The solution of ion mobility’s nonlinear function coefficients α2 and α4 is the basis for achieving substance identification of High Field Asymmetric waveform Ion Mobility Spectrometry(FAIMS).Currently,nonlinear function coefficients α2 and α4 lack priors,meanwhile,existed solving results about α2 and α4 are deficient in error evaluation standard.In this article,acetone,isopropanol and 1,2-dichlorobenzene were detected under different dispersion voltage by homemade FAIMS.In general,the spectrum peak of same sample at different dispersion voltage value is unique.Different dispersion voltage and corresponding compensation voltage value determines the value of α2 and α4.According to sample spectra at different dispersion voltage value,groups of spectral characteristics were obtained.Affirmatory number of data which were selected from multiple sets of compensation voltage value and dispersion voltage value,so that they were utilized to solved out lots of α2 and α4.Lots of factor have an effect on the accuracy of the solving results of α2 and α4,for instance,value of compensation voltage and dispersion voltage,style of fetching points of dispersion voltage,and so on.Comparing to other factors,style and amount of dispersion voltage is likely to control.By data analyzing huge amounts of α2 and α4 data,this paper explored their characteristic of distribution and correlation about them,research influence of number and method to fetch dispersion voltage detected points for error of solving results.After fitting frequency of α2 and α4,it was found that they conform to normal distribution,goodness of fitting exceed 0.96,thus standard deviation of their distribution are able to evaluate error of solving results.In addition,a strong correlation exists between them,relevance of sample is －0.977,－0.968,－0.992 respectively.With increasing of computing selected points,the corresponding error of solving results decrease.By comparing the standard deviation of method to fetch dispersion voltage detected points,found that detecting frequency in case of detecting maximum and the 70% of maximum of dispersion voltage value is lower at approximately same standard deviation,solving effect was optimized in unique fetching points style.Based on the premise of ensuring the accuracy of solving results of α2 and α4,it is obvious that reducing the frequency of detections for FAIMS effectively.It created favorable conditions for rapid field detection and precise spectral analysis.

Laser-induced breakdown spectroscopy(LIBS),a new kind of atomic spectrum analysis technology,has attracted much attention of the researchers due to its characteristics of real-time,simultaneous multi-element analysis,and no sample preparation.However,the poor analytical sensitivity has been an important factor that restricts the development of this technology.LIBS based on resonance excitation combines atomic fluorescence spectroscopy and laser-induced breakdown spectroscopy and selectively excites the target elements.In this way,the analytical sensitivity of LIBS can be improved substantially and its application for trace elements detection is greatly expanded.In this paper,the research development of LIBS based on resonance excitation is summarized.The generation of atomic fluorescence spectrum in laser-induced plasma,the typical classification and the basic principle of LIBS based on resonance excitation are introduced.The influence of ablation laser energy,resonant laser energy and wavelength,delay between the ablation laser and the resonant laser,and the gate width on spectral enhancement are analyzed in detail.The application status and deficiencies of LIBS based on resonance excitation in the fields of metallurgy,environmental monitoring and isotope detection are elaborated.Future prospects of LIBS based on resonance excitation are also described.

Single scattering properties for spherical and hexagonal ice crystal models with different size parameters and wavelengths were employed to calculate satellite observed radiation and downward flux in ground surface using RSTAR radiative transfer model.Results indicated that simulated satellite observed radiation and ground surface downward radiant flux from different shapes of ice crystal models were different.The difference in the spectral radiation fluxes between 0.4 and 1.0 μm was largest,and particle shapes affected the downward radiant flux significantly.It was verified that the proper selection of the effective ice crystal model is not only important for retrieval of the microphysical and optical parameters of the cirrus cloud,but also important for obtaining the radiant flux on the earth’s surface correctly.These results are important for retrieving cloud microphysical parameters and simulation of the ground surface downward radiant flux.

Colloidal PbSe QDs were prepared with the particle size of 3.6,5.1 and 6.0 nm,and the temperature-dependent optical properties of colloidal PbSe QDs were investigated.At the room temperature,the experiment showed that there is red shift with increasing temperature;photoluminescence spectra of large size colloidal PbSe QDs is blue shifted with increasing temperature.Proposed a temperature detection method of integrated circuit was proposed based on photoluminescence spectra of colloidal PbSe QDs.The method for temperature detection includes colloidal PbSe quantum dots deposited on the surface of the printed circuit board,colloidal PbSe quantum dots of the surface are excited by the laser and infrared spectrometer receives photoluminescence spectra.Image acquisition system used for micron scale areas of temperature detection collects a tiny and specific areas imaging in the surface of chip.Experiments showed that the measurement accuracy is ±3 ℃ and the relative error is less than 5％.

The detection limit of antibody content has reached level of nanograms per milliliter due to high sensitivity and extremely narrow band of photonic crystal(PC) filter.The PC filter based on guided-mode resonance(GMR) effect can also be applied to detecting the molecular interactions.As the transducing element,one-dimensional PC filters transform biological information to photoelectric signal on optical spectrum analyzer(OSA).The main sensing performance is the change of peak-wavelength of PC filter.The sensing system using PC filter is restricted to the system stability which determines the effectiveness of detecting data.So in this paper,a detecting system we designed is briefly addressed.The morphology and the spectrum of PC filter we fabricated are tested.Considering the coupling light loss and integration of the system,noise signal in spectrum is going to affect the detecting results.To monitor the influence,realization of real-time monitoring the changes of the peak wavelength of PC filter is mainly illustrated.The monitoring is realized by transferring detecting data to computer in time and the results can represent the stability of the system.The program is compiled by Lab VIEW.In our experiment,the shift of 0.25 nm of the peak wavelength caused by vibration of platform or unsteadiness of light source is within the sensitivity of the PC filter obtained by simulation,so we proposed this system we mentioned can be used in sensing most kind of bulk reagents.

The photoacoustic spectrum of glucose,sucrose and honey solutions in the visible range are measured by using the single-light photoacoustic spectrometer,and are compared with the spectra from spectrophotometry method.The spectral characteristics of the above solutions show that the spectral background intensity and spectral profile have some differences for different kinds of solutions.The spectra of the three kinds of solutions all have strong peak value at 485 and 655 nm,but the intensity ratios between the two peaks are different.Besides,there are characteristic peak at 475,576 and 630 nm for glucose,and the sucrose has apparent characteristic peak at 632 nm,these characteristic peaks can be used for detecting whether the natural honey has been added glucose or sucrose.By comparing two kinds of spectrum of the same solution,the intensity of photoacoustic spectrum is more responsive to the wavelength,indicating photoacoustic spectrometry has a higher sensitivity in the test of material composition.

Terahertz wave with modulation spectrum is valuable in many fields.Terahertz spectrum has been modulated with a pure-phase liquid crystal spatial light modulator by shaping the femtosecond laser beam profile.In the experiment,terahertz wave is generated by femtosecond laser pulses in mode of Optical Rectification and then its signals are detected by a terahertz time-domain spectroscopy system.Phase maps obtained with the GS algorithm are loaded to get the shaped beam profile.Therefore,Terahertz spectrum has been successfully modulated by changing the detection range and beam profile parameters.Simultaneously,the simulations have been performed with the Fresnel diffraction,and they agree with the experimental results well.The results show that the modulation of the THz spectrum with this method is feasible.

In the present paper,support vector machine(SVM) based on convex combination kernel function will be used for classification of THz pulse transmission spectra.Wavelet transform is used in data pre-processing.Peaks and valleys are regarded as location features of THz pulse transmission spectra,which are injected into maximum interval features of term frequency-inverse document frequency(TF-IDF).We can conclude weight of each sampling point from the information theory.The weight represents the possibility that sampling point becomes feature.According to the situation that different terahertz-transmission spectra are lack of obvious features,we composed a SVM classification model based on convex combination kernel function.Evaluation function should be used as an evaluation method for obtaining the parameters of optimal convex combination to achieve a better accuracy.When the optimal parameter of kenal founction was determined,we should compose the model for process of classification and prediction.Compared with the single kernel function,the method can be combined with transmission spectroscopic features with classification model iteratively.Thanks to the dimensional mapping process,outstanding margin of features can be gained for the samples of different terahertz transmission spectrum.We carried out experiments using different samples The results demonstrated that the new approach is on par or superior in terms of accuracy and much better in feature fusion than SVM with single kernel function.

