Search

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.

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.

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.

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.

In order to solve the problem of high cost and low efficiency by using the traditional soil geochemical survey methods, this paper studied the simple detection method of soil heavy metal content with visible and near-infrared reflectance spectroscopy. The study collected visible and near-infrared reflectance spectroscopy of soil samples in Xifanping mining area; then treated the reflectance spectroscopy with six mathematic changes such as differentials and continuum removal in advance; the next step was to select characteristic wavelengths that were sensitive to soil copper content by using stepwise regression method and Pearson correlation coefficient as set of comprehensive characteristic variables; finally, utilized different methods and parameters of characteristic variable selection to build the soil total copper content models and tested them. Results showed that: to extract the information of copper content in soil, the performance of different spectral transform methods varied, and each spectrum transform method corresponded to its certain sensitive spectral ranges; the inversion models based on the integrated spectrum transform information were better than that based on only one kind of spectrum transform information; as for establishing the prediction model of soil copper content by using the integrated spectrum transform information, backward elimination was better than forward selection and stepwise selection, and when the Removal is 0.20, the optimum model was obtained, its coefficients of determination(R(2))and determination coefficients of prediction(R(2)(pre))reached 0.851 and 0.830, root mean square error of calibration(RMSEC)and root mean square error of prediction(RMSEP)were 0.349 and 0.468 mg·kg(-1). The model has a good precision, and it provides a train of thought for the detection of other soil heavy metal elements with visible and near-infrared reflectance spectroscopy.

Spectral reflectance data quality is important for computer color matching. There are two existing methods for evaluating the quality—spectral reflectance method and K/S method, which are too complex to apply. In this paper, 45°/0° and d/8° geometric conditions are used in the measurement of spectral reflectance of the offset ink samples printed on coated paper and silver-foiled paper while improvement on the geometric condition is made on the basis of the spectral reflectance method. Moreover, a new evaluation method—lightness and chromaticity comparative method is put forward, and comparison is made among the three methods. The results show that both 45°/0° and d/8° are feasible in the measurement of spectral reflectance of coated paper; however the former one cannot meet the requirement of spectral reflectance measurement of silver-foiled paper. In addition, as to d/8° Specular Component Included (SCI), when the silver-foiled paper is taken as the substrate, the reflectance of transparent white ink samples are smaller than that of other primary inks; and abnormal intersections appear in the curves of cyan and magenta ink respectively at the concentration of 60%, resulting in a poor spectra quality at high ink concentration; In the figure of lightness and chromaticity curves, there is significant divergence of the cyan and magenta ink curves from the referenced coated paper. In conclusion, the spectral reflectance of the transparent ink should be greater than or at least equal to other primary inks, and the maximum concentration of cyan and magenta should be limited; when the coated paper with good diffusion performance is taken as the reference, the comparative analysis is more intuitive than the two existing methods.

Isonicotinic acid hydrazide (Isoniazid, INH) is one of the most commonly used first-line anti-tuberculosis drugs, which has been reported that the high concentration of INH in human body can lead to epilepsy, liver function failure, and even death. Therefore, studying the potential binding effects of INH on the structure and activity of human serum albumin (HSA) and catalase (CAT) is very essential for evaluating its toxicity and side effect. In this paper, multi-spectroscopic and molecular docking methods were used to elucidate the patterns of INH to HSA and CAT under imitated physiological conditions. The inner filter effect of all fluorescence data in the paper was eliminated to get accurate binding parameters. The Stern-Volmer quenching constants (KSV) of both HSA-INH system and CAT-INH system inversely correlated with temperatures, demonstrating that INH quench the intrinsic fluorescence of HSA and CAT via static quenching. The conformational investigation of HSA and CAT through UV-visible absorption spectroscopy, synchronous fluorescence and circular dichroism (CD) showed that INH could change the micro-environment of tryptophan residues and reduced the α-helix content of protein. These results demonstrated that the binding of INH may lead to the loosening of protein skeleton, which which may affect its physiological function. The results of molecular docking revealed that the INH was located in Sudlow’s site I of HSA. And INH bound to CAT at a cavity among the wrapping domain helical domain and β-barrel, which resulted in the inhibition of CAT activity. In addition, Levofloxacin (LVFX) is a new effective and safe second-line anti-tuberculosis drugs and can improve the curative effect on anti-TB by using with other anti-TB drugs, the result of Hill’s coefficients (nH) about synergy between INH and proved that LVFX promoted the interaction of HSA with INH. Moreover, according to the CD spectra, synergy between INH and LVFX changed the conformation of HSA and the amount of α-helix decreased about 7.9%. This work will provide important insights into the binding and toxicity mechanism of INH to HSA and CAT in vivo and is expected to be helpful in evaluating the essential information for using the INH safely.

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.

One of the most important topics in crop information science is how to make use of the crop’s information for non-destructive nutrient diagnosis which can be solved with spectrum analysis. The canopy’s spectrum feature is a key indicator to describe the nutritional status for the rapeseeds. The original spectrum is to be disturbed with external factors such as environment and climate; however, it is difficult to be directly used for rapeseed biomass diagnosis due to its huge fluctuation. However, the multifractal feature of the spectra remains stable relatively. In order to study the relationship between the canopy’s spectrum of the rapeseed and its chlorophyll, based on the multifractal theory, a quantitative model of chlorophyll prediction and a qualitative model of planting pattern identification were proposed in this paper to study the high oleic acid rapeseed samples in 24 transplanting regions and 24 direct planting regions. At first, the generalized Hurst exponent and mass exponents together with other relevant multifractal parameters of the spectra were extracted with popular multifractal detrended fluctuation analysis (MF-DFA) in different six considered wavelength ranges. It shows that all of them possess representative multifractal nature. However, there are some differences of the multifractal characteristics between the two kinds of regions with different planting pattern in some bands. In addition, by correlation analysis and detection between the multifractal parameters of the spectra and the SPAD values in six considered ranges of bands, it demonstrates that there is some difference of the effective information content in the different ranges of bands. In the quantitative model of chlorophyll prediction, for each groups of samples in transplanting regions and direct planting regions and mixed together in each significant bands, a selected multifractal parameter was used to establish the univariate model for predicting the rapeseed leaf’s SPAD values, respectively. The results of all the relative root mean square errors are small than 5%. Finally, the qualitative model was proposed to distinguish the samples by the two planting pattern. Youden index, as the identification accuracy was calculated for the six considered ranges of bands by the Fisher’s linear discriminant analysis. The best Youden index is 0.902 5 and the corresponding band range is 350~1 350 nm. The significant work provides a theoretical and practical method for predicting rapeseed leaf’s SPAD and also provides effective way to find the sensitive bands of the spectra for identification diagnosis.

Optical parameters which macroscopically characterize optical properties of materials indirectly reflect microscopic peculiarities of materials. Accurate extractions of optical parameters are significant for the research of microscopic behavior and macroscopic responses of materials. In recent years, as a new spectral analysis method, terahertz time-domain spectroscopy (THz-TDS) technology has become a research hotspot. Due to the low THz radiation energy and narrow pulse width (picosecond range), THz-TDS technology is nondestructive with high-temporal-resolution when being used to extract optical parameters of samples. This paper summarizes optical parameters extraction methods by using THz transmission and reflection spectroscopy technology, emphatically introduces several classic methods and analyses, along with their respective merits and demerits, and finally discusses the challenges of THz-TDS technology in optical parameters extraction. In conclusion, the transmission methods are adaptive for measuring substances which slightly absorb terahertz radiation, whereas the reflection methods are suitable for measuring materials with strong absorption capacity.

The conventional qualitative analysis of near infrared spectroscopy (NIR) commonly uses one single classification model. This paper focused on the fusion of multiple classifiers based on different single classifiers by using the fused classifier to determine different varieties of red-wines. NIR spectra of 170 red-wine samples were collected by using Fourier transform near-infrared spectrometer. Red-wine classification models were established respectively, based on PLS-DA, SVM, Fisher and Ada-Boost. Then these models were selected to obtain some different base classifiers according to Diversity Measure Feature Selective (DMFS). The highest accuracy rate of determining different varieties of red-wine test samples of four single base classifiers was up to 88.24%, and at the same time the lowest discriminant accuracy rate was 81.18%. At last, we got the fused classifier, which combined four base classifiers with weighted voting principle, and determined its test set again by using the fused classifier. The final classification accuracy rate for red-wine varieties increased to 92.94%, In contrast with one single classifier, the lowest misjudged number of fused classifiers decreased from 9 to 6.These results suggested that the performance of fused classifier is superior to one single classifier. It is feasible to use fused classifier combined with near infrared spectroscopy to determine different varieties of red-wines.

As a secondary analysis method, reproducibility and reliability of near-infrared spectroscopy (NIRS) quantitative analysis are quite dependent on modelling process. In this paper, it is focused on outlier analysis for protein quantitative model of wheat based on NIRS. The purpose is to discuss the outlier effect in modelling process of complex sample set. The indicator of outliers is the deviation between two interpretative percentage curves in partial least squares regression (PLSR) modelling, when two percentage curves have significant deviation or departure point, the sample set should include the outliers. The innovative research work is the analysis and treatment of outliers. On the basis of sub-model ergodic calculation method, outliers can be gradually identified and picked-up. The standard deviation of model’s prediction residual is used as the reference graduation to distinguish the degree of deviation. According to the degree of deviation from sample population, outliers can also be divided into significant outliers, relative outliers and potential outliers. In this paper, the significant outliers of the sample set are about 7.8%, and the relative outliers are about 15.6%. The outliers will pull normal samples apart from the ideal fitting line and make the dispersity increase. No matter modelling with removed outliers or weighted samples, the purpose is to make the fitting results of quantitative analysis modelling more inclined to majority samples, while reducing or eliminating the impact of outliers.

Using the UV absorption spectrum to detect Organic pollutants content in water has become one of the most important methods for real-time online monitoring in the field of water quality inspection, however, the water complex and unstable components often bring much uncertain offset to the standard test. In this paper, water samples were classified firstly by analyzing UV absorption spectrum ranging from 200 nm to 400 μm including the organic substances, through the way of combining principal component analysis (PCA) with Euclidean distance. In this paper, we compared the Principal component analysis combined with partial least squares regression (PCA-PLSR) and the direct multi-wavelength absorption models combined with partial least squares regression (MWA-PLSR), not only for the real water sample but also for the analysis of different concentrations of COD standard solution. The result indicates that the measurement errors of the PCA is less than 5%, it is the smallest by using the first and second principal components as regression parameters for PLSR. Using the methods above can simultaneously achieve to classify of water samples and to measure the concentration of water quality parameters more accurately.

Uranium is one of the important nuclear materials to nuclear industry. Because of the direct disposal of spent fuel, there is still a huge possibility that uranium migrates into the groundwater, causing water contamination. It is of great importance to understand the concentration and their species distribution in aqueous solutions. Surface-Enhanced Raman Scattering (SERS) technique has been widely used for the detection of uranium (Ⅵ). However, the interactions between uranium (Ⅵ) and SERS substrate cause the symmetric stretching vibration peak of uranium (Ⅵ) shift to low wave number direction, which is unfavorable for confirming the species of uranium (Ⅵ) in aqueous solution. For instance, the normal Raman bands of uranyl in nitric acid solution are 871 cm-1, which belongs to the symmetric stretching mode of UO2+2. However, it moves to 710 cm-1 on the surface of silver nanorods SERS substrtate. What’s more, different SERS substrate causes different number of shift. Graphene has advantages of inertness and integrity as well as 2-dimensional thickness. In this paper, graphene-isolated SERS substrate which is silver nanoparticles (AgNPs)/graphene complex substrate, was designed to prevent the interaction between SERS substrate and it was analyzed by using the inert graphene layer. First of all, according to our previous work, AgNPs SERS substrate was fabricated on silicon wafer by using an ascorbic acid-actived self-assembly method. Then, AgNPs/graphene complex substrate was prepared by transfering monolayer graphene onto the self-assembly AgNPs substrate. The morphology of complex substrate was obtained by SEM. Some AgNPs link together closely to form nanochain structures. Nanochain structures were distributed evenly on the surface of silicon wafer. The 2-dimensional thickness of graphene did not affect the morphology of AgNPs. When using the complex substrate to detect uranyl nitrate (5×10-4 mol·L-1)，the Raman peak that appeared around 771 cm-1 is considered to be the symmetric stretching mode of UO2+2, shifting back about 52 cm-1 to high wave number direction when compared with AgNPs substrate, which was about ~719 cm-1. The result indicates that graphene layer isolates the interaction between AgNPs substrate and uranyl in some degree.

The Visible absorption and Raman spectra of β-carotene were measured in dimethyl sulfoxide in temperature ranging from 81 to 25 ℃ and in carbon disulfide in pressure range from 0.04 to 0.60 GPa, respectively. The results indicated that the visible absorption and Raman spectra are both red-shifted, Raman scattering cross section increase with the temperature decreasing. And with the pressure increasing, the visible absorption spectra are red-shifted, but the frequency shift towards higher frequencies in the Raman spectra, the Raman scattering cross section decrease unexpectedly. The latter can’t be explained by the model of “effective conjugation length” and “coherent weakly damped electron-lattice vibrations”. In this paper, we combined electron-vibration coupling rule with theoretical calculations and found that the electron-phonon coupling constant had a certain changing trend with the temperature and pressure variation, which Indicate that the interaction between π-electron and CC bond vibration was essential for this experiment result. Thus, the turning effect of energy gap of the π on CC vibration mode is responsible for such phenomenon.

Typically, it is time-consuming to use Monte Carlo simulation to model light propagation in turbid media, such as breasts, mainly because of the thick simulated tissue and the large number of photons required by the stochastic nature of MC simulations. In this paper, in view of the light source and the receiver in a straight line, the transmitted light received by optical fiber model is analyzed; in terms of the optical properties of biological tissue itself, implementation of boundary constraint conditions and restriction of the number of backscatter events have been developed to reduce the simulation time. It is verified that the calculation is relatively simple by many experiments, when the position after two scattering is regarded as the demarcation and the boundary constraint conditions are efficiently solved by optical parameters of tissue respectively. At the same time, considering the actual situation in incident and emergent position, the boundary constraint conditions are expanded. The number of backscatter of every photon that received by optical fiber in the same position are recorded and tissues are selected different thickness and the similar optical parameters in the simulations. Additionally, it is found that the number of backscatter would increase as the depth of tissue or scattering coefficient increases, or as absorption coefficient or anisotropic factor decreases. Therefore, the time is saved further through limiting the number of backscatter. The simulation results show the combination of those new methods reduces the operation time of the MC simulation by 50% on a typical desktop computer. Those new methods are especially suitable for MC simulations of the thick tissue or the scatterer with a complex boundary. This acceleration method is applicable when light source and receiver are in a straight line the biological tissue is thicker and scattering coefficient is large. It can effectively save needed time and be beneficial to analyze the transmission imaging.

Distinguishing the rare spectra from the majority of stellar spectra is one of quite important issues in astronomy. As the size of the rare spectra is much smaller than the majority of the spectra, many traditional classifiers can’t work effectively because they only focus on the classification accuracy and have not paid enough attentions on the rare spectra. In view of this, the relationship between the decision tree and mutual information is discussed on the basis of summarizing the traditional classifiers, and the cost-free decision tree based on mutual information is proposed in this paper to improve the performance of distinguishing the rare spectra. In the experiment, we investigate the performance of the proposed method on the K-type, F-type, G-type, M-type datasets from Sloan Digital Sky Survey (SDSS), Data Release 8. It can be concluded that the proposed method can complete the rare spectra distinguishing task compared with several traditional classifiers.

Polycyclic Aromatic Hydrocarbons (PAHs) have been widely investigated in environmental field, for most of them are mutagenic (carcinogenic, teratogenic, mutagenic). The influence of delay time and gate width on the time-resolved fluorescence spectroscopy of fluoranthene in ethanol was studied in this paper. Furthermore, laser induced time-resolved fluorescence spectroscopy of fluoranthene with different concentration were also researched. According to the results, fluorescence kinetics decay curves and fluorescence lifetime of fluoranthene matched. The research results showed that there was closely relationship between the fluorescence spectrum of fluoranthene and the delay time and gate width of detector. When the delay time was fixed, the fluorescence intensity of fluoranthene grew increased as the gate width increased. When the gate width was fixed, the fluorescence intensity of fluoranthene increased first and then decreased with the delay time increases. The process of the attenuation of fluorescence intensity of fluoranthene with time delay conformed to the exponential decay process. The stepwise dilution of fluoranthene ethanol solution was also studied. With increasing dilution, the fitting of fluoranthene fluorescence lifetime increased. The results of this paper can provide a technical basis for the detection of PAHs in the environment, due to the different characteristics of the fluorescent substance having fluorescence lifetime.

High-concentration antibiotics are detected in surface water from time to time. There has been an increasing demand for strengthening the supervision of the antibiotic pharmaceutical wastewater. Three-dimensional fluorescence technique is known as a rapid, simple and high-sensitivity method. The three-dimensional fluorescence spectrum can display organic components and it was named as aqueous fingerprint. In this paper, three-dimensional fluorescence characteristics of a typical semi synthetic penicillin pharmaceutical wastewater were studied. There were totally four fluorescence peaks in the aqueous fingerprint of this wastewater, locating in excitation wavelength/emission wavelength of 360/445, 255/445, 275/305 and 230/300 nm respectively. Fluorescence peak’s intensity within certain range related linearly to the relative concentration. The possible fluorescent pollutants related to Peak C and Peak D might be the mixture of D-(-)-A-4-Hydroxyphenylglycine Dane Salt Methyl Potassium (pharmaceutical intermediates), Amoxicillin (pharmaceutical product) and D(-)-4-Hydroxyphenylglycine (pharmaceutical hydrolysate). PH played an important role in the fluorescence characteristics of this wastewater. This indicated that the fluorescent organic pollutants in this wastewater might contain acid or base groups. The aqueous fingerprint technique could be used to monitor the discharge of semi synthetic penicillin pharmaceutical wastewater as a novel tool.

In this paper, 9 most abundant PBDE congeners in environment and 14 congeners with high/medium biological toxicity were selected as target compounds. Firstly, IR spectra of 23 compounds were divided into 6 spectrum regions based on known vibrational assignment, and their identification abilities for PBDEs were evaluated by using similarity analysis. Then, the spectrum regions with high identification ability relatively have been analyzed to search identification method on the basis of each spectrum characteristic. At last, the principal component analysis and discriminant analysis method were used to extract characteristic spectrum information of congeners with high/medium biological toxicity and establish biological toxicity discriminant model. The triangle breathing vibration region (961～1 153 cm-1) and C—O stretching vibration region (1 153～1 346 cm-1) has been filtered as characteristic IR spectrum regions because of smaller similarity among PBDEs relatively. For the former, the information of vibration peaks distribution can be taken as tool to identification, with the smallest frequency difference of 3.19 cm-1 among 23 congeners and bad ability to distinguish PBDEs from dioxin-similar compounds. For the later, the frequency and shape of main peak is as mark and the smallest frequency difference among PBDEs and between PBDEs with dioxin-similar compounds are 0.74 and 0.67 cm-1 separately, both larger than the common minimum resolution of IR spectrum 0.5 cm-1, depicting good ability for both inner and outer identification of PBDEs. The established biological toxicity discriminant model via discriminant analysis also have shown well ability to biological toxicity prediction, with accuracy of 100% and 88.9% for high/medium and low biological toxicity relatively, representing the extracted IR spectrum information from congeners with high/medium toxicity can realize the accurate classification of biological toxicity for PBDEs.

The quality and safety of grain and oils are related to the national nutrition and health safety of the public. Owing to the difficulties in operation, destruction, high cost, reagent pollution and other shortcomings, conventional detection method cannot meet the fast, non-destructive, efficient and pollution-free requirements, which pose great difficulties in integrating with Industry 4.0. With the development of chemometrics, hyperspectral imaging (HSI) technology integrates the advantages of spectroscopy and image technology to overcome the defects of conventional detection method, which has become the developingt trend of grain and oils quality testing technology. Based on many interrelated research papers, this paper reviews the principles of HSI and the existing research in quality (component determination, germination test, variety classification) and safety (fungal detection, pest detection) of grain and oils. Meanwhile, in order to promote the application and development of hyperspectral imaging technology in the field of grain and oils, we specially analyze the aspect of HSI including spectral range, chemometrics, equipment and the accuracy of model, pointing out the current problems and prospecting the direction and priority.

The two-dimensional concentration distribution was reconstructed by using algebraic iterative reconstruction algorithm. This paper mainly focused on the effects of multispectral H2O absorptions on condition that the laser beam was less and the temperature was known, i.e. the influence of temperature on spectral line-strength was not considered as to this concentration distribution. Based on ART algorithm, increased spectral lines and increased laser beam were compared under the same concentration model. Three H2O lines were selected to reconstruct two-dimensional distribution of non-uniform gas concentration, and these three transitions were selected within the external cavity diode laser turning range in the simulated system. The interested region was discretized to 10×10 grid points, and the temperature and concentration of the reconstruction model were not evenly distributed, so the unimodal distribution and bimodal distribution were used to describe the concentration distribution. The simulated system also calculated the effective utilization of laser beams and absorption lines. The results showed that the reconstruction quality quickly increased with increasing H2O absorption lines when the laser beams were very few, the increased absorption lines could get more spectral information related to the concentration. The increased laser beam is also effective to improve the accuracy of reconstruction results, but increasing the absorption lines can better reconstruct a two-dimensional concentration distribution. Improving the absorption lines can also effectively reduce the costs of the hardware and the complexity of the measurement system, which shows that the multispectral absorption lines are applicable to in-situ measurements.

Chromium doped amorphous hydrogenated carbon a-C∶H(Cr) films (2.23 μm in thickness)have been successfully prepared with unbalanced magnetron sputtering technology(UBMS) in this paper. Raman spectrum and X-ray photoelectron spectroscopy (XPS) have been used to study the structure and thermal stability of the Chromium doped diamond-like carbon films (Cr-DLC). The results indicate that, at the room temperature, the Raman absorption peak “G” near 1 580 cm-1was assigned to C—C stretching vibration mode (E2g) in the Cr-DLC films, while the peak “D” near 1 350 cm-1was assigned to sp2 breathing vibration mode (A1g). The relative concentration of sp3 bond in the film is at 48%. When heated till 300 ℃, the Raman pattern of sample is similar to that of the sample at room temperature, indicating the structure of Cr-DLC film is stable. At 400 ℃, the ratio of ID/IG and the concentration of sp2 bond clearly increase, indicating the change of the structure in the Cr-DLC and the appearance of graphitization. With temperature going up, the rise of ID/IG ratio and the shift of the peak “G” to high wavenumber show that the rise of sp2/sp3 ratio, the intensity of graphitization, and the decline of the disorder of sp2 in the Cr-DLC films lead to the increase of the friction coefficient and wearing rate and the decline of the Cr-DLC thermal stability. When the it is up to 600 ℃, the ratio of ID/IG and the concentration of sp2 bond reach the max value while the Cr-DLC film loses its efficacy.

The varieties of cabbage seeds directly affect the yield and quality of cabbage, in order to rapidly and nondestructively identify the varieties of cabbage seeds, near infrared spectra technique were applied in this study and reflectance spectrum of the cabbage seeds was obtained. Firstly, to excavate the effective information in the spectral data and improve signal to noise ratio, the raw spectra was pre-processed with the method of standard normal variate (SNV) and multiplicative scatter correction (MSC). Secondly, principal component analysis (PCA) was used to analyze the clustering of cabbage samples, then the characteristic differentia of three cabbage varieties was obtained through qualitative analysis. Six Effective wavelengths were selected by successive projections algorithm (SPA). Finally, the full spectra variable, the first three principal components (PCs) using PCA and selected effective wavelengths using SPA were respectively set as inputs of the partial least squares discriminant analysis (PLS-DA) and least-squares support vector machine (LS-SVM) models for the classification of cabbage seeds. As can be seen from the two dimensional plot drawn with the scores of PC1 and PC2 (the first two principle components), PC1 and PC2 had a good clustering effect for different kinds of cabbage seeds. LS-SVM models performed better than PLS-DA models, the correct rates of discrimination were 100% achieved with LS-SVM models. PLS-DA and LS-SVM models built based on the selected wavelengths performed better than the models built based on the first three principal components, moreover, the SPA-LS-SVM model obtained the best results among all models, with 100% discrimination accuracy for both the calibration set and the prediction set. The overall results show that SPA can extract wavelengths, and the LS-SVM model combined with SPA can obtain optimal classification results. So the present paper could offer an alternate approach for the rapid discrimination of cabbage seeds variety.

The Polarized Interference Imaging Spectrometer (PIIS), which is based on the theory of Fourier Transform Spectroscopy, is consisted of a series of birefringent crystals such as polarizers, a beam splitter as well as various lengths of birefringent crystals required to achieve large delays. The PIIS, compared with a traditional grating-based dispersion spectrometer, has various advantages of multiple-channel measurements, simultaneous information acquisition of both original images and fringes containing spectral details, large light flux, better light signal-to-noise ratio (SNR) as well as anti-vibration etc. Therefore, the PIIS has also been developed in a range of astronomy and astrophysics areas such as remote sensing, extrasolar planet radial velocity measurements, spacecraft design, lunar exploration etc. However, by reviewing of former works and references, two major drawbacks still remain in PIIS and need to be fixed. For one thing, the classic PIIS has a very limited field-of-view (FOV) around ±2°, which means the acquired fringes on the image plane will show quite strong non-linear distortion and hence degrade the accuracy of spectral reconstruction via Fourier transform. For another, the random thermal-phase-drift (TPD), given rise from both thermal expansion and birefringence variation caused by the environmental temperature fluctuation, has barely been studied before and will inevitably result in extra radial velocity error based on Doppler Spectroscopy. In this paper, a noble polarization interference imaging spectrometer with the emphasis on the FOV widening technology is introduced. This technology, using a compensated Savart plate containing a half-wave plate sandwiched between two orthogonally placed displacer plates as a compensated Savart plate, produces an angle-dependent phase shear to create parallel spatial interference fringes with a FOV around ±10°. This improvement not only enhances the accuracy of Fourier Transform algorithm but also increases input luminous flux and therefore even weak input spectrum detection and calibration results with high SNR can be fully accomplished. Also, a secondary set of birefringent plates (α-BBO and LiNbO3) with opposite thermal properties is proposed to passively diminish TPD caused by temperature fluctuation. The experiment shows that thermal-drift-phase error is perfectly restricted within 0.02 rad in the laboratory environment. As a consequence, this advanced PIIS is eligible to realize the fast and accurate measurement and calibration application in the field of large astronomical spectral instruments with ultra-high spectral resolution occasions such as Astronomical Frequency Comb.

Metal nanostructure material has attracted great attention due to its surface plasmon resonance. The optical properties of heterodimer metallic nanostructure materials are different compared with that of homogeneous nanostructure materials because their symmetry structure is broken. The symmetry of the original structures will be changed, and the interaction between the two particles will produce Fano resonance. The Fano resonances are the result of the double or more surface plasmon resonances coupling, and be controlled by properly controlling the nanostructures. The electric field enhancement and the radiation characteristics of the nanostructure are further optimized for the Fano resonance controlled. Aluminum nanostructure materials have become the best choice of the surface plasmon resonance in the UV region, because gold, silver and other noble metals have inter-band transition effects. In this work, we study the local field and absorption spectra of heterodimer composed of a silver nanosphere and an aluminum nanosphere by the Finite-Difference Time-Domain (FDTD) theory. Firstly, the effects of the incident polarization, the geometric like, nanospheres separation, nanosphere radius and physical dielectric media on the optical response of silver-aluminum nanospheres heterodimer are analyzed. Secondly, the near field distributions of heterodimer are given in-depth discussion. Due to the destruction of the symmetry of dimer material, heterodimeric optical character is significantly different from homodimer. Fano resonances are produced in UV and visible light in the heterodimer respectively when silver-aluminum nanospheres heterodimer is illuminated by the Y-polarized light. More favorable Fano resonance effects can be obtained by regulating the spacing and size of heterodimer in the given dielectric environment which is also an effect factor certainly. Finally, the absorption of the heterodimer contributed from each nanosphere structure is also analyzed. In this way, the result which is a general and complete description of the optical properties of silver-aluminum nanospheres heterodimer nanostructure in the paper, leads to the suppression and enhancement of the surface plasmon resonance in different frequency bands and may be valuable for the design and development of plasmonic devices and optical tools in UV-visible light and could serve as the basis of the future experimental analysis of surface enhanced spectroscopy, molecular detection and biosensor etc.

As typical nano metarials in near infrared waveband, PbSe Quantum Dots have a very large exciton Bohr radius of 46 nm and a small band gap of 0.28 eV at room temperature. PbSe QDs have very unique properties, such as the quantum confined optical property, and which possess high photoluminescence (PL) quantum yield (QY) with size dependent tunable wavelength emissions. By analyzing the luminescence spectrum of PbSe Quantum Dots, a method through adjusting the particle size of PbSe Quantum Dots (QDs) to match gas absorption spectrum was presented in this paper. 4.6 and 6.1 nm PbSe QDs were synthesized and deposited on the GaN chip to fabricate the NIR QDs light sources. The PbSe QDs-UV glue composites thickness was determined to be 48.0 and 671.5 μm for 6.1 and 4.6 nm PbSe QDs. The NIR QDs were used to detect the C2H2 and NH3 gas. The experiments show that the PL spectrum of 4.6 nm NIR QDs can cover the entire absorption spectrum of C2H2 gas (from 1 500 to 1 550 nm) and the PL spectrum of 6.1 nm NIR QDs can cover the entire absorption spectrum of NH3 gas (from 1 900 to 2 060 nm). By changing the quantum size of QDs, the PL peak of the NIR QDS light source can be adjusted to cover the absorption peak of different gases. The matching method presented in this paper is efficient and feasible, which has great application potential in gas detection.

Torasemide (TOR) belongs to the pyridine sulfonylurea class of loop diuretics and is widely and effectively used in the treatment of hypertension, heart failure, chronic renal failure and liver disease. One of the adverse reactions caused by TOR was a slight gastrointestinal discomfort in the course of treatment. However, the molecular interactions of TOR with digestive proteases (trypsin and pepsin) rarely reported. The attempt of this paper was to completely investigate the binding characteristics between TOR and trypsin or pepsin at different temperatures under imitated physiological conditions by fluorescence spectroscopy, UV-vis absorption, circular dichroism (CD) and molecular modeling technique. The inner filter effect of all fluorescence data in the paper was eliminated to get accurate binding parameters. It was found that the fluorescence quenching of trypsin and pepsin by TOR was a static quenching type. The Stern-Volmer quenching constants (KSV) of TOR-pepisn and TOR-trypsin were inversely correlated with temperatures. The binding of TOR changed the conformational structures and internal micro-environment of pepsin and trypsin by UV-vis absorption, synchronous fluorescence, three dimensional (3D) fluorescence and circular dichroism (CD) spectroscopy. The results showed the polarity around Tyr residues of pepsin or trypsin was changed more obviously than that around Trp residues, the TOR alters the secondary structure of trypsin and pepsin and reduces the β-sheet content of protein, which may affect its physiological function. The molecular docking results showed that TOR inserted into the active site of pepsin to interact with the catalytic residues Asp32 and Asp215, and caused a decrease in pepsin activity. TOR bound into the primary substrate-binding pocket (S1 binding pocket) of trypsin by hydrophobic forces and affected the function of trypsin by increasing its catalytic activity. Our results offer insights for the binding and toxicity mechanism of TOR with pepsin and trypsin in vivo, which provides important information for using the TOR safely.

Large scale spectrum survey will produce mass spectral data and offer chances for searching rare and unknown types of spectra, which is contribute to revealing the evolution law of the universe and the origin of life. Data mining in outlier data in sky survey can serve the purpose of finding special spectra. Line index can be used in spectra data dimension reduction, keeping the spectral physical characteristics as much as possible, and at the same time, it can effectively solve the high dimensional spectral data clustering analysis in the high computation complexity. This paper proposed a method outlier data mining and analysis for massive stellar spectrum survey data based on line index characteristics, according to this, an outlier spectral data analysis method was proposed using line index characteristics space. Experimental results demonstrated that (1) using line index as the characteristic value of the spectrum can quickly perform the outlier data mining for high dimensional spectral data, and it can solve the problem of high computation complexity of the high dimensional spectral data. (2) this outlier data mining method was conducted based on the clustering results; it can effectively finding out emission stars, late type stars, late M type stars, extremely poor metal stars, and even finding spectra data missing certain data. (3) outlier data mining in line index feature space can help to analysis of rules of special stars found in the feature space. The mothed proposed in this paper based on the characteristics of line index outlier data mining and analysis method can be applied to the study of survey data.

As to most methods of detecting the inner information of inhomogenous tissue, a significant issue is that the detection position is ambiguous because of the complexity of human tissue structure and discrepancies among individuals. This paper studies the best source-detector distance (SDSbest) to detect internal information of a fat-muscle tissue with spatially resolved diffuse reflectance spectra. In order to weaken the measurement error caused by the discrepancies among individuals and multiple backscattered photons, and according to the transmission model of light in complex biological tissue, then we added the constraint condition——two ideal “banana shape” paths——to define the effective photon ratio(SNR), which was used to select the best source-detector separations (SDSbest), and the results from Monte Carlo simulation modified by adding constraint condition were statistically analyzed, and we regard the SNR as a basis and analyze the relationship between the fat thickness (hf)，the absorption coefficient of a fat layer (μaf)，the absorption coefficient of a muscle layer (μam) and the source-detector distance (SDS), and hf is used as the independent variable to develop a linear regression model to predict SDSbest. The result showed that μaf and μam have no effect on SDSbest when 0

Cu(InxGa1-x)Se2(CIGS) precursor films were prepared on ITO glass with potentiostatic electrodeposition. High quality CIGS films were obtained by selenization of the precursor films at high temperature in tubular furnace full of argon gas. X-ray diffraction (XRD), scanning electron microscopy (SEM) and UV-Vis-NIR spectroscopy were used to characterize the structure, morphology, composition and Vis-NIR absorption of CIGS films, respectively. XRD results show the selenized CIGS films have a preferential orientation (112) with average crystallite of 24.7 nm. Raman spectroscopy reveals that the CIGS films are pure quaternaryphases with chalcopyrite structure, and without binary or ternary phases in the films. Vis-NIR measurements determine that the bandgap of CIGS increases with the increase of Ga concentration in the film. When the Ga concentration is 5.41%, its bandgap is about 1.11 eV, and the calculated ratio of Ga to (Ga+In) is 16.3%, which is less than the ratio of Ga to (Ga+In), 21.4%, measured by SEM. This indicates that crystallinity of CIGS filmsneeds to be further improved. All the measurements demonstratethat optimum ITO/CIGS has a promising application in bifacial solar cells. In this paper, we provide a newmethodtoelectrodeposit low cost CIGS precursor films and a new method forselenization ofthe precursor films at high temperature. As a result, theuniform and compact CIGS films with good adhesion on ITO are successfully fabricated by these methods. The above characterization show that we have obtained CIGS films with high crystallinity, near stoichiometry, few impurity phases and superior light absorption. Electrodeposition, like magnetron sputtering, is very suitable for large-scale industrial production. The research work in this paper is therefore important and considerable to massive production of electrodeposition of CIGS films.

With the continuous pursuit of high brightness and low power consumption display technology, RGBW display technology has been attracting increasing attention in the world. Various kinds of displays based on this technology have been produced in the market. The key of this technology is signal mapping algorithm which converts RGB signal into RGBW signal without color distortion and compatible with different sub-pixel layouts. This paper, on the basis of five kinds of signal mapping algorithms, analyzes the mode of action of newly added white sub-pixel affects display color, and the display performance affected by four kinds of sub-pixel layouts; it proposes the corresponding condition of excellent signal mapping algorithm based on colorimetry and deduces the universal equation of excellent signal mapping algorithm and brightness factor which could measure the ability of enhancing brightness. The simulation experiment shows that the signal mapping algorithm which satisfies universal equation could be able to maintain the hue and saturation better. The signal mapping algorithm’s ability to enhance brightness is effectively characterized by brightness factor. In conclusion, the proposed universal equation can be used to evaluate existing signal mapping algorithms, and it provides theoretical references for the research of new signal mapping algorithm which could be compatible with different hardware parameters and sub-pixel layouts, promote the popularization of RGBW display technology.

Cu(InxGa1-x)Se2(CIGS) precursor films were prepared on ITO glass with potentiostatic electrodeposition. High quality CIGS films were obtained by selenization of the precursor films at high temperature in tubular furnace full of argon gas. X-ray diffraction (XRD), scanning electron microscopy (SEM) and UV-Vis-NIR spectroscopy were used to characterize the structure, morphology, composition and Vis-NIR absorption of CIGS films, respectively. XRD results show the selenized CIGS films have a preferential orientation (112) with average crystallite of 24.7 nm. Raman spectroscopy reveals that the CIGS films are pure quaternaryphases with chalcopyrite structure, and without binary or ternary phases in the films. Vis-NIR measurements determine that the bandgap of CIGS increases with the increase of Ga concentration in the film. When the Ga concentration is 5.41%, its bandgap is about 1.11 eV, and the calculated ratio of Ga to (Ga+In) is 16.3%, which is less than the ratio of Ga to (Ga+In), 21.4%, measured by SEM. This indicates that crystallinity of CIGS filmsneeds to be further improved. All the measurements demonstratethat optimum ITO/CIGS has a promising application in bifacial solar cells. In this paper, we provide a newmethodtoelectrodeposit low cost CIGS precursor films and a new method forselenization ofthe precursor films at high temperature. As a result, theuniform and compact CIGS films with good adhesion on ITO are successfully fabricated by these methods. The above characterization show that we have obtained CIGS films with high crystallinity, near stoichiometry, few impurity phases and superior light absorption. Electrodeposition, like magnetron sputtering, is very suitable for large-scale industrial production. The research work in this paper is therefore important and considerable to massive production of electrodeposition of CIGS films.

In this paper, an Nd∶YAG laser with 10ns pulse width and output wavelength of 1 064 nm was employed to ablate Gd metal target and Gd-doped glass target for plasma generation. The out-of-band (OOB) radiation of extreme ultraviolet sources with the two target configurations was comparatively studied. It has been found that the continuous radiation emitted by the plasma is the main component of the out-of-band radiation. The spectral distribution of the continuum emission matches that of blackbody radiation with a temperature of about 5 eV. And it is also found that the intensity of OOB radiation can be considerably decreased by using Gd-doped glass target. Optical Emission Spectroscopy (OES) has been used to analyze the temporal and spatial behaviors of electron temperature (Te) and density (Ne) of the Gd-doped glass target plasma, and experimental results show that temporal evolution of electron temperature and density of the plasma are found to be decayed exponentially with the increasing of delay time. At 125 ns after laser irradiation, electron temperature and density were 4 eV and 1.2×1018 cm-3 respectively, and then decreased to 1.5 eV and 8×1017 cm-3 with delaying time of 250 ns. On the other hand, spatial evolution of electron temperature and density show that both of them first increase and then decrease in the region of 1~10 mm from the target surface. The electron temperature and electron density achieves the maximum of 2.6 eV and 8.5×1017 cm-3, respectively, when the probe location away from the target surface 6 mm.

The stellar classification was an important research field for understanding the formation and evolution of stars and galaxies. With large sky surveys and its massive data, the speed and accuracy of the celestial automatic classification was very important. The depth confidence neural network (DBN), support vector machines (SVM) and BP neural networks used in the star classification were compared in this paper. And the applicability of star classification with these three methods was analyzed. First, K, F stars are classified according to the depth of confidence neural network and BP neural network and support vector machine.Then the K1, K3, K5 sub-type and F2, F5, F9 sub-type were separately identified. Finally, the data which did not belong to the k sub-type were excluded by a secondary classification model based on SVM support vector machine . The results shows that: the depth of belief networks is better for K, F-type star classification, but it is poor for K, F sub-type classification results; The recognition rate of SVM is high for the K, F-type stars and the classification effects of this method is better for K, F-type stars than the corresponding sub-type stars by comparison; The recognition rate of BP neural network is ordinary general for K, F-type stars and their sub-types. The experiment showed that the accuracy of excluding non-k-sub-type data can be up to 100% which indicates that the unknown spectral data can be screened and classified with SVM.

In virtue of the severity and scale of the pollution caused by oil pool flame, space remote sensing can provide us a new way of monitoring in real time the oil pool flame pollution. Space remote sensing monitoring is based on the analysis of target spectrum characteristics. Due to lack of adequate researches on the characteristics of infrared spectrum of oil pool flame, this paper carries out the analytical study on flame spectrums of several types of oil, mixed oil and other combustible objects in outdoor space by establishing all-flame infrared testing system with the spectrum range of 1～14 μm. The results show that the spectrum curves of oil pool flame of 92# gasoline, 95# gasoline, 0# diesel, aviation kerosene and lube have similar features, that there exist characteristics emission peaks at the area of certain wave lengths—H2O characteristics emission peak for 1.1, 2.4, 2.8 and 6.3 μm, CO2 characteristics emission peak for 4.2 and 4.5 μm, C—H stretching vibration emission peak for 3.4 μm, and no obvious characteristics peak for spectrum curves of 6.3 μm and above; that there is no obvious difference in the spectrum of oil pool flame among the mixtures of 92# gasoline and 0# diesel at different proportions, that the comparison of the flame spectrum of 92# gasoline with that of wood and paper shows that there appears a characteristics emission peak at 3.4 μm; that though the flame spectrum of alcohol has similar radiated emission near 3.4 μm, the proportion of its radiation intensity to that of CO2 at 4.5 μm is far less than that for the flame spectrum of 92# gasoline; that the flame spectrum of honeycomb briquette is similar to that of gray body radiation. The differences in flame spectrum among all kinds of combustible materials are closely linked to their chemical compositions and burning reaction mechanisms. Comparative analysis on the spectrum characteristics at continuous area, intermission area and flue gas area shows that C—H stretching vibration peak only exists in continuous area, which proves that the emission peak is caused by the combustible reaction of oil and gas. This result is in line with the mechanism of oil pool combustion reaction. The experimental conclusion is of great significance in the remote-sensing recognition of oil pool flame based on the analysis of spectrum characteristics.

Spectral analysis techniques were applied to geochemical element analysis to provide additional environmental data about evolution of salt lakes and climate change. The elements composition of lake sediments from L07-10 in the “Great Ear” Area of Lop Nur was analyzedby using Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES )and from 14 C carbon dating by using the EN accelerator mass spectrometry (AMS).This paper estimated the climate change in this region since 16.34 ka BP. Results demonstrate that the geochemical characteristics of major elements at all sediment levels can indicate environmental change sensitivity, and element composition is more sensitive to climate change. Overall, climate succession since 16.34 ka BP had been: warm-wet, warm-dry, cold-wet and warm-dry. From 8.09~6.34 ka BP，the climate obviously heated up and was warmer and drier, which is consistent with global and regional climate change estimates from other studies. By about 2 ka BP, the climate becomes warmer and drier and the water carrying capacity of this lake was reduced.

In order to enhance the monitoring of paddy growth, utilize the fertilizer more efficiently, increase crop yield and improve the quality of grain, thus the system of laser-induced fluorescence (LIF) was built. The system was designed to study the relationship between the rice leaf chlorophyll content and fluorescence ratio. In this paper, the samples came from the second upper leaves of paddy in shooting stage and the cultivated area was located in Jianghan plain of China. Firstly, the Kjeldahl method combined with the formula which was described by Zivcak et al. was utilized to calculate the chlorophyll content of paddy, then the fluorescence spectrum of paddy leaf with different chlorophyll content by the instrument of laser-induced fluorescence (the wavelength of excitation 355 nm). Fluorescence spectra of paddy leaf with different chlorophyll content were collected and then a fluorescence spectra database was established. It is discussed that the relationship between the ratio of fluorescence (F740/F685 is the ratio of fluorescence intensity of 740 nm dividing that by 685 nm) and the chlorophyll content of paddy. It is found that the effect of chlorophyll content on the fluorescence spectral characteristics is evident. The results demonstrated that it has the tightly positive correlation between the fluorescence ratio (F740/F685) and chlorophyll content of paddy leaf. The determination coefficient (R2) can reach up to 0.901 3 and 0.912 5 at tillering stage and shooting stage, respectively. The experimental analysis showed that the LIF technology has the advantages of convenient, quick and nondestructive, and it has the potential for quantitative monitoring of crop growth.

In the imaging process of satellite-based pushbroom hyperspectral imager, attitude motions of satellite platform, represented by vibrations, will cause aliasing of the object information comes from different sub-areas of the detector, leading to degradation of hyperspectral image quality. In order to suppress and correct the imaging errors caused by satellite vibrations more effectively, spatial and spectral degradation mechanisms of typical dispersive pushbroom imaging spectrometer caused by satellite vibration are studied in this paper, including theoretical simulation and experimental study. With the analysis of spectral mixing process during exposure, the relationship between spectrum of ground object and satellite attitude is obtained, and a degradation model of pushbroom spectral imaging is presented. The effects of different attitudes of vibration are considered in the degradation model. Mean mixing ratios of each pixel are easy to calculate with a universal coefficient matrix, as long as the satellite attitude parameters of each moment are known. Then the simulation degraded spectral image data cube is achieved. The common expression of mean mixing ration is derived in detail. More important, the effects of vibration amplitude and frequency are quantitative analyzed separately. Degraded simulation and ground simulation experiments are carried out based on real hyperspectral data cubes, then the quality of the cubes before and after degradation are evaluated. Results show that simulation is in good agreement with reality. Mean mixing ratio can reflect the degradation extent of hyperspectral data directly. The satellite vibrations bring about spatial quality deteriorate of hyperspectral image, and lead to the aliasing of spectrum comes from different ground object. The degradation extent of hyperspectral data is determined mainly by vibration amplitude. The influence of frequency is limited.

