176 Hits in 1.3 sec

ESR Estimation Schemes of Output Capacitor for Buck Converter from Capacitor Perspective

Lei Ren, Lei Zhang, Chunying Gong
2020 Electronics  
The aluminum electrolytic capacitor (AEC) is one of the most vulnerable parts in power electronic converters and its reliability is crucial to the whole system. With the growth of service time, the equivalent series resistance (ESR) increases and the capacitance (C) decreases due to the loss of electrolytes, which will result in extra power loss and even damage to transistors. To prevent significant damages, the AEC must be replaced at an optimal period and online health monitoring is
more » ... ble. Through the analysis of degradation parameters (ESR and C), ESR is proved to be a better health indicator and therefore is determined as the monitoring parameter for AEC. From the capacitor perspective, ESR estimation schemes of output capacitors for a Buck converter are studied. Based on the voltage–current characteristics, two ESR calculation models are proposed, which are applicable for both continuous conduction mode (CCM) and discontinuous conduction mode (DCM). From the point of implementation view, the advantages and disadvantages of the two estimation schemes are pointed out, respectively. A Buck prototype is built and tested, and simulation and experimental results are provided to validate the proposed ESR estimation schemes.
doi:10.3390/electronics9101596 fatcat:vkmqipnpmbe7bhv7vtnum2x34i

TP53 codon 72 polymorphism and glioma risk: A meta-analysis

2011 Oncology Letters  
TP53 codon 72 polymorphism has been reported to affect regulatory networks central to glioma development. Although a number of published studies noted the association between TP53 codon 72 polymorphism and glioma risk, their conclusions were inconsistent. A meta-analysis was used to assess the possible association between TP53 codon 72 polymorphism and glioma risk. The PubMed databases were searched, relevant articles were identified and data were retrieved based on the inclusion criteria. The
more » ... dds ratio (OR) and 95% confidence interval (95% CI) were determined on the pooled dataset. We retrieved eight different studies including 2,260 glioma cases and 3,506 controls. However, no association was found between the TP53 codon 72 polymorphism and glioma risk regarding the comparison between glioma cases and the controls. By further stratification based on criteria such as tumor grade, and the geographical location of the patients and the relevant controls, we found a significant association in the subgroup of patients with high-grade glioma in Europeans compared to controls in two models of TP53 codon 72 polymorphism, which include the dominant model [C/C + G/C vs. G/G: OR=1.35, 95% CI (1.14, 1.59), P=0.0005, P h =0.13] and the additive model [C allele vs. G allele: OR=1.16, 95% CI (1.02, 1.33), P=0.03, P h =0.37]. Our analysis suggests that TP53 codon 72 polymorphism is associated with an increased risk of high-grade glioma development in Europeans.
doi:10.3892/ol.2011.521 pmid:22740959 pmcid:PMC3362515 fatcat:cy3tfltgvjg7xk7rhj65ax4m7i

Inhibitory effect of silver nanomaterials on transmissible virus-induced host cell infections

Xiaonan Lv, Peng Wang, Ru Bai, Yingying Cong, Siqingaowa Suo, Xiaofeng Ren, Chunying Chen
2014 Biomaterials  
Coronaviruses belong to the family Coronaviridae, which primarily cause infection of the upper respiratory and gastrointestinal tract of hosts. Transmissible gastroenteritis virus (TGEV) is an economically significant coronavirus that can cause severe diarrhea in pigs. Silver nanomaterials (Ag NMs) have attracted great interests in recent years due to their excellent anti-microorganism properties. Herein, four representative Ag NMs including spherical Ag nanoparticles (Ag NPs, NM-300), two
more » ... of silver nanowires (XFJ011) and silver colloids (XFJ04) were selected to study their inhibitory effect on TGEV-induced host cell infection in vitro. Ag NPs were uniformly distributed, with particle sizes less than 20 nm by characterization of environmental scanning electron microscope and transmission electron microscope. Two types of silver nanowires were 60 nm and 400 nm in diameter, respectively. The average diameter of the silver colloids was approximately 10 nm. TGEV infection induced the occurring of apoptosis in swine testicle (ST) cells, down-regulated the expression of Bcl-2, up-regulated the expression of Bax, altered mitochondrial membrane potential, activated p38 MAPK signal pathway, and increased expression of p53 as evidenced by immunofluorescence assays, real-time PCR, flow cytometry and Western blot. Under non-toxic concentrations, Ag NPs and silver nanowires significantly diminished the infectivity of TGEV in ST cells. Moreover, further results showed that Ag NPs and silver nanowires decreased the number of apoptotic cells induced by TGEV through regulating p38/mitochondria-caspase-3 signaling pathway. Our data indicate that Ag NMs are effective in prevention of TGEV-mediated cell infection as a virucidal agent or as an inhibitor of viral entry and the present findings may provide new insights into antiviral therapy of coronaviruses.
doi:10.1016/j.biomaterials.2014.01.054 pmid:24524838 pmcid:PMC7112386 fatcat:6g33nt67cvapfji4nbg5a27agq

