Southeast University

About: Southeast University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: MIMO & Control theory. The organization has 66363 authors who have published 79434 publications receiving 1170576 citations. The organization is also known as: SEU.

Analysis and Optimization of Back EMF Waveform of a Flux-Switching Permanent Magnet Motor

Abstract: Flux-switching permanent magnet (FSPM) motors have a doubly salient structure, the magnets being housed in the stator and the stator winding comprising concentrated coils. They have attracted considerable interest due to their essentially sinusoidal phase back electromotive force (EMF) waveform. However, to date, the inherent nature of this desirable feature has not been investigated in detail. Thus, a typical three-phase FSPM motor with 12 stator teeth and ten rotor poles is considered. It is found that, since there is a significant difference in the magnetic flux paths associated with the coils of each phase, this results in harmonics in the coil back EMF waveforms being cancelled, resulting in essentially sinusoidal phase back EMF waveforms. In addition, the influence of the rotor pole-arc on the phase back EMF waveform is evaluated by finite-element analysis, and an optimal pole-arc for minimum harmonic content in the back EMF is obtained and verified experimentally.

Upregulated lncRNA-UCA1 contributes to progression of hepatocellular carcinoma through inhibition of miR-216b and activation of FGFR1/ERK signaling pathway

Abstract: // Feng Wang 1, * , Hou-Qun Ying 2, * , Bang-Shun He 1 , Yu-Qin Pan 1 , Qi-Wen Deng 1 , Hui-Ling Sun 3 , Jie Chen 3 , Xian Liu 1 , Shu-Kui Wang 1 1 Central Laboratory, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China 2 Medical college, Southeast University, Nanjing, Jiangsu, China 3 Department of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu, China * These authors have contributed equally to this work Correspondence to: Shu-Kui Wang, e-mail: shukwangnj@163.com Keywords: hepatocellular carcinoma, lncRNA, UCA1, miR-216b, FGFR1 Received: November 17, 2014 Accepted: January 26, 2015 Published: February 11, 2015 ABSTRACT The long non-coding RNA (lncRNA) urothelial carcinoma-associated 1 (UCA1) has been recently shown to be dysregulated, which plays an important role in the progression of several cancers. However, the biological role and clinical significance of UCA1 in the carcinogenesis of hepatocellular carcinoma (HCC) remain unclear. Herein, we found that UCA1 was aberrantly upregulated in HCC tissues and associated with TNM stage, metastasis and postoperative survival. UCA1 depletion inhibited the growth and metastasis of HCC cell lines in vitro and in vivo . Furthermore, UCA1 could act as an endogenous sponge by directly binding to miR-216b and downregulation miR-216b expression. In addition, UCA1 could reverse the inhibitory effect of miR-216b on the growth and metastasis of HCC cells, which might be involved in the derepression of fibroblast growth factor receptor 1 (FGFR1) expression, a target gene of miR-216b, and the activation of ERK signaling pathway. Taken together, our data highlights the pivotal role of UCA1 in the tumorigenesis of HCC. Moreover, the present study elucidates a novel lncRNA-miRNA-mRNA regulatory network that is UCA1-miR-216b-FGFR1-ERK signaling pathway in HCC, which may help to lead a better understanding the pathogenesis of HCC and probe the feasibility of lncRNA-directed diagnosis and therapy for this deadly disease.

Lower mortality of COVID-19 by early recognition and intervention: experience from Jiangsu Province

Abstract: © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/. A cluster of patients of novel coronavirus pneumonia (NCP) have been identified in Wuhan in December 2019 and soon this virus spread at a tremendous rate which swept through the whole China and more than 93 countries and regions around the world [1, 2]. This emerging, rapidly evolving situation has threatened the health of all mankind and WHO has raised COVID-19 risk to “very high” at global level. Up to now, 80,859 cases were confirmed, among which 10–15% patients were critically ill and 3100 (3.83%) died in China. The large number of transmission population between Jiangsu and Hubei provinces led to the infinite burden in controlling the COVID-19 epidemic in Jiangsu Province [3, 4]. By 24:00 on March 7, a total of 631 confirmed cases of NCP were reported with a portion of critically ill patients whose ages ranged from 9 months to 96 years old. A total of 610 cases have been discharged from hospital, and the cure rate of confirmed cases in our province has reached 96.67%, which is far exceeding that of national data [5–8]. Since the outcome of NCP patients in Jiangsu was much better than that in Hubei where the mortality of NCP patients was nearly 4.34%, we retrospectively summarized our therapeutic process and figured out that critical care-dominated treatment patterns might be the core in reducing mortality.

Adaptive Neural Network Control of a Marine Vessel With Constraints Using the Asymmetric Barrier Lyapunov Function

Abstract: In this paper, we consider the trajectory tracking of a marine surface vessel in the presence of output constraints and uncertainties. An asymmetric barrier Lyapunov function is employed to cope with the output constraints. To handle the system uncertainties, we apply adaptive neural networks to approximate the unknown model parameters of a vessel. Both full state feedback control and output feedback control are proposed in this paper. The state feedback control law is designed by using the Moore–Penrose pseudoinverse in case that all states are known, and the output feedback control is designed using a high-gain observer. Under the proposed method the controller is able to achieve the constrained output. Meanwhile, the signals of the closed loop system are semiglobally uniformly bounded. Finally, numerical simulations are carried out to verify the feasibility of the proposed controller.