On the Identification of N-rich Metal-poor Field Stars with Future Chinese Space Station Telescope

During the long term evolution of globular clusters(GCs), some member stars are lost to the field. The recently found nitrogen-rich(N-rich) metal-poor field stars are promising candidates of these GC escapees, since N enhancement is the fingerprint of chemically enhanced populations in GCs. In this work, we discuss the possibility of identifying N-rich metal-poor field stars with the upcoming Chinese Space Station Telescope(CSST). We focus on the main survey camera with NUV, u, g, r, i, z, y filters and slitless spectrograph with a resolution about 200.The combination of UV sensitive equipment and prominent N-related molecular lines in the UV band bodes well for the identification: the color–color diagram of(u-g) versus(g-r) is capable of separating N-rich field stars from normal halo stars, if metallicity can be estimated without using the information on u-band photometry.Besides, the synthetic spectra show that a signal-to-noise ratio of 10 is sufficient to identify N-rich field stars. In the near future, a large sample of N-rich field stars found by CSST, combined with state-of-the-art N-body simulations will be crucial to deciphering GC-Galaxy co-evolution.

Classification and Distribution of Common Aroma Components in Tobacco Leaf Based on Their Physical and Chemical Properties

[Objective] This study was aimed to find a new method for the classification of common aroma components in tobacco leaves. [Method] Sixty-four common aroma components in tobacco leaves were classified by cluster analysis based on their relative molecular weight. The contents and distribution of aroma components in another 71 C3F and 64 B2F tobacco leaf samples were analyzed by using the new method. [Result] The 64 common aroma components were divided into three categories trough the cluster analysis based on their molecular weight. CategoryⅠ consisted of 12 aroma components which had high molecular weight（281.308±21.536on average） and high boiling point（371.311±29.904 ℃ on average）. Category Ⅱ included 27 components which had low molecular weight（103.722 ± 13.115 on average） and low boiling point（176.132±42.342 ℃ on average）. Category Ⅲ included 25components which had middle molecular weight（175.393 ± 24.906 on average） and middle boiling point（250.562±45.431 ℃ on average）. The content of high-molecularweight aroma components in middle leaves（547.344±224.391 μg/g） was much higher than that in upper leaves（477.549±182.066 μg/g）. The content of low-molecularweight aroma component in middle leaves（17.468±3.459 μg/g） was also significantly higher than that in upper leaves（15.936±3.456 μg/g）. The content of middle-molecular-weight aroma component in middle leaves（44.931 ±8.953 μg/g） was extremely significantly higher than that in upper leaves（37.997±6.042 μg/g）. [Conclusion] This study proposed a new way to classify the aroma components in flue-cured tobacco leaves using the relative molecular weight as the index, which will provide theoretical reference for developing special tobacco leaves.

Chemical abundance analysis of 19 barium stars

We aim at deriving accurate atmospheric parameters and chemical abundances of 19 barium（Ba） stars, including both strong and mild Ba stars, based on the high signal-to-noise ratio and high resolution Echelle spectra obtained from the 2.16 m telescope at Xinglong station of National Astronomical Observatories, Chinese Academy of Sciences. The chemical abundances of the sample stars were obtained from an LTE, plane-parallel and line-blanketed atmospheric model by inputting the atmospheric parameters（effective temperatures Teff, surface gravities log g, metallicity [Fe/H] and microturbulence velocity ξt） and equivalent widths of stellar absorption lines. These samples of Ba stars are giants as indicated by atmospheric parameters, metallicities and kinematic analysis about UVW velocity. Chemical abundances of 17 elements were obtained for these Ba stars. Their Na, Al, α- and iron-peak elements（O, Na, Mg, Al, Si, Ca,Sc, Ti, V, Cr, Mn, Ni） are similar to the solar abundances. Our samples of Ba stars show obvious overabundances of neutron-capture（n-capture） process elements relative to the Sun. Their median abundances of[Ba/Fe], [La/Fe] and [Eu/Fe] are 0.54, 0.65 and 0.40, respectively. The Y I and Zr I abundances are lower than Ba, La and Eu, but higher than the α- and iron-peak elements for the strong Ba stars and similar to the iron-peak elements for the mild stars. There exists a positive correlation between Ba intensity and [Ba/Fe].For the n-capture elements（Y, Zr, Ba, La）, there is an anti-correlation between their [X/Fe] and [Fe/H]. We identify nine of our sample stars as strong Ba stars with [Ba/Fe]〉0.6 where seven of them have Ba intensity Ba=2-5, one has Ba=1.5 and another one has Ba=1.0. The remaining ten stars are classified as mild Ba stars with 0.17〈[Ba/Fe]〈0.54.