In the present work,computer simulation was performed on a model chemical system where two solutes(denoted as P and Q,respectively) are dissolved in the same solution.Under intermolecular interaction between P and Q,part of P undergoes subtle structural variation and converts into U while part of Q converts into V.The strength of intermolecular interaction can be characterized by the corresponding equilibrium constant K.Our preliminary studies indicate that the S/N ratio of cross peak increases considerably as n increases.Moreover,the S/N ratio of the cross peak from the asynchronous spectra can be improved significantly when the suitable concentrations of P and Q are adopted.This work is helpful for a selection of suitable concentration sequence to maximize S/N ratio of cross peaks in the 2D asynchronous spectra generated by using the DAOSD approach proposed in our previous study so that weak intermolecular interaction can be probed.

The Classical Least Square regression(CLS) is one of the most popular regression methods in FTIR quantitative estimation.However,CLS is the best unbiased estimator only under the assumption that error(noise) in the spectrum has equal variance,which usually is not the case in FTIR.This paper proposed a noise calibration method for FTIR spectrum analysis.Based on measured variance of noise in the FTIR spectrum by computer,the Weighted Least Square regression(WLS) method is used in quantitative estimation.The experiment results showed that the WLS performs much better than CLS in quantitative estimation of VOCs pollution.

Nowadays,the wastewater quantity discharged yearly from tannery industry is around 0.2 billion t in China.The contaminants of tannery wastewater include macromolecular organic matters,such as grease,fur scraps and collagen,and the alkaline wastewater appears to be of high content of salt and COD.The quality of tannery wastewater is monitored strictly among all kinds of industry wastewater.In the treatment process of tannery wastewater,the quality of inlet and outlet water is generally analyzed.In fact,the transformation behavior of contaminants should be additionally checked to optimize the treatment conditions.Dissolved organic matter(DOM) is commonly existed in water-bodies and helpful to understand the physicochemical characteristics,while the related work should be further studied on tannery wastewater.The approaches of elemental analysis,thermal gravimetric analysis(TG),Fourier infrared spectroscopy(FTIR) and 13C nuclear magnetic resonance(13C NMR) were used to reveal the characteristics of DOM in the treatment process of tannery wastewater.The results showed:the carbon content of DOM samples increased gradually,atomic ratios of H/C increased firstly and then decreased,indicating the organic matters were decomposed into chain structures firstly,finally forming the component hard to degraded.The pyrolysis process of DOM mainly proceeded in the regions of 110～530 ℃(aliphatic compound,protein,etc.) and 530～800 ℃(aromatic ring,single bond of C—C,etc.).The functional groups of DOM included —OH,—NH2,CO and so on,and the aromatic substances were detected,shown from FTIR figures,in the later period of the reaction,caused by the metabolism effect of micro-organism.The content of alkoxy-C increased to the maximum in the second biochemical pond,and the minimum content of aromatic-C appeared in the second biochemical pond,suggesting the transformation behavior of carbon functional groups.The investigation on DOM in tannery wastewater is significant to understand the purification mechanism of contaminants in tannery wastewater.

A study was carried out to retrieve optical thickness and cloud top height of cirrus clouds from the Atmospheric Infrared Sounder(AIRS) high spectral resolution data in 1 070~1 135 cm-1 IR band using a Combined Atmospheric Radiative Transfer model(CART) by brightness temperature difference between model simulation and AIRS observation.The research is based on AIRS L1B high spectral infrared observation data combined with Moderate Resolution Imaging Spectroradiometer(MODIS) cloud product data.Brightness temperature spectra based on the retrieved cirrus optical thickness and cloud top height were simulated and compared with brightness temperature spectra of AIRS observation in the 650~1 150 cm-1 band.The cirrus optical thickness and cloud top height retrieved were compared with brightness temperature of AIRS for channel 760(900.56 cm-1,11.1 μm) and cirrus reflectance of MODIS cloud product.And cloud top height retrieved was compared with cloud top height from MODIS.Results show that the brightness temperature spectra simulated were basically consistent with AIRS observation under the condition of retrieval in the 650~1 150 cm-1 band.It means that CART can be used to simulate AIRS brightness temperature spectra.The retrieved cirrus parameters are consistent with brightness temperature of AIRS for channel 11.1 μm with low brightness temperature corresponding to large cirrus optical thickness and high cloud top height.And the retrieved cirrus parameters are consistent with cirrus reflectance of MODIS cloud product with high cirrus reflectance corresponding to large cirrus optical thickness and high cloud top height.Correlation coefficient of brightness temperature between retrieved cloud top height and MODIS cloud top height was relatively high.They are mostly located in the range of 8.5~11.5 km,and their probability distribution trend is approximately identical.CART model is feasible to retrieve cirrus properties,and the retrieval is reliable.

In this study,effect of mineralizer on the structure and spectraproperties of calcium aluminates formation was extensively studied.Medium or low-grade bauxite and calcium carbonate were used as raw material and mineralizer CaF2 as additive.Calcium aluminates can be obtained after mixing fully,calcination and grinding.The prepared calcium aluminates can be directly used for the production of polyaluminiumchloride(PAC),polymeric aluminum sulfate,sodium aluminate and some other water treatment agents.The calcium aluminates preparation technology was optimized by investigating the mass ratio of raw materials(bauxiteand calcium carbonate) and mineralizer CaF2 dosage.The structure and spectra properties of bauxite and calcium aluminates were characterized by Fourier transform infrared(FTIR) spectroscopy analysis and the mineralization mechanism of the mineralizer was studied.FTIR spectra indicated that the addition of mineralizer promoted the decomposition and transformation of the diaspore,gibbsite and kaolinite,the decomposition of calcium carbonate,and more adequately reaction between bauxite and calcium carbonate.In addition,not only Ca in calcium carbonate and Si in bauxite were more readily reacted,but also Si—O,Si—O—Al and Al—Si bonds in the bauxite were more fractured which contributed to the release of Al in bauxite,and therefore,the dissolution rate of Al2O3 could be improved.The dissolution rate of Al2O3 can be promoted effectively when the mineralizer CaF2 was added in a mass ratio amount of 3%.And the mineralizer CaF2 cannot be fully functioned when its dosage was in a mass percent of 1.5%.Low-grade bauxite was easier to sinter for the preparation of calcium aluminates comparing with the high-grade one.The optimum material ratio for the preparation of calcium aluminates calcium at 1 250 ℃ was:the mass ratio between bauxite and calcium carbonate of 1∶0.6 and mineralizer CaF2 mass ratio percent of 3%.

To establish a phenylketonuria screening model by FTIR/ATR spectroscopy,and to compare the effects of different pretreatment methods,such as baseline correction,smoothing,derivation,Fourier deconvolution,on the model quality.A consensus partial least squares regression method(cPLS) was used to build the quantitative model of phenylalanine in dried blood spots.The effects of different pretreatment methods on the model performance were investigated,using the correlation coefficient(r),root mean square error of prediction(RMSEP),mean relative error(MRE) and predictive accuracy(Acc).The nine-point smoothing coupled with the first differential was found to perform the best.Compared with the model by the original spectra,its r,RMSEP,MRE and Acc were improved from 0.822 7,115.8,0.395 and 94.6 to 0.889 9,102.2,0.286 and 100,respectively.With the advantages of fast speed,easy process,no reagents consumption and environmental protection,the present method is expected to become a simple and green technology for rapidly screening the neonatal phenylketonuria in a large population.

Phenol is an important chemical engineering material and ubiquitous in industry wastewater,its existence has become a thorny issue in many developed and developing country.More and more stringent standards for effluent all over the world with human realizing the toxicity of phenol have been announced.Many advanced biological methods are applied to industrial wastewater treatment with low cost,high efficiency and no secondary pollution,but the screening of function microorganisms is certain cumbersome process.In our study a rapid procedure devised for screening bacteria on solid medium can degrade phenol coupled with attenuated total reflection fourier transform infrared(ATR-FTIR) which is a detection method has the characteristics of efficient,fast,high fingerprint were used.Principal component analysis(PCA) is a method in common use to extract fingerprint peaks effectively,it couples with partial least squares(PLS) statistical method could establish a credible model.The model we created using PCA-PLS can reach 99.5% of coefficient determination and validation data get 99.4%,which shows the promising fitness and forecasting of the model.The high fitting model is used for predicting the concentration of phenol at solid medium where the bacteria were grown.The highly consistent result of two screening methods,solid cultural with ATR-FTIR detected and traditional liquid cultural detected by GC methods,suggests the former can rapid isolate the bacteria which can degrade substrates as well as traditional cumbersome liquid cultural method.Many hazardous substrates widely existed in industry wastewater,most of them has specialize fingerprint peaks detected by ATR-FTIR,thereby this detected method could be used as a rapid detection for isolation of functional microorganisms those can degrade many other toxic substrates.

