316 results on '"Huang, Lixia"'
Search Results
2. Effect of Sitting Baduanjin exercise on early rehabilitation of sepsis patients with non-invasive ventilation : a randomized controlled trial
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Chen, Ming-Gui, Wang, Fangfang, Huang, Lixia, Qi, Tingjie, Guo, Hanhua, Zeng, Rui-Xiang, Li, Xiaoyan, Chen, Haizhen, Zhang, Min-Zhou, Guo, Liheng, and Zhang, Xiaoxuan
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- 2024
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3. Prediction of apoptosis signal-regulating kinase 1 (ASK1) inhibition with machine learning methods
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Kuang, Zheng-Kun, Huang, Qing, Pan, Hui, Duan, Xiaoling, and Huang, Lixia
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- 2024
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4. Relationship between hemoglobin and lung cancer: evidence from Mendelian randomization and National Health and Nutrition Examination Survey
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Dong, Peixin, Li, Wenjie, Deng, Jiating, Huang, Lixia, Liu, Baomo, Wang, Shuaishuai, Xu, Xiongye, Su, Yan, Lin, Ziying, Li, Shaoli, Gu, Jincui, Qiu, Yanli, and Zhou, Yanbin
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- 2024
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5. EEG Emotion Recognition Based on Brain Network Constructed by Fuzzy Cognitive Map and Granger Causality Analysis
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YAN Chao, ZHANG Xueying, ZHANG Jing, CHEN Guijun, SUN Ying, and HUANG Lixia
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eeg emotion recognition ,granger causality analysis ,fuzzy cognitive map ,support vector machine ,Chemical engineering ,TP155-156 ,Materials of engineering and construction. Mechanics of materials ,TA401-492 ,Technology - Abstract
Purposes Aiming at the problem that Granger Causality (GC) analysis in EEG emotion recognition does not consider the interaction between nodes when constructing brain network, a method of constructing brain network by combining fuzzy cognitive map (FCM) and GC analysis is proposed. Methods First, on the basis of the correspondence between the structure of FCM and GC brain network, the GC brain network is modeled and improved by using the causal attributes among FCM nodes, and the FCM-GC brain network is constructed, by taking into account the cooperative interaction among nodes. Furthermore, in order to deeply integrate FCM with GC brain network, the spatial position information of EEG electrode channel is added to FCM training, and a new IFCM-GC brain network is constructed. On the basis of DEAP emotional EEG database, the features of IFCM-GC brain network are extracted, and the support vec tor machine is used as the recognition model. The average recognition rates in valence dimension and incentive dimension are 97.10% and 97.00%, respectively, which are more than 8% higher than the existing research on GC improvement. Findings The GC brain network constructed by this method takes into account the cooperative interaction among multiple nodes, and effectively improves the performance of emotion recognition system.
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- 2024
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6. Indoor Wi-Fi coverage measurement without spatial coordinates
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XIE Zefeng, CHEN Weidong, HUANG Lixia, GU Yifan, ZHANG Bojun, and QUAN Zhi
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coverage probability ,Wi-Fi network ,minimization of drive test ,clustering algorithm ,received signal strength indicator ,Information technology ,T58.5-58.64 ,Management information systems ,T58.6-58.62 - Abstract
In R16, 3GPP proposed that user devices could utilize the 4G/5G cellular networks to report the received signal strength indicator (RSSI) of Wi-Fi signal based on the existing minimization of drive test (MDT) technology, making it possible to measure the coverage probability of indoor Wi-Fi networks. However, existing measurement methods of network coverage probability based on the MDT require the spatial coordinates provided by the GPS. As GPS has poor indoor localization accuracy, it is not able to be applied to indoor Wi-Fi networks. A measurement method for network coverage probability based on clustering without spatial coordinates was proposed. The proposed method could distinguish RSSI measurement reported on different locations, with the fact that their statistics were similar at similar locations. The coverage probability was accurately measured by utilizing the clustering results without knowing the spatial coordinates. Experimental results show that the coverage probability measured by the proposed method is very close to the probability measured by the known spatial coordinates, and the accuracy is much higher than existing methods.
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- 2024
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7. Thrombomodulin as a potential diagnostic marker of acute myocardial infarction and correlation with immune infiltration: Comprehensive analysis based on multiple machine learning
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Liu, Guoqing, Huang, Lixia, Lv, Xiangwen, Guan, Yuting, and Li, Lang
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- 2024
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8. Knee osteoarthritis pendulum therapy: In vivo evaluation and a randomised, single-blind feasibility clinical trial
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Huang, Lixia, Xia, Zhidao, Wade, Derick, Liu, Jicai, Zhou, Guoyong, Yu, Chuanhua, Dawes, Helen, Esser, Patrick, Wei, Shijun, and Song, Jiuhong
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- 2024
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9. Stroke classification based on deep reinforcement learning over stroke screening imbalanced data
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Zuo, Ting, Li, Fenglian, Zhang, Xueying, Hu, Fengyun, Huang, Lixia, and Jia, Wenhui
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- 2024
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10. A network pharmacology approach to reveal the key ingredients in Scrophulariae Radix (SR) and their effects against Alzheimer's disease
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Shi, Yingying, Chen, Zhongqiang, Huang, Lixia, Gong, Yeli, and Shi, Lu
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- 2024
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11. Cholesterol mediated ferroptosis suppression reveals essential roles of Coenzyme Q and squalene
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Sun, Qi, Liu, Diming, Cui, Weiwei, Cheng, Huimin, Huang, Lixia, Zhang, Ruihao, Gu, Junlian, Liu, Shuo, Zhuang, Xiao, Lu, Yi, Chu, Bo, and Li, Jian
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- 2023
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12. Acoustic-articulatory emotion recognition using multiple features and parameter-optimized cascaded deep learning network
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Li, Juan, Zhang, Xueying, Li, Fenglian, Duan, Shufei, and Huang, Lixia
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- 2024
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13. W-Net: A boundary-enhanced segmentation network for stroke lesions
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Wu, Zelin, Zhang, Xueying, Li, Fenglian, Wang, Suzhe, Huang, Lixia, and Li, Jiaying
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- 2023
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14. Speech emotion recognition based on optimized deep features of dual-channel complementary spectrogram
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Li, Juan, Zhang, Xueying, Li, Fenglian, and Huang, Lixia
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- 2023
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15. Diagnosis of neurosyphilis in HIV-negative patients with syphilis: development, validation, and clinical utility of a suite of machine learning models
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Zou, Huachun, Lu, Zhen, Weng, Wenjia, Yang, Ligang, Yang, Luoyao, Leng, Xinying, Wang, Junfeng, Lin, Yi-Fan, Wu, Jiaxin, Fu, Leiwen, Zhang, Xiaohui, Li, Yuwei, Wang, Liuyuan, Wu, Xinsheng, Zhou, Xinyi, Tian, Tian, Huang, Lixia, Marra, Christina M., Yang, Bin, Yang, Tian-Ci, and Ke, Wujian
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- 2023
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16. N, N′-methylene bisacrylamide/divinyl benzene based-highly cross-linked hybrid monolithic column: Production and its applications for powerful capture of four chlorophenols
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Wang, Xuemei, Yuan, Na, Huang, Lixia, Huang, Pengfei, Du, Xinzhen, and Lu, Xiaoquan
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- 2023
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17. Facile fabrication of a novel SPME fiber based on silicone sealant/hollow ZnO@CeO2 composite with super-hydrophobicity for the enhanced capture of pesticides from water
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Wang, Xuemei, Huang, Lixia, Yuan, Na, Huang, Pengfei, Du, Xinzhen, and Lu, Xiaoquan
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- 2022
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18. Multi-scale long-range interactive and regional attention network for stroke lesion segmentation
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Wu, Zelin, Zhang, Xueying, Li, Fenglian, Wang, Suzhe, and Huang, Lixia
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- 2022
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19. Nanocomposite pastes of gelatin and cyclodextrin-grafted chitosan nanoparticles as potential postoperative tumor therapy
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Xiao, Lin, Xu, Weichang, Huang, Lixia, Liu, Jili, and Yang, Guang
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- 2023
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20. Emotion Recognition Based on a EEG–fNIRS Hybrid Brain Network in the Source Space.
