Ring effect is defined as the phenomenon that the depth of solar Fraunhofer lines in scattered light is less than those observed in direct sunlight. The aerosol could change the light path and the scattering properties in the atmospheric, and influence Raman Scattering Possibility of the photons, and finally affect the filling-up effect. Aerosol parameters (aerosol optical depth, boundary layer height, single scattering albedo, asymmetric factor) could be obtained by observation of the Ring effect in different aerosol condition. The Ring effect is measured by ground-based MAX-DOAS instrument under clear days and the measurement results is compared with McAritim results. The comparison has a good agreement. Radiation transfer model McArtim is used to study the sensitivity of the Ring effect to the aerosol parameters. The study shows that in most conditions, aerosol optical depth (AOD) and boundary layer (bh) height has a great influence to RSP, and in 90 degree elevation angle, RSP has a decrease of 24.6% when AOD varies from 0.1 to 1, and a decrease of 4.4% when bh varies from 1km to 3 km. The study shows RSP is more sensitive to AOD and boundary layer height, which may provide a new method for aerosol profile.

Terahertz frequency resolution is an important factor affecting substance identification, but the presence of the device reflection within the terahertz time domain spectroscopy systems, causes the presence of a plurality of reflection peaks in the reference and measurement signals with low frequency resolution, because of the length truncation of time domain signal. In order to remove the influence of the reflection peak, this paper proposes a method based on empirical mode decomposition to remove the time domain reflection peak, to improve the terahertz frequency resolution. The time domain reflection peaks are positioned by correlation with the real terahertz peak, calculating the reflection peak upper and lower envelope and an average, obtaining intrinsic mode functions, and alternating reflection peaks with intrinsic mode functions, the effective length of the time domain signal is increased to improve the terahertz frequency resolution. Water vapor in the air terahertz transmission spectroscopy results show that this method can self adaptively remove a plurality of reflection peaks and has good repairing effect on the terahertz time-domain signal; the frequency resolution is increased by 12 times; and the useful information of absorption spectrum is not lost; the absorption peak position and the number is consistent with real spectrum; the terahertz spectrum ability to identify is well preserved.

In order to improve the retrieval accuracy of ocean aerosol , quantitative study was carried out in terms of the multi-spectral polarized properties of the aerosol in visible and near-infrared wavebands. Firstly, an aerosol model and a sea surface model were built. And the vector radiative transfer procedure of light in aerosol and atmosphere-ocean interface was simulated accurately based on the successive order of scattering method. Then from the perspective of the spectrum, the reflectance and polarized reflectance at the top of atmosphere in typical wavebands were quantitatively analyzed. Based on this, the spectrum distribution model of ocean aerosol polarized radiation was presented. And the model was validated with satellite data. Lastly, the influences of aerosol optical depth, viewing angle, chlorophyll a concentration and wind speed on multi-spectral polarized radiation of ocean aerosol were studied. The study shows that the changes of aerosol multi-spectral polarized radiation with wavelength can be best described with power function model when ignoring the absorbtion of atmosphere and solar flare effect in visible and near-infrared wavebands. This phenomenon can be caused by Rayleigh scattering and Mie scattering.The influences of chlorophyll a concentration and wind speed on multi-spectral polarized radiation of ocean aerosol emerge as very different in different wavebands. Specifically, the influences of chlorophyll a concentration on reflectance and polarized reflectance both can be neglected in near-infrared waveband. But in visible waveband, the influence on the reflectance must not be neglected any longer. Due to the increasement of the wind speed, the reflectance and the polarized reflectance increased significantly. But there are differences in the increases in different wavebands. The multi-spectral polarized radiative information of ocean aerosol can embody its own charactersitics effectively. And furthermore, the change of polarized reflectance with each factor has more obvious differences in different wavebands compared with reflectance. As a result, the multi-spectral polarized information of ocean aerosol can be used to retrieve the parameters of the aerosol over the ocean. The achievement of multi-spectral information has great significance for improving the retrieval accuracy of the ocean aerosol.

The interior of the Earth is a high temperature and high pressure environment. High temperatures cause important changes in the physical and chemical properties of minerals. An increase in temperature leads to significant changes in the molecular and lattice vibrations, elasticity, and seismic velocity of minerals. The high temperature vibrational spectroscopy (infrared and Raman) used to study these changes can provide highly significant understanding of the Earth’s interior. During high temperature spectroscopy, the heating device that is used to heat the sample can work at a very high temperature (e.g., 1 500 ℃) because it has a cooling device surrounding it that is used to prevent the temperature of its environments from getting too high. However, radiation from its heating elements is intense and this will shine on and heat the objective lens of the focusing system for the spectroscopic light source, and this would result in damage to the lens. Thus, to avoid damage to the objective lens, an upper limit is placed on the heater temperature. The significance of this work is that it presents a method to exceed the present instrument’s temperature limit so that we can perform in situ spectroscopy on samples at higher temperatures. This work extended the temperature limit for the sample to a higher temperature by using an air blower around the objective lens to create a gas flow around it. The gas flow serves to remove heat from the objective lens by forced convection and its turbulent flow also served to increase the rate of heat transport from the lens to the moving gas stream, which together prevented overheating of the objective lens. Our results have shown that although this device is simple, it was highly effective: for a sample temperature of 1 000 ℃, the objective lens temperature was reduced from ～235 to ～68 ℃. Using this device, we performed in situ high temperature Raman spectroscopy of forsterite up to a sample temperature of 1 300 ℃. The results agreed well with previous studies and demonstrated that with our simple air blower device, we can perform in situ high temperature spectroscopy up to 1 300 ℃ without damaging the objective lens and without expensive components like a high temperature composite objective lens or a long focus objective lens.

Modelling and fitting the reflectance anisotropy of land surfaces is one of the most important issues in remote sensing studies. In the traditional linear kernel-driven model, the most widely used kernel functions are derived from radiative transfer model of vegetation canopy. Therefore, it is not validate to represent the forward scattering effect of snow/ice surfaces. We proposed a method by adding a forward kernel function to the traditional linear kernel-driven model, and validate it with in situ measured bidirectional reflectance factor (BRF) data. The validation results show that this method is efficient for fitting the BRF of snow/ice surfaces (R2=0.997 5, RMSE=0.022 6). We also compared it with empirical functions and the traditional linear kernel-driven model. The results show that: (1) The fitting results of linear kernel-driven model are better than those of empirical functions; (2) The fitting results can be significantly improved by adding the forward kernel function; (3) The fitting results of the improved linear kernel-driven model are stable at different wavelengths.

The frequency stability of the terahertz (THz) radiation source is one of the key issues which directly affect its application regarding to THz imaging, Radar detection, Coherent communication and so on. Based on two-photon light shift effect, the physical model for the frequency shift of optically pumped THz lasers has been built up and the analytical formula for calculating the frequency shift has been derived. Taking the optically pumped methanol(CH3OH) for example, the absorption line of methanol under different pressure has been given, the influence of the bump laser frequency offset and the power of pump laser on the frequency stability of output THz laser have been analyzed quantitatively while the effect of the pressure in THz cavity on the THz laser frequency drift has also been discussed. The results show that THz laser frequency drift increases with the increasing of the bump power, whereas it decreases with the increasing of pressure in THz cavity. The maximum of THz laser frequency drift reaches under the condition that the bump laser frequency drift is equal to a quarter of the absorbed line width of the operating gas when the bump laser frequency offset locates within a certain range. In practice, in order to improve the output frequency stability of THz laser, not only the appropriate working conditions (pressure, temperature) should be chosen, but also the measure for controlling the bump laser frequency shift within a certain range should be taken.

The combustion reaction of raw coals in the air was analyzed withThermal Gravimetric Analyzer 6300 and FTIR (Fourier Transform infrared spectroscopy). The raw coals came from three different sources which were SL lignite, SH bitumite and TT anthracite. The chars were prepared by fixed bed pyrolysis equipment in different reaction temperature. The overlapping peaks were fitted into some sub-peaks by Gaussian function. The aromatic index (R), aromatic structure fused index (D) and organic maturity index (C) were calculated through sub-peaks areas. It showed that three kinds of ignition temperature of SL, SH and TT were 299.3, 408.2 and 441.0 ℃ respectively. The peak temperature of maximum weight loss rate were 348.6, 480.5 and 507.0 ℃ respectively. With the increase of coal rank, both ignition temperature and peak temperature of maximum weight loss rate increased in some degree. The result showed that coal structure was very complex. Vibration absorption peaks of hydroxyl (—OH), aliphatic hydrocarbons (—CH2, —CH3), aromatic (CC), oxygen-containing functional group(CO, C—O) and other major functional groups could be observed in the infrared spectral curves of all samples. With the increase of pyrolysis temperature, infrared vibration absorption peaks of aliphatic hydrocarbons (—CH2—, —CH3) were gradually decreased. the stretching vibration peak of CO which was at 1 700 cm-1 almost disappeared after coked at 550 ℃. SL samples’ absorption peak area infrared curve of oxygen functional groups at 1 000～1 800 cm-1 was more complex. With the increase of coking temperature they changed more significantly compared with others. While peak position and peak intensity for aromatic CC absorption peaks of SH and TT did not change apparently when temperature was changing. Variation trends of main functional groups among three ranks of coals were obviously different with changes of R, D and C values.

The objective of the research was to study the correlations between near infrared spectra and molecular structures of 20 standard amino acids. It was to establish the theoretical foundation for widely use of the amino acids near infrared spectra in animal science, food and medicine. Measurement of the near infrared spectra was performed using a Shimadzu Fourier transform infrared spectrophotometer IRPrestige-21, with FlexIRTM Near-Infrared Fiber Optics module. The spectrometric data acquisitions were performed by Shimadzu IRsolution 1.50 system. The spectrometric room temperature was 25 ℃ and humidity was 38%. Spectra of 20 amino acid standard substances were collected by reflectance mode from 1 000 to 2 502 nm in 8 cm-1 increment. Each sample was scanned in three times, each scan was 50 cycles, and the average value of three times scan result was used for each sample. Based on the differences of amino acids side chains, the correlations between near infrared spectra and molecular structures were compared in the fat family amino acids, aromatic amino acids and heterocycle amino acids. The result shows that all 20 standard amino acids have very specific absorption line patterns. It is distinctly different in these absorption line patterns. Near-infrared spectra of high molecular weight fat family amino acids are affected by side chains. Near-infrared spectra of glycine are affected by carboxyl and amino. The differences of near-infrared spectra between two aromatic amino acids are in benzene ring. —OH groups on benzene ring of tyrosine lower the symmetry of benzene molecule. It leads to the emergence of more vibration absorption. Near-infrared spectra of heterocycle amino acids are distinctly different in 1 000～2 502 nm because of side chains. In conclusion, there are four different characteristic spectral regions. The first one is 1 050～1 200 nm spectral region which is composed mainly of second-order frequency doubling of C—H group. The second is 1 300～1 500 nm spectral region which is composed mainly of combination tune of C—H group. Due to side chains of amino acid have different molecular structure, they yield a complete set of near infrared fingerprint spectra between 1 600～1 850 and 2 000～2 502 nm. In another words, these four characteristic regions of near infrared spectra can be used to build the model of qualitative analysis and quantitative analysis for amino acid, and improves the accuracy and reliability of model.

