During the multi-wire GMAW, the working state of the arc will become unstable because of the arcs interference, which will affect the stability of welding process and welding quality. In this paper, the distribution of the electron temperature of the arc have been researched based on Boltzmann spectrometry. Electron densities under different conditions have also been calculated based on Stark width of the plasma spectrum. Combined with the analysis of high-speed photography, quantitative analysis of the arc interference can be obtained. For double wire case, the results of spectral diagnosis show that when the adding arc current is larger than the original arc, the temperature center of original arc is shifted to the new arc side, and the electron density of the original arc near new arc side is obviously increased. While the current of the new arc is equal to the original arc, the temperature and electron density distribution of the original arc all lead to the instability. In the case of triple-wire, the addition of the third arc causes the temperature distribution of intermediate arc become complex, and its electron density distribution is close to that of single wire case.

This article is devoted to the computation of equilibrium compositions of the shielding gases in gas metal arc welding (GMAW) Ar, CO2, and 82%Ar-18%CO2 as well as their mixtures with Fe metal vapour at atmospheric pressure between 3 000 and 25 000 K. The above gases were treated as a type of Ar-CO2-Fe mixture with 39 particles. These particles were divided as two categories: 5 basis particles and 34 non-basis particles. The particle number densities of non-basis particles were expressed by that of basis particles based on chemical equation, thus reducing the unknowns and the computation. Finally, the conservation equations were solved by Newton’s method to obtain the number density of each particle. The results indicate that primary and secondary ionization occur in pure argon with the increase of temperature, the dissociation of molecules of CO2, O2 and CO at low temperature (T＞8 000 K) occur in pure CO2 besides the ionization at high temperature, and both ionization and dissociation exist in the 82%Ar-18%CO2 mixture. It also found that the addition of Fe can increase the electron number density, especially at temperature below 15 000 K. The determination of chemical compositions built a solid foundation for the calculation of radiative properties of GMAW arc plasmas and for the spectroscopic measurement of iron vapour concentration in arcs.

Transition metal sulfide pyrite is a kind of excellent photovoltaic material, doping modification is an important mean to improve the properties of pyrite PV. To explore the impact of Co-doped amount on pyrite crystal structure and light absorption performance, nano-micron-sized pyrite samples were prepared via thermal sulfide method at 360 ℃. In addition, the crystal structure, morphology characteristics and grain size of samples were analyzed with X-ray diffraction(XRD)and multi- functional field-emission scanning electron microscope (FESEM). Moreover, the chemical composition of the samples was tested using the energy dispersive spectrometer (EDS), the light absorption performance and the change of the forbidden band width of the samples were characterized through the ultraviolet-visible-near infrared absorption spectroscopy (UV-Vis-NIR). The results of XRD and FESEM indicated that co-doped led to crystallinity changes, crystal grain reunion, larger size in the range of 1～1.45 μm, but did not change the cubic crystal structure of pyrite, compared with pyrite samples without doping. The grain size decreased slightly with the increasing amount of co-doped, but the impact was not obvious. EDS test showed that the actual samples doping was not uneven, the test value was less than the nominal doping Co amount when amount of co-doped was less than 7at%, while it was larger than nominal when doping Co amount was greater than 7 at %.The ratios of S/(Fe+Co) were within the scope of 1.92 to 2.05, the degree of deviation 2 of the ratio suggested the number change of point defect of internal samples, affecting the light absorption performance of the samples. Besides, reflection spectrum showed that band gap Eg was from 0.57 to 0.72 eV. The width of forbidden band reduced (Co3 at%) before it increased as doping Co amount increased (Co5～9 at%). The additional energy level, formed by a number of point defects in internal samples, led to band gap narrowing, as mixing amount of Co increased from 0% to 3 at%. With further increasing mixing amount of Co, S/(Fe+Co) ratio was closer to 2, the crystal structure was more perfect and the Fe vacancy or S clearance point defect ratio was more decreased, leading to the forbidden band width Eg tend to widen. In addition, with the increase mixing amount of Co, the increasing trace CoS2 phase caused the forbidden band width to larger, up to 0.72 eV, as the mixing amount of Co further increased to 9 at %, which was greater than the forbidden band width of 0.65 eV of not doped samples at the same temperature, the same synthetic methods, in theory, which could effectively improve the photoelectric conversion efficiency.

Net emission coefficient (NEC) is the most implemented method in the numerical models developed for thermal plasma. This paper is devoted to the calculation of NECs for ［82%Ar-18%CO2］-Fe plasmas with different iron contents between 3 and 25 kK. By considering various radiative mechanisms (spectral lines, continuum and molecular bands), we developed a complet database of radiative proerty for the modelling of GMAW arcs (with 82%Ar-18%CO2 shielding gas and a steel wire). Also, it was found that the presence of iron vapour in the plasmas (even with very low content) can greatly improve the NEC and make the contribution of molecular bands and continuum, which are considerable in the NEC of 82%Ar-18%CO2, negligible.

Edible oil is a significant source of human nutrition and energy, providing essential fatty acids for human body. Thus, the investigation on the optical properties of edible oils in THz region for component analysis and quality evaluation is considered to be of great importance. As a newly developed-technique, Terahertz time-domain attenuated total reflection spectroscopy can obtain the THz spectra through the interaction between sample and evanescent wave. Compared with Terahertz time-domain transmission or reflection spectroscopy, this technique can effectively avoid the influence of sample cell when measuring liquid samples such as edible oils, thus acquiring the optical parameters more accurately. The absorption spectra of soybean oil were measured via both Terahertz time-domain transmission spectroscopy and Terahertz time-domain attenuated total reflection spectroscopy. Compared with Terahertz time-domain transmission spectroscopy, the Terahertz time-domain attenuated total reflection spectroscopy showed greater advantages in acquiring the absorption coefficients and distribution of absorption peaks. Furthermore, the optical properties of soybean oil, walnut oil and grape seed oil were investigated by using Terahertz time-domain attenuated total reflection spectroscopy. In addition, the refractive index and absorption spectra of the three edible oils in the range from 1 to 1.8 THz were obtained. Using density functional theory, we also calculated the vibration and rotation modes of four kinds of principal components (hexadecanoic acid, octadecanoic acid, octadecenoic acid, and octadecadienoic acid) in THz region which were consistent well with the experimental results. In conclusion, the absorption peaks of edible oils in terahertz region are related to the components and contents of fatty acidsas well as result from their vibration and rotation modes. Moreover, this research may contribute to qualitative and quantitative components analysis as well as quality inspection of edible oils.

Due to the different production material and process between real and counterfeit paper currency, we identified the true and counterfeit hundred RMB of the 2005 edition based on transmitted THz pulse imaging. The point-to-point terahertz pulse imaging technique was used to scan two feature anti-counterfeit area, white watermark and holographic safety margin. Based on the obtained time-domain data and the corresponding frequency-domain data, the THz images with time-domain display mode and frequency-domain display mode were mapped. The difference of imaging effect is obvious at white watermark area and safety line area, which confirm that the transmission terahertz pulse imaging technique can truly and effectively carry out multi-regional and multi-dimensional authenticating true and counterfeiting RMB.

The extraction and research of cultural relic’s information played an important role in revealing the historical information of human society and culture. We could not only understand the ancient technological features to explore the origin and development process of cultural relics making technology, but also carry out disease investigation and analysis to provide valuable information for the protection of cultural relics. Because of the scarcity and non-renewable nature of cultural relics, it was very important to explore and apply modern nondestructive analysis technology for cultural relic’s research and protection. In this article the common methods and the application status of nondestructive analysis of cultural relics were introduced, which were based on the internal and surface image analysis methods. The applications of X ray photography technology, infrared imaging technology, CT technology, multispectral imaging technology and 3D Laser Scanning technology in imaging of various cultural relics were introduced, and then optical microscope and electron microscope in the analysis of surface morphology and microstructure of cultural relics were applied. Followed is the application of chemical composition of X ray fluorescence spectroscopy and laser ablation inductively coupled plasma mass spectrometry, finally the micro XRD phase analysis, IR reflective material structure analysis and micro Raman spectra analysis on the material structure used in the analysis of material structure. Moreover the advantages and limitations of each technology were preliminarily analyzed. Expecting with the continuous improvement of the technology research, the nondestructive analysis technology in the future will be developing towards miniaturization, automation and portability which have a very broad application prospects in the research and protection of cultural relics.

The mechanoluminescence (ML) materials Sr2SiO4∶Eu, Dy were prepared by high temperature solid-state reaction method. The luminescent and mechanoluminescent properties of Sr2SiO4∶Eu, Dy with differentDy3+ concentrations have been investigated. The results showed that α and β phases of Sr2SiO4 co-existed for the low doped content of Dy3+. When the doped Dy3+ concentration increased, the β phase transited into α phase gradually. Since the Eu2+ ions occupied different Sr sites, the samples presented both blue emission at 486 nm (Sr1) and green emission at 530 nm (Sr2). However, the mechanoluminescent (ML) and afterglow spectra were consistent in the emission at 530 nm, which indicated that both emissions originated from Eu2+ transition located at Sr2 sites. Comparing thechange of mechanoluminescent (ML) and afterglow intensity, we can conclude that the changes of mechanoluminescence performance are not only related to the traps but also related to its structural. At the same time, the ML intensity of Sr2SiO4∶Eu, Dy increased with the increase of mechanical load and the ML images of Sr2SiO4∶Eu, Dy can be observed by naked eyes, which suggested this phosphor can be applied as potential sensors to detect stress. Furthermore, combined with afterglow, thermoluminescence and ML properties, it can be inferred thatthe origin of ML is piezoelectricity-induced electroluminescence, that is, piezoelectricity impelled the trapped electrons from the traps and produce ML.