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Hou, Mingxing, Zhang, Xueying, Chen, Guijun, Huang, Lixia, and Sun, Ying
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EMOTION recognition ,LARGE-scale brain networks ,NEAR infrared spectroscopy ,NETWORK performance ,ELECTROENCEPHALOGRAPHY - Abstract
Background/Objectives: Studies have shown that emotion recognition based on electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) multimodal physiological signals exhibits superior performance compared to that of unimodal approaches. Nonetheless, there remains a paucity of in-depth investigations analyzing the inherent relationship between EEG and fNIRS and constructing brain networks to improve the performance of emotion recognition. Methods: In this study, we introduce an innovative method to construct hybrid brain networks in the source space based on simultaneous EEG-fNIRS signals for emotion recognition. Specifically, we perform source localization on EEG signals to derive the EEG source signals. Subsequently, causal brain networks are established in the source space by analyzing the Granger causality between the EEG source signals, while coupled brain networks in the source space are formed by assessing the coupling strength between the EEG source signals and the fNIRS signals. The resultant causal brain networks and coupled brain networks are integrated to create hybrid brain networks in the source space, which serve as features for emotion recognition. Results: The effectiveness of our proposed method is validated on multiple emotion datasets. The experimental results indicate that the recognition performance of our approach significantly surpasses that of the baseline method. Conclusions: This work offers a novel perspective on the fusion of EEG and fNIRS signals in an emotion-evoked experimental paradigm and provides a feasible solution for enhancing emotion recognition performance. [ABSTRACT FROM AUTHOR]
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- 2024
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21. RETRACTED: Cost-based distributionally robust tourist attraction recommendation with demand uncertainty.
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Li, Zexin, Li, Qiulin, Li, Zepeng, Huang, Lixia, Pu, Song, and Luo, Zunhao
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RETRACTION of scholarly articles ,TOURIST attractions - Abstract
This article has been retracted. A retraction notice can be found at . [ABSTRACT FROM AUTHOR]
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- 2024
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22. Effect of fluoride varnish, glass ionomer and resin sealant on the prevention of pit and fissure caries in young children
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LIU lei, HUANG Lixia, DI Lisha, and SU Kui
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young children ,pit and fissure caries ,pit and fissure sealant ,fluorides ,duraphat ,glass ionomer pit and fissure sealant ,resin pit and fissure sealant ,incidence of caries ,retention rate ,Medicine - Abstract
Objective To study the effect of fluoride varnish, glass ionomer and resin sealant on the prevention of pit and fissure caries in young children, and to identify an a method to reduce the sensitivity of operation technique to prevent pit and fissure caries in young children with limited moisture isolation. Methods A self-control design was used to select 370 young children aged 3 to 5. Eight molars in the mouth were distributed in four quadrants, and each quadrant was randomly allocated to the blank group, fluoride varnish Duraphat group, glass ionomer GC FujiⅦ group, and resin ClinproTM Sealant group. The retention rate of pit and fissure sealant and the incidence of primary molar caries were observed in the 6th, 12th, 24th and 36th months respectively. Results In the 6th month, 12th month and 24th month, there were no significant differences in the material retention rate between the GC Fuji Ⅶ group and ClinproTM Sealant group. In the 36th month, the retention rate of the ClinproTM sealant group was better than that of the GC Fuji Ⅶ group (P < 0.05). In the 6th month, the caries incidence in the Duraphat group, GC Fuji Ⅶ group and ClinproTM sealant group was significantly lower than that in the blank group (P < 0.001). There was no significant difference between the Duraphat group, GC Fuji Ⅶ group and ClinproTM sealant group. In the 12th month, 24th month and 36th month, the incidence of caries in the GC Fuji Ⅶ group and ClinproTM sealant group was lower than that in the Duraphat group and blank group (P < 0.001), but there was no significant difference between the blank group and Duraphat group, and there was no significant difference in caries incidence between the GC Fuji Ⅶ group and ClinproTM sealant group. Conclusion The GC Fuji Ⅶ and ClinproTM sealant treatments continuously and effectively prevented pit and fissure caries compared with simple fluoride application. However, in cases of limited cooperation and poor moisture isolation in young children, the preventive measures of glass ionomer pits and fissure sealants (GC Fuji Ⅶ) are simpler and more feasible.
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- 2022
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23. Recent Progress of Medical CT Image Processing Based on Deep Learning
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Tan, Yun, Qin, Jiaohua, Huang, Lixia, Tan, Ling, Xiang, Xuyu, Tang, Hao, Peng, Haikuo, Wu, Jiang, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Sun, Xingming, editor, Zhang, Xiaorui, editor, Xia, Zhihua, editor, and Bertino, Elisa, editor
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- 2021
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24. Acoustic emission source location method for glass fibre reinforced plastics based on virtual loading focusing enhancement technology.
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Qin, Rengchuan, Zhou, Ruiqi, Li, Qiufeng, Lu, Chao, and Huang, Lixia
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GLASS fibers ,ACOUSTIC radiators ,ACOUSTIC emission ,PIXELS ,ARRAY processing ,TIME reversal ,SPEED of sound - Abstract
Because of the inhomogeneity and anisotropy of glass fibre reinforced plastics (GFRP), it is always a challenge to detect the real-time dynamic quality during manufacturing and service. In this paper, a virtual loading focusing enhancement technology (VLFET) based on time reversal (TR) theory is proposed to accurately locate the acoustic emission (AE) source in the GFRP. First, the focusing enhancement theoretical model with virtual reverse loading is deduced according to the TR theory. Then, after measuring the optimal detection range and the average acoustic velocity, the sensor array is positioned on the GFRP specimen. The excitation signals applied to simulate the AE source at some positions are produced by using lead breaking, and the detection signals are received by the sensor array. Finally, the signals received by the sensor array are processed according to the theoretical model, and the fluctuation image in the monitoring area is reconstructed with fluctuation amplitude of each pixel to evaluate the AE source position. The experimental results demonstrate that the excitation sources can be accurately evaluated with the VLFET. The location error with the proposed method is less than 3.1%, higher than that from the current AE instrument. The proposed technology can also be applied to the AE evaluation of other anisotropic materials. [ABSTRACT FROM AUTHOR]
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- 2024
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25. Nanocellulose hyperfine network achieves sustained release of berberine hydrochloride solubilized with β-cyclodextrin for potential anti-infection oral administration
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Xiao, Lin, Poudel, Abishek Jung, Huang, Lixia, Wang, Yang, Abdalla, Ahmed M.E., and Yang, Guang
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- 2020
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26. Evaluating the Clinical Utility of Semi-Quantitative Luciferase Immunosorbent Assay Using Treponema pallidum Antigens in Syphilis Diagnosis and Treatment Monitoring
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Ke, Wujian, primary, Ao, Cailing, additional, Wei, Ran, additional, Zhu, Xiaozhen, additional, Shui, Jingwei, additional, Zhao, Jianhui, additional, Zhang, Xiaohui, additional, Wang, Liuyuan, additional, Huang, Liping, additional, Leng, Xingying, additional, Zhu, Rui, additional, Wu, Jiaxin, additional, Huang, Lixia, additional, Huang, Nanxuan, additional, Wang, Haiying, additional, Weng, Wenjia, additional, Yang, Ligang, additional, and Tang, Shixing, additional
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- 2024
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27. Cost-based distributionally robust tourist attraction recommendation with demand uncertainty
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Li, Zexin, primary, Li, Qiulin, additional, Li, Zepeng, additional, Huang, Lixia, additional, Pu, Song, additional, and Luo, Zunhao, additional
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- 2024
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28. Enhancing Colonoscopy Preparation in Elderly Constipation Patients: A Personalized Approach with PEG and Exercise - A Case Study
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Zhang, Lanlang, primary, Huang, Lixia, additional, Liu, Shanshan, additional, and Sun, Xiaofeng, additional