The Chemical Classification of the AGB Star IRAS 17515-2407

The chemical classification of IRAS 17515-2407 has been debated for a longtime. Up to now there are two contenders, oxygen-rich or carbon-rich. We believe that IRAS17515-2407 is an oxygen-rich source: because (ⅰ) it shows the silicate self-absorbed emission; (ⅱ)in the near infrared-IRAS diagram it is located in the oxygen-rich object region and (ⅲ)particularly, it has detected SiO maser emission.

Chemical Classification of Space Debris

Space debris, here referring to all non-operating orbital objects, has steadily increased in number so that it has become a potential barrier to the exploration of space. The ever-increasing number of space debris pieces in space has created an increasingly threatening hazard to all on-the-orbit spacecraft, and all future space exploration activities have to be designed and operated with respect to the increasing threat posed by space debris. Generally, space debris is classified as large, medium and small debris pieces based on their sizes. The large debris piece is easily catalogued, but medium to small debris pieces are very difficult to track and also quite different in damage mechanisms from the large ones. In this paper, a scheme of chemical classification of space debris is developed. In our scheme, the first-order classification is employed to divide space debris into two groups: natural micrometeoroids and artificial space debris. The second-order classification is based on their chemical patterns and compositions. The natural micrometeoroids are further divided into three types, namely mafic, metal and phyllosilicate micrometeorites, while the artificial space debris is divided into seven types, which are polymers, non-metal debris, metals and their alloys, oxides, sulphides and their analogs, halides and carbides. Of the latter seven types, some can also be further divided into several sub-types. Chemical classification of space debris is very useful for the study of the chemical damage mechanism of small debris pieces, and also is of great significance in constraining the origin and source of space debris and assessing their impact on spacecraft and human space activities.

Chemical abundances of three new Ba stars from the Keck/HIRES spectra

Based on high resolution,high signal-to-noise(S/N)ratio spectra from Keck/HIRES,we have determined abundances of 20 elements for 18 Ba candidates.The parameter space of these stars is in the range of 4880≤Teff≤6050 K,2.56≤log g≤4.53 dex and-0.27≤[Fe/H]≤0.09 dex.It is found that four of them can be identified as Ba stars with[s/Fe]>0.25 dex(s:Sr,Y,Zr,Ba,La,Ce and Nd),and three of them are newly discovered,which include two Ba giants(HD 16178 and HD 22233)and one Ba subgiant(HD 2946).Our results show that the abundances ofα,odd and iron-peak elements(O,Na,Mg,Al,Si,Ca,Sc,Ti,Mn,Ni and Cu)for our program stars are similar to those of the thin disk,while the distribution of[hs/ls](hs:Ba,La,Ce and Nd,ls:Sr,Y and Zr)ratios of our Ba stars is similar to those of the known Ba objects.None of the four Ba stars show clear enhancement in carbon including the known CH subgiant HD 4395.It is found that three of the Ba stars present clear evidence of hosting stellar or sub-stellar companions from the radial velocity data.

A Catalog and Statistical Analysis for Magnetic Stars

Magnetic fields are significant in the structure and evolution of stars. We present a comprehensive catalog of 1784known magnetic stars, detailing their identifications, HD numbers, precise locations, spectral types and averaged quadratic effective magnetic fields among other important information. The group comprises 177 O-type stars, 551B-type stars, 520 A-type stars, 91 F-type stars, 53 G-type stars, 61 K-type stars, 31 M-type stars and an additional300 stars whose spectral classification remains indeterminate. Our analysis examines the statistical properties of these magnetic stars. The relative integrated distribution function and number distribution function for all magnetic stars of the same spectral type can be effectively approximated using an exponential function of the averaged quadratic effective magnetic field. The analysis further reveals that A and B-type stars possess the strongest mean magnetic fields, indicating an easier detection of their magnetic fields.