Time-resolved particle image velocimetry (TR-PIV) is a widely used non-intrusive flow visualization technique that allows the acquisition of instantaneous flow fields in a planar cross section of a flow. In order to refine the instantaneous spatial structure and study the evolution of a flow, a multispectral-based PIV system is developed to improve the time resolution. With multiple-wavelength monochromatic laser pulses, a planar cross the section of the flow is illuminated, and an image is formed of the tracer particles those are located inside the light sheet. Through a process of image decomposition and interrogation, a velocity vector map is yield. In order to verify the feasibility of the principle, an experimental setup of time-resolved particle image velocimetry is arranged. A light source with three monochromatic spectrums (488, 532, 632.8 nm) is produced in an accurate time sequence by a laser projector. Particle images at three different instants under the illumination are captured in one snapshot. The time interval between two frames is reduced from 10 ms to 3.4 ms and the time resolution is improved 3 times by means of multispectral-based imaging technique. The experiment result demonstrates that the multispectral-based PIV system is a feasible resolution to obtain instantaneous whole flow field, as well as to improve time resolution.

Liquid oxidation techniques by sub-molten salt media for the effective extraction of amphoteric metal from refractory minerals have been developed. An innovative synergistic process by electrochemical oxidation and reactive oxygen species (ROS) intensify was further proposed. In the present study, the mechanism of ROS formation and conversion in the electrocatalytic process was systematically revealed by UV-Vis spectra and electron spin resonance (ESR) measurement. The reactive species were in-situ generated by two-electron oxygen reduction reaction (ORR) at the cathode surface. The ·OH was produced from the self-induced reaction between amphoteric metal ions and HO-2, which was beneficial for the oxidation dissolution process and considered as an alkaline electrochemical advanced oxidation process. The catalytic oxidation process of low-valance amphoteric metal oxides (Cr2O3 and V2O3) by ROS was illustrated by UV-Vis spectra. Furthermore, V2O3 was more easily dissolved than Cr2O3 with the presence of ROS according to the thermodynamic data of standard free energy change. The ·OH in the electrochemical system was detected by the ESR technique. The ESR signal of ·OH catalyzed by V2O3 was more remarkable than that of Cr2O3. The quenching experiment result proved that ·OH with high standard oxidation potential played a promoting role in the liquid oxidation process. The present investigation provides further standing for the electrochemical oxidative dissolution in alkaline media.

Tunable diode laser absorption spectroscopy (TDLAS) is often used to detect CO2 concentrations in many fields. But because of the variation of ambient temperature, the measured the line strength and line-shape are affected and may lead to the monitoring errors. Therefore, in order to overcome the influence of temperature change on the concentration measurement, we used the DFB laser with the center wavelength of 1 580 nm and the direct absorption method was used to measure the high concentration of carbon dioxide gas in the flue of the power plant under the condition of room temperature (298 K) and variable temperature (298~338 K, interval 10 K). The results showed that the maximum relative error of the concentration measurement was -5.26%, the minimum relative error was 1.25% and the relative error mean square was 3.39%, which indicated that TDLAS measurement system had good measurement precision and stability at room temperature. But the concentration measurement in the temperature measurement error, the maximum of relative error was more than 25%. Then, the influence of temperature change on the measurement of the concentration was solved to meet the needs of industrial measurement and on the basis of temperature change measurement, the least squares method was used to fit the correction relation between the concentration of the measurement system and the gas absorption at different temperatures. After the correction, the relative error of the CO2 concentration measurement was reduced to below 5%, and the relative error mean square value fell below 3.5%.The correction results showed that the proposed method can effectively suppress the influence of temperature change on the concentration measurement and improve the measurement accuracy and stability of the system in the variable temperature environment, which provides theoretical support and technical support for the TDLAS system field application.

The Forbidden City in Beijing is the world’s largest and most complete preserved ancient wooden structure buildings. 2016 has witnessed its fisrt restoration since its extablishment one handred years ago. The Yanxi Hall, which has a large area of colored paintings, is an exquisite hall in the rear of the Yangxin Hall and is one of the most important objects in this restoration project. The colored paintings have the function of decoration and conservation of the wood inside. The identification of the original materials in the colored paintings is important for the study of the craftsmanship and the judgement of the disease. As the concept of “restoration as the past” is one of the main theory for the conservation of the heritage in China, the original material study is important for the design of restoration. In this study, a set of integrated testing methods, including cross-section analysis method, back scattered electron (BSE) image, energy dispersive spectrometer(EDS), Raman spectroscopy(RS), fluorescence staining, enzyme-linked immune sorbent assay(ELISA), immunofluorescence microscopy(IFM) and pyrolysis gas chromatography mass chromatography (py-GC-MS), was put forward and utilized to demonstrate the pigments and binders of the colored paintings of the Yanxi Hall. The results showed that the pigments are ascribed to cinnabar, red ochre, ultramarine, malachite azurite and paratacamite. The plaster embossing was composed of quartz, talc, chalk or dolomite. Tung oil was the binder of the ground layer, while animal glue was used as binder in the pigment layer. When studying the colored paintings from the roof beams, a red pigment layer, which was composed of cinnabar, was found both at the bottom and inside of the ground layer. The red pigment layer was composed of two layers. The internal layer was made up of cinnabar and red ochre, which had the diameter of only about 1 μm, while the outer layer was composed of cinnabar, whose diameter distributed in the range of 1~30 μm. The red pigment layer inside the ground layer and the two red layer to decorate the suface are unique crafts for the colored paintings from the Yanxi Hall. These results demonstrate that this set of integrated methods has the advantages of micro destructive sampling and high reliability. It is an economical and practical method to investigate the pigments and binders of colored paintings.

Using the density functional theory (DFT), the geometrical structures of the (Li2F)nM (M=Li, Na, K; n=1, 2) clusters were optimized at the B3LYP/6-311+G* level of theory, and all of ground-state structures were determined, while their chemical stabilities, electronic properties and infrared spectra were systematically discussed. The calculated results showed that the (Li2F)M (M=Li, Na, K) clusters had the same double-triangular geometries, whereas the structures of (Li2F)2M were distinctly different. It was also found that the (Li2F)Li and (Li2F)2Na clusters were strongly stable due to the large binding energy and HOMO-LUMO energy gap. The high chemical stability can be explained by the strong sp hybridization to form the σ bonds (e. g., HOMO, LUMO). Meanwhile, it was predicted that the (Li2F)2K cluster could be considered as novel superalkali compound because of its low ionization potential (4.23 eV). In addition, we simulated the infrared spectra of these (Li2F)nM clusters, and assigned the main vibrational peaks for further experimental references.

In order to elucidate the relationship between structure evolution and carbon isotope of alkane gas in coal pyrolysis process, we selected low rank coal to carry out pyrolysis experiments in autoclave closed system. The carbon isotopic composition of alkane gas was analyzed, and the evolution of coal structure was studied using Fourier transform infrared spectroscopy (FTIR). The relationship model between carbon isotope composition of alkane gas and structure evolution was established. Moreover, the reasons for changes in carbon isotope of alkane gas were revealed. The results showed that light carbon isotopes fractionation of lipid chains cause heavy carbon isotopes to be retained in long chains when Ro, max＜1.3%. The materials within the loop, containing heavy carbon isotopes, are not fractionated out heavily when 1.3%＜Ro, max＜2.0%, and carbon isotope of alkane gas still depends on the further fractionation from lipid chains. Namely, the changes in carbon isotope of alkane gas are mainly caused by lipid chain orientation fracture when Ro, max＜2.0%. Since then (Ro, max＞2.0%), due to the intensification of aromatic condensation and disintegration, the heavy carbon in the loop can be released into the alkane gas, and its carbon isotopic composition rapidly becomes heavier. There is a synchronization phenomenon between carbon isotope composition of methane and ethane and structure evolution of lipid chain, and the values of δ13CCH4 and δ13CC2H6 can be used as the sensitivity index of structure evolution of lipid chain. In addition, it was pointed out that Ro, max=1.3% and 2.0% are important nodes in the relationship between structure evolution of coal and carbon isotopic composition of alkane gas in pyrolysis process. The research results have theoretical significance in exploring the coupling relationship between hydrocarbon generation of coal and structure evolution and mechanism of secondary hydrocarbon generation.

Refined coal tar pitch (QI＜0.2%) was used as the raw materials to produce coal-based needle coke. The quality of coal-based needle coke was decided by the thermal conversion properties of refined coal tar pitch. In this study, FTIR spectrum combined with curve-fitted method were used to quantitative analysis the structure changes of refined coal tar pitch in different thermal conversion temperature. The aromaticity index (Iar), branched index (CH3/CH2), contents of each basic function-groups (CO, CC, and C—O), and the species of aromatic substitution have been studied. The results showed that: The Iar and CH3/CH2 index of refined coal tar pitch increased with the increase of thermal conversion temperature. It meant that the rupture of the Branched chain may cause the production of active site, and the active site was one of the reasons to induce the aromatic rings increase. With the increase of thermal conversion temperature, the contents of CO decreased from 26.25% to 15.62%, the contents of CC improved from 43.39% to 51.28%, and the contents of C—O remained essentially unchanged. It means that, CO groups were another important reason to induce the occurrence of the condensation reaction of large molecule aromatic ring. The contents of 1H and 3H were decreased, but the content of 4H was increased, which indicated that, the aromatic substitution was also decreased, and the aromaticity improved. This phenomenon was match up to the Iar analysis.

