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Your search keyword '"Ren, Haifeng"' showing total 17 results
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17 results on '"Ren, Haifeng"'

2. Automatic recognition of active landslides by surface deformation and deep learning.

Author

Wang, Xianmin, Chen, Wenxue, Ren, Haifeng, and Guo, Haixiang

Subjects
ARTIFICIAL neural networks, CONVOLUTIONAL neural networks, MACHINE learning, SYNTHETIC aperture radar, LANDSLIDES, DEFORMATION of surfaces
Abstract

Catastrophic landslides are generally evolved from potential active landslides, and early identification of active landslides over an extensive region is vital to effective prevention and control of disastrous landslides in urban areas. Interferometric Synthetic Aperture Radar (InSAR) has immense potential in mapping active landslides. However, artificial interpretation of InSAR measurements and manual recognition of active landslides are very laborious and time-consuming, with a relatively high missing and false alarms. That hinders the application of InSAR technique and the identification of active landslides in wide areas. Automatic recognition of active landslides has always been a great challenge and has been relatively rarely investigated by previous studies. This work establishes comprehensive identification indices of geoenvironmental, disaster-triggering, and surface deformation features. Moreover, it suggests a novel deep learning algorithm of SDeepFM to conduct automatic identification of active landslides across a vast and landslide-serious area of Hualong County. Some new viewpoints are suggested as follows. (1) The identification indices consist of disaster-controlling, disaster-inducing, and active deformation characteristics and are constructed in terms of the cause characteristics of active landslides. Thus, it can effectively decrease the false alarms of active landslide identification. (2) The proposed SDeepFM algorithm features a spatial-perception ability and can adequately extract and fuse the low-level and high-level semantic features. It outperforms the classification and regression tree (CART), multi-layer perceptron (MLP), convolutional neural network (CNN), and deep neural network (DNN) algorithms. The test accuracy attains 0.91, 99.73%, 90.21%, 0.92, 0.96, and 0.91 in F1-score, Accuracy, Precision, Recall, AUC, and Kappa, respectively. (3) A total of 164 active landslides are exactly recognized, and 39 active landslides are newly identified in this work. (4) In Hualong County, the characteristics of slope deformation, spatial context, lithology, tectonic movement, human activity, and topography play important roles in active landslide identification. River distribution and rainfall also contribute to active landslide recognition. [ABSTRACT FROM AUTHOR]

Published
2024
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4. Study on Failure Law of Mining Process of Narrow Coal Pillars in Fully Mechanized Caving Roadway

Author

Ren Haifeng, Zhao Xuewen, and Cao Peng

Subjects
Environmental sciences, GE1-350
Abstract

In order to determine the damage law of narrow coal pillars in the roadway along the goaf, taking the 4-5(06) working face of a mine in Xinjiang as the research object, the 3D finite difference software FLAC3D is used to analyse the stress and displacement distribution characteristics of narrow coal pillars in the mining process. The results show that the internal stress of the coal pillar reaches the peak when the narrow coal pillar advances from 11m to 12m, and the coal pillar is subjected to the pre-supporting pressure, the range of the rupture zone is increased, and the bearing capacity is obviously reduced. When the working face advances 65m, the displacement in the coal column reaches a peak, and the deformation of the coal column is more serious. The field test results show that the damage law of the narrow coal pillars in the working face mining process is basically consistent with the simulation results. After the bolts, the cable-stayed anchor cable and the shotcrete, the deformation of the narrow coal pillar is in a controllable range, and the safety production requirements of the working face are realized.

Published
2019
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9. miR-1305 Inhibits The Progression Of Non-Small Cell Lung Cancer By Regulating MDM2

