Qilin Chen

Shandong Provincial Hospital

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Co-Authors

Rui‐tang Guo

Shanghai University of Electric Power

Weiguo Pan

Shanghai University of Electric Power

Qingshan Wang

Central South University

Chunzhen Ren

Gansu University of Traditional Chinese Medicine

Chen-zi Lu

Shanghai University of Electric Power

Ning-zhi Yang

Shanghai University of Electric Power

Xiaodong Zhi

Gansu University of Traditional Chinese Medicine

Xiang Gao

Fudan University

Song He

Wuhan University of Technology

Shuxian Wang

Kunming University of Science and Technology

Cooperative Institutions

Chinese Academy of Sciences

Research Institute of Petroleum Exploration and Development

Chongqing Medical University

Peking University

Central South University

Sun Yat-sen University

Gansu University of Traditional Chinese Medicine

University of Chinese Academy of Sciences

Huazhong University of Science and Technology

Tsinghua University

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Re-Discussion of Relationship between Petroleum and Sand-Type Uranium Deposit

Xinjiang shiyou dizhi (2006)

Qilin Chen

The relationship between petroleum and sand-type uranium deposit is increasingly concerned. There exists paragenetic relationship between uranium ores and petroleum trace elements (Re, Ni and V, etc.), which indicates that they might be all originated from deep sources. The tracing and dating by Pb, Sr, Nd isotopes in crude and bitumen also prove the nature of deep sources. The deposition and formation of sand-ype uranium ores are related with reduction of hydrocarbon, especially with methane and hydrogen. Based on these deep source features and origin relationship between crude oil and uranium, the general criterion for finding out large oil and gas fields is presented, that is, as long as a sand-type uranium deposit is found with low-velocity and highly-conductive zones in the mid-crust, the target of large oil and gas fields could be delineated.

Uranium ore

Petroleum geochemistry

Deposition

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Correlation Between the MTHFR C677T Genotype and Coronary Heart Disease in Populations from Gansu, China

DNA and Cell Biology (2022)

Xue Wu Kai Liu Xinke Zhao Xiaowei Zhang Huan Guo

This study was designed to evaluate the relationship between polymorphisms in the methylenetetrahydrofolate reductase (MTHFR) gene and coronary heart disease (CHD) in populations from the Gansu region of China. The MTHFR C677T polymorphism genotypes from 209 patients with CHD, as confirmed by coronary angiography, and 212 non-CHD control patients were identified using PCR gold magnetic particle chromatography. We simultaneously evaluated homocysteine (Hcy) and folate levels in these samples using biochemical methods. The TT genotype of the MTHFR C677T locus was significantly more frequent in the CHD group than in the control, while the CC genotype was significantly less frequent in CHD patients than in non-CHD patients (p < 0.05). In addition, biochemical analysis revealed that the serum Hcy levels increased, and folate levels decreased in the TT genotype. Logistic regression analysis showed that this correlation was independent of nationality, sex, age, body mass index, medical history, and blood lipid level (p < 0.05). The occurrence of the TT genotype at the MTHFR C677T locus was closely associated with CHD in the Gansu population and may serve as a biomarker of increased risk for this disease.

10.1089/dna.2022.0329

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Citations (2)

The deactivation of Ce/TiO2 catalyst for NH3-SCR reaction by alkali metals: TPD and DRIFT studies

Catalysis Communications (2016)

Shuxian Wang Rui‐tang Guo Weiguo Pan Qilin Chen Peng Sun

Selective catalytic reduction

10.1016/j.catcom.2016.11.005

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Citations (101)

Virtual Metrology Modeling for CVD Film Thickness With Lasso-Gaussian Process Regression

2022 China Semiconductor Technology International Conference (CSTIC) (2023)

Shijia Yan Cong Luo Sen Wang Shenglan Ding Lei Li

In order to achieve statistical process control in high volume semiconductor manufacturing, it is of great significance to detect the film thickness of wafers and further achieve early warning of abnormal conditions. Virtual metrology (VM), based on the production parameters, has been utilized for process monitoring and control for the last decades. It can realize the real-time online prediction of measurement value, with the existing sampling system, to reducing the sampling rate and ultimately compress cycle time. However, most of existing VM strategies for CVD usually use global nonlinear models, which are difficult to catch sudden changes of the fluctuating production process. Moreover, the machine learning methods used in existing VM can only obtain the predicted values, but cannot judge the confidence of the results. This also results in a low accuracy of traditional approaches when dealt with the high-dimensional data with small sizes. Based on the just-in-time learning framework, this paper proposes the Lasso-Gaussian Process Regression(LGPR) and develops an intelligent VM system, which can realize the real-time prediction of film thickness in CVD process. The experiment results show that the LGPR is more stable and higher accurate.