Most published works focused on the characteristics of chemiluminescence in homogeneous flames, but the research about radiation spectrum in heterogeneous flames was still limited. In this paper, improved hot oxygen burner (HOB) technology is applied to ignite coal water slurry (CWS) directly in the open space, for stable combustion. Radiation spectrum and two-dimensional OH* chemiluminescence in methane and CWS diffusion flames are measured by a fiber optic spectrometer and a high-spatial-resolution UV imaging system. The results show that OH* (309.12 nm), CH* (431.42 nm) and C2* (463.52~563.43 nm) radicals exist in both methane and CWS diffusion flame, but Na* (589.45 nm), Li* (670.88 nm), K* (766.91, 770.06 nm), H* (816.04, 819.99 nm) radiation spectrum line and continuous black-body radiation have been detected only in the CWS flame. These differences can be used to characterize the combustion or gasification of CWS and distinguish whether CWS is ignited or not. In addition, the injection of CWS into methane flame leads to a significant reduction in OH* and an increase in C2* and CH* radiation intensity. This is because a lot of heat is absorbed in the processes of CWS combustion reactions. Then the generation of CH is inhibited, and the production of OH* is reduced. The increase of C2* and CH* is due to simple substance carbon produce more after injecting CWS. Besides, axial OH* radiation intensity increases at first then decreases, and the position of peak intensity is closer to outlet of hot oxygen burner compared with methane flames. Radial OH* radiation distribution is bimodal in methane flame because reactions take place in the thin layer where methane and oxygen meet. However, in CWS flame, radial OH* radiation distribution is always unimodal since CWS diffuses fiercely and mixes with oxygen sufficiently. As the ratio of oxygen atom to carbon atom ([O/C]e) increases, the reaction region of OH* radicals becomes larger in methane and CWS flame. This indicates that increasing oxygen can promote reactions and benefit OH* radicals’ generation. Moreover, with the increase of CWS flow, reaction center is closer to burner outlet, OH* distribution range and peak intensity decrease obviously, CH*, C2*, Na*, Li*, K*, H* and black-body radiation intensities markedly rise. And these characteristics can reflect the changes of operation loads.

The inner part of the oil pool flame could be divided into different combustion areas, and there have been a limited number of researches on the heat transfer characteristics within oil pool fire. Due to the lack of adequate researches on the characteristics of heat transfer in oil pool flame, this paper carries out an analytical study to pool flame spectrums of 92# gasoline，95# gasoline and lube by establishing flame infrared testing system. Spectral information about different combustion regions of oil pool fire is collected. The results show that three kinds of oil pool fire have similar spectral characteristics, with several characteristics emission bands of such combustion products as CO2, H2O and carbon black particles and that 3.4 μm C—H stretching vibration peak is obvious; the main spectral characteristics of smoke zone is high temperature CO2 emission peak at the band range of 4～4.5μm, the heat exchange of flame and air is violent; the temperature changes unstably, and flame pulse frequency is high; spectral characteristics in the intermittent area is high temperature CO2 emission peak at 4～4.5 μm; and flame pulse frequency in intermittent zone is relatively lower compared with that in the smoke zone; compared with that in the flue gas zone and intermittent zone, the combustion in continuous zone is more stable, the spectral characteristics of the region is obvious, and carbon black particle emission intensity is high at 2.5～3 μm, and C—H stretching vibration emission peak shows itself at 3.4 μm, which showed that the characteristic peak oil pool flame spectrum at 3.4 μm is caused by high temperature oil vapor steam. Spectral characteristics analysis of the oil pool flame in different combustion areas shows that the heat transfer is absorbed by the fuel rich layer on the surface of the oil pool flame, which leads to the change in the energy level of the oil vapor near 3.4 μm. The calculation of the emission spectrum intensity of oil pool flame in different combustion areas shows that the intensity in flame continuous zone is the largest, followed by the intermittent zone, that the connection between the flame smoke zone and the air is strong, and that the emission spectrum intensity is the lowest. The results in this study provide a reference for the modification of flame oil heat transfer model.

Due to the [Al] reaction with the CaO-SiO2-based mold flux used in the high-Al steels continuous casting processes, decreasing the SiO2 content is decreased and the Al2O3 content in mold flux is increased, thus converting the original CaO-SiO2-based mold flux into a CaO-SiO2-Al2O3-based mold flux. This conversion of the mold fluxes can cause the problem of high-Al steels continuous casting. Hence, study on the structural characteristics of the CaO-SiO2-Al2O3- based mold flux can provide fundamental data to design optimum fluxes for high Al-containing steels. In this paper, the structural characteristics of the CaO-SiO2-based and CaO-SiO2-Al2O3-based flux were studied by Raman spectroscopy. The results have shown that, the CaO-SiO2-based flux was the silicate structure whose main micro-structure units were Q0, Q1, Q2 and Q3. The network breakers prefer to depolymerize the silicate network in CaO-SiO2-Al2O3-based flux. While the CaO-SiO2-Al2O3-based flux with low SiO2 content, the [AlO4] tetrahedron was entered the silicate network and the melt converted into the aluminosilicates structure, the formation of Al-O-Al linkages and Si-O-Al linkages increased the degree of disorder of network. The results of Li2O replace Na2O and CaO replace MgO have shown that the ions will influence the formation of [AlO4] tetrahedron linkages. CaF2 replace CaO shown that the polymerization degree of mold slag decreased first, and then increased with the content of CaF2 more than 13 mol%. So, the influences of the ions type and the ions content on the structure were both need considered while designing the CaO-SiO2-Al2O3-based flux.

Nitrogen cycle is an important process in the circle of soil ecosystem elements, and nitrification has significant effect on soil nitrogen cycling. The main completer of nitrification is nitrification microbial communities. Soil microorganisms are vital components of wetland ecosystem. They can indicate the variations of wetland ecological environment, and this helps us to have the correct understanding of nitrogen cycle and pollution purification function in wetland ecosystem. This paper tries to study nitrification microbial communities in wetland soils from the perspective of hyperspectral remote sensing technology, based on the monitoring mechanisms of soil nitrogen spectrum. The study explores hyperspectral estimation techniques for nitrification microbial communities in wetland soils, and it can provide a new technical approach to estimate the temporal and spatial distribution of nitrification microbial communities. The study adopted most probable number method (MPN) to count the numbers of ammonia oxidizing bacteria and nitrite oxidizing bacteria respectively, which were main completers of two independent stages in nitrification. And the total results of both count measurements were used as the values of soil nitrification microorganisms for each sampling area. The estimation models of nitrification microorganism and total nitrogen in wetland soils were developed respectively using spectral transformation techniques, such as log-transformed spectra (LR), first derivative (FD), second derivative (SD), continuum removal (CR) and band depth (BD), and modeling methods, such as stepwise multiple linear regression (SMLR) and partial least-squares regression (PLSR) based on the bootstrap technology. The results indicated that the selected estimation bands of nitrification microorganism and total nitrogen were close (especially for original spectral data (R) and SD spectra) when the modeling method of bootstrap SMLR was used. Compared to the bootstrap SMLR, the bootstrap PLSR achieved higher accuracies for estimating nitrification microorganism and total nitrogen in wetland soils. The spectral transformation technique of SD combined with the modeling method of bootstrap PLSR yielded the highest estimation accuracy to predict nitrification microorganism in wetland soils. The CR spectral data combined with bootstrap PLSR produced the highest estimation accuracy to predict total nitrogen content in wetland soils.

