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| 1 | Geochemical characteristics and genetic model of dolomite reservoirs in the eastern margin of the Pre-Caspian Basin显示文摘The widespread Carboniferous KT-I dolomite in the eastern margin of the Pre-Caspian Basin is an important hydrocarbon reservoir. The dolomite lithology is dominated by crystalline dolomite. The δ18O values range from -6.71‰ to 2.45‰, and average 0.063‰, obviously larger than -2.5‰, indicating low-temperature dolomite of evaporation origin. Stable strontium isotope ratios (87Sr/86Sr) range from 0.70829 to 0.70875 and average 0.708365, very consistent with 87Sr/86Sr ratios in Carboniferous seawater. Chemical analysis of Ca and Mg elements shows that the dolomite has 9.1 mole% excess Ca or even higher before stabilization. The degree of order of dolomite is medium-slightly poor, varying in a range of 0.336-0.504 and averaging 0.417. It suggests that the dolomite formed under near-surface conditions. There are two models for the origin of the Carboniferous KT-I dolomite reservoir. These are 1) the evaporation concentration - weathering crust model and 2) the shoal facies - seepage reflux model. The former is mainly developed in restricted platforms - evaporate platforms of restricted marine deposition environments with a representation of dolomite associated with gypsum and mudstone. The latter mainly formed in platform edge shoals and intra-platform shoals and is controlled by dolomitization due to high salinity sea water influx from adjacent restricted sea or evaporate platform. | Wang Shuqin Zhao Lun Cheng Xubin Fan Zifei He Ling | 2012 | Petroleum Science2012，9，2： | 12 |
| 2 | Fusion of machine vision technology and AlexNet-CNNs deep learning network for the detection of postharvest apple pesticide residues显示文摘Pesticide residue is an important factor that affects food safety.In order to achieve effective detection of pesticide residues in apples,a machine-vision-based segmentation algorithm and hyperspectral techniques were used to segment the foreground and background regions of the apple image.By calculating the roundness value and extracting the region with the highest roundness value in the connected region,a region of interest(ROI)maskwas created for the apple.Four pesticides(chlorpyrifos,carbendazimand two mixed pesticides)and an inactive control were used at the same concentration of 100 ppm(except for the control group),and the hyperspectral region of the corresponding sample image was extracted by obtaining the different types of pesticide residues in the ROI masks.To increase the diversity of the samples and to expand the dataset,Gaussianwhite noise with a varying signal-to-noise ratio was added to each of the hyperspectral images of the apple.The number of samples was increased from four types of 12 samples to four types of 72 samples,giving 4608 hyperspectral data images in each category.The structure and parameters of a convolutional neural network(CNN)were determined using theoretical analysis and experimental verification.All the extracted hyperspectral images of apples were normalized to 227×227×3 pixels as the input of the CNN network for pesticide residue detection.There were 18,432 sample data of four types for 72 samples.Of these,12,288 images were selected using a bootstrap sampling method as the training set,and 6144 as the test set,with no overlap.The test results showthatwhen the number of training epochswas 10,the accuracy of the test set detectionwas 99.09%,and the detection accuracy of the single-band average imagewas 95.35%.A comparison with traditional k-nearest neighbor(KNN)and support vectormachine classification algorithms showed that the detection accuracy for KNNwas 43.75%and the average time was 0.7645 s.These results demonstrate that our method is a small-sample,noncontact,fast,effective and low-cost technique that can provide effective pesticide residue detection in postharvest apples. | Bo Jiang Jinrong He Shuqin Yang Hongfei Fu Tong Li Huaibo Song Dongjian He | 2019 | Artificial Intelligence in Agriculture2019，，1： | 8 |