Soilmercury (Hg) contamination may affect the growth of rice plant and rice quality. However, little information has been available so far on the effect of Hg pollution on the molecular structure of nutrientcomponents in rice by Fourier transform-infrared spectroscopy(FT-IR). This study aimed to detect the effect of soil Hg pollution on the FT-IRcharacteristics of rice plant organs through a FT-IR scanning of riceroot, stalkplus leaf, and seed collected from rice field under low-, medium-, high-Hg contamination. Results showed that soil Hg resulted in an accumulation in rice organs with an Hg allocation: root >stalk plus leaf>seed. FT-IR signals of root and stalk plus leaf at 3 428, 2 922, 2 851, 2 364, 2 344, 1 750～1 500, 1 150～935 cm-1 were under influence of Hg stress. Meanwhile, FT-IR spectra of rice seed seemed to be affected by Hg pollution at 3 426, 2 361, 2 335 and 1 750～1 300 cm-1. FT-IR analysis may indicate that Hg stress reduced absorbance of carbohydrate in all rice organs and stimulated the production of carboxylic acids, galactosum, and saturated lipids in root and the synthesis of polysaccharides in stalk and leaf. Root, stalk and leaf were the main organs to resist Hg stress for rice plant. Root may secrete organic acids to chelate Hg and enhance the formation of cytoderm to adsorb Hg, which may withhold Hg transportation from root surface to rice plant. It is supposed that an appropriate utilization of such mechanism of Hg resistance may reduce the harm to rice plant. Attention should be paid not only on the content accumulation of Hg in rice but also the effect of Hg contamination on rice growth and rice quality.

The Fe, Al, Mn oxides play an important role in the catalytic action of lignin being transformed into HS. In order to elucidate the relationship among the microorganism-lignin-Fe, Al, Mn oxides effectively and reveal the structural characteristics of mineral-microbial residues, the culture method of liquid shake flask was adopted in this article, the lignin serving as the C source, through the addition of goethite, bayerite and δ-MnO2 powder to start the liquid culture of 110 days after inoculating the multiple strains, and then the mineral-microbial residues were dynamically collected and their characteristics were studied by FT-IR and SEM techniques. The results were as follows: goethite had some pine needle structures, and the strips of dark materials were formed and attached to its surface after its participation into the formation of mineral-microbial residues from the microbial utilization of lignin. The apparent structures of goethite were irregular, but its crystal structure had not been changed. The polysaccharides from the multiple strains could exchange with the anions of free hydroxyl groups of goethite, and the proportion of aromatic C structures could be increased. The Fe—OH bond and γ-OH bond of (001) surface were masked due to the microbial thallus covered on the surface of goethite, and the vibration frequency of Fe—O bond was enhanced by the protonation of Fe—OH; The surface structure of bayerite was loose and resembled with the fluff sphere-like substances. After the participation of bayerite in the formation of mineral-microbial residues, its polycondensation effect was obvious, the loose degree was decreased, and the microcellular structure from its surface was reduced. The aluminum hydroxyl vibration frequency of mineral-microbial residues was decreased due to the hydrogen bonding effect, namely the polarity of O—H bond combined with AlOH was weakened. The introduction of lignin could enhance the proportion of aromatic C structure of mineral-microbial residues, but with the culture, its content was decreased first, and then was through the condensation; The surface of δ-MnO2 particles were rough, which could be aggregated in the flocculent or granular form. After the participation in the formation of mineral-microbial residues, the aggregation trend of particles was obvious, the stacking was more compact and its surface structure was more smooth. During the period of 60 days, the crystallinity from δ-MnO2 was affected by the superposition from the microbial thallus and hydrogen bonding, which could reduce the polarity of O—H bond. The increase of —OH content of H2O molecule in the interlayer could produce a superposition effect on the O—H bond, which could enhance the absorption peak intensity of 3 404~3 435 cm-1. The proportion of aromatic C structure of mineral-microbial residues was caused by the association of the hydroxyl groups from the polysaccharides of microbial thallus with the δ-MnO2 through the hydrogen bond and chemical force, but in the process the Mn—O group was masked. The participation of δ-MnO2 could make the mineral-microbial residues produce much more aromatic C structures and provide much more stable C contents for the formation of HS, followed by goethite, while the bayerite was beneficial to the microbial degradation of lignin during the culture of 30~60 d.

In order to investigate the feasibility of two-dimensional (2D) visible/near-infrared (Vis/NIR) spectroscopy method to optimize the characteristic variables of total volatile basic nitrogen (TVB-N) in pork, storage time was employed as external disturbance and 2D correlation spectral characteristics of pork samples with different freshness degrees were studied in this paper. First, Vis/NIR reflectance spectra in the spectral region of 400~1 000 nm of 56 pork samples stored for 1～14 days were collected. Partial least squares regression (PLSR) model was established to relate full-band spectra after pre-processed with standard normalized variate (SNV) and TVB-N values with determination coefficient in the prediction set (R2p) of 0.792 1 and standard error in the prediction set (SEP) of 3.658 2 mg·(100 g)-1. Then ten samples which had a certain concentration gradient were selected for 2D correlation spectrum analysis (with storage time of 0, 36, 72, 108, 144, 180, 216, 252, 288 and 324 h) according to the reference values of TVB-N determined by the standard methods. To eliminate the influence of noise and environmental temperature, the original spectra were pre-treated with first derivative and seven bands were selected for 2D correlation spectrum analysis according to the spectral differences between different samples. The wavelength ranges were 400~420, 450~465, 500~550, 555~580, 586~717, 726~787 and 860~960 nm, respectively. By analyzing synchronization spectrum and autocorrelation spectrum of each band, 23 variables were selected as the sensitive wavelengths to TVB-N. Then simplified PLSR model was built based on the selected feature variables. Compared with the model based on full band spectral data, the model performance was improved with R2p increased to 0.865 8 and the SEP dropped to 3.246 0 mg·(100 g)-1. The results showed that it was feasible to optimize the characteristic variables of TVB-N based on 2D correlation spectrum and this method was capable of selecting feature variables which were related to target attribute. The study also provided a new method to select the characteristic wavelengths from NIR spectra.

The SiO2 content of iron is an essential index to control and measure the quality of iron ore. It is important to determine the method of mineral processing and the process of ore blending. The traditional method of SiO2 content measurement has the defects of heavy workload, complex operations and long period,thus it is difficult to determine SiO2 content of iron quickly and efficiently. The thermal infrared spectrum data of Anshan-type iron experimental samples from Anqian mining area of Liaoning province was measured and collected by Turbo FT. The spectral characteristics of the experimental samples were analyzed. In addition, the RI, DI and NDI were established based on the spectrum data of the samples. The most sensitive waveband and correlation coefficient between spectral indexes and SiO2 content were determined. The NDI which had the most significant correlation with SiO2 content was selected out. Besides, the model for predicting SiO2 content of experimental samples was established based on NDI. We tested and verified the practicality of the model. The results showed that the sensitive waveband of the three spectral indexes and SiO2 content were all located at 8.06 and 8.20 μm which was the left border of Reststrahlen Features. And the correlation coefficient of the three spectral indexes and SiO2 content were all above 0.9. The correlation between NDI and SiO2 content was the best. Moreover, the predictive residual of SiO2 content prediction model which was based on NDI was 3.57%. The prediction results of the model were ideal. We provide a new method for determining the SiO2 content of Anshan-type iron. The method has the advantages of low working strength, simplicity, efficiency and non-pollution nature. It has some certain guiding significance for remote sensing exploration.

Coal serves as the main energy in industrial field, the quality of which has a decisive effect on industry and environment. In the using process of coal, if the category of the coal fails to be identified correctly, it will result in great harm to production efficiency, environmental pollution and economical loss. The traditional way of classifying coal mainly depends on artificial classification as well as chemical analysis, which however entails high cost and consumes too much time. Therefore, it becomes more and more important to identify the quality of coal quickly and correctly. Hence, this essay comes up with the idea of combining deep learning, ELM arithmetic and visible, infrared spectra to construct coal classification model. Firstly, we collected different coal samples from Fushun, Yimin and Henan Jiajinkou coal mining area, and used the American Spectra Vista SVC HR-1024 spectrometer for the measurement of the spectral data. Then we used the deep learning of convolutional neural network-CNN to extract spectral characteristics, and adopted ELM arithmetic to construct classification model for spectral data. Finally, in order to further improve the classification accuracy, this article made use of particle swarm optimization algorithm by using a range of newly defined inertia weight and acceleration factor values to improve the particle swarm optimization algorithm. Then, we used the improved particle swarm optimization to optimize CNN-ELM networks. Experimental results from comparison between PCA and CNN network reveal CNN network as a better feature extraction method for the spectrum. The results also show that CNN-ELM classification model has a good classification effect. The improved ELM classification model accuracy is higher than that of the basic ELM and SVM classification model. Compared with the traditional chemical methods and artificial methods, this method has the advantage of being unparalleled in economy, speed and accuracy.

Fourier Transform Infrared Spectroscopy combined with correlation analysis, second derivative infrared spectroscopy and two-dimensional correlation infrared spectroscopy was used to discriminate 13 species of wild mushrooms. The results showed that the general characteristics of absorption bands in the original spectra were similar, which were mainly composed of protein and polysaccharides. Correlation analysis was applied for the spectra of samples, and the correlation coefficient between Termitomyces eurrhizus and Tylopilus plumbeoviolaceoides was 0.779, which was the minimum, while the correlation coefficient between Pleurotus lignatilis Gill and Hygrophorus lucorum Kalchbr was 0.960, which was the maximum. Coprinus comatus had little correlation with other samples. The differences of intensity, position and shape were observed in second derivative spectra in the range of 1 700～1 400 and 1 400～800 cm-1. In two-dimensional correlation spectra, the differences of the position or form of auto-peaks and cross peaks have been found in the range of 1 380~1 680 cm-1. The number, position and intensity of auto-peaks and cross peaks were obviously different in the range of 920~1 230 cm-1. The study demonstrates that Fourier Transform Infrared spectroscopy combined with correlation analysis, second derivative infrared spectroscopy and two-dimensional correlation infrared spectroscopy might be developed as a rapid method to discriminate different kinds of mushrooms.

Derived from ancient plants, ambers are the natural fossilized resins undergone a variety of geological reworking. Copal resins of lesser age and lower maturity are similar in appearance to ambers but semi-fossilized. Both copal resins and ambers are the products of fossilized processes of natural resins, and the chemical compositions of them bear typical characteristics of transitivity, over tapping and similarity, which makes the identification difficult. Recently copal resins from two origins are found in Chinese market. Borneo copal resins with brownish-red or brown appearance are easily mistaken for Burmese ambers, while Madagascar Copal Resins with faint yellow or golden color are confused with Baltic ambers. The market prices of copal resins and ambers with similar appearances vary considerably, which has aroused wide attention. Research objects were Borneo copal resins and Burmese ambers, Madagascar copal resins and Baltic ambers. Each category were selected 4 representative samples, a total of 16 pieces. Fourier-transform infrared (FTIR) spectroscopies were performed at the School of Gemology, China University of Geosciences in Beijing (CUGB). Using KBr pellet transmission method (100 mg KBr and 1.0 mg sample), mid-infrared (4 000~400 cm-1) spectra of investigated copal resins and ambers were obtained by a BRUKER TENSOR 27 FTIR spectrophotometer, with a resolution of 4 cm-1 and 16 scans each sample, at room temperature. Investigated Copal resins and ambers had distinct differences of shift and intensity of absorption peaks in the spectra, which might be used to rapidly identify them. The spectroscopic characteristics of Borneo copal resins were four absorption peaks in the region 3 000~2 800 cm-1, one strong absorption peak at 1 710 cm-1 and one shoulder peak at 1 730 cm-1, two weak peaks at 887 and 824 cm-1. The spectroscopic characteristics of Madagascar copal resins were three typical absorption peaks relevant to CC functional group, one strong absorption peak at 1 697 cm-1 and one shoulder peak at 1 724 cm-1, “W-shaped figure”composed by two absorption peaks at 1 271 and 1 176 cm-1. Burmese ambers similar with Borneo copal resins can be rapidly identified by the absorption peaks in the region 3 000~2 800 cm-1, one strong absorption peak at 1 724 cm-1, “W-shaped figure”in the region 1 300~1 100 cm-1. Baltic ambers confused with Madagascar copal resins can be rapidly distinguished by the typical figure of “Baltic shoulder”. In addition, R (A1 383 cm-1/A1 464 cm-1) value of Borneo copal resins are 0.823~0.860, greater than 0.605~0.643 of Burmese ambers. 0.900~0.985 of Madagascar copal resins were greater than 0.704~0.783 of Baltic ambers. R value can also be one of identification features. Domestic researches about ambers and copal resins were focused on GC-MS ClassⅠtype whose macromolecular structure were based on polymers or copolymers of labdanoid diterpenes. Previous research objects of copal resins were mainly from New Zealand and Colombia, lacking of Borneo and Madagascar copal resins. This research comparatively analyzed copal resins and ambers with similar appearances (Borneo copal resins and Burmese ambers, Madagascar copal resins and Baltic ambers), It revealed the infrared spectroscopic characteristics of Borneo copal resins and Madagascar copal resins and provided the scientific evidence to rapidly identify copal resins and ambers with similar appearances. Combined with previous studies, these research findings showed that infrared spectroscopy may have scientific significance for the classification of copal resins from different origins, as well as for the identification between confused copal reins and ambers.

We had testified that the decay volatile of fruit could be detected by using infrared spectroscopy. We collected volatile to a gas cell in this methods and used multi-reflecting structure to enhance optical path. In this study, we used open-path infrared spectroscopy to monitor grape decay volatiles and tried both active and passive modes. We qualitatively analyzed the volatiles produced by the decay grape according to the characteristics of infrared spectroscopy, and measured the infrared spectra of the volatiles during storage establishing the method for different decay status according to the changing rules. We also tried to directly analyze the volatile by the origin spectra and demonstrated that it still had obvious spectra characteristics. In this study, It was proved to be feasible using open-path infrared spectroscopy to monitor the decay volatiles. With the advantages of flexible use and non-contact on-line measurement, the method could be applied in large area to monitor the decay status of fruit and even to locate decay source.

Dilute acid pretreatment (DAP) is an attractive method to overcome the natural recalcitrance of lignocellulosic materials, the enzymatic conversion of which can be improved significantly. Therefore, lignocellulosic biomass can be converted to biofuels with a higher efficiency. However, the mechanism of cell wall deconstruction during DAP on sub-cell level is still unclear. In this study, the topochemical changes of Pinus massonianafiber cell walls after DAP was investigated using confocal Raman microscopy combined with principal component analysis and cluster analysis. The samples were presented with specific distribution in the first and second principal component space, which were with cumulative contribution of 94.61%. The accurate average Raman spectra from different lamellas of cell walls were obtained by cluster analysis. With Raman imaging combined, it was observed that the high-lignified cell corner (CC) was with a high concentration of lignin and the low-lignified secondary wall (SW) was with a high concentration of carbohydrates. The heterogeneity of cell wall deconstruction in Pinus Massoniana during DAP was alsovisualized; the compact structure of raw materials was disrupted. The Raman intensity of typical carbohydrates bans at 2890 cm-1 in the SW decreased 26.9% when compared with that for untreated samples, which indicated thatvast carbohydrates were removed from the SW. A certain amount of carbohydrates was also removed from the compound middle lamella (CML), but slight carbohydrates enrichment was observed in the cell corner. Lignin redistributed during DAP and therefore the Raman intensity of lignin in cell corner was enhanced. The removal of carbohydrates (mainly hemicelluloses) and the lignin redistribution can improve the enzymatic hydrolysis by increasing the cellulose accessibility. The present study not only provides a convenient and efficient method for investigating topochemistry of fiber cell walls, but also brings new insights into studying the high-value conversion of lignocellulosic biomass.

The dinosaur eggs from Qiyunshan, Anhui Province, are the newly discovery which can provide new information for researching the formation mechanisms of dinosaur eggshell. Polarizing microscope and Laser Raman spectroscopy were used to analyze the inner mineral composition and structure characteristics of Qiyunshan dinosaur eggshell in this paper. The results showed that the main minerals of eggshells composed of calcite, organic matter and little quartz, opal, muscovite, dolomite, glauconite and goethitewere formed by permineralization and carbonization. Polarizing microscope results revealed that primary calcite and secondary calcite appeared graphic structure. The crystalline degree of primary calcite was poor, which was the product of eggshell petrification, while the crystallinity of secondary calcite was better and there were little quartz in secondary calcite. Raman spectra analysis indicated that the Raman peaks of primary calcite and secondary calcite both appeared near 1087, 282, 713 and 155 cm-1, but the Raman intensity and crystallinity of secondary calcite with coarser particles were higher than primary calcite, which was consistent with the microscopic observations. Raman peaks appearing near at 1 360 and 1 600 cm-1were related to the tiny crystal vibration and C—C stretching vibration of organic matter. All of Raman peaks near 466, 209, 130, 357 and 404 cm-1were the characteristic peaks of quartz. In addition, the Raman peaked near 898, 629, 1 458, 654 and 481 cm-1represent opal, muscovite, dolomite, glauconite and goethite respectively, which suggested that minerals in the surrounding rock hadentered the inside of the eggshell. The conclusion provided important data for studying the mineral formation of eggshell and sedimentary environment of the dinosaur-egg-bearing strata.

Haze has seriously affected the people’s daily life. By detecting the polarization information of the scattered ultraviolet light of haze particles, the causes of haze can be effectively analyzed. Small-scale surface roughness is a morphological feature that is obtained from mineral and dust particles in haze, therefore Chebyshev particle modelcan be used to knowthe haze particles. The “solar blind” ultraviolet light will be scattered due to the Chebyshev haze particles. The polarized properties of the scattered light can invert the physical properties (such as particle size parameters, complex refractive index, particle deformation, ripple parameter) of the Chebyshev haze particles. This paper has used the ultraviolet single scattering model and T matrix method to analyze the relationship between the physical properties of Chebyshev haze particles and the ultraviolet light polarization properties (Stokes vector and the degree of polarization). The results show that the particle size has a great influence on the change trend of the scattered Stokes vectorIsand Qs with the scattering angle. The change of the particle size and the imaginary part of the particle complex refractive index caused the degree of polarization the scattered light changed with the scattering angle. Meanwhile, the article has been specifically analyzed the effect of the Chebyshev particle size on the scattered light Stokes vector Is and Qs is the largest when the scattering angle is 10°. And when particle size r<1 μm, the change of Is with particle size shows a parabolic trend. When the deformation of the Chebyshev particle isincreased, the scattered Stokes vectorIspresents increased initially and then decreased.