Near-infrared(NIR)As a fast and non-destructive testing technology, spectroscopy techniques is very suitable for pharmaceutical discrimination. Autoencoder network, as a hot research topic, has drawn widespread attention in machine learning research in recent years. Compared with traditional surface learning algorithm models, Autoencoder network has more powerful modeling capability as a typical deep networks model. Based on the unsupervised greedy layer-wise pre-training, autoencoder trains the network layer by layer while minimizing the error in reconstructing. Each layer is pre-trained with an unsupervised learning algorithm, learning a nonlinear transformation of the input of each layer which is the output of the previous layer. Pre-whitening process could get the inner structural features of the data more effectively. The supervised fine-tuning is followed with the unsupervised pre-training which sets the stage for a final training phase. The deep architecture is fine-tuned with respect to a supervised training criterion with gradient-based optimization. In this paper, firstly, the preprocessing step and pre-whitening transformation were used to treat near-infrared spectroscopy data of erythromycin ethylsuccinate, The pre-whitening transformation would reduce the correlation of the features, which gave each feature the same variance. Experimental results showed that the pre-whitening process had improved the classification accuracy of Sparse Denoising Autoencoder (SDAE) effectively. The SDAE with two hidden layers combined with pre-whitening was used to build the classification model for the identification of counterfeit pharmaceutical. The BP neural networks was compared with SVM algorithm for the classification accuracy and mean absolute difference (MAD). SDAE algorithm had higher classification accuracy than BP neural networks which had the same network structure with the SDAE networks, and SDAE algorithm also performed better than the SVM algorithm when the train datasets achieved a certain amount. As to the generalization performances, SDAE algorithm had less mean absolute difference of classification accuracy than SVM and BP Neural Networks. This result showed that SDAE algorithm could be effectively used to discriminate the counterfeit pharmaceutical.

Based on Fourier transform infrared (FTIR) and Raman spectroscopy (FT - Raman), the effective medicinal composition and its content change of Qi chrysanthemum are directly and quickly determined among the virus-free breeding and sulfur smoked samples of three different groups. FTIR and FT-Raman spectra of three groups of Qi chrysanthemum sample are compared and analyzed. The results show that the intensities of multiple infrared absorption peaks are obvious different within the range of 1 800~500 cm-1 and the characteristic peak shapes are slightly different in the FTIR spectra of the three groups with obvious differences of characteristic peak shapes in FT - Raman spectrum have. FTIR and FT - Raman spectrum directly reflect that the stem tip virus-free breeding will make the volatile oil, flavonoids and other medicinal component content increase in Qi Chrysanthemum, but the sulfur smoked reduce. The FTIR, FT Raman spectroscopy for detection of effective medicinal composition changes in Qi Chrysanthemum caused by virus-free breeding or sulfur smoked establishes a scientific basis, also an effective method to test their component content.

Extreme learning machine (ELM) has been applied in near infrared spectral analysis as a novel chemometric method which attracted the attentions of various researchers. However, the dimension of spectral data is usually very high while more hidden nodes should be incorporated in original ELM model for spectral data. Thus the problems of high dimension and high colinearity in the output matrix of hidden layer of ELM model are inevitable. The solutions obtained with the existing Moore-Penrose generalized inverse can be ill-conditional due to the high dimension and high colinearity in the hidden layer output matrix. This study aims to propose an improved ELM to build spectral regression model. The proposed method firstly uses extreme learning machine (ELM) to relate spectral variables to response variable; then the output of each hidden node are treated as new variables; VIP-SPLS ( improved stacked PLS based on variable importance in the projection) proposed by our group recently is used to build the regression model between those new variables and the response variable. In this paper, this method is called as improved ELM (iELM). VIP-SPLS model can fully utilize the output information of each hidden node and can effectively solve the problems of high dimension and high colineariy. At the same time, VIP-SPLS also has the advantage of model ensemble. Therefore, the performance of ELM model used for spectral data can be improved if the VIP-SPLS is incorporated to relate the hidden layer output matrix and response variable. The proposed method is applied to a commonly used benchmark NIR spectral data for evaluation. The results demonstrate that the precision improvement of iELM model is 29.06% to PLS model and 27.47% to original ELM model, respectively.

Di-n-butyl phthalate ( DBP ) is one kind of Phthalate esters ( PEs ) widely employed as plasticizers in the production of polymeric materials. PEs are dialkyl and alkyl aryl esters of 1,2-Benzenedi-carboxylic acid, which comprise a wide group of compounds. Since these compounds are not linked to the polymeric matrix, they can migrate from their original containers to the surrounding environment, resulting in ubiquitous environmental pollutants. The infrared vibration spectra of isolated DBP was assigned according to DFT calculations by Gaussesview 5.0 software with First Principles. The method of B3LYP of the density functional theory ( DFT ) at 6-31G* level has been used to calculate its geometrical parameters and convergence criteria. Compared with the Fourier transform infrared spectrum of DBP in 400~4 000 cm-1 band, the characteristic absorption peaks of the simulation spectrum were broadly in agreement, and the position of the peaks were almost corresponding to each other. Considering the influence of the experimental conditions and temperature, theoretical calculations were in good agreement with experimental data. According to the linear fitting of the peak position of the experimental spectra with respect to the theoretical spectra, the correlation degree is more than 99%. This research provides a theoretical basis to the detection and analysis of DBP.

Traditional coal origin identification method generally take the calorific value, volatiles, caking index, hardgrove index and crucible swelling number as the classification index, process complicated, use manpower and material resources and can’t get coal sample origin directly, take advantages of the near-infrared spectrum technology fast nondestructive testing, due to be collected in the original spectrum that contains some or false spectral data, using Leave-one-out cross validation based on SVM to eliminate abnormal sample of spectral data set, get the correct spectral information of coal sample spectra data sets, and construct the qualitative analysis model based on SVM algorithm and LVQ algorithm, complete based on near-infrared spectral analysis technology of coal origin identification, don’t need to make summary and coal samples of various indicators forecast. In view of the random parameter optimization problems in SVM model, the PSO-SVM model of loss parameters (C) and the radius of kernel function (g) are improved, get the optimal parameters, finally, calculation accuracy of the method above contrast model is introduced to evaluate and analysis. Experiments collect the near infrared spectrum of Canada, Russia, Australia, Indonesia and China’s five regions, all the data sets, a total of 305 samples, of which 10 simples is abnormal samples and the first 31 groups of the coal spectra were selected as training samples, 6 sets of data after as test samples. Results show that the classification accuracy of classification model can achieve 75% above, including the analysis of the SVM model based on PSO algorithm to improve the accuracy can reach 96.67%, only a sample appear problem, it will be realized quickly and efficiently based on near-infrared spectral analysis technology of coal origin identification.

Currently on the market, the sale of olive oil is mainly divided into extra virgin olive oil and common virgin olive oil. In order to identify the qualities of two different olive oils, a new method to identify the quality of olive oil with siPLS-IRIV-PCA algorithm is developed. Based on the near infrared spectral data of olive oil, the efficient spectral subintervals are selected with a synergy interval partial least squares (siPLS). The performance of the model is evaluated by using the root mean square error of cross-validation (RMSECV). The characteristic wavelengths are selected from the efficient spectral subintervals by iteratively retains informative variables (IRIV) algorithm. Principal component analysis (PCA) model is constructed based on the selected characteristic wavelengths. The samples of 90 groups of extra virgin olive oil and 90 groups of common olive oil are identified. PCA uses 1 427 wavelength variables as input variables and the contribution rates of the first two principal components are 51.891 8% and 26.473 2% respectively. siPLS-PCA uses 408 wavelength variables as input variables and the contribution rates of the first two principal components are 56.039 1% and 36.2355%. siPLS-IRIV-PCA uses 6 wavelength variables as input variables and the contribution rates of the first two principal components are 66.347 6% and 32.3043%. The result shows that, compared with PCA and siPLS-PCA, siPLS-IRIV-PCA has the best identification performance. The method is simple and convenient and has a high identification degree which offers a new approach to identify the quality of olive oil.

Rapid classification of leather variety means important to product process control, trading process and market surveillance. There is no official detection standard on classification of leather variety for the present. By now the testers use organoleptic method, burning method, chemical dissolution method, microscope method, or combination of them, to give a convincing result. The testers are required to highly sufficiently experienced, and not influenced by subjective factors. It also costs too much time. For the purpose of this research, spectra of five common varieties of leather samples (full-grain leather, split leather, sheep leather, reborn leather and manmade leather) were collected from market. Discriminant analysis combined with pre-processing method, including multiplicative signal correction (MSC), standard normal variate (SNV), first derivative and second derivative were used to classify the spectra above. It shows that the above five varieties of leather overlapped seriously in the same space. But manmade leather can be easily distinguished from the other four leather varieties using rear spectra, with the misclassified percent of 1.2%. The last four leather varieties covered each other partly in the same space, classify of any two of them can reach a lower misclassified percent, about 1.3%～17.9%. Different pre-processing method affected the discriminantion model positively or negatively with no regularity. None of these pre-processing methods was found to give a positive effect in a stable and persistent way. It can be concluded that it is feasible to discriminate the common leather varieties by near infrared Spectroscopy. All of the samples were taken from the finish products in the market (eg, handbag, belt, leather coat), which were processed in different ways (eg. tanning, knurling, dyeing). The different processes of the samples could bring an unforeseeable influence to the model which may be reduced by some method, for example, increasing the number and variety of samples.