To address the characteristic of uneven surface temperature of hollow brick wall,the present research adopts soft wares of both ThermaCAM P20 and ThermaCAM Reporter to test the application of infrared thermal image technique in measuring surface temperature of hollow brick wall,and further analyzes the thermal characteristics of hollow brick wall,and building material’s impact on surface temperature distribution including hollow brick,masonry mortar,and so on.The research selects the construction site of a three-story-high residential,carries out the heat transfer experiment,and further examines the exterior wall constructed by 3 different hollow bricks including sintering shale hollow brick,masonry mortar and brick masonry.Infrared thermal image maps are collected,including 3 kinds of sintering shale hollow brick walls under indoor heating in winter;and temperature data of wall surface,and uniformity and frequency distribution are also collected for comparative analysis between 2 hollow bricks and 2 kinds of mortar masonry.The results show that improving heat preservation of hollow brick and masonry mortar can effectively improve inner wall surface temperature and indoor thermal environment;non-uniformity of surface temperature decreases from 0.6 to 0.4 ℃,and surface temperature frequency distribution changes from the asymmetric distribution into a normal distribution under the condition that energy-saving sintering shale hollow brick wall is constructed by thermal mortar replacing cement mortar masonry;frequency of average temperature increases as uniformity of surface temperature increases.This research provides a certain basis for promotion and optimization of hollow brick wall's thermal function.

The whole spectrum usually contains a lot of redundant information in the near-infrared spectroscopy model,the presence of redundant information will increase the model resolution time and increase the difficulty of parsing model,Therefore,how to select the characteristic wavelength quickly and effectly is very crucial.In this paper,we combined the algorithm based on SPA(successive projections algorithm ) with IPLS(interval partial least squares ) to selec the characteristic wavelength in the fermentation of wheat straw microbial biomass,A total of 85 samples prepared by measuring microbial biomass using glucosamine method,68 samples are chosen as calibration set and 17 samples are chosen as verification set.First,the whole spectral region 520 points are segmented modeling according to the interval wavelength point size 10,20,30,40 and 4 450～4 925 cm-1,9 194～9 993 cm-1 two-band range are selected as the characteristic wavelength band,then pick out the new feature wavelength points by Successive Projections Algorithm band and Genetic Algorithm(GA),comprehensive analysis and comparison the result of model.The experimental results show that the using of IPLS-SPA algorithm to select the combination band 4 450～4 925 cm-1 & 9 194～9 993 cm-1 has the best modeling effect,compared with the modeling of whole spectrum,the wavelength points decrease from 520 to 10,the correction coefficient of determination R2 rised from 0.884 9 to 0.945 28,root mean square error(RMSE) dropped from 11.104 9 to 8.203 3,although the genetic algorithm model achieved the better accuracy,but the results are instable and have a strong randomness ,while IPLS combined SPA method can select characteristic wavelength information stability and accurately,which can improve the model calculation speed and reduce the fitting difficulty of the model,it can be used as a new reference method for band selection.The results show that using near infrared spectroscopy method for straw biomass rapid detection is feasible.

The feasibility of utilizing near infrared spectroscopy for estimating frozen and thawed white croaker surimi with different grades was presented in the research.First-derivative and standard normal variable transformation were used as pretreatment method,then principal component analysis was carried out on the processed datas.Establish grade estimation model on white croaker surimi with different grades by principal component analysis-mahalanobis distance pattern recognition method.Seven kinds of physicochemical indexes(moisture,protein,crude fat,salt-soluble protein,gel strength,water-holding ability and whiteness) of white croaker surimi with different grades were determinated.We came to the following conclusions.Firstly,white croaker surimi with three grade could be distinguished effectively by principal component analysis.Secondly,the model of grade estimation established by principal component analysis-mahalanobis distance pattern recognition method had better performance on frozen white croaker surimi than thawed ones,the former’s comprehensive accuracy was 96.3% with the latter’s is 83.3%.Thirdly,the physicochemical indexes of white croaker surimi with different grades had some distinctions.The research indicated that near infrared spectroscopy could estimate the grade of white croaker surimi rapidly and nondestructively.

Clubroot,caused by Plasmodiophora brassicae,is considered the most devastating soilborne disease in Brassica crops.It has emerged as a serious disease threatening the cruciferous crop production industry in China.Nowadays,the detection techniques for P.brassicae are laborious,time-consuming and low sensitivity.Rapid and effective detection methods are needed.The objective of this study is to develop a Fourier transform infrared spectrometer(FTIR) technique for detection of P.brassicae effectively and accurately.FTIR and Real-time PCR techniques were applied in quantitative detection of P.brassicae.Chinese cabbages were inoculated with P.brassicae.By analyzing the FTIR spectra of P.brassicae,infected clubroots and healthy roots,three specific bands 1 105,1 145 and 1 228 cm-1 were selected.According to the correlation between the peak areas at these sensitive bands and Real-time PCR Ct value,quantitative evaluation model of P.brassicae was established based on FTIR y=34.17+12.24x1－9.81x2－6.05x3,r=0.98(p<0.05).To validate accuracy of the model,10 clubroot samples were selected randomly from field,and detected by FTIR spectrum model,the results showed that the average error is 1.60%.This demonstrated that the FTIR technology is an available one for the quantitative detection of P.brassicae in clubroot,and it provides a new method for quantitative and quickly detection of Chinese cabbage clubroot.

Visible near infrared spectra technology was adopted to detect soil total nitrogen content.394 soil samples were collected from Wencheng,Zhejiang province to be used for calibration model(n=263) and independent prediction set(n=131).Raw spectra and wavelength-reduced spectra with five different pretreatment methods(SG smoothing,SNV,MSC,1st-D and 2nd-D) were compared to determine the optimal wavelength range and pretreatment method for analysis.The results with 5 different pretreatment methods were not improved compared to that both of full spectra PLS model and wavelength reduction spectra model.Spectral variable selection is an important strategy in spectrum modeling analysis,because it tends to parsimonious data representation and can lead to multivariate models with better performance.In order to simply calibration models,the wavelength variables selected by two different variable selection methods(i.e.regression coefficient analysis(RCA) and successive projections algorithm(SPA) were proposed to be the inputs of calibration methods of PLS,MLR and LS-SVM models separately.These calibration models were also compared to select the best model to predict soil TN.In total,9 different models were built and the best results indicated that PLS,MLR and LS-SVM obtained the highest precision with determination coefficient of prediction R2pre=0.81,RMSEP=0.0031 and RPD=2.26 based on wavelength variables selected by RCA(0.0002) and SPA as inputs of models.SPA-MLR model and other three models based on 7 sensitive variables selected by RC using 0.0002 regression coefficient threshold value obtained the best result with R2pre,RMSEP and RPD as 0.81,0.0031 and 2.26.This prediction accuracy is classied to be very good.For all the models,it could be concluded that RCA and SPA could be very useful ways to selected sensitive wavelengths,and the selected wavelengths were effective to estimate soil TN.It is recommended to adopt SPA variable selection or RCA variable selection method with both linear and nonlinear calibration models for measurement of the soil TN using Vis-NIR spectroscopy technology,and wavelengths selection could be very useful to reduce collinearity and redundancies of spectra.

Wood electromagnetic shielding material,which was made by treating wood with electroless plating,not only keep the superior characteristics of wood,but also improve the conductivity,thermal conductivity and electromagnetic shielding properties of wood.The emergence of this material opens the way to the value-added exploitation of wood and widens the processing and application field for the electromagnetic shielding material.In order to explore the feasibility of using NIR technology to investigate the properties of wood electromagnetic shielding material,this study analysis the samples before and after copper plated process by the NIR spectroscopy coupled with principal component analysis(PCA).The results showed that(1) there exist significant differences between samples before and after copper plated process both on the spectral shape and absorption,and the great differences can also be seen in the samples with different treat time,especially for the samples with 5 min treat time;(2) after PCA analysis,six clusters from the samples before and after copper plated process were separately distributed in the score plot,and the properties of untreated wood and sensitized wood were similar,and the properties of samples for 25 and 40 min treat time were also similar in order that these samples were close to each other,all of which might suggest that the NIR spectroscopy reflected major feature information about material treatment;(3) After comparing the PCA performance between NIR and visible spectral region,it could be found that the classification performance of samples before and after copper plated process based on the NIR region were better than that based on the visible region,and the information of color on the surface of samples were preferably reflected in the visible region,which could indicate that there are more information about samples’ surface characters using the visible spectroscopy coupled with NIR spectroscopy and it is feasible to use visible-NIR technology to investigate the surface characteristics of natural polymers treated with electroless copper plating.