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- 2024
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29. Treatment of plasma cell balanitis associated with male genital lichen sclerosus using abrocitinib
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Xiong, Xiaoyu, primary, Chen, Rongyi, additional, Wang, Liuyuan, additional, Huang, Nanxuan, additional, Huang, Lixia, additional, Wang, Chunmei, additional, and Ke, Wujian, additional
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- 2024
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30. FHL2 promotes the aggressiveness of lung adenocarcinoma by inhibiting autophagy via activation of the PI3K/AKT/mTOR pathway
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Wang, Shuaishuai, primary, Liu, Baomo, additional, Su, Yan, additional, Wang, Nian, additional, Dong, Peixin, additional, Xu, Xiongye, additional, Huang, Lixia, additional, Li, Shaoli, additional, Gu, Jincui, additional, Qiu, Yanli, additional, Deng, Jiating, additional, Lin, Ziying, additional, and Zhou, Yanbin, additional
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- 2024
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31. Enhancing Colonoscopy Preparation in Elderly Constipation Patients: A Personalized Approach with PEG and Exercise - A Case Study
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Zhang,Lanlang, Huang,Lixia, Liu,Shanshan, Sun,Xiaofeng, Zhang,Lanlang, Huang,Lixia, Liu,Shanshan, and Sun,Xiaofeng
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Lanlang Zhang,1 Lixia Huang,2 Shanshan Liu,3 Xiaofeng Sun4 1Department of Haemodialysis, Fuyong Peopleâs Hospital of Baoan District, Shenzhen, Guangdong Province, 518103, Peopleâs Republic of China; 2Department of Gastrology, Fuyong Peopleâs Hospital of Baoan District, Shenzhen, Guangdong Province, 518103, Peopleâs Republic of China; 3Nursing Department, Fuyong Peopleâs Hospital of Baoan District, Shenzhen, Guangdong Province, 518103, Peopleâs Republic of China; 4Department of Ultrasound, Shenzhen Baoan Womenâs and Childrenâs Hospital, Shenzhen, Guangdong Province, 518000, Peopleâs Republic of ChinaCorrespondence: Xiaofeng Sun, Department of Ultrasound, Shenzhen Baoan Womenâs and Childrenâs Hospital, Shenzhen, Guangdong Province, 518000, Peopleâs Republic of China, Tel +86-13723457417, Email 350787457@qq.comAbstract: This study aimed to optimize bowel preparation efficacy for colonoscopy in elderly constipation patients. A 71-year-old patient with chronic constipation and a history of poor bowel preparation. To address these challenges, we implemented a personalized strategy combining of PEG administration and walking exercise. The PEG was administered according to a protocol, with intermittent exercise breaks of 10 minute. Bowel cleanliness was assessed using the Boston Bowel Preparation Scale (BBPS). Adverse reactions and tolerance were closely monitored throughout the intervention. The patientâs BBPS score improved from 3 to 8 post-intervention. The exercise intervention was well-tolerated (rating I), and mild nausea was observed only after the first PEG dose. No severe adverse reactions occurred. Subsequent Follow-up revealed symptom relief. The personalized approach combining (PEG and exercise intervention) successfully improved bowel preparation quality in the elderly constipation patient undergoing colonoscopy. This approach considers age-related changes in gastrointestinal function and activity level, offering an effective strategy
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- 2024
32. Knee osteoarthritis pendulum therapy : in vivo evaluation and a randomised, single-blind feasibility clinical trial
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Huang Lixia, Xia Zhidao, Wade, Derick, Liu Jicai, Zhou Guoyong, Yu Chuanhua, Dawes, Helen, Esser, Patrick, Wei Shijun, Song Jiuhong, Huang Lixia, Xia Zhidao, Wade, Derick, Liu Jicai, Zhou Guoyong, Yu Chuanhua, Dawes, Helen, Esser, Patrick, Wei Shijun, and Song Jiuhong
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Background. Exercise is recommended as the first-line management for knee osteoarthritis (KOA); however, it is difficult to determine which specific exercises are more effective. This study aimed to explore the potential mechanism and effectiveness of a leg-swinging exercise practiced in China, called ‘KOA pendulum therapy’ (KOAPT). Intraarticular hydrostatic and dynamic pressure (IHDP) are suggested to partially explain the signs and symptoms of KOA. As such this paper set out to explore this mechanism in vivo in minipigs and in human volunteers alongside a feasibility clinical trial. The objective of this study is 1) to analyze the effect of KOAPT on local mechanical and circulation environment of the knee in experimental animals and healthy volunteers; and 2) to test if it is feasible to run a large sample, randomized/single blind clinical trial. Methods. IHDP of the knee was measured in ten minipigs and ten volunteers (five healthy and five KOA patients). The effect of leg swinging on synovial blood flow and synovial fluid content depletion in minipigs were also measured. Fifty KOA patients were randomly divided into two groups for a feasibility clinical trial. One group performed KOAPT (targeting 1000 swings/leg/day), and the other performed walking exercise (targeting 4000 steps/day) for 12 weeks with 12 weeks of follow-up. Results. The results showed dynamic intra-articular pressure changes in the knee joint, increases in local blood flow, and depletion of synovial fluid contents during pendulum leg swinging in minipigs. The intra-articular pressure in healthy human knee joints was −11.32 ± 0.21 (cmH2O), whereas in KOA patients, it was −3.52 ± 0.34 (cmH2O). Measures were completed by 100% of participants in all groups with 95–98% adherence to training in both groups in the feasibility clinical trial. There were significant decreases in the Oxford knee score in both KOAPT and walking groups after intervention (p < 0.01), but no significant differences between
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- 2024
33. Acoustic emission source localization method for high-speed train bogie
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Wei, Xincheng, Chen, Yao, Lu, Chao, Chen, Guo, Huang, Lixia, and Li, Qiufeng
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- 2020
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34. PTEN loss correlates with T cell exclusion across human cancers
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Lin, Ziying, Huang, Lixia, Li, Shao Li, Gu, Jincui, Cui, Xiaoxian, and Zhou, Yanbin
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- 2021
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35. Recent Progress of Medical CT Image Processing Based on Deep Learning
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Tan, Yun, primary, Qin, Jiaohua, additional, Huang, Lixia, additional, Tan, Ling, additional, Xiang, Xuyu, additional, Tang, Hao, additional, Peng, Haikuo, additional, and Wu, Jiang, additional
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- 2021
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36. Acoustic-articulatory emotion recognition using multiple features and parameter-optimized cascaded deep learning network
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Li, Juan, primary, Zhang, Xueying, additional, Li, Fenglian, additional, Duan, Shufei, additional, and Huang, Lixia, additional
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- 2023
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37. Optimizing the Service Network Design Problem for Railroad Intermodal Transportation of Hazardous Materials
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Huang, Lixia and Zhao, Jun
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Algorithm ,Hazardous substances -- Methods ,Railroads -- Shipments data -- Methods ,Transportation industry -- Shipments data -- Methods ,Algorithms -- Methods ,Intermodal transportation -- Shipments data - Abstract
The service network design problem is one of the key problems in the field of railroad intermodal transportation of hazardous materials (hazmat). It lies in determining the frequency of the trains and the allocation of both hazardous and ordinary shipments to these trains, as well as the railroad connecting plan of all shipments based on the established train formation plan. Based on a unified method, we build a multiobjective mixed-integer linear-programming model that comprehensively considers both hazardous and ordinary materials, the compatibility of goods and services, the capacity of the transfer station, and the delivery time limit of each shipment. An augmented ε -constraint algorithm is customized to solve the model. Computational results of a practical example in China show that an increase of 8.4 million yuan in the total cost could reduce nearly 24541 the total risk. Moreover, the algorithms comparison and sensitivity analysis indicate that the augmented ε -constraint algorithm is a more suitable approach to handle the model because of its advantage in the uniqueness of distinct nondominated solutions. Finally, the sensitivity analysis shows that the total cost and risk could simultaneously be reduced if the delivery time limit is relaxed or if the transfer time is shortened., Author(s): Lixia Huang (corresponding author) [1]; Jun Zhao [2,3] 1. Introduction Hazardous materials (hazmat), such as combustibles, explosives, poisons, and radioactive substances, are the basic components of our modern industrialized [...]
