Developing the Low-Temperature Oxidation Mechanism of Cyclopentane: An Experimental and Theoretical Study

At present, the reactivity of cyclic alkanes is estimated by comparison with acyclic hydrocarbons. Due to the difference in the structure of cycloalkanes and acycloalkanes, the thermodynamic data obtained by analogy are not applicable. In this study, a molecular beam sampling vacuum ultraviolet photoionization time-of-flight mass spectrometer (MB-VUV-PI-TOFMS) was applied to study the low-temperature oxidation of cyclopentane (CPT) at a total pressure range from 1–3 atm and low-temperature range between 500 and 800 K. Low-temperature reaction products including cyclic olefins, cyclic ethers, and highly oxygenated intermediates (e. g., ketohydroperoxide KHP, keto-dihydroperoxide KDHP, olefinic hydroperoxides OHP and ketone structure products) were observed. Further investigation of the oxidation of CPT – electronic structure calculations – were carried out at the UCCSD(T)-F12a/aug-cc-pVDZ//B3LYP/6-31+ G(d,p) level to explore the reactivity of O₂ molecules adding sequentially to cyclopentyl radicals. Experimental and theoretical observations showed that the dominant product channel in the reaction of CPT radicals with O₂ is HO₂ elimination yielding cyclopentene. The pathways of second and third O₂ addition – the dissociation of hydroperoxide – were further confirmed. The results of this study will develop the low-temperature oxidation mechanism of CPT, which can be used for future research on accurately simulating the combustion process of CPT.     

基于深度学习的中医古文献临床经验抽取

中医古文献蕴藏着丰富的临床经验，是古代中医在行医过程中对临床诊疗的经验性总结，体现了中医学形成和发展的理论框架和思想基础.然而这些宝贵的临床经验不仅量大，而且分散在不同的文献中，使得中医从业者手工很难快速全面地获取它们，文献检索工具也只能提供文档级别的信息筛选，无法为这种细粒度的信息获取提供支持.此外，古汉语相对于现代汉语的不同特点也限制了主流文本分析工具的使用效果.为此本文提出面向临床经验获取的中医古文献信息抽取任务，用于识别古文献中描述临床经验的文本片段，手工标注了样本数据用于这种抽取模型的训练和测试，并设计了基于深度学习的序列标注器用于完成该任务.考虑到标注数据量小可能带来的过度拟合问题，本文引入对抗训练和虚拟对抗训练来增强模型的泛化能力.一系列充分的实验验证了模型的有效性，表明利用信息抽取技术从古文献获取中医临床经验具有可行性，为这一新的信息抽取任务提供了有希望的研究基线和可复用的标注数据集.     

人才吸引力因素与政策工具契合关系研究以河北省为例

人才是第一资源,人才引进培养是经济社会发展的一个关键,近年来我国各地纷纷出台吸引人才的重磅政策.为探求人才政策工具对人才的吸引力情况,在构建人才吸引力因素理论模型基础上,通过对178位人才问卷调查获得人才吸引力关键因素,对河北省163份人才政策文本进行数据挖掘,分析政策工具与人才吸引力因素的契合关系.研究得出创新氛围、人才培训培养、人才激励评价、创新创业支持、人才服务和薪资待遇等方面契合度高,政策效果较佳;工作场所仪器设备条件、配偶子女安置和住房补贴的契合关系为政策不足,应加大政策制定;人才载体和医疗社会保障的契合关系为政策冗余,需加强政策实施.     

A New Quassinoid from Brucea javanica

Chemistry of Natural Compounds - A new quassinoid, dehydrobruceantinol B (1), was isolated from the seeds of Brucea javanica, together with two known compounds, bruceantinol (2) and bruceine A (3)....     

基于LQG控制的整车8-DOF系统振动分析

建立了整车8-DOF系统动力学模型,考虑了主动悬架控制,并增设了主动座椅控制,设计了车辆主动悬架系统的LQG控制器。基于Matlab仿真平台建立了整车8-DOF系统动力学仿真模型,对所得最优控制策略下的动态响应进行了仿真验证。仿真结果表明:为了改善人椅系统质心及车身质心的跳振性能需要在一定程度上弱化各轮轮胎动位移性能。从控制效能上来看,该最优控制器能够满足各行驶状态下对悬架性能的要求,改善了车辆的行驶平顺性。     

超强筋小麦粉面包烘焙技术研究

为了烘焙出能充分表现超强筋小麦济麦229面粉品质特性的优良面包,设置了4种醒发时间处理、5种酵母和糖用量处理、4种配粉处理,对超强筋小麦面粉的面包品质进行了评价分析。结果表明,在4个醒发时间处理中,当面团醒发时间为30min和面包胚醒发时间为50min时,烘焙的面包品质最好。在5种酵母和糖用量的处理中,利用吐司面包程序时,干酵母和糖的用量分别为6g和24g时烘焙的面包品质最好；利用法式面包程序时,干酵母和糖的用量分别为3g和18g时烘焙的面包品质最好。在4个配粉处理中,200g超强筋小麦济麦229面粉中添加100g普通小麦济麦22面粉的混粉烘焙得到的面包品质最好。因此,适当调整超强筋小麦粉面包的面团、面包胚醒发时间及物料配比,可以烘焙出品质优良的面包。     

Organocatalytic asymmetric chlorinative dearomatization of naphthols

An organocatalytic asymmetric chlorinative dearomatization of naphthols was realized for the first time, providing chiral naphthalenones with a Cl-containing all-substituted stereocenter in excellent yields and enantioselectivity (up to 97% yield and 96% ee). The reaction features mild reaction conditions, good tolerance of diverse functional groups and simple reaction operation.     

零维到三维结构中三核铜自旋阻挫簇单元的磁构关系和反对称交换

量子自旋液体是最近几年刚被人们证实除铁磁体、反铁磁体之外的第三种磁性类型,因其有望解释高温超导的运行机制、改变计算机硬盘信息存储方式而在物理、材料等领域备受关注。自旋阻挫作为量子自旋液体的最小单元可能是解开量子自旋液体诸多问题的钥匙,所以在磁学、电学研究领域再一次成为人们研究的热点。基于文献报道的三核铜配合物[Cu3(μ3-OH)(μ-OPz)3(NO3)2(H2O)2]·CH3OH(1),我们合成了三维金属有机框架配合物{[Ag(HOPz)Cu3(μ3-OH)(NO3)3(OPz)2Ag(NO3)]·6H2O}n(2)(HOPz=甲基(2-吡嗪基)酮肟),并从自旋阻挫的角度对二者磁性质进行对比和详细分析。磁化率数据表明自旋间有很强的反铁磁相互作用和反对称交换。通过包含各向同性和反对称交换的哈密顿算符对两者磁学数据进行拟合并研究其磁构关系,所获最佳拟合参数为:配合物1:Jav=-426 cm^-1,g⊥=1.83,g∥=2.00;配合物2:Jav=-401 cm^-1,g⊥=1.85,g∥=2.00。