Measurements of NH3 in the ν2 = 1 state by a solid-state, photomixing, THz spectrometer, and a simultaneous analysis of the microwave, terahertz, and infrared transitions between the ground and ν2 inversion-rotation levels

In this paper, we report 30 THz measurements of ammonia in its excited, ν₂ = 1, inversion state. These measurements include transition frequencies and pressure shifts (where significant enough to be observed). Included in the data are two forbidden and three ro-inversion transitions, as well as 18 transitions never directly measured before. The measurements were made with an all-solid-state, diode-laser, difference-frequency spectrometer. Using an innovative laser-frequency locking scheme, this spectrometer provided accurately determined and continuously tuned THz-frequencies without requiring accurate knowledge of the absolute laser frequencies. The details of the spectrometer’s frequency calibration is discussed. A global analysis of NH₃ based on the available ground state, ν₂ = 1 state, and ν₂-band transitions was carried out, and the resulting set of recommended molecular effective-Hamiltonian parameters for ammonia is presented. In addition, calculated center frequencies and intensities for all possible transitions up to J = 20 between rotation, inversion, and vibration levels in the ground and ν₂ = 1 states are included as supplementary material.     

Jackknife evaluation of uncertainty judgments aggregated by the Kullback-Leibler distance

One feasible approach to aggregating uncertainty judgments in risk assessments is to use calibration variables (or seed questions) and the Kullback-Leibler (K-L) distance to evaluate experts’ substantive or normative expertise and assign weights based on the corresponding scores. However, the reliability of this aggregation model and the effects of the number of seed questions or experts on the stability of the aggregated results are still at issue. To assess the stability of the aggregation model, this study applies the jackknife re-sampling technique to a large data set of real-world expert opinions. We also use a nonlinear regression model to analyze and interpret the resulting jackknife estimates. Our statistical model indicates that the stability of Cooke’s classical model, in which the components of the scoring rule are determined by the K-L distance, increases exponentially as the number of seed questions increases. Considering the difficulty and importance of creating and choosing appropriate seed variables, the results of this study justify the use of the K-L distance to determine and aggregate better probability interval or distribution estimates.     

LIBS结合单变量定标法对土壤中铅元素含量检测

重金属污染一直影响着人们的健康生活,如镉,铅和铜等的污染,故而土壤重金属的快速检测和如何预防,一直受各国学者关注和研究。传统土壤重金属检测方法（如原子吸收光谱法、X荧光光谱法等）样品预处理复杂,分析成本较高,易形成样品的二次污染,不能满足快速分析的要求。激光诱导击穿光谱（LIBS）是一种典型的原子发射光谱,它是基于分析物质中原子和离子受激发而发射的特征谱线信息,进而研究物质成分的分析方法。LIBS技术能够快速检测任何状态（固、液和气态）物质元素的成分和含量,被看作是未来化学检测和快速绿色分析领域的新兴技术。LIBS技术具有对样本简单预处理（或不需要处理）、多元素同步分析、远距离测量、适用性广等优势,被广泛用于生活生产的各个领域,已成为近年来国内外学者广泛关注和研究的热点之一。在农业信息快速感知的大背景下,以激光诱导击穿光谱技术为技术手段,以土壤重金属铅元素为研究对象,运用理论分析和数学建模相结合,建立了多种基于单变量定标曲线的土壤重金属铅检测模型,并进行了模型验证。自制15个已知的铅元素浓度梯度的谱线土壤样本,在获取了土壤LIBS数据之后,对其进行预处理对比,建立了基于谱峰强度、谱峰积分、洛伦兹拟合强度三种定标曲线模型,对土壤中铅元素含量进行定量分析,得出基于三种定标曲线模型对土壤中铅元素含量的预测决定系数R2分别为0.918 0,0.910 1和0.914 3,三种定标曲线分析方法的预测结果都较好,说明了LIBS结合单变量定标曲线法对土壤中铅含量的检测可靠性高。最后选取部分样本数据进行验证,结果较好。研究结果为研发便携式农田土壤污染物检测技术与装备提供技术支撑,也为农田精准管理和科学施肥奠定基础。     

Optical pressure sensors for high-pressure–high-temperature studies in a diamond anvil cell

We review the various optical pressure sensors that are suitable for high-pressure and high-temperature studies in a diamond anvil cell. Two different kinds of sensors are considered: those based on the pressure shift of a fluorescence line (ruby, SrB₄O₇:Sm²⁺) and those based on the pressure shift of a Raman line (c-BN, diamond). The calibration of those sensors are presented in detail, and discussion is made on their useful pressure and temperature ranges.     

