Browsing by Author "Li, Lei"

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    An arbitrary Lagrangian-Eulerian method for simulating interfacial dynamics between a hydrogel and a fluid
    Li, Lei; Zhang, Jiaqi; Xu, Zelai; Young, Y. -N.; Feng, James J.; Yue, Pengtao (Academic Press/Elsevier, 2022-02-15)
    Hydrogels are crosslinked polymer networks swollen with an aqueous solvent, and play central roles in biomicrofluidic devices. In such applications, the gel is often in contact with a flowing fluid, thus setting up a fluid-hydrogel two-phase system. Using a recently proposed model (Young et al. [41] 2019), we treat the hydrogel as a poroelastic material consisting of a Saint Venant-Kirchhoff polymer network and a Newtonian viscous solvent, and develop a finite-element method for computing flows involving a fluid-hydrogel interface. The interface is tracked by using a fixed-mesh arbitrary Lagrangian-Eulerian method that maps the interface to a reference configuration. The interfacial deformation is coupled with the fluid and solid governing equations into a monolithic algorithm using the finite-element library deal.II. The code is validated against available analytical solutions in several non-trivial flow problems: one-dimensional compression of a gel layer by a uniform flow, two-layer shear flow, and the deformation of a Darcy gel particle in a planar extensional flow. In all cases, the numerical solutions are in excellent agreement with the analytical solutions. Numerical tests show second-order convergence with respect to mesh refinement, and first-order convergence with respect to time-step refinement.
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    Drivers of a habitat shift by critically endangered Siberian cranes: Evidence from long-term data
    Hou, Jinjin; Liu, Yifei; Fraser, James D.; Li, Lei; Zhao, Bin; Lan, Zhichun; Jin, Jiefeng; Liu, Guanhua; Dai, Nianhua; Wang, Wenjuan (2020-09)
    Many waterbird populations have become increasingly dependent on agricultural habitats for feeding. While habitat destruction has been proposed as a key reason forcing waterbirds to move from natural habitats to agricultural habitats, few have used long-term data to test this hypothesis. The Siberian crane (Leucogeranus leucogeranus) is an IUCN Critically Endangered species. About 98% of its global population winters at Poyang Lake, China. Recently, many cranes shifted from feeding in natural wetlands to agricultural habitats. Here, we integrate bird surveys,Vallisneriatuber (the traditional food of cranes in natural wetlands) surveys, water level data, and remotely sensed images from 1999 to 2016 to explore the drivers of this habitat shift. Changes in Siberian crane numbers in natural wetlands and agricultural fields indicated that the habitat shift occurred in the winters of 2015-2016. Analyses using generalized linear mixed models suggested that crane numbers in natural wetlands were positively related to tuber density and the interaction between dry season (October-March) water level and tuber density. The changes in tuber density and dry season water level in 2015-2016 indicated that tuber disappearance may have been the primary driver of the habitat shift, with a smaller effect of high water level. Submerged plants at Poyang Lake have degraded seriously in the past two decades. The plant degradation at Shahu Lake, a sublake of Poyang Lake, may have been caused by high spring water, high winter temperature, and low summer temperature. However, the drivers of tuber disappearance at Poyang Lake may not be restricted to these variables. Because Poyang Lake is an important refuge for many waterbirds in the Yangtze River floodplain, it is urgent to take effective measures to restore its submerged plants and ecosystem health. Agricultural fields can be important refuges for Siberian cranes, mitigating the negative impacts of wetland deterioration.
