Enhancing the Limit of Detection for Comprehensive Two‐Dimensional Gas Chromatography (GC×GC) using Bilinear Chemometric Analysis

The chemometric method referred to as the generalized rank annihilation method (GRAM) is used to improve the precision, accuracy, and resolution of comprehensive two‐dimensional gas chromatography (GC×GC) data. Because GC×GC signals follow a bilinear structure, GC×GC signals can be readily extracted from noise by chemometric techniques such as GRAM. This resulting improvement in signal‐to‐noise ratio (S/N) and detectability is referred to as bilinear signal enhancement. Here, GRAM uses bilinear signal enhancement on both resolved and unresolved GC×GC peaks that initially have a low S/N in the original GC×GC data. In this work, the chemometric method of GRAM is compared to two traditional peak integration methods for quantifying GC×GC analyte signals. One integration method uses a threshold to determine the signal of a peak of interest. With this integration method only those data points above the limit of detection and within a selected area are integrated to produce the total analyte signal for calibration and quantification. The other integration method evaluated did not employ a threshold, and simply summed all the data points in a selected region to obtain a total analyte signal. Substantial improvements in quantification precision, accuracy, and limit of detection are obtained by using GRAM, as compared to when either peak integration method is applied. In addition, the GRAM results are found to be more accurate than results obtained by peak integration, because GRAM more effectively corrects for the slight baseline offset remaining after the background subtraction of data. In the case of a 2.7‐ppm propylbenzene synthetic sample the quantification result with GRAM is 2.6 times more precise and 4.2 times more accurate than the integration method without a threshold, and 18 times more accurate than the integration method with a threshold. The limit of detection for propylbenzene was 0.6 ppm (parts per million by mass) using GRAM, without implementing any sample preconcentration prior to injection. GRAM is also demonstrated as a means to resolve overlapped signals, while enhancing the S/N. Four alkyl benzene signals of low S/N which were not resolved by GC×GC are mathematically resolved and quantified.     

Design and Implementation of Comprehensive Gas Chromatography with Cryogenic Modulation

Comprehensive gas chromatography is the realization of true continuous multidimensional (dual column) gas chromatography. The key requirement in the comprehensive GC experiment is that the second dimension analysis is completed in a rapid time‐frame compared to the elution of components in the first dimension, and that the two coupled dimensions represent ‘orthogonal’ analyses towards the analytes to be separated. The former normally necessitates pulsing of contiguous segments of each chromatographic band from the first to the second dimensions. The two dimensions should be in fluid communication. The comprehensive GC×GC experiment passes all the column flow from the first column to the second column, leading to no sample loss, but this also requires a suitable method for time‐ or zone‐compression of the band to be pulsed to the second column. The final pulse should be narrow, and should be delivered to the second column quickly. A simple procedure can achieve this using the cryogenic modulator that has been recently described by this group. The system uses a cryogenic trap which can be moved away from the cooled zone of the column faster than 10 ms. A fast‐acting pneumatic ram achieves this performance. The cooled column heats up to the prevailing oven temperature within 10–15 ms. Molecules as volatile as C5 alkanes or small aromatics will be fully retained by the trap within the period of modulation used for GC×GC. The technique is simple to implement and requires no special column connections. Using a gas chromatograph which allows control of external events and can acquire from a detector at 50 Hz or faster, and a timing controller for modulation, the comprehensive result can easily and effectively be achieved.     

Is Multidimensional High Performance Liquid Chromatography (HPLC) an Alternative in Protein Analysis to 2D Gel Electrophoresis?

The interactive modes of High Performance Liquid Chromatography (HPLC) of proteins provide a platform for the construction of a multidimensional HPLC system coupled to mass spectrometry. We present a system composed of both anion and cation exchanger columns, in the first dimension, and n‐octadecyl bonded 1.5 μm nonporous silica columns in the second dimension. Both columns are operated under gradient conditions. A system suitability test with standard proteins showed that the total analysis can be performed within about 20 minutes. The fractions taken from the ion exchanger column are directly analyzed within one minute on the reversed phase column at a high flow rate. Two reversed phase columns are applied and operated alternatively: while the first column performs the separation within one minute, the analytes leaving the first dimension are enriched in an on‐column focusing mode on top of the second column. The sample clean‐up and enrichment is performed on a novel type of restricted access cation exchanger column with internal sulfonic acid groups and external diol groups. The columns exhibit a molecular weight exclusion limit for globular proteins of about 15 kDa. Our next studies will be directed towards the analysis of proteins and peptides from extracts of fibroblasts.     