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- 2022
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38. Porous chitosan microspheres as microcarriers for 3D cell culture
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Huang, Lixia, Xiao, Lin, Jung Poudel, Abishek, Li, Jixiang, Zhou, Ping, Gauthier, Mario, Liu, Haiqing, Wu, Zhihong, and Yang, Guang
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- 2018
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39. Supramolecular hydrogels based on poly (ethylene glycol)-poly (lactic acid) block copolymer micelles and α-cyclodextrin for potential injectable drug delivery system
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Poudel, Abishek Jung, He, Feng, Huang, Lixia, Xiao, Lin, and Yang, Guang
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- 2018
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40. The surgical safety checklist and patient outcomes after surgery: a prospective observational cohort study, systematic review and meta-analysis
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Pearse, Rupert M., Beattie, Scott, Clavien, Pierre-Alain, Demartines, Nicolas, Fleisher, Lee A., Grocott, Mike, Haddow, James, Hoeft, Andreas, Holt, Peter, Moreno, Rui, Pritchard, Naomi, Rhodes, Andrew, Wijeysundera, Duminda, Wilson, Matt, Ahmed, Tahania, Everingham, Kirsty, Hewson, Russell, Januszewska, Marta, Phull, Mandeep-Kaur, Halliwell, Richard, Shulman, Mark, Myles, Paul, Schmid, Werner, Hiesmayr, Michael, Wouters, Patrick, de Hert, Stefan, Lobo, Suzana, Fang, Xiangming, Rasmussen, Lars, Futier, Emmanuel, Biais, Matthieu, Venara, Aurélien, Slim, Karem, Sander, Michael, Koulenti, Despoina, Arvaniti, Kostoula, Chan, Mathew, Kulkarni, Atul, Chandra, Susilo, Tantri, Aida, Geddoa, Emad, Abbas, Muntadhar, Della Rocca, Giorgio, Sivasakthi, Datin, Mansor, Marzida, Luna, Pastor, Bouwman, Arthur, Buhre, Wolfgang, Beavis, Vanessa, Campbell, Douglas, Short, Tim, Osinaike, Tunde, Matos, Ricardo, Grigoras, Ioana, Kirov, Mikhail, Protsenko, Denis, Biccard, Bruce, Aldecoa, Cesar, Chew, Michelle, Hofer, Christoph, Hubner, Martin, Ditai, James, Szakmany, Tamas, Fleisher, Lee, Ferguson, Marissa, MacMahon, Michael, Cherian, Ritchie, Currow, Helen, Kanathiban, Kathirgamanathan, Gillespie, David, Pathmanathan, Edward, Phillips, Katherine, Reynolds, Jenifer, Rowley, Joanne, Douglas, Jeanene, Kerridge, Ross, Garg, Sameer, Bennett, Michael, Jain, Megha, Alcock, David, Terblanche, Nico, Cotter, Rochelle, Leslie, Kate, Stewart, Marcelle, Zingerle, Nicolette, Clyde, Antony, Hambidge, Oliver, Rehak, Adam, Cotterell, Sharon, Huynh, Wilson Binh Quan, McCulloch, Timothy, Ben-Menachem, Erez, Egan, Thomas, Cope, Jennifer, Fellinger, Paul, Haisjackl, Markus, Haselberger, Simone, Holaubek, Caroline, Lichtenegger, Paul, Scherz, Florian, Hoffer, Franz, Cakova, Veronika, Eichwalder, Andreas, Fischbach, Norbert, Klug, Reinhold, Schneider, Elisabeth, Vesely, Martin, Wickenhauser, Reinhart, Grubmueller, Karl Gernot, Leitgeb, Marion, Lang, Friedrich, Toro, Nancy, Bauer, Marlene, Laengle, Friedrich, Haberl, Claudia, Mayrhofer, Thomas, Trybus, Christoph, Buerkle, Christian, Forstner, Karin, Germann, Reinhard, Rinoesl, Harald, Schindler, Elke, Trampitsch, Ernst, Bogner, Gerhard, Dankl, Daniel, Duenser, Martin, Fritsch, Gerhard, Gradwohl-Matis, Ilse, Hartmann, Andreas, Hoelzenbein, Thomas, Jaeger, Tarkan, Landauer, Franz, Lindl, Gregor, Lux, Michael, Steindl, Johannes, Stundner, Ottokar, Szabo, Christian, Bidgoli, Jawad, Verdoodt, Hans, Forget, Patrice, Kahn, David, Lois, Fernande, Momeni, Mona, Prégardien, Caroline, Pospiech, Audrey, Steyaert, Arnaud, Veevaete, Laurent, De Kegel, Dirk, De Jongh, Karen, Foubert, Luc, Smitz, Carine, Vercauteren, Marcel, Poelaert, Jan, Van Mossevelde, Veerle, Abeloos, Jacques, Bouchez, Stefaan, Coppens, Marc, De Baerdemaeker, Luc, Deblaere, Isabel, De Bruyne, Ann, Fonck, Kristine, Heyse, Bjorn, Jacobs, Tom, Lapage, Koen, Moerman, Anneliese, Neckebroek, Martine, Parashchanka, Aliaksandra, Roels, Nathalie, Van Den Eynde, Nancy, Vandenheuvel, 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Robert, Axe, Belda, Margarita Tormo, Norton, Tracy, Alherz, Fadhel, Barneto, Lisa, Ramirez, Alberto, Sayeed, Ahmed, Smith, Nicola, Bennett, Cambell, McQuoid, Shane, Jansen, Tracy-Lee, Nico, Zin, Scott, John, Freschini, David, Freschini, Angela, Hopkins, Brian, Manson, Lara, Stoltz, Deon, Bates, Alexander, Davis, Simon, Freeman, Victoria, McGaughran, Lynette, Williams, Maya, Sharma, Swarna Baskar, Burrows, Tom, Byrne, Kelly, English, Duane, Johnson, Robert, Manikkam, Brendon, Naidoo, Shaun, Rumball, Margot, Whittle, Nicola, Franks, Romilla, Gibson-Lapsley, Hannah, Salter, Ryan, Walsh, Dean, Cooper, Richard, Perry, Katherine, Obobolo, Amos, Sule, Umar Musa, Ahmad, Abdurrahman, Atiku, Mamuda, Mohammed, Alhassan Datti, Sarki, Adamu Muhammad, Adekola, Oyebola, Akanmu, Olanrewaju, Durodola, Adekunle, Olukoju, Olusegun, Raji, Victor, Olajumoke, Tokunbo, Oyebamiji, Emmanuel, Adenekan, Anthony, Adetoye, Adedapo, Faponle, Folayemi, Olateju, Simeon, Owojuyigbe, Afolabi, Talabi, Ademola, Adenike, Odewabi, Adewale, Badru, Collins, Nwokoro, Ezekiel, Emmanuel, Fatungase, Oluwabunmi Motunrayo, Grace, Anuforo, Sola, Sotannde, Stella, Ogunmuyiwa, Ademola, Adeyinka, Adeolu, Augustine A., Adigun, Tinuola, Akinwale, Mukaila, Fasina, Oluyemi, Gbolahan, Olalere, Idowu, Olusola, Olonisakin, Rotimi Peter, Osinaike, Babatunde Babasola, Asudo, Felicia, Mshelia, Danladi, Abdur-Rahman, Lukman, Agodirin, Olayide, Bello, Jibril, Bolaji, Benjamin, Oyedepo, Olanrewaju Olubukola, Ezike, Humphrey, Iloabachie, Ikechukwu, Okonkwo, Ikemefuna, Onuora, Elias, Onyeka, Tonia, Ugwu, Innocent, Umeh, Friday, Alagbe-Briggs, Olubusola, Dodiyi-Manuel, Amabra, Echem, Richard, Obasuyi, Bright, Onajin-Obembe, Bisola, Bandeira, Maria Expedito, Martins, Alda, Tomé, Miguel, Costa, Ana Cristina Miranda Martins, Krystopchuk, Andriy, Branco, Teresa, Esteves, Simao, Melo, Marco António, Monte, Júlia, Rua, Fernando, Martins, Isabel, Pinho-Oliveira, Vítor Miguel, Rodrigues, Carla Maria, Cabral, Raquel, Marques, Sofia, Rêgo, Sara, Jesus, Joana Sofia Teixeira, Marques, Maria Conceição, Romao, Cristina, Dias, Sandra, Santos, Ana