危化品王国的奇妙之旅

实验室的化学品种类繁多,其中有一类极具危险的化学品,它们时常引发各类事故,但又在人类生活中有着十分重要的作用,这就是危险化学品。在实验室中大家总是无法避免接触这类化学品,因此认识危化品,分辨它们的危险属性,确保正确储存和规范使用至关重要。本文以和平大使淇淇的视角,带大家走进危险化学品国度里的各个部落,介绍实验室危险化学品的分类以及储存方法,让大家了解并从容面对他们,并且能够安全使用,避免实验室危险事故的发生。

HFACS-MI改进模型在危险化学品仓储事故人因分析中的应用

为了研究危险化学品仓储事故的关键人因,通过人因分析与分类系统-煤矿(Human Factors Analysis and Classification System-Mine,HFACS-MI)改进模型从员工的不安全行为、影响不安全行为的前提条件、监督行为、组织影响和企业外部因素5个层次系统地分析65起危险化学品仓储事故,并运用卡方检验和让步比分析了产生不安全行为的原因和各层次间的内在关系。结果表明,外部管理、组织过程、监督不充分、个人因素、技能差错和违规是导致危险化学品仓储事故发生的重要因素。HFACS-MI改进模型上下层级的人为因素间存在显著的因果关系,且主要的危险化学品仓储事故致因路径共有5条,其中“外部管理因素—组织过程漏洞—监督不充分—个人因素—违规”是最关键的致因路径。改进的HFACS-MI模型可以有效分析危险化学品仓储事故人因因素。

典型煤化工装置设备风险评级与管理系统

为实现对煤化工装置设备风险的科学管理,建立以装置安全运行为目标,集基础数据、运行数据、状态监测数据、设备风险分级和孪生模型展示于一体的煤化工装置设备风险评级与管理系统。系统基于RBI中风险评估技术实现煤化工装置设备风险评级与管理策略,通过数字孪生技术实现多源信息的交互,并实现面向不同层级管理人员的设备管理、关键安全状态监测、风险评级等功能。系统应用支撑了设备数据和风险的管理、安全状态感知和评估等工作,有利于推进设备科学管理,提升设备管理工作的有效性和针对性,支撑了化工装置安全生产运行。

准东煤半焦赤铁矿载氧体化学链燃烧及碱(土)金属迁移特性

准东煤在常规燃烧利用过程中出现严重的积灰结渣和CO_(2)排放等问题,极大地限制了其低碳清洁高效利用。采用中低温热解低阶煤生产半焦、焦油和热解气是煤炭分质分级利用的龙头技术,准东高碱煤热解半焦气化活性高,采用化学链燃烧方式有利于实现其低碳清洁高效转化。以CO_(2)为气化介质,赤铁矿石为载氧体,在固定床上开展准东煤半焦原位气化化学链燃烧特性研究,并探究了准东煤半焦中碱(土)金属(AAEMs)的迁移转化规律。研究表明,赤铁矿载氧体能够显著提高固定床反应器出口烟气中CO_(2)体积分数,然而随着载氧体与半焦质量比(mOC/mC)不断增加,CO_(2)体积分数先急剧增加而后趋于不变,最佳的mOC/mC为50:1,而700℃热解制取的准东煤半焦经酸洗脱灰处理后固定床反应器出口相应烟气中CO_(2)的选择性降低了8.95%,这表明准东煤半焦中具有催化活性的AAEMs显著影响其化学链燃烧性能。赤铁矿载氧体对准东煤半焦表面AAEMs的分布也有显著影响,与未加入时相比,Na、K元素在半焦表面呈现较为明显的团簇富集,Ca、Mg元素在空间分布上呈更为明显的依赖关系。采用原位气化化学链燃烧方式后准东煤半焦中的AAEMs向赤铁矿载氧体中发生迁移与转化,并生成霞石(NaAlSiO_(4))、钾长石(KAlSi_(3)O_(8))、钙铝黄长石(Ca_(2)Al_(2)SiO_(7))、镁橄榄石(Mg_(2)SiO_(4))等高熔点矿物质,有效抑制了准东煤半焦中AAEMs向气相的挥发。