Lasso

Statistical Process Control

Advanced process control

10.1109/cstic58779.2023.10219236

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The poisoning effect of Na and K on Mn/TiO2 catalyst for selective catalytic reduction of NO with NH3: A comparative study

Applied Surface Science (2014)

Rui‐tang Guo Qingshan Wang Weiguo Pan Wenlong Zhen Qilin Chen

Selective catalytic reduction

Deposition

10.1016/j.apsusc.2014.08.082

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Citations (105)

Deactivation of Mn/TiO₂ catalyst for NH₃-SCR reaction: effect of phosphorous

RSC Advances (2016)

Ning-zhi Yang Rui‐tang Guo Qingshan Wang Weiguo Pan Qilin Chen

The deactivation mechanism of phosphorous on a Mn/TiO₂ catalyst for selective catalytic reduction of NO with NH₃ was investigated in this study.

Selective catalytic reduction

10.1039/c5ra27713b

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Citations (59)

アルカリ金属によるNH_3SCR反応のCe/TiO_2触媒の失活:TPDとDRIFT研究【Powered by NICT】

Catalysis Communications (2017)

Wang Shu-xian Rui‐tang Guo Pan Wei-guo Qilin Chen Sun Peng

Source

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A Real-Time Automated Defect Classification System Based on Two-Step Convolutional Neural Network

Journal of Physics Conference Series (2022)

Sen Wang Shijia Yan Qiang Shen Cong Luo Lei Li

Abstract The increasing amount of defect images in semiconductor manufacturing process imposes the demand of classifying these images in real-time. In this paper we adopt a two-step deep learning based Convolutional Neural Network (CNN) to detect and classify the defect images from clean ones. The proposed method integrates the detection and classification process into one forward step, which takes image-level feature as well as empirical defect classification rules into account. In practice, the Real-Time Automated Defect Classification (RT-ADC) system was deployed in inline production process, which brings high efficiency; better wafer analysis and root cause determination for yield enhancement.

Feature (linguistics)

Contextual image classification

10.1088/1742-6596/2337/1/012006

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Nbでの修飾によるNH_3SCR反応のMn/TiO_2触媒の増強されたZn耐性【Powered by NICT】

Fuel Processing Technology (2016)

Li Wei Rui‐tang Guo Wang Shu-xian Pan Wei-guo Qilin Chen

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Online/offline self‐disclosure to offline friends and relational outcomes in a diary study: The moderating role of self‐esteem and relational closeness

International Journal of Psychology (2020)

Liman Man Wai Li Qilin Chen Haojie Gao Wen–Qiao Li Kenichi Ito

Previous work suggests that the experiences of online and offline self‐disclosure are heterogeneous among individuals. Yet little work has been done to identify the moderating role of individual characteristics and pre‐existing relationship characteristics on the diverse relational outcomes. The present study using a 7‐day diary design examined whether individuals' self‐esteem level and relational closeness would moderate the relationships between online and offline self‐disclosure to offline friends and two relational outcomes, that is, relationship satisfaction and trust in friendships. The analyses on 686 diary responses from 98 participants revealed that offline self‐disclosure generally predicted greater relationship satisfaction and trust in friendships, whereas the role of online self‐disclosure was not statistically significant. More importantly, self‐esteem moderated the pattern associated with offline self‐disclosure but not that with online self‐disclosure. Specifically, offline self‐disclosure predicted greater benefits to people with lower self‐esteem relative to people with higher self‐esteem. Moreover, pre‐existing relational closeness moderated the relationship between offline self‐disclosure and trust in friendships such that casual friendships benefited more from offline self‐disclosure than close friendships did. The present study highlights the importance of personal characteristics and relationship characteristics in understanding the heterogeneous relational influence of different communication modes.

Closeness

Self-disclosure

Online and offline

Moderation

Casual

10.1002/ijop.12684

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Citations (13)