Urea family plays significant role in the bio-science area.Because of the unique frame,they can form Hydrogen bond with water as well as other substance.Hydrogen bonds are normal weak interactions in the system of bio-molecules.A Raman spectrum is the most powerful method to obscure the Hydrogen bond interaction between molecules.Initially,we measure the Raman spectra of DMU crystal,and then use density function theory with a B3LYP/6-311G** basis set to optimize the geometry structure and calculate the vibrational frequency of gas phase DMU,which assigns the Raman pecks.Then,measure the solvent.When dissolving DMU in water,the interaction between DMU-DMU will replaced by the interaction between water-DMU.The orbital hybridization of nitrogen atoms changes from the solid-state the sp2 orbital hybridization to sp3.So,the frame of this molecule goes from in-planet to out of plant during this process.

The SiO2 shell with the thickness of 4 nm was attached onto high surface enhanced Raman spectroscopy(SERS) active Au core nanoparticles to obtain Au@SiO2 core shell nanoparticles by the hydrolysis of sodium silicate solution with the boiling water bath.The inert shell of SiO2 isolated the direct interaction of Au nanoparticles and probe molecules.The stable,compact and uniform monolayer nanoparticles film was self assembled at water/oil interface,and one to six monolayers film was transferred to Si wafer as SERS substrates through layer by layer technique.The relationship between the SERS activities and layers of the monolayer nanoparticles film on Si surface was investigated.The SERS mapping was developed to determine the layers of the Au@SiO2 film.The coupling effect among the Au@SiO2 films was explored by changing the adsorption location of the probe on the multilayer films.The result revealed that the monolayer film was a favourable candidate with high-quality performances for the SERS application.The SERS signal was distributed on the surface with high uniformity at the same monolayer film,and it was enhanced in the intensity with the increase in film layers.It reached the maximun intensity as the film was over five layers.It indicated that the SERS signal was contributed mainly by the first five monolayers.The probe molecules were immobilized onto the first monolayer nanoparticles film,and the SERS signal from the probe approached to the maximum as the second monolayer covered the probe modified first nanoparticles film.It was dominated by the coupling effect(“hot spots”) of the adjacent layers.The SERS signal decreased in intensity when the third layer was transferred onto the second layer,and it disappeared after the fouth layer was covered,mainly duo to the shield of the nanoparticles film to the incident laser and Raman signal.The preliminary results provided guidance for fabricating optimal SERS substrates.

Overglaze decoration porcelain is an important category of ancient Chinese ceramics,which has significant artistic value and scientific value.Nondestructive analysis methods such as Raman spectroscopy and EDXRF were used to analyze the overglaze decorations on the Jingdezhen ceramic samples of Yuan,Ming and Qing Dynasty.The recipe and color mechanism of the overglaze pigments were discussed according to the chemical composition and phase composition analysis.The study found that dark red overglaze decorations of ancient Honglvcai,Wucai and famille rose in Jingdezhen are colored by hematite,yellow color is lead tin yellow,carmine decoration is colored by gold less than 0.1% in concentration,and green decorations are colored by bivalent copper ion.The result also indicates that the effective combination of Raman spectroscopy and EDXRF can play an important role in the deep research on ceramic artifacts,especially for the overglaze decoration pigments which are interveined each other.

The projection algorithm used in mixture analysis to determine whether there is unknown disturbance existing in grey system can not accurately identify different samples and similar samples at the same time when it is used in the identification of drugs,because of the insufficient criteria.In the present study,one of its criteria for whether the size of measurement error of testing sample is at a limited level is improved for whether the size and distribution of measurement error is equal and similar between testing sample and standard sample.By testing 6 kinds of normal drugs(including BAYER Aspirin Enteric-coated Tablets,TYLENOL Acetaminophen Sustained Release Tablets,BAYER Compound Paracetamol Tablets(Ⅱ),HUAZHONG Compound Vitamin C,HUAZHONG Vitamin B and MADINGLIN Demperidone Tablets) and 3 kinds of similar drugs of aspirin(including BAYER Aspirin Enteric-coated Tablets,Shanghai SINE Aspirin Enteric-coated Tablets and Bamyl Aspirin Effervescent Tablets),it was found that the un-improved projection algorithm directly used in discrimination of drugs shows poor performance with many problems existing,however,the improved projection algorithm can discriminate different drugs and similar drugs with accuracy up to 100%.The improved projection algorithm can be a universal,accurate and reliable automated pharmaceutical identification algorithm and can provide a reference for the study on identification of substance.

The magnetic Fe3O4/Ag composite materials were synthesized by reducing AgNO3 with sodium citrate in the presence of Fe3O4 which were prepared by co-precipitation firstly.The enrichment and extraction of ethoprophos assembled on Fe3O4/Ag were achieved with the applied magnetic field.The different concentrations of ethoprophos adsorbed on Fe3O4/Ag were analyzed by SERS and it was showed that the trace analysis of ethoprophos had been established,while the enhancement factor of probe molecules on Fe3O4/Ag was 1.48×105.The structure and morphology of Fe3O4/Ag were characterized by UV-Vis,EDX and TEM.Compared with Ag,the UV-Vis absorption peak of Fe3O4/Ag shifted from 417 to 369 nm,and the UV-Vis of Fe3O4 almost had no characteristic absorption peak in this region.At the same time,it was showed that the surface properties of Fe3O4/Ag changed with Raman enhancement effect during the aggregation process of Ag around the surface of Fe3O4.Further EDX images of micro area element analysis suggested that the chemical composition of products were Ag,Fe and O while the Cu peak was from the copper mesh.In addition,TEM images indicated that the average particle size of Fe3O4 was between 30 and 60 nm with shape tended to be spherical.And the silver nanoparticles were attached to the Fe3O4 particles and agglomeration occured.Density functional theory calculations which can be applied to qualitative judgment of molecule was carried out to obtain the molecular optimization structure and theoretical Raman spectra.It was found that the stabilized SERS signals were detected under the saturated adsorption equilibrium after 15 min.Finally,Raman response of ethoprophos was achieved with lower than 2×10-8 mol·L-1,indicatint that the established method had reached the requirements of ethoprophos residues detection and could be used for analysis of sulfur-containing organophosphorus pesticide.

The baseline correction is an extremely important spectral preprocessing step and can significantly improve the accuracy of the subsequent spectral analysis algorithm.At present most of the baseline correction algorithms are manual and semi-automated.The manual baseline correction depends on the user experience and its accuracy is greatly affected by the subjective factor.The semi-automated baseline correction needs to set different optimizing parameters for different Raman spectra,which will be inconvenient to users.In this paper,a locally dynamically moving average algorithm(LDMA) for the fully automated baseline correction is presented and its basic ideas and steps are demonstrated in detail.In the LDMA algorithm the modified moving averaging algorithm(MMA) is used to strip the Raman peaks.By automatically finding the baseline subintervals of the raw Raman spectrum to divide the total spectrum range into multi Raman peak subintervals,the LDMA algorithm succeed in dynamically changing the window half width of the MMA algorithm and controlling the numbers of the smoothing iterations in each Raman peak subinterval.Hence,the phenomena of overcorrection and under-correction are avoided to the most degree.The LDMA algorithm has achieved great effect not only to the synthetic Raman spectra with the convex,exponential,or sigmoidal baseline but also to the real Raman spectra.

Fluorescence analysis is an important means of detecting mineral oil in water pollutants because of high sensitivity,selectivity,ease of design,etc.Noise generated from Photo detector will affect the sensitivity of fluorescence detection system,so the elimination of fluorescence signal noise has been a hot issue.For the fluorescence signal,due to the length increase of the branch set,it produces some boundary issues.The dbN wavelet family can flexibly balance the border issues,retain the useful signals and get rid of noise,the de-noising effects of dbN families are compared,the db7 wavelet is chosen as the optimal wavelet.The noisy fluorescence signal is statically decomposed into 5 levels via db7 wavelet,and the thresholds are chosen adaptively based on the wavelet entropy theory.The pure fluorescence signal is obtained after the approximation coefficients and detail coefficients quantified by thresholds reconstructed.Compared with the DWT,the signal de-noised via SWT has the advantage of information integrity and time translation invariance.

