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Weipeng Liu,Xin Zhou,Yuanqiang Li,Hong Jiang,Aijun Chen 한국유방암학회 2021 Journal of breast cancer Vol.24 No.3
Purpose: Non-coding RNA activated by DNA damage (NORAD) has been reported to be a cancer-related long non-coding RNA (lncRNA) implicated in the progression of several cancers; however, its role in breast cancer (BC) has not yet been clarified. Methods: Quantitative real-time polymerase chain reaction was used to examine NORAD, microRNA (miR)-155-5p, and suppressor of cytokine signaling 1 (SOCS1) mRNA expression levels. Western blotting was used to analyze SOCS1 protein expression. The malignancy of BC cells was assessed using the cell counting kit-8 (CCK-8), BrdU, and Transwell assays. Bioinformatics analysis, RNA immunoprecipitation assay, and dual-luciferase reporter gene assays were used to verify the targeted relationship between NORAD and miR-155-5p. Additionally, the regulatory effects of NORAD and miR-155-5p on SOCS1 expression were determined by western blotting. Results: NORAD expression was significantly reduced in BC cell lines and tissues, and its low expression was associated with poor tumor tissue differentiation. NORAD overexpression repressed BC cell proliferation, migration, and invasion, whereas its knockdown produced the opposite effects. Additionally, miR-155-5p was found to be a target of NORAD, and the biological functions of miR-155-5p and NORAD were counteractive. MiR-155-5p was confirmed to target SOCS1, and SOCS1 was found to be positively regulated by NORAD. Conclusion: NORAD suppresses miR-155-5p to upregulate SOCS1, thereby repressing the proliferation, migration, and invasion of BC cells.
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Liu, Weipeng,Cui, Xiaofeng,Zhou, Jiyao,Zhang, Zehua,Hou, Mingxuan,Shan, Shengqi,Wu, Shang The Korean Institute of Power Electronics 2022 JOURNAL OF POWER ELECTRONICS Vol.22 No.11
In this paper, a composite passivity-based control method based on a finite-time disturbance observer (FTDO) and a passivity-based control (PBC) is proposed to improve the stability of the Boost converters with constant power loads in DC Microgrids. The FTDO improves the robustness and rapidity of the system by accurately estimating system disturbances. The PBC ensures the stability of the system via its transient energy dissipation. The FTDO operates parallel to the PBC, and compensates the observed value to the PBC through a feedforward channel. When compared with other controls, the proposed composite passivity-based control has the advantages of a fast dynamic response and accurate tracking of system disturbances in a wide working range. Finally, the control method proposed in this paper is verified by MATLAB/Simulink simulations and hardware in the hard-ware-in-loop experiments.
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Hierarchical Reinforcement Learning Based on KNN Classification Algorithms
Shanhong Zhu,Weipeng Dong,Wei Liu 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.8
In recent years, machine learning is increasingly becoming an important field of computer science. A new method using KNN classification algorithm identifies the layered boundary to find subgoal condition, to automatic classifying of large state space, reaches the dimension reduction of state space, and on the basis of generated subspace classifying to structure subtasks, and then realizes the hierarchical learning tasks automatically. In autonomous system, Agent assigns to their task through interaction with the environment, using hierarchical reinforcement learning technology can help the Agent in the large, complex environment to improve learning efficiency. Through the experimental results the effectiveness of the proposed algorithm is demonstrated. The goal of this paper is to provide a basic overview for both specialists and non-specialists to how to decide a good reinforcement learning algorithm for classification.
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Amino-modified Mg-MOF-74: Synthesis, characterization and CO₂ adsorption performance
Xiaoying Lin,Weipeng Zeng,Minyi Liu,Qinhua Zhong,Ting Su,Linzhu Gong,Yamin Liu 대한환경공학회 2023 Environmental Engineering Research Vol.28 No.1
Based on the solvothermal method to synthesize Mg-MOF-74, the amino-functionalized Mg-MOF-nNH₂ was prepared through addition of amino-containing ligands. Physicochemical properties of Mg-MOF-nNH₂ materials were well characterized by Powder X-ray diffraction (PXRD), Scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FT-IR), N₂ adsorption/desorption isotherms (BET). The adsorption properties of the resulting materials were studied for CO₂. In all the samples, the micropore volume of Mg-MOF-1/8NH₂ was 0.46 ㎤ g<SUP>−1</SUP> and the specific surface area was 924.19㎡ g<SUP>−1</SUP>, the highest CO₂ saturated adsorption capacity was 3.9 mmol g<SUP>−1</SUP>, and the dynamic adsorption capacity was 1.27 mmol g<SUP>−1</SUP>. The adsorption processes agreed well with the Langmuir isotherm and Avrami model.
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Amino-modified Mg-MOF-74: Synthesis, characterization and CO2 adsorption performance
Xiaoying Lin,Weipeng Zeng,Minyi Liu,Qinhua Zhong,Ting Su,Linzhu Gong,Yamin Liu 대한환경공학회 2023 Environmental Engineering Research Vol.28 No.1
Based on the solvothermal method to synthesize Mg-MOF-74, the amino-functionalized Mg-MOF-nNH2 was prepared through addition of amino-containing ligands. Physicochemical properties of Mg-MOF-nNH2 materials were well characterized by Powder X-ray diffraction (PXRD), Scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FT-IR), N2 adsorption/desorption isotherms (BET). The adsorption properties of the resulting materials were studied for CO2. In all the samples, the micropore volume of Mg-MOF-1/8NH2 was 0.46 cm3 g−1 and the specific surface area was 924.19m2 g−1, the highest CO2 saturated adsorption capacity was 3.9 mmol g−1, and the dynamic adsorption capacity was 1.27 mmol g−1. The adsorption processes agreed well with the Langmuir isotherm and Avrami model.
