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In integrating lab-on-a-chip (LOC) technologies facilitated with a series of microfluidic units, microfluidic channels, with substrates put into metal nanoparticles, especially when gold, silver or copper nanoparticles, were prepared and pumped into μl or nl analytes. This sample preparation methods have important significance in real time, in-situ trace- or processing reaction analysis jointing with surface enhanced spectroscopies (SES).This combined technologies would integrate the mertis of the two technologies of lab-on-a-chip LOC and SES. LOC has the advantages of minuming the amount of analytes and stable test environments for step by step processing operations to achieve screening samples, segmentating, real-time detecting and so on, whiel SES has the characteristics of fast spectral response, high sensitivemess and selectivness,and in-situ detectoring. On the base of Drude medol and appropriate boundary conditions, external electric field induces localizing plasmon oscillation of valence electron of metal nano particles, then which derivates the mechannisms of resonant localized suface plasmon enhancement and electromagnetic enhancement mechanism of the surface enhanced Raman scattering by dipole polarization. In this paper, combined LOC and localized surface plasmon resonance technologies analysed in biological, pharmaceutical and food safety fileds with additional channels prompting detecting efficiencies and the limits of trace detections further being broken out. This paper also summarizes the application of chip laboratory technology in the fields of public safety testing, biomedical medicine detecting, electrochemical or biological sensors with surface enhanced Raman spectroscopieswhich were capable of high sensitivitiness and molecular spectral fingerprint. LOC technologies have gotten great develoment in their respective fileds, especially combinning with 3D fingerprint technologies, which could precisely control the sizes of 3D structures and high-accuracy manufacture 3D structures according to the special purpose. LSPR and SERS have been more maturing in some applications of near filed imaging and Tip-enhanced Raman spectroscopies (TERS), which have the ability to break through the optical limit of conventional microscopes and do that the width and depth of the SES technologies have been greatly extended in the micro and nano scales. So The jointed technologies would have a bright prospects in the practical applications for the qualitative and semi quantitative determination of trace analysis.

In order to research the effect of X-ray fluorescence (XRF) analysis on the results in the sample’s micro particles, MCNPX models had been established for an X-ray fluorescence analyzer in this paper. It had studied the characteristics of the samples with different particle sizes, the fluorescence peak counts, the peak to total ratios and the peak to source ratios. A micro particle analysis experiment had been designed for its verification. The results showed that: as for the relationship between the fluorescence intensity and the particle sizes, the MCNPX calculations were consistent with the theoretical, but contrary with the experimental results; the reason is that some hypotheses about samples in the MCNPX models were contrary with the actual states; the samples were crushed by grinding to small particles and tableting process, the MCNPX calculations and experimental results can be conversion; when the particle sizes of the samples reached the certain sizes, the fluorescence peak counts, the peak to total ratios and the peak to source ratios were stable value; within a particular size range, the influence of the particle size effects cannot be ignored, otherwise this influence can be ignored. The research methods and conclusions in this paper can provide a technical reference guide for X-ray analysis in practices.

For the small frequency shift and large error of tunable diode laser absorption spectroscopy (TDLAS) velocity method based on Doppler Effect in measuring the gas velocity, velocity measurement method combined fixed wavelength absorption spectroscopy and cross correlation is proposed in this paper. Considering the characteristics of the hydrocarbon fuel combustion products, 7 158.597 cm(- 1) absorption line of H(2)O molecular was selected. Through arranging two beams of fixed wavelength absorption measurement point of upstream and downstream, the gas velocity can be calculated by analyzing the cross-correlation properties of the two signals. The flat flame burner experiment system was used in the experimental research of the velocity measurement. The change of gas velocity with time under variable working condition was obtained. Under the same condition, numerical calculation is carried out. And the measurement results are compared with the results of the numerical simulation with relative deviation less than 8%. Then the method is preliminarily applied to measure the high speed plume of the kerosene-fueled Rocket Based Combined Cycle (RBCC) engine, and the upstream and downstream fluctuant signals of detectors were obtained. The velocity of the plume was calculated with cross correlation analysis which verifies the feasibility of this method. The experimental results show that the gas velocity measurement method has a wide measuring range with high measuring accuracy and little environment interference. The method proposed in this paper provides a simple and reliable method for the measurement of engine gas velocity.

Supercontinuum laser refers to the spectral broadening of an incident laser beam due to a series of nonlinear effects when the incident beam passes through a special light guide. With the development of ultrafast lasers and the photonic crystal fiber technology, the coherent and bright supercontinuum laser, generated with ultrashort pulses propagating in photonic crystal fibers, has become a kind of ideal white light source. Since supercontinuum lasers have been put into practice, their application domain is getting wider, especially for cells and bloods analysis in the biomedical field with fluorescence spectroscopy, flow cytometry, confocal microscopy, and optical coherence tomography as powerful analysis tools. Supercontinuum laser source has become one of the mail optical components in these scientific instruments that employ advanced technologies. In this paper, international research progress on supercontinuum laser sources was introduced in detail firstly, and then the development and application of supercontinuum laser spectroscopy technology in biomedical fields, such as microscopic imaging, flow cytometry instrument, fluorescence lifetime imaging microscopy, fluorescence resonance energy transfer, optical coherence tomography, and confocal microscopy was comprehensively elaborated. The requirements, schemes and research progress of supercontinuum laser spectroscopy technologies in the noncontact identification for blood products were also discussed in the paper, including studies on light fiber supercontinuum laser sources with spectra range from 400 to 2000nm, distinguishing species characteristic of bloods with supercontinuum laser spectroscopy, analyzing and establishing mathematical models based on meta databases of big data bloods spectra, determining the bloods species based on these models, and developing portable instruments for bloods spectra identification. Finally, the prospect of applications of supercontinuum laser spectroscopy in the biomedical field is discussed.

With the transition of Chinese traditional medicine manufacture industry, modernization has become the inexorable tendency in its future development. However, during the current Chinese traditional medicine producing process, the lack of online monitoring leads to the lagging of quality detection, as well as quality differences between products. In this paper, aiming at realizing online monitoring and end point automatic determination for Chinese traditional medicine (CTM) extraction unit, which is one of the most important units in CTM producing, ultraviolet (UV) spectroscopy is applied to build UV absorbance dynamic model based on the Lambert-Beer law and the CTM extraction kinetic model which presents a new method of UV absorbance dynamic analysis and endpoint determination, including curve regression, robustness analysis and endpoint calculation. In the experiment for online monitoring homalomena occulta extraction, the online UV spectral collection system for CTM extraction, developed by our laboratory, was applied for spectral collection; meanwhile, solid component contents in the offline samples were measured as reference. During the analysis, first of all, we pretreated the spectrum collected in the current period with interpolation and smoothing, and calculated the mean value within a UV region of 230.2～400 nm to form an absorbance mean value sequence with data obtained in the early measurements; then we verified the linear correlation between the sequence of absorbance and the concentrations of effective component in the solution, the linear correlation coefficient equals 0.982 8, showing a high linearity between UV spectra and solid component contents; finally, we regressed the absorbance mean value sequence with the dynamic model, analyzing its robustness and the extraction endpoint. Experimental results demonstrate that, the robustness analysis could recognize the bad points of measurement during the regression process, and improve the consistency between the regression and the original curves, raising its squared correlation coefficient to more than 0.99; meanwhile, with endpoint determination, we shortened the homalomena occulta extraction process from the original manually set 180 to 122 min effectively. The experiment above proves that this method with UV spectroscopy realizes online monitoring and automatic endpoint determination for the CTM extraction process, and is of significant importance for stabilizing production as well as improving economic benefit.

In this paper, confocal Raman spectroscopy was applied to detect the contents of lead chrome green as a heavy-metal stain illegally added in tea. Firstly, Raman spectra of five different concentrations of lead chrome green in tea infusion were acquired based on specific concentration method. The qualitative analysis of sample added with lead chrome green was achieved with comparing the Raman spectra of sample and standard substance. Four main Raman characteristic wavenumbers, 1 341, 1 451, 1 527 and 1 593 cm(-1), were extracted for the qualitative identification of lead chrome green in tea. After spectral preprocessing of the raw Raman spectra, backward interval PLS (biPLS), competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) were combined to deeply mine the characteristic wavenumbers of lead chrome green in Raman spectra, and finally 14 characteristic wavenumbers were optimized. Partial least squares (PLS) and least square support vector machine (LS-SVM) were separately used to build the model based on the extracted 14 wavenumbers. As a result, these two models both had good robustness and high ability to predict and all the determination coefficient (R(2)) of calibration, validation and prediction were higher than 0.9, which proved the effectiveness of the extracted characteristic wavenumbers. Compared with the PLS model, the nonlinear model built by LS-SVM got a better result, R(2) of prediction was 0.964 and the root mean square error of prediction (RMSEP) was 0.535. This study indicated that it is feasible to detect the contents of lead chrome green illegally added in tea based on confocal Raman spectroscopy combined with specific sample treatment and chemometrics methods. This study helped the valid supervision of food safety problem on lead chrome green illegally added in tea.

