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本文开发了一种新型的方舱夹芯板用室温固化高强度环氧结构胶黏剂,验证了其物化特性、相关力学性能和环境适应性。结果表明此胶黏剂具有优良性能,可以满足方舱用大板胶黏剂的使用需求。 相似文献
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Nianxiu Duan Junjun Li Sha Song Feng Wang Yiwei Yang Di Nie Caifen Wang Yingjie Sheng Yali Tao Jie Gao Can Xu Yan Wei Yong Gan 《Advanced functional materials》2021,31(46):2100605
Tumor-specific enhanced delivery of chemotherapeutics and modulators to tumor cells and activated pancreatic stellate cells (aPSCs), respectively, represents safer and more effective therapy for pancreatic cancer. Herein, a membrane type 1-matrix metalloproteinase (MT1-MMP)-cleavable spacer is used to assemble low-density cRGDfK onto thermosensitive liposomes loaded with phosphorylated calcipotriol (PCAL) and doxorubicin (DOX), yielding MR-T-PD. The liposome-linked cRGDfK prodrug on MR-T-PD surface is first activated by MT1-MMP, which is selectively expressed on tumor endothelial cells, to release cRGDfK. The free cRGDfK specifically promotes tumor angiogenesis, leading to 3.4-fold higher accumulation and a wider distribution of MR-T-PD in tumors. Furthermore, MR-T-PD rapidly releases PCAL and DOX into the interstitium under heat treatment. The released DOX enters tumor cells to induce apoptosis, whereas the PCAL prodrug is converted to CAL by alkaline phosphatase on the surface of aPSCs; CAL can then enter aPSCs to induce quiescence and promote the antitumor effect of DOX. Finally, by enhancing the exposure of DOX and CAL to tumor cells and aPSCs, respectively, in a tumor-specific manner, MR-T-PD exerts superior efficacy (a 5.9-fold decrease in tumor weight) without causing additional side effects. Overall, this prodrug-based smart liposome system represents a promising paradigm for pancreatic cancer therapy. 相似文献
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Matteo Di Giosia Alice Soldà Markus Seeger Andrea Cantelli Fabio Arnesano Maria I. Nardella Vincenzo Mangini Francesco Valle Marco Montalti Francesco Zerbetto Stefania Rapino Matteo Calvaresi Vasilis Ntziachristos 《Advanced functional materials》2021,31(20):2101527
Fullerenes are candidates for theranostic applications because of their high photodynamic activity and intrinsic multimodal imaging contrast. However, fullerenes suffer from low solubility in aqueous media, poor biocompatibility, cell toxicity, and a tendency to aggregate. C70@lysozyme is introduced herein as a novel bioconjugate that is harmless to a cellular environment, yet is also photoactive and has excellent optical and optoacoustic contrast for tracking cellular uptake and intracellular localization. The formation, water-solubility, photoactivity, and unperturbed structure of C70@lysozyme are confirmed using UV-visible and 2D 1H, 15N NMR spectroscopy. The excellent imaging contrast of C70@lysozyme in optoacoustic and third harmonic generation microscopy is exploited to monitor its uptake in HeLa cells and lysosomal trafficking. Last, the photoactivity of C70@lysozyme and its ability to initiate cell death by means of singlet oxygen (1O2) production upon exposure to low levels of white light irradiation is demonstrated. This study introduces C70@lysozyme and other fullerene-protein conjugates as potential candidates for theranostic applications. 相似文献
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实施独立计量分区(district metered area,DMA)是辅助供水管网管理和漏损识别的重要手段.图划分算法是进行DMA分区的方法之一,常规图划分算法应用中,存在解空间受限、分区后原水流状态易发生较大改变、形成较多串联分区(对流量计算不利)的缺点.在常规图划分算法基础上进行了改进:粗化阶段按照特定规则匹配、合并非输水干管两端的节点,形成简化的管网拓扑结构;分区阶段得到管网初步分区方案;细化阶段提出基于贪心算法、枚举算法、蒙特卡洛算法的分区调整方法,结合改进的仪表安置方法、水力模拟、优劣解距离法(technique for order preference by similarity to an ideal solution,TOPSIS),对分区方案进行调整.将该方法应用于YX市供水管网,成功进行了分区. 相似文献
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Xinyu TONG Ziao YU Xiaohua TIAN Houdong GE Xinbing WANG 《Frontiers of Computer Science》2022,16(1):161310
Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice. 相似文献
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