An Iterative Calculation Method for Internal Forces and Deformation of Curved Tunnel Lining

Lu-yuan Wu,Meng Li,Hai-bo Bai,Yong-feng Yun,Hui Li,Yi Feng 대한토목학회 2024 KSCE Journal of Civil Engineering Vol.28 No.4

The accurate prediction of lining forces and deformations is crucial for the design of arched tunnel lining. However, in traditional tunnel structural mechanics methods, the distribution shape of the surrounding rock elastic resistance (SRER), as well as the zero point and maximal point locations of SRER, are not clearly defined. In this paper, an iterative calculation method is proposed based on the gradual convergence of the unitized values of SRER and total displacement (TD) of the lining, and the one-to-one functional relationship between the two in the stability process of the surrounding rock and lining. In this method involves using the initial displacement caused by the pressure of the surrounding rock pressure is used to initiate the iterative process, and iterative calculation is carried out until the errors between the unitized value of SRER and the unitized value of TD of the lining structure meet the error requirements. This enables precise determination of the SRER and TD. In order to verify the effectiveness of the proposed method, a case study is conducted on the tunnel of Lianghe Expressway tunnel in Yunnan province, China . The results showed that when the semi-lining structure is divided into unit blocks and the average error of consistency is required to be less than 1e-3, it takes about 20 iterations are needed to meet the error requirement. Furthermore, the accuracy of the calculated results is verified through site-measuring experiments. This method provides an effective tool for failure analysis of arched tunnel lining structures.

Separation of Nattokinase from Bacillus subtilis Fermentation Broth by Expanded Bed Adsorption with Mixed-mode Adsorbent

Lu Miao-Hua,Lin Dong-Qiang,Wu Yuan-Chun,Yun Jun-Xian,Mei Le-He,Yao Shan-Jing The Korean Society for Biotechnology and Bioengine 2005 Biotechnology and Bioprocess Engineering Vol.10 No.2

Mixed-mode hydrophobic/ionic matrices exhibit a salt-tolerant property for adsorbing target protein from high-ionic strength feedstock, which allows the application of undiluted feedstock via an expanded bed process. In the present work, a new type of mixed-mode adsorbent designed for expanded bed adsorption, Fastline $PRO^{\circledR}$, was challenged for the capture of nattokinase from the high ionic fermentation broth of Bacillus subtilis. Two important factors, pH and ion concentration, were investigated with regard to the performance of nattokinase ad-sorption. Under initial fermentation broth conditions (pH 6.6 and conductivity of 10 mS/cm) the adsorption capacity of nattokinase with Fastline PRO was high, with a maximum capacity of 5,350 U/mL adsorbent. The elution behaviors were investigated using packed bed adsorption experiments, which demonstrated that the effective desorption of nattokinase could be achieved by effecting a pH of 9.5. The biomass pulse response experiments were carried out in order to evaluate the biomass/adsorbent interactions between Bacillus subtilis cells and Fastline PRO, and to demonstrate a stable expanded bed in the feedstock containing Bacillus subtilis cells. Finally, an EBA process, utilizing mixed-mode Fastline PRO adsorbent, was optimized to capture nattokinase directly from the fermentation broth. The purification factor reached 12.3, thereby demonstrating the advantages of the mixed-mode EBA in enzyme separation.

Novel Two-dimensional Network Based on Amino-acid-octamolybdate Bridged by Second Metals: {M(H₂O)₃(pro)Mo₄O₁₃}₂·2H₂O (pro = proline, M = Co, Ni, Cu, Zn)

Wu, Xiao-Yuan,Lu, Can-Zhong,Xia, Chang-Kun,Chen, Shu-Mei,Liu, Jiu-Hui,Chen, Li-Juan,Yang, Wen-Bin Korean Chemical Society 2006 Bulletin of the Korean Chemical Society Vol.27 No.8

Four isostructural amino-acid-based polyoxomolybdates, {$M(H_2O)_3(pro)Mo_4O_{13}$}$_2{\cdot}2H_2O$ (pro = proline, M = Co (1), Ni (2), Cu (3), Zn (4)), have been synthesized and structurally characterized by single crystal X-ray diffraction, elemental analysis, IR spectrum, TG analysis. The structures of 1-4 are layered networks built up from {$Mo_8O_{26}(pro)_2$}$^{4-}$ units and {$M(H_2O)_3O_3$} octahedra, the uncoordinated water molecules occupying the interlayer regions.