Atmosphere high frequency plasma is widely used due to its advantages of free of electrode pollution, high energy density high temperature and controllable redox conditions. As the key parameter in practical use, electron temperature of plasma is commonly diagnosed with atomic emission spectroscopy and calculated with Boltzmann plots. But electron temperatures calculated based on different lines by different researchers are usually not comparable due to transition probability data, application environment, instrumental error and data processing. This paper discussed influences of element and spectral range on calculated electron temperature for the first time in order to obtain reliable electron temperature of atmosphere high frequency air plasma. 7-channel high resolution fiber spectrometer with measurement range of 200~1 077 nm was used to test atomic emission spectroscopy. The experiment indicates that: The R square of fitted slope is 0.95 and standard deviation is the lowest using N Ⅰ lines in 738~940 nm and the calculated electron temperature is the most reliable; electron temperature calculated with Si and O lines are unreliable because they are easily binding to heavy SiO2 particles; reliable electron temperature also cannot be obtained by mixed Ar lines.

Decanoic acid/porous activated carbon function material was made with microwave oven method from waste walnut shell and decanoic acid as the carrier and the phase change material respectively in this paper. Synthetic materials in different preparation stages (ie. precursor activated carbon preparation stage, porous activated carbon preparation stage and decanoic acid/porous activated carbon function material preparation stage) were measured with Fourier transform infrared spectrum. Complex network structure forming mechanism of porous activated carbon, decanoic acid embed mode, chimeric mechanism of decanoic acid and porous activated carbon were researched, respectively, in order to explain how to prepare decanoic acid/porous activated carbon function material with microwave oven method. Meanwhile, moisture property, thermal property and absorption property of this function material were tested by dynamic was used to vapor sorption, differential scanning calorimeter and environmental test chamber. The results show that the decanoic acid/porous activated carbon function material has developed pore structure and complex network composition, which adsorb the decanoic acid and formaldehyde molecules. Besides, the pore surface has some hydrophilic functional groups, which can adsorb the water molecules. The decanoic acid/porous activated carbon function material has good moisture property, thermal property and absorption property. Experiments suggest that the equilibrium moisture content can reach 0.063 1~0.257 g·g(-1) in the relative humidity ranges from 40% to 60%. While the phase transition temperature reaches 27.42~33.96 ℃, the phase change enthalpy is 52.14~52.67 J·g(-1). Besides, the adsorption efficiency of formaldehyde gas can reach 50.57% after 4 h.

In this paper, based on the measurements of soil elements content and infrared spectra of 26 soil samples collected in more than 10 places, the relationship between soil emissivity in mid-infrared bands and the content of 11 soil elements including organic matters such as NO(3)-N, P, K, Ca, Mg, Cu, Fe, Mn, Zn and pH are analyzed. The bands where the soil elements content are significantly correlated with emissivity are given. And soil elements content estimation method is established based on the soil emissivity spectra with the partial least squares regression model and multiple stepwise regression model. The results show that: (1) In 8~10 μm, the correlation coefficient (R(2)) between Ca and soil emissivity is the highest, followed by Mg, Mn and Fe, with the highest correlation coefficient of 0.85 and the lowest, 0.52. In the range of 6~8 μm, the correlations between the contents of K, Fe, NO(3)-N, Zn and emissivity decrease gradually, with the highest correlation coefficient of 0.75 and the lowest 0.48. In 10~14 μm, the correlation between soil elements contents and emissivity is the highest for Mn, followed successively by P and K. (2) The scatter plot of soil emissivity and pH value has a parabola relation basically. The emissivity is the highest when pH value is 7, while the emissivity decreases gradually with the gradual decrease of pH value. (3) The accuracy of the estimated soil elements content from the partial least squares regression method is higher than that from the multiple stepwise regression method. It is noted that R(2) between the measurements and the estimates for the elements of Cu, Fe and Ca from the partial least squares regression method are very high (larger than 0.9). Additionally, using the simulated emissivity spectrum in the ASTER thermal infrared bands, modeling R(2) and validation R(2) between the measurements and the estimates for the elements of Ca from the multiple stepwise regression method are high (0.774 and 0.892, respectively). Using the simulated emissivity spectrum in the MODIS infrared bands, modeling R(2) and validation R(2) for Ca and Fe are higher than 0.85, and modeling R(2) and validation R(2) for Mg, K are higher than 0.5. As a whole, the emissivity spectrum in ASTER band 10 and band 11 and MODIS bands 28, 29, 30 are more sensitive to soil elements content, and thus they are more suitable for the estimation of soil elements content.

As emerging modalities, terahertz time-domain spectroscopy and imaging have been widely applied to investigate the optical properties of different biological tissues. The substrate materials are usually needed for biological spectroscopic measurements. The ultra-broadband and facility in remote sensing of the terahertz air-biased-coherent-detection (ABCD) system mean it is a good potential tool for the spectroscopic study of biological tissues. In this paper, the optical parameters of four typical substrate materials (quartz, high-density polyethylene, teflon and paraffin) are measured using terahertz ABCD spectrometer. The absorption coefficients and refractive indices are presented in the frequency range of 1～15 THz. It is demonstrated that high-density polyethylene and paraffin are good candidates as sample substrate for broadband terahertz biological spectroscopic measurement. However, quartz and teflon which are common substrate materials in narrowband (0.1～3 THz) terahertz system can not be utilized in high terahertz frequency range because they have strong absorption above 5 THz.

Semiconductor detector is widely used in energy dispersive X-ray fluorescence measurements due to its excellent performance. In this paper, Si-PIN and CdTe semiconductor detectors were studied, performances of the two detectors were compared in material properties, detection efficiency, energy resolution and other aspects. Focused on the performance of the detectors influenced by the thickness of detector sensitive area, energy of incident X-ray, shaping time of post-stage circuit, and analyzed the differences of energy spectrum caused by escape peaks and hole trailing. Aiming at the problem of incomplete hole collection in detector, a digital multi-channel analyzer (DMCA) based on FPGA with rise-time discriminator was designed, it could reduce the influence of hole trailing effectively and improve energy resolution. The experimentation results indicate that the detection efficiency of Si-PIN and CdTe is roughly equal when energy is below 15 keV while CdTe has much higher detection efficiency than Si-PIN when energy is above 15 keV. The optimum forming time of the Si-PIN detector is about 10 μs, and the CdTe detector is about 2.6 μs, so the CdTe detector is more suitable for the high count rate condition. Si-PIN detector has better energy resolution than CdTe detector for different energy incident X-ray. CdTe detector has obvious hole tailing effect and the energy resolution of CdTe detector is significantly improved by using DMCA with rise-time discrimination.

In this paper, hyperspectral imaging combined with chemometrics was applied for the detection of internal defects of Korla pear. The hyperspectral images covering the spectral range of 380～1 030 nm were acquired for 60 Korla pears before, and seven consecutive days after internal damages were induced by being dropped from a distance of 30 cm. The mean spectrum were computed from region of interests (ROI) of pear in each image, and was preprocessed with wavelet transform for eliminating system noise and external disturbances, and optimizing the spectral identification region (470～963 nm). Based on the preprocessed samples, the support vector machine models were built respectively through the full and feature wavebands selected by the second derivative. The results on testing set demonstrate that both of the two approaches achieved the discrimination accuracy of 93.75%. Furthermore, F-value based method was applied for image analysis to find out the optimal waveband ratio for the visual discrimination of bruises against normal surface. Based on the optimal waveband ratio images, the selective search algorithm was utilized for segmenting bruises from the pear surface, and shows the accurate identification results. Our research revealed that the hyperspectral imaging technique for detecting bruised features in pears is feasible, which could provide a theoretical reference and basis for designing classification system of fruits in further work.

In this paper, a series of CaMoO4 phosphor co-doped rare earth ions were prepared with chemistry co-precipitation method. The concentration of Pr(3+)/Tb(3+) and temperature had obvious influence on the luminescent properties. The crystal structures and spectrum characteristics of the samples were identified with X-ray powder diffraction (XRD) and fluorescence spectrophotometer (PL). According to XRD analysis, the main diffraction peaks of samples are consistent with the standard card (JCPDS 29-0351) of the diffraction peak data. This showed doped rare earth ions did not change matrix lattice structure. The emission spectrum excited by 275 nm exhibit sharp lines peaking at 488, 560, 621 and 560 nm assigned to the (3)P(0)—(3)H(4), (3)P(0)—(3)H(5)，(1)D(2)—(3)H(4) and (3)P(0)—(3)F(2) transitions of the Pr(3+) ions. The intensity of fluorescence reached the strongest when the concentration of the doping amount was 3%. The optimum calcination temperatures of CaMoO(4)∶0.03Pr(3+) and CaMoO(4)∶0.05Tb(3+) were 800 and 600 ℃. Furthermore, the intensity of excitation spectra and emission spectra are dependent on the concentration of the doping amount. The emission spectra intensities of CaMoO(4)∶Pr(3+) phosphors decrease and CaMoO(4)∶Tb(3+) phosphors firstly increase and then decrease because of concentration quenching effect with increasing Pr(3+) and Tb(3+) concentration. In addition, the luminescence properties of Pr(3+) ion in CaMoO(4)∶0.03Pr(3+), yTb(3+) system could be evidently improved with co-doping of Tb(3+) ions which was due to the efficient energy transfer process from Tb(3+) to Pr(3+) ions.