| 3 | A FCC Catalyst Prepared by in situ Technique Based on Application of Filter Residue and Kaolin显示文摘This paper has provided an effective method to utilize the filter residue. A Y zeolite-containing composite and a fluid catalytic cracking(FCC) catalyst had been successfully prepared by an in-situ crystallization technology using filter residue and kaolin as raw materials. The samples were characterized by XRD, FT-IR, SEM, and N_2 adsorption-desorption techniques and evaluated in a bench FCC unit. In comparison to the reference samples synthesized from single kaolin,the silica/alumina molar ratio, the external surface area, and the total pore volume of the composite increased by 16.2%,14.5%, and 16.2%, respectively. The catalyst possessed more meso-and macro-pores and more acid sites than the reference catalyst, and exhibited better coke selectivity. The prepared catalyst had the optimum isomerization and aromatization performance. The olefin content in the cracked gasoline obtained over this catalyst was reduced by 5.05 percentage points with the research octane number of gasoline increased by 0.5 units. | Zheng Shuqin He Lijun Yao Hua Ren Shao Zhang Jiance | 2017 | China Petroleum Processing & Petrochemical Technology2017，19，1： | 3 |
| 4 | Predicting wheat kernels’protein content by near infrared hyperspectral imaging显示文摘The objective of this study was to explore the potential of near infrared hyperspectral imaging combined with statistical regression models and neural networks for nondestructive prediction of protein content of wheat kernels.Seventy-nine samples from 11 breeds of wheat kernels were collected.The protein percentage of each sample measured by semimicro-Kjeldahl method was taken as the reference value.After comparing the prediction models of principal components regression(PCR)and partial least squares regression(PLSR)with various pretreatment methods,PLSR preprocessed by zero mean normalization(z score)function of MATLAB was found to obtain better prediction results than other regression models.Based on 10 latent variables of PLSR,the radial basis function(RBF)neural network was applied to improve the prediction,in which the coefficients of determination(R2)were greater than 0.92 for both the calibration set and validation set,while the corresponding RMSE values were 0.3496 and 0.4005,respectively.Therefore,hyperspectral imaging can provide a fast and non-destructive method for predicting the wheat kernels’protein content. | Yang Shuqin He Dongjian Ning Jifeng | 2016 | International Journal of Agricultural and Biological Engineering2016，9，2： | 2 |
| 5 | Synthesis and Application of a Zeolite-containing Composite Material Made from Spent FCC Catalyst显示文摘Novel composite material with a wide pore distribution was synthesized by an in situ technique using spent FCC catalyst as raw material. The characterization results indicated that the composite material contained 56.7% of zeolite Y and exhibited a much larger specific surface area and pore volume as well as strong hydrothermal stability. Fluid catalytic cracking(FCC) catalyst was prepared based on the composite material. The results indicated that the as-prepared catalyst possessed a unique pore structure that was advantageous to the diffusion-controlled reactions. In addition, the attrition resistance, activity and hydrothermal stability of the studied catalyst were superior to those of the reference catalyst. The catalyst also exhibited excellent nickel and vanadium passivation performance, strong bottoms upgrading selectivity, and better gasoline and coke selectivity. In comparison to the reference catalyst, the yields of the gasoline and light oil increased by 1.61 and 1.31 percentage points, respectively, and the coke yield decreased by 0.22 percentage points, and the olefin content in the produced gasoline reduced by 2.51 percentage points, with the research octane number increased by 0.7 unit. | Zheng Shuqin He Lijun Yao Hua Ren Shao Yu Hongxia Zhang Jiance | 2015 | China Petroleum Processing & Petrochemical Technology2015，17，4： | 2 |
| 6 | Fire safety assessment of halogen-free flame retardant polypropylene based on cone calorimeter显示文摘 | Hu Yuan Song Lei | 2007 | Journal of Fire Sciences2007，25，3： | 1 |
| 7 | Properties of rosin - based waterborne polyurethanes/ cellulose nanocrystals composites 显示文摘 | Liu He Cui Shuqin Shang Shibin | 2013 | Carbohydrate Polymers2013，96，2： | 1 |
| 8 | Influences of thermal pretreatment temperature and solvent on the organosilane modification of Al 13 -intercalated/Al-pillared montmorillonite显示文摘 | Zonghua Qin Peng Yuan Jianxi Zhu Hongping He Dong Liu Shuqin Yang | 2010 | Applied Clay Science2010，，4： | 1 |
| 9 | Properties of rosin-based waterborne polyurethanes/cellulose nanocrystals composites显示文摘 | He Liu Shuqin Cui Shibin Shang Dan Wang Jie Song | 2013 | Carbohydrate Polymers2013，，2： | 1 |
| 10 | Changes of soil surface roughness under water erosion process显示文摘 | Zheng Zicheng He Shuqin Wu Faqi | 2014 | Hydrological Processes2014，28，12： | 1 |
