乙肝病毒表面抗原基因转化番茄

将乙肝病毒表面抗原 (HBs Ag)基因与 Ca MV3 5 s启动子及 nos终止子构建植物表达载体 p1 3 0 1 HBs,直接法转入根癌农杆菌 EHA1 0 5 (Agrobacterium tumefaciens) ,以该菌株介导叶盘法转化番茄 ,得到抗潮霉素的再生植株 .抗性苗总 DNA经 PCR、Southern斑点杂交证实目的基因已整合到番茄基因组中 ,EILSA检测证明在番茄中正确表达了乙肝表面抗原蛋白

Community Discovery Algorithm with the Label Propagation Based on the Initial Division

采用标签传播算法进行社区发现时间效率高,无需人工参数,但容易产生精度限制的问题.研究了启发式的标签传播算法,快速地进行社区的初始划分,大量减少了初始标签的个数,进行标签迭代传播来修正初始划分得到最终的社区.理论分析和实验证明这种方法在不增加时间复杂度的情况下,提高了准确率,并有效消除了精度限制的现象.The label propagation algorithm for community discovery enjoys high time efficiency and does not need artificial parameters,but it is prone to the resolution-limit problem.A new heuristic label propagation algorithm is studied.The central idea lies in accelerating the initial division of the community first,obtaining a significant reduction in the number of initial tag,and then correcting the initial division to achieve the final divided societies by iteration of the label propagation.Theoretical analysis and experimental results show that the method improves the accuracy and effectively eliminates the phenomenon of resolution-limit problem without increasing the time complexity.国家自然科学基金(61373147); 福建省教育厅A类项目(JA13238); 厦门市科技计划项目(3502Z20133041); 厦门理工学院对外科技合作交流专项(E201301300

新疆天山自然遗产价值与保护管理研究

一、项目简要说明 该成果是新疆申报世界自然遗产研究的总结。本成果全面审视筛选了新疆世界自然遗产潜力区,分析了遗产潜力区的资源类型和空间格局,明确了遗产潜力区申报世界自然遗产的组合方式和优先次序,提出了新疆申报世界自然遗产战略,确定了新疆天山优先申报策略。针对新疆天山提名遗产地,全面调查了提名片区的动植物物种、植被类型以及具有美学价值的自然景观资源;全面系统研究了新疆天山自然遗产科学价值体系,揭示了新疆天山全球突出普遍价值,并通过全球对比,提出了符合世界遗产的标准;建立了基于“3S”技术的自然遗产边界完整性划分技术。通过对新疆天山遗产价值体系的全面研究,构建了遗产安全评估指标体系,确定..

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies