Zooplanktonic diversity in the western Pacific

西太平洋区是全球海洋生物种源中心,许多类群的最高物种多样性都出现于该区域,因此,在该区开展种类多样性的研究不仅重要和必要,而且具有在跨国尺度上进行综合管理和相互合作的迫切性。本文在西太平洋的浮游动物样品鉴定分类、编目、文献资料整理和分析的基础上,记录和编入西太平洋10个浮游动物类群2,658种(含亚种),隶属于206科675属,其中水螅水母类99科251属697种,栉水母类12科22属59种,浮游软体动物14科35属86种,介形类8科89属416种,桡足类51科156属908种,糠虾类4科58属202种,磷虾类2科8属56种,十足类8科22属105种,毛颚类5科8属48种,被囊类5科26属81种。The western Pacific region has been operating as a centre for the origin of marine biodiversity: the richest diversity of many marine taxa was found in these waters.Therefore,biodiversity research and con-servation efforts in this area are necessary in order to promote the integrative and international management of this resource.The present work is a compilation of numbers of all the families,genera and species of ma-jor taxa of zooplankton known in the western Pacific Ocean(106°–150°E,0°–44°N).In all,2,658 zooplank-tonic species(including subspecies) belonging to 206 families and 675 genera have been recorded from taxonomic identifications and literature,99 families,251 genera and 697 species belong to the Medusozoa,12 families,22 genera and 59 species to the Ctenophora,14 families,35 genera and 86 species to the pelagic Molluscs(Pteropoda and Heteropoda),8 families,89 genera and 416 species to the Ostracoda,51 families,156 genera and 908 species to the Copepoda,4 families,58 genera and 202 species to the Mysidcea,2 fami-lies,8 genera and 56 species to the Euphausiacea,8 families,22 genera and 105 species to the Decapoda,5 families,8 genera and 48 species to the Chaetognatha,5 families,26 genera and 81 species to the Tunicata.908专项“中国海洋生物种类名录和图谱”(908-ZC-II-02)和908专项海洋生物样品库;科技部基础工作专项“我国和邻近西北太平洋海洋生物物种编目和分布图集编制”(2006FY220700

柯萨奇病毒A组6型抗体中和试验Nt-ELISPOT方法的建立

目的建立快速、高效的柯萨奇病毒A组6型(CVA6)抗体中和试验Nt-ELISPOT检测法。方法取CVA6单克隆抗体(1D5)用HRP标记,以此为检测抗体,基于酶联免疫斑点检测技术(ELISPOT)建立CVA6抗体中和试验Nt-ELISPOT,通过对不同效价血清以及手足口病疑似患者血清标本的检测,比较该方法与传统抗体中和试验(NtCPE)的一致性。结果以CVA6单克隆抗体1D5为检测抗体,建立了快速检测针对CVA6中和抗体的Nt-ELISPOT检测法;该方法与Nt-CPE法相比,其检测时间显著缩短;运用这两种方法分别对4份不同效价血清样品及70份手足口病疑似患者血清样品进行CVA6抗体检测,其中和试验结果的一致性为100%。结论建立的Nt-ELISPOT方法快速、高效,可用于手足口病CVA6感染检测,为CVA6的疫苗免疫原性评价、血清流行病学调查等提供了技术支持。国家自然科学基金项目(No.31670933

自制CsI(Tl)晶体的光输出非均匀性

实验测试了中国科学院近代物理研究所制备的9根大尺寸闪烁晶体样品(40 mm×40 mm×300 mm)的光输出及其非均匀性。使用了多种光反射材料和包装方法对样品进行包装,对其光输出及其非均匀性进行测试。对实验数据进行分析,确定了大尺寸晶体的最佳读出端和包装方法。在测试中,所有CsI(Tl)闪烁晶体样品的光输出非均匀性均好于7%,部分样品可达到2%左右。结合本次实验结果,对影响CsI(Tl)晶体光输出非均匀性的因素进行了简要分析

1995～2011年CERN土壤环境元素含量数据集

土壤环境是地球环境的重要组成部分。目前土壤环境问题的关注重点在于土壤污染。我国土壤污染以无机污染为主。中国生态系统研究网络(Chinese Ecosystem Research Network,CERN)自1988年组建以来,在中国主要农田、森林、草原、荒漠、湿地生态系统中,按统一的规范,对与土壤环境状况有关的铁、锰、铜、锌、硼、钼、镉、铬、铅、镍、汞、砷、硒元素进行了长期定位监测。通过对CERN典型生态样地表层土壤环境元素监测数据进行加工处理,获得1995～2011年中国陆地生态系统土壤环境元素含量数据集。本数据集中13种土壤环境元素指标测定的相对误差平均为6.55%,重复测定的相对偏差为7.70%。同时附有完整的背景信息,保证了数据在空间和时间上的一致性。本数据集可以为全国和区域土壤环境质量评估、土壤污染风险评价以及环境土壤学研究等工作提供数据基础

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

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

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