This study investigated how the anions had the effect on the spectral characteristics of dissolved organic matter (DOM) of secondary effluent from municipal wastewater treatment by using three-dimensional fluorescence spectroscopy and UV spectrophotometry in order to provide the data foundation for DOM’s environmental behavior. The results showed that the addition of SO2-4 and Cl- could increase or decrease the fluorescence intensity of DOM’s fluorescence peaks. In addition, the fluorescence peak representing the visible humus-like was observed with the additional concentration of NO-3 with 0.005~0.1 mol·L-1. Moreover, the fluorescence intensity of each fluorescence peak decreased obviously with the increase of NO-3 concentration, and the excitation and emission wavelengths of the fluorescence peaks representing the humus-like were red shifted with the right side of UV absorption peak. The added NO-3 concentration was positively correlated with HIX with the determination coefficient of 0.993. This was similar to that with UV254(0.994), UV253/UV203(0.987), α300(0.998) and α250/α365(0.995). And it had the negative correlation with BIX as the determination coefficients was 0.949. However, it had no significant effect on α350 and α355. In conclusion, the addition of SO2-4 and Cl- had little effect on the fluorescence and UV characteristics of secondary effluent DOM except fluorescence intensity. When the concentrations of NO-3 in the samples were different, it had a certain effect on analyzing the source and the properties of the different DOMs by using fluorescenct parameters and UV parameters.

A new method was put forward to study vinegar brand traceability based onthree-dimensional fluorescence spectra technology combined with quaternion principal component analysis. Firstly, the three-dimensional fluorescence spectral data of vinegar samples with different brands were acquired by F7000 fluorescence spectrometer. The contour and 3D fluorescence spectra about four different brands vinegar were acquired and the three-dimensional fluorescence contour maps were analyzed; Then the parallel quaternion matrix representation model of vinegar three-dimensional fluorescence spectral data was established by using the emission spectral data under excitation wavelength of 380, 360 and 400 nm respectively. The quaternion features were extracted using quaternion principal component analysis, and the exacted quaternion principal components were conducted feature fusion based on operations of multiplication, modulus and summation respectively; At last, the fusion features were as the input of K-Nearest Neighbors, and the optimal classification model of vinegar brand traceability was made. The relationships between the model classification accuracy and the three different feature fusion methods and the number of quaternion principal components were discussed. According to the analysis results with 120 vinegar samples of four different brands, the fusion feature obtained by summation operation can establish the best traceability model by using the least number of features, and the accuracy of the prediction set can reach 100%. The results of this study showed that the quaternion principal component feature extraction and feature fusion methods can represent the rich information contained in the three-dimensional fluorescence spectral data in parallel, which provides a new idea for the analysis of three -dimensional fluorescence spectral data.

A metal-organic framework ［Zn (3,4’-Hdpdc)2(4,4’-bpy)］ (Zn-MOF) has been synthesized by hydrothermal reaction with the Zn(NO3)2·6H2O, 3,4’-biphenyl dicarboxylic acid (3,4’-H2dpdc) and 4,4’-bipyridine (4,4’-bpy) , and its crystal structure was confirmed by X-ray single crystal diffraction. The complex was the monoclinic system, C2/c space group. The complex had a “Z”-shaped chain structure formed by the 4,4’-bpy ligand and Zn(Ⅱ) ion. The Zn-MOF exhibited intense ligand-based blue luminescence with the maximum excitation wavelength of 278 nm, and the emission band was in the range of 341~537 nm from the π*—π transition of the ligand. The emission maximum was at 406 nm. The luminescence properties of the complex toward Ln(Ⅲ) metal ions in methanol/aqueous solutions were studied. Fluorescence spectrum show the characteristic emission peaked of Tb (Ⅲ) ions at 490, 545, 585 and 624 nm, which corresponded to 5D4→7FJ (J=6～3) transitions of Tb (Ⅲ), the strongest emission peaked at 545 nm (5D4→7F5), for the green light. The experimental results showed that the Zn-MOF can sensitize the Tb(Ⅲ) ion in the methanol solution and in water, and thus the compound can be used as a fluorescent probe to detect Tb(Ⅲ) ions in methanol solutions and in water.

In order to provide theoretical guidance for the grading of winter jujube maturity after harvesting, this study applied hyperspectral technique to obtain the characteristic wavelengths and calculate the spectral indices to achieve its maturity visualsort. A total of 336 samples of jujube with three types of maturity (immature fruit, white ripeness and primary red fruit, half red and red fruit) were collected and their hyperspectral information wereacquired. The samples were divided into training set (226) and testing set (110) using Kennard-Stone (K-S) method after the original spectral noise was reduced by Savitzky-Golay(S-G) smoothing algorithm. The characteristic wavelengths (CWs) were selected withsuccessive projections algorithm (SPA) and Competitive adaptive reweighted sampling (CARS). At the same time, 7 Spectral indices (SIs) were imported from the perspective of fruit varied physiological components. Three partial least squares discriminant analysis (PLS-DA) models were established based on the CWs selected by SPA and CARS and the introduced SIs, and the classification results of three models were compared. The results show that the discrimination accuracy of PLS-DA models based on two kind of CWs(selected by SPA and CARS, respectively)and SIs wereseparately 97.27%, 95.45%, and 98.18%. For the purpose of showing the discriminant results intuitively, a regression equation of the discriminant vector Y was fitted with SIs joint its PLS-DA regression coefficients, and the discriminant results were visually displayed by different colors in accordance with the rule that the corresponding category of the maximum value in Y is the sample belonging category. This study will contribute some proposals to visual grading of winter jujube maturity, and the imported SIs parameters will provide technical support for the manufacture of device that suitable for multiple fruits maturity sorting.

A multichannel hyperspectral imaging probe with 30 optic fibers covering the wavelength range of 550～1 650 nm and the light source-detector distances of 1.5～36 mm was recently developed for property and quality assessment of food products. Spatially resolved spectra were acquired using the new developed multichannel probe for 600 “Sun Bright” tomato fruit, which were grouped into six maturity grades (i.e., green, breaker, turning, pink, light red, red), based on their internal color distributions. Partial least squares discriminant analysis (PLSDA) and support vector machine discriminant analysis (SVMDA) models for the 15 spatially resolved spectra were developed and compared to determine the optimal models for classification of tomato maturity. The results showed that for PLSDA models, SR spectra 15 gave the best classification results with the accuracy of 81.3%, while for SVMDA models, SR spectra 10 had the best accuracy of 86.3%. Overall, SVMDA models will provide better performance than PLSDA models for tomato maturity classification. Moreover, spatially resolved spectra with larger source-detector distances could offer better classification results, which suggests that spatially resolved spectra has potential for measuring fruit and vegetables quality.

Synthesis of rare-earth chelate is a key part of homogeneous time-resolved fluorescence immunoassay. To synthesize optimal rare-earth chelate, we select diethyl 2,6-dibromomethyl-3,5-pyridinecarboxylate as raw material and optimally synthesize Li+2,6-{N,N’,N,N’-［bis(2,2’-bipyridine-6,6’-dimethyl)］ bis(aminomethyl)}-pyridine-3,5-diethyl diester, and then the spectral difference of europium cryptate synthesized by the different reactive systems of acetonitrile and methyl alcohol are discussed. Studies show the excitation spectra(the maximum excitation wavelength is 310 nm), emission spectra(the maximum emission wavelength is 616 nm) and quantum yield of europium cryptate synthesized by the different reactive systems are consistent. Fluorescence intensity are linear with the concentration of europium in the range of 10-8～10-5 mol·L-1 (R2=0.993 73, 0.986 65), respectively. But the fluorescence intensity between them (c=2.5×10-5 mol·L-1) are slightly different. Their fluorescence lifetime are 825 and 830 μs, respectively. Therefore, europium cryptate synthesized has big Stoke’s shift, high fluorescence intensity, long fluorescence lifetime and so on. Pyridine-2,2-bipyridine in europium cryptate can protect europium from interference. It is an ideal europium cryptate used for the labeling of biomolecules such as protein, nucleic acid. This study not only expands the synthesis of new rare earth chelate, but also lays the foundation for the establishment of homogeneous time-resolved fluorescence immunoassay.

Basingthe titration to analyze the total boron, total alkalinityand made references to the determination of serum bicarbonate, we have developed a new method by combining UV spectrophotometry and titration to determine CO2-3 and HCO-3 values accurately in boron-containing brine. The effects of spectrophotometric reaction were studied by analyzing the wavelength, the dosage of chromogenic reagent, temperature and pH, choosing phonel red as chromogenic reagent. The further research was studied by analyzing the linearity between the absorbance and the concentration, the detection limitation, the recovery rate and so on. The results showed that the maximum absorbance peak is at 558 nm. There was a good linear relationship in the ranges of 0～10.0 mmol·L-1, correlation coefficient R2=0.999 8. The detection limitation is 2.53×10-3 mmol·L-1. The recoveries ranges from 97.75% to 101.76%. The relative standard devivation (RSD) is in the range of -1.67%~-1.95%. The dosage of chromogenic reagent was 1.0 mL. The room temperature was suitable and pH is 8.4. The proposed method is of high accuracy and precision. This method optimized the determination of CO2-3 and HCO-3 in boron-containing brine. The new method provides a new idea and experimental method for the basic research and practical application of brine, has potential to be applied in fundamental research and process development of brine.