Fe-S series,especially FeS2 and Fe1-xS is the main component of crustal rocks as important metal sulphides.Pyrite(FeS2) shows a promising vision in solar cell materials for its high absorption coefficient and suitable band gap.Predecessors have done some researches on the photovoltaic properties of Fe-S series under different conditions.However,little researches have been done on the coexisted sulphide of FeS2 and Fe1-xS.FeS2 and Fe1-xS often appear as symbiotically due to their similar formation conditions.So the study on the optical absorption characteristics of FeS2 and Fe1-xS are of important significance.In order to study the optical absorption characteristics of FeS2-Fe1-xS heterostructures,using the SEM and XRD to characterize the morphology,composition and structure,respectively.The results show that the samples were cubic pyrite with a certain amount of pyrhotite(Fe1-xS).The crystal partical size was between 5 and 10 nm.Measurement of the absorption spectrum was performed using Cary 500 UV-Vis-NIR spectrophotometer,acquiring the results of 1 860～1 889 nm,and the absorption peak in 1879nm.According to the band gap(eV) formula,the band gap value is calculated to be 0.657 8 eV.The extreme electrical-to-optical conversion efficiency achieved was about 15%.By the first principles,we analysed the reason of the changing of the band gap value,and then compared the result with previous one.The internal structure of mineral is the important factor affecting the photoelectric conversion.The light absorption characteristics of FeS2-Fe1-xS heterostructures synthesized under hydrothermal conditions is better than the characteristics from natural pyrite with defects of Co and Ni.The heterostructures can improve the electrical-to-optical conversion efficiency and provide scientific basis for the absorption characteristics research of Fe-S series materials.

The utilization of organic phosphorus(P) has directly or indirectly improved after exogenous phytase was added to soil.However,the mechanism by which exogenous phytase affected the soil phosphatases(phosphomonoesterase and phosphodiesterase) activities was not clear.The present work was aimed to study red soil,brown soil and cinnamon soil phosphomonoesterase(acid and alkaline)(AcP and AlP) and phosphodiesterase(PD) activities responding to the addition of exogenous phytase(1 g phytase/50 g air dry soil sample) based on the measurements performed via a fluorescence detection method combined with 96 microplates using a TECAN Infinite 200 Multi-Mode Microplate Reader.The results indicated that the acid phosphomonoesterase activity was significantly enhanced in red soil(p≤0.01),while it was significantly reduced in cinnamon soil;alkaline phosphomonoesterase activity was significantly enhanced in cinnamon soil(p≤0.01),while it was significantly reduced in red soil;phosphodiesterase activity was increased in three soils but it was significantly increased in brown soil(p≤0.01) after the addition of exogenous phytase.The activities still remained strong after eight days in different soils,which indicated that exogenous phytase addition could be enhance soil phosphatases activities effectively.This effect was not only related to soil properties,such as pH and phosphorus forms,but might also be related to the excreted enzyme amount of the stimulating microorganism.Using fluorescence spectroscopy to study exogenous phytase addition influence on soil phosphatase activities was the first time at home and abroad.Compared with the conventional spectrophotometric method,the fluorescence microplate method is an accurate,fast and simple to use method to determine the relationships among the soil phosphatases activities.

Recently,the problem of food security is more and more serious,and people pay attention to mercury because of the toxic of it.A new approach for the determination of mercury content in foodstuff is devised.In this paper,first,we design and synthesis a new kind of fluorescent probe whose matrix based on rhodamine B,hydrazine hydrate and hydroxy benzaldehyde.Through the analysis of H-NMR spectra of the synthesized product L1,we confirm that the synthetic substance is the adjacent carboxyl benzaldehyde hydrazone structure generation of rhodamine B.Then,we measure the fluorescence signal intensity of the probe with different concentrations of mercury ions fully upon complexation by fluorescence spectrometer and we can study the relationship between the mercury ion concentration and the fluorescence intensity and draw the standard working curve.Following,It’s time to discuss the microwave digestion processing of tea,after digestion we use the synthetic probe L1 for determination of mercury content in tea.The experimental results show that the maximum excitation wavelength of the probe and coordination compound are 568.05 and 560.00 nm,the maximum emission wavelength are 587.94 and 580.00 nm.Then we can find the best testing conditions to improve the degree of accuracy,that is:room temperature,50% the methanol solution,3.0 mL pH 4.0 buffer solution,in the extent of 30 min.The experimental results show that Na+,K+,Ca2+,Cu2+,Zn2+,Al3+ have little impact on the fluorescence intensity of the probe.Fe3+,Mg2+,Ba2+ has a weak enhancement to the fluorescence intensity of the probe.While a low concentrations of Hg2+ have an obviously enhanced effect on the fluorescence intensity of the probe.In contrast to other metal ions,the probe for Hg2+ has a good selectivity.Linear relationship between the magnitude of increase in fluorescence intensity and concentration of mercury ion was in the range of 5～20 ng·L-1 with detection limit(3S/N) of 1.9 ng·L-1.The proposed method was applied to determination of mercury ion in samples of tea and sausage and the obtained result and sample recovery were all satisfactory.The methods of analysis instrument has the advantages of simple structure,sensitivity,high accuracy,good selectivity and less volume of simple,without the need for enrichment,being very practical.

Se is a necessary trace element for human and animals,but the excess intake of Se caused poison.Thus,it is very important to determination of Se in foods and water.The target of this study is development of a new,sensitive and selective hydride generation-molecular fluorescence method for the determination of Se.In 0.36 mol·L-1 sulfuric acid,NaBH4 as reducing agent,Se(Ⅳ) is reduced to H2Se.Using I-3 solution as absorption liquid,I-3 is reduced to I- by H2Se.When adding rhodamine 6G,Rhodamine 6G and I-3 form association particles,which lead to the fluorescence intensity decreased .When Se(Ⅳ) existing,Rhodamine 6G and I-3 bind less,And the remaining amount of Rhodamine 6G increase.So the fluorescence intensity is enhanced.The analytical conditions were optimized,a 0.36 mol·L-1 H2SO4,21.6 g·L-1 NaBH4,23.3 μmol·L-1 rhodamine 6G,and 50 μmol·L-1 KI3 were chosen for use.When the excitation wavelength is at 480nm,the Rayleigh scattering peak does not affact the fluorescence recording,and was selected for determination of Se.Under the selected conditions,Se(Ⅳ) concentration in the 0.02～0.60 μg·mL-1 range and the increase value of the fluorescence intensity(ΔF) at 562 nm linear relationship.The linear regression equation is ΔF562 nm=12.6ｃ+20.9.The detection limit was 0.01 μg·mL-1.The influence of coexistence substances on the hydride generation-molecular fluorescence determination of 5.07×10-6 mol·L-1 Se(Ⅳ) was considered in details.Results showed that this new fluorescence method is of high selectivity,that is,0.5 mmol·L-1 Ba2+,Ca2+,Zn2+ and Fe3+,0.25 mmol·L-1 Mg2+,0.05 mmol·L-1 K+,0.2 mmol·L-1 Al3+,0.025 mmol·L-1 Te(Ⅵ) do not interfere with the determination.The influence of Hg2+,Cd2+ and Cu2+ that precipitate with Se(Ⅳ),can be eliminated by addition of complex reagent.This hydride generation-molecular fluorescence method has been applied to determination of trace Se in water samples,with a recovery of 91.8%～107.1%.

