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Jun Duan,Feng Deng,Wan-Shan Li,Xue-Lei Li,Lei-Lei Zheng,Gui-Yuan Li,Yan-Jie Bai 대한치과교정학회 2015 대한치과교정학회지 Vol.45 No.4
Objective: To compare the positions of the mandibular premolars in Angle Class I subjects according to vertical facial type. The results will provide a theoretical basis for predicting effective tooth movement in orthodontic treatment. Methods: Cephalometric parameters were determined using cone-beam computed tomography in 120 Angle Class I subjects. Subjects were categorized as short, normal, and long face types according to the Frankfort mandibular angle. Parameters indicating the position of the mandibular right premolars and the mandible were also measured. Results: The angle between the mandibular first premolar axis and buccal cortex, the distance between the root apex and buccal cortex, angle of vestibularization, arc of vestibularization, and root apex maximum movable distance were significantly greater in the short face type than in the long and norm face types. The angle between the mandibular second premolar axis and buccal cortex, the distance from root apex to buccal cortex, and the arc of vestibularization were significantly greater in the short face type than in the normal face type. Conclusions: There are significant differences in the mandibular premolar positions in Class I subjects according to vertical facial type.
Bolt looseness detection and localization using time reversal signal and neural network techniques
Zhifeng Tang,Yuan-Feng Duan,Xiaodong Sui,Chung Bang Yun 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.30 No.4
It is essential to monitor the working conditions of bolt-connected joints, which are widely used in various kinds of steel structures. The looseness of bolts may directly affect the stability and safety of the entire structure. In this study, a guided wave-based method for bolt looseness detection and localization is presented for a joint structure with multiple bolts. SH waves generated and received by a small number (two pairs) of magnetostrictive transducers were used. The bolt looseness index was proposed based on the changes in the reconstructed responses excited by the time reversal signals of the measured unit impulse responses. The damage locations and local damage severities were estimated using the damage indices from several wave propagation paths. The back propagation neural network (BPNN) technique was employed to identify the local damages. Numerical and experimental studies were conducted on a lap joint with eight bolts. The results show that the total damage severity can be successfully detected under the effect of external force and measurement noise. The local damage severity can be estimated reasonably for the experimental data using the BPNN constructed by the training patterns generated from the finite element simulations.
Yan-Qing Duan,Song-Tao He,Qing-Qing Li,Ming-Feng Wang,Wen-Yuan Wang,Wei Zhe,Yong-Hong Cao,Ming-He Mo,Yu-Long Zhai,Wen-Jun Li 한국미생물학회 2013 The journal of microbiology Vol.51 No.3
A Gram-positive, catalase- and oxidase-positive, strictly aerobic, endospore-forming rod bacterium, designated K3514T, was isolated from the leaves of Nicotiana tabacum. The strain was able to grow at temperatures of 8–40°C, pH 5.0–10.0 and NaCl concentrations of 0–7%. The predominant quinones (>30%) of this strain were MK-7(H2) and MK-7. Phylogenetic analysis of 16S rRNA gene sequence showed that strain K3514T was affiliated to the genus Lysinibacillus, with its closest relatives being Lysinibacillus mangiferihumi (98.3% sequence similarity), Lysinibacillus sphaericus (97.9% sequence similarity), Lysinibacillus fusiformis (97.4% sequence similarity), and Lysinibacillus xylanilyticus (97.3% sequence similarity). However, low levels of DNA-DNA relatedness values suggested that the isolate was distinct from the other closest Lysinibacillus species. Additionally, based on analysis of morphological, physiological, and biochemical characteristics, the isolate could be differentiated from the closest known relatives. Therefore, based on polyphasic taxonomic data, the novel isolate likely represents a novel species, for which the name Lysinibacillus tabacifolii sp. nov. and the type strain K3514T (=KCTC 33042T =CCTCC AB 2012050T) are proposed.
Gang Wang,Peng-yu Duan,Yuan Ma,Xi-na Li,Feng-zhi Qu,Liang Ji,Xiao-yu Guo,Wang-jun Zhang,Fan Xiao,Le Li,Ji-sheng Hu,Bei Sun 생화학분자생물학회 2019 Experimental and molecular medicine Vol.51 No.-
Currently, preliminary results have confirmed the existence of receptor-interacting protein kinase 3 (RIPK3) and mixed lineage kinase domain-like protein (MLKL)-dependent necroptosis of pancreatic acinar cells during early acute pancreatitis (AP), which might be a potential target for the effective regulation of necroinflammatory injury. However, the exact effect of receptor-interacting protein kinase 1 (RIPK1)-dependent regulated acinar cell necrosis on AP is still uncertain. In our study, we first explored the changes in the degree of local and systemic inflammation in AP rats when the activation of acinar cell RIPK1 was inhibited. The RIPK1 inhibitor Nec-1 was used to treat rats, and the levels of related inflammatory markers, necrosis indicators and apoptotic indicators were measured. Changes in pancreatic nuclear factor κB (NF-κB) and aquaporin 8 (AQP8) expression were noted. Next, the expression of AQP8 in AR42J cells was inhibited, and the degree of cell necrosis and inflammatory damage was found to be significantly reduced. Most importantly, we demonstrated that the RIPK1/NF-ĸB/AQP8 axis might be a potential regulatory pathway mediating RIPK1-dependent regulated acinar cell necrosis in early AP. Finally, we used the NF-κB inhibitor PDTC and Nec-1 to treat rats in different groups and measured the degree of pathological pancreatic injury, the activation of RIPK1, and the expression of NF-κB and AQP8. In summary, we hypothesized that there might be a RIPK1/NF-ĸB/AQP8 pathway controlling RIPK1-dependent regulated necrosis of acinar cells in AP, which might be a promising therapeutic target against AP-related injury.