Margarida, Alves, Maria Joao, Salta, Cristina, Cruz, Salome, Duarte, Célia, Paiva, António Armando Furtado, Cabral, Tiago do Nascimento, Faria e Maia, Dionisio, Correia da Silva, Rui Freitas Mendonça, Langner, Anuschka, Resendes, Hernâni Oliveira, Soares, Maria da Conceição, Abrunhosa, Alexandra, Faria, Filomena, Miranda, Lina, Pereira, Helena, Serra, Sofia, Ionescu, Daniela, Margarit, Simona, Mitre, Calin, Vasian, Horatiu, Manga, Gratiela, Stefan, Andreea, Tomescu, Dana, Filipescu, Daniela, Paunescu, Marilena-Alina, Stefan, Mihai, Stoica, Radu, Gavril, Laura, Pătrășcanu, Emilia, Ristescu, Irina, Rusu, Daniel, Diaconescu, Ciresica, Iosep, Gabriel Florin, Pulbere, Dorin, Ursu, Irina, Balanescu, Andreea, Grintescu, Ioana, Mirea, Liliana, Rentea, Irina, Vartic, Mihaela, Lupu, Mary-Nicoleta, Stanescu, Dorin, Streanga, Lavinea, Antal, Oana, Hagau, Natalia, Patras, Dumitru, Petrisor, Cristina, Tosa, Flaviu, Tranca, Sebastian, Copotoiu, Sanda Maria, Ungureanu, Liviu Lucian, Harsan, Cristian Remus, Papurica, Marius, Cernea, Daniela Denisa, Dragoescu, Nicoleta Alice, CarmenVaida, Laura Aflori, Ciobotaru, Oana Roxana, Aignatoaie, Mariana, Carp, Cristina Paula, Cobzaru, Isabelle, Mardare, Oana, Purcarin, Bianca, Tutunaru, Valentin, Ionita, Victor, Arustei, Mirela, Codita, Anisoara, Busuioc, Mihai, Chilinciuc, Ion, Ciobanu, Cristina, Belciu, Ioana, Tincu, Eugen, Blaj, Mihaela, Grosu, Ramona - Mihaela, Sandu, Gigel, Bruma, Dana, Corneci, Dan, Dutu, Madalina, Krepil, Adriana, Copaciu, Elena, Dumitrascu, Clementina Oana, Jemna, Ramona, Mihaescu, Florentina, Petre, Raluca, Tudor, Cristina, Ursache, Elena, Kulikov, Alexander, Lubnin, Andrey, Grigoryev, Evgeny, Pugachev, Stanislav, Tolmasov, Alexander, Hussain, Ayyaz, Ilyina, Yana, Roshchina, Anna, Iurin, Aleksandr, Chazova, Elena, Dunay, Artem, Karelov, Alexey, Khvedelidze, Irina, Voldaeva, Olga, Belskiy, Vladislav, Dzhamullaev, Parvin, Grishkowez, Elena, Kretov, Vladimir, Levin, Valeriy, Molkov, Aleksandr, Puzanov, Sergey, Samoilenko, Aleksandr, Tchekulaev, Aleksandr, Tulupova, Valentina, Utkin, Ivan, Allorto, Nikki Leigh, Bishop, David Gray, Builu, Pierre Monji, Cairns, Carel, Dasrath, Ashish, de Wet, Jacques, Hoedt, Marielle den, Grey, Ben, Hayes, Morgan Philip, Küsel, Belinda Senta, Shangase, Nomcebo, Wise, Robert, Cacala, Sharon, Farina, Zane, Govindasamy, Vishendran, Kruse, Carl-Heinz, Lee, Carolyn, Marais, Leonard, Naidoo, Thinagrin Dhasarthun, Rajah, Chantal, Rodseth, Reitze Nils, Ryan, Lisa, von Rhaden, Richard, Adam, Suwayba, Alphonsus, Christella, Ameer, Yusuf, Anderson, Frank, Basanth, Sujith, Bechan, Sudha, Bhula, Chettan, Biccard, Bruce M., Biyase, Thuli, Buccimazza, Ines, Cardosa, Jorge, Chen, James, Daya, Bhavika, Drummond, Leanne, Elabib, Ali, Abdel Goad, Ehab Helmy, Goga, Ismail E., Goga, Riaz, Harrichandparsad, R., Hodgson, Richard E., Jordaan, J., Kalafatis, Nicky, Kampik, Christian, Landers, A.T., Loots, Emil, Madansein, Rajhmum, Madaree, Anil, Madiba, Thandinkosi E., Manzini, Vukani T., Mbuyisa, Mbali, Moodley, Rajan, Msomi, Mduduzi, Mukama, Innocent, Naidoo, Desigan, Naidoo, Rubeshan, Naidu, Tesuven K., Ntloko, Sindiswa, Padayachee, Eneshia, Padayachee, Lucelle, Phaff, Martijn, Pillay, Bala, Pillay, Desigan, Pillay, Lutchmee, Ramnarain, Anupa, Ramphal, Suren R., Ryan, Paul, Saloojee, Ahmed, Sebitloane, Motshedisi, Sigcu, Noluyolo, Taylor, Jenna L., Torborg, Alexandra, Visser, Linda, Anderson, Philip, Conradie, Alae, de Swardt, Mathew, de Villiers, Martin, Eikman, Johan, Liebenberg, Riaan, Mouton, Johan, Paton, Abbey, van der Merwe, Louwrence, Wilscott-Davids, Candice, Barrett, Wendy Joan, Bester, Marlet, de Beer, Johan, Geldenhuys, Jacques, Gouws, Hanni, Potgieter, Jan-Hendrik, Strydom, Magdel, WilberforceTurton, Edwin, Chetty, Rubendraj R., Chirkut, Subash, Cronje, Larissa, de Vasconcellos, Kim, Dube, Nokukhanya Z., Gama, N. Sibusiso, Green, Garyth M., Green-Thompson, Randolph, Kinoo, Suman Mewa, Kistnasami, Prenolin, Maharaj, Kapil, Moodley, Manogaran S., Mothae, Sibongile J., Naidoo, Ruvashni, Aslam F Noorbhai, M., Rughubar, Vivesh, Reddy, Jenendhiran, Singh, Avesh, Skinner, David L., Smith, Murray J., Singh, Bhagwan, Misra, Ravi, Naidoo, Maheshwar, Ramdharee, Pireshin, Selibea, Yvonne, Sewpersad, Selina, Sham, Shailendra, Wessels, Joseph D., Africander, Cucu, Bejia, Tarek, Blakemore, Stephen P., Botes, Marisa, Bunwarie, Bimalshakth, Hernandez, Carlos B., Jeeraz, Mohammud A., Legutko, Dagmara A., Lopez, Acela G., De Meyer, Jenine N., Muzenda, Tanaka, Naidoo, Noel, Patel, Maryam, Pentela, Rao, Junge, Marina, Mansoor, Naj, Rademan, Lana, Scislowski, Pawel, Seedat, Ismail, van den Berg, Bianca, van der Merwe, Doreen, van Wyk, Steyn, Govender, Komalan, Naicker, Darshan, Ramjee, Rajesh, Saley, Mueen, Kuhn, Warren Paul, Matos-Puig, Roel, Alberto Lisi, Zaheer Moolla, Perez, Gisela, Beltran, Anna Valle, Lozano, Angels, Navarro, Carlos Delgado, Duca, Alejandro, Ernesto, Ernesto Pastor Martinez, Ferrando, Carlos, Fuentes, Isabel, García-Pérez, Maria Luisa, Gracia, Estefania, Palomares, Ana Izquierdo, Katime, Antonio, Miñana, Amanda, Incertis, Raul Raul, Romero, Esther, Romero Garcia, Carolina Soledad, Rubio, Concepcion, Artiles, Tania Socorro, Soro, Marina, Valls, Paola, Laguarda, Gisela Alaman, Benavent, Pau, Cuenca, Vicente Chisbert, Cueva, Andreu, Lafuente, Matilde, Parra, Asuncion Marques, Rodrigo, Alejandra Romero, Sanchez-Morcillo, Silvia, Tormo, Sergi, Redondo, Francisco Javier, De Andrés Ibanez, José Antonio, Diago, Lorena Gómez, José Hernández Cádiz, Maria, Manuel, Granell Gil, Peris, Raquel, Saiz, Cristina, Vivo, Jose Tatay, Soto, Maria Teresa Tebar, Brunete, Tamara, Cancho, David, Delgado García, David R., Zamudio, Diana, Del Valle, Santiago Garcia, Serrano, M. Luz, Alonso, Eduardo, Anillo, Victor, Maseda, Emilio, Salgado, Patricia, Suarez, Luis, Suarez-de-la-Rica, Alejandro, Villagrán, María José, Alonso, José Ignacio, Cabezuelo, Estefania, Garcia-Saiz, Irene, Lopez del Moral, Olga, Martín, Silvia, Gonzalez, Alba Perez, Doncel, Ma Sherezade Tovar, Vera, Martin Agüero, José Ávila Sánchez, Francisco, Castaño, Beatriz, Moreira, Beatriz Castaño, Risco, Sahely Flores, Martín, Daniel Paz, Martín, Fernando Pérez, Poza, Paloma, Ruiz, Adela, Serna