As an important part in the modern warfare, camouflage technology plays a critical role in the battlefield, and the results of detection of camouflage target directly affect the results of war. However, there is little paper to detect camouflage paint by depolarization characteristics, so it is of great significance to use the depolarization technology to study the distinguishment of camouflage paints. To address this issue, we studied the mechanism of the scattering of electromagnetic wave, and analysed the relationship between the characteristics of depolarization and mechanism of scattering. Jones Matrix and Mueller Matrix were used to set up the physical model, and the Mueller-Jones Matrix was decomposed with the characteristics of polarization, then the depolarization coefficients(ωd) of the surfaces of the samples was acquired. In this experiment, we measured soil and three kinds of camouflage yellow paints in seven different incident angles to analyze the characteristics of depolazation of the soil and three kinds of camouflage yellow paints’ surfaces. Finally, we applied the theory of Fresnel formulas to verify the theoretical model. The results showed that: the depolarization coefficients of the samples’ surfaces were related to the scattering, and with the increase of the incident angles, the depolarization coefficients were decline. But in the whole measurement process, the depolarization coefficients of the soil were far above the camouflage paints’. Research indicated that: this article was the first paper which used the depolarization coefficients as an important parameter to identify the camouflage targets, and could identify the camouflage yellow paints in the soil-background accurately and effectively. The processes of the experiments were simpler, and the time was shorter. In modern battlefield, it could identify the camouflage targets quickly and easily, and furnish the precious time for the victory of the war. Therefore, the depolarization technology had a great application value, and the paper had very important significance on the development of camouflage recognition technology.

Cultural relics are non-renewable precious heritages, while artworks are limited cultural fortune. Therefore, it cannot afford any damage when cultural relics and artworks are analyzed. Fiber optic reflectance spectroscopy (FORS) has features of non-destructive testing, direct measurement and remote analysis and has its unique advantages in the research of cultural relics and artworks. This paper introduced the application of FORS in the identification pigments and dyes, the analysis of binders and the research of conservation results and preservation environments. Detection limits, reproducibility and signal characterization method were discussed. The future development of FORS in the research of cultural relics and artworks was summarized.

Camellia oleifera oil has the reputation of “oriental olive oil”; it is important to detect the adulterated camellia oleifera oil. In this paper, NIR spectra were used to detect camellia oleifera oil adulterated with sunflower oil. Camellia oleifera oil adulterated with varying mass fraction of sunflower oil were prepared, i. e., 11 samples in 0%～10% with the gradient of 1%, 6 samples in 15%～40% with the gradient of 5%, 6 samples in 50%～100% with the gradient of 10%, and all the samples were divided into four groups such as A(0%～5%), B(6%～10%), C(15%～40%) and D(50%～100%). A total of 207 absorbance spectra(1 000～2 500 nm) were acquired by sampling 9 times in each adulteration. Calibration set was consist of two-thirds of the spectra data in each group selected randomly, and the validation set was made up of the last spectral data. After removing the noise in both ends of the spectra, principal component analysis(PCA) was used to reduce the dimensionality, then the first four PCs were used to build the support vector machine (SVM) identification model, and the identification accuracies of 96.38% and 94.20% in calibration and validation set were obtained. Furthermore, five characteristic wavelengths (1 212, 1 705, 1 826, 1 905 and 2 148 nm) were selected based on the loading of the PCs, the peaks or troughs of the original spectra and the chemical functional groups they were corresponding to. A NIR simplified SVM identification model was built by them, and the identification accuracies were 94.20% and 92.75%. Overall, both NIR spectroscopy and NIR characteristic spectra can realize the identification of camellia oleifera oil adulterated with sunflower oil, and the characteristic wavelengths, selected in this study, provide a basis for the design of corresponding instrument.

The ancient fossils are formed by the ancient animals and plants after a long geological period and geological processes. They have witnessed the history of the earth and recorded the information of the evolution of the earth’s ecological environment; Meteorites traveling in the solar system for a long time with the abrasion of nuclear reactions and atmosphere of the universe, have formed a unique shape and texture. They recorded the original information about the formation and evolution of out space. The analysis of the ancient fossils composition is the scientific basis for the study of the origin and evolution of the earth; the meteorites as rock sample from outer space are gifts from nature. They are extremely valuable and rare; the analysis of the composition of meteorites can provide a better foundation for the development of the foreign planet exploration and the development of the celestial chemistry. In this paper, the method of sample dissolution was selected and optimized. The final choice of nitric acid, hydrofluoric acid and perchloric acid as the mixed reagent, a microwave digestion method was used in treatment of ancient fossil samples; The aqua regia, nitric acid, hydrofluoric acid and perchloric acid as the mixed reagent, both microwave digestion method and wet digestion method were used in treatment of meteorite samples. Inductively coupled plasma atomic emission spectrometry (ICP-AES) was used to determine three different ancient fossil samples and three meteorite samples. And the content of same elements was compared. Analysis results show that the ancient fossils and meteorites contain Pb, Hg, Ge, Fe, Ni, Cu, Co, Mn and other heavy metal elements as well as part of the rare earth element. The standard addition recovery of the method was between 98.2%~106%, and the relative standard deviation was less than 2.12%. The method had high sensitivity, accuracy and precision.

Caulis spatholobi and caulis sargentodoxae are two different kinds of traditional Chinese medicine, which are similar to each other in appearance, but they are from differ sources with different functions.. This paper presents their spectrum using terahertz time-domain spectroscopy technology combines spectral matching algorithm to identify five different kinds of these samples. Due to the complex chemical composition of traditional Chinese medicine, different components of the characteristic absorption peak occurred easily mutually overlapping, therefore, it’s very difficult to find obvious characteristic absorption peak in terahertz range, caulis spatholobi and caulis like this. Every sample was measured 10 times in some position. These standard spectral data have been calculated in different frequency, data show good stability in range of 0.2~1.3 THz. The second order differential method is used to process the THz spectrum data from 0.2~1.3 THz. These tiny differences of absorption coefficient have been hemerged between caulis sargentodoxae and caulis spatholobi and compare with these data using the method of correlation coefficient block coding method, spectral angle method and information divergence method, respectively. The analysis results, the spectral angle method is the best algorithm, the discriminate accuracy of a total of 100 sets of data is 95%. It is a new way to distinguish difference of traditional Chinese medicine.

In order to predict the content of chlorophyll in tomato rapidly and accurately, this study, with spectrum technology, focused on the extraction of sensitive spectral bands of tomato chlorophyll in glass greenhouse environment and created an effective estimation model. During the period of cultivating tomatoes, leaf spectra were measured with an ASD FieldSpec HH spectrophotometer and chlorophyll content was measured with Type 752 UV-Vis spectrophotometer. Based on the original spectra, absorbance spectra, first derivative spectra and continuum removal spectra, spectral data was preprocessed, in which the effectiveness of spectral features of chlorophyll content of tomato was highlighted and spectral response characteristics of the absorbance spectra in the visible part was enhanced. It was shown that both the continuum removal spectra and the first derivative spectra have strong blue and red absorption valley and green reflection peak. In this paper, the original spectrum, absorbance spectrum, first derivative spectrum and continuum removal spectrum were analyzed and compared, and then optimal spectral feature parameters were extracted with methods of Inter-Correlation analysis and multivariate collinearity diagnosis. Sensitive bands from original spectrum are 639, 672, 696, 750 and 768 nm. Sensitive bands from absorbance spectrum are 638, 663, 750 and 763 nm. Sensitive bands from first derivative spectrum are 516, 559 and 778 nm. Sensitive bands from continuum removal spectrum are 436, 564, 591, 612, 635, 683 and 760 nm. The stepwise multiple regressions were used to develop the prediction models of the chlorophyll content of tomato leaf. The result showed that the prediction model, which used the values from continuum removal spectrum at 436, 564, 591, 612, 635, 683, 760 nm as input variables, had the best predictive ability. The calibration R-Square was 0.88 and the validation R-Square was 0.82.

Nowadays, a great quantity of heat treating corundums are emerging in our market. It is hard to distinguish them scientifically just by conventional methods. In order to accurately determine whether the corundums have been heated or not, we need to analyse their spectral characteristics. This paper describes the spectroscopy identification of untreated and heated corundum. The experiment is conducted as follows: First, We observed the inclusions of corundum samples, then measured and recorded their infrared spectra, UV-Vis spectra by Fourier Transform Infrared Spectrometer and Ultraviolet-visible Spectrophotometer respectively. Next we chose a part of samples to heat, after the heat treatment, we recorded their spectra and made a comparison with that of untreated corundums. The results showed that we can detect the absorption peaks at 1 980 and 2 110 cm(-1) which represent diaspore in untreated ruby. However, after heat treatment, the absorption peaks disappear which means the structure of AlO(OH) has been destroyed. The sapphires which grown in alkali basalt under reductive condition appear the absorption peak at 3 310 cm(-1). However, this peak vanishes after 18 h heat treatment when the temperature is 1 600 ℃. For UV-Vis spectra of ruby, after heat treatment, the slight shift occurs in strong, wide absorption band at around 555 nm, and this band becomes more pointed. In addition, absorption intensity difference between wave crest and wave hollow increases. The absorption bands at 375, 387, 454 nm of heated sapphires are more pointed than that of the untreated sapphires, and absorption intensity difference rises. These changes in spectral characteristics can help us to distinguish untreated corundum from heat treating corundum.