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    Measurement of the B0 lifetime and flavor-oscillation frequency using hadronic decays reconstructed in 2019-2021 Belle II data
    Ablikim, M.; Achasov, M. N.; Adlarson, P.; Ahmed, S.; Albrecht, M.; Amoroso, A.; An, Q.; Bai, X. H.; Bai, Y.; Bakina, O.; Ferroli, R. Baldini; Balossino, I.; Ban, Y.; Begzsuren, K.; Bennett, J.; Berger, N.; Bertani, M.; Bettoni, D.; Bianchi, F.; Biernat, J.; Bloms, J.; Bortone, A.; Boyko, I.; Briere, R. A.; Cai, H.; Cai, X.; Calcaterra, A.; Cao, G. F.; Cao, N.; Cetin, S. A.; Chang, J. F.; Chang, W. L.; Chelkov, G.; Chen, D. Y.; Chen, G.; Chen, H. S.; Chen, M. L.; Chen, S. J.; Chen, X. R.; Chen, Y. B.; Cheng, W.; Cibinetto, G.; Cossio, F.; Cui, X. F.; Dai, H. L.; Dai, J. P.; Dai, X. C.; Dbeyssi, A.; de Boer, R. B.; Dedovich, D.; Deng, Z. Y.; Denig, A.; Denysenko, I.; Destefanis, M.; De Mori, F.; Ding, Y.; Dong, C.; Dong, J.; Dong, L. Y.; Dong, M. Y.; Du, S. X.; Fang, J.; Fang, S. S.; Fang, Y.; Farinelli, R.; Fava, L.; Feldbauer, F.; Felici, G.; Feng, C. Q.; Fritsch, M.; Fu, C. D.; Fu, Y.; Gao, X. L.; Gao, Y.; Gao, Y.; Gao, Y. G.; Garzia, I.; Gersabeck, E. M.; Gilman, A.; Goetzen, K.; Gong, L.; Gong, W. X.; Gradl, W.; Greco, M.; Gu, L. M.; Gu, M. H.; Gu, S.; Gu, Y. T.; Guan, C. Y.; Guo, A. Q.; Guo, L. B.; Guo, R. P.; Guo, Y. P.; Guskov, A.; Han, S.; Han, T. T.; Han, T. Z.; Hao, X. Q.; Harris, F. A.; He, K. L.; Heinsius, F. H.; Held, T.; Heng, Y. K.; Himmelreich, M.; Holtmann, T.; Hou, Y. R.; Hou, Z. L.; Hu, H. M.; Hu, J. F.; Hu, T.; Hu, Y.; Huang, G. S.; Huang, L. Q.; Huang, X. T.; Huesken, N.; Hussain, T.; Andersson, W. Ikegami; Imoehl, W.; Irshad, M.; Jaeger, S.; Ji, Q.; Ji, Q. P.; Ji, X. B.; Ji, X. L.; Jiang, H. B.; Jiang, X. S.; Jiang, X. Y.; Jiao, J. B.; Jiao, Z.; Jin, S.; Jin, Y.; Johansson, T.; Kalantar-Nayestanaki, N.; Kang, X. S.; Kappert, R.; Kavatsyuk, M.; Ke, B. C.; Keshk, I. K.; Khoukaz, A.; Kiese, P.; Kiuchi, R.; Kliemt, R.; Koch, L.; Kolcu, O. B.; Kopf, B.; Kuemmel, M.; Kuessner, M.; Kupsc, A.; Kurth, M. G.; Kuehn, W.; Lane, J. J.; Lange, J. S.; Larin, P.; Lavezzi, L.; Leithoff, H.; Lellmann, M.; Lenz, T.; Li, C.; Li, C. H.; Li, Cheng; Li, D. M.; Li, F.; Li, G.; Li, H. B.; Li, H. J.; Li, J. L.; Li, J. Q.; Li, Ke; Li, L. K.; Li, Lei; Li, P. L.; Li, P. R.; Li, W. D.; Li, W. G.; Li, X. H.; Li, X. L.; Li, Z. B.; Li, Z. Y.; Liang, H.; Liang, H.; Liang, Y. F.; Liang, Y. T.; Liao, L. Z.; Libby, J.; Lin, C. X.; Liu, B.; Liu, B. J.; Liu, C. X.; Liu, D.; Liu, D. Y.; Liu, F. H.; Liu, Fang; Liu, Feng; Liu, H. B.; Liu, H. M.; Liu, Huanhuan; Liu, Huihui; Liu, J. B.; Liu, J. Y.; Liu, K.; Liu, K. Y.; Liu, Ke; Liu, L.; Liu, L. Y.; Liu, Q.; Liu, S. B.; Liu, T.; Liu, X.; Liu, Y. B.; Liu, Z. A.; Liu, Zhiqing; Long, Y. F.; Lou, X. C.; Lu, H. J.; Lu, J. D.; Lu, J. G.; Lu, X. L.; Lu, Y.; Lu, Y. P.; Luo, C. L.; Luo, M. X.; Luo, P. W.; Luo, T.; Luo, X. L.; Lusso, S.; Lyu, X. R.; Ma, F. C.; Ma, H. L.; Ma, L. L.; Ma, M. M.; Ma, Q. M.; Ma, R. Q.; Ma, R. T.; Ma, X. N.; Ma, X. X.; Ma, X. Y.; Ma, Y. M.; Maas, F. E.; Maggiora, M.; Maldaner, S.; Malde, S.; Malik, Q. A.; Mangoni, A.; Mao, Y. J.; Mao, Z. P.; Marcello, S.; Meng, Z. X.; Messchendorp, J. G.; Mezzadri, G.; Min, T. J.; Mitchell, R. E.; Mo, X. H.; Mo, Y. J.; Muchnoi, N. Yu; Muramatsu, H.; Nakhoul, S.; Nefedov, Y.; Nerling, F.; Nikolaev, I. B.; Ning, Z.; Nisar, S.; Olsen, S. L.; Ouyang, Q.; Pacetti, S.; Pan, Y.; Pan, Y.; Papenbrock, M.; Pathak, A.; Patteri, P.; Pelizaeus, M.; Peng, H. P.; Peters, K.; Pettersson, J.; Ping, J. L.; Ping, R. G.; Pitka, A.; Poling, R.; Prasad, V.; Qi, H.; Qi, M.; Qi, T. Y.; Qian, S.; Qiao, C. F.; Qin, L. Q.; Qin, X. P.; Qin, X. S.; Qin, Z. H.; Qiu, J. F.; Qu, S. Q.; Rashid, K. H.; Ravindran, K.; Redmer, C. F.; Rivetti, A.; Rodin, V.; Rolo, M.; Rong, G.; Rosner, Ch; Rump, M.; Sarantsev, A.; Savrie, M.; Schelhaas, Y.; Schnier, C.; Schoenning, K.; Shan, W.; Shan, X. Y.; Shao, M.; Shen, C. P.; Shen, P. X.; Shen, X. Y.; Shi, H. C.; Shi, R. S.; Shi, X.; Shi, X. D.; Song, J. J.; Song, Q. Q.; Song, Y. X.; Sosio, S.; Spataro, S.; Sui, F. F.; Sun, G. X.; Sun, J. F.; Sun, L.; Sun, S. S.; Sun, T.; Sun, W. Y.; Sun, Y. J.; Sun, Y. K.; Sun, Y. Z.; Sun, Z. T.; Tan, Y. X.; Tang, C. J.; Tang, G. Y.; Thoren, V.; Tsednee, B.; Uman, I.; Wang, B.; Wang, B. L.; Wang, C. W.; Wang, D. Y.; Wang, H. P.; Wang, K.; Wang, L. L.; Wang, M.; Wang, M. Z.; Wang, Meng; Wang, W. P.; Wang, X.; Wang, X. F.; Wang, X. L.; Wang, Y.; Wang, Y.; Wang, Y. D.; Wang, Y. F.; Wang, Y. Q.; Wang, Z.; Wang, Z. Y.; Wang, Ziyi; Wang, Zongyuan; Weber, T.; Wei, D. H.; Weidenkaff, P.; Weidner, F.; Wen, H. W.; Wen, S. P.; White, D. J.; Wiedner, U.; Wilkinson, G.; Wolke, M.; Wollenberg, L.; Wu, J. F.; Wu, L. H.; Wu, L. J.; Wu, Z.; Xia, L.; Xiao, S. Y.; Xiao, Y. J.; Xiao, Z. J.; Xie, Y. G.; Xie, Y. H.; Xing, T. Y.; Xiong, X. A.; Xu, G. F.; Xu, J. J.; Xu, Q. J.; Xu, W.; Xu, X. P.; Yan, L.; Yan, W. B.; Yan, W. C.; Yang, H. J.; Yang, H. X.; Yang, L.; Yang, R. X.; Yang, S. L.; Yang, Y. H.; Yang, Y. X.; Yang, Yifan; Yang, Zhi; Ye, M.; Ye, M. H.; Yin, J. H.; You, Z. Y.; Yu, B. X.; Yu, C. X.; Yu, G.; Yu, J. S.; Yu, T.; Yuan, C. Z.; Yuan, W.; Yuan, X. Q.; Yuan, Y.; Yue, C. X.; Yuncu, A.; Zafar, A. A.; Zeng, Y.; Zhang, B. X.; Zhang, Guangyi; Zhang, H. H.; Zhang, H. Y.; Zhang, J. L.; Zhang, J. Q.; Zhang, J. W.; Zhang, J. Y.; Zhang, J. Z.; Zhang, Jianyu; Zhang, Jiawei; Zhang, L.; Zhang, Lei; Zhang, S.; Zhang, S. F.; Zhang, T. J.; Zhang, X. Y.; Zhang, Y.; Zhang, Y. H.; Zhang, Y. T.; Zhang, Yan; Zhang, Yao; Zhang, Yi; Zhang, Z. H.; Zhang, Z. Y.; Zhao, G.; Zhao, J.; Zhao, J. Y.; Zhao, J. Z.; Zhao, Lei; Zhao, Ling; Zhao, M. G.; Zhao, Q.; Zhao, S. J.; Zhao, Y. B.; Zhao, Z. G.; Zhemchugov, A.; Zheng, B.; Zheng, J. P.; Zheng, Y.; Zheng, Y. H.; Zhong, B.; Zhong, C.; Zhou, L. P.; Zhou, Q.; Zhou, X.; Zhou, X. K.; Zhou, X. R.; Zhu, A. N.; Zhu, J.; Zhu, K.; Zhu, K. J.; Zhu, S. H.; Zhu, W. J.; Zhu, X. L.; Zhu, Y. C.; Zhu, Z. A.; Zou, B. S.; Zou, J. H. (American Physical Society, 2023-05-15)
    We measure the B0 lifetime and flavor-oscillation frequency using B0→D(∗)-π+ decays collected by the Belle II experiment in asymmetric-energy e+e- collisions produced by the SuperKEKB collider operating at the ϒ(4S) resonance. We fit the decay-time distribution of signal decays, where the initial flavor is determined by identifying the flavor of the other B meson in the event. The results, based on 33000 signal decays reconstructed in a data sample corresponding to 190 fb-1, are τB0=(1.499±0.013±0.008) ps, Δmd=(0.516±0.008±0.005) ps-1, where the first uncertainties are statistical and the second are systematic. These results are consistent with the world-average values.