In the process of evidence identification, detecting chemical composition of evidence with instrumental analysis techniques will help get more information relevant to the case quickly and accurately, while the commonly used techniques are chromatography, mass spectrometry and spectroscopy techniques. Forensic science laboratory relates to the identification of evidence from a wide range of complex situations, we need to decide what kind of analytical methods according to the type of physical evidence and instrument characteristics. For example, with the advantages of high resolution, high sensitivity, and strong ability to analysis; gas chromatography-mass spectrometry is often used to detect evidence of fire scene such as flammable liquids. The more common scenarios of the application in forensic science laboratory is related to the case of various organic certificate (ink, paint, plastic, etc.) and inorganic (mineral, inorganic fillers, etc.) for quick and efficient analysis. Infrared spectroscopy is one of the most effective conventional analysis methods to identify and determine the molecular structure of the compound, whihc is especially widely used in the field of forensic science evidence identification. The infrared spectroscopy technique can be used to determine the type of evidence, which also serves as an effective means of test; the test results can offer evidence to the court to settle a lawsuit. This paper reviewed the application status and latest research advances of infrared spectroscopy technique in forensic document examination, oil test, plastic test, paint inspection, fiber inspection, common areas of drugs and other evidence examination, and prospected infrared spectroscopy technology in the field of evidence identification, from a practical point of view to provide infrared spectroscopy research profile for the scientific research personnel.

To research surface-enhanced Raman scattering effect of different diameters’ polystyrene nanospheres (Ag-coated) substrates, we had prepared a new surface-enhanced Raman scattering substrate. It was prepared by using spin-coating and self-assembled to form monolayer and hexagonal close-packed (HCP) order colloidal-crystal films with PS nanospheres of different diameters. Then, a 30 nm Ag film was deposited on the PS arrays with magnetron sputtering. We detected Raman scattered spectrum by means of Roman spectroscopy instrument with Rhodamine R6G as a probe molecule, and the conclusion was drawn that all the substrates of Ag-coated PS nanospheres displayed stronger Raman enhancement. With the increase of the diameter of the microspheres, the degree of fluctuation of polystyrene nanospheres array was continuously strengthened (increasing roughness), and the SERS signal was enhanced gradually. The signal peak reached a maximum when the ball diameter was 600 nm, and then we aquired an optimal SERS substrate. Simultaneously, we found that the SERS spectra of R6G of a high signal to noise ratio was obtained on the substrate, and associated with the benzene ring within a range of CC double bond stretching vibration characteristic spectrum and the inner surface and the outer surface deformation vibration characteristic spectra were significantly enhanced. The single and large-scale Raman scattering substrate presents especial nanostructure of high and low distribution. The depth and the gap between different PS microspheres show the obvious differences, which can significantly improve the surface morphology structure of Ag film and Raman scattering effect of PS nanospheres substrate. The substrate presenting special arrays’ structure has significantly great potential in exploring molecule of chemical and biological filed.

Raman spectroscopy which belongs to scattering spectroscopy obtained molecular vibrational and rotational information to achieve detection and analysis of molecular structure and corresponding changes through recording the frequency shift when light interacted with materials. Compared with routine biochemical analysis, Raman spectroscopy has the advantage of non-invasive, label-free and no sample requirement. Raman spectroscopy has been widely applied in biomedical field such as human tissue, organs, cells and human body fluids for disease diagnosis. This article mainly focuses on recent research advances of Raman spectroscopy in human semen. Firstly, Raman spectroscopy(including surface-enhanced Raman spectroscopy, SERS) employed in forensic science for semen analysis, and some related data processing methods were introduced, then Raman spectroscopy involved investigations of male fertility was highlighted, more specifically, the Raman-based qualitative and quantitative analysis which assist the objective detection and evaluation of male fertility. Furthermore, studies of single sperm cell based on micro-Raman system to characterize and evaluate sperm quality and the preliminarily obtained Raman biomarkers which indicate high-quality sperm cell were introduced. Finally, the potential development of Raman spectroscopy involved in reproduction and fertility field was also discussed.

Non-destructive measurement methods including video microscopy (VM), Raman spectrometer (RS), and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) were employed to analyze the printing materials of a green curled-up dragon stamp sample from the late Qing Dynasty in terms of the paper and ink. The results indicated that the plate-making process of the sample belonged to handcrafted gravure while the slender and dense paper fiber with no coating, watermark, or gumming. Elements of Al and Si were inspected in fillers of paper, therefore, it could be inferred that kaolin (Al2O3·2SiO2·2H2O) was the filler of paper. Green ink was made up of blue pigment Prussian Blue (Fe4［Fe(CN)6］3·14-16H2O) and yellow pigment Lead(II) chromate(PbCrO4). According to theories of additive color and subtractive color, ink presented green color due to the effect of Prussian blue and Lead chromate mixed together. Elements of Na, Mg, S, Cl, K, Ca, V, Zn and Ba were measured from fillers of the ink and it could be inferred that MgCO3, BaSO4, CaCO3 and other substances might be contained in ink fillers. This study with three techniques mentioned above is viable and it has a broad application in non-destructive analysis of printing and paper-based artwork.

Accurate identification of daughter minerals existed in fluid inclusions has a great significance for obtaining the geochemical information on fluids related to processes of sedimentation, diagenesis or mineralization, and using micro-Raman spectra to identify the types of daughter minerals is in-situ, nondestructive, high sensitive, good-stability, quick and convenient, so which has been widely used at present. In this paper, we used micro-Raman spectra, for the first time, to identify the types of daughter minerals in primary inclusions, which trapped in rock salt from the lower submember of Eocene Sha-4 member of Shahejie Formation (Es4x) in Dongying sag. On this basis, the indication significances of these daughter minerals to geochemical characteristics of paleo-brines in Eocene salt lake of Dongying sag were discussed in detail. The results show that anhydrite and starkeyite are the main daughter minerals in primary inclusions in rock salt of Es4x. Among them, anhydrite has strongest Raman band at 1 018 cm-1 and other five additional weaker bands at 500, 611, 629, 676, 1 131 cm-1, respectively. Starkeyite has strongest Raman band at 1 000 cm-1 and other three additional weaker bands at 462, 618, 1 156 cm-1. These two kinds of daughter minerals existed in primary inclusions indicate that salt lake brines contained small amount of compositions of CaSO4 and MgSO4, the brines just reached early stage of evapo-concentrated precipitations at this moment, that is, the end of sulfates deposit and the beginning of early stage of rock salt deposit, and halite was the main product of brines precipitation. Moreover, based on the precipitation temperature of anhydrite and starkeyite, the temperature of paleo-brines of Eocene salt lake during the early stage of evapo-concentrated precipitations was determined, namely, the values of temperature ranged from 37 to 61 ℃ and sedimentary environment was featured by drought.

In this research, the surface enhanced Raman spectroscopy (SERS) technique is used to develop a nondestructive and fast detecting method for the detection of residual chlorpyrifos on spinach. Silver colloids used for SERS spectroscopy is prepared by the reduction of silver nitrate with hydroxylamine hydrochloride at alkaline pH. The prepared silver colloids are dropped onto spinach samples, then the SERS spectra are collected non-destructively with a self-developed Raman system. This method can be made without physical contact to samples, and rapidly completed without time-consuming sample pre-treatments, and suited to the development of real-time on-line detection methods for trace pesticide residues. SERS signals are collected from 20 points on each spinach sample with 450 mW laser power and 2.5 s exposure time. Chlorpyrifos concentrations in 24 samples are determined with gas chromatography after SERS spectra taken. Savitzky-Golay (SG) smoothing filter and effective peak linear fitting method are used to remove the random noise and the fluorescence background for improving the accuracy of SERS results. The SERS signals are collected from different parts of 50 spinach samples with the same concentration of chlorpyrifos but at different fresh degrees. The relative standard deviation (RSD) of chlorpyrifos' characteristic peak intensities is 13.4%. Although the differences of samples lead to differences in the curves of Raman spectrum, they have little influence on the characteristic peak intensities, which indicates the stability of the proposed detecting method. After the fluorescent background removed, the 20 curves of each sample are averaged. Correlation analysis is done between chlorpyrifos concentration and signal intensity at every Raman shift. Results show that correlation coefficients are higher than 0.85 in the range of 615.5~626.4 cm-1. Signals in this range are used to establish multiple linear regression (MLR) model for the prediction of residual chlorpyrifos. MLR model was developed for chlorpyrifos concentration versus Raman signal intensity at 615.5~626.4 cm-1 for predicting residual chlorpyrifos content in samples, the correlation coefficients of calibration (RC) and validation (RP) are 0.961 and 0.954, which indicate a good linear relationships between them. The minimum detectable threshold for this method is 0.05 mg·kg-1 which is close to the value limited by the national standard of China (0.1 mg·kg-1 for chlorpyrifos in spinach). The proposed practical method is sample, fast, without sample preparation, thus it shows great potential in safety detection of fruits and vegetables.

New complex ［Tb(2,2′-oba)2(phen)2］-(H+3O) (2,2′-oba=2,2′-oxybis(benzoic acid), phen=1,10-phenanthroline) was synthesized under hydrothermal condition and characterized with X-ray single crystal diffraction. Complex reveals mononuclear structure containing TbO4N4 unit. Complex displays the emission peaks at 489, 546, 584 and 622 nm, corresponding to the 5D4→7FJ(J=6-3) transitions of Tb(Ⅲ) ion. The emission band at 546 nm corresponds to the 5D4→7F5 transition of the Tb(Ⅲ) ion, which gives an intense green luminescence output for the solid sample. The recognition for metal ions was discussed with fluorescent spectroscopy. The results show that it has high selectivity for Fe3+ via a fluorescence quenching mechanism. Luminescent investigations reveal that it can detect Fe3+ with relatively high sensitivity and selectivity, even when pH 4.0～8.0, which leads to its application in biotic and environmental system.

Compared with traditional quantum dots, carbon quantum dots (CQDs) have aroused tremendous research interest among scientists as new fluorescent carbon nanomaterials due to their unique properties (easy surface functionalization, good biocompatibility, and low toxicity). The nitrogen-doped carbon quantum dots (NCDs) was synthesized with one-step hydrothermal treatment with citric acid as carbon source, and ammonia as nitrogen source. The obtained NCDs exhibited excellent water-solubility and high stability. High-resolution Transmission electron microscopy (HRTEM) image showed that the diameter of particles was about 3nm. Fourier transform infrared (FIIR) and X-ray photoelectron spectroscopy (XPS) spectra analysis demonstrated that the NCDs are functionalized with hydroxyl, amino, carbonyl, and carboxylic acid groups, which indicated NCDs has better water-solubility. It was further demonstrated that such NCDs can serve as effective fluorescent sensing platform for Hg2+ ions detection with sensitivity and selectivity. In a PBS butter solution (0.1 mol·L-1 pH 7.0), the fluorescence quenching ratio (F/F0) indicated linear responses with Hg2+ concentration ranging from 0.001 to 0.1 μmol·L-1, with the detection limit of 2.1 nmol·L-1. The fluorescence technique was superior in terms of sensitivity, selectivity and simplicity. It was successfully applied to determination of Hg2+ in samples.