Wang, Zebin,Wang, Feng,Duan, Rui,Liu, Jin-Yuan Korean Society for Biochemistry and Molecular Biol 2007 Journal of biochemistry and molecular biology Vol.40 No.3
Phospholipid hydroperoxide glutathione peroxidase (PHGPx) is an unique antioxidant enzyme that directly reduces lipid hydroperoxides in biomembranes. In the present work, the entire encoding region for Oryza sativa PHGPx was expressed in Escherichia coli M15, and the purified fusion protein showed a single band with 21.0 kD and pI = 8.5 on SDS- and IFE-PAGE, respectively. Judging from CD and fluorescence spectroscopy, this protein is considered to have a well-ordered structure with 12.2% $\alpha$-helix, 30.7%$\beta$-sheet, 18.5% $\delta$-turn, and 38.5% random coil. The optimum pH and temperature of the enzyme activity were pH 9.3 and 27$^{\circ}C$. The enzyme exhibited the highest affinity and catalytical efficiency to phospholipid hydroperoxide employing GSH or Trx as electron donor. Moreover, the protein displayed higher GSH-dependent activity towards t-Butyl-OOH and $H_2O_2$. These results show that OsPHGPx is an enzyme with broad specificity for hydroperoxide substrates and yielded significant insight into the physicochemical properties and the dynamics of OsPHGPx.
Ultrasonic guided waves-based fatigue crack detection in a steel I-beam: an experimental study
Jiaqi Tu,Xian Xu,Chung Bang Yun,Yuan-Feng Duan 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.31 No.1
Fatigue crack is a fatal problem for steel structures. Early detection and maintenance can help extend the service life and prevent hazards. This paper presents the ultrasonic guided waves-based (UGWs-based) fatigue crack detection of a steel Ibeam. The semi-analytical finite element model has been built to obtain the wave propagation characteristics. Damage indices in both time and frequency domains were analyzed by considering the characteristic variations of UGWs including the amplitude, phase angle, and wave packet energy. The pulse-echo and pitch-catch methods were combined in the detection scheme. Labscale experiments were conducted on welded steel I-beams to verify the proposed method. Results show that the damage indices based on the characteristic variations in the time domain can identify and localize the fatigue crack before it enters the rapid growth stage. The damage severity can be reasonably evaluated by analyzing the time-domain damage indices. Two nonlinear damage indices in the frequency domain give earlier warnings of the fatigue crack than the time-domain damage indices do. The identification results based on the above two nonlinear indices are found to be less consistent under various excitation frequencies. More robust nonlinear techniques needed to be searched and tested for early crack detection in steel I-beams in further study.
Wang, Zhi-Jun,Wang, Mao-Qiang,Duan, Feng,Song, Peng,Liu, Feng-Yong,Wang, Yan,Yan, Jie-Yu,Li, Kai,Yuan, Kai Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.3
Objective: This work aimed to evaluate the safety and clinical efficacy of transcatheter arterial chemoembolization (TACE) combined with c-arm cone-beam CT guided synchronous radiofrequency ablation (RFA) in treatment of large hepatocellular carcinoma (HCC). Methods: 21 patients with large HCC were studied from January 2010 to March 2012. TACE combined with synchronous C-arm cone-beam CT guided RFA were performed on a total of 25 lesions. Conventional imaging examination (CEUS, enhanced CT or MRI) and AFP detection were regularly conducted to evaluate the technical success rate of combined treatment, complications, treatment response, time without disease recurrence and survival rate. Results: The technical success rate of combined treatment was 100%, without any significant complication. After 1 month, there were 19 cases with complete response and 2 cases with partial response, with an complete response rate of 90.4% (19/21) and a clinical effective rate of 100% (21/21). The complete response rates of single nodular lesions (100%, 17/17) was significantly higher than that of multiple nodular lesions (50%, 2/4) (P<0. 05). During 2 to 28 months of follow-up, in 19 cases with complete response, the average time without disease recurrence was $10.8{\pm}6$ months. The total survival rates of 6, 12 and 18 months in 21 patients were 100%, respectively. Conclusion: TACE combined with synchronous C-arm CT guided RFA is safe and effective for treatment of large HCC. The treatment efficacy for single nodular lesion is better than that for multiple nodular lesions.
Jiangpeng Shu,Gaoyang Liu,Yanbo Niu,Weijian Zhao,Yuan-Feng Duan 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.29 No.1
The deployment of advanced structural health monitoring (SHM) systems in large-scale civil structures collects large amounts of data. Note that these data may contain multiple types of anomalies (e.g., missing, minor, outlier, etc.) caused by harsh environment, sensor faults, transfer omission and other factors. These anomalies seriously affect the evaluation of structural performance. Therefore, the effective analysis and mining of SHM data is an extremely important task. Inspired by the deep learning paradigm, this study develops a novel generative adversarial network (GAN) and convolutional neural network (CNN)-based data anomaly detection approach for SHM. The framework of the proposed approach includes three modules : (a) A three-channel input is established based on fast Fourier transform (FFT) and Gramian angular field (GAF) method; (b) A GANomaly is introduced and trained to extract features from normal samples alone for class-imbalanced problems; (c) Based on the output of GANomaly, a CNN is employed to distinguish the types of anomalies. In addition, a dataset-oriented method (i.e., multistage sampling) is adopted to obtain the optimal sampling ratios between all different samples. The proposed approach is tested with acceleration data from an SHM system of a long-span bridge. The results show that the proposed approach has a higher accuracy in detecting the multi-pattern anomalies of SHM data.