基于危险性类别分析的实验室危险化学品风险管控研究

危险化学品是实验室风险管控的重点,根据危险性类别可以对危险化学品实施科学有效的管控。对危险化学品的危险性类别分析与统计的结果表明,绝大多数危险化学品只具有一种物理危险类别,但具有多种健康危害类别。对于物理危险应采取有针对性的防护措施,而健康危害则应采取全方位的防护措施。高校实验室的分级分类管理可以将危险化学品分类信息表作为参考,通过信息化系统能够对危险性进行科学高效的评估与分级,从而采取相应的管控措施,降低安全风险,维护实验室安全。

基于CNN与LSTM复合深度模型的恒星光谱分类算法

恒星光谱分类是天文学领域中非常重要的研究方向。随着科技的迅猛发展,大型巡天望远镜采集的恒星光谱数据已经达到了TB或甚至PB级别,传统的分类方法已经无法满足如此庞大数据量的处理需求。正确分类光谱对于研究恒星的物理性质以及演化过程具有重要意义。CNN通过卷积运算学习数据的局部特征,去除冗余信息,并通过最大池化运算对特征进行压缩。然而,由于原始CNN模型的全连接层缺乏长距离依赖挖掘的功能,如果加入LSTM网络,通过其独特的三个“门”的远距离依赖挖掘能力可提取的重要特征,并检测特征中的微小差异,恰好可以解决这个问题。因此,提出了一种基于CNN和LSTM复合的深度模型,用于对LAMOST DR8中的恒星光谱进行分类。这种模型能够更好地学习恒星光谱的特征,为恒星演化研究提供了重要的帮助。为了提高模型的收敛速度,使用了常见的Z-Score标准化方法对数据进行处理。提出的模型在F、G、K三分类实验中取得了94.56%的分类准确率。同时,与前人使用过的RBM、PILDNN、PILDNN、DBN、Inception v3、1D-SSCNN、LSTM方法进行对比,结果表明该方法具有更高的分类准确率。在十分类实验中,该方法取得了97.35%的准确率,并且相比于仅使用LSTM、1D-SSCNN方法的实验结果,该方法的结果更好,且训练时间减少了近十倍。使用F1-score对每类恒星光谱分类准确度进行说明,在三分类和十分类实验中,每类的F1值都在0.9以上。与前人在文献中的实验结果进行对比,该模型的结果更好。通过混淆矩阵的结果,可以得出该模型在光谱种类越多的实验中准确率越高,甚至可以达到100%。综上所述,所提出的基于CNN和LSTM相结合的模型可以有效地对大规模恒星光谱数据进行分类,并取得了优异的分类效果。

对化学教学中“模型认知”的认识与思考

模型认知是高中化学课程标准的核心素养之一。当前在中学化学学科领域内,关于模型及建模的研究主要集中在模型认知视角下的教学研究、建模教学在中学化学中的应用、中学化学复习课中模型的建构与应用研究等三个方面。模型的定义和化学模型的分类能帮助教师和学生更好地认识模型。模型定义的核心表达是为了某种特定的目的,利用简化、抽象、类比等方法,对事物的本质进行表征,将抽象思维外显化。化学认知模型和化学认识模型共同指导化学学科知识的学习,基于模型的教学策略是落实模型认知素养的重要途径之一。