B is a necessary trace element for human and animals,but the excess intake of B caused poison.Thus,it is very important to determination of B in foods and water.The target of this study is development of a new,sensitive and selective resonance Rayleigh scattering energy transfer(RRS-ET) for the determination of B.The combination of energy transfer with resonance Rayleigh scattering(RRS) has developed a new technology called RRS-ET,which can realize selective and sensitive detection of boric acid.The gold nanorods in diameter of 12 nm and length of 37 nm were prepared by the seed growth procedure.In pH 5.6 NH4Ac-HAc buffer solution and in the presence of azomethine-H(AMH),the gold nanorod particles exhibited a strong resonance Rayleigh scattering(RRS) peak at 404 nm.In the presence of boric acid,it reacts with AMH to form AMH-boric acid(AMH-B) complexes.When the complexe as a receptor close to the gold nanorod as a donor,the resonance Rayleigh scattering energy transfer(RRS-ET) take placed that resulted in the Rayleigh scattering signal quenching.With the increase of the concentration of boric acid,the formed complexes increased,the scattering light energy of gold nanorod transfer to the complexes increased,resulting in the Rayleigh scattering intensity linearly reduced at 404 nm.The decreased RRS intensity responds linearly to the concentration of boron over 10～750 ng·mL-1 B,with a regress equation of ΔI404 nm=3.53ｃ+24 and a detection of 5 ng·mL-1 B.The influence of coexistence substances on the RRS-ET determination of 2.3×10-7 mol·L-1 B was considered in details.Results showed that this new RRS-ET method is of high selectivity,that is,4×10-4 mol·L-1 Mn2+,Cd2+,Zn2+,Bi3+,Na+,Al3+,glucose,Hg2+,IO-3,F-,SO2-4,SiO2-3,NO-3,ClO-4,H2O2,mannitol,glycerol,and ethylene glycol,4×10-5 mol·L-1 L-tyrosine,and 2×10-4 mol·L-1 L-glutamic acid do not interfere with the determination.Based on this,a new sensitive,selective,simple and rapid RRS-ET method has been developed for the determination of trace boron in six mineral water samples that contain 24.9,29.3,57.9,59.0,84.9,and 105.1 ng·mL-1 B,with relative standard deviation of 1.6%～4.1% and recovery of 95.6%～109.6%.

Gasoline,kerosene,diesel is processed by crude oil with different distillation range.The boiling range ofgasoline is 35~205 ℃.The boiling range of kerosene is 140~250 ℃.And the boiling range of diesel is 180~370 ℃.At the same time,the carbon chain length of differentmineral oil is different.The carbon chain length of gasoline is within the scope of C7 to C11.The carbon chain length of kerosene is within the scope of C12 to C15.And the carbon chain length of diesel is within the scope of C15 to C18.The recognition and quantitative measurement of three kinds of mineral oil is based on different fluorescence spectrum formed in their different carbon number distribution characteristics.Mineral oil pollution occurs frequently,so monitoringmineral oil content in the ocean is very important.A new method of components content determination of spectra overlapping mineral oil mixture is proposed,with calculation of characteristic peak power integrationof three-dimensional fluorescence spectrum by using Quasi-Monte Carlo Method,combined with optimal algorithm solving optimum number of characteristic peak and range of integral region,solving nonlinear equations by using BFGS(a rank to two update method named after its inventor surname first letter,Boyden,Fletcher,Goldfarb and Shanno) method.Peak power accumulation of determined points in selected area is sensitive to small changes of fluorescence spectral line,so the measurement of small changes of component content is sensitive.At the same time,compared with the single point measurement,measurement sensitivity is improved by the decrease influence of random error due to the selection of points.Three-dimensional fluorescence spectra and fluorescence contour spectra of single mineral oil and the mixture are measured by taking kerosene,diesel and gasoline as research objects,with a single mineral oil regarded whole,not considered each mineral oil components.Six characteristic peaks are selected for characteristic peak power integration to determine components content of mineral oil mixture of gasoline,kerosene and diesel by optimal algorithm.Compared with single point measurement of peak method and mean method,measurement sensitivity is improved about 50 times.The implementation of high precision measurement of mixture components content of gasoline,kerosene and diesel provides a practical algorithm for components content direct determination of spectra overlapping mixture without chemical separation.

To optimize color rendering of mixed-color LEDs,the Gaussian model was used to analyze the color-mixed LED’s spectrum power distribution.The peak wavelength “λm”,spectral half width “Δλ” and amplitude “A” were basic parameters for optimizing color rendering R9,which is very important for objects to be colorful and vivid under the white light LED’s illuminating.The typical methods for color mixing were used to get white light LEDs.Result was that to get the satisfied color rendering index,one of the color primaries should be certain and then other color primaries would be analyzed through changing three basic parameters step by step.It was concluded that the analysis in this paper would be referential to optimize the color-mixed white LED’s color rendering.

For realizing the real-time monitoring of organic thin film preparation process in vacuum environment,the present paper proposes a high precision measurement approach based on differential reflectance spectroscopy(DRS).An optical system was constructed with off the shelf optical components,such as off-axis parabolic mirror,optical flat and optical fiber.A differential algorithm was employed to analyze the spectral signals.Based on the homebuilt setup,instability induced by variation of temperature was investigated.It was concluded that with the good control of temperature and air flow,the measurement repeatability of this system is better than 2‰ for a long-term period.Furthermore,an initial stage of organic thin film growth of pentacene molecules on the surface of Au was studied.As compared with the data of film thickness gauge and atomic force microscope,DR spectra accurately recorded the fine optical evolution with sub-monolayer resolution,which is related to the growth of the thin film.As a result,the DR optical system exhibits characteristics of broad spectrum(range from 300 to 820 nm),high stability(repeatability better than 2×10-3),and high precision(sub-monolayer resolution) after efforts were done to decrease the influences on the spectral quality produced by misalignments of the optical components,the defects of the optics,and the disturbances of the environmental conditions.It is indicated that the proposed DR method is suitable for real-time online monitoring of thin film growth with high precision.

The present paper proposes a new building change detection method combining Lidar point cloud with aerial image,using multi-level rules classification algorithm,to solve building change detection problem between these two kinds of heterogeneous data.Then,a morphological post-processing method combined with area threshold is proposed.Thus,a complete building change detection processing flow that can be applied to actual production is proposed.Finally,the effectiveness of the building change detection method is evaluated,processing the 2010 airborne LiDAR point cloud data and 2009 high resolution aerial image of Changchun City,Jilin province,China;in addition,compared with the object-oriented building change detection method based on support vector machine(SVM) classification,more analysis and evaluation of the suggested method is given.Experiment results show that the performance of the proposed building change detection method is ideal.Its Kappa index is 0.90,and correctness is 0.87,which is higher than the object-oriented building change detection method based on SVM classification.

Chaenomeles speciosa fruits were extracted using water.The extracts were precipitated with 20%～95%(φ) ethanol,respectively.The amount of total polysaccharide was measured with phenol-sulfuric acid method.A method using high-performance size-exclusion chromatography(HPSEC) equipped with multiangle laser-light-scattering photometry(MALLS) and differential refractometry(RI) was presented for determining the molecular weight and molecular weigh distribution.RAW264.7 macrophage were cultured and stimulated with the polysaccharides in vitro and the production of nitric oxide in the cells was determined by the Griess assay.The aim of the study is to determine the amount and the molecular weight of the polysaccharides from Chaenomeles speciosa fruits,and preliminary investigate the immunomodulatory activity,The study provided the basis datas for the further research of Chaenomeles speciosa fruits.,and provided a simple and system method for the research of natural polysaccharide.The ethanol fractional precipitation showed that the order of total polysaccharide content was 95%＞80%＞40%≥60%＞20%.The results indicated that most polysaccharide from Chaenomeles speciosa fruits might be precipitated when ethanol concentration was up to 95%(φ) and the crude polysaccharide purity had risen from 35.1% to 45.0% when the concentration of ethanol increased from 20% to 95%.HPSEC-MALLS-RI system showed that all the polysaccharide samples had the similar compositions.They appeared three chromatographic peaks and the retention time were not apparently different.The Mw were 6.570×104 g·mol-1and 1.393×104 g·mol-1 respectively,and one less than 10 000 which was failure to obtain accurate values.The molecular weight of the first two polysaccharide distribution index(Mw/Mn)were 1.336 and 1.639 respectively.The polysaccharide samples had not exhibited immunomodulatory activity assessed on the basis of nitric oxide production by RAW264.7 macrophage cells in the experiment.

