的因果关系,其中IVW法得出的因果关系相对稳定,作为本研究的主要统计方法。进一步采用贝叶斯分析法对孟德尔分析结果进行验证。使用Cochran's Q检验评估遗传工具变量的异质性,使用MR-Egger截距检验评估多效性,使用留一法评估作为工具变量的单核苷酸多态性(SNPs)对暴露和结局因果关系影响的敏感性。结果:IVW法结果显示,91种炎性因子中白介素-22受体A1(IL-22RA1)、磺基转移酶1A1(ST1A1)与前列腺癌发病风险呈正向因果关联:IL-22RA1:IVW[OR(95%CI):1.12(1.00~1.25),P=0.04];ST1A1:IVW[OR(95%CI):1.08(1.00~1.16),P=0.03]。趋化因子配体11(CXCL11)、白介素17A(IL-17A)与前列腺癌发病风险呈反向因果关联;CXCL11:IVW[OR(95%CI):0.88(0.81~0.95),P=0.00];IL-17A:IVW[OR(95%CI):0.91(0.84~0.98),P=0.02]。MR-Egger截距分析未检测到潜在的水平多效性(P均>0.05,IL-22RA1=0.885,ST1A1=0.949,CXCL11=0.391,IL-17A=0.884)。MR-PRESSO未检测到偏倚SNPs(P均>0.05,IL-22RA1=0.479,ST1A1=0.629,CXCL11=0.326,IL-17A=0.444),未发现异质性(P均>0.05,IL-22RA1=0.543,ST1A1=0.677,CXCL11=0.336,IL-17A=0.494),留一法敏感性分析结果图提示无个别单核苷酸多态性位点对整体因果关系预测产生明显影响,故分析结果可靠。结论:91种炎性因子中IL-22RA1、ST1A1与前列腺癌有正向因果关系,随着这些因子的水平增加,前列腺癌发病的风险升高;CXCL11、IL-17A与前列腺癌有反向因果关系,即随着这些因子的水平增加,前列腺癌发病风险降低。

关键词：炎性因子前列腺癌孟德尔随机化分析敏感性分析单核苷酸多态性贝叶斯分析

Predicting soil depth in a large and complex area using machine learning and environmental correlations

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Journal of Integrative Agriculture 2022年第8期21卷 2422-2434页

作者： LIU Feng YANG Fei ZHAO Yu-guo zhang gan-lin LI De-cheng State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008P.R.China University of the Chinese Academy of Sciences Beijing 100049P.R.China Key Laboratory of Watershed Geographic Science Nanjing Institute of Geography and LimnologyChinese Academy of SciencesNanjing 210008P.R.China

Soil depth is critical for eco-hydrological modeling,carbon storage calculation and land ***,its spatial variation is poorly understood and rarely *** a limited number of sparse samples,how to predict soil depth in a large area of complex landscapes is still an *** study constructed an ensemble machine learning model,i.e.,quantile regression forest,to quantify the relationship between soil depth and environmental *** model was then combined with a rich set of environmental covariates to predict spatial variation of soil depth and straightforwardly estimate the associated predictive uncertainty in the 140000 km^(2)Heihe River basin of northwestern China.A total of 275 soil depth observation points and 26 covariates were *** results showed a model predictive accuracy with coefficient of determination(R)of 0.587 and root mean square error(RMSE)of 2.98 cm(square root scale),i.e.,almost 60% of soil depth variation *** resulting soil depth map clearly exhibited regional patterns as well as local *** deep soils occurred in low lying landscape positions such as valley bottoms and plains while shallow soils occurred in high and steep landscape positions such as hillslopes,ridges and *** oases had much deeper soils than outside semi-desert areas,the middle of an alluvial plain had deeper soils than its margins,and the middle of a lacustrine plain had shallower soils than its *** predictive uncertainty mainly occurred in areas with a lack of soil survey *** pedogenic and geomorphic processes contributed to the shaping of soil depth pattern of this basin but the latter was *** findings may be applicable to other similar basins in cold and arid regions around the world.