The skylines, superimposing on the target spectrum as a main noise, will reduce the signal-to-noise ratio of the spectrum. If the spectrum still contains a large number of high strength skylight residuals after sky-subtraction processing, it will not be conducive to the follow-up analysis of the target spectrum. At present, the study on the automatic recognition of the abnormal sky-subtraction stellar spectra is limited in number. We can only find the abnormal sky-subtraction spectra by manual inspection, and this will reduce the speed of detection. This paper analyzes the influence factors of sky-subtraction results and finds the characteristics of the abnormal sky-subtraction spectra. A simple and effective method is proposed to automatic recognize the abnormal sky-subtraction stellar spectra which have been processed with the LAMOST Pipeline processing procedure and find the positions of the abnormal skylines. In this method, all the spectra are normalized first; the abnormal skyline is determined by detecting whether there exits any high strength skyline residuals which are similar to the emission line or absorption line. Finally, all the abnormal skyline positions in the spectra are obtained in this method. The experimental results with the LAMOST spectroscopic dataset show that this method can recognize the abnormal sky-subtraction spectra and find the abnormal skyline positions of different residual strength effectively. In addition, the method is simple and has high recognition efficiency, and can be applied to the automatic detection of abnormal sky-subtraction of large number of spectra.

High voltage light emitting diodes (HV-LEDs) have potential advantages on general lighting application for their special features. But as novel power LEDs, their optical, electrical and thermal characteristics still need to be further studied. In this paper, 6 and 9 V GaN-based HV-LEDs were packaged in the same package structure and process conditions. The optical characteristics of two samples were investigated under different temperatures range from 10 to 70 ℃ which were calibrated to junction temperatures using thermal impedance measurement. To ensure the same current density, working current was set to 150 mA for 6 V sample and 100 mA for 9 V sample respectively. Results show that the increasing junction temperature has a great effect on EL spectra of two samples, such as peak wavelength red-shifting, full width at half maximum (FWHM) broadening, luminous efficiency reducing and color rendering index (CRI) increasing. The junction temperature of 9V sample is lower than that of 6 V sample in the same platform temperature and injection power. With temperature increasing, the extended quantitative value of FWHM for 9 V sample is 1.3 nm less than that of 6 V sample, the reduced quantitative value of luminous efficiency is 1.13 lm·W(-1) less than that of 6 V sample, while the increased quantitative value of CRI is 0.28 less than that of 6 V sample. Those data suggest that EL spectra of HV-LEDs is less affected by junction temperature than traditional LEDs. It is because HV-LEDs perform better in current spreading and generate less heat. This conclusion has reference value for study, development and applications of GaN-based HV-LEDs. In addition, peak wavelength still has a good linear relationship with junction temperature and it can be a temperature-sensitive parameter when the spectra measurement accuracy is enough.

The soluble lignin and furan compounds in hydrolysate of lignocellulose biomass have absorbed peaks and inter-superimpose in UV spectroscopy. Therefore, this paper developed a method for the determination of furfural and 5-hydroxymethyl furfural in ethanol-water refining liquors of lignocellulose biomass based on UV spectroscopy. The study showed that there is a good and linear relationship between maximum absorption (λmax) and the concentration percent of 5-HMF (W(5-HMF)) of M, the regression coefficient up to 0.998 4 (R(2)=0.998 4). Furthermore, a better linear relationship was also observed between the concentration of mixture (cM) and absorptivity (A) when the W(5-HMF) was constant, the R(2) of 0.998 6～1.000 0 and reproducibility are desirable. The contents of F and 5-HMF could be calculated accurately according to the perfect liner relationship of A and c(M), λ(max) and W(5-HMF), and the relative deviation of F and 5-HMF of 5.6% and 3.7%, recovery of 89%～96%, RSD of 0.21%～0.85%, respectively. Overall, The simple rapid and precise method in this paper can be applied to the determination of the F and 5-HMF in the hydrolysate of ethanol-water refining lignocellulose biomass.

This paper aimed to reveal the degradation behavior of a new type of biodegradable containers. The biodegradable containers, which was made of modified soybean adhesive and straw, was processed in situ biodegradation under natural condition. The physicochemical property and microstructure of straw nursery containers treated and untreated were characterized with Cellulose Tester, Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscope - Energy Dispersive X-ray Spectroscopy (SEM-EDS), and Thermo-gravimetry Analysis (TGA), respectively. The results indicated that the content of cellulose, hemicellulose and lignin of treated specimen decreased to 21.43%, 21.41% and 9.54% from 29.03%, 30.44% and 12.52%, respectively, comparing with those of untreated straw nursery container. FTIR analysis revealed that the ester and fat bond have been ruptured, and the aromatic characteristic peak became weakened. SEM-EDS spectrum showed the microfibril chain in the container has been fragmentation, and the soybean adhesive was also degradation. The surface of container appeared oxidization degradation. TGA analysis showed that a large number of small molecules have been produced in the process of degradation and the thermo-stability of treated samples improved.

In this paper, a new method based on LASSO algorithm is studied for the estimation of stellar alpha element abundance. The information of alpha elements (O, Mg, Ca, Si, and Ti) of massive stars will help us to better understand the evolution of the galaxy. Presently the main method of determining the alpha element abundances from the low resolution spectra is the template matching method. However, it is difficult for us to optimize the algorithm parameters and the algorithm is sensitive to the noise. Thus, it is necessary to study the new method to determine the abundance. The experimental results show that the accuracy of LASSO algorithm on ELODIE spectra is 0.003 (0.078) dex. To explore the impact of the spectral resolution variation, we use ELODIE spectra to generate the spectral data sets with following resolutions: 42 000, 21 000, 10 500, 4 200 and 2 100 by using the Gaussian convolution. The results of the LASSO algorithm on these data sets are 0.003 3 (0.078) dex, -0.05 (0.059) dex, -0.007 (0.069) dex and -0.004 5 (0.067) dex, respectively. These results show that the LASSO algorithm is not sensitive to the change of the resolution. In order to verify the robustness of LASSO algorithm against the change of SNRs, we use ELODIE to generate the spectral data sets with following SNRs: 30, 25, 20, 15 and 5. The results of LASSO algorithm on the above data sets are: -0.002 (0.076) dex, -0.090 (0.073) dex, 0.003 6 (0.075) dex, 0.007 6 (0.078) dex and -0.009 (0.080) dex, respectively. Thus, LASSO algorithm is not sensitive to the change of SNR. Therefore, the LASSO algorithm is suitable for low resolution and low SNR spectra such as LAMOST and SDSS spectra. The accuracy of Lasso algorithm on the SDSS spectra is 0.003 7 (0.097) dex, and the results of LASSO on globular and open clusters show good agreement with literature values (within 1σ). Therefore, the LASSO algorithm can be used to estimate the alpha element abundances of stars.

Currently, increasing importance has been attached to heavy metal pollution of water environment. In order to help geologist and environmentalist to obtain on-site experimental data, there is an urgent need to develop portable analysis techniques of water quality, which can be used to give an timely and accurate assessment of water quality of the contaminated area with low cost and to monitor water environment conveniently in daily preventing and controlling work of water pollution. Based on adsorption with Purolite S930 chelating resin at pH 4 and thin-film sample preparation technique, a rapid and simple on-site-oriented analysis method of heavy metal ions, namely Mn, Fe, Ni, Cu, Zn and Pb in aqueous solutions, was developed utilizing a handheld energy-dispersive X-ray fluorescence in this paper. The correlation coefficients of the calibration curves were greater than 0.992 for all six metal ions, the lower limits of detection were between 5.8 and 18.6 μg·L-1. Precision tests carried out on multi-element mixed solutions showed that the relative standard deviations (RSD, n=10) were better than 15%. The method has been used on-site to analysis 21 water samples collected from different river or well sites near a mining area northeast China. Out of the five underground water samples one was found contaminated by Cu and Zn (Class Ⅲ), one by Zn and Fe (Class Ⅱ), and one by Fe(in between Class Ⅱ to Ⅲ). Surface water samples showed better qualities. But two out of the sixteen were found to be contaminated by Mn heavily (Class Ⅳ). Laboratory ICPMS was used to analyze the same samples. The results for Cu, Ni and Pb were coincident with the on-site data in general. But for Zn and Mn with higher concentrations, on-site data were lower than that by ICPMS. The reason for that might be the inclusion of the fine suspending particles in the samples by ICPMS. We conclude that the on-site data were effective. With the described method, an overall data acquisition time, including sampling, processing and measuring, can be within 12 hours for a batch of 10 samples. The pre-concentration device and the XRF instrument are both small, light, portable and can operate without external power supply. So, the method is suitable for on-site water sample analysis, especially in remote areas.