苍术属植物分类研究进展

苍术属是菊科中重要的药用植物属,属内植物形态变异多样,种间和种下分类模糊不清。因此,明确苍术属系统分类、种间关系对属内药材资源开发利用具有重要作用。本文从苍术属系统分类、植物形态、细胞学、植物化学分类、分子系统等方面简要回顾苍术属分类研究成果,比较了不同学者对苍术属植物分类的分歧,对该属分类鉴定和种间关系进行了探讨和总结。苍术属植物形态的连续变化是植物形态分类分歧的根本原因,属内植物系统的分类要充分结合多学科或技术方法,并要考虑到资源利用的可持续性。本文结合属内药用植物的药材品质和临床用药,对苍术属植物分类研究提出了展望,以期为苍术属药用植物资源的保护利用提供参考。

江西省烟叶化学指标分析及感官质量分类模型构建

为探究江西省烟叶的质量特征,利用方差分析、区间估计等统计学方法分析不同感官质量档次(A类、B类、C类)上、中、下3个部位江西省烟叶11项化学指标的差异性及协调性等特征,在此基础上构建支持向量机(SVM)和随机森林(RF)2种模型用于烟叶感官质量分类预测。结果表明,上、中、下3个部位C类烟叶分别有7、6、6项化学指标高于A类、B类,B类烟叶分别有3、3、2项高于A类、C类,而A类烟叶分别有0、2、3项高于B类、C类;从区间长度来看,上、中、下3个部位C类烟叶分别有9、9、7项化学指标高于A类、B类,B类烟叶分别有1、0、3项高于A类、C类,而A类烟叶分别有1、2、1项高于B类、C类,3个部位C类烟叶化学成分的协调性远差于A类、B类,这可能是导致感官质量变差的重要原因。SVM和RF 2种模型的精确率、召回率和F1分数的加权平均值均超过84%,且SVM模型的3项指标稍高于RF模型。C类烟叶化学指标特征与A类、B类存在明显区别,而A类、B类之间差别相对较小;SVM模型对A类、B类烟叶样品的分类性能优于RF模型,RF模型对C类的识别性能优于SVM模型。

化工企业雷击风险部位精细化分级与应用

化工企业因涉及易燃易爆物质的建(构)筑物的生产、储存和运输,已成为防雷安全监管的重点对象,一旦遭受雷击,可能引发火灾、爆炸及危险品泄漏等严重后果。文章以苏州市化工企业为例,具体分析了不同功能区域建筑物的雷击风险部位。依据国家标准对风险等级进行了划分,并提出了提高化工企业雷电灾害防御能力的改进措施,为增强化工企业雷电安全防范的针对性和有效性提供了指导。

煤化工回用水再利用工程实例分析

某煤化工项目废水处理站的回用水以及零排放处理站的回用水作为循环水场冷却塔补水时,因夏季温度过高,而影响循环水系统的运行;作为脱盐水站的原水补水时,导致脱盐水反渗透清洗频繁、混床出水品质下降、树脂再生周期缩短、自用水率升高等问题。经分析与研究,提出部分回用水可作为气化等生产装置用水,其他回用水可经过分类提优、梯次回用至冷却循环塔补水以及生产水补水。经分析与研究,提出部分回用水可作为气化等生产装置生产用水直接使用,其他回用水可经过分类提优、梯次回用至冷却循环塔补水以及生产水补水的工作思路,可实现水资源合理化再利用。

前胡类习用品种的分类鉴定与研究进展

系统地整理了7种前胡习用品种的药用植物分布和资源概况、植物药材和饮片性状分类特征以及化学药理作用方面的研究进展。白花前胡、紫花前胡、硬前胡(包括华北前胡和/或少毛北前胡)的化学成分和药理研究较深入,而华中前胡、毛前胡、长前胡与旱前胡(羽苞拟藁本)的化学成分和药理作用研究相对较少,可进一步深入研究,扩大前胡类习用药材的资源药用价值。

世园会瀑布酒店电气设计要点与思考

结合酒店管理公司、国家及行业规范的要求,对成都世园会瀑布酒店项目的变配电系统、电力配电系统、消防与生命安全系统等设计要点进行探讨,总结该类项目电气设计注意事项。指出该类型项目设计中应特别关注的地方:柴油发电机组的供电范围、储油量的要求;特殊场所的电气设计要求;消防与生命安全系统的特殊要求。