A model which is capable of capturing the spectral distribution features helps to improve the WDMS(White Dwarf + M Sequence Binaries) classification system running in SDSS-DR10 because the distribution feature of a spectra is one of the most important factors that determine its spectral type. Radial basis function (RBF) neural network is an efficient computational model that is widely used for numerical approximation and object classification. However, due to the reason that the network’s hyper-parameters are usually determined empirically, the performance of the network is limited. In this paper, on the basis of analyzing the distribution features of WDMS in a high dimensional space, an automatic classification model for WDMS ia propose based on RBF neural network. And according to the features, we propose centroids criterion and width criterion to determine hyper-parameters for the network in a more theoretical way, which improves the accuracy of the model. After training and applying the model, a total number of 4 631 WDMS candidates are classified and 25 of them are newly identified, which proves the feasibility of the model and provides further researches on WDMS with more data.

Compared with the monomer, aggregate exhibits unique features such as electron and energy transfer which can be understood with the study of absorption spectra. In the experimental the absorption spectra of lutein monomer in ethanol solution and aggregate in 1∶1 aqueous ethanol solution are detected by utilizing UV-lVis spectrophotometer. The vibration structure of excited state of lutein monomer is obtained with Gauss decomposition of the absorption spectra. Theoretically, the molecular parameters of excitation energy, vibration frequency of characteristic mode, Huang-Phys factor are calculated by means of simulation of the monomer absorption spectra described by temporal correlation function and Frenkel exciton model. The spectral calculation of the lutein aggregate is conducted by using these parameters and then the factors of the spectral changes affected by the aggregate structure are analyzed. Some conclusions are drawn from the analysis: (1) The absorption peak position of the aggregate is determined mainly by intermolecular interaction. The calculation shows that the interaction is about 2 000 cm-1 according 77 nm blue shift of absorption spectra from experiment result. (2) With the increase of molecular number of the aggregate the half-width of the absorption spectra decreases and the peak position blue shift slightly due to enhanced cooperation effect. (3) Disorder degree from environment has great influence on half-width for the greater disorder degree the larger half-width. The results of this paper will provide a theoretical reference for the further study of lutein aggregate function in biological and materials systems.

Detection of gas concentration with tunable diode laser absorption spectroscopy (TDLAS) techniques is affected by baseline drift and high-frequency noise. Therefore, how to remove the systematic noises has been a hot spot. This paper analyzes the significance of singular value decomposition (SVD) in TDLAS detection system with two different methods of constructing a matrix, and it discusses the differences of processing results for different noises. The second harmonic signal is arranged in a matrix and decomposed. We select the appropriate threshold and putthose singular values smaller than the threshold into zero, then reconstruct the matrix. Experiments show that SVD method does not require additional system components or pass into the zero gas to subtract background. This method is able to remove noises of TDLAS system quickly and effectively. We found that the method of constructing a hankel matrix is suitable for removing high-frequency noise. However, the method of constructing a continuous-cutoff-signal matrix is suitable for removing baseline drift. For example, we set up a TDLAS system to measure the concentration of NH3 while the noise removal rate of the second harmonic curve is up to 80% with this method.

This paper proposed a method for rapid identification of rice storage period based on manifold dimensionality reduction algorithms and near infrared spectroscopy (NIRS) technique. The reflection spectrum curve of old rice and new rice were obtained with a field spectroradiometer and the acquired spectral data was preprocessed with direct orthogonal signal correction method (DOSC) to filter the independent signal from the spectral data which is irrelevant with the dependent variable Y array and eliminate the influence and interference of the irrelevant information in the following chemometric analysis. The Durbin-Watson test and Run test methods were utilized to detect the nonlinearity which exists in the spectral data structure. The enhanced partial residual plot analysis method (Augmented partial residual plot) was employed to quantitative analysis of the degree of nonlinearity of the spectral data. Popular linear manifold dimensionality reduction methods including principal component analysis (PCA) method and multidimensional scaling analysis (MDS) method and popular nonlinear manifold dimensionality reduction methods including Isometries mapping method (ISOMAP), locally linear embedding (LLE) method and Laplacian Eigenmap method (LE) were used to extract the real variable from the preprocessed spectral data. Then, the intrinsic variable was taken as the input of the kernel partial least squares method (KPLS) to establish the relationship between the intrinsic variables and the storage time of rice samples. The number of experiment samples of the new rice and the old rice were 200 respectively and randomly separated into the training set with 300 samples and the test set with 100 samples. Through comparing the prediction results of the regression models which were established with different manifold reduction methods, the experiment results show that the prediction effects of the nonlinear-based models are superior to the linear-based models. Finally, the KPLS model established with 40 true variables extracted with ISOMAP approach achieved the optimal prediction effect. The prediction correlation coefficient (R2p), RMSEP (RMSEP) and relative prediction error value (RPD) were 0.917, 0.187 and 2.698, respectively. It was concluded that NIRS combined with ISOMAP-KPLS method can be successfully used to determine the storage period of rice accurately and quickly. The study provides a scientific means for rapid non-destructive detecting for rice storage period research in the future.

Currently, the technological development of non-destructive analysis and micro-damage analysis of turquoise is fast. LA-ICP-AES, an almost non-destructive analysis, has multiple advantages. This paper attempts to use this analysis method to examine sample turquoise from five places of origin on Mount East Qinling, including ancient turquoise ore in Laziya, in order to attain its major element and microelement data. Then the paper uses PCA to analyze and study its chemical elements in a comparative way. Three main elements are gained through analysis, and their cumulative variance contribution rate has reached 84.96%. The former two main elements’ variance contribution rate is 72.289%. Therefore, the corresponding elements, including V2O5, NiO, B2O3, SrO, BaO, CaO, ZrO, MnO2, are the featured chemical elements of turquoise from different places of origin. Through comparative analysis and research on corresponding chemical elements, turquoise samples produced by different ores vary in terms of the content of some chemical element and chemical components. Two analysis methods combined together will basically realize the appreciation of turquoise in various places of origin. In addition, the research indicates that some chemical contents have positive or negative correlations. Such correlations can be regarded as features of producing area, and can also provide clues as to the cause of formation of turquoise ore. This study preliminarily indicates that LA-ICP-AES combined with PCA and comparative analysis of chemical composition and content has the function of distinguishing turquoise produced in different places of origin to a certain extent.

With direct prediction in the spectral reflectance space with principal component analysis, the numbers of eigenvectors will surpass the numbers of real primary pigments while the eigenvectors and the corresponding coefficients have negative value, which can not directly presented original primary pigment spectral characteristics and corresponding concentration. We proposed an innovative spectral prediction method in which a complete linear spectral space was created according to optical properties of originals pigment. A constrained non-negative matrix factorization algorithm to predict the numbers and spectral curve shapes of real primary pigments was used in the space. So, this paper designed an overall research plan and implementation process about spectral prediction method firstly, and studied how to select and establish a spectral linear space which was conformed to optical properties of originals; taking transparent pigments as example, and spectra constrained non-negative matrix factorization (SCNMF) algorithm was established to predict primary pigment spectra based on basic non-negative matrix factorization algorithm (BNMF). Aiming at realizing multiple optimal solution of BNMF and improving the prediction accuracy as well as make the matrix decomposition results to be clearly physically meaningful; the proposed SCNMF needs to satisfy four constraints: non negative constraint, additive constraint, smoothness constraint and sparseness constraint. The objective function and iterative algorithm to meet four constraints were set up. The prediction results show that the proposed method can realize accurate prediction of original primary pigments’ numbers and spectra effectively.

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.