The modeling and predicting of vegetation Leaf area index (LAI) is an important component of land surface model and assimilation of remote sensing data. The MODIS LAI product (i.e. MOD15A2) is one of the most widely used LAI data sources. However, the time series of MODIS LAI contains some data of low quality. For example, because of the influence of the cloud, aerosol, etc., the MODIS LAI presents the characteristics of the discontinuous in time and space. In fact, the time series of MODIS LAI include both linear and nonlinear components, which cannot be accurately modeled and predicted by either linear method or nonlinear method alone. In this paper, the original LAI time series data were first smoothed with Savitzky-Golay (SG) filtration and linear interpolation; SARIMA, BP neural network and a hybrid method of SARIMA-BP neural network were then used for modeling and predicting MODIS LAI time series. The SARIMA-BP neural network combined both SARIMA and BP neural network, which could model the linear and the nonlinear component of MODIS LAI time series respectively. That is, the final result of SARIMA-BP neural network was the sum of results of the two methods. Experiments showed that the time series of MODIS LAI that were smoothed with the SG filtration and linear interpolation were more smooth than original time series, with a determination coefficient up to 0.981, closer to 1 than that of SARIMA (0.941) and BP neural network (0.884); the correlation coefficient between SARIMA-BP neural network and the observation is 0.991, higher than that of between SARIMA (0.971) or BP neural network (0.942) SARIMA and the observation. Thus, it can be concluded that, the proposed SARIMA-BP neural network method can better adapt to the LAI time series, and it outperforms the SARIMA and BP neural network methods.

Because of its small volume, simple structure, low energy consumption, low working temperature, strong ability of sample dissociation/excitation and other significant characteristics, the dielectric barrier discharge is especially suitable for the miniaturization and portable analytical instruments. By now, atomizer or excitation source based on dielectric barrier discharge has applied in atomic absorption spectrometer, atomic fluorescence spectrometer and atomic emission spectrometer successfully, which promoted the development of miniaturization atomic spectrum instrument. This paper reviews DBD’s recent progress in atomic spectrum field, emphatically introduces the applications of the DBD-AFS system in different sampling modes and analyses, along with their respective merits and demerits. This paper also introduces the new applications of DBD in vapor generation and direct solid sampling. Due to the DBD’s reaction mechanism is still unclear; the study of its subsequent development may be restricted.

CO(2) retrievals with high quality facilitate resolving the sources and sinks of CO(2) are helpful in predicting the trend in climate change and understanding the global carbon cycle. Based on a nonlinear least squares spectral fitting algorithm, we investigate the optimization method for CO2 products derived from ground-based high resolution Fourier transform infrared spectra. The CO(2) vertical column densities (VCDs) are converted into column-averaged dry air mole fraction XCO(2) by using the fitted O(2) VCDs, and thus the system errors (e. g. pointing errors, ILS errors, zero-level offset) are corrected greatly. The virtual daily variation which is related to air mass factor is corrected with an empirical model. The spectra screening rule proposed in this paper can greatly improve the XCO2 quality. The CO(2) retrievals before and after the optimized method are compared using a typical CO(2) daily time series. After using the optimized method, the fitting error is reduced by 60%, and the two-hours-averaged precision is ~0.071% (equals to ~0.28 ppm), which is perfectly in line with the TCCON (the total carbon column observing network) threshold, i. e., less than 0.1%.

In order to expand the application range of the model for a single kind of fruits in the portable near infrared instrument, this paper comes up with a new method for the soluble solid content (SSC) model transfer between different kinds of fruits. This method is focusing on the idea of model transfer between different instruments. Based on the similar physical and chemical properties of apples, peaches and pears, such as the range of SSC content, fruit size and the thickness of peel, a simple Slope/Bias algorithm is applied to the transfer of apple SSC partial least square (PLS) model. After that, it can be used to predict pear & peach SSC value with very little extra samples. It’s more convenient and costs less by using this method. For pear samples, by using extra 35 standard samples to transfer apple SSC model, RMSEP reduced from 1.009 °Brix to 0.565 °Brix. For peaches, extra 40 standard samples led to a significant reduce of RMSEP from 1.726 °Brix to 0.677 °Brix after model transfer. To validate the feasibility of this model transfer method, both pear and peach SSC models were tested using the same Slope/Bias algorithm model transfer respectively. A pear SSC model was firstly set up and then transferred with Slope/Bias method. Taking 30 standard apples as samples, RMSEP value reached 0.597°Brix, while taking 40 standard peaches as samples, RMSEP value reached 0.689°Brix. The peach SSC model was transferred in the same way. For apples, using 35 standard samples, RMSEP value reached 0.654°Brix, and for pears, using 30 standard samples, RMSEP value reached 0.439°Brix. These results show that slope/bias algorithm can be used to transfer model between similar kinds of fruits such as apples, pears and peaches. The paper provides innovative ideas for the model transfer among similar kinds of materials, so that the portable near infrared instruments can be used more conveniently and widely.

Based on the difference of the depolarization of the emitted light before and after the interaction of molecules, fluorescence anisotropy, also known as fluorescence polarization, can be beneficial for the study of interactions and the detection of the targets. In 1950s, Gregorio Weber first studied the interactions between dansyl chloride and bovine serum albumin or ovalbumin with fluorescence anisotropy method, which paved the way for fluorescence anisotropy in biochemical applications. Since the early 1990s, functional nucleic acids (FNAs, including aptamers, and nucleic acid enzymes) were discovered and synthesized, which have been widely used in functional nucleic acid-based sensing. Aptamers are oligonucleotides that can recognize and bind specifically to various molecular targets. The fluorescence anisotropy methods which are based on aptamer recognition have the advantages of high selectivity, sensitivity and through-put. They play an important role in the study of interaction with protein, nucleic acids and small molecules. However, the way of enhancing the fluorescence anisotropy change of small molecules associated with the binding events is challenging. This paper reviews the basic principles and designs of fluorescence anisotropy methods bases on functional nucleic acid recognition for study and detection of proteins, nucleic acids and small molecules that play an important role in the life activity.

Due to the needs of industrial development, the different content and uncertain distribution of magnesite mineral lead to great difficulties in o determining its grade, therefore, we propose a combination of near-infrared spectroscopy and the ELM magnesite grade classification model. The model can achieve rapid classification of magnesite grade. Near infrared spectroscopy, considering that different types of H group in magnesite have different absorption degrees to near-infrared spectroscopy, is used to determine the composition and content of magnesite. It is simple, fast, accurate and efficient without destroying the sample. In this paper, we take magnesite 30 group from Yingkou City, Liaoning Province Dashiqiao for the study, collecting their magnesite NIR data samples at 30×973, using principal component analysis (PCA) for data dimensionality reduction process. The main element contribution rate is greater than 99.99% obtained characteristic variables of 10, established quantitative analysis ELM algorithm mathematical model, take 20 groups of samples as the training samples (including 6 super group, 14 groups non), 10 groups of samples for testing samples (including super grade4 groups, 6 groups non), ELM algorithm model hidden layer nodes selection 20. In order to further improve the classification performance, two kinds improved ELM algorithm models are proposed: conduct optimization selection ELM for the traditional ELM input weights and threshold using the circulation patterns and integrate integration-Featured ELM based on Featured ELM. And compare to which use the artificial method, chemical method and BP neural network model approach. The results showed that magnesite grade classification with the near-infrared spectroscopy and ELM model have a distinct advantage regardless of cost or time, and the accuracy rate can reach over 90%, which provides a new way to classify magnesite grade.

In this paper, a kind of snapshot imaging spectrometer is designed by using image replication based on Wollaston prism. The system includes telephoto lens, collimator lens, Wollaston prism, the imaging lens and compensation filters. With this optical system, we can obtain two-dimensional information at different wavelengths of the same target through one time exposure. When Light beam is passing Wollaston prisms, in order to make sure that the different wavelengths will not overlap, the Wollaston prism needs to be designed with relatively large beam splitting angle. Then the incidence angle of the imaging lens is relatively large. It will increase the difficulty of the imaging lens design. We design, analyze the principle and the characteristics of the snapshot imaging spectrometer using image replication based on Wollaston prism, and design a complete set of imaging spectrometer system. The structure is complex; the aperture of the optical system must be well matched. In order to make sure that we can obtain good image quality through the single lens, but also the whole system, we design the telephoto lens which is imaging telecentric structure, the collimator lens which is objective telecentric structure. We use the multiple structures in ZEMAX to optimize the 16 spectral bands. At 56 lp·mm(-1), the MTF is close to the diffraction limit, the RMS of the SPT is in the Airy disk, proving good image quality.