相对时间法计算凝胶渗透色谱测试大分子分子量和分子量分布

在凝胶渗透色谱(GPC)对大分子的分子量和分子量分布的测试中,本研究利用小分子乙二醇在系统中出峰时间恒定的现象,采用乙二醇的出峰时间作为标识物,将GPC的色谱图转化为相对时间,再以相对时间建立校正曲线,作为计算分子量和分子量分布的依据。此方法解决了在测试色谱图的记录、校准曲线的建立和分子量的计算中以实际时间来表示和计算分子量时,由于GPC泵的重复性不稳定、色谱柱柱效的下降、仪器更换过不同的色谱柱等因素造成的使校正曲线出现偏差、分子量计算结果出现误差等问题。     

Calibration transfer between electronic nose systems for rapid In situ measurement of pulp and paper industry emissions

Electronic nose systems when deployed in network mesh can effectively provide a low budget and onsite solution for the industrial obnoxious gaseous measurement. For accurate and identical prediction capability by all the electronic nose systems, a reliable calibration transfer model needs to be implemented in order to overcome the inherent sensor array variability. In this work, robust regression (RR) is used for calibration transfer between two electronic nose systems using a Box–Behnken (BB) design. Out of the two electronic nose systems, one was trained using industrial gas samples by four artificial neural network models, for the measurement of obnoxious odours emitted from pulp and paper industries. The emissions constitute mainly of hydrogen sulphide (H₂S), methyl mercaptan (MM), dimethyl sulphide (DMS) and dimethyl disulphide (DMDS) in different proportions. A Box–Behnken design consisting of 27 experiment sets based on synthetic gas combinations of H₂S, MM, DMS and DMDS, were conducted for calibration transfer between two identical electronic nose systems. Identical sensors on both the systems were mapped and the prediction models developed using ANN were then transferred to the second system using BB–RR methodology. The results showed successful transmission of prediction models developed for one system to other system, with the mean absolute error between the actual and predicted concentration of analytes in mg L⁻¹ after calibration transfer (on second system) being 0.076, 0.1801, 0.0329, 0.427 for DMS, DMDS, MM, H₂S respectively.     

Calibration transfer employing univariate correction and robust regression

This paper proposes a new method for calibration transfer, which was specifically designed to work with isolated variables, rather than the full spectrum or spectral windows. For this purpose, a univariate procedure is initially employed to correct the spectral measurements of the secondary instrument, given a set of transfer samples. A robust regression technique is then used to obtain a model with low sensitivity with respect to the univariate correction residuals. The proposed method is employed in two case studies involving near infrared spectrometric determination of specific mass, research octane number and naphthenes in gasoline, and moisture and oil in corn. In both cases, better calibration transfer results were obtained in comparison with piecewise direct standardization (PDS). The proposed method should be of a particular value for use with application-targeted instruments that monitor only a small set of spectral variables.     

Determination of Total Sugar in Tobacco by Near-Infrared Spectroscopy and Wavelet Transformation-Based Calibration

Based on wavelet transformation (WT) and mutual information (MI), a simple and effective procedure is proposed for multivariate calibration of near-infrared spectroscopy. In such a procedure, the original spectra of the training set are first transformed into a set of wavelet representations by wavelet prism transform. Then, the MI value between each wavelet coefficient variable and the dependent variable is calculated, resulting in a MI spectrum; by retaining a subset set of coefficients with higher MI, an update training set consisting of wavelet coefficients is obtained and reconstructed/converted back to the original domain. Based on this, a partial least square (PLS) model can be constructed and optimized. The optimal wavelet and decomposition level are determined by experiment. A NIR quantitative problem involving the determination of total sugar in tobacco is used to demonstrate the overall performance of the proposed procedure, named RPLS, meaning PLS in reconstructed original domain coupled with MI-induced variable selection in wavelet domain (RPLS). Three kinds of procedures, that is, conventional full-spectrum PLS in original domain (FPLS), PLS in original domain coupled with MI-induced variable selection (OPLS), and direct PLS in MI-based wavelet coefficients (WPLS), are used as reference. The result confirms that it can build more accurate and robust calibration models without increasing the complexity.     

基于多粒子LIBS谱线的自吸收校正方法研究

为克服自吸收效应对炉渣样品定量分析结果的影响,基于快速模拟退火算法的优化过程,结合等离子体发射光谱的基本理论,发展了一种基于多种粒子发射谱线的自吸收校正算法,给出了该算法的流程图。利用前述自吸收校正算法分别对精炼渣和高炉渣样品的激光诱导等离子体发射光谱强度进行校正,并结合无标分析法,对比分析了自吸收校正算法对样品成分定量分析结果的影响。对比自吸收校正前后的Boltzmann图可以看出,经自吸收校正后,等离子体中各粒子的温度均稳定在11600K左右,结果明显趋于一致。利用自吸收校正后同种粒子的等离子体光谱构建的Boltzmann图中,除一组数据外,其他数据在Boltzmann图中的截距基本一致。利用经自吸收校正后的谱线,对两种炉渣样品成分进行定量分析的结果表明：对于精炼渣,MgO的定量分析结果精度不高,若不分析MgO的含量,则CaO,Al₂O₃和SiO₂等成分定量分析结果的相对误差会明显降低;对于MgO含量为8.49%的高炉渣样品,Al₂O₃定量分析结果的精度最高,相对误差为2.38%,MgO最低,相对误差为28.27%,但基本可以反映出该成分在样品中的含量。     

A fast automatic calibration system for a sound level meter in an anechoic room

A fast automatic calibration system for a sound level meter in an anechoic environment has been developed. The precise and fast generation of the constant frequency-independent acoustic pressure field and reduction of digital voltmeter readout to sound pressure level were achieved by a newly designed software algorithm, assuming the system linearity. The performance test justified the assumed linearity, and showed that the searching speed was sufficiently fast within the small error limit.