Investigation and Simulation Study on the Cascading Trip-off Fault of a Large Number of Wind Turbines in China on May 14, 2012

Ying Qiao,Zong-Xiang Lu,Ji Lu,Jia-Yang Ruan,Lin-lin Wu 대한전기학회 2015 Journal of Electrical Engineering & Technology Vol.10 No.6

The integration of the large-scale wind power brings great challenge to the stability of the power grid. This paper investigates and studies the fault on May 14, 2012 of the large-scale cascading trip-off of wind turbines in North China. According to the characteristics of the voltage variation, the fault process is divided into three stages: the pre-event stage, the critical stage before cascading, and the cascading stage. The scenes in the fault are reproduced, using the full-size actual power system model. Simulation models of double-fed induction generators (DFIGs) and SVCs including protection settings and controller strategies are carefully chosen to find out the reason of voltage instability in each stage. Some voltage dynamic that have never been observed before in the faults of the same kind are analyzed in detail, and an equivalent voltage sensitive dynamic model of DFIG is proposed for the fast computation. The conclusions about the voltage dynamics are validated by the actual PMU observation evidence.

중국 그린소비 담론의 탐색적 연구: 텍스트마이닝과 감성분석을 중심으로

Ying Lu,박상도 한국유통경영학회 2023 유통경영학회지 Vol.26 No.2

Purpose: China’s green consumption is crucial for implementing sustainable development goals and carbon neutrality. The public practices China’s green consumption, and we need to understand macroscopically the changing trend and prepare strategically for related industries/products. We need the wisdom to draw strategic implications for future competition and cooperation by analyzing the green consumption discourse. Research design, data, and methodology: First, we analyzed China’s previous studies and policies on green consumption. In addition, discourses were collected under the theme of green consumption, and text mining and sentiment analysis were performed. The data used was collected based on the online channels Baidu and CNKI. Text mining utilized TF-IDF and centrality, and sentiment analysis was conducted using the sentiment dictionary. Results: As a result of text mining, the social transition to green consumption was characterized by a change from government-led to business-led and citizen-led. In particular, words related to digital transformation have recently been attracting attention, suggesting that science and technology should be incorporated into the green consumption transformation process. As a result of the sentiment analysis, it was found that the general public had a positive evaluation of green consumption during the entire period. Although there was some lack of understanding and indifference to green consumption, it was found that they generally had hope for conversion to green consumption. Implications: First, as China’s green consumption transition progresses rapidly, the government and businesses should pay attention to technological changes and export indicators related to green consumption. Second, it is necessary to establish a good image of Korean companies by actively carrying out CSR activities to spread green consumption awareness. Third, concerning carbon neutrality and environmental protection issues, it is necessary to pay attention to environmental regulations and subsidies in the Chinese market and prepare strategies for entering the Chinese market.

Mechanism of stress-whitening in semicrystalline polymers

Ying Lu,Yaotao Wang,Yongfeng Men 한국고분자학회 2016 한국고분자학회 학술대회 연구논문 초록집 Vol.41 No.2

Protective effects of 2',4'-dihydroxy-6'-methoxy-3',5'-dimethylchalcone against hydrogen peroxide-induced oxidative stress in hepatic L02 cell

Lu, Yue,Zhang, Yan-Yan,Hu, Ying-Chun,Lu, Yan-Hua 대한약학회 2014 Archives of Pharmacal Research Vol.37 No.9

2',4'-Dihydroxy-6'-methoxy-3',5'-dimethylchalcone (DMC) is a chalcone isolated from the buds of Cleistocalyx operculatus (Roxb.) Merr. et Perry, and the hepatoprotective effects of DMC on Kunming mice have been studied in previous study. However, the effects of DMC on hepatocyte toxicity and corresponding mechanism remain unclear. The aim of this study was to evaluate the hepatoprotective mechanism of DMC in human hepatocytes (L02) treated with $H_2O_2$. The results demonstrated that pretreatment with DMC effectively protected $H_2O_2$-induced cell viability loss, cell membrane damage (lactate dehydrogenase, nitric oxide production and caspase-3 accumulation. Besides, DMC pretreatment increased the amount of glutathione, decreased malondialdehyde and the percentage of apoptotic L02 cells compared with only $H_2O_2$ treated group. Taken together, these results indicated that DMC had hepatoprotective effects against $H_2O_2$-induced liver injury by alleviating oxidative stress and apoptosis process in L02 cells, and DMC might be a potential candidate for the intervention of liver diseases.

Sparse Polynomial Mapping for Manifold Learning

Ying Xia,Qiang Lu,Hae-Young Bae 보안공학연구지원센터(IJSIP) 2014 International Journal of Signal Processing, Image Vol.7 No.6

Manifold learning is an approach for nonlinear dimensionality reduction and has been a hot research topic in the field of computer science. A disadvantage of manifold learning methods is, however, that there are no explicit mappings from the high-dimensional feature space to the low-dimensional representation space. It restricts the application of manifold learning methods in many practical problems such as target detection and classification. Previously, some methods have been proposed to provide linear or nonlinear mappings for manifold learning methods. However, a disadvantage of all these methods is that the learned projective functions are combinations of all the original features, thus it is often difficult to interpret the results. Moreover, the dense projection matrices of these approaches lead to a high cost of computation and storage. In this paper, a sparse polynomial mapping approach is proposed for manifold learning. We first get the low-dimensional representations of the high-dimensional input data by using a manifold learning method, and then a 1-based simplified polynomial regression is used to get a sparse polynomial mapping between the high-dimensional data and their low-dimensional representations. In particular, we apply this to the method of Laplacian eigenmap and derive a sparse nonlinear manifold learning algorithm, which is named sparse locality preserving polynomial embedding. Experimental results on real-world data show the effectiveness of our approach.