Our daily life is disturbed seriously by the haze weather now. It is very important to measure the haze composition quantificationally. The main composition of haze is SO(2), NO(2) and particles. At present, the research of measuring gas and particle simultaneously is rare relatively. This paper use differential optical absorption spectroscopy (DOAS) to simulate the concentration measurement of gas and particle simultaneously and obtain some meaningful results. Absorption spectral of many groups of different concentration of SO(2), NO(2) and particle were simulated, and each concentration was inverted by DOAS. In the first group of single component, the concentration change from 100 to 1 000 ppm, the inverted error of SO(2) is not greater than 0.17%, and which is 0.64% for NO(2). When the diameter of particle change from 100 to 500 nm, the inverted error is not greater than 2.08%. In the second group of multiple gases, when the concentration ratio of SO(2) and NO(2) is at the range of 1 : 10 and 5 : 1, the error of SO(2) is not bigger than 8%, and 5% for NO(2), relatively. But when the concentration of SO(2) is 10 times than NO(2), the error is higher than 10% for NO(2). In the third group of gas and particle, the error of gas concentration is lower than 10%, but the concentration error of particle is depended on signal to noise ratio (SNR) greatly. When SNR is higher than 40 dB, error can lower than 10% and when SNR is lower than 30dB, the error is bigger than 20%. From these results, we can see that DOAS can measurement SO(2), NO(2) and particles simultaneously effectively, and can applied to measure and analyze haze composition. However, when the absorption strength of the gases is different greatly, the strong absorption gas influent the weak absorption gas largely. And the SNR is lower, the error of inverted particle concentration increased greatly. The solution of these problems need better filtering and noise reduction method.

Glutathione (GSH) is an important three-peptide molecule, which has the functions of antioxidation and detoxification, and plays a crucial role in the fields of biology, medicine and food science. It is involved in many important biochemical reactions in cells and body fluid, and the changes of GSH content reflect the specific health problems of human body. Current methods of GSH detection are always complicated, time-consuming and expensive instrument depended, such as surface enhanced Raman spectroscopy (SERS), electrochemical analysis, high performance liquid chromatography (HPLC) and so on. The probe’s photochemical properties can be modified by the reaction between GSH and nanoclusters, which will result in the changes of fluorescence intensity and wavelength. In this paper, a new method to realize precise and rapid GSH detection is developed by using silver na-noclusters as a fluorescent probe, and simultaneously measures the probe’s fluorescence intensity and wavelength. The synthesis of the fluorescence probe reported in this paper possesses the advantages of steps-simple and pollution free, and the GSH detection method has faster response, more accurate measurement and smaller relative error over the traditional methods. The good specificity of GSH detection among other molecules with the similar structure is further proved in control group experiments by comparing the differences of their fluorescence intensities and wavelength. The measurement accuracy is fully assured due to the insensitivity of the probe to a variety of salt ions and amino acids. This technique can be further employed in the intracellular detection and imaging of GSH.

By virtue of the characters of rapid analysis and simple pretreatment, near infrared reflectance spectroscopy technique is widely used in agriculture, medicine, environment, petrochemical and other fields. To satisfy the rapid on-site identification and analysis, portable near-infrared spectrometers have gained more and more attention. Because near infrared reflectance spectroscopy technique also is a green tool for multi-component analysis, the paper aims at investigating the feasibility for simultaneous quantitative analysis of various heavy metal ions in dilute solution using portable near infrared spectrometer. First, amino modified polymerized starch was used as adsorbent to enrich nickel ions and copper ions in diluted solution. Then, the diffuse reflectance spectra of amino modified polymerized starch samples were measured directly by portable near-infrared spectrometer. Furthermore, with the help of spectral preprocessing methods and partial least-squares regression, quantitative models were built from the near infrared diffuse reflectance spectra of amino modified polymerized starch enriched with heavy metal ions and reference concentrations. At last, the stability of the models was proved through cross validation and external validation. The results show that nickel ions and copper ions in diluted solution can be efficiently enriched by amino modified polymerized starch in the presence of other interfering ions. The adsorption rates for nickel ions and copper ions are 99.5% and 99.8%, respectively. Two robust models can be achieved after spectra processing and partial least squares regression. The spectra processing methods contains Continuous wavelet transform and multiplicative scatter correction combined with Savitzky-Golay. The obtained corresponding correlation coefficients of the two robust models are 0.981 9 and 0.965 4, respectively. Thus, simultaneous quantitative analysis of nickel ions and copper ions in the mixed diluted solution was achieved, and the detectable concentrations of nickel ions and copper ions are both as low as 3.0 mg·L(-1). The method not only improves the sensitivity of near infrared reflectance spectroscopy technique, but also demonstrates the feasibility for simultaneous quantitative determination of various heavy metal ions by using portable near infrared spectrometer. Moreover, the method may be a useful exploration to further broaden the application of near infrared reflectance spectroscopy technique.

As a highly active free radical in vivo, peroxynitrite can damage various biological macromolecules and cause a series of major diseases, which is of great significance to determine its content and reactive mechanism. It is very difficult to capture the dynamic process of peroxynitrite due to its active property and fast reacted rate. In this paper, we firstly explored the kinetic characteristics of peroxynitrite and tyrosine with the presence of Hemoglobin and Hemin by using flow injection analyzer. The results showed that the oxidation processes of peroxynitrite and tyrosine catalyzed with hemoglobin and hemin were in accordance with Michaelis-Menten’s dynamics law; Based on the Michaelis constant (K(m)) and the maximum initial rate (V(max)), we deduced the reaction mechanism that peroxynitrite, catalyzed by mimic enzymes, directly oxidized tyrosine combined with mimic enzymes, rather than decomposed to · OH and O(-₂)·; In addition, we detected the rate constant of the reaction catalyzed by these two kinds of enzymes at different temperature and pH, resulting that the optimum conditions of hemoglobin to catalyze this system were 25 ℃ and pH 8, the rate constant was 1.035×10(6) mol·L(-1) · s(-1), while hemin was 37 ℃ and pH 9.5, the rate constant was 6.842×10(5) mol·L(-1) · s(-1); Comparing the kinetic parameters, K(m)Hb(4.46 μmol·L(-1))V(Hemin)(max)(0.026 ΔIF/s), we discovered that the rate constant of hemoglobin in optimum condition was greater than that in hemin, and the catalytic activity of hemoglobin was higher than that of hemin. All these results have provided kinetic parameters for the study of determining the content of peroxynitrite and exploring its reaction mechanism with enzymatic method. It also laid a theoretical foundation for developing new diagnosis technology to prevent and cure diseases caused by free radicals in vivo.

Spectrophotometric determination of the amount of zinc on the imprint left on hands by zinc coatings with 2-(5-Bromo-2-pyridylazo)-5-(diethylamino)-phenol (5-Br-PADAP) as a chromogenic reagent has been studied in this paper. The effect of reaction conditions including volume and pH of buffer solution as well as the volume of chromogenic reagent on the determination has also been studied. On the optimized condition, the standard curve of zinc has been established and the amount of zinc on the imprint left on hands by zinc coatings with different contact time and time elapse has been determined separately. As the results shown, the optimized reaction condition is 4 mL of boric acid and borax buffer solution(pH 8.0), 0.2 mL of 5-Br-PADAP with the concentration of 1 g·L(-1) and 1 mL of Triton-X-100 with volume fraction of 10%. Under this circumstance, high linearity of zinc is followed between 0 and 14 μg and the regression equation of zinc is y=1.851 34x+0.002 29. The amount of zinc on the imprint left on hands by zinc coatings, ranging from 0.425 to 2.377 μg·cm(-2), increases with contact time from 10 second to 5 min and varies insignificantly from 5 to 10 min. The amount of zinc left on hands declines sharply with time elapse from 0 h to 2 h, and then slowly from 2 to 7 h. The amount of zinc within 7 h is only 0.188 μg·cm(-2), which is 90% lower than that of 0 h. Therefore, it is suggested that the trace metal detection should be conducted as soon as possible. Besides, the amount of zinc on the imprint left on hands by zinc coatings with different time elapse is not entirely comply with the intensity of imprint left by zinc coatings. This demonstrates that the amount of zinc on hands is not the only factor influencing the intensity of imprint on hands with different time elapse. Additionally, it also proves the hypothesis that zinc in the complex of zinc and protein can be captured and bonded by 5-Br-PADAP resorting to a stronger chelating capacity in the experiment for the first time. The application of the combined methods in a macro and micro view is useful for study in mechanism of influencing factors in trace metal detection, which lays foundations l for further researches.