The various characteristics of DOM have great impact on the transformation process of contaminants in soil due to the generation of the feedback regulation in cycles of plant, Rhizosphere soil and environmental contaminants. Currently, more attention was paid on contaminants behaviors of adsorption, transformation, accumulation and detoxification than DOM derived from Rhizosphere soil. The chemical speciation of lead/cadmium and growth efficiency related variations were revealed in the growth process of Calendula officinalis seedlings, and the spectral characteristics of DOM in Rhizosphere loess were discussed with UV, FT-IR and 3D-EEMs spectra. The results showed: the dominant contents of lead/cadmium are in residual and exchangeable speciation, and the exchangeable contents increase greatly after the growth of Calendula officinalis seedlings. It causes negative effects on the height and emergency rate of Calendula officinalis seedlings with lead/cadmium, and the Calendula officinalis is able to positively improve loess characteristics. The root of Calendula officinalis appears to be longer, thinner and flexuous. The maximum absorption band of DOM in UV spectra locates in 200~240 nm, and the sharper and greater intensity of peaks can be detected under lead/cadmium stress. The absorption peaks in FT-IR spectra move from 3 444 and 1 637 to 3 440 and 1 645 cm-1, respectively, indicating the combination effects between metal ions and functional groups of—OH and CO. The dominant fluorescence peaks of DOM are found to be aroundλex/em=240/430, described as fulvic-acid like components, and metals in loess affect more on peaks intensity than locations. The characteristics of DOM in Rhizosphere loess of Calendula officinalis seedlings contain much micro-eco-environmental information, and the spectral approaches are efficient to reveal the relationship between DOM and chemical speciation of lead/cadmium.

Rapid source identification of mine water inrush has great significance for early warning and rescuing after the mine water inrush. Conventional method taking the concentration of ions as the discriminant factor takes such a long time that a method of rapid source identification of mine water inrush is in urgent need. This method is combined with Laser induced fluorescence (LIF) technology and Partial Least Squares-Discriminant Analysis (PLS-DA) algorithm. In the experiment, 405 nm laser was used to excite the water and 100 groups of fluorescence spectrum from 5 different aquifer of the mine were obtained. According to the spectra curve features, the data was compressed to obtain proper spectral data. 15 groups of spectrum of each water inrush samples were applied, with a total of 75 groups of spectrum as the prediction set while the rest of 25 groups of spectrum as the test set. To verify the experimental result, an experimental model was built with soft independent modeling of class analogy (SIMCA) to compare with PLS-DA. The result shows that the fluorescence spectra of different aquifer water samples is of great difference, without any pre-treatment, the PLS-DA algorithm based on the PLS model has higher modeling accuracy compared with SIMCA algorithm, which reaches to 100%, the validation results and the correlation of separation of variables are both more than 0.951, the RMSECV and RMSEP are both less than 0.123, using the model to identify the 5 water samples of test set, the accuracy are up to 100%.

As the representative component for eco-environmental researchers, dissolved organic matter (DOM) is playing a significant role for the indication effect on environmental quality and efficiency assessment on remediation approaches. Nowadays, it lacks related investigation on DOM derived from rivers and sediments, and the advanced discussion is in urgent need because of the dynamic variations of experimental target, such as spatial-temporal condition, hydrological condition, environmental condition and research dimension. The spectral approaches, including elemental analysis, ultraviolet spectra (UV), Fourier transform infrared spectroscopy (FT-IR), Raman spectra (Raman), three dimensional excitation emission matrix fluorescence spectroscopy (3D-EEMs) and nuclear magnetic resonance (NMR) were used to reveal the characteristics of DOM derived from water and sediment samples in the intersection zone of Jing River and Wei River (Gaoling District, Xi’an City, Shaanxi Province). The results showed: the ratios of H/C and N/C for DOM in sediment are higher than that of DOM in water, suggesting the saturation degree in DOM from sediment are higher with more content of nitrogen. The UV absorbance of DOM decreases with the increasing of wave length, and obvious absorption region (240～310 nm) appears in DOM from sediment. The functional groups of —OH, CC and C—O could be found in DOM from FTIR spectra, and the characteristics might be more complicated in sediment for various peak shapes and intensities. The Raman spectra of DOM in water are similar to that of the sediment. The fluorescence peaks of DOM in water are regarded as visible tryptophane-like and UV fulvic-like components, mainly from terrestrial source; while fluorescence peaks of DOM in sediment belong to UV fulvic-like fluorescence without protein-like fluorescence peaks being detected. The principal carbon chains are similar in DOM samples from water and sediment, and the aliphatic characteristics are more obvious for the latter, which contains more carbohydrate-binding hydrogen than aromatic-binding hydrogen and γ-H. It proves that DOM in water mainly comes from terrestrial source, and DOM in sediment is more complicated and fresher. The achievements are significant to reveal the microscopic characteristics and environmental behavior of DOM in representative systems.

In the study, N-t-butyl-2-benzothiazole sulfenimide (TBSI) was prepared by NS-acetic anhydride method with acetic anhydride as solvent. It was detected with FTIR, XRD, UV-Vis, TG-DTA. Micro-structure and essence disciplinarian of them were disclosed. Chemical bond types into TBSI molecule were revealed with FTIR. TBSI phase composition and structure were revealed with crystallographic data from XRD detecting such as cell parameters and crystal face index. The phase composition and qualitative identification of TBSI structure were completed. The absorption peaks were detected by UV-vis at 228.3, 281.3 and 298.3 nm, respectively caused by n→σ*, π→π*, n→π* electron transition. It could provide basic data with the enterprise of ZBPD product quality inspection. Two kinds of information were detected with TG-DTA as quality change and thermal effect. There were three absorption peaks of 46.5, 188.9, 368. 5 ℃ due to a few residual solvent volatilization in the sample, phase transition peak and decomposition peak. The decomposition temperature of TBSI was very high. It could provided reference with research on rubber vulcanizing properties with TBSI on rubber vulcanizing machine. This study could provide basis experimental data on the enterprises to designate the working standard tracing detection of TBSI industrialized production. Performance index of TBSI was judged. The project of TBSI industry standard could be declared by the enterprises, written a draft standard.

The structure characteristic of soybean selenoprotein and soy protein isolate (SPI) were investigated with fluorescence, ultraviolet and Fourier transform infrared (FTIR) spectrum. The unfolding process of two proteins was analyzed with fluorescence phase diagram method. The stability of emulsion properties and the influence of concentration, temperature and pH on the conformation of soy selenoproteins were also determined. The results indicated that the covalent disulfide bond of soybean selenoprotein molecules was damaged; the hydrogen bonding become weak; the hydrophobic interactions were enhanced and the protein chain molecules were extended. Soybean selenoprotein displayed only “folding” and “loose” state in solution, which illustrated soybean selenoprotein more tend to hydrolysis when compared with soybean protein. With temperature increasing, the fluorescence quenching effect occurred and the hydrophobicity of soy selenoproteins was also gradually increased, which reflected the protein molecules tends to be folded. In the range of pH 2.8～8.0, the Trp residue of soybean selenoprotein was mainly distributed in the polarity of the external environment and presented different conformational change on both sides of the isoelectric point under different pH value. In acidic environment, the soybean selenoprotein was easy to appear conformational transition from loose to fold. But it was conducive for soybean selenoprotein to existence in loose structure in alkaline conditions. In addition, the emulsifying properties of soybean selenoprotein were analyzed based on UV spectral data. Results showed that lower temperature helps to enhancement the emulsification but unfavorable the stability of the soybean selenoprotein.

The interaction between colistin sulfate (CS) with bovine serum albumin in physiological buffer (pH 7.4) was investigated with resonance light scattering spectroscopy at 298, 310, and 318 K. The analysis of data indicated that quenching mechanism of BSA-CS was probably static. The value of n was approximately 1, indicating there was only a single class of binding sites on BSA for CS compounds. The thermodynamic parameters were calculated at different temperatures, implying that the interaction was spontaneous and electrostatic force played major role in the binding between CS and BSA. The values of nH were equal to 1 at different temperatures, indicating there was non-cooperative reaction between BSA and CS. The feasibility of resonance light scattering spectroscopy was verified by fluorescence quenching spectroscopy. The quenching reactive parameters (KSV, Kq, n, Ka) from two methods were similar, suggesting resonance light scattering spectroscopy could be used to study the binding interaction between protein and drugs. Resonance light scattering spectroscopy can be used to explore the substance without intrinsic fluorescence, suggesting that the application of resonance light scattering spectroscopy broadens the understanding of the interaction between small molecules and protein.

The aquatic landscape plants lotus and water lily were selected to repair the heavy metal in black odorous river sediments. With ICP-AES inductively coupled full spectrum of direct reading plasma emission spectrometry, the total and forms of content of heavy metals Cd, Cr, Cu, Ni, Pb in sediment and plants, the distribution of heavy metals in plants to were determined .The results showed that the average removal rate of the lotus in terms of the removal of heavy metals in the sediments was 20.42% while that of water lily was 18.23%; after lotus and water lilies were planted, the forms of content of heavy metals in sediments were decreased, the phytoremediation of main forms of Cr, Pb, Ni in sediments were theresidual state; the main forms of Cd, Cu were extractable. The distribution of Cu, Ni among the water lilies was stem<leaf<root, Cd and Pb was leaf<stem<root, Cr was stem<root<leaf. The distribution of Cr, Ni in the lotus for root<leaf<stem, Cu was leaf<root<stem, Cd, Pb were mainly in the lotus leaf tissue.

Spectral data or chrominance data acquired with color measurement device is able to objectively characterize the true color information of the object. As to the measuring target that without direct contact with the measuring instrument, it needs to adopt the non-contact color measurement method to obtain the color information.The spectral irradiance theoretical analysis shows that the changes of the color illumination distance, measuring distance and exposure time have greater impact on the measurement results. However, there is no in-depth study on the influence of the changes of measuring parameters for the measured results. In order to get the most accurate measurement results in the process of non-contact color measurement, parameter optimization study based on orthogonal experiment was proposed. Experiment with different combinations of parameters was conducted to obtain the color information of ColorChecker via PR705 spectroradiometer with range analysis and variance analysis method.Experimental results show that the minimum color difference of measured value and the standard value is 0.878 8ΔE, and the maximum color difference is 1.543 1ΔE. Data results show that the proposed method can effectively select the best combination of parameters, and to analyze the impact of various parameters on the result.

