Qualitative and quantitative determination of Atractylodes rhizome using ultra‐performance liquid chromatography coupled with linear ion trap–Orbitrap mass spectrometry with data‐dependent processing

A quick and effective workflow based on ultra‐performance liquid chromatography coupled with electron spray ionization and LTQ‐Orbitrap mass spectrometry (UPLC‐LTQ‐Orbitrap MS) was established for compositional analysis and screening of the characteristic compounds of three species of Atractylodes rhizome for quality evaluation. This technique was employed to determine the seven main components in Atractylodes rhizome samples. Ultimately, 78 constituents were identified; of these, seven characteristic compounds were selected for species discrimination, comprising atractylodin (63), atractylenolide I (43), atractylenolide II (49), atractylenolide III (53), atractylon (69), methyl‐atractylenolide II (54) and (4E,6E,12E)‐tetradecadecatriene‐8,10‐diyne‐1,3‐diacetate (59). The seven main compounds, including six characteristic compounds, were simultaneously determined in 29 batches of Atractylodes rhizome samples. Thus, the method validation showed acceptable results. Quantitative analysis showed significantly different contents of the seven main components among the three species of Atractylodes rhizome, which indicates possible distinctions in the pharmacological effects. This established method can simultaneously provide qualitative and quantitative results for compositional characterization of Atractylodes rhizomes and for quality control.     

Enhancing signal-to-noise ratio and resolution in low-field NMR relaxation measurements using post-acquisition digital filters

The traditional way to enhance signal-to-noise ratio (SNR) of nuclear magnetic resonance (NMR) signals is to increase the number of scans. However, this procedure increases the measuring time that can be prohibitive for some applications. Therefore, we have tested the use of several post-acquisition digital filters to enhance SNR up to one order of magnitude in time domain NMR (TD-NMR) relaxation measurements. The procedures were studied using continuous wave free precession (CWFP-T₁) signals, acquired with very low flip angles that contain six times more noise than the Carr–Purcell–Meiboom–Gill (CPMG) signal of the same sample and experimental time. Linear (LI) and logarithmic (LO) data compression, low-pass infinity impulse response (LP), Savitzky–Golay (SG), and wavelet transform (WA) post-acquisition filters enhanced the SNR of the CWFP-T₁ signals by at least six times. The best filters were LO, SG, and WA that have high enhancement in SNR without significant distortions in the ILT relaxation distribution data. Therefore, it was demonstrated that these post-acquisition digital filters could be a useful way to denoise CWFP-T₁, as well as CPMG noisy signals, and consequently reducing the experimental time. It was also demonstrated that filtered CWFP-T₁ method has the potential to be a rapid and nondestructive method to measure fat content in beef and certainly in other meat samples.     

Code2vect: An efficient heterogenous data classifier and nonlinear regression technique

The aim of this paper is to present a new classification and regression algorithm based on Artificial Intelligence. The main feature of this algorithm, which will be called Code2Vect, is the nature of the data to treat: qualitative or quantitative and continuous or discrete. Contrary to other artificial intelligence techniques based on the “Big-Data,” this new approach will enable working with a reduced amount of data, within the so-called “Smart Data” paradigm. Moreover, the main purpose of this algorithm is to enable the representation of high-dimensional data and more specifically grouping and visualizing this data according to a given target. For that purpose, the data will be projected into a vectorial space equipped with an appropriate metric, able to group data according to their affinity (with respect to a given output of interest). Furthermore, another application of this algorithm lies on its prediction capability. As it occurs with most common data-mining techniques such as regression trees, by giving an input the output will be inferred, in this case considering the nature of the data formerly described. In order to illustrate its potentialities, two different applications will be addressed, one concerning the representation of high-dimensional and categorical data and another featuring the prediction capabilities of the algorithm.     

