Determination of Phenolic Endocrine Disrupting Chemicals in Human Urine by High Performance Liquid Chromatography Tandem Electrospray Ionization Mass Spectrometry

采用通用电喷雾离子源的高效液相色谱-串联质谱(HPlC-ESI MS/MS)分析技术,通过丹磺酰氯衍生化处理,建立了同时测定人尿液中双酚A(bPA)、三氯生(TCS)、炔雌酮(EE2)、雌酮(E1)、雌二醇(E2)5种酚类内分泌干扰物的高灵敏方法。5种酚类化合物在0.2~100μg/l质量浓度范围内线性关系良好,相关系数(r2)均在0.99以上,检出限(lOd)在0.02~0.27μg/l之间。在5、10、50μg/l加标水平下,平均回收率为85%~125%,相对标准偏差(rSd,n=3)为0.53%~14.4%。该方法灵敏度高、重现性好、回收率高、操作简单,可作为人尿液中酚类内分泌干扰物暴露分析的备选方法之一。A high performance liquid chromatography tandem electrospray ionization mass spectrometry(HPLC-ESI MS/MS) method was developed and validated for the determination of phenolic endocrine disrupting chemicals(EDCs),including bisphenol A(BPA),triclosan(TCS),17α-ethynylestradiol(EE2),estrone(E1) and 17 β-estradiol(E2)in human urine.The samples were purified by liquid-liquid extraction,derivertized with dansyl chloride,and detected by HPLC-ESI MS/MS.The target compounds were quantified by the stable isotope dilution technique.The calibration curve were linear in the range of 0.2-100 μg/L for the 5 EDCs with correlation coefficients more than 0.99.The limits of detection of 5 EDCs were in the range of 0.02-0.27 μg/L.The matrix recoveries of the method for 5 EDCs at three spiked levels of 5,10 and 50 μg/L ranged from 85% to 125%.The relative standard deviations(RSDs,n=3) were between 0.53% and 14.4%.The method was successfully applied in the analysis of 5 EDCs in human urine with its sensitivity and accurancy.中科院“百人计划”项目; 厦门市科技计划项目(3502Z20122003

Mechanism of Self discharge Performance Improvement in the Ni-MH Batteries with NaOH Electrolyte

以NaOH电解液代替KOH能够明显改善MH/N i电池的自放电性能和高温(60℃)充电效率.电化学阻抗和循环伏安测试表明,NaOH电解液的作用可能是改变了H原子于负极表面的吸(脱)附行为,并在一定程度上抑制了负极的析氢过程,从而改善了电池的自放电性能.The self-discharge performance and charge efficiency at 60 ℃ for Ni-MH battery can be markedly enhanced by using NaOH electrolyte instead of KOH electrolyte.Both the results of electrochemical impedance spectroscopy and cyclic voltammetry tests indicate that the separation of H_2 from the negative electrode may be partly blocked in the former because of the change of the adsorption/desorption behavior of H on the surface of the negative electrode,thus results in an improvement of self-discharge performance of the battery.作者联系地址：郑州轻工业学院材料与化工学院,郑州轻工业学院材料与化工学院,郑州轻工业学院材料与化工学院,郑州轻工业学院材料与化工学院 河南郑州450002,河南郑州450002,河南郑州450002,河南郑州450002Author's Address: *,XIA Tong-chi,DONG Hui-chao,WEI Yan-weiDepartment of Material and Chemical Engineering,Zhengzhou University of Light Industry,Zhengzhou 450002,Henan,Chin

智能传感器主动协同的变电站机器人智能巡检系统及方法

本发明提供了一种智能传感器主动协同的变电站机器人智能巡检系统及方法，本发明巡检系统包括：智能机器人协同巡检层、自主协同层和变电站智能传感层形成三层智能巡检架构。本发明巡检系统中，巡检机器人进行自主路径规划完成图像数据采集，智能传感器感知被检测设备的状态并进行数据预处理和分析，巡检机器人和智能传感器通过近场通信机制和智能执行器进行主动协同，协同服务器基于巡检机器人感知数据进行复杂场景识别，以及对巡检机器人感知数据和智能传感器感知数据进行多源数据融合分析。显著的提升了巡视的及时性，避免操作过程的人员安全风险.减少巡检时的人工干预，保证变电巡视任务顺利进行

中国被子植物濒危等级的评估

本文基于文献和标本信息收集以及专家提供的数据,运用IUCN濒危物种红色名录方法首次对中国范围内所有已知被子植物进行灭绝风险评估。结果显示,在评估的30,068种被子植物中,灭绝等级(含灭绝、野外灭绝、地区灭绝)共计40种;受威胁等级(极危、濒危、易危)3,363种,受威胁比例为11.18%。从空间分布看,我国受威胁被子植物主要集中分布在西南地区以及台湾、海南等岛屿,且主要分布在中低海拔地区。对受威胁物种的分析结果表明,包括原生植被破坏在内的生境丧失及破碎化是我国被子植物濒危的首要因子,涉及约84.1%的受威胁物种;过度采挖和物种内在系统问题位列致危因子的第二、三位,分别涉及38%和14%的物种。其他的致危因子包括外来入侵种在内的种间竞争、环境污染、自然灾害和全球气候变化等。一个物种的致危因子往往是多方面的。本次评估与2004年红色名录相比,生境变化、实施保护措施及分类学新修订使一些物种的濒危等级发生了变化,这也印证了红色名录是一个动态的系统,需要根据最新信息进行更新,以便为生物多样性保护提供实时准确的基础数据

中国高等植物受威胁物种名录

2008年,环境保护部和中国科学院联合启动了《中国生物多样性红色名录——高等植物卷》的编制工作。通过这项工作,我们依据IUCN濒危物种红色名录标准对中国野生高等植物的濒危状况进行了全面评估,编制了中国高等植物红色名录。2013年9月,该名录以环境保护部、中国科学院第54号公告形式发布,即《中国生物多样性红色名录—

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