Astrocytic 5-HT1A receptor mediates age-dependent hippocampal LTD and fear memory extinction in male mice

Wu Qian-Yun,Lin Lian-Hong,Lu Kun,Deng Si-Fu,Li Wei-Min,Xu Yuan,Zhang-Bin Tan,Liu Ji-Hong 생화학분자생물학회 2024 Experimental and molecular medicine Vol.56 No.-

NMDA receptor-dependent long-term depression (LTD) in the hippocampus is a well-known form of synaptic plasticity that has been linked to different cognitive functions. Although the underlying mechanisms remain unclear, this form of LTD cannot be induced by low-frequency stimulation (LFS) in adult mice. In this study, we found that LFS-induced LTD was not easily induced in adult animals and was age dependent. Interestingly, the level of the 5-HT1A receptor was correspondingly increased and exhibited an inverse correlation with the magnitude of LFS-LTD during development. Knockout or pharmacological inhibition of the 5-HT1A receptor reversed impaired LFS-LTD in adult mice (P60), while activation or inhibition of this receptor disturbed or enhanced LFS-LTD in adolescent mice (P21), respectively. Furthermore, the astrocytic 5-HT1A receptor in the hippocampus predominantly mediated age-dependent LFS-LTD through enhancing GABAergic neurotransmission. Finally, fear memory extinction differed among the above conditions. These observations enrich our knowledge of LTD at the cellular level and suggest a therapeutic approach for LTD-related psychiatric disorders.

Semi-supervised Multi-view Manifold Discriminant Intact Space Learning

( Lu Han ),( Fei Wu ),( Xiao-yuan Jing ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.9

Semi-supervised multi-view latent space learning is gaining considerable popularity recently in many machine learning applications due to the high cost and difficulty to obtain the large amount of label information of data. Although some semi-supervised multi-view latent space learning methods have been presented, there is still much space for improvement: 1) How to learn latent discriminant intact feature representations by employing data of multiple views; 2) How to exploit the manifold structure of both labeled and unlabeled point in the learned latent intact space effectively. To address the above issues, we propose an approach called semi-supervised multi-view manifold discriminant intact space learning (SM2DIS) for image classification in this paper. SM2DIS aims to seek a manifold discriminant intact space for data of different views by making use of both the discriminant information of labeled data and the manifold structure of both labeled and unlabeled data. Experimental results on MNIST, COIL-20, Multi-PIE, and Caltech-101 databases demonstrate the effectiveness and robustness of our proposed approach.

Trajectory Planning for Energy Minimization of Industry Robotic Manipulators Using the Lagrange Interpolation Method

Lu-Ping Luo,Hanyang Universit,Rui-Jun Yan,Quan Yuan,Jing Wu,신규식,한창수 한국정밀공학회 2015 International Journal of Precision Engineering and Vol. No.

We propose to use Lagrange interpolation method to express each joint trajectory function to realize trajectory planning for energy minimization of industrial robotic manipulators. We give the position constraints to the industrial robotic manipulators and the stability of the industrial robotic manipulators should be satisfied. In order to avoid Runge’s phenomenon of Lagrange interpolation method, we use the Chebyshev interpolation points for our approach. Through derivation, the angular velocity functions and angular acceleration functions can be obtained. Lagrange interpolation method can satisfy position constraints, and ensure the smoothness of joint angular positions, velocities, accelerations, and joint torques. By taking these functions into the Performance Index (PI) of energy minimization, as well as the direct iteration method used for optimization of energy consumption, we can obtain the optimal trajectory for industrial robotic manipulators.

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.