Martínez, Wilson Fabio, Vicente, Bárbara Vázquez, Dominguez, Saul Velaz, Fernández, Salvador, Munoz-López, Alfonso, Bernat, Maria Jose, Mas, Arantxa, Planas, Kenneth, Jawad, Monir, Saeed, Yousif, Hedin, Annika, Levander, Helena, Holmström, Sandra, Lönn, David, Zoerner, Frank, Åkring, Irene, Widmark, Carl, Zettergren, Jan, Liljequist, Victor Aspelund, Nystrom, Lena, Odeberg-Wernerman, Suzanne, Oldner, Anders, Fagerlund, Malin Jonsson, Reje, Patrik, Lyckner, Sara, Sperber, Jesper, Adolfsson, Anne, Klarin, Bengt, Ögren, Katrin, Barras, Jean-Pierre, Bührer, Thomas, Despotidis, Vasileios, Helmy, Naeder, Holliger, Stephan, Raptis, Dimitri Aristotle, Schmid, Roger, Meyer, Antoine, Jaquet, Yves, Kessler, Ulf, Muradbegovic, Mirza, Nahum, Solange R., Rotunno, Teresa, Schiltz, Boris, Voruz, François, Worreth, Marc, Christoforidis, Dimitri, Popeskou, Sotirios Georgios, Furrer, Markus, Prevost, Gian Andrea, Stocker, Andrea, Lang, Klaus, Breitenstein, Stefan, Ganter, Michael T., Geisen, Martin, Soll, Christopher, Korkmaz, Michelle, Lubach, Iris, Schmitz, Michael, Meyer zu Schwabedissen, Moritz, Moritz, Meyer zu Schwabedissen, Zingg, Urs, Hillermann, Thomas, Wildi, Stefan, Pinto, Bernardo Bollen, Walder, Bernhard, Mariotti, Giustina, Slankamenac, Ksenija, Namuyuga, Mirioce, Kyomugisha, Edward, Kituuka, Olivia, Shikanda, Anne Wesonga, Kakembo, Nasser, Tom, Charles Otim, Antonina, Webombesa, Bua, Emmanuel, Ssettabi, Eden Michael, Epodoi, Joseph, Kabagenyi, Fiona, Kirya, Fred, Dempsey, Ged, Seasman, Colette, Nawaz Khan, Raja Basit, Kurasz, Claire, Macgregor, Mark, Shawki, Burhan, Francis, Daren, Hariharan, Vimal, Chau, Simon, Ellis, Kate, Butt, Georgina, Chicken, Dennis-Wayne, Christmas, Natasha, Allen, Samantha, Daniel, Gayatri Daniel, Dempster, Angie, Kemp, Juliette, Matthews, Lewis, Mcglone, Philip, Tambellini, Joanne, Trodd, Dawn, Freitas, Katie, Garg, Atul, Gupta, Janesh Kumar, Karpate, Shilpaja, Kulkarni, Aditi, O'Hara, Chloe, Troko, Jtroko, Angus, Kirsty, Bradley, Jacqueline, Brennan, Emma, Brooks, Carolyn, Brown, Janette, Brown, Gemma, Finch, Amanda, Gratrix, Karen, Hesketh, Sue, Hill, Gillian, Jeffs, Carol, Morgan, Maureen, Pemberton, Chris, Slawson, Nicola, Spickett, Helen, Swarbrick, Gemma, Thomas, Megan, Van Duyvenvoorde, Greta, Brennan, Andrew, Briscoe, Richard, Cooper, Sarah, Lawton, Tom, Northey, Martin, Senaratne, Rashmi, Stanworth, Helen, Burrows, Lorna, Cain, Helen, Craven, Rachael, Davies, Keith, Jonas, Attila, Pachucki, Marcin, Walkden, Graham, Davies, Helen, Gudaca, Mariethel, Hobrok, Maria, Arawwawala, Dilshan, Fergey, Lauren, Gardiner, Matthew, Gunn, Jacqueline, Johnson, Lyndsay, Lofting, Amanda, Lyle, Amanda, Neela, Fiona Mc, Smolen, Susan, Topliffe, Joanne, Williams, Sarah, Bland, Martin, Balaji, Packianathaswamy, Kaura, Vikas, Lanka, Prasad, Smith, Neil, Ahmed, Ahmed, Myatt, John, Shenoy, Ravikiran, Soon, Wai Cheong, Tan, Jessica, Karadia, Sunny, Self, James, Durant, Emma, Tripathi, Shiva, Bullock, Clare, Campbell, Debbie, Ghosh, Alison, Hughes, Thomas, Zsisku, Lajos, Bengeri, Sheshagiri, Cowton, Amanda, Khalid, Mohammed Shazad, Limb, James, McAdam, Colin, Porritt, Mandy, Rafi, M. 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Parizade, Szafranski, Jan, Twohey, Linda, Watt, Philip, Weatherall, Lucie, Weatherill, J., Whitman, Zoe, Wighton, Elinor, Abayasinghe, Chamika, Chan, Alexander, Darwish, Sharif, Gill, James, Glasgow, Emma, Hadfield, Daniel, Harris, Clair, Hopkins, Phil, Kochhar, Arun, Kunst, Gudrun, Mellis, Clare, Pool, Andrew, Riozzi, Paul, Selman, Andrew, Smith, Emma-Jane, Vele, Liana, Gercek, Yuksel, Guy, Kramer, Holden, Douglas, Watson, Nicholas, Whysall, Karen, Andreou, Prematie, Hales, Dawn, Thompson, Jonathan, Bowrey, Sarah, McDonald, Shara, Gilmore, Jemma, Hills, Vicky, Kelly, Chan, Kelly, Sinead, Lloyd, Geraint, Abbott, Tom, Gall, Lewis, Torrance, Hew, Vivian, Mark, Berntsen, Emer, Nolan, Tracey, Turner, Angus, Vohra, Akbar, Brown, Andrew, Clark, Richard, Coughlan, Elaine, Daniel, Conway, Patvardhan, Chinmay, Pearson, Rachel, Predeep, Sheba, Saad, Hesham, Shanmugam, Mohanakrishnan, Varley, Simon, Wylie, Katharine, Cooper, Lucy, Makowski, Arystarch, Misztal, Beata, Moldovan, Eliza, Pegg, 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Cooper, Lauren, Denham, Samuel, Griffiths, Ewen, Ip, Peter, Jeyanthan, Somasundaram, Joory, Kavita, Kaur, Satwant, Marriott, Paul, Mitchell, Natalie, Nagaiah, Sukumar, Nilsson, Annette, Parekh, Nilesh, Pope, Martin, Seager, Joseph, Serag, Hosam, Tameem, Alifia, Thomas, Anna, Thunder, Joanne, Torrance, Andrew, Vohra, Ravinder, Arlo whitehouse, Wong, Tony, Blunt, Mark, Wong, Kate, Giles, Julian, Reed, Isabelle, Weller, Debbie, Bell, Gillian, Birch, Julie, Damant, Rose, Maiden, Jane, Mewies, Clare, Prince, Claire, Radford, Jane, Reynolds, Tim, Balain, Birender, Banerjee, Robin, Barnett, Andrew, Burston, Ben, Davies, Kirsty, Edwards, Jayne, Evans, Chris, Ford, David, Gallacher, Pete, Hill, Simon, Jaffray, David, Karlakki, Sudheer, Kelly, Cormac, Kennedy, Julia, Kiely, Nigel, Lewthwaite, Simon, Marquis, Chris, Ockendon, Matthew, Phillips, Stephen, Pickard, Simon, Richardson, James, Roach, Richard, Smith, Tony, Spencer-Jones, Richard, Steele, Niall, Steen, Julie, Van Liefland, Marck, White, Steve, Faulds, Matthew, Harris, Meredyth, Kelly, Carrie, Nicol, Scott, Pearson, Sally Anne, Chukkambotla, Srikanth, Andrew, Alyson, Attrill, Elizabeth, Campbell, Graham, Datson, Amanda, Fouracres, Anna, Graterol, Juan, Graves, Lynne, Hong, Bosun, Ishimaru, Alexander, Karthikeyan, Arvind, King, Helen, Lawson, Tom, Lee, Gregory, Lyons, Saoirse, Hall, Andrew Macalister, Mathoulin, Sophie, Mcintyre, Eilidh, Mclaughlin, Danny, Mulcahy, Kathleen, Paddle, Jonathan, Ratcliffe, Anna, Robbins, James, Sung, Weilin, Tayo, Adeoluwa, Trembath, Lisa, Venugopal, Suneetha, Walker, Robert, Wigmore, Geoffrey, Boereboom, Catherine, Downes, Charlotte, Humphries, Ryan, Melbourne, Susan, Smith, Coral, Tou, Samson, Ullah, Shafa, Batchelor, Nick, Boxall, Leigh, Broomby, Rupert, Deen, Tariq, Hellewell, Alistair, Helliwell, Laurence, Hutchings, Melanie, Hutchins, David, Keenan, Samantha, Mackie, Donna, Potter, Alison, Smith, Frances, Stone, Lucy, Thorpe, Kevin, Wassall, Richard, Woodgate, Andrew, Baillie, Shelley, Campbell, Tara, James, Sarah, King, Chris, Marques