红外光学系统光谱透射比校准技术

针对红外光学系统透射比参数无法准确测量的问题,开展了红外光学系统光谱透射比测量和校准技术研究。通过对积分球法、大面积均匀源法等测量方法进行分析,研究构建了基于回返射法的红外光学系统光谱透射比校准装置,并建立了完整的光谱透射比量值溯源和量传链条。利用该装置实现了2μm～14μm波长范围的光谱透射比测量,对测量结果进行不确定度分析,结果为2%。相对于以往的透射比测量装置,该装置的测量结果具有更高的准确性和可靠性。     

Graphene Nanocomposites Based Electrochemical Sensing Platform for Simultaneous Detection of Multi-drugs

Three reduced graphene oxide nanocomposites were employed to achieve the simultaneous electrochemical determination of multi-drugs including acetaminophen (ACTM), carbendazim (CB) and ciprofloxacin (CFX). All nanocomposite modified electrodes showed improved current responses for three drugs. Notably cauliflower-like platinum nanoparticles decorated reduced graphene oxide modified electrode (or Pt−RGO/GCE) exhibited the best performance in terms of electrochemical stability. Using Pt−RGO/GCE, the linear detect ranges of 30–120 μM, 25–115 μM and 10–25 μM, and detection limit values of 3.49, 2.96, and 1.53 μM were achieved for ACTM, CB and CFX respectively. The electrode was further used for the successful determination of above drugs in tap and river water using differential pulse voltammetry. From the obtained results, we believe that Pt-RGO/GCE is highly promising for the fabrication of robust electrochemical sensors for simultaneously determining ACTM, CB and CFX or similar types of drugs in the future.     

离子选择电极阵列土壤中硝态氮测定

土壤硝态氮反映土壤短期氮素供应水平,实时了解土壤硝态氮的含量为精准农业和农业面源污染防控提供支撑,因此,在线实时检测土壤硝态氮方法突破就显得十分迫切。土壤硝态氮中的硝酸根离子在土壤中的高水溶性和流动性为全固态硝酸根离子选择电极高敏感检测土壤中硝态氮提供了条件,固态硝态氮离子选择电极的离子选择膜反应硝酸根离子在被测溶液中的浓度。采用全固态硝酸根离子选择电极,且与温度电极和pH电极融合组成电极阵列对土壤饱和溶液中的硝态根离子进行检测。设计了高输入阻抗运算放大电路对电极信号进行采集,并通过微处理控制蠕动泵完成土壤硝态氮待测溶液连续流动测量及实时传输结果。实验结果表明,电极响应时间≤15 s,斜率-51.63 mV/decade,线性范围10-5-10-2.2 mol/L,最低检测限10-5.23 mol/L。相对标准差在0.78%-4.47%范围内,加标回收率均在90%-110%以内。与国家标准紫外可见分光光度法测试结果相比,相关系数（R2）为0.9952,为土壤硝态氮在现场检测奠定技术基础。     

Simultaneous voltammetric determination of carbendazim and carbaryl in medicinal plant infusions with a boron-doped diamond electrode

This study is aimed to develop an electroanalytical methodology using a boron-doped diamond electrode to determine simultaneously and selectively carbendazim (CBZ) and carbaryl (CAR). In previous studies using cyclic voltammetry oxidation, peaks were observed at 1.03 V (CBZ) and 1.44 V (CAR), with characteristics of an irreversible process controlled by diffusion of species, with a supporting electrolyte of BR buffer (0.1 mol L^?1) and pH adjusted to 6.0. The differences between the potentials for both pesticides, about 400 mV, indicate the possibility of selective determination of CBZ and CAR. The square-wave voltammetric parameters were optimised. The best separation conditions were pH 6.0, square-wave frequency of 100 s^?1, pulse amplitude of 50 mV and scan increment of 2.0 mV. These parameters were used to obtain the calibration curves of CBZ and CAR. An analytical curve was constructed in the range concentration of CBZ of 1.3 mg L^?1 to 15.3 mg L^?1 and CAR of 1.0 mg L^?1 to 11.4 mg L^?1, respectively. The limits of detection (LOD) and limits of quantification (LOQ) for CBZ were 0.40 mg L^?1 and 1.30 mg L^?1, respectively. For CAR, the LOD and LOQ were 0.30 mg L^?1 and 1.00 mg L^?1, respectively. Sensitivity values were 0.78 and 2.60 µA/mg L^?1 for CBZ and CAR, respectively. The electroanalytical method was applied in Mikania glomerata infusions. The recovery values were 106.2% and 116.5% for CBZ and CAR, respectively. The results show that the developed method is suitable for application in medicinal plant samples.     

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We extend the instrumental variable method for the mean regression models to linear quantile regression models with errors-in-variables. The proposed estimator is consistent and asymptotically normally distributed under some fairly general conditions. Moreover, this approach is practical and easy to implement. Simulation studies show that the finite sample performance of the estimator is satisfactory. The method is applied to a real data study of education and wages.     