Quantifying Urban Land Sprawl and its Driving Forces in Northeast China from 1990 to 2015

Lin Chen, Chunying Ren, Bai Zhang, Zongming Wang, Mingyue Liu
2018 Sustainability  
Author Contributions: Lin Chen, Chunying Ren, and Bai Zhang designed this research. Lin Chen and Mingyue Liu conducted the analysis. Lin Chen, Chunying Ren, and Zongming Wang wrote the paper.  ... 
doi:10.3390/su10010188 fatcat:bwifpcdmwfcqpefkss2whqdhwm

Multi-Sensor Prediction of Stand Volume by a Hybrid Model of Support Vector Machine for Regression Kriging

Lin Chen, Chunying Ren, Bai Zhang, Zongming Wang
2020 Forests  
Quantifying stand volume through open-access satellite remote sensing data supports proper management of forest stand. Because of limitations on single sensor and support vector machine for regression (SVR) as well as benefits from hybrid models, this study innovatively builds a hybrid model as support vector machine for regression kriging (SVRK) to map stand volume of the Changbai Mountains mixed forests covering 171,450 ha area based on a small training dataset (n = 928). This SVRK model
more » ... rated SVR and its residuals interpolated by ordinary kriging. To determine the importance of multi-sensor predictors from ALOS and Sentinel series, the increase in root mean square error (RMSE) of SVR was calculated by removing the variable after the standardization. The SVRK model achieved accuracy with mean error, RMSE and correlation coefficient in –2.67%, 25.30% and 0.76, respectively, based on an independent dataset (n = 464). The SVRK improved the accuracy of 9% than SVR based on RMSE values. Topographic indices from L band InSAR, backscatters of L band SAR, and texture features of VV channel from C band SAR, as well as vegetation indices of the optical sensor were contributive to explain spatial variations of stand volume. This study concluded that SVRK was a promising approach for mapping stand volume in the heterogeneous temperate forests with limited samples.
doi:10.3390/f11030296 fatcat:sr5dfz54ojfrdmaceicq4hbrni

Spatio–Temporal Changes of Forests in Northeast China: Insights from Landsat Images and Geospatial Analysis

Chunying Ren, Lin Chen, Zongming Wang, Bai Zhang, Yanbiao Xi, Chunyan Lu
2019 Forests  
Dramatic changes of forests have strong influence on regional and global carbon cycles, biodiversity, and ecosystem services. Understanding dynamics of forests from local to global scale is crucial for policymaking and sustainable development. In this study, we developed an updating and object-based image analysis method to map forests in Northeast China using Landsat images from 1990 to 2015. The spatio–temporal patterns of forests were quantified based on resultant maps and geospatial
more » ... . Results showed that the percentage of forested area occupying the entire northeast China was more than 40%, about 94% of initial forest cover remained unchanged (49.37 × 104 km2) over the course of 25 years. A small net forest loss (1051 km2) was observed during 1990–2015. High forest gain (10,315 km2) and forest loss (9923 km2) both occurred from 2010 to 2015. At the provincial level, Heilongjiang demonstrated the highest rate of deforestation, with a net loss of 1802 km2 (0.89%). Forest changes along elevation, slope, and distance from settlements and roads were also investigated. Over 90% of forest changes occurred in plains and low mountain areas within the elevation of 200–1000 m and slope under 15°. The most dramatic forest changes can be found within the distance of 2000 m from settlements and roads. The reclamation of sloping land, construction of settlements and roads, and possible smallholder clearing contributed more to forest loss, while ecological projects and related government policies play an important role on afforestation and reforestation. These results can provide useful spatial information for further research on the driving forces and consequences of forest changes, which have critical implications for scientific conservation and management of forests.
doi:10.3390/f10110937 fatcat:j6raj6m2tvdtpn6e7u3ircxwse

Estimation of Forest Above-Ground Biomass by Geographically Weighted Regression and Machine Learning with Sentinel Imagery