Trypsin was treated by high pressure technology,and its spatial structure was changed,the relationship between structural changes and trypsin activity was investigated.The secondary structure change of trypsin after pressure treatment was observed by Fourier transform infrared spectroscopy(FTIR).Moreover its tertiary structure change was observed by fluorescence spectroscopy;and its activity was tested using Folin phenol method.The results showed that,compared with the untreated(0.1 MPa),trypsin activity change was significant(p<0.05) under different pressure(100～600 MPa) treatment at 37 ℃ for 20 min.After treated with 300 MPa,its activity was 0.386 times higher than the untreated.Secondary structure of trypsin was analysed using FTIR,and the peak area ratio of α-helix and β-turn in secondary structure was the maximum(2.749);Endogenous fluorescence spectra intensity was the maximum(1 353) at excitation wavelength 295 nm,and was 4 262 at excitation wavelength 280 nm;exogenous fluorescent spectra intensity was 2 022 at excitation wavelength 228 nm,all these change was remarkable(p<0.05)comparing with the untreated.Therefore,ultrahigh pressure processing influence on the spatial structure of trypsin and induce enzyme activity change.Trypsin activity is relate to the peak area ratio of α-helix and β-turn and the exposure degree of Trp and other hydrophobic a mino acid residues and Tyr.

A zwitterionic viologen derivative ligand,1,1’-bis(4-carboxybenzyl) -4,4’-bipyridinium dichloride(H2BpybcCl2) as a multifunctional ligand,has been synthesized incorporating a 4,4’-bipyridine core with two carboxylate groups as a building block,specifically designed for the rational construction of metal-organic frameworks.H2BpybcCl2 ligand is a multifunctional ligand that contains viologen’s specific functions and carboxylate coordination groups.The coordination polymers of viologen carboxylate with copper thiocyanate are not reported to date.A novel copper coordination polymer,［Cu(SCN)2(Bpybc)］(Ⅰ) was by solution diffusion method and characterized by single-crystal X-ray diffraction,XRD,elemental analyses,IR spectroscopy,UV-Vis DRS,TG analysis and liquid-state luminescent properties.Compound Ⅰ crystallized in the monoclinic system with C2/c space group.Crystal data for complex Ⅰ is as follow:a=19.508(4) ,b=9.474(2) ,c=16.963(3) ,α=90°,β=124.92(3)°,γ=90°.Two SCN- anions were coordinated to the Cu2+ cation forming a ［Cu(SCN)2］ unit.Complex Ⅰ was built up by ［Cu(SCN)2］ units bridged sequentially by ladder-shaped Bpybc ligands to form one-dimensional zigzag chains running along the ［203］ direction.The chains were held together by π—π interaction between the pyridine rings and phenyl rings,thus yielding a 3-D extended supramolecular network.The UV-Visible absorption spectra show the absorption bands of π—π* transitions of Bpybc ligands and d→d transition of Cu2+.The liquid-state luminescent property of compound Ⅰ was investigated at room temperature.Attractively,the complex exhibits strong blue emission peak at 533 nm(λEx=360 nm) that can be assigned to intraligand transition of Bpybc ligand when it was excited at 360 nm.

There is a regular use of Moderate Resolution Imaging Spectroradiometer(MODIS) 250 meter EVI to classify the crops on a regional level throughout the world.A rapid agricultural land use change attributed to new Chinese agriculture policy is attracting many researchers to focus.The objective of this study is to present a more straightforward multiyear classification methodology using time series MODIS EVI with 250 meters spatial resolution and subsequent field data in Xinjiang,China.An extensive polygon based ground reference annual crop data were collected for the years 2011,2012 and 2013 throughout the study area.The most pure pixel within each polygon was selected which eases crop differentiation.Artificial Immune Network(ABNet) was used to classify cotton,maize,wheat/others,rice and grapes,dominating most of the study area.The data of two different years were used together to classify the crop of next year,as 2011 and 2012 were used to classify crops of 2013.Classification results were validated using the same year ground data.Results showed the classification accuracy above 80% for each year with kappa coefficient of 0.7 and above.However more research and additional ground reference data are needed to classify a range of crops in the study area which will give a more detailed view of the land use land cover change strengthening agriculture decisions practices in the future.

The fast estimation of leaf area index(LAI) is significant for learning the crops growth,monitoring the disease and insect,and assessing the yield of crops.This study used the hyperspectral compact airborne spectrographic imager(CASI) data of Zhangye city,in Heihe River basin,on July 7,2012,and extracted the spectral reflectance accurately.The potential of broadband and red-edge vegetation index for estimating the LAI of crops was comparatively investigated by combined with the field measured data.On this basis,the sensitive wavebands for estimating the LAI of crops were selected and two new spectral indexes(NDSI and RSI) were constructed,subsequently,the spatial distribution of LAI in study area was analyzed.The result showed that broadband vegetation index NDVI had good effect for estimating the LAI when the vegetation coverage is relatively lower,the R2 and RMSE of estimation model were 0.52,0.45(p<0.01),respectively.For red-edge vegetation index,CIred edge took the different crop types into account fully,thus it gained the same estimation accuracy with NDVI.NDSI(569.00,654.80) and RSI(597.60,654.80) were constructed by using waveband combination algorithm,which has superior estimation results than NDVI and CIred edge.The R2 of estimation model used NDSI(569.00,654.80) was 0.77(p<0.000 1),it mainly used the wavebands near the green peak and red valley of vegetation spectrum.The spatial distribution map of LAI was made according to the functional relationship between the NDSI(569.00,654.80) and LAI.After analyzing this map,the LAI values were lower in the northwest of study area,this indicated that more fertilizer should be increased in this area.This study can provide technical support for the agricultural administrative department to learn the growth of crops quickly and make a suitable fertilization strategy.

With the development of remote sensing technology and imaging spectrometer ,the resolution of hyperspectral remote sensing image has been continually improved,its vast amount of data not only improves the ability of the remote sensing detection but also brings great difficulties for analyzing and processing at the same time.Band selection of hyperspectral imagery can effectively reduce data redundancy and improve classification accuracy and efficiency.So how to select the optimum band combination from hundreds of bands of hyperspectral images is a key issue.In order to solve these problems,we use spectral clustering algorithm based on graph theory.Firstly,taking of the original hyperspectral image bands as data points to be clustered ,mutual information between every two bands is calculated to generate the similarity matrix.Then according to the graph partition theory,spectral decomposition of the non-normalized Laplacian matrix generated by the similarity matrix is used to get the clusters,which the similarity between is small and the similarity within is large.In order to achieve the purpose of dimensionality reduction,the inter-class separability factor of feature types on each band is calculated,which is as the reference index to choose the representative bands in the clusters furthermore.Finally,the support vector machine and minimum distance classification methods are employed to classify the hyperspectral image after band selection.The method in this paper is different from the traditional unsupervised clustering method,we employ spectral clustering algorithm based on graph theory and compute the inter-class separability factor based on a priori knowledge to select bands.Comparing with traditional adaptive band selection algorithm and band index based on automatically subspace divided algorithm,the two sets of experiments results show that the overall accuracy of SVM is about 94.08% and 94.24% and the overall accuracy of MDC is about 87.98% and 89.09%,when the band selection achieves a relatively optimal number of clusters using the method propoesd in this paper .It effectively remains spectral information and improves the classification accuracy.

The precipitation of floating and sinking dust on leaves of plants is called as foliar dustfall.To monitor foliar dustfallIt,it will provide fundamental basis for environmental assessment and agricultural disaster evaluation of dust area.Therefore,the aim of this work to(1) study the effect of foliar dustfall content(FDC) on high spectral characteristics of pear leaves,(2) analyze the relationship between reflectances and FDC,and(3) establish high spectral remote sensing quantitative inversion model of FDC.The results showed that FDC increased reflectances of visible band(400~700 nm) with maximum band of 666 nm.Absolute and relative rates of change were -10.50% and -62.89%,respectively.The FDC decreased reflectances of near infrared band(701~1 050 nm) with maximum band of 758 nm.Absolute and relative rates of change were 12.04% and 41.75%,respectively.After dustfall was removed,reflection peak of green light and absorption valley of red and blue light became prominent,and slope of 500~750 nm wave band increased when FDC was more than 20 g·m-2.While FDC just slightly affected shape and area of reflection peak of green light when FDC was less than 20 g·m-2.FDC were positive and negative correlated with reflectances of visible band and near infrared band,respectively.Maximum correlation coefficient(0.61) showed at 663 nm.All of 7 inversion models,the model based on the first-order differential of logarithm of the reciprocal had better stability and predictive ability.The coefficient of determination(R2),root mean square error(RMSE) and relative percent deviation(RPD) of this model were 0.78,3.37 and 2.09,respectively.The results of this study can provide a certain reference basis for hyperspectral remote sensing of FDC.