Porphyrin is a kind of photosensitizer for photodynamic therapy of cancer. Many porphyrin derivatives have been used in clinical treatment. Human Serum Albumin (HSA) is the carrier of drug transportation. Therefore, investigation on the interaction of porphyrin with HSA is very important to understand the pharmacokinetic of the porphyrin. In this paper, a new water-soluble carboxyl porphyrins, meso-tetrakis(carboxyl) zinc(Ⅱ) porphyrin (2-Zn), was synthesized and characterized. Its interaction with human serum albumin (HSA)was investigated by UV-Vis absorption spectra, fluorescence spectra, circular dichroism (CD) spectra and molecular modeling. The results indicated that the fluorescence quenching of HSA by 2-Zn was a static process with the quenching constants are 1.96×104 L·mol-1 (298 K) and 1.37×104 L·mol-1 (310 K) and the binding constants were calculated to be 1.93×104 L·mol-1 (298 K) and 1.50×104 L·mol-1 (310 K). According to the Van’t Hoff equation, the thermodynamic parameters were characterized by negative enthalpy (ΔH=-16.132 kJ·mol-1) and positive entropy (ΔS=27.905 J·mol-1·K-1), which indicated that 2-Zn binds with HSA mainly via electrostatic interaction along with the hydrogen bonding and hydrophobic interaction. Site marker competitive binding experiment confirmed that 2-Zn mainly binds at site Ⅱ. The distance between HSA and the receptor (2-Zn) and the efficiency energy transfer were obtained to be 4.01 nm and 0.163 respectively, based on the Forster theory on resonance energy transfer. Synchronous fluorescence, absorption and CD spectroscopy showed that the interaction of HSA with 2-Zn induced a conformational change of protein, and the amount of α-helical structures were decrease. Furthermore, the binding details between 2-Zn and HSA were further studied with the molecular docking, which was in good agreement with the site marker competitive binding experiments and thermodynamic parameters.

There are four major problems related to fuel consumption, “large consumption”, “low quality”, “lack of front-end clean” and “lack of end emission control”, which needs to address urgently for our country. More than 60 percent of the air pollution is due to the burning of coal and oil in our country, so the haze problem depends on how much we can deal with energy issues. We should achieve the identification and measurement of gasoline, diesel, kerosene and other refined oil products rapidly and accurately, which is important for the implementation of air pollution monitoring and controlling. in order to characterize the type information of the refined oil accurately and to improve the efficiency of the network model identification, it is effective to use principal component analysis method which could achieve the data dimension reductionwhile reducing the complexity of the problem. With principal component analysis of the most commonly used three-dimensional fluorescence spectra based on excitation-emission matrix (Excitation-Emission Matrix, EEM) data, we could obtain finer, deeper characteristic parameters. During the process of classification, it could avoid the “over-fitting” phenomenon because of the application of the cross-validation method, A neural network capable of both qualitative and quantitative analysis is designed. The neural network pattern recognition result becomes feedback to the input of the concentration network, together with the relative slope, the comprehensive background parameters, and the relative fluorescence intensity, we could achieve the measurement of the concentration of the corresponding types, then use the extension neural network pattern recognition technology to achieve identification and measurement of kerosene, diesel, gasoline and other refined oil products. The results of the study show that the average recognition rate reaches 0.99, the average recovery rate of concentration reaches 0.95, the average time of pattern recognition is 2.5 seconds and this time is 48.5% of the time used by PARAFAC model analysis method. The method significantly improves the operation speed with ideal application effect . It should be pointed out that, in order to ensure the accuracy and precision of the analysis, we should make corresponding calibration samples for specific analytes in terms of the analysis of complex mixtures such as refined oil, pesticides, tea, etc.

Siliva as a kind of biomarker containing a variety of bioactive components can be used to help disease diagnosis. Compared with the urine and blood, the collection of saliva is more simple and convenient while the collection process is completely non-invasive. Therefore, saliva detection attracts more and more attention in non-invasive disease diagnosis. Histatins are a family of small, cationic, histidine-rich peptides, which secreted by salivary bringing innate defense of the oral cavity. It has been reported that histatins are related to many other diseases, such as HIV and AIDs. Thus the detection of histatins in saliva is significantly important for oral healthy monitoring and disease diagnosis. In this paper, a new label free method for rapid detection of histidine-rich peptides was developed based on the fact that histidine-rich peptides can interact with 3-azidocoumarin through hydrogen bonds which decreases the electron-donating ability of the azido group and results in fluorescence enhancement of the system. The results showed that the fluorescence intensities were dramatically increased when histatin 5 were incubation with 3-azidocoumarin. There is a good relationship with the linear co r of 0.994 between the enhanced fluorescence and histatin 5 concentration ranging from 0.23 to 31.05 μmol·L-1, and the limit of detection is 72 nmol·L-1 (3σ/k). Moreover, the detection of histidine-rich peptides in saliva was successfully achieved by the new developed label free method since amino acids and proteins in saliva will not be interfered with the detection with the recoveries between 96.7%~111.6%. Compared with the existing saliva analysis methods, this method has the advantage of simple, fast and low cost. It might be applied in non-invasive disease diagnosis.

Dust-fall distribution of vegetation leaves can indicate the degree of air pollution; therefore the analysis of spatial characteristics of urban vegetation dust-fall has important practical significance for making more effective air pollution control policy. Based on the data of weight of dust, spectral reflectance and leaf area of Euonymus japonicus, Sophora japonica, poplar and davidiana collected in the main area of Beijing city, we compared the curve of spectrum of four plants “dust leaves” to “clean leaves”; the correlation analysis between leaf spectral reflectance ratio (Dust/Clean) of narrow band and satellite band was processed with the weight of dust-fall respectively, with application of four plants leaf data. Then, we built the regression model of the satellite band reflectance and NDVI with dustfall weight respectively, and we used the best model to retrieve the dust-fall distribution of vegetation coverage area in Beijing city, furthermore, we obtained the dust distribution of the whole Beijing city through interpolation. Finally, we carried out the rationality verification of the result by the land cover and land use of the high dust region, as well as the average concentration of PM10. The results showed that, dust leaves had an obviously lower reflectance than clean leaves in 780~1 300 nm which belonged to near-infrared bands; therewas a higher correlation between narrow band reflectance and dust-fall weight in 520~620 and 1 390~1 600 nm, up to -0.626; the coefficients of determination (R2) of inversion models were respectively 0.446 and 0.465,which were constructed by green band and NDVI of Landsat8 with dust-fall weight. Using the model established with NDVI to retrieving the dust-fall distribution of Beijing city, the results demonstrate that the distribution of dust-fall is high in north and low in south, high in east and low in west, high in downtown and low in the suburbs. This study offers a low-cost and effective method for investigating dust-fall distribution in urban area, and provides data support to analysis sources of pollution for the environmental protection department.

Traditional hyperspectral image classification algorithms focus on spectral information application, however, with the increase of spatial resolution of hyperspectral remote sensing images, hyperspectral imaging presents clustering properties on spatial domain for the same category. It is critical for hyperspectral image classification algorithms to use spatial information in order to improve the classification accuracy. However, the marginal differences of different categories display more obviously. If it is introduced directly into the spatial-spectral sparse representation for image classification without the selection of neighborhood pixels, the classification error and the computation time will increase. This paper presents a spatial-spectral joint sparse representation classification algorithm based on neighborhood segmentation. The algorithm calculates the similarity with spectral angel in order to choose proper neighborhood pixel into spatial-spectral joint sparse representation model. With simultaneous subspace pursuit and simultaneous orthogonal matching pursuit to solve the model, the classification is determined by computing the minimum reconstruction error between testing samples and training pixels. Two typical hyperspectral images from AVIRIS and ROSIS are chosen for simulation experiment and results display that the classification accuracy of two images both improves as neighborhood segmentation threshold increasing. It concludes that neighborhood segmentation is necessary for joint sparse representation classification.

Characteristic bands method selection and subsequent spectral extraction has a great influence on the hyperspectral model performance. For rapid and accurate detection of mutton pH value, the effects of 2 band-selection methods on PLS models of mutton pH based on HSI technique were carried out and discussed. Initially, the preprocessing method of second derivative (2D), multiplicative scatter correction (MSC) and mean-centering together was implemented on the representative spectra of mutton muscle portion. Then, 2 methods of synergy interval partial least square (siPLS) and the combination of synergy interval partial least squares with genetic algorithm (siPLS-GA) were used to extract the characteristic bands in the spectral range of 473～1 000 nm. Finally, 2 PLS models of lamb pH value were established with the corresponding characteristic bands, and were also compared with the effect of full-band PLS model. The results indicated that the effect of siPLS-GA-PLS model was the best. As for the siPLS-GA-PLS model, 56 characteristic wavelength points were chosen, the correlation coefficient(Rcal) and root mean square error(RMSEC) of calibration set was 0.96 and 0.043 respectively, and the correlation coefficient(Rp) and root mean square error(RMSEP) of prediction set was 0.96 and 0.048 respectively. Spectral variables were reduced and model accuracy was improved. It can be concluded that characteristic bands selection and rapid and accurate detection of lamb pH can be achieved using hyperspectral imaging technique combined with siPLS-GA method.

In order to know the potatoes nitrogen situation rapidly and accurately, promoting the efficient use of nitrogen fertilizer on the potatoes. Using the feature of portable hyperspectral spectrometer, digital cameras and SPAD-502 chlorophyll meter to abtain the potato digital indicators, leaf spectral and SPAD. Analysing the change status of digital indicators, leaf spectral index, SPAD and production of potatoes under different nitrogen levels in two key periods. Analysing the correlation between canopy image, leaf spectral and SPAD and production, with SPAD as auxiliary validation index, nitrogen fertilizer efficiency evaluation of yield to make sure potato canopy image under the most economic nitrogen application levels and leaf spectral’s critical value to explore the methods of nitrogen nutrition diagnosis quickly and simply. The results show: (1)With nitrogen levels increased, potato tuber formation stage and tuber bulking stage leaf spectral reflectance is the emergence of the "red shift" phenomenon, and the red edge parameters REP, Lwidth, FD_Max increased, Lo decreased. (2)With the nitrogen levels increased, potatoes tuber formation stage and tuber bulking stage digital indicators G/B, (G－B)/(R+G+B) decreased gradually, B/(R+G+B) increased gradually. (3) with the increase of nitrogen application rate SPAD is increased.It is obvious low nitrogen levels increase production with nitrogen increased. It is not obvious the high level of nitrogen stimulation effect. Potato canopy image, leaf spectral and red edge parameters have good correlation with SPAD value and productions, establishing the index evaluation of nitrogen nutrition abundance or lack of quantitative standard of potatoes. Indicating digital image and spectrum technology to nitrogen nutrition diagnosis of potatoes is feasible, provide research ideas and technical support for the potato accurate monitoring of nitrogen nutrition.