de Araujo, Daniela, Martin, Daniel, Morkane, Clare, Neely, Julia, Rajendram, Rajkumar, Burton, Megan, James, Kathryn, Keevil, Edward, Minik, Orsolya, Morgan, Jenna, Musgrave, Anna, Rajanna, Harish, Roberts, Tracey, Adamson, Michael, Jumbe, Sandra, Kendall, Jennie, Muthuswamy, Mohan Babu, Anderson, Charlotte, Cruikshanks, Andrew, Wrench, Ian, Zeidan, Lisa, Ardern, Diane, Harris, Benjamin, Hellstrom, Johanna, Martin, Jane, Thomas, Richard, Varsani, Nimu, Brown, Caroline Wrey, Docherty, Philip, Gillies, Michael, McGregor, Euan, Usher, Helen, Craig, Jayne, Smith, Andrew, Ahmad, Tahania, Bodger, Phoebe, Creary, Thais, Fowler, Alexander, Hewson, Russ, Ijuo, Eke, Jones, Timothy, Kantsedikas, Ilya, Lahiri, Sumitra, McLean, Aaron Lawson, Niebrzegowska, Edyta, Phull, Mandeep, Wang, Difei, Wickboldt, Nadine, Baldwin, Jacqueline, Doyle, Donna, Mcmullan, Sean, Oladapo, Michelle, Owen, Thomas, Williams, Alexandra, Daniel, Hull, Gregory, Peter, Husain, Tauqeer, Kirk-Bayley, Justin, Mathers, Edward, Montague, Laura, Harper, Mark, White, Stuart, Jack, James, Ridley, Carrie, Avis, Joanne, Cook, Tim, Dali-Kemmery, Lola, Kerslake, Ian, Lambourne, Victoria, Pearson, Annabel, Boyd, Christine, Callaghan, Mark, Lawson, Cathy, McCrossan, Roopa, Nesbitt, Vanessa, O'connor, Laura, Scott, Julia, Sinclair, Rhona, Farid, Nahla, Morgese, Ciro, Bhatia, Kailash, Karmarkar, Swati, Ahmed, Jamil, Branagan, Graham, Hutton, Monica, Swain, Andrew, Brookes, Jamie, Cornell, Jonathan, Dolan, Rachael, Hulme, Jonathan, Jansen van Vuuren, Amanda, Jowitt, Tom, Kalashetty, Gunasheela, Lloyd, Fran, Patel, Kiran, Sherwood, Nicholas, Brown, Lynne, Chandler, Ben, Deighton, Kerry, Emma, Temlett, Haunch, Kirsty, Cheeseman, Michelle, Dent, Kathy, Garg, Sanjeev, Gray, Carol, Hood, Marion, Jones, Dawn, Juj, Joanne, Rao, Roshan, Walker, Tara, Al Anizi, Mashel, Cheah, Clarissa, Cheing, Yushio, Coutinho, Francisco, Gondo, Prisca, Hadebe, Bernard, Hove, Mazvangu Onie, Ahamed khader, Krishnachetty, Bobby, Rhodes, Karen, Sokhi, Jagdish, Baker, Katie-Anne, Bertram, Wendy, Looseley, Alex, Mouton, Ronelle, Hanna, George, Arnold, Glenn, Arya, Shobhit, Balfoussia, Danai, Baxter, Linden, Harris, James, Jones, Craig, Knaggs, Alison, Markar, Sheraz, Perera, Anisha, Scott, Alasdair, Shida, Asako, Sirha, Ravneet, Wright, Sally, Frost, Victoria, Gray, Catherine, Andrews, Emma, Arrandale, Lindsay, Barrett, Stephen, Cifra, Elna, Cooper, Mariese, Dragnea, Dragos, Elna, Cifra, Maclean, Jennifer, Meier, Sonja, Milliken, Donald, Munns, Christopher, Ratanshi, Nadir, Ramessur, Suneil, Salvana, Abegail, Watson, Anthony, Ali, Hani, Campbell, Gill, Critchley, Rebecca, Endersby, Simon, Hicks, Catherine, Liddle, Alison, Pass, Marc, Ritchie, Charlotte, Thomas, Charlotte, Too, Lingxi, Welsh, Sarah, Gill, Talvinder, Johnson, Joanne, Reed, Joanne, Davis, Edward, Papadopoullos, Sam, Attwood, Clare, Biffen, Andrew, Boulton, Kerenza, Gray, Sophie, Hay, David, Mills, Sarah, Montgomery, Jane, Riddell, Rory, Simpson, James, Bhardwaj, Neeraj, Paul, Elaine, Uwubamwen, Nosakhare, Alexander, Maini, Arrich, James, Arumugam, Swarna, Blackwood, Douglas, Boggiano, Victoria, Brown, Robyn, Chan, Yik Lam, Chatterjee, Devnandan, Chhabra, Ashok, Christian, Rachel, Costelloe, Hannah, Matthewman, Madeline Coxwell, Dalton, Emma, Darko, Julia, Davari, Maria, Dave, Tejal, Deacon, Matthew, Deepak, Shantal, Edmond, Holly, Ellis, Jessica, El-Sayed, Ahmed, Eneje, Philip, English, Rose, Ewe, Renee, Foers, William, Franklin, John, Gallego, Laura, Garrett, Emily, Goldberg, Olivia, Goss, Harry, Greaves, Rosanna, Harris, Rudy, Hennings, Charles, Jones, Eleanor, Kamali, Nelson, Kokkinos, Naomi, Lewis, Carys, Lignos, Leda, Malgapo, Evaleen Victoria, Malik, Rizwana, Milne, Andrew, Mulligan, John-Patrick, Nicklin, Philippa, Palipane, Natasha, Parsons, Thomas, Piper, Rebecca, Prakash, Rohan, Ramesh, Byron, Rasip, Sarah, Reading, Jacob, Rela, Mariam, Reyes, Anna, Stephens, Robert, Rooms, Martin, Shah, Karishma, Simons, Henry, Solanki, Shalil, Spowart, Emma, Stevens, Amy, Thomas, Christopher, Waggett, Helena, Yassaee, Arrash, Kennedy, Anthony, Scott, Sara, Somanath, Sameer, Berg, Andrew, Hernandez, Miguel, Nanda, Rajesh, Tank, Ghanshyambhai, Wilson, Natalie, Wilson, Debbie, Al-Soudaine, Yassr, Baldwin, Matthew, Cornish, Julie, Davies, Zoe, Davies, Leigh, Edwards, Marc, Frewer, Natasha, Gallard, Sian, Glasbey, James, Harries, Rhiannon, Hopkins, Luke, Kim, Taeyang, Koompirochana, Vilavan, Lawson, Simon, Lewis, Megan, Makzal, Zaid, Scourfield, Sarah, Ahmad, Yousra, Bates, Sarah, Blackwell, Clare, Bryant, Helen, Collins, Hannah, Coulter, Suzanne, Cruickshank, Ross, Daniel, Sonya, Daubeny, Thomas, Edwards, Mark, Golder, Kim, Hawkins, Lesley, Helen, Bryant, Hinxman, Honor, Levett, Denny, Salmon, Karen, Seaward, Leanne, Skinner, Ben, Tyrell, Bryony, Wadams, Beverley, Walsgrove, Joseph, Dickson, Jane, Constantin, Kathryn, Karen, Markwell, O'Brien, Peter, O'Donohoe, Lynn, Payne, Hannah, Sundayi, Saul, Walker, Elaine, Brooke, Jenny, Cardy, Jon, Humphreys, Sally, Kessack, Laura, Kubitzek, Christiane, Kumar, Suhas, Cotterill, Donna, Hodzovic, Emil, Hosdurga, Gurunath, Miles, Edward, Saunders, Glenn, Campbell, Marta, Chan, Peter, Jemmett, Kim, Raj, Ashok, Naik, Aditi, Oshowo, Ayo, Ramamoorthy, Rajarajan, Shah, Nimesh, Sylvan, Axel, Blyth, Katharine, Burtenshaw, Andrew, Freeman, David, Johnson, Emily, Lo, Philip, Martin, Terry, Plunkett, Emma, Wollaston, Julie, Allison, Joanna, Carroll, Christine, Craw, Nicholas, Craw, Sarah, Pitt-Kerby, Tressy, Rowland-Axe, Rebecca, Spurdle, Katie, McDonald, Andrew, Simon, Davies, Sinha, Vivek, Smith, Thomas, Banner-Goodspeed, Valerie, Boone, Myles, Campbell, Kathleen, Lu, Fengxin, Scannell, Joseph, Sobol, Julia, Balajonda, Naraida, Clemmons, Karen, Conde, Carlos, Elgasim, Magdi, Funk, Bonita, Hall, Roger, Hopkins, Thomas, Olaleye, Omowunmi, Omer, Omer, Pender, Michelle, Porto, Angelo, Stevens, Alice, Waweru, Peter, Yeh, Erlinda, Bodansky, Daniella, Evans, Adam, Kleopoulos, Steven, Maril, Robert, Mathney, Edward, Sanchez, Angela, Tinuoye, Elizabeth, Bateman, Brian, Eng, Kristen, Jiang, Ning, Ladha, Karim, Needleman, Joseph, Chen, Lee-lynn, Lane, Rondall, Robinowitz, David, Ghushe, Neil, Irshad, Mariam, O'Connor, John, Patel, Samir, Takemoto, Steven, Wallace, Art, Mazzeffi, Michael, Rock, Peter, Wallace, Karin, Zhu, Xiaomao, Chua, Pandora, Mattera, Matthew, Sharar, Rebecca, Thilen, Stephan, Treggiari, Miriam, Morgan, Angela, Sofjan, Iwan, Subramaniam, Kathirvel, Avidan, Michael, Maybrier, Hannah, Muench, Maxwell, Wildes, Troy, Abbott, T.E.F., Ahmad, T., Phull, M.K., Fowler, A.J., Hewson, R., Biccard, B.M., Chew, M.S., Gillies, M., and Pearse, R.M.
