台风灾害下海岸带城市社会-生态系统脆弱性评估:大数据视角

2016年莫兰蒂台风对厦门城市社会-生态系统造成重创,该系统在灾害影响下的脆弱性成为亟待研究的重要问题。基于新浪微博平台进行大数据挖掘,结合统计年鉴及空间基础数据,建立台风灾害影响下基于暴露-敏感-应对-恢复力体系的海岸带城市社会-生态系统脆弱性指标体系,评估灾前灾后台风对厦门不同地区的影响;同时根据微博大数据的定位信息,对不同受灾信息进行灾情跟踪及分析,结果表明,在本次台风灾害中思明、湖里区表现出的脆弱性较低,而海沧、集美区表现出的脆弱性较高,主要是由于思明、湖里区的应对能力明显高于其他各区,从大数据显示的恢复情况来看,除海沧区外,其他三区在电力方面的恢复速度都较为迅速。研究成果能够为台风灾害背景下的城市脆弱性评价提供新的方法与技术,为灾前防治、灾后恢复提供决策参考。国家重点研发计划（２０１６ＹＦＣ０５０２９０４）；厦门大学大学生创新创业训练计划项目（１０３８４２０１７１０３

台风灾害下海岸带城市社会-生态系统脆弱性评估——大数据视角

2016年莫兰蒂台风对厦门城市社会-生态系统造成重创,该系统在灾害影响下的脆弱性成为亟待研究的重要问题。基于新浪微博平台进行大数据挖掘,结合统计年鉴及空间基础数据,建立台风灾害影响下基于暴露-敏感-应对-恢复力体系的海岸带城市社会-生态系统脆弱性指标体系,评估灾前灾后台风对厦门不同地区的影响;同时根据微博大数据的定位信息,对不同受灾信息进行灾情跟踪及分析,结果表明,在本次台风灾害中思明、湖里区表现出的脆弱性较低,而海沧、集美区表现出的脆弱性较高,主要是由于思明、湖里区的应对能力明显高于其他各区,从大数据显示的恢复情况来看,除海沧区外,其他三区在电力方面的恢复速度都较为迅速。研究成果能够为台风灾害背景下的城市脆弱性评价提供新的方法与技术,为灾前防治、灾后恢复提供决策参考。国家重点研发计划(2016YFC0502904)厦门大学大学生创新创业训练计划项目(103842017103

台风灾害下海岸带城市社会-生态系统脆弱性评估——大数据视角

2016年莫兰蒂台风对厦门城市社会-生态系统造成重创,该系统在灾害影响下的脆弱性成为亟待研究的重要问题。基于新浪微博平台进行大数据挖掘,结合统计年鉴及空间基础数据,建立台风灾害影响下基于暴露-敏感-应对-恢复力体系的海岸带城市社会-生态系统脆弱性指标体系,评估灾前灾后台风对厦门不同地区的影响;同时根据微博大数据的定位信息,对不同受灾信息进行灾情跟踪及分析,结果表明,在本次台风灾害中思明、湖里区表现出的脆弱性较低,而海沧、集美区表现出的脆弱性较高,主要是由于思明、湖里区的应对能力明显高于其他各区,从大数据显示的恢复情况来看,除海沧区外,其他三区在电力方面的恢复速度都较为迅速。研究成果能够为台风灾害背景下的城市脆弱性评价提供新的方法与技术,为灾前防治、灾后恢复提供决策参考。国家重点研发计划(2016YFC0502904)厦门大学大学生创新创业训练计划项目(103842017103

Prediction of Energy Resolution in the JUNO Experiment

International audienceThis paper presents the energy resolution study in the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The study reveals an energy resolution of 2.95% at 1 MeV. Furthermore, the study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data taking. Moreover, it provides a guideline in comprehending the energy resolution characteristics of liquid scintillator-based detectors

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