This paper focused on the research on identifying and classifying for mutton varieties of Tan-han hybrid sheep,Yanchi Tan-sheep and small-tailed sheep in Ningxia by using visible/ near-infrared (400~1 000 nm). Near infrared (900~1 700 nm) hyperspectral technologies, baseline and SG convolution smoothing spectra pretreatment methods were applied respectively according to the characteristics of different spectrum bands; the characteristic wavelengths were extracted by using successive projection algorithm (SPA);then combined with linear discriminant analysis (LDA) and radial basis kernel function of support vector machine (RBFSVM) model were applied to identify the different mutton varieties under characteristic wavelengths and full-wave bands. Results showed that there were good effects for mutton varieties identification in different hyperspectral bands, among which Baseline-Fullwave-RBFSVM and the same models under 12 characteristic wavelengths obtained accuracy of 100% and 98.75% in 400~1 000 nm respectively, and Baseline-Fullwave-RBFSVM and the same models under 7 characteristic wavelengths obtained accuracy of 96.25% and 87.80% in 900~1 700 nm respectively.The identification accuracy of RBFSVM nonlinear classification was higher than the LDA linear discriminant result, meanwhile the identification accuracy in 400~1 000 nm bands was better than in 1 000~1 700 nm bands, which explained that the differences of color and texture were more significant than the component contents among the 3 varieties mutton. Combined hyperspectral technologies with RBFSVM models can obtain a better recognition effect of mutton varieties.

Increased concentration of air respirable particulate matter associated with a number of combination factors. Spatial dispersion is also correlated with elevation DEM. In order to study the fog haze pollution associated with digital elevation model of spatial relations, this paper used the capital area ring within 100 km as the research scope, partitioning different length scale grid according to the rectangular grid method in the study area, obtaining visible light image data and hyperspectral image data by using unmanned aerial vehicle (UAV) for the extraction and integration air pollution factor and elevation factor within the scope of this study. GS+ software of kriging interpolation method was used to research the spatial correlation of variable data extraction; the MODIS remote sensing image data combined with field survey were used to analyze nonlinear regression of the terrain and environmental data.With the Calculation of variation effects of the particulate matter in the air and the spatial of the elevation factor under different grid scale ring of capital region, an optimization model of spatial correlation between them was established. Then the relation between the concentration of PM10 and height was determined. The biggest influence distance of elevation DEM associated with particulate matter API is 14.74 km. DEM space since the correlation of waning with the increase of the distance between sample points, which is also an important innovation of this paper. This result shows that the spatial correlation between the elevation DEM and environment conforms to the statistical spherical Gaussian model, correlation coefficient R2 were over 90%, which model fittings good. This study provides a certain theoretical and practical guidance for the control of air pollution index in the future as the change of height to select different tree species for afforestation.

Aiming at understanding the light radiation properties of KClO4/Zr combusting under different conditions, emission spectrum and combustion products for KClO4/Zr combusting in open air and closed quartz tubes were studied respectively. Energy distribution of the light radiation signal and the emission intensity evolution with time were measured with fiber optic spectrometer, and photo-diode and oscilloscope. Spectral efficiency within (590±10), (750±10) and (808±10) nm were analyzed respectively according to the obtained flame emission spectrum. Morphology of the combustion products of KClO4/Zr were observed with scanning electronic microscopy (SEM). Results showed that the flame emission spectrum of KClO4/Zr distributed within the visible and near infrared width wave band, whiel the strongest radiation appeared within 730 nm to 820 nm band. When burning in closed quartz tubes, detected combustion emission spectrum intensity decreased significantly with the decrease in size of the tube. Also, the energy distribution of the emission spectrum showed different variation trends, and to deal with flame emission spectrum distribution, as the change of volume of quartz tubes, (590±10), (750±10) and (808±10) nm bands’ spectral efficiency are also present different change rules. Generally, increasing the diameter of the quarts tube favored the increase of the effective light radiation energy detected outside of the tube, and decreasing the diameter of the quartz tubes favored the peak emission intensity of KClO4/Zr. With the increase of tube diameter, KClO4 burning more fully, the product particle size is smaller; the morphology is the rule of the globular. And the change of tube length is not too large effect in the reaction results.

The mechanism of laser paint removal is studied based on emission spectrum and composition analysis by using laser induced breakdown spectroscopy and X-ray energy spectrum technology. The electron density and electron temperature of the plasma was calculated with the LIBS spectrums with different laser parameters. The morphologies of ablated paint surface were analyzed with a scanning electron microscopy while the changes of paint composition before and after ablation were measured with an X-ray spectrometer. The results show that, the plasma electron density, temperature and ablation area gradually increase with the increasing of incident laser energy. The carbon (C) content in paint decreases from 78.25% to 67.07% after the laser irradiation, indicating the occurrence of the ablation in the process of laser paint removal. By comparing the content of titanium (Ti) elements, C element and aluminum (Al), we found that the paint ablation will be more severe at higher laser energy. This paper is important to in-depth study of laser paint removal mechanism.

Balikun County is located in the Hami region of eastern Xinjiang which is the junction point connecting central China and northern Xinjiang, Shirenzigou sites in the Balikun County was a great nomadic tribe settlement in the eastern Tianshan Mountains. The glass beads excavated from the tomb of M011 in the Shirenzigou site and the tomb of M1 in the Xigou site, which can be dated back to late Warring States to the early West Han dynasty (3rd century B.C—1st century B.C). To understand the provenance of these glass beads, the chemical composition of these glass beads were analyzed through the examinations of LA-ICP-AES and LRS. The results showed that the glass beads from the Xigou site were all Na2O-CaO-SiO2 system; with plant ash as flux, the lead antimonite were used as opacifying agents of seven green glass beads. Meanwhile, the glass beads from the Shirenzigou site were PbO-BaO- SiO2 system, the lead were used as flux. Compared with the contemporaneous glass beads, the result illustrated that the chemical composition of glass beads from the Xigou site were different from the Egyptian or Mesopotamian Na2O-CaO-SiO2 glass, it was highly plausible that the glass beads were manufactured in the central Asia or Xinjiang region; while the chemical composition of glass beads from the Shirenzigou site were relatively centralized, which showed they were manufactured from the same place, the glass beads from the Shirenzigou site were imported from the central region of China. The study confirmed that the Balikun was an important place for the communication of material culture between the East and the West; meanwhile the nomadic people played a significant role for the spread and communication of glass beads.

At present, the way to introduce the sample into the inductively coupled plasma atomic emission spectrometry (ICP-AES) light source is still in the form of solution. In order to improve the treatment effect of the aqueous solution and change its physical properties, the surface tension and viscosity under different experimental conditions were measured with magnetic stirring combined with laser irradiation. . The treated samples were introduced into the inductively coupled plasma (ICP) to measure the spectral line intensity, signal-to-background ratio, excitation temperature and electron density emitted by the ICP source. The experimental results showed that: when the magnetic stirrer rotate speed was 1 197 r·min-1, the laser power density was 0.227 6 W·cm-2 and irradiation for 15 min, the surface tension and viscosity of the solution were decreased by 27.85% and 8.66% respectively than those of the untreated solution. As to the element spectral lines of As 188.980 nm, Cd 214.439 nm, Cr 267.716 nm, Cu 324.754 nm, Hg 253.652 nm and Pb 220.353nm: the intensity was enhanced 32.07%, 65.36%, 18.27%, 32.29%, 19.38% and 54.28%; the signal-to-background ratio increased by 25.13%, 60.97%, 18.18%, 27.69%, 21.11% and 48.93%, respectively. The enhancement of the plasma radiation was explained to a certain extent by measuring the excitation temperature and electron density of the plasma. The processing method of the aqueous solution can effectively improve the spectral intensity and signal-to-background ratio of the ICP. Compared with the laser irradiation aqueous solution separately, this method significantly shortened the processing time, improve the efficiency. This method is simple, with no secondary pollution in the treatment of the sample solution, convenient popularization and use.

This paper focuses on the study on continuous XRF (X-Ray Fluorescence) scanning elements of a 39 m core from Fuzhou Basin. The XRF scanning result is used to recognize the different sedimentary environment before the discussion of the element variation of different deposit in transitional zone between land and ocean. There are five sedimentary facies in the study area from the late Pleistocene: lacustrine-fluvial-estuary (mud tidal flat)-mixed tidal flat-fluvial. The XRF result from the 5 sedimentary stages shows that the high concentration of Co, Fe, Ti, Si are controlled largely by grain size. The average element intensity of layers with similar grain size indicates that Ca, Ti, Mn, Fe and Co from the marine (tidal flat) deposit is 3~10 times bigger than those from terrestrial (fluvial) deposit, with higher content of Si coinciding with terrestrial deposit. It is indicated that except grain size, the deposit environment is an important factor for element concentration. In this study, Ca, Ti, Mn, Fe and Co are relatively better indicator elements for marine sediments while Si is good and K, Rb and Sr have some indication for terrestrial sediments. The study result shows XRF continuous scanning can help to identify the subtle variation of elements, as to the determination of the sediment facies. Thus, XRF scanning is an important supplement to sediment facies identification. This study also provides an application example of XRF in a typical transitional zone between land and ocean.

A new kind of imitation of turquoise named “Violet” and “White buffalo” which is a type of associated mineral of turquoise have appeared on the market recently and are becoming increasingly popular. Conventional instruments, X-ray fluorescence spectrometer, Infrared spectrometer, X-ray powder diffraction, Scanning electronic microscope, UV-Vis have been employed to discuss the gemmological characteristics of this kind of imitation of turquoise in this paper, to study their chemical composition, mineral composition, microstructure, spectral characteristics and color emerging mechanism. The X-ray fluorescence spectrum shows that the chemical composition of the sample is complicated. The basic elements of different-colour samples are basically identical which contains of Ca, Al, P, Cu, Si, K, Fe, Ba. It can be deduced from the intensity of infrared absorption bend that the major anion group of this kind of imitation of tuequoise is PO3-4. The analysis for X-ray powder diffraction data indicated that the major mineral of the sample is crandallite and woodhouseite. Meanwhile, the scanning electron microscopy showed that the structure of the dense sample is determined by numerous of scaly, leaf-shaped and irregular granular aggregates. With the study of absorption spectrum, the conclusion is drawn that Fe3+ electronic transitions are the main factor for coloring of the sample and color varies with the content of Fe3+.