Identifying and monitoring the heavy metal pollution information of crops isthe research focus by hyperspectral remote sensing technology today. The potted corn experiments were set up with different Cu2+ and Pb2+ stress gradients in this research, measuring the spectral data, the content of heavy metals icon and chlorophyll of corn leaves. On the basis of the collected data, the spectra were divided into six spectral characteristic intervals: purple vallley, blue edge, green peak, red valley, red edge and red shoulder, and spectral characteristic intervals were transformed and analyzed by spatial spectrum, which was constructed by first order differential and 2D multiple signal classification (2D-MUSIC) algorithm. The analyzed and processed results show, the spatial spectra of the array signals of the blue edge, green peak and red edge are double peaks under Cu2+ stress. However, the spatial spectra of the array signals of the blue edge, green peak and red edge were single peak under Pb2+ stress. Thus, the heavy metals elements categories of Cu2+ and Pb2+ in polluted corn could be quickly and visually distinguished. Azimuth spectrum peaks of array signal spatial spectra of red valley and red shoulder were gradually decreased under Cu2+ stress, and the correlation coefficients of azimuth spectrum peak values of red valley and red shoulder and the Cu2+ contents in corn leaves reached -0.954 5 and -0.964 8. It was indicated that the effect was ideal when monitoring the level of Cu2+ pollution; azimuth spectrum peaks of array signal spatial spectrum of purple valley were gradually decreased under Pb2+ stress, and the correlation coefficient of azimuth spectrum peak value of purple vallley and the Pb2+ contents in corn leaves reached 0.999 8, it was indicated that the effect was ideal when the level of Pb2+ pollution was monitored. At the same time, the application results of the spatial spectrum were analyzed and compared with the results obtained by some conventional methods such as green-peak height (GH), red edge position (REP), maximum-value of red-edge (MR) and first-derivative area of red-edge (FAR) for monitoring the crop heavy metal pollution information, the spatial spectrum theory was verified to have better effectiveness and superiority in monitoring heavy metal pollution information of the corn leaves.

The rapid estimation of soil moisture content (SMC) is of great significance to precision agriculture in arid areas, and hyperspectral remote sensing technology had been widely used in the estimation of soil moisture content due to its non-destructive, rapid, and high spectral resolution characteristics. Meanwhile, there are many prediction models of soil moisture content, such as BP, SVM, RF and so on, but the prediction model has some shortcomings. Recently, the extreme learning machine(ELM) as a new algorithm began to emerge in the field of soil property prediction. In the present study, a total of 39 soil samples at 0～20 cm depth were collected from delta oasis in Weigan-Kuqain, Xinjiang Province. We brought back to the laboratory to dry it naturally, groundnd and passed through a 2 mm hole scree, and then the sample holders were clear black boxs in 12 cm diameter and 1.8 cm deep, which were filled and leveled at the rim with a spatula. Reflectance of soil samples were measured using ASD Fieldspec 3 Spectrometer in a dark room. We used the following steps to process soil reflectance: First, discrete wavelet transformation (DWT) was used to decompose the original spectral in 8 levels using db4 wavelet basis by MATLAB programming language. In order to select the maximum level of DWT, correlation coefficients between SMC and the spectra of each level was computed. Secondly, On the basis of wavelet transform, CARS (the adaptive variable weighting algorithm), SPA (successive projections algorithm) and CARS-SPA were used to filter the redundant variables, the wavelength variables with better correlation with SMC were screened out. Thirdly, On the basis of the preferred wavelengths, BP neural network, SVM (support vector machine), RF (random forest) and ELM (extreme learning machine) prediction models were employed to build the hyperspectral estimation models of SMC, and the advantages and disadvantages of the model were further analyzed. Statistical parameters of root mean square error of calibration (RMSEC), determination coefficient of calibration (R2c), root mean square error of prediction (RMSEP), determination coefficient of predicting (R2p) and relative prediction deviation (RPD) were selected as comparison criteria. The results showed that: (1) With the increase of the number of decomposed layers, the correlation between soil reflectance and SMC showed a trend of increasing first and then decreasing, and L6 was the most significant band at 0.01 level. In general, the characteristic spectrum of L6 was denoised at the same time, and the spectral detail was preserved to the maximum extent. So the maximum decomposition order of the wavelet was 6 order decomposition; (2) On the basis of L6, the CARS, SPA and CARS-SPA algorithms were used to optimize the variables, and the number of selected wavelength variables were 81, 23 and 12, respectively. The predictive models constructed by three algorithms were better than those of the whole-band model. The prediction model based on the CARS-SPA was the most accurate in the corresponding model. It can be seen that the CARS-SPA coupling algorithm not only simplified the model complexity, but also increased the robustness of the model; (3) Compared with the BP, SVM, RF and ELM, In all the SMC predicting models, there were 6 models with predictive ability, Sort by: L6-CARS-SPA-ELM>L6-CARS-SPA-RF>L6-CARS-ELM>L6-CARS-RF>L6-SPA-ELM>L6-SPA-RF. Results showed that ELM performed much better than BP, SVM and RF in predicting SMC in this study. At the same time, the L6-CARS-SPA-ELM model had the highest accuracy, and the model had RMSEC=0.015 1, R2c=0.916 6, RMSEP=0.014 2, R2p=0.935 4, RPD=2.323 9. It was shown that the combination of wavelet transform and CARS-SPA algorithm made it possible to remove the noise as much as possible and to remove the noise completely when the model was established. At the same time, and ELM model was a new method to predict other soil properties.

The study on spectral characteristics of biological soil crust in the water-wind erosion crisscross region in the Loess Plateau has important scientific value for the identification of biological soil crust based on remote sensing technology at regional scale, also provides important technical support for estimating the effect of biological soil crust on regional soil erosion control. The spectra of higher vegetation as well as the biological soil crust of algae with different coverage and different types of mosses were measured and quantified by Surface Species Spectrometry. The results are as follows, the algal bio-soil crust has similar spectral characteristics with soil in the water-wind erosion crisscross region in the Loess Plateau, and there is no obvious “peak-valley” characteristic in the spectral curve. The reflectivity was reduced by the increasing coverage of the biological soil crust. Compared with the bare area, the spectral reflectance normalized mean of algae biological soil crust deceased 8.64%, 15.80% and 23.09% respectively in the coverage of 10% to 20%, 30% to 40% and 50% to 60% in the visible area. The absorption characteristic at 680 nm (Chlorophyll) became increasingly obvious and the absorption valley at 2 200 nm (secondary mineral) became smaller as the coverage of algae biological soil crust increased. The spectral curve of moss biological soil crust showed the reflection peak of the green band, the absorption valley of the red light band and the high reflection of the near infrared band, which is similar with the vegetation. In the range of 760~930 nm, the slope of moss biological soil crust was 2.5 to 4.5 timed higher than that of vegetation. The study can provide some theoretical basis and technical support for the identification of biological soil crust.

Adsorption resin chromatography obtains wide application in characterizing the distribution of hydrophilic/hydrophobic fractions in natural organic matters. As a basic parameter of chromatography, the critical retention factor has a potential impact on results of adsorption and separation. In this study, water samples from a reservoir were fractionated into hydrophilic substances (HIS), hydrophobic acids (HOA), hydrophobic bases (HOB) and hydrophobic neutrals (HON) under the conditions of various critical retention factors (k′cr=5, 10, 25, 50, 100). The distribution of the hydrophilic/hydrophobic fractions were systematically characterized, with special attention placed to their spectroscopic properties. The results showed that the relative proportions of hydrophilic/hydrophobic fractions depended on the value of k′cr, and the proportion of hydrophobic components and the degree of hydrophobicity increased with the increase of k′cr value. In wavelength range of 250~280 nm, the UV absorbance of HIS increased with increasing k′cr, while the absorbance of hydrophobic fractions performed in the reserved trend. The difference in UV spectra between the hydrophilic and hydrophobic fractions was enlarged with increasing k′cr value. The specific UV absorbance (i. e. UV absorbance per unit concentration) of the hydrophobic fractions was found to be sensitive to the value of k′cr, indicating that the critical retention factor may affect the properties of aromatic functional groups in the obtained fractions. Three dimensional excitation-emission matrix fluorescence spectroscopy was further conducted to characterize the hydrophilic/hydrophobic fractions, with the spectral data analyzed using fluorescence regional integration and fluorescence index techniques. The results revealed that the fluorescence peak appearance (peak location and intensity), fluorescence regional distribution and fluorophore density were related to the value of k′cr, meanwhile the fluorescence indices of BIX, HIXem and Peak T/C were sensitive to the value of k′cr. It is speculated that the critical retention factor may have profound impact on the chemical compositions and transformation behaviors of the resultant hydrophilic/hydrophobic fractions. Therefore, it is suggested that particular attention should be paid to the setting of the critical retention factor and indicating its value clearly when conducting separating and characterizing of the distribution of hydrophilic/hydrophobic fractions.