关键词： digital soil mapping spatial variation uncertainty machine learning soil-landscape model soil depth

An integrated method of selecting environmental covariates for predictive soil depth mapping

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Journal of Integrative Agriculture 2019年第2期18卷 301-315页

作者： LU Yuan-yuan LIU Feng ZHAO Yu-guo SONG Xiao-dong zhang gan-lin State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008P.R.China University of Chinese Academy of Sciences Beijing 100049P.R.China

Environmental covariates are the basis of predictive soil *** selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil spatial heterogeneity is *** this study,we proposed an integrated method to select environmental covariates for predictive soil depth ***,candidate variables that may influence the development of soil depth were selected based on pedogenetic ***,three conventional methods(Pearson correlation analysis(PsCA),generalized additive models(GAMs),and Random Forest(RF))were used to generate optimal combinations of environmental ***,three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental *** tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China.A total of 129 soil sampling sites were collected using a representative sampling strategy,and RF and support vector machine(SVM)models were used to map soil *** results showed that compared to the set of environmental covariates selected by the three conventional selection methods,the set of environmental covariates selected by the proposed method achieved higher mapping *** combination from the proposed method obtained a root mean square error(RMSE)of 11.88 cm,which was 2.25–7.64 cm lower than the other methods,and an R^2 value of 0.76,which was 0.08–0.26 higher than the other *** results suggest that our method can be used as an alternative to the conventional methods for soil depth mapping and may also be effective for mapping other soil properties.

关键词： environmental covariate selection integrated method predictive soil mapping soil depth

Progress in Significant Soil Science Fields of China over the Last Three Decades: A Review

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Pedosphere 2011年第1期21卷 1-10页

作者： ZHAO Qi-Guo HE Ji-Zheng YAN Xiao-Yuan zhang Bin zhang gan-lin CAI Zu-Cong State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences Nanjing 210008 (China) State Key Laboratory of Urban and Regional Ecology Research Centre for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 (China) Key Laboratory of Plant Nutrition and Nutrient Cycling of the Ministry of Agriculture of China Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing 100081 (China)

Due to continuous decreases in arable land area and continuous population increases,Chinese soil scientists face great challenges in meeting food demands,mitigating adverse environmental impacts,and sustaining or enhancing soil productivity under intensive *** the aim of promoting the application of soil science knowledge,this paper reviews the achievements of Chinese scientists in soil resource use and management,soil fertility,global change mitigation and soil biology over the last 30 *** this period,soil resource science has provided essential support for the use and exploitation of Chinese soil resources,and has itself developed through introduction of new theories such as Soil Taxonomy and new technologies such as remote *** fertility science has contributed to the alleviation and elimination of impeding physical and chemical factors that constrain availability of essential nutrients and water in soils,the understanding of nutrient cycling in agroecosystems,and the increase in nutrient use efficiency for sustainable crop *** soil scientists have contributed to the understanding of the cropland's role in global change,particularly to the understanding of methane and nitrous oxide emission from rice fields and the effect of elevated carbon dioxide and ozone on rice-wheat *** biology research has progressed in biological N fixation,distribution of fauna in Chinese soils,and bioremediation of polluted soils.A new generation of soil scientists has arisen in the last three *** gaps between research and application in these soil science fields are also discussed.

关键词： global change soil biology soil fertility soil resources

Application of a Digital Soil Mapping Method in Producing Soil Orders on Mountain Areas of Hong Kong Based on Legacy Soil Data

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Pedosphere 2011年第3期21卷 339-350页

作者： SUN Xiao-lin ZHAO Yu-Guo zhang gan-lin WU Sheng-Chun MAN Yu-Bon WONG Ming-Hung Croucher Institute for Environmental Sciences and Department of Biology Hong Kong Baptist University Hong KongSpecial Administrative Region (China) State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences Nanjing210008 (China) joint Open Laboratory of Soil and Environment Institute of Soil Science Chinese Academy of Sciences and Hong KongBaptist University (China)

Based on legacy soil data from a soil survey conducted recently in the traditional manner in Hong Kong of China, a digital soil mapping method was applied to produce soil order information for mountain areas of Hong Kong. Two modeling methods （decision tree analysis and linear discriminant analysis） were used, and their applications were compared. Much more effort was put on selecting soil covariates for modeling. First, analysis of variance （ANOVA） was used to test the variance of terrain attributes between soil orders. Then, a stepwise procedure was used to select soil covariates for linear discriminant analysis, and a backward removing procedure was developed to select soil covariates for tree modeling. At the same time, ANOVA results, as well as our knowledge and experience on soil mapping, were also taken into account for selecting soil covariates for tree modeling. Two linear discriminant models and four tree models were established finally, and their prediction performances were validated using a multiple jackknifing approach. Results showed that the discriminant model built on ANOVA results performed best, followed by the discriminant model built by stepwise, the tree model built by the backward removing procedure, the tree model built according to knowledge and experience on soil mapping, and the tree model built automatically. The results highlighted the importance of selecting soil covariates in modeling for soil mapping, and suggested the usefulness of methods used in this study for selecting soil covariates. The best discriminant model was finally selected to map soil orders for this area, and validation results showed that thus produced soil order map had a high accuracy.

