中国鼠疫自然疫源地分型研究Ⅶ.中国鼠疫自然疫源地分型生物学特征/Ecological-geographic landscapes of natural plague foci in China Ⅶ.Typing of natural plague foci[J]

目的 研究中国鼠疫自然疫源地分型.方法 根据中国鼠疫自然疫源地鼠疫生态地理景观学、鼠疫耶尔森菌基因组学、鼠疫宿主动物学、鼠疫媒介昆虫学特征,提出“鼠疫生物地理群落指征、两级分型法和三项指征命名法”；区划中国鼠疫自然疫源地型及其亚型.结果 中国鼠疫自然疫源地分为12型19亚型.阐明中国鼠疫自然疫源地生物学特征.结论 中国鼠疫自然疫源地型及其亚型的划分,为掌握其生物学基本规律奠定基础

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