Research on the Factors Influencing the Reading Volume of WeChat Official Account at Chinese Universities

Lu-Hao Cao,Xi-Yuan Wu K기업경영연구원 2023 KBM Journal(K Business Management Journal) Vol.7 No.2

By the end of 2022, the number of WeChat 5.0 users has reached more than 1000 million, 800 million of whom stay active, and WeChat public platform also had acquired 2 million public accounts. Among the numerous WeChat official accounts, the official accounts of colleges and universities have always been the focus of media attention. With the development of We Media, the presentation mode of WeChat official account has changed from simple information transmission mode to various other modes, and the information presentation mode has become more diversified. By studying the characteristics of content on university WeChat official accounts and reference items for audience reactions such as likes, this study aims to explore the relationship between audience reactions on WeChat official accounts, effectively understand the factors influencing the reading volume of university WeChat official accounts, and explore the communication strategies of WeChat public accounts. This paper uses the content analysis method to rank the number of weekly push articles read by Qingbo's big data on college WeChat public accounts from 2016 to 2017. These ranked articles are selected as samples, and random sampling is conducted from these samples. A total of 1200 valid samples will be analyzed to draw conclusions: The higher the popularity, the more likes and reading volume; The correlation between the originality of the posted article and the reading volume is not strong. I hope this paper can provide some reference meaning for the development of the Wechat official accounts.

Study on Polysaccharide Bonded Abrasive Tool Using Hydrothermal Gelatinisation for Green Machining of Single Crystal Sapphire

Zhe Wu,Yuying Zhang,Yong Liu,Fangli Mo,Chengwu Wang,Huizong Lu,Julong Yuan,Zhifeng Liu 한국정밀공학회 2024 International Journal of Precision Engineering and Vol.25 No.1

Aiming to green machining of single crystal sapphire, polysaccharide-bonded soft abrasive tool using hydrothermal gelatinisation method was proposed. Mechanical properties of prepared polysaccharide films show that when the weight ratio of natural polysaccharide to cross-linked polysaccharide is 1:1, the tensile strength and extension rate of the film are relatively optimal. Composition and making process of polysaccharide bonded abrasive tool was built. Samples of polysaccharide bonded soft abrasive tools were made by which the single crystal sapphire substrates were machined. It is found that by adopting guar gum as dispersion agent and hydrothermal gelatinisation, the abrasive sedimentation during making process of abrasive tool is substantially eliminated, and better abrasive holding ability is attained. XPS and Raman microscope analysis showed that material of single crystal sapphire was removed by mechano-chemical reaction with good surface integrity. Abrasive tools with abrasive to binder ratio of 4:1 presented relatively better self-sharpening and machining performance, and the material removal rate reached 0.427 μm/min. More interesting, XPS and FT-IR analyses both indicated that the polysaccharide binder dehydrated by the friction heat during machining process.

The Influence of Resilience on the Coping Strategies in Patients with Primary Brain Tumors

Shu-Yuan Liang,Hui-Chun Liu,Yu-Ying Lu,Shu-Fang Wu,Ching-Hui Chien,Shiow-Luan Tsay 한국간호과학회 2020 Asian Nursing Research Vol.14 No.1

Purpose: The purpose of this study was to assess the amount of variance in the coping strategies of patients with brain tumors that could be accounted for by resilience. Methods: This cross-sectional survey involved 95 patients who had experienced surgical, chemotherapy, or radiotherapy therapies for their brain tumors at least 1 month before data collection. The investigator collected data using the scales of the Ways of Coping Checklist-Revised and Resilience Scale. Data were analyzed using descriptive statistics, t tests, analysis of variance, Pearson product–moment correlation, and hierarchical multiple regression. Results: The results revealed that resilience was significantly positively associated with patients' problem-focused coping (r = .65, p < .001) and total coping (r = .49, p < .001). In addition, resilience accounted for 27% (R2inc = .27, p < .001) and 16% (R2inc = .16, p < .001) of the distinct variances in predicting patients’ problem-focused coping and total coping. Conclusion: The current results provide evidence to support the importance of resilience in shaping the coping strategies of relevant patients. As resilience shows a crucial element in patient coping with brain tumors, health team members should develop and employ appropriate strategies to improve the resilience of patients with brain tumors.