Transfer radiometer is the critical calibration facility of remote sensing instruments on satellites to achieve spectral radiometric calibration on-orbit. It’s also the core for spectral calibration with high accuracy in the laboratory on earth. This paper compares the similarities and differences between several transfer radiometers developed by various institutes covering 200～700, 700～2 000 nm spectrum bandwidth separately through describing their construction, design and operational principles and the method of transferring radiometric calibration benchmark. It shows the realizable accuracy of every transfer radiometers by introducing their central technology applied in the calibration procedures of different wavelength range. The advantages and shortcomings together with every transfer radiometer determine the application circumstance. According to the introduction of the process of the calibration traceability based on radiance standard in international institutes of standard technology, it emphasizes the importance of transfer radiometers in the procedure. It demonstrates the significance of transfer radiometer in radiometric calibration of aeronautics and space through its application of monitoring the calibration light source for spectrometers. Finally, it presents the prospect for the development and crucial issues of transfer radiometer’s technology in the future research through describing the new transfer radiometer designed in internal institute. Simultaneously, it predicts and summarizes difficult problems required to be solved in the future as to high-accuracy calibration transferring system on-orbit against SI-traceable primary standard, which consists of cryogenic radiometers and transfer radiometers.

Blood constituent examination is an important means of health diagnosis. For blood constituent examination, we usually adopt the method of drawing blood, which bring pain and the risk of cross infection to the patient. Near infrared spectrum spectroscopy (NIRS) is a research hotspot in noninvasive blood constituent examination. The spectral data acquisition system of existing instruments is using a Single Chip Microcomputer (SCM) as its microcontroller. The spectral data acquisition system cannot realize the high speed multi-channel acquisition and storage of large amounts of data because of the SCM itself has certain deficiency. So a high speed multi-channel spectral data acquisition system based on Field Programmable Gate Array (FPGA) was designed in this paper in order to realize the system of high speed, multi-channel and high signal-to-noise ratio (SNR) in the area of noninvasive blood constituent examination by near infrared spectroscopy. An Altera Cyclone IV series FPGA was used as the microcontroller in this spectral data acquisition system, which simultaneously controlled two pieces of eight channels AD conversion chip acquiring 16 channels blood pulse wave signal parallel. Under the control of FPGA, the data was cached in FPGA internal ping-pong RAM first, after that it was transferred to an SRAM chip, finally it was sent to the computer via the USB port. Experiment result shows that the spectral data acquisition system can collect 16 channels signal parallel and fast under the sampling frequency of 19 531 Hz and the repetitive signal-to-noise ratio is over 40 000∶1. The system can collect 305 spectrograms per second, more over it can get high SNR human body blood pulse wave signal under the same circumstances. The spectral data acquisition system satisfies the basic requirements of the noninvasive blood constituent examination instrument by NIRS and it can make the instrument collect the human body blood pulse wave data at a high speed. The main innovation point of this article is applying FPGA to the spectral data acquisition system of near infrared noninvasive blood constituent examination instrument. FPGA is able to simultaneously control two pieces of eight channels AD conversion chip acquiring 16 channels blood pulse wave signal parallel. By using FPGA as the microcontroller of the spectral data acquisition system, we solve the problem that SCM as the microcontroller can’t realize multi-channel high speed data acquisition and storage of large amounts of data. The acquisition speed is greatly faster than the system before. The second innovation point of this article is we use FPGA internal resources establish a ping-pong RAM buffer. The spectral data from the AD chip is 24 bit, however, the SRAM chip has only 16 bit data bus. Via the ping-pang RAM buffer, the spectral data can transfer from AD chip to SRAM chip. The ping-pong RAM can realize different digits data seamless transfer from AD chip to SRAM chip.

Tunable diode laser absorption spectroscopy (TDLAS) technology combined with wavelength modulation spectroscopy (WMS) technology is an important technique for trace gas detection. Detected with the lock-in amplifier, the second harmonic signal obtained after demodulation is analyzed to get the gas absorption information. However, the second harmonic signal is affected by noise which reduces the accuracy and stability of the detection system. To improve the signal to noise ratio (SNR) of the TDLAS detection system, a denoising method based on Gabor transform is proposed for second harmonic signal noise reduction. Taking the CH4 absorption spectrum at 1 653.72 nm as an example, the effectiveness of the noise reduction method is verified through simulation and experiments. The simulation results show that the signal to noise ratio for the second harmonic signal of 0 dB can be improved 15.73 dB with Gabor transform-based denoising method. Experimental results show that with the Gabor transform-based denoising method, the linear correlation coefficient r can be as high as 0.996 59 between the second harmonic peak value and the CH4 concentration in the range of 0.001%~0.02%. At the same time, the detection accuracy and stability of the system have been improved significantly.

For the influence of temperature drift of the spectral responsivity on the repeatability infrared spectral emissivity measurement system, a temperature drift correction method is proposed based on the polynomial fitting. By analyzing the function of detector output voltage depended on its temperature. After studying the functional relationship between the temperature and spectral responsivity of detector, the spectral response curve varies with temperature is fitted and get the fitting equation. Calculating the drift correction factor of spectral responsivity, the output voltage of infrared detector is corrected. The effect of spectral response drift on the output voltage of detector is eliminated. With the development of temperature drift correction device of spectral responsivity, the temperature drift curve of spectral response is measured. Compared to the exponential fitting, the fitting consistency of sixth-order polynomial curve is excellent. Because of the application of this method, the repeatability of spectral emissivity measurement system is improved.

A fiber humidity sensor based on Fiber-Bragg Grating (FBG) sandwiched in single-mode-multimode fiber core-single mode (SMS) fiber structure is proposed and demonstrated. When the surrounding humidity changes, the central wavelength of FBG remains unchanged for it is insensitive to humidity, while the interference spectrum of SMS fiber structure will shift for it is sensitive to the surrounding humidity. Hence, the shift of the SMS fiber structure interference spectrum with humidity could modulate the FBG core mode. Through measuring the reflected power of the FBG core mode the detection of humidity can be realized. The beam propagation of the SMS fiber structure with different lengths of multimode fiber core (MMFC), diameters of MMFC, and surrounding refractive indices are theoretically simulated with beam propagation method. Theoretical simulation indicates that the output core mode power coefficients shift with surrounding humidity of the SMS fiber structure. Experimental results show that the sensor has a linear response to humidity with enhanced sensitivity of 0.06 dBm·(%RH)-1 in the humidity range of 45%~95%RH with length of 35 mm and diameter of 85 μm. The temperature effect of the sensor is also discussed, the temperature sensitivity is 0.008 nm·℃-1 in the temperature range of 20~80 ℃ and the measurement error of temperature is 0.047% RH·℃-1. Such cost-effective, high sensitive, and reflective power detection based optical fiber humidity sensor could be used in humidity sensing applications.

By using doppler asymmetric spatial heterodyne spectroscopy and doppler effect, the wind speed can be achieved through detecting the interferogram of airglow in the upper atmosphere. This paper mainly analyses the data processing method of the interferogram and then derive the interferometer phase in order to get the wind speed. Comparing with the traditional spatial heterodyne spectroscopy, not only the noise and error of the system should be taken into consideration, but the window function that used to isolate the spectrum has a great influence during the data processing. Then the effect of window type and window width on phase difference of interferogram and the wind error curve are simulated through software. On basis of this the wind error curve under the noise of system and flat field factor are simulated by choosing appropriate window function. The window function simulation indicates that although the joining of window leads to a distortion of the interferogam and phase, the wind speed error can be less than 0.5% with Hanning window in the appropriate optical path difference. The noise of the system simulation indicates that the wind speed error increases with the noise, so it is necessary to control the system noise and preprocess the sampling data. The research on data processing method has great theoretical significance and practical value for designing the system parameter and improving the precision of spatial heterodyne wind detection.

Near infrared spectroscopy analysis, as a kind of nondestructive real-time continuous detection method, has provided ideas for the noninvasive measurement of blood components. In this article, in order to ensure the accuracy and reliability of the collected spectral data, the 405 acquired samples are evaluated by combining valid single edge counts of dynamic spectrum pulse wave in the time domain with the quality factor Q value of dynamic spectrum pulse wave in the frequency domain. As a result, the abnormal samples are removed and 218 cases of valid samples are selected. We use the dynamic spectrum data of the selected 218 samples as the experimental group and another 218 samples as a control group modeling analysis with the hemoglobin concentration of the corresponding samples. Each group select 200 cases of samples as a calibration set and 18 cases of sample as a prediction set. The prediction accuracy of the experimental group reach 93.8%. The prediction accuracy of the two control group respectively evaluated by the valid single edge counts or Q value are 65.6% and 67.7% and the three unfiltered control groups are 53.7%, 33.3%, 42.6% respectively. The prediction mean relative error (MSEP) of the experimental group is 0.067 5, the other two control groups are 0.072 3 and 0.072 2, and the other three control groups are 0.082.3, 0.078 9, 0.082 8. So compared with another control groups, the MSEP of the experimental group is the minimal. The results show that the filtering method of the spectral data samples through combining time domain with frequency domain is reliable and effective.this will provide a method to the precision research of dynamic spectrum noninvasive detection.

The electronic structure and UV-Vis properties of ground state CuSin (n=4～10) and CuSin anion clusters were studied using B3LYP density functional theory (DFT) at a 6-311+G (d) level. Calculations indicate that: (1) the band gap of neutral CuSin clusters is narrower than their anion, indicating anion clusters are relatively stable; (2) the energy gap and electronic structure calculations indicate that the anion CuSi5 cluster is more stable than neighboring clusters; and (3) the UV-Vis spectrum of CuSin clusters and CuSin anions suggests that the neutral clusters are weakly absorbing; the anion clusters are strongly absorbing, and anion clusters with increasing size of the Si atoms experience a redshift in the absorption spectra.

The UV-Vis and infrared (IR) absorption spectra of organophosphorus (OP) pesticides have been studied. A correlation in spectra was developed to optimize the OP pesticides in the environments. The spectroscopic (UV-Vis and IR) spectrum of OP pesticides like methyl parathion, malathion and parathion has been interpreted in detail. A complete calculation of the normal frequencies and absolute intensities of UV-Vis and IR absorption bands are interpreted with the help of corresponding experimental data. In the colorimetric reactions, the bands appear at 2 077, 1 637, 1 455, 1 015, 655 cm-1 for malathion; 2 081, 1 639, 1 316, 1 015, 794, 683 cm-1 for parathion; 2 078, 1 632, 1 032, 794 cm-1 for methyl parathion were used for quantitative or qualitative analysis. All these IR spectra were acquired by averaging 100 scans at a resolution of 4 cm-1. It is determined experimentally in the region 200～450 nm for UV-Vis absorption bands and in the region 400～4 000 cm-1 for IR absorption bands. It is concluded that the mainly optically active groups (P—OH, CO, PO, C—O—C, P—O—C, PS, —OH) present in pesticides which are responsible in change in significant data for quantitative and qualitative analysis. The various optical properties like wavelength, band energy, wave number, and frequency, also are calculated.

