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- 저자 : Wang Xiaozhe (검색결과 4 건)
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Xiaozhe Wang,Xiaofeng Ren,Jie Yang,Zican Zhao,Xiaoyu Zhang,Fan Yang,Zheye Zhang,Peng Chen,Liping Li,Ruiping Zhang 한국생체재료학회 2023 생체재료학회지 Vol.27 No.00
Rationale To realize imaging-guided multi-modality cancer therapy with minimal side effects remains highly challenging. Methods We devised a bioinspired hollow nitrogen-doped carbon sphere anchored with individually dispersed Mn atoms (Mn/N-HCN) via oxidation polymerization with triton micelle as a soft template, followed by carbonization and annealing. Enzyme kinetic analysis and optical properties were performed to evaluate the imaging-guided photothermally synergized nanocatalytic therapy. Results Simultaneously mimicking several natural enzymes, namely peroxidase (POD), catalase (CAT), oxidase (OXD), and glutathione peroxidase (GPx), this nano-multizyme is able to produce highly cytotoxic hydroxyl radical (•OH) and singlet oxygen (1O2) without external energy input through parallel and series catalytic reactions and suppress the upregulated antioxidant (glutathione) in tumor. Furthermore, NIR-II absorbing Mn/N-HCN permits photothermal therapy (PTT), enhancement of CAT activity, and photoacoustic (PA) imaging to monitor the accumulation kinetics of the nanozyme and catalytic process in situ. Both in vitro and in vivo experiments demonstrate that near-infrared- II (NIR-II) PA-imaging guided, photothermally enhanced and synergized nanocatalytic therapy is efficient to induce apoptosis of cancerous cells and eradicate tumor tissue. Conclusions This study not only demonstrates a new method for effective cancer diagnosis and therapy but also provides new insights into designing multi-functional nanozymes.
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A Highly Efficient Aeroelastic Optimization Method Based on a Surrogate Model
Zhiqiang, Wan,Xiaozhe, Wang,Chao, Yang The Korean Society for Aeronautical and Space Scie 2016 International Journal of Aeronautical and Space Sc Vol.17 No.4
This paper presents a highly efficient aeroelastic optimization method based on a surrogate model; the model is verified by considering the case of a high-aspect-ratio composite wing. Optimization frameworks using the Kriging model and genetic algorithm (GA), the Kriging model and improved particle swarm optimization (IPSO), and the back propagation neural network model (BP) and IPSO are presented. The feasibility of the method is verified, as the model can improve the optimization efficiency while also satisfying the engineering requirements. Moreover, the effects of the number of design variables and number of constraints on the optimization efficiency and objective function are analysed in detail. The accuracy of two surrogate models in aeroelastic optimization is also compared. The Kriging model is constructed more conveniently, and its predictive accuracy of the aeroelastic responses also satisfies the engineering requirements. According to the case of a high-aspect-ratio composite wing, the GA is better at global optimization.
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A Highly Efficient Aeroelastic Optimization Method Based on a Surrogate Model
Wan Zhiqiang,Wang Xiaozhe,Yang Chao 한국항공우주학회 2016 International Journal of Aeronautical and Space Sc Vol.17 No.4
This paper presents a highly efficient aeroelastic optimization method based on a surrogate model; the model is verified by considering the case of a high-aspect-ratio composite wing. Optimization frameworks using the Kriging model and genetic algorithm (GA), the Kriging model and improved particle swarm optimization (IPSO), and the back propagation neural network model (BP) and IPSO are presented. The feasibility of the method is verified, as the model can improve the optimization efficiency while also satisfying the engineering requirements. Moreover, the effects of the number of design variables and number of constraints on the optimization efficiency and objective function are analysed in detail. The accuracy of two surrogate models in aeroelastic optimization is also compared. The Kriging model is constructed more conveniently, and its predictive accuracy of the aeroelastic responses also satisfies the engineering requirements. According to the case of a high-aspect-ratio composite wing, the GA is better at global optimization.
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Lateral Load Distribution for Hollow Slab Bridge: Field Test Investigation
Yu Zhao,Xiaozhe Cao,Yongjun Zhou,Gangqiang Wang,Ruixin Tian 한국콘크리트학회 2020 International Journal of Concrete Structures and M Vol.14 No.3
Distribution factors (DFs) for one typical cross-section as specified in the AASHTO LRFD specification can be varied when the bridge parameters such as span length, loading lanes and skew are changed. The diversity between design and actual DFs may be varied as the bridge parameters changed. To study this diversity, this paper presents an evaluation of lateral load DFs for prefabricated hollow slab bridges. The response of the bridge was recorded during the field test. This field test was divided into two stages: a concentrated force loading test on the prefabricated girder that settled on the bridge supports before the girders were connected transversely and a vehicle loading test after the girders were connected transversely. The instruments used to record the response of the bridge were strain gauges and dial indicators. The measured data in the multi-stages of the field test could be used to calibrate the support condition of the bridge and transverse connection between adjacent girders in the finite element model (FEM) using beam and plate elements. From the FEM, DFs for this hollow slab bridge were determined and compared with the DFs in the AASHTO LRFD specification. A parametric study using the calibrated FEM was then used to investigate the effect of various parameters including span length, skew and bridge deck thickness on the DFs. It was found that AASHTO LRFD specification is conservative compared with the analysis in the FEM, while this conservatism decreased as the span length and skew of the hollow slab bridge increased.
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