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Oil Pipeline Weld Defect Identification System Based on Convolutional Neural Network
( Jiaze Shang ),( Weipeng An ),( Yu Liu ),( Bang Han ),( Yaodan Guo ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.3
The automatic identification and classification of image-based weld defects is a difficult task due to the complex texture of the X-ray images of the weld defect. Several depth learning methods for automatically identifying welds were proposed and tested. In this work, four different depth convolutional neural networks were evaluated and compared on the 1631 image set. The concavity, undercut, bar defects, circular defects, unfused defects and incomplete penetration in the weld image 6 different types of defects are classified. Another contribution of this paper is to train a CNN model "RayNet" for the dataset from scratch. In the experiment part, the parameters of convolution operation are compared and analyzed, in which the experimental part performs a comparative analysis of various parameters in the convolution operation, compares the size of the input image, gives the classification results for each defect, and finally shows the partial feature map during feature extraction with the classification accuracy reaching 96.5%, which is 6.6% higher than the classification accuracy of other existing fine-tuned models, and even improves the classification accuracy compared with the traditional image processing methods, and also proves that the model trained from scratch also has a good performance on small-scale data sets. Our proposed method can assist the evaluators in classifying pipeline welding defects.
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Yang Jiejin,Chen Zeyang,Liu Weipeng,Wang Xiangpeng,Ma Shuai,Jin Feifei,Wang Xiaoying 대한영상의학회 2021 Korean Journal of Radiology Vol.22 No.3
Objective: The mitotic count of gastrointestinal stromal tumors (GIST) is closely associated with the risk of planting and metastasis. The purpose of this study was to develop a predictive model for the mitotic index of local primary GIST, based on deep learning algorithm. Materials and Methods: Abdominal contrast-enhanced CT images of 148 pathologically confirmed GIST cases were retrospectively collected for the development of a deep learning classification algorithm. The areas of GIST masses on the CT images were retrospectively labelled by an experienced radiologist. The postoperative pathological mitotic count was considered as the gold standard (high mitotic count, > 5/50 high-power fields [HPFs]; low mitotic count, ≤ 5/50 HPFs). A binary classification model was trained on the basis of the VGG16 convolutional neural network, using the CT images with the training set (n = 108), validation set (n = 20), and the test set (n = 20). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated at both, the image level and the patient level. The receiver operating characteristic curves were generated on the basis of the model prediction results and the area under curves (AUCs) were calculated. The risk categories of the tumors were predicted according to the Armed Forces Institute of Pathology criteria. Results: At the image level, the classification prediction results of the mitotic counts in the test cohort were as follows: sensitivity 85.7% (95% confidence interval [CI]: 0.834–0.877), specificity 67.5% (95% CI: 0.636–0.712), PPV 82.1% (95% CI: 0.797–0.843), NPV 73.0% (95% CI: 0.691–0.766), and AUC 0.771 (95% CI: 0.750–0.791). At the patient level, the classification prediction results in the test cohort were as follows: sensitivity 90.0% (95% CI: 0.541–0.995), specificity 70.0% (95% CI: 0.354–0.919), PPV 75.0% (95% CI: 0.428–0.933), NPV 87.5% (95% CI: 0.467–0.993), and AUC 0.800 (95% CI: 0.563–0.943). Conclusion: We developed and preliminarily verified the GIST mitotic count binary prediction model, based on the VGG convolutional neural network. The model displayed a good predictive performance.
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Lin Xiaoying,Zeng Weipeng,Chen Yilan,Su Ting,Zhong Qinhua,Gong Linzhu,Liu Yamin 한국탄소학회 2022 Carbon Letters Vol.32 No.3
A porous-carbon material UiO-66-C was prepared from metal–organic frameworks UiO-66 by carbonization in inert gas atmosphere. Physicochemical properties of UiO-66-C materials were well characterized by Powder X-ray diffraction (PXRD), Scanning electron microscope (SEM), Fourier-transform infrared spectroscopy (FT-IR), Raman spectrometer, N2 adsorption/desorption isotherms (BET), and the adsorption properties of the products were studied UiO-66-C has a high specific surface area up to 1974.17 m2/g. Besides, the adsorption capacity of tetracycline could reach 678.19 mg/g, the adsorption processes agreed well with the pseudo-second-order kinetic model and Langmuir isotherm model.
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Yang, Xiaojuan,Wu, Qingping,Zhang, Jumei,Guo, Weipeng,Mo, Shuping,Liu, Shengrong 한국식품과학회 2016 Food Science and Biotechnology Vol.25 No.4
This study aimed to classify a collection of Enterobacter sakazakii (E. sakazakii) strains previously identified from powdered infant formula (PIF) to species level by recN gene sequencing and biochemical testing to determine the distribution of Cronobacter species in China and investigate the strain diversity by cellular fatty acid (CFA) analysis. Of 24 E. sakazakii isolates, 23 were identified as C. sakazakii and one was C. malonaticus. The 23 C. sakazakii isolates showed the same CFA profiles. The C. malonaticus isolate was discriminated from the C. sakazakii isolates by the significant difference in the amounts of $C_{12:0}$, $C_{14:0}$, and $C_{17:0\;cyclo}$ acids. These results showed that C. sakazakii and C. malonaticus were the common Cronobacter species distributed in PIF in China and that the isolates of the two species exhibited different CFA profiles. These findings are of value for epidemiological investigations and provide an alternative method for confirming various Cronobacter spp.
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