基于虚拟相位平面的相位展开方法

在基于相位分析的三维测量系统中,为了准确地得到物体的高度,相位展开扮演着很重要的角色。传统的相位展开方法常常需要额外的投影图,而傅里叶变换轮廓术只需要采集一幅或两幅变形条纹图就可以实现对物体轮廓的测量,其方法速度快,易于实现。针对傅里叶变换轮廓术方法计算得到的截断相位分布,本文提出了一种利用截断相位与参考平面相位差值2π的整数倍数获得截断相位的正确级次,辅助相位展开的方法。当被测物体较复杂,或者相位截断次数较多时,该方法在已有参考平面相位的基础上虚拟新的相位平面,依次比较截断相位和虚拟相位,进行多次分级相位展开,结合多个展开相位结果,最终得到正确的展开相位。该方法展开速度快,展开错误不会蔓延传递。仿真和实物实验结果证明了该方法的可行性,说明该方法可用于傅里叶变换轮廓术中进行截断相位的快速展开。     

Multiphase Flow Regime Characterization and Liquid Flow Measurement Using Low-Field Magnetic Resonance Imaging

Multiphase flow metering with operationally robust, low-cost real-time systems that provide accuracy across a broad range of produced volumes and fluid properties, is a requirement across a range of process industries, particularly those concerning petroleum. Especially the wide variety of multiphase flow profiles that can be encountered in the field provides challenges in terms of metering accuracy. Recently, low-field magnetic resonance (MR) measurement technology has been introduced as a feasible solution for the petroleum industry. In this work, we study two phase air-water horizontal flows using MR technology. We show that low-field MR technology applied to multiphase flow has the capability to measure the instantaneous liquid holdup and liquid flow velocity using a constant gradient low flip angle CPMG (LFA-CPMG) pulse sequence. LFA-CPMG allows representative sampling of the correlations between liquid holdup and liquid flow velocity, which allows multiphase flow profiles to be characterized. Flow measurements based on this method allow liquid flow rate determination with an accuracy that is independent of the multiphase flow profile observed in horizontal pipe flow for a wide dynamic range in terms of the average gas and liquid flow rates.     

Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares

A direct, reagent-free, ultraviolet spectroscopic method for the simultaneous determination of nitrate (NO₃⁻), nitrite (NO₂⁻), and salinity in seawater is presented. The method is based on measuring the absorption spectra of the raw seawater range of 200–300 nm, combined with partial least squares (PLS) regression for resolving the spectral overlapping of NO₃⁻, NO₂⁻, and sea salt (or salinity). The interference from chromophoric dissolved organic matter (CDOM) UV absorbance was reduced according to its exponential relationship between 275 and 295 nm. The results of the cross-validation of calibration and the prediction sets were used to select the number of factors (4 for NO₃⁻, NO₂⁻, and salinity) and to optimize the wavelength range (215–240 nm) with a 1 nm wavelength interval. The linear relationship between the predicted and the actual values of NO₃⁻, NO₂⁻, salinity, and the recovery of spiked water samples suggest that the proposed PLS model can be a valuable alternative method to the wet chemical methods. Due to its simplicity and fast response, the proposed PLS model can be used as an algorithm for building nitrate and nitrite sensors. The comparison study of PLS and a classic least squares (CLS) model shows both PLS and CLS can give satisfactory results for predicting NO₃⁻ and salinity. However, for NO₂⁻ in some samples, PLS is superior to CLS, which may be due to the interference from unknown substances not included in the CLS algorithm. The proposed method was applied to the analysis of NO₃⁻, NO₂⁻, and salinity in the Changjiang (Yangtze River) estuary water samples and the results are comparable with that determined by the colorimetric Griess assay.     

Avoiding Pitfalls in Comparison of Activity and Selectivity of Solid Catalysts for Electrochemical HMF Oxidation

Electrocatalytic oxidation of 5-hydroxymethylfurfural (HMF) offers a renewable approach to produce the value-added platform chemical 2,5-furandicarboxylic acid (FDCA). The key for the economic viability of this approach is to develop active and selective electrocatalysts. Nevertheless, a reliable catalyst evaluation protocol is still missing, leading to elusive conclusions on criteria for a high-performing catalyst. Herein, we demonstrate that besides the catalyst identity, secondary parameters such as materials of conductive substrates for the working electrode, concentration of the supporting electrolyte, and electrolyzer configurations have profound impact on the catalyst performance and thus need to be optimized before assessing the true activity of a catalyst. Moreover, we highlight the importance of those secondary parameters in suppressing side reactions, which has long been overlooked. The protocol is validated by evaluating the performance of free-standing Cu-foam, and CuCoO modified with NaPO₂H₂ and Ni, which were immobilized on boron-doped diamond (BDD) electrodes. Recommended practices and figure of merits in carefully evaluating the catalyst performance are proposed.     

Quantum Bayesian computation

Quantum Bayesian computation is an emerging field that levers the computational gains available from quantum computers. They promise to provide an exponential speed-up in Bayesian computation. Our article adds to the literature in three ways. First, we describe how quantum von Neumann measurement provides quantum versions of popular machine learning algorithms such as Markov chain Monte Carlo and deep learning that are fundamental to Bayesian learning. Second, we describe quantum data encoding methods needed to implement quantum machine learning including the counterparts to traditional feature extraction and kernel embeddings methods. Third, we show how quantum algorithms naturally calculate Bayesian quantities of interest such as posterior distributions and marginal likelihoods. Our goal then is to show how quantum algorithms solve statistical machine learning problems. On the theoretical side, we provide quantum versions of high dimensional regression, Gaussian processes and stochastic gradient descent. On the empirical side, we apply a quantum FFT algorithm to Chicago house price data. Finally, we conclude with directions for future research.