Description of a new earthworm species of the genus Drawida (Oligochaeta: Moniligastridae) from Northeast China and Far East Russia

Yufeng Zhang,Dmitry Atopkin,Linfei Wang,Donghui Wu 국립중앙과학관 2021 Journal of Asia-Pacific Biodiversity Vol.14 No.3

A new species of Drawida Michaelsen 1900, named Drawida ganini Zhang and Wu sp nov., is describedfrom the material collected in the Muling River of Heilongjiang Province, Northeast China, and theadjacent region near Russia. The new species is morphologically similar to Drawida ghilarovi Gates 1969. The molecular data were more useful for comparison of D. ghilarovi samples. D. ganini is geneticallydifferent from D. ghilarovi by a p-distance value of 18.35 1.37% based on the COI gene sequence data. Thus, Ganin and Atopkin’s (2018) data validate taxonomical status of D. ganini as separated species.

Selective surface functionalization at regions of high local curvature in graphene

Wu, Qingzhi,Wu, Yaping,Hao, Yufeng,Geng, Jianxin,Charlton, Matthew,Chen, Shanshan,Ren, Yujie,Ji, Hengxing,Li, Huifeng,Boukhvalov, Danil W.,Piner, Richard D.,Bielawski, Christopher W.,Ruoff, Rodney S. The Royal Society of Chemistry 2013 Chemical communications Vol.49 No.7

<P>Monolayer graphene was deposited on a Si wafer substrate decorated with SiO<SUB>2</SUB> nanoparticles (NPs) and then exposed to aryl radicals that were generated <I>in situ</I> from their diazonium precursors. Using micro-Raman mapping, the aryl radicals were found to selectively react with the regions of graphene that covered the NPs. The enhanced chemical reactivity was attributed to the increased strain energy induced by the local mechanical deformation of the graphene.</P> <P>Graphic Abstract</P><P>Due to the increased strain energy caused by local mechanical deformation, aryl radicals were found to selectively react with regions of graphene that were curved by underlying SiO<SUB>2</SUB> nanoparticles. <IMG SRC='http://pubs.rsc.org/services/images/RSCpubs.ePlatform.Service.FreeContent.ImageService.svc/ImageService/image/GA?id=c2cc36747e'> </P>

Downstream Neighbor of Son Overexpression is Associated With Breast Cancer Progression and a Poor Prognosis

Yufeng Qi,Haodong Wu,Conghui Liu,Danni Zheng,Congzhi Yan,Wenjing Hu,Xiaohua Zhang,Xuanxuan Dai 한국유방암학회 2022 Journal of breast cancer Vol.25 No.4

Purpose: The incidence rate of breast cancer (BC) has increased annually. Downstream neighbor of son (DONSON) critically affects cell cycle progression and maintains stable genomic properties; however, its relevant effects on BC growth and progression require in-depth investigation. Methods: DONSON upregulation was validated in public databases. DONSON expression in matched BC and adjacent tissues and cell lines (MDA-MB-231, BT-549, and HS-578T) was determined using quantitative reverse transcription polymerase chain reaction. In vitro apoptosis, invasion, migration, and proliferation tests were performed to ascertain the functions of DONSON in BC cell lines. Then, using western blot analysis, the levels of DONSON downstream proteins were determined. Results: Compared to the control, DONSON was expressed at higher levels in BC tissues and cell lines. DONSON knockdown facilitated apoptosis and limited proliferation, migration, invasion, and S/G2 transition of BC cells in vitro. Furthermore, DONSON overexpression promoted BC cell proliferation and inhibited apoptosis in vitro. Moreover, DONSON knockdown reduced cyclin A1 and cyclin-dependent kinase 2 levels. Moreover, DONSON knockdown limited the progression of epithelial-mesenchymal transition. Conclusion: DONSON critically affects BC growth and serves as a possible target and marker for the efficacy of subsequent therapies.

Security Authentication Method of Terminal Trusted Access in Smart Grid

Yufeng Wang,Lie Wu,Yun Yang 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.7

A security authentication method in smart grid terminal is proposed in this paper. This method layers the terminal authentication system structure of smart grid so as to improve the simplicity and extensibility on system deployment and realize flexible communication mechanism and the interaction mechanism among systems. This paper aims at preventing terminal information from being destroyed and achieving terminal verification integrity. Besides, this kind of authentication method has no special requirements for terminal users.

The Fabrication of High-Aspect-Ratio Cylindrical Nano Tool using ECM

Yufeng Wang,Ningsong Qu,Yongbin Zeng,Xiujuan Wu,Di Zhu 한국정밀공학회 2013 International Journal of Precision Engineering and Vol. No.

With the miniaturization of various types of components and devices, micro- and nanometer-scale tools are increasingly in demand. Electrochemical machining (ECM) is a well-established technique for the fabrication of micro tools and nano tips. This paper presents a machining method for the fabrication of a high-aspect-ratio cylindrical nano tool using liquid membrane ECM, in which a straight reciprocating motion is applied to the anodic electrode. The method is based on periodic machining of the anodic rod within the amplitude of the straight reciprocating motion. In this process, the machining rate within amplitude varies periodically, allowing nano tools with high aspect ratios to be obtained by the presented method. Experiments were conducted to verify the proposed method. The influences of applied voltage, electrolyte concentration, amplitude and velocity of the straight reciprocating motion on the fabrication of cylindrical nano-electrode were investigated. By using this method, nano-electrodes with average diameters of several hundred nanometers and aspect ratios up to 70 were successfully fabricated.