Lin Chen, Chunying Ren, Bai Zhang, Zongming Wang, Yanbiao Xi
2018 Forests  
Accurate forest above-ground biomass (AGB) is crucial for sustaining forest management and mitigating climate change to support REDD+ (reducing emissions from deforestation and forest degradation, plus the sustainable management of forests, and the conservation and enhancement of forest carbon stocks) processes. Recently launched Sentinel imagery offers a new opportunity for forest AGB mapping and monitoring. In this study, texture characteristics and backscatter coefficients of Sentinel-1, in
more » ... ddition to multispectral bands, vegetation indices, and biophysical variables of Sentinal-2, based on 56 measured AGB samples in the center of the Changbai Mountains, China, were used to develop biomass prediction models through geographically weighted regression (GWR) and machine learning (ML) algorithms, such as the artificial neural network (ANN), support vector machine for regression (SVR), and random forest (RF). The results showed that texture characteristics and vegetation biophysical variables were the most important predictors. SVR was the best method for predicting and mapping the patterns of AGB in the study site with limited samples, whose mean error, mean absolute error, root mean square error, and correlation coefficient were 4 × 10−3, 0.07, 0.08 Mg·ha−1, and 1, respectively. Predicted values of AGB from four models ranged from 11.80 to 324.12 Mg·ha−1, and those for broadleaved deciduous forests were the most accurate, while those for AGB above 160 Mg·ha−1 were the least accurate. The study demonstrated encouraging results in forest AGB mapping of the normal vegetated area using the freely accessible and high-resolution Sentinel imagery, based on ML techniques.
doi:10.3390/f9100582 fatcat:3sz7s46wl5f3hdhfppatxmvyyq

Cyclin-Dependent Kinase 2 Promotes Tumor Proliferation and Induces Radio Resistance in Glioblastoma

Jia Wang, Tong Yang, Gaofeng Xu, Hao Liu, Chunying Ren, Wanfu Xie, Maode Wang
2016 Translational Oncology  
Accumulating evidence indicates that CDK2 promotes hyperproliferation and is associated to poor prognosis in multiple cancer cells. However, the physiological role of CDK2 in GBM and the biological mechanism still remains unclear. In this study, we identified that CDK2 expression was significantly enriched in GBM tumors compared with normal brain. Additionally, CDK2 was functionally required for tumor proliferation and its expression was associated to poor prognosis in GBM patients.
more » ... , CDK2 induced radio resistance in GBM cells and CDK2 knock down increased cell apoptosis when combined with radiotherapy. Therapeutically, we found that CDK2 inhibitor attenuated tumor growth both in vitro and in vivo. Collectively, CDK2 promotes proliferation, induces radio resistance in GBM, and could become a therapeutic target for GBM.
doi:10.1016/j.tranon.2016.08.007 pmid:27863310 pmcid:PMC5118617 fatcat:zgdd2krfq5fqpgizmhn6wtvswm

Mapping Forest Cover in Northeast China from Chinese HJ-1 Satellite Data Using an Object-Based Algorithm

Chunying Ren, Bai Zhang, Zongming Wang, Lin Li, Mingming Jia
2018 Sensors  
Forest plays a significant role in the global carbon budget and ecological processes. The precise mapping of forest cover can help significantly reduce uncertainties in the estimation of terrestrial carbon balance. A reliable and operational method is necessary for a rapid regional forest mapping. In this study, the goal relies on mapping forest and subcategories in Northeast China through the use of high spatio-temporal resolution HJ-1 imagery and time series vegetation indices within the
more » ... xt of an object-based image analysis and decision tree classification. Multi-temporal HJ-1 images obtained in a single year provide an opportunity to acquire phenology information. By analyzing the difference of spectral and phenology information between forest and non-forest, forest subcategories, decision trees using threshold values were finally proposed. The resultant forest map has a high overall accuracy of 0.91 ± 0.01 with a 95% confidence interval, based on the validation using ground truth data from field surveys. The forest map extracted from HJ-1 imagery was compared with two existing global land cover datasets: GlobCover 2009 and MCD12Q1 2009. The HJ-1-based forest area is larger than that of MCD12Q1 and GlobCover and more closely resembles the national statistics data on forest area, which accounts for more than 40% of the total area of the Northeast China. The spatial disagreement primarily occurs in the northern part of the Daxing'an Mountains, Sanjiang Plain and the southwestern part of the Songliao Plain. The compared result also indicated that the forest subcategories information from global land cover products may introduce large uncertainties for ecological modeling and these should be cautiously used in various ecological models. Given the higher spatial and temporal resolution, HJ-1-based forest products could be very useful as input to biogeochemical models (particularly carbon cycle models) that require accurate and updated estimates of forest area and type.
doi:10.3390/s18124452 fatcat:g6fmntdekjhcfhrrw7fjxdvtpm

Octahedral-shaped perovskite nanocrystals and their visible-light photocatalytic activity

Simin Yin, He Tian, Zhaohui Ren, Xiao Wei, Chunying Chao, Jingyuan Pei, Xiang Li, Gang Xu, Ge Shen, Gaorong Han
2014 Chemical Communications  
Octahedral-shaped perovskite PbTiO3 nanocrystals have been hydrothermally synthesized for the first time by the introduction of lithium nitride, demonstrating remarkable visible-light potocatalytic activity in the degradation of MB aqueous solution.
doi:10.1039/c4cc01118j pmid:24769605 fatcat:uywkjpwgcrbrpbpcedu6oduslq

