M RPÊ 中物料清单树型结构的分析与实现

针对MRPÊ 物料清单的树状特点, 提出了以物料结构与单据相结合的程序开发模式, 以及 相应的数据库设计方法. 并且采用V isual Foxp ro5. 0 对物料清单管理进行了编程实现, 得到了较为 直观、方便、灵活的实用效果. 另外, 也与Gozintograph 设计形式比较分析说明了物料清单树状结构 设计实现的优势.香港尖端资讯有限有司资助项

Analysis and Implement of BOM on Tree-Type Structure in MRPⅡ

针对 MRP 物料清单的树状特点 ,提出了以物料结构与单据相结合的程序开发模式 ,以及相应的数据库设计方法 .并且采用 Visual Foxpro5.0对物料清单管理进行了编程实现 ,得到了较为直观、方便、灵活的实用效果 .另外 ,也与 Gozintograph设计形式比较分析说明了物料清单树状结构设计实现的优势 .According to the character of tree- Type structure for BOM( Bill of material) in MRP ,the mode of program development by combining material structure with bills of document,as well as the method of database design is proposed. By using VF5 . 0 ,a management system of BOM has been established and confirmed in practice.Compared with Gozintograph mode,the BOM design on tree- Type structure has many advantages.香港尖端资讯有限有司资助项

浅析二氧化碳灭火系统的设计[J]

二氧化碳灭火系统是目前应用非常广泛的一种现代化消防设备,具有设计参数完整、功能完善、工作准确可靠安装调试简单、操作维修方便等特点.适用于票据库、档案库、计算机房、图书馆、珍品库、配电房、电讯中心等重要场所的消防保护.本文着重介绍了高压管管网式全淹没二氧化碳灭火系统的原理、适用范围、分类及其系统设计

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

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 → 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