Study on identification of seed varieties is an important means of ensuring seed quality. The paper uses hyperspectral image technology and fusing image feature to identify different varieties of delinted cottonseeds. Hyperspectral image data (400～1000nm) of 4 types a total of 240 delinted cottonseeds samples were acquired. In addition, the spectral information and 12 morphological characteristics such as length width area, and circularity were extracted. Moreover, 11 effective wave-lengths(EWs) were to be selected by successive projection algorithm(SPA). And then 11 EWs of the calibration set were used as input to build a partial least quares discriminant analysis(PLS-DA), soft independent modeling of class analogy(SIMCA), K-nearest neighbor algorithm(KNN), principal component analysis was combined with linear discriminant analysis (PCA-LDA) and quadratic discriminant analysis (PCA-QDA) were used to build models. The results showed that the total identification rate of the PLS-DA model were 93% for the calibration set and 90% for the prediction set, respectively. When using image information modeling analysis, the overall recognition rate of the model is not high, which showed that the effect of classification is not good when only using morphological characteristics of hyperspectral images. Then, we fused the spectral and morphological information of the feature band as input, and established the data fusion model based on the analysis of PLS-DA, SIMCA, KNN, PCA-LDA and PCA-QDA. It suggested that the data fusion model showed better performance than the individual image model and spectral model, PLS-DA model had the best recognition effect, the overall recognition rate of calibration set and prediction set was 98% and 97% respectively. The experimental results indicated that fusing the spectral and image information of hyperspectral images could effectively improved discrimination accuracy for delinted cottonseeds at the case of a small amount of wavebands.

Crop disease is one of the important factors for yield. The early monitoring of crop diseases mainly rely on traditional methods of judging disease classes of plant protection, with strong subjectivity, low efficiency, delay and other defects, and crop-dust is also carried out to prevent plant diseases in advance. However, this method has the risk of excessive pesticide, which affects the ecological environment of rice growth. In recent years, with the rapid development of information technology, hyperspectral image technology has been applied in agricultural production with huge data, sensitive and reliable . It has become an effective method to detect crop diseases. This paper describes the spectral response mechanism under the plant disease stress, from 5 aspects of food crops, cash crops, vegetable crops, fruits and other crops, and summarizes the progress of hyperspectral image technology in the study of plant diseases in recent 7 years at home and abroad. On this basis, this paper puts forward the deficiencies of the technology in the field and the prospect for the future, also, provide a reference in the crop disease monitoring.

In order to test the performances of different color matching functions, 16 pairs of nearly metamerism color patches based on gray, brown, purple and blue were prepared, and 14 observers with normal color vision were organized to compare the color difference with the psychological method of comparison. The results indicated that the spectral response of the older observers will decrease and the performance of the CIE1931 outperform the CIE1964. In different color regions, the color matching functions have different performances. For the description and assessment of gray, purple and blue colors, even though the viewing fields is larger than 4°, the performance of the CIE1931 still outperforms the CIE1964. The existing CIE2006, which considering the eye-lens and macular pigment optical density variations, have been improved than the CIE1931 and CIE1964.The further work can intensify the macular pigment optical density for the accuracy improvement compared with the visual response.

National Monitoring Station of Soil Fertility as a research platform was used combined with UV-Visible absorption spectroscopy to explore how the following fertilizer application: (1) CK (non-fertilization); (2)NPK (applied chemical nitrogen, phosphorus and potassium); (3) NPKS (chemical nitrogen, phosphorus and potassium combined with straw); (4) 1.5NPKS (1.5 times of chemical nitrogen, phosphorus and potassium combined with straw); (5) NPKM (chemical nitrogen, phosphorus and potassium combined with manure) to influence the DOM content and structure in 0~20 and 20~40 and 40~60 cm soil layers. The results showed that long term application chemical fertilizers had less effects on soil DOM content, but chemical fertilizers combined with straw and organic manure significantly increased soil DOM content by 39.1 and 12.1 mg·kg-1 in topsoil. Compared to CK treatment and NPK treatment, chemical fertilizers combined with manure and straw could decrease C/N in 0~20 and 20~40 cm soil layers, and improved the supply of nitrogen in soil, but the DOM and C/N had not significantly difference between different fertilizations in 40~60 cm soil layer. In 0~20 and 20~40 cm soil layers, compared to CK treatment and NPK treatment, the treatments of NPKM, NPKS and 1.5 NPKS increased conjugated structure and humus of soil DOM . In 40~60 cm soil layer, the increased by different fertilizations were not obvious. Chemical fertilizers combined with straw or manure can increase ultraviolet spectrum absorption values of DOM (SUVA254 and SUVA260 and SUVA280) and α (355) in 0~20 cm soil layer, and decrease Ultraviolet spectrum absorption ratios of soil DOM (A250/A365). It showed that the fragrance, hydrophobicity, molecular weight and CDOM increased. Meanwhile, it was not obvious in 20~40 and 40~60 cm soil layers. A300/A400 in different soil layers was greater than 3.5, and it showed this soil was rich in Fulvic Acid. Long term chemical fertilizers combined with manure and straw can increase DOM content in 0~20 and 20~40 cm soil layers, decrease C/N, and increase soil fertility. Meanwhile, it also can increase the conjugated structure, humus, fragrance, hydrophobicity and molecular weight of DOM in 0~20 cm soil layer. Long term fertilization has less effects on soil DOM content and structure in 40~60 cm soil layer.

In the laser-induced breakdown spectroscopy (LIBS) quantitative analysis technique, the baseline is an important part of the LIBS signal. Due to the fluctuation of laser energy and inhomogeneity of sample surfaces, the phenomenon of plasma emission line drift is obvious. Thus, baseline correction is an essential part during the spectrum data preprocessing. However, the existing algorithms do not have adaptability, thus there usually needs to set some key parameters, such as the suitable fitting function and order. In this paper, baseline correction and spectral signal denoising method are proposed on the basis of the data characteristics, such as the independence and sparsity of the spectral peak as well as the low-pass signal feature of baseline, which forme non-parametric baseline correction model under convex optimization framework. Meanwhile, efficient iterative algorithm is used to ensure the convergence of the results. In this paper, the spectral signal of 23 high alloy steel samples was firstly calibrated, and then the Cr element in the samples of alloy steel was analyzed. Subsequently, 11 analytical lines were selected for quantitative analysis. To verify the effectiveness of the proposed method, we utilized partial least squares (PLS) and support vector machine (SVM) quantitative model for training and prediction respectively. Compared with the traditional methods, the proposed method has a better performance in improving the quantitative analysis accuracy.

Rapid identification of mine water inrush has great significance for mine safety production. The identification method of laser induced fluorescence(LIF) in mine water inrush requires to pretreat and characterizing the spectral curve is complicated. Therefore, a method to quickly identify the type of mine water inrush by using the convolutional neural network(CNN) was proposed. According to the coal mine water distribution characteristics and the most common type of water inrush, we selected three kinds of raw water samples and two kinds of mixed water mixed by the original water as experimental material, in the experiment, we used LIF technology to quickly obtain 200 sets of fluorescence spectrum curves of 5 kinds of water samples. After gray degree transformation, the fluorescence spectrum curves inputed into CNN algorithm,150 groups of spectrum as the training set while the rest 50 groups of spectrum as the test set. In the model test, CNN’s recognition rate was 100%. The experimental results showed that the CNN algorithm can not only save the data processing and feature extraction in the image of recognition of mine water inrush, but also quickly and effectively identify the type of mine water inrush.

The continuous development of nanotechnology requires more powerful nanoparticle characterization techniques. Single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) is a new technique for nanoparticle detection in recent years. It can quickly provide researchers with information on nanoparticle size, size distribution, particle number concentration and element composition, with small interference for samples. In this paper, the factors influencing the detection of gold nanoparticles (AuNPs)by SP-ICP-MS were discussed, which include the setting of parameters of the instrument, such as dwell time, the influence of sample matrix, including salt-containing and carbon-containingmatrix, and the dissolved analytical elements. The detection limit of gold nanoparticles was 23 nm. The recoveries of AuNPs were measured by spiked recovery. The recoveries were 97.7% and 84.4% for Taihu Lake and Dongli Lake, respectively. Finally, some existing problems were discussed in nanoparticle detection by SP-ICP-MS.

For the sake of the quick analysis of sodium in oil sands, near infrared spectroscopic technology was applied combing with Least Absolute Shrinkage and Selection Operator (Lasso) modeling algorithm in order to establish quantitative calibration model. The comparison with the traditional PLS modeling method was conducted for comparative analysis. The results showed that the calibration models of the sodium content established by both methods had almost the same accuracy, but the prediction performance was slightly different. The verification experiment illustrated that the model evaluation indexes of PLS and Lasso algorithms were Rp=0.998 1, RMSEP=0.010 8 and Rp=0.998 6, RMSEP=0.009 5 respectively. The effectiveness of near-infrared spectroscopic analysis to determine the sodium content in oil sands was verified. The modeling precision and applicable areas of the PLS and Lasso algorithms were compared and analyzed.

In this paper, we selected the Wanshan mercury mine soil as the research object, processed and studied by thermal analysis of low temperature plasma, By study of temperature, time, additives and other process parameters on mercury removal rate and treatment after Mercury, we analysed and compared the process on the mercury containing waste residue , exploring its mechanism of action and summarizing the key factors influencing the process exhaust system. The main results were as follows: (1) The main form of mercury in contaminated soil was organic binding state (52.5%). Secondly, the oxide bound state was (32.5%), acid extractable state was (8.13%) and residual state was (6.25%). (2) Under the condition of 500 ℃ and 40 minute, the residual mercury concentration was only 1.44 mg·kg-1. (3) Under the condition of 400 ℃, with the extension of time, the removal rate of total mercury in soil increased gradually, and the pyrolysis process was basically completed within 40 minute. In the 200~1 600 mg·kg-1 interval, the higher the initial oncentration of mercury, the smaller the removal rate of total mercury in soil. (4) The synergistic effect of calcium chloride on the pyrolysis of mercury containing soil was the best, followed by citric acid and sublimation sulfur, and sodium sulfide had a certain inhibitory effect. (5) The pulse voltage was 21.1 kV, and the discharge frequency was 650 Hz, which was the best parameter to match the high voltage pulse power supply with the low temperature plasma reactor. The total mercury removal rate could reach above 89.73%.

