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.     

Main Components of Xinjiang Lavender Essential Oil Determined by Partial Least Squares and Near Infrared SpectroscopySCIEI北大核心CSCD

This work was undertaken to establish a quantitative analysis model which can rapid determinate the content of linalool, linalyl acetate of Xinjiang lavender essential oil. Totally 165 lavender essential oil samples were measured by using near infrared absorption spectrum(NIR), after analyzing the near infrared spectral absorption peaks of all samples, lavender essential oil have abundant chemical information and the interference of random noise may be relatively low on the spectral intervals of 7100-4 500 cm(-1). Thus, the PLS models was constructed by using this interval for further analysis. 8 abnormal samples were eliminated. Through the clustering method, 157 lavender essential oil samples were divided into 105 calibration set samples and 52 validation set samples. Gas chromatography mass spectrometry (GC-MS) was used as a tool to determine the content of linalool and linalyl acetate in lavender essential oil. Then the matrix was established with the GC-MS raw data of two compounds in combination with the original NIR data. In order to optimize the model, different pretreatment methods were used to preprocess the raw NIR spectral to contrast the spectral filtering effect, after analysizing the quantitative model results of linalool and linalyl acetate, the root mean square error prediction(RMSEP) of orthogonal signal transformation (OSC) was 0.226, 0.558, spectrally, it was the optimum pretreatment method. In addition, forward interval partial least squares (FiPLS) method was used to exclude the wavelength points which has nothing to do with determination composition or present nonlinear correlation, finally 8 spectral intervals totally 160 wavelength points were obtained as the dataset. Combining the data sets which have optimized by OSC-FiPLS with partial least squares(PLS) to establish a rapid quantitative analysis model for determining the content of linalool and linalyl acetate in Xinjiang lavender essential oil, numbers of hidden variables of two components were 8 in the model. The performance of the model was evaluated according to root mean square error of cross-validation (RMSECV) 9 root mean square error of prediction (RMSEP). In the model, RESECV of linalool and linalyl acetate were 0.170 and 0.416, respectively; RMSEP were 0.188 and 0.364. The results indicated that raw data was pretreated by OSC and FiPLS, the NIR-PLS quantitative analysis model with good robustness, high measurement precision; it could quickly determine the content of linalool and linalyl acetate in lavender essential oil. In addition, the model has a favorable prediction ability. The study also provide a new effective method which could rapid quantitative analysis the major components of Xinjiang lavender essential oil.     

A macroscopic model for an intermediate state between type‐I and type‐II superconductivity

A vectorial nonlocal and nonlinear parabolic problem on a bounded domain for an intermediate state between type‐I and type‐II superconductivity is proposed. The domain is for instance a multiband superconductor that combines the characteristics of both types. The nonlocal term is represented by a (space) convolution with a singular kernel arising in Eringen's model. The nonlinearity is coming from the power law relation by Rhyner. The well‐posedness of the problem is discussed under low regularity assumptions and the error estimate for a semi‐implicit time‐discrete scheme based on backward Euler approximation is established. In the proofs, the monotonicity methods and the Minty–Browder argument are used. © 2015 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 31: 1551–1567, 2015     

Enantioselective Total Synthesis of (−)-Finerenone Using Asymmetric Transfer Hydrogenation

(−)-Finerenone is a nonsteroidal mineralocorticoid receptor antagonist currently in phase III clinical trials for the treatment of chronic kidney disease in type 2 diabetes. It contains an unusual dihydronaphthyridine core. We report a 6-step synthesis of (−)-finerenone, which features an enantioselective partial transfer hydrogenation of a naphthyridine using a chiral phosphoric acid catalyst with a Hantzsch ester. The process is complicated by the fact that the naphthyridine exists as a mixture of two atropisomers that react at different rates and with different selectivities. The intrinsic kinetic resolution was converted into a kinetic dynamic resolution at elevated temperature, which enabled us to obtain (−)-finerenone in both high yield and high enantioselectivity. DFT calculations have revealed the origin of selectivity.     