Author

Cai,Yuxing, Hao,Yi, Ren,HaiFeng, Dang,ZhiGuo, Xu,Hui, Xue,Xiangfei, and Gao,Yan

Subjects
Cancer Management and Research, neoplasms
Abstract

Yuxing Cai,1 Yi Hao,2 HaiFeng Ren,3 ZhiGuo Dang,3 Hui Xu,1 Xiangfei Xue,1 Yan Gao3 1Department of Respiratory Medicine, Baoji Central Hospital, Baoji, 721008, People’s Republic of China; 2Department of Pediatric Surgery, Baoji Maternal and Child Health Hospital, Baoji, 721008, People’s Republic of China; 3Department of Respiratory Medicine, People Hospital BaoJi City, Baoji, 721001, People’s Republic of ChinaCorrespondence: Yan GaoDepartment of Respiratory Medicine, People Hospital BaoJi City, No. 24 Xinhua Street, Weibin District, Baoji City, Shanxi Province 721001, People’s Republic of ChinaEmail zhungao703730393@126.comBackground: Increasing evidence has suggested the critical implication of microRNAs (miRNAs) in the initiation and progression of non-small cell lung cancer (NSCLC). Previous studies have shown the tumor-suppressive function of miR-1305 in cancer; however, the role of miR-1305 in NSCLC has not been fully understood.Methods: The expression of miR-1305 in NSCLC was detected by RT-qPCR. The influence of miR-1305 on the growth of NSCLC cells was determined via Cell Counting Kit 8 (CCK-8), colony formation and FACS analysis. The targets of miR-1305 were predicted with the miRDB database. Luciferase reporter assay was performed to investigate the binding between miR-1305 and 3ʹ-UTR of MDM2. Western blot was applied to check the expression of MDM2 with miR-1305.Results: Here, we found that miR-1305 was down-regulated in NSCLC tissues and cell lines. Decreased miR-1305 was significantly correlated with the metastasis and poor prognostics of NSCLC patients. Overexpression of miR-1305 inhibited the proliferation and migration and promoted the apoptosis of NSCLC cells. Bioinformatics and luciferase assay uncovered that the mouse/murine double minute 2 (MDM2) was a target of miR-1305. miR-1305 bound the 3ʹ-untranslated region (UTR) of MDM2 and decreased the expression of MDM2 in NSCLC cells. As MDM2 was a negative regulator of p53, decreased MDM2 by miR-1305 up-regulated the abundance of p53 in NSCLC cells. Restoration of MDM2 markedly attenuated the suppressive role of miR-1305 in the proliferation and migration of NSCLC cells.Conclusion: The findings provided novel mechanism of miR-1305/MDM2 signaling in regulating the progression of NSCLC, suggesting miR-1305 as a promising target for the treatment of NSCLC.Keywords: NSCLC, miR-1305, MDM2, p53

Published
2019

11. Fault prediction method based on multi-field information fusion for complicated ammunition feeding system

Author

Pan Mingzhi, Xu Xin, Pan Hong-xia, and Ren Haifeng

Subjects
Engineering, Signal processing, business.industry, 02 engineering and technology, Structural engineering, 010502 geochemistry & geophysics, Fault (power engineering), 01 natural sciences, Maintenance engineering, Fault detection and isolation, Reliability engineering, Vibration, Ammunition, Information fusion, 0202 electrical engineering, electronic engineering, information engineering, Multi field, 020201 artificial intelligence & image processing, business, human activities, 0105 earth and related environmental sciences
Abstract

Combining multi-field information fusion theory with the ammunition feeding system, a multi-level information fusion method for fault detection and prediction is proposed in this paper. Firstly, it is studied that the occurrence and development mechanism of damage and failure of complicated ammunition feed system under rapid impact. The wear damage and stop shooting faults are diagnosed by measuring the power loss characteristics at different scales. Using modern signal processing and intelligent algorithm, the weak damage and wear stuck failure characteristics are extracted, and the fault positions are identified. On this basis, and combining the theories of impact vibration and wear damage, the degree of wear stuck failure, the law of damage development and expansion, and the remaining life of the system after the emergence of multi-damage fault, can be predicted. Finally, multi-field information fusion theories and methods for fault monitoring are established, and a monitoring platform with embedded system is developed.

Published
2017
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12. Role of cytokines and chemokines in alcohol-induced tumor promotion

Author

Chen,Danlei, Zhang,Fengyun, Ren,Haifeng, Luo,Jia, and Wang,Siying

Subjects
OncoTargets and Therapy
Abstract

Danlei Chen,1 Fengyun Zhang,1 Haifeng Ren,1 Jia Luo,2 Siying Wang1 1School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, People’s Republic of China; 2Department of Pharmacology and Nutritional Sciences, University of Kentucky, College of Medicine, Lexington, KY, USA Abstract: Excessive chronic alcohol consumption has become a worldwide health problem. The oncogenic effect of chronic alcohol consumption is one of the leading concerns. The mechanisms of alcohol-induced tumorigenesis and tumor progression are largely unknown, although many factors have been implicated in the process. This review discusses the recent progress in this research area with concentration on alcohol-induced dysregulation of cytokines and chemokines. Based on the available evidence, we propose that alcohol promotes tumor progression by the dysregulation of the cytokine/chemokine system. In addition, we discuss specific transcription factors and signaling pathways that are involved in the action of these cytokines/chemokines and the oncogenic effect of alcohol. This review provides novel insight into the mechanisms of alcohol-induced tumor promotion. Keywords: alcohol, tumor promotion, cytokines, chemokines, transcription factors, signal transduction, therapy

Published
2017

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