Separating a single rare earth element (REE) from the rare-earth concentrate is a continuous process, in which the artificial sampling - ICP laboratory analysis is usually used for process monitoring and control. The results of the test lag behind the actual production and may lead to problems such as the instability of the product quality and so on. Based on the energy dispersive X-ray fluorescence spectrometry, a method to determine the REE distribution in the process of rare earth separation was established. The X-ray fluorescence spectral signal of single rare earth element was obtained by multiple stepwise regression via analysis of typical north rare earth elements (lanthanum, cerium, praseodymium, neodymium). The experimental conditions, such as the filter, tube and tube flow, were optimized according to the relative theoretical deviation, which laid the foundation for online analysis of REE distribution. In this study, the XOR-50 analytical equipment and on-line detection method of rare earth distribution were developed, which could fast reflect the technical condition of rare earth extraction and separation, providing real-time online extraction data and offering accurate and reliable data for process adjustment. The results showed that using 0.2 mm of Al filter, 25 kV of lightpipes excitation voltage, 1 100 μA light tube current test conditions, the relative standard deviation of the REE distribution in the same sample for 11 consecutive times was less than 1%. The results of field analysis were consistent with ICP-AES test results. The detection limit of rare earth elements, such as lanthanum, cerium, praseodymium, neodymium and other light rare earth elements, was detected to be less than 5 μg·mL-1, which completely met the accuracy and reliability requirements of rare earth distribution online monitoring.

XRD-Rietveld full-spectrum fitting method broke through many technical limitations of traditional XRD quantitative analyses and is of great significance in solving the quantitative problem of multi-phase mineral system. Our efforts in this study focused on a comparative study on two granite weathering profiles (A and B profile) in Darongshan area in Yulin, Guangxi. These two profiles were developed adjacent with similar climatic and topographic condition but different parent rock lithology. In order to achieve an accurate and reliable quantitative result, a special fitting strategy was set for the granite weathering samples. Analytical results showed that A and B profile contained similar mineral composition as a whole, mainly including Quartz, K-feldspar, kaolinite, illite and plagioclase. Quantitatively, A profile derived from coarse-grained biotite granite was composed by kaolinite (6.05%~44.67%)+illite (15.85%~49.59%) + quartz (29.72%~46.15% ) + K-feldspar (12.04%~22.85%) + plagioclase (24.33%~32.70%). In contrast, B profile derived from fine-grained biotite granite was composed by kaolinite (3.12%~11.47%) + illite (13.95%~31.94%) + quartz (26.60%~58.05%) + K-feldspar (13.70%~43.47%) + plagioclase (17.95%~23.47%). Both Rwp value (less than 15) and gof value (less than 5) indicated that the calculated spectrum fitted well with the original spectrum, and thus the final quantitative data of minerals was reliable. Also, the analytical results were consistent with geological observations. The geological significance of this study lied in providing quantitative evidence to indicate the weathering process of granite-forming minerals, especially for feldspar group minerals which show an evolution path as feldspar → illite → kaolinite. In addition, based on the significant difference in total clay minerals contents between A and B profile, this study suggested that the granite with coarse-grained texture was more susceptible to suffer intense chemical weathering than those with fine-grained texture under the subtropical climatic environment.

The ash melting temperature of X coal with high ash melting temperature was reduced by adding calcium-magnesium compound flux (WCaO/WMgO=1). In the process of simulated coal gasification, the ash and slag were prepared, and the existence form and evolution process of oxygen, silicon, aluminum, calcium, magnesium at different temperature were analyzed by X-ray photoelectron spectroscopy (XPS). Calcium-magnesium compound flux can reduce ash melting temperature and mainly affect structure change of silicon, aluminum and oxygen. The change of the coordination mode of aluminum and oxygen was shown, namely aluminum-oxide tetrahedrons ［AlO4］ and aluminum-oxide tetrahedrons ［AlO6］ varied with temperature changes. The addition of Ca2+ and Mg2+ can destroy the silica chain, making bridging oxygen silicon change into non bridge oxygen silicon; Bridged oxygen bond fracture was broken and non bridging oxygen bond was formed in oxygen element structure. Combined with the Factsage thermodynamic analysis software, the high temperature phase equilibrium composition of coal ash was analyzed after adding calcium-magnesium compound flux, and the fluxing mechanism of flux was studied from the change of mineral structure. The results showed that Ca2+ and Mg2+ were easy to combine with the non bridging oxygen bonds in the silicon-oxide and aluminum-oxide tetrahedrons and aluminum-oxide octahedrons to produce low melting temperature feldspar minerals and magnesia minerals. Therefore the ash melting temperatures were reduced.

With Na2SiO3, NaOH and Ca(OH)2 preparation of alkali solution, then steel slag was activated using alkali solution. The effects of Na2SiO3 amount, NaOH amount and Ca(OH)2 amount on the mechanical property of the alkali steel slag cementations materials were studied in order to obtain optimal mechanical properties of alkali steel slag cementations materials. The optimal mechanical properties of alkali steel slag cementations materials were characterized by XRD, FTIR and SEM. The results show that When Na2SiO3 amount is 11.25 g, NaOH amount is 4.50 g and Ca(OH)2 amount is 6.75 g, alkali steel slag cementations materials’ the mechanical property is the best. Na2SiO3 has significant effect on 7 d compressive strength of alkali steel slag cementations materials, NaOH has significant effect on 3 d compressive strength of alkali steel slag cementations materials, Ca(OH)2 has significant effect on 28 d compressive strength of alkali steel slag cementations materials. The addition of alkali solution, such as Na2SiO3, NaOH and Ca(OH)2 causes steel slag to form stable C-S-H gel and zeolite.

Support vector machine (SVM), a typical classification method, has been widely used in stellar spectra classification. It performs well in practice, while it encounters the multi-class classification challenge. In order to solve the problem above, multi-class support vector machine (MCSVM) was proposed in this paper based on the in-depth analysis of SVM. Meanwhile, the stellar spectra classification model based on multi-class support vector machine was constructed. The advantage of the proposed method is that the samples’ class can be determined by a classification process. Comparative experiments with the existed multi-class classification method on the SDSS DR8 datasets verify the effectiveness of the proposed method.

At present, more than 7.6 million celestial spectra has been obtained by the LAMOST spectrum sky surveys, and the processing of low SNR spectra has been regarded as a difficulty in this domain. In this paper, a new method was proposed to deal with repeated observation spectra. The process of the method was: for every group of repetitive observation spectra, selecting that whose difference of red shift was within a certain range, and then an optimal stack algorithm based on SNR weighting was run to increase the SNR. The results of the processing of all repetitive observation spectra in LAMOST DR4 showed that this method was very effective for increasing the SNR for low SNR repetitive observation spectra. This method made the SNR of the 7 571 sets of stellar spectra reach the standard of parameter measurement; The SNR of the 3 357 quasar and Galaxy spectra improved at an average improvement rate of 56.38%; And 43 021 binary candidate candidates were obtained.

In order to obtain the complete polarized two-dimensional image information and its spectrum information at the same time, a new polarized spectrum imaging system based on orthogonal modulation is designed. The system consists of optical antenna, phase modulator, Wollaston prism, Savart polarizer, analyzer and imaging module. The original optical signal is decomposed into two beams of mutually orthogonal polarized light, and they are respectively imaged in the upper and lower portions of the focal plane of the CCD, so that it forms two full polarization images. The superposition of the two sets of images can cancel the data of the interference fringes to obtain pure image information of the target. The subtraction of the two sets of images can cancel the target gray scale images to obtain the pure interference fringes of the target. The light intensity distribution function and spectrum variation form were obtained by theoretical calculation. High contrast targets with background plates were used in the experiment, real-time acquisition of fully polarized images was completed in a stable light source environment. The distortion of the interference image is improved by phase correction and apodization, through high-pass filtering and threshold filtering, the influence of background noise in the image is suppressed, so that the extraction of the target image and the restoration of the polarization spectrum are realized. It has the characteristics of high stability, adjustable spectrum resolution, high signal-to-noise ratio and strong ability to identify. It is important to extract the target image, spectrum and polarization information in complex background.

Based on the resonance principle of waveguide grating and Goos-Hnchen displacement theory, a refractive index sensing model of surface coated waveguide grating is proposed, and the resonance spectral characteristics are analyzed. In addition, the resonance spectral characteristics are optimized by coating the polymer film upper the grating, the porous silicon is used as the sensing unit, the samples detected and electromagnetic wave will contact fully and the sensitivity can be improved effectively. According to the phase condition of the waveguide grating resonance, the relationship between the resonance wavelength and the refractive index of samples detected is established, and the concentrations of samples can be detected by detecting the shift of the resonance wavelength. The results show that the surface coated waveguide grating sensing structure has the sensing characteristics of high quality factor and high sensitivity, the quality factor of the surface coated sensing structure is 1 488, and the detection limit of refractive index is 5×10－4 RIU. Moreover, the sensing characteristics are analyzed by detecting different concentrations of glucose solution, the results show that there is a good liner relationship between resonance wavelength and the concentrations of the glucose solution, and the sensitivity of the glucose solution is 1.12 nm/1%, the validity of the sensing structure is proved. The surface coated waveguide grating sensing structure can be used to detect the samples with low concentrations and provide theoretical guidance for the further study of the optical refractive index sensors.