- Published
- 2018
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41. Research on Simulation Method of Mineral Monitoring With Remote Sensing Satellites
- Author
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Zhang, Yue, Wei, E., Yin, Jianfeng, Huang, Lixia, Urbach, H. Paul, editor, and Zhang, Guangjun, editor
- Published
- 2017
- Full Text
- View/download PDF
42. Design and Implementation of Virtual Real Fusion Metaverse Scene Based on Deep Learning
- Author
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Zeng, Wenying, primary, Hu, Jianhua, additional, Huang, Lixia, additional, and Wu, Weimei, additional
- Published
- 2023
- Full Text
- View/download PDF
43. Supramolecular Responsive Chitosan Microcarriers for Cell Detachment Triggered by Adamantane
- Author
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Huang, Lixia, primary, Jiang, Yifei, additional, Chen, Xinying, additional, Zhang, Wenqi, additional, Luo, Qiuchen, additional, Chen, Siyan, additional, Wang, Shuhan, additional, Weng, Fangqing, additional, and Xiao, Lin, additional
- Published
- 2023
- Full Text
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44. Uncommon Presentation of COVID-19: XBL Variant
- Author
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Zhang, Jing, primary, Dong, Peixin, additional, Liu, Baomo, additional, Wang, Shuaishuai, additional, Su, Yan, additional, Xu, Xiongye, additional, Deng, Jiating, additional, Lin, Ziying, additional, Li, Shaoli, additional, Gu, Jincui, additional, Qiu, Yanli, additional, Huang, Lixia, additional, and Zhou, Yanbin, additional
- Published
- 2023
- Full Text
- View/download PDF
45. Acoustic emission source location method for glass fibre reinforced plastics based on virtual loading focusing enhancement technology
- Author
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Qin, Rengchuan, primary, Zhou, Ruiqi, additional, Li, Qiufeng, additional, Lu, Chao, additional, and Huang, Lixia, additional
- Published
- 2023
- Full Text
- View/download PDF
46. Pan-cancer analysis of genomic properties and clinical outcome associated with tumor tertiary lymphoid structure
- Author
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Lin, Ziying, Huang, Lixia, Li, ShaoLi, Gu, Jincui, Cui, Xiaoxian, and Zhou, Yanbin
- Published
- 2020
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47. A Multi-satellite Scheduling Method for Emergency Observation Mission Based on Hierarchical Planning Strategy.
- Author
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Huang, Lixia, Zhao, Xuemei, Zhang, Qiang, and Li, Qunzhi
- Published
- 2024
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48. Sensing Signal Analysis and Imaging Processing With High Frequency Ultrasonic Testing for Fe-Based Amorphous Coatings
- Author
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Xinpeng Zhang, Qiufeng Li, Huang Lixia, Junwu Zhu, Yao Chen, and Chao Lu
- Subjects
Signal processing ,Materials science ,Scanning electron microscope ,business.industry ,Ultrasonic testing ,engineering.material ,Amorphous solid ,Quality (physics) ,Optics ,Coating ,Aliasing ,engineering ,Ultrasonic sensor ,Electrical and Electronic Engineering ,business ,Instrumentation - Abstract
In harsh environments, Fe-based amorphous coatings can provide effective protection for equipment. A method of thickness measurement of thin layer and quality evaluation based on high-frequency water-immersion ultrasonic testing and imaging is proposed here. In this paper, because of the interface echoes of the micron-scale coating in the aliasing of ultrasonic testing signals, wavepacket decomposition and extraction technology proposed according to the matching pursuit theory is used to separate the interface echoes. After using the narrow pulse replacement method, the coating structure imaged is reconstructed. The decomposed interface echoes will not be mixed again, thus reflecting the coating thickness information more accurately. Consequently it can be used to evaluate the coating quality. Finally, the experimental results show that the coating structure image can be reconstructed after the high-frequency water-immersion ultrasonic scanning signals are processed with the above method. The relative error of the coating thickness detection is only 3.13% compared with the scanning electron microscope (SEM) results. At the same time, the coating spraying quality can be evaluated effectively through the imaged results.
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- 2022
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49. Relationship between hemoglobin and lung cancer: evidence from Mendelian randomization and National Health and Nutrition Examination Survey
- Author
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Dong, Peixin, primary, Li, Wenjie, additional, Deng, Jiating, additional, Huang, Lixia, additional, Liu, Baomo, additional, Wang, Shuaishuai, additional, Xu, Xiongye, additional, Su, Yan, additional, Lin, Ziying, additional, Li, Shaoli, additional, Gu, Jincui, additional, Qiu, Yanli, additional, and Zhou, Yanbin, additional
- Published
- 2023
- Full Text
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50. The effectiveness of motivation‐guided PDCA cycle nursing for self‐management ability and outcomes of patients with gestational diabetes mellitus
- Author
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Zhao, Mingxia, primary, Li, Haixiang, additional, Wang, Jing, additional, Chu, Limin, additional, Huang, Lixia, additional, and Li, Hailian, additional
- Published
- 2023
- Full Text
- View/download PDF
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