关键词： decision tree analysis linear discriminant analysis soil covariate selection

Mapping Soil Texture of a Plain Area Using Fuzzy-c-Means Clustering Method Based on Land Surface Diurnal Temperature Difference

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Pedosphere 2012年第3期22卷 394-403页

作者： WANG De-Cai zhang gan-lin PAN Xian-zhang ZHAO Yu-Guo ZHAO Ming-Song WANG Gai-Fen State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008(China) Graduate University of Chinese Academy of Sciences Beijing 100049(China)

The use of landscape covariates to variability of soil properties in similar estimate soil properties is not suitable topographic and vegetation conditions. for the areas of low relief due to the high A new method was implemented to map regional soil texture （in terms of sand, silt and clay contents） by hypothesizing that the change in the land surface diurnal temperature difference （DTD） is related to soil texture in case of a relatively homogeneous rainfall input. To examine this hypothesis, the DTDs from moderate resolution imagine spectroradiometer （MODIS） during a selected time period, i.e., after a heavy rainfall between autumn harvest and autumn sowing, were classified using fuzzy-c-means （FCM） clustering. Six classes were generated, and for each class, the sand （〉 0.05 mm）, silt （0.002-0.05 mm） and clay （〈 0.002 mm） contents at the location of maximum membership value were considered as the typical values of that class. A weighted average model was then used to digitally map soil texture. The results showed that the predicted map quite accurately reflected the regional soil variation. A validation dataset produced estimates of error for the predicted maps of sand, silt and clay contents at root mean of squared error values of 8.4%, 7.8% and 2.3%, respectively, which is satisfactory in a practical context. This study thus provided a methodology that can help improve the accuracy and efficiency of soil texture mapping in plain areas using easily available data sources.

关键词： digital soil mapping land surface temperature low relief area MODIS remote sensing

A novel method for the green utilization of waste fried oil

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Particuology 2024年第1期84卷 1-11页

作者： gan Cheng Mengni zhang Yang Lu Yanhui zhang Bin lin Ee Von Lau College of Chemistry and Chemical Engineering Henan Polytechnic UniversityJiaozuo454003China Henan Key Laboratory for Green and Efficient Mining&Comprehensive Utilization of Mineral Resources Henan Polytechnic UniversityJiaozuo454003China Collaborative Innovation Center of Coal Work Safety and Clean High Efficiency Utilization Henan Polytechnic UniversityJiaozuo454003China School of Engineering Monash University MalaysiaSubang JayaSelangor47500Malaysia

Waste fried oil was studied to prepare three different types of detergent such as soap,liquid soap and soap powder via saponification *** preparation conditions of soap base were optimized by orthogonal *** specific preparation processes included waste fried oil treatment,orange peel extract preparation,saponification,demoulding and *** showed that the optimal con-ditions for saponification were as follows:ratio of pure waste fried oil to coconut oil=6∶4,alkali liquor(NaOH)mass fraction 30%,saponification temperature 70℃,orange peel extract concentration 15%.The mature soap was then used to make liquid soap and soap powder by surfactant(sodium dodecylbenzene sulfonate,coconut diethanol amide)addition,followed by *** prepared detergent conforms to the production standard of strong decontamination ability,possesses stable performance,is gentle to skin and non-toxic.

关键词： Waste fried oil Detergent Saponification Decolorization

基于免疫生态系统探讨中药在三阴性乳腺癌中的治疗策略

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北京中医药 2024年第1期43卷 31-33页

作者：吴桐桐张甘霖李姝蒙杨国旺首都医科大学附属北京中医医院北京100010

三阴性乳腺癌(TNBC)是乳腺癌中恶性度最高的亚型,预后较差。研究发现TNBC具有良好的免疫原性,针对TNBC的免疫治疗干预措施具有很大的前景,但临床疗效存在一定争议。通过恢复机体免疫能力来消除肿瘤的机制,与中医“养正积自除”的理念一... 详细信息

三阴性乳腺癌(TNBC)是乳腺癌中恶性度最高的亚型,预后较差。研究发现TNBC具有良好的免疫原性,针对TNBC的免疫治疗干预措施具有很大的前景,但临床疗效存在一定争议。通过恢复机体免疫能力来消除肿瘤的机制,与中医“养正积自除”的理念一致。中医药应用于TNBC患者疗效较好,其作用与调节机体免疫,参与肿瘤免疫生态系统调控相关。本文总结了目前中医药调控肿瘤免疫生态系统的研究,为进一步机制探索及临床应用提供依据,以优化联合策略。

关键词：三阴性乳腺癌免疫生态系统免疫微环境中医药