The Direct Partial Oxidation of Methane to Dimethyl Ether over Pt/Y2O3 Catalysts Using an NO/O2 Shuttle

Using a mixture of NO + O₂ as the oxidant enabled the direct selective oxidation of methane to dimethyl ether (DME) over Pt/Y₂O₃. The reaction was carried out in a fixed bed reactor at 0.1 MPa over a temperature range of 275–375 °C. During the activity tests, the only carbon‐containing products were DME and CO₂. The DME productivity (μmol g_cat^?1 h^?1) was comparable to oxygenate productivities reported in the literature for strong oxidants (N₂O, H₂O₂, O₃). The NO + O₂ mixture formed NO₂, which acted as the oxygen atom carrier for the ultimate oxidant O₂. During the methane partial oxidation reaction, NO and NO₂ were not reduced to N₂. In situ FTIR showed the formation of surface nitrate species, which are considered to be key intermediate species for the selective oxidation.     

A Novel Approach to the Partial Information Decomposition

We consider the “partial information decomposition” (PID) problem, which aims to decompose the information that a set of source random variables provide about a target random variable into separate redundant, synergistic, union, and unique components. In the first part of this paper, we propose a general framework for constructing a multivariate PID. Our framework is defined in terms of a formal analogy with intersection and union from set theory, along with an ordering relation which specifies when one information source is more informative than another. Our definitions are algebraically and axiomatically motivated, and can be generalized to domains beyond Shannon information theory (such as algorithmic information theory and quantum information theory). In the second part of this paper, we use our general framework to define a PID in terms of the well-known Blackwell order, which has a fundamental operational interpretation. We demonstrate our approach on numerous examples and show that it overcomes many drawbacks associated with previous proposals.     

Local Lead–Lag Relationships and Nonlinear Granger Causality: An Empirical Analysis

The Granger causality test is essential for detecting lead–lag relationships between time series. Traditionally, one uses a linear version of the test, essentially based on a linear time series regression, itself being based on autocorrelations and cross-correlations of the series. In the present paper, we employ a local Gaussian approach in an empirical investigation of lead–lag and causality relations. The study is carried out for monthly recorded financial indices for ten countries in Europe, North America, Asia and Australia. The local Gaussian approach makes it possible to examine lead–lag relations locally and separately in the tails and in the center of the return distributions of the series. It is shown that this results in a new and much more detailed picture of these relationships. Typically, the dependence is much stronger in the tails than in the center of the return distributions. It is shown that the ensuing nonlinear Granger causality tests may detect causality where traditional linear tests fail.     

Numerical Approximation and Error Analysis for the Timoshenko Beam Equations with Boundary Feedback

In this paper,the numerical approximation of a Timoshenko beam with bound- ary feedback is considered.We derived a linearized three-level difference scheme on uniform meshes by the method of reduction of order for a Timoshenko beam with boundary feedback.It is proved that the scheme is uniquely solvable,unconditionally stable and second order convergent in L_∞norm by using the discrete energy method. A numerical example is presented to verify the theoretical results.     

局部偏最小二乘回归建模参数对近红外检测结果的影响研究

报道了在局部加权(LWR)回归方法基础上,自主改进的更简单、实用的局部偏最小二乘回归(LPLS)的原理和方法。并以云南优质烤烟为实验材料,在国产光栅漫反射型近红外仪器上,研究了主成分数以及局部建模样品数对检测结果的影响。结果表明：应用交叉验证方法推荐的尼古丁组分模型主成分数并不是最优,通过适当降低主成分数可提高检测效果;局部建模样品数为30～50个时总糖、总氮、尼古丁预测准确度的提高幅度可分别达7%,14%,10%以上。该方法能有效提高近红外数学模型的预测准确度,是建立具有高度适应性近红外数学模型的有效方法。     

一组新氨基酸描述子用于肽定量构效关系研究

用主成分分析从20种天然氨基酸0D～3D结构信息中收集到的共1369个描述子变量得到了一组新氨基酸描述子(SZOTT), 将其用于血管紧张素转化酶抑制剂和苦味二肽结构表征并以偏最小二乘法建立定量构效关系模型, 得复相关系数R_CU²分别为0.894和0.908, 留一法交互检验的复相关系数R_CV²分别为0.828和0.736, 估计均方根误差RMS分别为0.331和0.195. 研究结果表明, SZOTT描述子含信息量大, 操作简便, 结构表达能力强, 有望在多肽定量构效关系研究中得到进一步推广.