Fuzzy Approximation-Based Backstepping Control of Permanent Magnet Synchronous Motor

Zhang Yufeng,Yan Qi,Huang Nan,Wu Zihui,Gong Hao,Du Guanghui 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.3

A permanent magnet synchronous motor(PMSM) control system based on backstepping control can effectively improve the dynamic performance, and the design process is simple and easy to be implemented in engineering. However, factors such as changes in motor parameters due to environmental changes, wear and aging, and external load disturbances can adversely affect the control system, resulting in degraded control performance. To address this problem, this paper proposes a fuzzy approximation-based backstepping control method for PMSM. The method constructs a mathematical model containing the perturbation term of the PMSM body parameters and the load disturbance term. And the universal approximation property of the fuzzy logic system is used to approximate the disturbance terms in the model, based on which a backstepping controller satisfying the stability requirements is designed. Finally, the simulation and experiment are given, which compare with the traditional backstepping method. The results show that the proposed method can effectively suppress the adverse effects of motor parameter changes and load disturbances on the motor control system.

Limit analysis of 3D rock slope stability with non-linear failure criterion

Gao, Yufeng,Wu, Di,Zhang, Fei,Lei, G.H.,Qin, Hongyu,Qiu, Yue Techno-Press 2016 Geomechanics & engineering Vol.10 No.1

The non-linear Hoek-Brown failure criterion has been widely accepted and applied to evaluate the stability of rock slopes under plane-strain conditions. This paper presents a kinematic approach of limit analysis to assessing the static and seismic stability of three-dimensional (3D) rock slopes using the generalized Hoek-Brown failure criterion. A tangential technique is employed to obtain the equivalent Mohr-Coulomb strength parameters of rock material from the generalized Hoek-Brown criterion. The least upper bounds to the stability number are obtained in an optimization procedure and presented in the form of graphs and tables for a wide range of parameters. The calculated results demonstrate the influences of 3D geometrical constraint, non-linear strength parameters and seismic acceleration on the stability number and equivalent strength parameters. The presented upper-bound solutions can be used for preliminary assessment on the 3D rock slope stability in design and assessing other solutions from the developing methods in the stability analysis of 3D rock slopes.

OTRCaptcha : A Novel Object and Text Recognition Based Image CAPTCHA

Zhen Ye,Yufeng Wu,Wenyao Zhu,Mingjun Wang 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.12

CAPTCHA is an important technology to prevent auto-script attack. Currently most of the CAPTCHA systems are text based, which firstly distort, rotate different characters and then use some obfuscation, aiming to make the text difficult to be recognized by auto-script while still can be learnt easily by real users. However, such kind of CAPTCHA schema either too simple, which can be attacked easily by using optimal character recognition (OCR) or machine learning based technology, or it is too complex that even real users cannot tell it. By observing such contradiction between security and usability, we propose a novel object and text recognition based image CAPTCHA system called OTRCaptcha. In OTRCaptcha, some object images (each has a label) and their names are attached into a background image respectively. In order to pass this CAPTCHA, users have to identify all the object images, labels within those objects and their names. Besides, users also need to identify the semantic relationship between object and its name. Both the theoretical analysis and experiment result show that OTRCapthcha can provide both high security and strong usability.

Artificial Intelligence in the Prediction of Gastrointestinal Stromal Tumors on Endoscopic Ultrasonography Images: Development, Validation and Comparison with Endosonographers

Lu Yi,Wu Jiachuan,Hu Minhui,Zhong Qinghua,Er Limian,Shi Huihui,Cheng Weihui,Chen Ke,Liu Yuan,Qiu Bingfeng,Xu Qiancheng,Lai Guangshun,Wang Yufeng,Luo Yuxuan,Mu Jinbao,Zhang Wenjie,Zhi Min,Sun Jiachen 거트앤리버 소화기연관학회협의회 2023 Gut and Liver Vol.17 No.6

Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers. The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions: We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.

Principal weighted support vector machines for sufficient dimension reduction in binary classification

Shin, Seung Jun,Wu, Yichao,Zhang, Hao Helen,Liu, Yufeng Oxford University Press 2017 Biometrika Vol.104 No.1

<P><B>SUMMARY</B></P><P>Sufficient dimension reduction is popular for reducing data dimensionality without stringent model assumptions. However, most existing methods may work poorly for binary classification. For example, sliced inverse regression (Li, 1991) can estimate at most one direction if the response is binary. In this paper we propose principal weighted support vector machines, a unified framework for linear and nonlinear sufficient dimension reduction in binary classification. Its asymptotic properties are studied, and an efficient computing algorithm is proposed. Numerical examples demonstrate its performance in binary classification.</P>