Advance in new determination methods for pesticide residues

第一作者简介：王兆守（1972—），男，博士，讲师。研究方向为有机 污染物的生物降解。电话 0592–2186195；E–mail [email protected]。 联系人：王兆守。[中文文摘]介绍了农药残留检测的步骤与方法。农药残留检测主要分为4个步骤:样品的提取、净化、浓缩和检测。提取方法主要有震荡法、索式提取法、固相微萃取法、超临界流体萃取法、快速溶剂萃取法等。净化方法主要有:液-液分配净化法、柱层析法、磺化法等。浓缩方法主要有:蒸发浓缩、反渗透浓缩、K-D浓缩仪浓缩等。检测方法主要有:气相色谱-质谱联用法、荧光分析法、酶抑制法、免疫分析法、生物传感器检测法、红外光谱法、拉曼光谱法等。评述了这些方法的优点与缺陷,提出了今后的发展方向。[英文文摘]The determination of residual pesticides is mainly divided into four processes:extraction,cleanup,concentration and detection. The methods for extracting samples include shaking extraction,soxhlet’s extraction,solid phase micro-extraction,supercritical fluid extraction，accelerated solvent extraction and so on. The cleanup methods include liquid-liquid partition process,column chromatography,sulfonation and so on. The concentration methods include evaporation and concentration,reverse-osmosis，Kuderna Danish (K-D) concentrator and so on. The detection methods include gas chromatography-mass ectrometry,fluorometry,enzyme inhibition,immunoassay, biosensor and infrared spectrometry,Raman spectrometry,and so on. The advantages and disadvantages of these methods were reviewed and the development tendency in the future was pointed out.福建省青年科技人才创新项目(2007F3094);厦门大学引进人才科研启动费项目(0000-X071C3);近海海洋环境科学国家重点实验室(厦门大学)开放基金(MEL0603);国家海洋局第三海洋研究所海洋生物遗传资源重点实验室开放研究基金(HY200601);国家海洋局近岸海域生态环境重点实验室开放基金(200702

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

Measurement of integrated luminosity of data collected at 3.773 GeV by BESIII from 2021 to 2024

We present a measurement of the integrated luminosity e+e- of collision data collected by the BESIII detector at the BEPCII collider at a center-of-mass energy of Ecm = 3.773 GeV. The integrated luminosities of the datasets taken from December 2021 to June 2022, from November 2022 to June 2023, and from October 2023 to February 2024 were determined to be 4.995±0.019 fb-1, 8.157±0.031 fb-1, and 4.191±0.016 fb-1, respectively, by analyzing large angle Bhabha scattering events. The uncertainties are dominated by systematic effects, and the statistical uncertainties are negligible. Our results provide essential input for future analyses and precision measurements

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

Determination of the number of ψ(3686) events taken at BESIII

The number of ψ(3686) events collected by the BESIII detector during the 2021 run period is determined to be (2259.3±11.1)×106 by counting inclusive ψ(3686) hadronic events. The uncertainty is systematic and the statistical uncertainty is negligible. Meanwhile, the numbers of ψ(3686) events collected during the 2009 and 2012 run periods are updated to be (107.7±0.6)×106 and (345.4±2.6)×106, respectively. Both numbers are consistent with the previous measurements within one standard deviation. The total number of ψ(3686) events in the three data samples is (2712.4±14.3)×10^