基于计算机视觉技术的茶叶品质随机森林感官评价方法研究

为弥补茶叶品质感官审评存在的缺陷，利用计算机视觉技术对茶叶品质进行快速无损评价研究。以碧螺春绿茶为对象，依据专家感官审评结果，将茶样分成4个等级；采用中值滤波及拉普拉斯算子对茶样图像进行预处理，并提取预处理后的茶样图像的颜色特征和纹理特征以表征茶叶图像的外形特征，利用随机森林算法对茶叶外形特征属性进行重要性排序；筛选出重要性较大的特征及随机森林算法中最优的决策树棵数建立感官评价模型，并与建立的支持向量机(SVM)模型性能相比较。结果表明：色调均值、色调标准差、绿体均值、平均灰度级、饱和度均值、红体均值、饱和度标准差、亮度均值、一致性等9个特征属性的重要性较大，且与感官审评特征描述结果相一致；当采用优选出的9个重要性较大的特征及决策数棵数为500时，建立的模型性能最优，模型总体判别率为95.75%，Kappa系数为0.933，OOB误差为5%，较SVM模型分别提高了3.5%，0.066，优选的9个重要性较大的图像特征与感官审评特征描述相一致。研究表明：利用随机森林方法筛选出对茶叶外形特征属性贡献最大的少数几个特征建立模型，模型性能就能达到很好的识别效果，模型得到简化，同时模型精度和稳定性都高于其他方法。     

自由基浓度测定方法的再验证及其在煤化学中应用

对前人建立的标准曲线法测煤中自由基浓度进行优化,以DPPH标准样品和基准样品的二次积分面积比值为新参数,结果显示新参数标准曲线法的实测值与理论值相对误差都在5%以内;重复性、复现性实验的相对标准偏差都小于3%。将新参数标准曲线法用于分析不同煤化程度煤和新疆黑山煤(HS)沥青质的自由基浓度,发现随着煤化程度增加,其煤中自由基浓度逐渐增大,从低阶褐煤的8.531×10~(17)/g上升到高阶无烟煤3.37899×10~(19)/g;而在HS煤液化过程中,随着加氢液化温度的升高,其沥青质自由基浓度逐渐下降,从290℃的1.5793×10~(18)/g降到450℃的7.410×10~(17)/g,沥青质自由基浓度变化趋势与其产率变化趋势相一致。     

基于NPP-VIIRS夜间灯光数据的山西省GDP空间化模拟

选取山西省为研究对象，以美国国家极轨合作仪件-可见红外成像辐射计套件（NPP-VIIRS）夜间灯光数据、GDP统计数据等为数据源，构建GDP空间化拟合模型，建立山西省GDP密度图，据此研究山西省经济的空间差异性。通过对NPP-VIIRS夜间灯光数据的空间化处理，提取灯光指数，并将其与GDP进行回归拟合，建立最佳回归模型，得到GDP密度拟合图；利用县级GDP数据进行线性纠正，从而提高GDP的模拟精度。结果表明：（1）NPP-VIIRS夜间灯光数据与GDP的相关性较高，可用于山西省GDP模拟；（2）与GDP分区建模相比，GDP整体建模的精度更高；（3）山西省GDP的空间分布整体呈由城市中心逐渐向周边辐射的特点，构成GDP过渡带。     

组合式十字形钢管混凝土柱偏压力学性能试验研究

设计了一种由槽钢和方形钢管拼焊形成的组合式十字形钢管混凝土柱,将其灵活地布置在框架结构的中节点,可使柱肢与填充墙等厚,有效地提高建筑使用面积。共制作了6根组合式十字形钢管混凝土柱试件,考虑了偏心距和长细比两种变化参数。通过对其进行偏心受压试验研究,考察了试件的破坏形态和荷载-挠度曲线,并分析了其在不同偏心距和长细比下的荷载-应变曲线发展规律。结果表明:组合式十字形钢管混凝土柱中钢管和槽钢对混凝土的约束作用强,表现为较高的延性系数;偏心距或长细比越大,试件的极限承载力及弹性刚度越小,且偏心距越大延性越好,长细比对延性影响不显著;在受拉侧纵向应变基本上符合平截面假定,在受压侧纵向应变不符合平截面假定。     

双原子分子激发态势能的自旋相关局域Hartree-Fock密度泛函理论方法

基于自旋相关局域Hartree-Fock (SLHF)势函数，本文提出了一种计算双原子分子激发态势能的密度泛函理论(DFT)方法，并将该方法应用于和的激发态势能曲线的计算。在只考虑交换能的情况下，本文的DFT计算结果与文献中精确方法和Hartree-Fock (HF)方法的结果符合的非常好，说明采用SLHF势函数作为交换势的DFT方法是一个很好的计算激发态势能的方法。本文还计算和探讨了电子的关联势函数和关联能，发现传统的近似方法在较大核间距的情况下大大低估了电子的关联能.