一种自适应低损耗三维有源光网络结构设计

针对三维有源光网络路径配置时间长、光路由器插入损耗大和网络硬件开销高等问题,文章设计了自适应路由算法和无阻塞、低损耗光路由器。自适应路由算法利用XYZ确定路由算法进行端口的初次判断,再根据端口阻塞情况进行二次判断,最终选择无阻塞和距离短的端口作为节点输出端口;针对三维通信需求分别设计层内6端口和层间3端口光路由器代替7端口光路由器。实验结果表明,利用自适应路由算法进行路由计算时,路径建立过程延迟小、阻塞低,光路由器所需波导和微环谐振器数量少、插入损耗低,平均插入损耗仅为0.88 dB,光网络硬件开销低

基于微流控的海洋监测技术

In the process of recognizing the laws of the ocean, developing the marine economy, protecting and restoring the marine ecological environment, marine analysis and monitoring are essential technologies. Modern ocean monitoring presents the characteristics of in-situ, on-site, and comprehensive, and requires analysis and monitoring equipment to be small, sensitive, rapid, and automated. Microfluidic chip technology, with its outstanding characteristics of micro channel control, low-cost, and high throughput, combined with advanced chemical analysis methods, has shown excellent prospects in the construction of core sensing components of marine analysis and monitoring equipment. In this review, starting from the manufacture of microfluidic chips and the construction of analysis methods, the typical objects of marine monitoring were classified, involving pH, dissolved oxygen, nutrients, heavy metals, organic pollutants and marine microorganisms. The progress of application research in monitoring was reviewed, and its future development was prospected

博斯腾湖细菌丰度时空分布及其与环境因子的关系/Spatiotemporal dynamics of bacterial abundance and related environmental parameters in Lake Bosten[J]

于2010年6月-2011年6月在新疆博斯腾湖共进行了9次采样,获得了140份样品,采用表面荧光显微镜直接计数法及广义可加模型(Generalized Additive Models,GAM)研究了表层水体中细菌丰度的时空分布规律及其与环境因子的关系.结果表明博斯腾湖细菌丰度平均值为(1.48±0.95)×106个/mL;细菌丰度季节差异显著,夏季最高(2.05×106个/mL),冬季最低(3.81×105个/mL).在大湖区,春季和冬季细菌丰度最大值均位于湖区中部,冬季细菌丰度由湖区中部向东南、西南逐渐减少.夏季和秋季细菌丰度分布与春季大致相反,湖区中部较低,西北部较高.GAM分析结果表明,温度、溶解性有机碳(DOC)、叶绿素a、电导率、浊度等5个环境因子对细菌丰度总偏差解释率为81.2％,其中温度贡献最大,贡献率为63.3％,DOC、叶绿素a和电导率,贡献率分别为12.5％、2.7％和1.7％;浊度对偏差的解释率仅为1.0％.在温度超过22℃时,影响博斯腾湖细菌丰度空间分布的主要因子是DOC

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