The microscopic fluorescence spectroscopy has become a mature technology of fluid inclusions test and analysis system, which is used to distinguish different types of crude oil and oil inclusions. These would be the important basis to study the history of hydrocarbon accumulation of petroleum basins. The mixture of crude oil from different sources could occur in migration and accumulation process. In order to effectively identify the type of geological process, mixing ratio of crude oil experiment has been carried out. This study result shows that mixing of crude oil make fluorescence color and spectral parameters(λmax, QF535 and CIE-XY) change nonlinearly. Fluorescence spectral parameters of mixed oil is between end member oil A and B. The greater A or B ratio of mixed oil, the closer to A or B. Fluorescence color of mixed oil show nonlinear and gradual change in CIE-XY chromaticity diagram. Variation of spectral spectrum shape show that single peak is changed into double and three peaks. The relationship between QF535 and degree of mixing could calculate quantitatively relative contribution. Mixing different types of crude oil make spectral spectrum shape changes, which present characteristics of two peaks and three peaks but not unimodal peak. The main and subsidiary wavelength reserve wavelength information of end member oils. Based on variation characteristics of fluorescence spectrum, there are three different types of oil including blue, blue-green and yellow fluorescing oil filling in the bottom member of Pinghu formation in A gas field. At the same time, there also was a mixing process of blue-green fluorescing oil and yellow fluorescing oil. The degree of mixing is 47%~55%.

In order to understand the spatial distribution and evaluate the pollution degree of heavy metals (As, Cd, Cr, Co, Cu, Mn, Ni, Pb, and Zn) in upper reaches of the Yellow River, surface water samples were collected from 12 selected sites during two field surveys in April 2014 (drought season) and October 2014 (normal season). The concentrations of heavy metals were determined using inductively coupled plasma mass spectrometry (ICP-MS) for spatial variation and heavy metal pollution index. The average concentrations of the metals in the drought season and normal season decreased respectively in the order: Cr (18.56 μg·L-1)>As (2.95 μg·L-1)>Ni (1.87 μg·L-1)>Mn (1.20 μg·L-1)>Cu (1.12 μg·L-1)>Zn (0.59 μg·L-1)>Pb (0.08 μg·L-1)>Cd (0.01 μg·L-1); Mn (596.89 μg·L-1)>Zn (52.46 μg·L-1)>Cu (36.27 μg·L-1)>Ni (25.11 μg·L-1)>Cr (23.19 μg·L-1)>Pb (19.51 μg·L-1)>As (7.30 μg·L-1)>Cd (0.37 μg·L-1). The results were compared with national and international water quality guidelines, as well as literature values reported for the same river in flood season. To assess the composite influence of all the considered metals on the overall quality of the water, heavy metal pollution indices were calculated. The Heavy Metal Pollution Index (HPI) of the river calculated for the individual locations showed ranging from 6.46 to 11.95 in drought season, 4.53 to 210.53 in normal season, respectively. Both the distribution of metals and HPI of two seasons revealed obvious seasonal variation. The results showed that the degree of heavy metal contaminant was not very high and had seasonal variation; both the concentrations of metals and HPIs indicated the pollution level of the normal season was higher than it of the drought season. The results of this paper provided reliable experimental data and theoretical basis for the relevant departments to make further policy decision.

The interactions of Salvianolic acid A (SAA) and Salvianolic acid B (SAB) with insulin were studied by using fluorescence spectroscopy, UV-vis spectroscopy and ATR-FTIR spectroscopy in simulating physiological condition (pH 7.40). The fluorescence quenching of insulin by SAA and SAB were static quenching process. The results of synchronous fluorescence and three-dimensional fluorescence spectra suggested no obvious conformation changes of insulin after SAA or SAB binding. But ATR-FTIR spectra showed that SAA and SAB could change the secondary structures of insulin, of which β-turns decreased and random coil increased accompanied with α-helices and β-sheets no clear change. The glucose might influenced the the bioactivity of insulin in the SAA-insulin and SAB-insulin systems by changing the binding constants of SAA (or SAB) with insulin and exacerbating the changes of insulin conformation and relative contents of α-helices.

La-Co-O mixed oxides (LCO) were prepared by co-precipitation method with the presence of polyethylene glycol (PEG) as dispersant. The influence of adding different molecular weight of PEG (0, 2 000, 6 000, 20 000 g·mol-1) on the physicochemical and catalytic properties of La-Co-O mixed oxides for total oxidation of benzene was investigated. The samples were characterized by means of N2 physical adsorption, X-ray diffraction (XRD), scanning electron microscopy (SEM), temperature-programmed reduction by H2 (H2-TPR), temperature-programmed desorption of O2 (O2-TPD), and X-ray photoelectron spectroscopy (XPS). The order of catalytic activity was found to be LCO-PEG6000>LCO>LCO-PG20000>LCO-PG2000. Particularly, LCO-PEG6000 exhibited benzene conversion of 99% at temperature as low as 383 ℃, which was 126 ℃ lower than that of LCO. The characterization result reveals that all samples had a BET surface area of about 9～10 m2·g-1. The XRD result shows that on all samples LaCoO3 perovskite was mainly formed together with a small amount of La2O3 and Co3O4. The addition of PEG was favorable for the formation of LaCoO3 perovskite. Particularly, the addition of PEG-6000 effectively suppressed the agglomeration of LaCoO3 perovskite, giving rise to small and uniform particles as observed by SEM. Moreover, the results of H2-TPR and O2-TPD indicate that the obtained La-Co-O mixed oxides showed higher reducibility and lattice oxygen mobility, and the Co 2p XPS analysis suggests that more surface Co3+ active species were presented by the addition of PEG-6000. These properties are thought to contribute to the high activity in benzene total oxidation.

Women of reproductive age are at an increased risk of minerals deficiencies, especially for women in recent years. The objective of this study was to investigate the concentrations of 21 elements (Ca, Mg, Cu, Zn, Fe, Mn, Cr, Ti, B, Co, Mo, Si, V, Ni, Cd, Al, Pb, Ba, Sr, Sn and Se) in scalp hair of apparently healthy women at childbearing age of Xinghe County, Ulanqab city of Inner Mongolia. The hair samples were determined by inductively coupled plasma-atomic emission spectrometry (ICP-AES) and atomic fluorescence spectrometry (AFS), respectively. The results revealed that the concentration levels of 21 elements were clearly differed from the mean levels reported in the literatures. Micronutrient deficiencies and apparent excess of toxic elements are present in female of childbearing age in studied area. The higher Mg and Al levels may be due to the largest bentonite deposit in North China lay in the study area. The soils in the studied areas had been detected to have low total Se concentration which may account for that 98% participants had Se concent below 0.2 μg·g-1. Inter-element interactions were studied by evaluation of correlation coefficients between two elements, as well as by multiple regression analysis. These elements form divalent ions and their sources are similar were significantly inter-correlated. The strongest relations found between the elements in the hair were as follows: Mg and Ca, Cr and B, Si and Pb, Mn and Pb, Fe and Mn. No correlation was found between Cd and Pb, which is different with other reports. This could be explained by the rarely industrial exposure to these elements. And kinds of geographical environment, dietary habits and other factors in different regions impact human trace element metabolism. Multiple regression analysis presented the results: Ca=f(Mg, Se) (Se are negatively correlated, β<0), Fe=f(Cu, Mn, Ti), Zn=f(Ca, Se, Fe, Ni) (Fe, Ni are negatively correlated, β<0), Cu=f(Pb, Fe, Cd), Al=f(Mg, Pb), Se=f(Zn, Cr, Ca) (Ca are negatively correlated, β<0). These relations can be useful to study the relationships among different elements inside an organism of women. Cluster analysis (CA) was used for further classifying the different sources of elements on the basis of the similarities of their chemical properties. The significantly correlated subcluster of Mn-Pb-Si-Al proved that Pb exposure came from a nature source. The results will provide a reliable basis for improving macro- and microelements status of women in childbearing age in rural area. Meanwhile, this study may help to make more effective strategies to improve the reproductive-aged women’s health and the pregnancy outcome.

Cr-MnOx/cordierite composites were prepared by Sol-gel, Impregnation, Co-precipitation and Rheological phase reaction method. Various technologies including X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), thermogravimetry/differential scanning calorimetry (TG/DCS), and temperature-programmed reduction (TPR) were used to characterize the structure and morphology properties of the synthesized composites. The catalytic ability test of 1,2-dichlorobenzene (o-DCB) over the catalysts was conducted in a fixed-bed flow reactor with a gas hourly space velocity (GHSV) of 30,000 h-1 to investigate the catalytic performance of the prepared composites. The results indicated that the combined Cr2O3 and Mn2O3 phases supported on cordierite possessed a special ball-shaped and better redox property in the catalyst prepared by the Co-precipitation method with a Cr/Mn atomic ratio of 2∶5, which was conducive to the increase of the synergistic effect and subsequently enhancement of the catalytic performance. Furthermore, it exhibited better stability within 60 h, which indicates a good prospect for industrial applications.

Dried sclerotia of Wolfiporia extensa has a long history of medicinal uses in Asia and also is a traditional snack in Beijing that is called “fuling jiabing”. This study aimed at providing and evaluating data on total Hg contents of sclerotia collected across of the Yunnan land in China, which is generally lacking information. Sclerotia of W. extensa showed a low contamination with Hg when compared to fruiting bodies of many mushroom species. The Hg contents ranged from 0.004 1 to 0.019 mg Hg per kg dry matter with a median value of 0.011 mg·kg-1 dry matter and an overall mean value of (0.011±0.004) mg·kg-1 dry matter. Mercury content of sclerotia varied between the places of collection in mountainous Yunnan. Assessed intake of Hg by adult eating 50 g of the “average” Yunnan’s origin sclerotia contained in the “Fuling jiabing” snack could be between 0.000 009 2 and 0.000 55 mg per capita or between 0.000 003 4 and 0.000 016 mg per kg body mass for a typical adult of mass 60 kg, which is a low intake and Hg intakes would even be much less if taking decoctions of sclerotia. This study has revealed that sclerotia of W. extensa showed a weak contamination with Hg and possible Hg intake eating sclerotia of W. extensa is below health limits. Also Hg intake from the decoctions of W. extensa is much below health limits and “fuling jiabing” snack made of sclerotia of W. extensa provides little Hg.