Resonance-like enhancement in high-order above threshold ionization of atoms and molecules in intense laser fields.

We investigate the high-order above-threshold ionization (HATI) of atoms (Ar and Xe) and molecules (N2 and O2) subjected to strong laser fields by numerically solving time-dependent Schrödinger equation. It is demonstrated that resonance-like enhancement of groups of adjacent peaks in photoelectron spectrum of HATI is observed for Ar, Xe, and N2, while this peculiar phenomenon is absent for O2, which is in agreement with experimental observation [ Phys. Rev. A88, 021401 (2013)]. In addition, analysis indicates that resonance-like enhancement in HATI spectra of atoms and molecules is closely related to excitation of the high-lying excited states.

Study of the rapid detection of γ-aminobutyric acid in rice wine based on chemometrics using near infrared spectroscopy.

Rice wine, in which γ-aminobutyric acid is present, is beneficial to human health and is one of the three most well-known fermented wines in the world, and is very popular in China. The rapid detection of γ-aminobutyric acid was studied in rice wine using near infrared spectroscopy with an optical fibre probe. Through the selection of detection conditions, including a waveband range of 12500-4000 cm(-1), a scanning duration of 16 scans and a resolution of 8 cm(-1), the near infrared spectrum of rice wine was acquired three times, for every wine sample, with an optical fibre probe. The resulting average value of the spectrum was obtained and the corresponding data were analysed via normalization. By adopting a multivariate calibration partial least squares method (PLS) and establishing a calibration model, the highest precision for γ-aminobutyric acid in rice wine was predicted when the factor coefficient was 17. The overall results demonstrating the content of γ-aminobutyric acid in rice wine was predicted to be between 157.6696-317.5813 mg/L, with a relative standard deviation of prediction between 0.01-5 %, as well as the fact that the single sample measuring time was less than 20 s, prove that near infrared spectroscopy is a rapid, accurate and effective method to adopt for detecting the content of γ-aminobutyric acid in rice wine.

Development and Investigation of Lanthanum Sulfadiazine with Calcium Stearate and Epoxidised Soyabean Oil as Complex Thermal Stabilizers for Stabilizing Poly(vinyl chloride).

Lanthanum sulfadiazine (LaSD) was synthesized from sulfadiazine and lanthanum nitrate using water as solvent under alkaline conditions, and was used as a novel rare earth thermal stabilizer to stabilize poly(vinyl chloride) (PVC). The structure of LaSD was characterized by elemental analysis (EA), Fourier transform infrared spectroscopy (FTIR) and thermo- gravimetric analysis (TGA). The influence of lanthanum sulfadiazine with calcium stearate (CaSt2) and epoxidized soybean oil (ESBO) on stabilizing PVC was studied by using the Congo red test, oven discoloration test, UV-vis spectroscopy and thermal decomposition kinetics. The results showed that the addition of LaSD as a thermal stabilizer can significantly improve the initial whiteness and long-term stability of PVC. In addition, the synergies between LaSD, ESBO, and CaSt2 can provide outstanding improvement in the long-term thermal stability of PVC. When the ratio of LaSD/ESBO/CaSt2 is 1.8/0.6/0.6, its thermal stability time is 2193 s which is the best state for stabilizing PVC. Furthermore, comparing the reaction energy (Ea) and the variations in the conjugate double bond concentration in PVC samples, the order of thermal stability of PVC was PVC/LaSD/ESBO/CaSt2 > PVC/LaSD/ESBO > PVC/LaSD. The thermal stability mechanism of LaSD on PVC was studied by the AgCl precipitation method and FTIR spectrum. The results showed that the action of LaSD on PVC was achieved through replacing unstable chlorine atoms and absorbing hydrogen chloride.

Prediction of enological parameters and discrimination of rice wine age using least-squares support vector machines and near infrared spectroscopy.

The use of least-squares support vector machines (LS-SVM) combined with near-infrared (NIR) spectra for prediction of enological parameters and discrimination of rice wine age is proposed. The scores of the first ten principal components (PCs) derived from PC analysis (PCA) and radial basis function (RBF) were used as input feature subset and kernel function of LS-SVM models, respectively. The optimal parameters, the relative weight of the regression error gamma and the kernel parameter sigma 2, were found from grid search and leave-one-out cross-validation. As compared to partial least-squares (PLS) regression, the performance of LS-SVM was slightly better, with higher determination coefficients for validation ( Rval2) and lower root-mean-square error of validation (RMSEP) for alcohol content, titratable acidity, and pH, respectively. When used to discriminate rice wine age, LS-SVM gave better results than discriminant analysis (DA). On the basis of the results, it was concluded that LS-SVM together with NIR spectroscopy was a reliable and accurate method for rice wine quality estimation.

Cobalt-Catalyzed Selective Synthesis of Isoquinolines Using Picolinamide as a Traceless Directing Group.

Picolinamide has first been employed as a traceless directing group for the cobalt-catalyzed oxidative annulation of benzylamides with alkynes to synthesize isoquinolines through C-H/N-H bonds activation. Oxygen is used as a terminal oxidant. This protocol exhibits good functional group tolerance and excellent regioselectivity. Both terminal and internal alkynes can be efficiently applied to this catalytic system as substrates.

Discrimination of producing area of Chinese Tongshan kaoliang spirit using electronic nose sensing characteristics combined with the chemometrics methods.

In the ancient history of the Yue Nation, the Chinese Tongshan kaoliang spirit (CTKS) has been one of the most popular liquor in the last 2,500 years. The most common fraudulent practice for the commercialization of CTKS is to produce and sell adulterated spirit from different geographical origins. In this study, the use of GC-flash electronic nose (EN) technique combined with chemometrics analysis has proven to provide a rapid tool for the discrimination of CTKS from different geographical origins. The discriminant models were developed by using principal component analysis (PCA), and discriminant factor analysis (DFA). In addition, the volatile organic matters of CTKS were also investigated to find out the difference between samples from varied origins and adulterated liquor. The results demonstrated that the EN technique combined with chemometrics methods could be used to fingerprinting techniques to protect the fame of the prestigious CTKS and to enable its authentication.

Differentiation of Chinese rice wines from different wineries based on mineral elemental fingerprinting.

Discrimination of Chinese rice wines from three well-known wineries ("Guyuelongshan", "Kuaijishan", and "Pagoda") in China has been carried out according to mineral element contents in this study. Nineteen macro and trace mineral elements (Na, Mg, Al, K, Ca, Mn, Fe, Cu, Zn, V, Cr, Co, Ni, As, Se, Mo, Cd, Ba and Pb) were determined by inductively coupled plasma mass spectrometry (ICP-MS) in 117 samples. Then the experimental data were subjected to analysis of variance (ANOVA) and principal component analysis (PCA) to reveal significant differences and potential patterns between samples. Stepwise linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA) were applied to develop classification models and achieved correct classified rates of 100% and 97.4% for the prediction sample set, respectively. The discrimination could be attributed to different raw materials (mainly water) and elaboration processes employed. The results indicate that the element compositions combined with multivariate analysis can be used as fingerprinting techniques to protect prestigious wineries and enable the authenticity of Chinese rice wine.

Fourier transform infrared (FT-IR) imaging coupled with principal component analysis (PCA) for the study of photooxidation of polypropylene.

Fourier transform infrared (FT-IR) imaging coupled with principal component analysis (PCA) is used to characterize the photooxidation of polypropylene (PP) and identify the photooxidative products at different oxidation times. PP slices were exposed to ultraviolet (UV) irradiation for times up to 60 hours and spatially resolved spectra were acquired with a transmission FT-IR imaging system in order to view the steric inhomogeneity of the photooxidation process of PP. The evolution of the oxidized products with irradiation time is shown through the application of PCA. Carboxylic acid is the major oxidized product in the initial period from 0 h to 8 h while ketone becomes the major product with the increase of irradiation time. Carboxylic anhydride is identified for the first time to our knowledge in oxidized PP after 16 h irradiation. Carboxylate ester is also observed in the oxidized PP after 32 h irradiation. Possible mechanisms forming these products have been discussed.

Multivariate classification of rice wines according to ageing time and brand based on amino acid profiles.

Discrimination of Chinese rice wines according to ageing time and brand using amino acid profiles was presented in this study. Free amino acids (16) in 98 rice wines were simultaneously determined using high-performance liquid chromatograph-diode array detection (HPLC-DAD). Then the experimental data was subjected to multivariate analysis. Principal component analysis (PCA) was employed to differentiate samples from various ageing times (3, 9, 11 and 15months) and brands ("pagoda", "kuaijishan", and "guyuelongshan"). Partial least square discriminant analysis (PLS-DA) and full (leave-one-out) cross-validation were used to develop classification models. The overall correct classification rate for different ageing times and brands was 99.7% and 94.9%, respectively. The proposed method shows an effective strategy for the detection of mislabelling of rice wines.

Determination of amino acids in Chinese rice wine by fourier transform near-infrared spectroscopy.

Chinese rice wine is abundant in amino acids. The possibility of quantitative detection of 16 free amino acids (aspartic acid, threonine, serine, glutamic acid, proline, glycine, alanine, valine, methionine, isoleucine, leucine, tyrosine, phenylalanine, lysine, histidine, and arginine) in Chinese rice wine by Fourier transform near-infrared (NIR) spectroscopy was investigated for the first time in this study. A total of 98 samples from vintage 2007 rice wines with different aging times were analyzed by NIR spectroscopy in transmission mode. Calibration models were developed using partial least-squares regression (PLSR) with high-performance liquid chromatography (HPLC) by postcolumn derivatization and diode array detection as a reference method. To validate the calibration models, full cross (leave-one-out) validation was employed. The results showed that the calibration statistics were good (rcal>0.94) for all amino acids except proline, histidine, and arginine. The correlation coefficient in cross validation (rcv) was >0.81 for 12 amino acids. The residual predictive deviation (RPD) value obtained was >1.5 in all amino acids except proline and arginine, and it was >2.0 in 6 amino acids. The results obtained in this study indicated that NIR spectroscopy could be used as an easy, rapid, and novel tool to quantitatively predict free amino acids in Chinese rice wine without sophisticated methods.