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| 1 | Emergency logistics scheduling with multiple supply-demand points based on grey interval显示文摘This study aimed to address the problem of post-disaster emergency material dispatching from multiple supply points to multiple demand points.In large-scale natural disasters,it is very important for multiple emergency material supply points to serve as sources of materials for multiple disaster sites and to determine emergency material scheduling solutions accurately.Furthermore,the quantity of emergency materials required at each disaster site is uncertain.To address this issue,in this study,we developed an emergency material scheduling model with multiple logistics supply points for multiple demand points based on the grey interval numbers.To optimize the proposed multi-supply-point and multi-demand-point emergency material scheduling mode,a multi-objective optimization algorithm based on a genetic algorithm was used.Experimental results demonstrate that the multi-objective optimization method can solve the emergency logistics scheduling problem better than the particle swarm optimization multi-objective solution algorithm.Additionally,the multi-supply point and multi-demand point emergency material dispatch model and optimization algorithm provides robust support for emergency management system decision-makers when they need to respond quickly to disaster relief activities. | Zhiming Ding Xinrun Xu Shan Jiang Jin Yan Yanbo Han | 2022 | Journal of Safety Science and Resilience2022，3，2： | 5 |
| 2 | 3D-printed strontium-incorporatedβ-TCP bioceramic triply periodic minimal surface scaffolds with simultaneous high porosity,enhanced strength,and excellent bioactivity显示文摘In bone tissue engineering,scaffolds with excellent mechanical and bioactive properties play prominent roles in space maintaining and bone regeneration,attracting increasingly interests in clinical practice.In this study,strontium-incorporatedβ-tricalcium phosphate(β-TCP),named Sr-TCP,bioceramic triply periodic minimal surface(TPMS)structured scaffolds were successfully fabricated by digital light processing(DLP)-based 3D printing technique,achieving high porosity,enhanced strength,and excellent bioactivity.The Sr-TCP scaffolds were first characterized by element distribution,macrostructure and microstructure,and mechanical properties.Notably,the compressive strength of the scaffolds reached 1.44 MPa with porosity of 80%,bringing a great mechanical breakthrough to porous scaffolds.Furthermore,the Sr-TCP scaffolds also facilitated osteogenic differentiation of mouse osteoblastic cell line(MC3T3-E1)cells in both gene and protein aspects,verified by alkaline phosphatase(ALP)activity and polymerase chain reaction(PCR)assays.Overall,the 3D-printed Sr-TCP bioceramic TPMS structured scaffolds obtained high porosity,boosted strength,and superior bioactivity at the same time,serving as a promising approach for bone regeneration. | Yanbo Shan Yang Bai Shuo Yang Qing Zhou Gang Wang Biao Zhu Yiwen Zhou Wencan Fang Ning Wen Rujie He Lisheng Zhao | 2023 | Journal of Advanced Ceramics2023，12，9： | 0 |
| 3 | An Internet of Things based scalable framework for disaster data management显示文摘In recent years, undesirable disasters attacked the cities frequently, leaving heavy casualties and serious economiclosses. Meanwhile, disaster detection based on the Internet of Things(IoT) has become a hot spot that benefitedfrom the established development of smart city construction. And the IoT is visibly sensitive to the managementand monitoring of disasters, but massive amounts of monitoring data have brought huge challenges to datastorage and data analysis. This article develops a new and much more general framework for disaster emergencymanagement under the IoT environment. The framework is a bottom-up integration of highly scalable Raw DataStorages(RD-Stores) technology, hybrid indexing and queries technology, and machine learning technology foremergency disasters. Experimental results show that hybrid index and query technology have better performanceunder the condition of supporting multi-modal retrieval, and providing a better solution to offer real-time retrievalfor the massive sensor sampling data in the IoT. In addition, further works to evaluate the top-level sub-applicationsystem in this framework were performed based on the GPS trajectory data of 35,000 Beijing taxis and thevolumetric ground truth data of 7,500 images. The results show that the framework has desirable scalability andhigher utility. | Zhiming Ding Shan Jiang Xinrun Xu Yanbo Han | 2022 | Journal of Safety Science and Resilience2022，3，2： | 0 |
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