拉开档次法稳定性分析及改进

采用随机模拟仿真的方法分别从增添异常对象和极端样本两个方面对拉开档次法的稳定性进行了分析,给出了相关结论。在此基础上,基于“因子分析”提出了拉开档次法的改进方法,算例部分的分析表明该方法因兼顾了同类数据之间的内部差异,能够削弱“异常值”对原始数据的干扰作用,从而进一步提升了方法的稳定性。最后,指出拉开档次法适用于评价指标数目较少的评价问题,而基于“因子分析”的改进方法则适合于数据数目较多且指标有相关关系的评价问题。     

我国建筑企业核心竞争力评价体系研究

对建筑企业核心竞争力的理论渊源与内涵特征进行了分析,并通过对国内建筑企业的调研,构建了包括建筑引领能力、建筑整合能力和建筑品牌能力三个方面的建筑企业核心竞争力评价指标体系.在此基础上,运用层次分析法(AHP)和模糊综合评判方法(FCE)建立了建筑企业核心竞争力评价模型,并以实例为证,为建筑企业有效的识别与评价其核心竞争力提供了理论依据.     

基于指标区分权重的未确知测度综合评价模型及其应用

分析了指标对区分样本所属类别所作贡献的大小,定义了指标的区分权重.建立基于指标区分权重的未确知综合评价模型,并用于滏阳河水质污染综合评价.     

线上线下混合式-六环节实验教学实践与探索——以化学生物学实验"基于生物正交反应的蛋白质标记"为例

化学生物学综合实验是针对化学生物学专业高年级本科生开设的一门衔接本科-硕士教学的综合性实验课程。本文以“基于生物正交反应的蛋白质标记”科研融合型实验为例,结合化学生物学学科特点,将实验教学内容模块化,探索设计线上线下混合式-六环节教学方式,应用于本科生综合实验教学。经实践取得良好的教学效果,为综合型实验课程教学提供了参考与借鉴。     

Group-type quantitative analysis of flavor compounds in ripening avocados

Avocados are a superfood gaining popularity in people's diet. Profiling and quantifying the volatiles associated with flavor can further help in understanding the fruit. However, this is challenging due to relatively low abundance of volatile compounds. The complex mixtures inherent to avocado flavor can result in coelutions using classical chromatographic techniques. To overcome these challenges, solid-phase microextraction was used to extract and preconcentrate volatiles, then separated and quantified using two-dimensional gas chromatography with a flame ionization detector. This technique enhances separation power and produces well-ordered chromatograms, allowing for templated groupings of compounds of similar chemical composition into regions. Using the flame ionization detector, an average response factor was determined and used for quantification of these templated group-type regions, as well as individual compounds. This group-type quantification improved the overall precision of compound classes in 50 avocados by at least a factor of 2, when compared to that of the individual components. Overall, the abundance of associated flavor groups, such as terpenes and alcohols decreased, whereas aldehyde groups remained constant throughout ripening. The combination of solid-phase microextraction with two-dimensional gas chromatography and group-type quantification allows for an overall better understanding of the volatiles associated with flavor of avocados.     

自抗扰控制技术在高低温环境模拟系统中的应用

针对现有健康状态评估方法主观性较强,准确度不高等问题,提出一种基于DSmT理论和模糊综合评判的健康状态评估模型。首先,确定评估对象的评价指标体系,对采集的原始数据进行预处理;然后利用模糊综合评判理论确定广义基本信度赋值;接着采用DSmT融合规则对广义基本信度赋值合成,得到健康状态等级。对于多级的系统评估,可将融合后的结果作为新的广义基本信度赋值进行DSmT融合。实例验证表明,该状态评估模型能够准确有效地实现对系统的健康状态评估,而且能够克服高冲突证据的融合问题,具有良好的应用价值。     

基于相对熵排序的建筑工程项目投标决策

投标决策是施工企业面对的重要问题.在建筑工程项目投标问题上,先建立风险指标体系,再结合层次分析法和信息熵法求得风险指标的综合权重,然后借助相对熵排序法,对各个方案进行综合评价,得到有效反映各方案差异的评价模型,通过对比可知此法可行有效,且灵敏度高.