| 11 | Properties of rosinbasedwaterborne polyurethanes/cellulose nanocrystalscomposites显示文摘 | Liu He Cui Shuqin Shang Shibin | 2013 | Carbohydrate Polymers2013，96，2： | 1 |
| 12 | Crystal and Molecular Structure of Mo_2[(μ_2-S)SCNEt_2]_2(S_2CNEt_2)_2显示文摘Crystal structure of the title complex was determined by X-ray diffraction method. It crystallizes in space group P21/n with cell dimensions:α=10. 041(5) , b=10. 719(4) , c= 1. 5671(6) nm, β=104. 36(3)°. The structure was solved by Patterson method. The final residual factor is R=0. 050. | Sun Chunting, Huang Qijun, Li Shuqin and Wang Tiegang(Department of Chemistry, Jilin University, Changchun)Zhang Guangren, Qu Xiangbang, Tang Zhongkun, He Guoqiang and Shen Yankui (Logistics Engineering Institute, Chongqing) Jin Zhongsheng and Wei Gecheng (Changchun Institute of Applied Chemistry, Changchun) | 1991 | Chemical Research in Chinese Universities1991，7，2： | 0 |
| 13 | Forecasting oil production in unconventional reservoirs using long short term memory network coupled support vector regression method: A case study显示文摘Production prediction is crucial for the recovery of hydrocarbon resources.However,accurate and rapid production forecasting remains challenging for unconventional reservoirs due to the complexity of the percolation process and the scarcity of available data.To address this problem,a novel model combining a long short-term memory network(LSTM)and support vector regression(SVR)was proposed to forecast tight oil production.Three variables,the tubing head pressure,nozzle size,and water rate were utilized as the inputs of the presented machine-learning workflow to account for the influence of operational parameters.The time-series response of tight oil production was the output and was predicted by the optimized LSTM model.An SVR-based residual correction model was constructed and embedded with LSTM to increase the prediction accuracy.Case studies were carried out to verify the feasibility of the proposed method using data from two wells in the Ma-18 block of the Xinjiang oilfield.Decline curve analysis(DCA)methods,LSTM and artificial neural network(ANN)models were also applied in this study and compared with the LSTM-SVR model to prove its superiority.It was demonstrated that introducing residual correction with the newly proposed LSTM-SVR model can effectively improve prediction performance.The LSTM-SVR model of Well A produced the lowest prediction root mean square error(RMSE)of 5.42,while the RMSE of Arps,PLE Duong,ANN,and LSTM were 5.84,6.65,5.85,8.16,and 7.70,respectively.The RMSE of Well B of LSTM-SVR model is 0.94,while the RMSE of ANN,and LSTM were 1.48,and 2.32. | Shuqin Wen Bing Wei Junyu You Yujiao He Jun Xin Mikhail A.Varfolomeev | 2023 | Petroleum2023，9，4： | 0 |
| 14 | Immunoregulatory effects of human amniotic mesenchymal stem cells and their exosomes on human peripheral blood mononuclear cells显示文摘Background:The immunomodulatory effects of mesenchymal stem cells(MSCs)and their exosomes have been receiving increasing attention.This study investigated the immunoregulatory effects of human amniotic mesenchymal stem cells(hAMSCs)and their exosomes on phytohemagglutinin(PHA)-induced peripheral blood mononuclear cells(PBMCs).Methods:The hAMSCs used in the experiment were identified by light microscopy and flow cytometry,and the differentiation ability of the cells was determined by Oil Red O and Alizarin Red staining.The expressions of transforming growth factor(TGF)-β,indoleamine 2,3-dioxygenase(IDO),cyclooxygenase-2(COX-2),hepatocyte growth factor(HGF),and interleukin(IL)-6 were detected by quantitative real-time polymerase chain reaction and western blotting.PBMCs,hAMSCs,and their exosomes were collected for in vitro group culture.Then the immunoregulatory ability of hAMSCs and their exosomes were analyzed by flow cytometry and Enzymelinked immunosorbent assay.Results:The hAMSCs and exosomes were successfully extracted from the human amniotic membrane.TGF-β,IDO,COX-2,HGF,and IL-6 were significantly expressed in hAMSCs.In vitro co-culture showed that hAMSCs promoted the proliferation of Th2 cells in PHA-induced PBMCs,while hAMSCs and exosomes inhibited the secretion of TNF-αin PHA-induced PBMCs,and promoted the secretion of IL-4 and IL-10,and hAMSCs had more significant effects than exosomes.Conclusions:hAMSCs or exosomes could exert immunoregulatory effects on PHA-induced PBMCs by affecting Th2 cell proliferation and cytokine secretion. | XIN TIAN XIANGLING HE SHUQIN QIAN RUNYING ZOU KEKE CHEN CHENGGUANG ZHU ZEXI YIN | 2023 | BIOCELL2023，47，5： | 0 |