The key to extract the contents of cadmium in water by using remote sensing technique is to measure the spectrum of extinction coefficient per g·L(-1) and reflectance for its compounds. So in this paper, firstly, we choose two kinds of cadmium compounds, cadmium sulfide (CdS) and cadmium oxide (CdO), which are most commonly exsit in natural water, to measure the spectrums of extinction coefficient and reflectance for them. We use the equipment, designed on our own, which can adjust the path length of light passing and make our measuring results more accurate at visible and near-infrared wavelength range than others. Then we use Analytical Spectral Devices (ASD) spectrometer to measure the radiance of the light spot, which is from the direct light passed through cadmium compounds solutions of different concentrations reflected by the standard board. Using the ratio method to eliminate environmental errors and the effects of the thimbleful of suspended solids in water, we obtain the extinction coefficient per g·L(-1) of these two kinds of cadmium compounds from 400 to 900 nm. Secondly, we use ASD spectrometer to measure the reflectance spectrum of them in the sunny day at outdoor. The reflectance we obtain in this paper can help us to calculate the absorption and scattering coefficient per g·L(-1) in the future. The measuring results show that the extinction coefficient spectrum of CdS has two troughs at 550 and 830 nm and one peak at 675 nm. And the extinction coefficient spectrum of CdO decrease from purple to near-infrared. Both of their coefficient spectrums in blue are larger than green and red. And the value of the extinction coefficient per g·L(-1) of CdS is larger than CdO in the whole measuring wavelength range. The reflectance of CdS in yellow and red is larger than purple and blue, which increases rapidly from 500 to 650 nm and then leveling off. While the reflectance of CdO increase linearly from 525 to 900 nm. Both have obvious spectral characteristic. According to our results, the largest extinction coefficient appear at blue color, while the largest reflectance appear at yellow and red, which means that those bands are the most sensitive wavelength to detect the change of cadmium concentration in water. This study carries out with optical parameters measurements for optical activity of cadmium compounds specifically for water quality remote sensing for the first time. We conclude that the extinction coefficient and reflectance spectrums we obtained are reasonable, and the results can be used as the base parameter in the remote sensing inversion model for cadmium contents in water, which provides a breakthrough on using remote sensing technique to extract the heavy metal contents in water. Obtained these two optical parameters in this paper can provide powerful reference for band selection of the remote sensing image, which is used to extract cadmium contents in water, as well as provide the necessary important parameters of the remote sensing inversion model of cadmium contents in water.

For dual band visible/near infrared spectroscopy system (350~1 100 and 1 000~2 500 nm), there exsits a band overlap and for the same sample the reflectivity data were unlike due to the performance difference between instruments. A band connection and data fusion method was proposed in this paper to make better use of the dual-band data. A dual-band visible/near-infrared spectroscopy system was built in the study to collect 60 pork samples’ reflectance spectra. The reflectance spectra of samples were performed with pretreatment methods of Savitzky-Golay (S-G) and standard normal variable transform to eliminate the spectral noise. Then partial least squares regression (PLSR) prediction models of pork quality attributes (color, pH and cooking loss) based on single-band spectrum and dual-band spectrum were established, respectively. For the cross of two band overlap, the data were connected and integrated using the method put forward in this paper and then PLSR models were established based on the integrated data. The PLSR model yielded prediction result with correlation coefficient of validation (R(p)) of 0.948 8, 0.920 0, 0.950 5, 0.930 1 and 0.903 5 for L(*), a(*), b(*), pH value and cooking loss, respectively. To simplify the model, uninformative variables elimination (UVE) was employed to select characteristic variables. The experimental results show that the proposed method was able to achieve a better fusion of the two band spectral data, and it was good for the establishment of a more simplified and better prediction model.

Because of ground observation instruments and other factors, we can not recognize the space target only from the external shape in the image. Since the reflection spectrum of the space target is determined by the surface material of space object, spectral analysis technique can be used for classifying the space objects. Based on the K-nearest neighbor algorithm (KNN), a method called adaptive weight k-local hyperplane (AWKH) is proposed in this paper. The main improvement of the algorithm is that weight discrimination is added in the processes of calculating the hyperplane distance between predicted samples. The algorithm constructs a hyperplane model by using the difference between the groups and within group ratio for the weights of features. In order to verify the classification effectiveness and efficiency of the algorithm, this paper carried out four sets of verification experiments. In the first set of experiments, 9 kinds of common materials were extracted from the database of United State Geological Survey. Then 3 kinds of these materials were mixed into multi-class objections. In the second and third sets of experiments, the spectra of four normal space target materials were mixed in different classes. Then these classes were identified from the visible and near-infrared wave bands. In the fourth set of experiments, four square models of hexahedron were classified by the spectra of their surface material. The experimental results indicate that the AWKH algorithm has more advantages in identification accuracy and effectiveness of the complex samples by comparing with the support vector machine (SVM) method.

Raman spectroscopy plays an improtant role in analytical science because of its unique characteristics, such as non-contact and non-destructive detecting, fewer sample consumption, high sensitivity and other characteristics, and it provides a powerful analytical tool for the modern basic research fields. Because of the combination of confocal microscopy technology and Raman spectroscopy technology, confocal Raman microscopy has the advantage of both high resolution spectroscopy and chromatography detection, which inherits from confocal microscopy and raman spectroscopy. As a result, it is widely used in many fields, such as physical chemistry, materials science, biomedical, archaeological, cultural identification, and forensic science. But with the environmental changing, the system drifting or other issues, during the long detection process, the system turns to defocusing. As a result, during the hole scanning process, the system can not be focused on every detection point, and then it would lead to a mistake. Eventurally, conventional confocal Raman system could obtain the presence of measurement error even erroneous results in the long process. In this paper, on the basis of conventional confocal Raman system, a confocal Raman spectroscopy method based on quadratic curve fitting is proposed to solve this problem. Based on the principle that the maxium of the concal curve corresponding the system foucs, the steps to find system foucus as follows: fist, usesing quadratic curve to fit confocal curve; second, finding the maxium of the confocal curve; and last obtaining the system foucs. With this method, during the scanning process, every point should be focused, therefore, the effect of defocusing is eliminated efficiently, and accurate measurements of confocal Raman spectroscopy system is achieved. Through simulation and experimental results show that: the proposed method that confocal Raman spectroscopy method based on quadratic curve fitting can effectively eliminate the influence of system defocus on experimental result, and effectively improve the axial system of fixed focus accuracy, which could provide a guarantee for further application of confocal Raman spectroscopy. This anti-drift method is effective and accurate in focusing with great potential to be applied in broader areas.

Fiber optic sensing technology has been widely used for acoustic emission (AE) measurement in aerospace and geotechnical engineering due to the advantages of immunity to electro-magnetic interference, high accuracy, and multiplexing capacity. As for the fiber Bragg grating based on AE measurement system, traditional efforts have been made to study the spectra of Fiber Bragg Grating under AE signal. While this paper focused on phase-shifted fiber Bragg grating (PS-FBG) which is a new type fiber Bragg grating, and investigated the spectra of under dynamic strain field generating with an AE signal. A dynamic strain sensing model of PS-FBG was built based on the transfer matrix theory, and a cosine exponential attenuation function was utilized to simulate the dynamic strain field. Then the effects of amplitude, sampling time, exponential attenuation coefficient, frequency and wavelength of AE signal on the spectra of PS-FBG were studied in detail using numerical simulation. The result demonstrate that the spectra of PS-FBG changes periodically with frequency and different sampling time, especially the peak wavelength of the transmission window in the PS-FBG spectrum shifts periodically; and the increase of amplitude mainly contribute to more harmonic peaks in the reflected spectrum. The attenuation coefficient affects the spectrum of PS-FBG within certain range. And the AE wavelength affect the spectrum of PS-FBG when it is between 0.1 to 2 L, beyond the range, the spectrum of PS-FBG has minor variation with the AE wavelength. Finally, dynamic strain experiments were conducted, and the spectrum of PS-FBG under continuously vibration signal with different amplitude and frequency were logged for analysis. The experimental results agree well with simulation, which indicate that under different dynamic strain fields generated by AE signal, the spectra of PS-FBG are different, while the variation of spectra follows certain laws. This paper provides theoretical support for the AE measurement system on the basis of PS-FBG.

The far-field optical technology of single gold-nanorod(AuNR) has attracted a great deal of attention in recent years. Because of special local surface plasmon resonance (LSPR) property, AuNR particles have high conductivity of optical signals localized on the surface from physical or chemical irritants. The mechanism, application, progress and novel optical characteristics of AuNRs in optical detection and spectroscopy method are being reviewed in our work. The paper describes an overall introduction as follows: (1)various related technologies on AuNR scattered spectrum, including dark-field technology, homodyne and heterodyne technology, photonic crystal technology, spatial modulation, polarization modulation technology, etc; (2) the properties of AuNR scattered spectrum, including spectral line-shape functions, effects of line-width and substrate, comparison of theoretical and experimental spectrums, etc; (3) the development of related spectrum technologies in recent years. The paper focuses on the method of far-field optical scattering based on LSPR and mainly discusses the linear method based on AuNRs, such as direct and indirect scattering detection method. We also put emphasis upon studying the importance of medium environment (for example, substrate, the molecules combined on surface and other nanomaterials) and the influence on scattered spectrum and the extinction rate. Of particular note is the quantitative method and correlation studies of AuNR’s surface and morphology, and its character is that most of the methods are compared with theoretical model and experiments in terms of accuracy. The combination of the experiments and theoretical tools can be used to explain the optical properties of single gold-nanorod particle in detail.