Wet-Spinning Fabrication of Flexible Conductive Composite Fibers from Silver Nanowires and Fibroin

Ying Lu,Jianwei Jiang,Sanghyuk Park,Dong Wang,Longhai Piao,Jinkwon Kim 대한화학회 2020 Bulletin of the Korean Chemical Society Vol.41 No.2

Biocompatible flexible conductive composite fibers have attracted great research interest because of multitude of their potential applications, such as wearable devices, biomedical sensors, and actuators. Herein, highly conductive and flexible silver nanowire (AgNW)/fibroin composite fibers were fabricated by using a wet-spinning technique. The composite fiber conductivity was as high as 5670?S/cm at an AgNW concentration of 29.1?wt%. The composite fibers also exhibited high flexibilities and could be folded without losing their conductivities. Furthermore, the composite fiber fabricated with a 3? draw ratio exhibited a breaking strain of 27.3% and breaking stress of 118.1 cN/dtex. Our attempt to produce such biocompatible flexible conductive composite fibers by using sustainable regenerated silk fibroins and compatible AgNWs via wet spinning may provide a practical way for fabricating functional biocompatible fiber materials.

Study on the Application of Ant Colony Algorithm in the Route of Internet of Things

Ying Lu,Wen Hu 보안공학연구지원센터 2013 International Journal of Smart Home Vol.7 No.3

Deficiency of Follistatin-Like Protein 1 Accelerates the Growth of Breast Cancer Cells at Lung Metastatic Sites

Ying Zhang,Xiaozhou Xu,Ying Yang,Jie Ma,Lulu Wang,Xiangzhi Meng,Bing Chen,Ling Qin,Tao Lu,Yan Gao 한국유방암학회 2018 Journal of breast cancer Vol.21 No.3

Purpose: Follistatin-like protein 1 (FSTL1) is a secreted glycoprotein that has been shown to play a role in various types of cancer. However, the clinical significance and function of FSTL1 in breast cancer have not been reported. We investigated the role of FSTL1 in breast cancer in this study. Methods: Enzyme-linked immunosorbent assays, western blot analysis, and reverse transcription polymerase chain reaction were used to monitor the expression of FSTL1 in breast cancer tissue and in serum samples from breast cancer patients. We employed a 4T1 breast cancer model and Fstl1+/− mice for in vivo studies. Hematoxylin and eosin staining, western blot analysis, and RNA sequencing were used to analyze the effect of FSTL1 on primary tumor growth and lung metastasis. Results: We demonstrated that the expression of FSTL1 is reduced in both the breast cancer tissue and the serum of breast cancer patients. We showed that reduced levels of FSTL1 in serum correlate with elevated expression of Ki-67 and epidermal growth factor receptor (EGFR) in cancer tissues. Moreover, lowered expression of FSTL1 was associated with decreased survival in breast cancer patients. Experiments on the Fstl1+/− mouse model established that FSTL1 deficiency had no effect on primary tumor growth, but increased the lung metastases of breast cancer cells, resulting in reduced survival of tumor-bearing mice. RNA sequencing found significantly reduced expression of Egln3 and increased expression of EGFR in Fstl1+/− mice. Thus, our results suggest that FSTL1 may affect the expression of EGFR through Egln3, inhibiting the proliferation of breast cancer cells at lung metastatic sites. Conclusion: In conclusion, we suggest a suppressor role of FSTL1 in breast cancer lung metastasis. Furthermore, FSTL1 may represent a potential prognostic biomarker and a candidate therapeutic target in breast cancer patients.

Profile of disposition, tissue distribution and excretion of the novel anti-human immunodeficiency virus (HIV) agent W-1 in rats

Ying-Yuan Lu,Xiao-Wei Wang,Xin Wang,Wen-Bing Dai,Qiang Zhang,Pu Li,Ya-Qing Lou,Chuang Lu,Jun-Yi Liu,Guo-Liang Zhang 대한약학회 2016 Archives of Pharmacal Research Vol.39 No.7

The purpose of this study was to characterize the disposition, distribution, excretion and plasma protein binding of 6-benzyl-1-benzyloxymethyl-5-iodouracil (W- 1) in rats. Concentrations of W-1 within biological samples were determined using a validated high performance liquid chromatography method. The plasma protein binding of W-1 was examined by equilibrium dialysis method. After oral administration of W-1 (50, 100 and 200 mg/kg, respectively) in self-microemulsifying drug delivery system formulation, the pharmacokinetic parameters of W-1 were as follows: the peak plasma concentrations (Cmax) were 0.42, 1.50 and 2.55 μg/mL, the area under the curve (AUC0-t) were 0.89, 2.27 and 3.96 lg/h mL and the plasma half-life (t1/2) were 5.15, 3.77 and 3.77 h, respectively. Moreover, the prototype of W-1 was rapidly and extensively distributed into fifteen tissues, especially higher concentrations were detected in intestine, stomach and liver, respectively. The plasma protein binding of W-1 in rat, beagle dog and human were in the range of 97.96–99.13 %. This study suggested that W-1 has an appropriate pharmacokinetics in rats, such as rapid absorption, moderate clearance, and rapid distribution to multiple tissues. Those properties provide important information for further development W-1 as an anti-HIV-1 drug candidate.

The Facile Fabrication of Hollow Cu2O Nanoparticles Induced by the Kirkendall Effect on Cu@Ag Core-Shell Nanoparticles

Ying Lu,강현숙,Young S. Lim,이병철,김상호,Longhai Piao 대한화학회 2015 Bulletin of the Korean Chemical Society Vol.36 No.8