| 15 | Inhomogeneity of Rare Earth Doped Ⅲ-Ⅴ Compounds Grown by LPE显示文摘The processing of InP, GaAs and related compounds doped with rare earth metals, such as Er, Nd and Gd, grown by LPE isdescribed. The inhomogeneity of rare earth heavily doped epi-layers is studied by SIMS, SEM and X-ray diffraction techniques. | Yuan Yourong He Shengfu Zhu Youcai,Li Xiangwen Zhao Yu Du Shuqin Shi Yihe Liu Guoyuan Li Yunyi Zhou Ji Changchun Institute of Physics,Academia Sinica 130021 China General Research Institute for Non-ferrous Metals,Beijing 100088 Department of Chemistry, Peking University | 1990 | Rare Metals1990，10，2： | 0 |
| 16 | The effect of tea plantation age on soil water-stable aggregates and aggregate-associated carbohydrate in southwestern China显示文摘Soil carbohydrates constitute an important component of soil organic matter(SOM),and substantially contribute to the stabilization of soil aggregates.Here,we aimed to investigate the distribution of water-stable aggregates and carbohydrates within water-stable aggregates of soil in tea plantations located in Zhongfeng Township of Mingshan County,Sichuan,which is in southwest China.Samples were collected from tea plantations of different ages(18,25,33,and 55 years old)and an area of abandoned land was used as a control(CK).We also examined correlations between soil carbohydrates fractions and aggregate stability.The results showed that the mean weight diameter(MWD)of soil aggregates in the tea plan-tations was significantly higher than that the control.Furthermore,the soil aggregate stability was significantly enhanced in tea plantations,with the 25-year-old plantation showing the most pronounced effect.Soils in the plantations were also characterized by higher concentrated acid-extracted carbohy-drate content,and carbohydrate content in both surface and sub-surface layers were higher in the 25-year-old plantation.We also detected a significant positive correlation between the carbohydrate con-tent of soil and MWD after tea plantation(P<0.01).Notably,the association between dilute-acid extracted carbohydrate and the aggregate stability showed the highest correlation,indicating this car-bohydrate fraction could be used as an index to reflect changes in soil quality during tea plantation development.We should develop a potential fertilisation programme to maintain SOM-Carbohydrates within aggregates and the appropriate pH for preventing soil structure degradation after 25 years of tea planting. | Shuqin He Renhuan Zhu Zicheng Zheng Tingxuan Li | 2023 | International Soil and Water Conservation Research2023，11，2： | 0 |
| 17 | Effects of rainfall intensities and slope gradients on nitrogen loss at the seedling stage of maize(Zea mays L.)in the purple soil regions of China显示文摘Loss of soil nitrogen has been reported to reduce soil productivity and result in eutrophication.The objective of this work was to understand the mechanisms of nitrogen loss at the maize seedling stage from purple soil in the sloping farmlands of southwest China.The characteristics of nitrogen loss were explored in experiments simulating rainfall conditions during the maize seedling stage at different rainfall intensities(60 mm/h,90 mm/h,and 120 mm/h)and slope gradients(10°,15°,and 20°).The results showed that the runoff and sediment yield increased with time.The surface runoff and sediment yield increased with the rainfall intensity and slope gradient.Nitrogen losses increased in the surface runoff and sediment but decreased in the interflow as the rainfall intensity and slope gradient increased.Dissolved total nitrogen(DTN)was the main form of nitrogen in the surface runoff and interflow,and nitrate nitrogen(NO3-N)was the main form of DTN.The surface runoff and sediment accounted for less than half of the TN losses.Thus,interflow was the main pathwayfor nitrogen loss.The regression lines between the surface runoff and forms of nitrogen losses in the runoff and interflow were linear.The results indicated that an increasing rainfall intensity and slope gradient generally increased the surface runoff,sediment,andnitrogen losses.However,the opposite trend was observed for the interflow and its nitrogen losses. | Shuqin He Yuanbo Gong Ziheng Zheng Ziteng Luo Bo Tan Yunqi Zhang | 2022 | International Journal of Agricultural and Biological Engineering2022，15，2： | 0 |
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