The feature compression algorithm which was reformed from the original Moment method was used for the pre-processing of the fluorescence spectral data, then combined the data and the Weighted Least Squares Support Vector Machine(WLS-SVM) algorithm to establish a robust regression model, which is used for forecasting the purity of edible pigment powder. In this paper, brilliant blue and ponceau 4R served as an example to discuss the method of forecasting effect of edible pigment powder purity. The emission fluorescence spectra of two edible pigment at the optimal excitation wavelength were measured by FLS920 fluorescence spectrometer. The compression and transformation of the fluorescence spectral data was acquired by the feature compression algorithm reformed from the Original Moment method. On the one hand the feature compression algorithm shortened the operation time, on the other hand it improved the prediction accuracy of the model. Then, the concentration prediction model was established after inputting the fluorescence spectral data pre-processed into the Weighted Least Squares Support Vector Machine. The model gave anastomotic predicted spectral data with the actual experiments of the brilliant blue and ponceau 4R, and the average coefficient of determination in the half peak width was 0.700 and 0.930 respectively. There was a good linear relationship between the predicted and the nominal concentration of the brilliant blue and ponceau 4R, and the correlation coefficients were 0.997 and 0.992 respectively. It can be concluded that, the predicted concentration of the brilliant blue and ponceau 4R powder were got the results of 61.0% and 72.3% respectively.

Polarization is an important characteristic of electromagnetic wave, and using polarization information to study ground features has been proved to be an effective means. Research on ground feature’s polarized properties is an essential part of earth observation. At present, it is in highly need of accurate polarization sensors globally. AirMSPI , (Airborne Multiangle Spectro-Polarimetric Imager) as a new airborne polarized sensor, can obtain multi-band and multi-angle polarization data, and the spatial resolution can reach to ~10 meters. Using the experimental data of Tracy in the year of 2013, this paper analyzes the varying pattern of DOLP (Degree of Linear Polarization) as well as pBRF(polarized Bidirectional Reflectance Factor) in 470 nm, 660 nm, 865 nm bands and 9 view zenith angles. The result shows that, forward scattering of ground features contains plenty of polarized radiation, and ground features present strong non-lambertian effect near principal plane of incidence. DOLP and pBRF has strong correlation to relative position between incidence and view angle. DOLP reaches the maximum value when two directions are perpendicular while pBRF increases with larger view zenith angle. Because of atmospheric effect, radiance of blue band contains most polarized light. However, red and infrared band can attenuate atmospheric molecular polarization scattering effectively, thus contain more polarization details of ground features. Water, artificial structure, residential area, bare soil and vegetation show distinct polarization characteristics, and can be clearly identified. Due to depolarization effect from multi-scattering effect, DOLP and reflected radiation intensity have highly negative correlation, with correlation coefficient generally more than -0.8. AirMSPI sensor can provide high-quality polarization data, as a strong verification to ground-based and satellite-based polarization data, and support parameters inversion of atmosphere and ground features.

To improve time resolution of the Raman measurement system, we need to adopt short scanning time. In this case, the weak Raman signal with vibrational spectrum of the molecular structure is easily to be buried by the high background noise, which influences the further analysis seriously. So it is necessary to de-noise the raw Raman signals. Conventional methods manage to de-noise signal by means of smoothing or averaging based on the difference between signal and noise in frequency characteristic or statistical features. They are commonly applied in the situation where the background noise is not so strong, and cannot give satisfactory results to the Raman signals with low signal-to-noise ratio. In this paper, the algorithm proposed detects peak positions and get peak half-width based on wavelet transform, and then reconstructs the Raman signals by least square fitting algorithm with characteristic parameters obtained, which extracts the useful signal from high background noise efficiently. In the simulation, the Raman curve fitted by the proposed algorithm was smooth, and the peak positions obtained were accurate, so the signal-to-noise ratio improved significantly. In the experiment, we adopted this algorithm to de-noise the tested Raman signal of Cefuroxime Axetil Tablets and Roxithromycin, respectively. The peak positions, peak half-width and amplitude were obtained and proved to be accurate. Therefore, the useful pure Raman signal could be recovered from the high background noise efficiently by the proposed algorithm, which improved the time resolution of Raman system. Both the simulation and the experiment showed that the proposed method could be easily performed with only a few parameters. Comparing with conventional methods, it could achieve satisfactory results under high background noise and provide accurate and reliable information for further analysis.

The cloud microphysical properties such as cloud effective radius and cloud water path are fundamental properties for understanding the cloud formation, radiative impacts and interactions with aerosol and precipitation. The downwelling infrared radiance spectra is studied here to retrieve microphysical properties of clouds. The sensitivity of the downwelling radiance spectra and cloud emissivity spectra to the liquid cloud and ice cloud effective radius and optical depth is analyzed. The look-up-tables are established for optically thin clouds (cloud optical depth less than 6) that rely on parameters of the slopes and differences of the emissivity spectra. These parameters include the difference in the emissivity between 862.1 and 934.9 cm(-1), the difference in the emissivity between 1 900.1 and 2 170.1 cm(-1), the slope of the cloud emissivity and the radiation between 900 and 1 000 cm(-1), the slope of the cloud emissivity and the radiation between 1 100 and 1 200 cm(-1). The look-up-tables are constrained by the incorporation of mean ozone band transmissivity between 1 050 and 1 060 cm(-1). Cloud effective radius and optical depth can be obtained with by least squares fitting between observed and modeled above-mentioned multiple spectral parameters. The cloud water path can then be derived from the experiential relationship. The inversion results are compared with the ARM baseline cloud microphysics product (MICROBASE). It is shown that, the cloud effective radius is roughly in the same order of magnitude while the water paths derived from both method are of large differences especially for the liquid cloud path. The algorithm proposed in this paper is efficient for retrieving microphysical properties of thin clouds with cloud optical depth less than 6.

As the basis of plant canopy chlorophyll fluorescence kinetics, light distribution within the canopy determines the interaction relationship between plant physical processes and ecological environment. Spectroscopy technology plays a very important role in building a prediction model of component content to plant canopies. However, there is only limited number of reports about chlorophyll fluorescence properties of different light intensity areas to free spindle apple canopies. In this paper, with the free spindle apple tree as the research object, the canopy space of apple tree was divided into five layers, and six cube grids with 50cm length of side in each layer, and then the light distribution was determined through measuring the light intensity of each cube grids space. firstly, spectrum data and characters of chlorophyll fluorescence were obtained in the different light area; secondly, a differential spectrum curve in red area(680~760 nm) was determined through removing the interference of system error by a differential spectrum; thirdly, relationship model has been established innovatively between the maximum value in red area(680~760 nm) and the chlorophyll fluorescence characters, which has been used as calculation method of chlorophyll fluorescence characters in different light area to apple tree canopy. Fourthly, root mean square error, mean absolute percentage error, mean forecast error were adopted to evaluate the method. The test result shows that the accuracy of the method is all above 80%, which can be the theoretical basis for pruning and getting best light distribution to apple tree canopy.

As the saying goes that “no ash, no glaze”, lime-ash has been the core material widely used to prepare glaze in ancient China. Among all the lime-ashes, those made in Jingdezhen are the most influential and representative ones. Not only did lime-ash contribute greatly to the prosperity of porcelain making of Jingdezhen in Song, Yuan, Ming and Qing Dynasty, but also it has a complicated, rigorous and a touch of “mysterious” in its preparation process, technical principle and glaze mechanism. Therefore, the research of the lime-ash has been an important subject in exploring the “secret” of ancient Chinese porcelain production by Chinese and foreign researchers. In this paper, four representative firewood and two lime stones as the raw materials were collected for the comparative studies, and three kinds of lime-ash with different smolder times were collected from one of the only two traditional lime-ash workshops in Shou’an town nearby Jingdezhen urban area. The chemical composition and phase composition of the raw materials and lime-ash with different smolder times made in Jingdezhen were discussed by testing with the Energy Dispersive X Ray Fluorescence (EDXRF) and X-Ray Diffraction (XRD). The results showed that Fe(2)O(3), MnO contents reaches 1.41% and 1.52% respectively, but the P(2)O(5) content is just 0.54% of Langqi grass which is lower than other firewood that is not only benefited to form the characteristic of “Green in the white” in Jingdezhen traditional glaze, but also is favor to enhance the transparency of glaze and promote the coloration of traditional under-glazed color painted porcelain, such as the blue and white porcelain. The CaO content of grey lime stone is lower than that of the black lime stone with MgO content of 35.79%.This could be the main reason why the craftsmen prefer to use black lime stone to prepare lime-ash. In addition, the EDXRF results show that the K(2)O, P(2)O(5), MnO and Fe(2)O(3) contents have increased as the time of smoldering increases. In the meanwhile, the calcium carbonate (CaCO(3)) phase has also increased, but the calcium hydroxide (Ca(OH)(2)) phase has decreased. The study helps Jingdezhen porcelain “look like jade” and is also good to avoid the “thickness” of glaze when there is a certain amount of Ca(OH)(2) in glaze. So it could be concluded that the unique raw materials and smolder technology of the lime-ash which have provided the technical support for the development of lime-ash glaze are the unique features of ancient Jingdezhen ash glaze.