Polyoxometalate-based homochiral metal-organic frameworks for tandem asymmetric transformation of cyclic carbonates from olefins

Qiuxia Han, Bo Qi, Weimin Ren, Cheng He, Jingyang Niu, Chunying Duan
2015 Nature Communications  
Currently, great interest is focused on developing auto-tandem catalytic reactions; a substrate is catalytically transferred through mechanistically distinct reactions without altering any reaction conditions. Here by incorporating a pyrrolidine moiety as a chiral organocatalyst and a polyoxometalate as an oxidation catalyst, a powerful approach is devised to achieve a tandem catalyst for the efficient conversion of CO 2 into value-added enantiomerically pure cyclic carbonates. The
more » ... ic sites are orderly distributed and spatially matched in the framework. The captured CO 2 molecules are synergistically fixed and activated by well-positioned pyrrolidine and amine groups, providing further compatibility with the terminal W ¼ O activated epoxidation intermediate and driving the tandem catalytic process in a single workup stage and an asymmetric fashion. The structural simplicity of the building blocks and the use of inexpensive and readily available chemical reagents render this approach highly promising for the development of practical homochiral materials for CO 2 conversion.
doi:10.1038/ncomms10007 pmid:26678963 pmcid:PMC4703842 fatcat:sipf73mmovfkdbilrxyhuagn6e

Exploitation of time series Sentinel-2 data and different machine learning algorithms for detailed tree species classification

Yanbiao Xi, Chunying Ren, Qingjiu Tian, Yongxing Ren, Xinyu Dong, Zhichao Zhang
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
(Corresponding author: Chunying Ren.)  ... 
doi:10.1109/jstars.2021.3098817 fatcat:54so3pca5rfjxfuom6cwh44nay

Optimal Combination of Predictors and Algorithms for Forest Above-Ground Biomass Mapping from Sentinel and SRTM Data

Lin Chen, Yeqiao Wang, Chunying Ren, Bai Zhang, Zongming Wang
2019 Remote Sensing  
Accurate forest above-ground biomass (AGB) mapping is crucial for sustaining forest management and carbon cycle tracking. The Shuttle Radar Topographic Mission (SRTM) and Sentinel satellite series offer opportunities for forest AGB monitoring. In this study, predictors filtered from 121 variables from Sentinel-1 synthetic aperture radar (SAR), Sentinal-2 multispectral instrument (MSI) and SRTM digital elevation model (DEM) data were composed into four groups and evaluated for their
more » ... in prediction of AGB. Five evaluated algorithms include linear regression such as stepwise regression (SWR) and geographically weighted regression (GWR); machine learning (ML) such as artificial neural network (ANN), support vector machine for regression (SVR), and random forest (RF). The results showed that the RF model used predictors from both the Sentinel series and SRTM DEM performed the best, based on the independent validation set. The RF model achieved accuracy with the mean error, mean absolute error, root mean square error, and correlation coefficient in 1.39, 25.48, 61.11 Mg·ha−1 and 0.9769, respectively. Texture characteristics, reflectance, vegetation indices, elevation, stream power index, topographic wetness index and surface roughness were recommended predictors for AGB prediction. Predictor variables were more important than algorithms for improving the accuracy of AGB estimates. The study demonstrated encouraging results in the optimal combination of predictors and algorithms for forest AGB mapping, using openly accessible and fine-resolution data based on RF algorithms.
doi:10.3390/rs11040414 fatcat:llt3tmh7mnborlvmbi243npu5i

Functionalized graphene oxide for anti-VEGF siRNA delivery: preparation, characterization and evaluation in vitro and in vivo

Lulu Ren, Yifan Zhang, Chunying Cui, Yanzhao Bi, Xu Ge
2017 RSC Advances  
GO–PLL–SDGR/VEGF-siRNA inhibits tumor growth as a tumor targeting delivery system.
doi:10.1039/c7ra00810d fatcat:r47ey46ai5extkzqq4zbb5cora

Impact of land use/land cover changes on ecosystem services in the Nenjiang River Basin, Northeast China

Zhiliang Wang, Zongming Wang, Bai Zhang, Chunyan Lu, Chunying Ren
2015 Ecological Processes  
However, annual and seasonal precipitation in Northeastern China shows slightly decreasing trends, especially in summer precipitation (Ren et al. 2000; Lu, 2009 ).  ... 
doi:10.1186/s13717-015-0036-y fatcat:y4wjcs5jybcizjhrpmbo2vxd7u
« Previous Showing results 1 — 15 out of 176 results