The most common methodology used in element concentration measurement and analyzing of wear particles is Atomic emission(AE) spectroscopy.The present paper presents an evaluation method on wear in power-shift steering transmission(PSST).By removing the problematic components which were highly correlated with oil additives,the robust kernel principal component analysis(RKPCA) method and the principal component analysis(PCA) method were accessed to extract the principal components of spectral data for oil samples collected from the life-cycle test of PSST in different stage and to calculate the amount of each principal component and its contribution rate respectively.A comparison between the above mentioned two methods was made to show that RKPCA method has fewer amounts of principal components and higher cumulative contribution rate indicating that RKPCA method acts more effectively in variable dimension reduction due to the outliers and nonlinearity of spectral data.Therefore,the effectiveness of RKPCA method in classification and identification of the wear in friction pairs was demonstrated subsequently through the correlation analysis between the variable coefficients of RKPCA and metal elements of friction pairs.The demonstration showed that RKPCA functioned precisely in the classification and identification of the wear in friction pairs,and in the evaluation on the wear in PSST.Thereafter,to detect the threshold point where the wear took place,the fuzzy C-means clustering algorithm was introduced to classify the RKPCA eigenvalues,and the results were compared with that of the spectral clustering algorithm.The fuzzy C-means clustering algorithm showed higher sensitivity in detecting the threshold point indicting a more precise evaluation on the wear in PSST.It is clear that the introduction of RKPCA method in wear evaluation,which takes the eigenvalues of spectral data as a critical variable to classify and identify the wear in different friction pairs as well as in the integral PSST configuration,shows better accuracy in wear prediction and will contribute to the reliable determination of life between overhauls and the accurate positioning of worn-out parts.As might be expected,the proposed method can be extended to other cases of wear detection and evaluation in complex mechanical system.

In order to develop a method to analyze the metal elements in the thin film samples rapidly,directly and without sample preparation,a laboratory LIBS system was established recently for nanometer film analysis.This system could determine the position of sample plane,observe the profiles of sample after pulse-material interaction and detect the plasma morphologyand spectral emission at the same time.Samplesused were ZrO2 films about 40 nm thickness prepared on Si by a sol-gel process,and they were located on a manual X-Y-Z translational stage with theaccuracy of 0.01 mm.Final results showed that the positional accuracy is about 20μm with the help of two CW lasers,and the RSD of repeatability of single-shot spectra could be to 1.6%.We investigated special morphology of plasma,variation tendency of signal intensity as a function of pulse energy,LTSD(laser focus to sample distance) and time,which provide cornerstone for optimizing experimental parameters under the conditions of room temperature and atmospheric pressure.We calculated plasma temperature by way of Boltzmann curve and electron densitythrough the acquired data.We also appraised necessary LTE conditions for quantitativeanalysis.

In the present paper,the spectrum analytic method was used to comparatively study the ICP electron density distribution through two typical ICP sources(spiral-type and planar-type) in closed quartz chamber.The E-H mode transition of inductively coupled plasma and power coupling efficiency were researched through the change in the relative intensity of argon ion spectral line(476.45 nm).Electron density distribution on the antennas-vertical plane of different ICP source was calculated through non-hydrogen-like Stark broadening of spectral line method.The test results show that the ICP electronic density distribution in H-mode discharge is significantly impacted by skin current of alternating magnetic field.The skin depth decreases with the increase in discharge power.Meanwhile,the bulk of the main plasma narrows and electron density increases.On the vertical plane of the antenna,electron density distribution presents center-symmetry by spiral-ICP source and bimodal by planar-ICP source.The power coupling efficiency is directly affected by source antenna shape and capacitive coupling effect.The relative intensity of the argon spectrum shows that the power coupling efficiency of spiral-type source is lower than that of planar-type source.The proposed experimental method provides a way to obtain a plasma source in closed quartz cube chamber with the highest electron density ranging from 1.4×1017 to 2.5×1017 m-3(spiral-ICP source) and 1.8×1017 to 3.0×1017 m-3(planar-ICP source).

The concentration of silica in groundwater and mineral water was determined by inductively coupled plasma-atomic emission spectrometry(ICP-AES).After a more sensitive analytical line of silicon was chosen,the effects of operating conditions of the ICP spectrometer on the analysis results were investigated,at the same time,the impact of coexisting ions on determination results of SiO2 was also considered and eliminated.The transmit power of 1 350 W,observation height of 12 mm,the nebulizer pressure of 0.20 MPa and the pump speed of analysis of 75 r·min-1 were selected by experimental conditions.Under the optimum analytical conditions of spectrometer,the method was used for the determination of SiO2 in groundwater and mineral water with the detection limit of 0.017 mg·L-1,recoveries between 94.10% and 103.8%,and relative standard deviation(RSD)≤3.06%.Compared with the results of silicon molybdenum yellow spectrophotometry,the results were basically consistent with the relative deviation ≤3.00%.In conclusion,the method is simple and efficient with high precision and accuracy,and can be used for research and routine production.

Cu in navel orange was detected rapidly by laser-induced breakdown spectroscopy(LIBS) combined with partial least squares(PLS) for quantitative analysis,then the effect on the detection accuracy of the model with different spectral data pretreatment methods was explored.Spectral data for the 52 Gannan navel orange samples were pretreated by different data smoothing,mean centralized and standard normal variable transform.Then 319~338 nm wavelength section containing characteristic spectral lines of Cu was selected to build PLS models,the main evaluation indexes of models such as regression coefficient(r),root mean square error of cross validation(RMSECV) and the root mean square error of prediction(RMSEP) were compared and analyzed.Three indicators of PLS model after 13 points smoothing and processing of the mean center were found reaching 0.992 8,3.43 and 3.4 respectively,the average relative error of prediction model is only 5.55%,and in one word,the quality of calibration and prediction of this model are the best results.The results show that selecting the appropriate data pre-processing method,the prediction accuracy of PLS quantitative model of fruits and vegetables detected by LIBS can be improved effectively,providing a new method for fast and accurate detection of fruits and vegetables by LIBS.

P,Na,Ca,Cu,Fe,Mg,Zn,As,Cd,Co,Cr and Ni contents have been examined in caps and stipes of Boletus tomentipes collected from different sites of Yunnan province,southwest China.The elements were determined using inductively coupled plasma atomic emission spectroscopy(ICP-AES) with microwave digestion.P,Ca,Mg,Fe,Zn and Cu were the most abundant amongst elements determined in Boletus tomentipes.The caps were richer in P,Mg,Zn and Cd,and the stipes in Ca,Co and Ni.Cluster analysis showed a difference between Puer(BT7 and BT8) and other places.The PCA explained about 77% of the total variance,and the minerals differentiating these places were P(PC1) together with Ca,Cu,Fe,Mg,As and Ni,Na(PC2) together with Cd,and Zn(PC3).The results of this study imply that element concentrations of a mushroom are mutative when collected from the different bedrock soil geochemistry.

In the present work we presented a new method for determination of total Se and As in coal by electric hot plate-mixed acids-hydride generation atomic fluorescence spectrometry(HG-AFS),the wet digestion method.The detailed operation procedures of the new method are as follows:About 0.05～0.10 g of powdered(200 mesh) coal sample was placed in a glass beaker,10 mL of nitric acid(HNO3) and 2 mL of perchloric acid(HClO4) were added to the beaker in sequence,then the beaker was covered with a watching glass and placed in a fume cupboard standing overnight.The beaker was placed on an electric hot plate(180 ℃) for sample decomposition the next day.The beaker was moved away from the electric hot plate when white smoke arose in the beaker,the sample color turned white or grey and the solution turned clear.Three milliliter of hydrochloric acid(HCl) solution(6 mol·L-1) was added to the beaker after the temperature of the beaker returned to room temperature.The beaker was heated on the electric hot plate again,and then moved away when white smoke started arising again.One milliliter of HCl was added in the beaker after the temperature of the beaker returned to room temperature.After that,the digested sample was transferred to a 25 mL test tube which was filled with ultrapure water to the tube’s full volume.This solution was used for Se determination directly.Three milliliter of the Se test solution prepared above was transferred to a 15 mL glass test tube,1 mL of thiourea/ascorbic acid solution(2.5 g·mL-1) and 1 mL of the concentrated HCl was added to the 15 mL test tube.The test tube was then filled with ultrapure water to its full volume.The solution was used for As determination after shaking well and 40 min standing.Finally,Se and As concentrations in these prepared solutions were measured by using the AFS-9780 instrument(Beijing Haiguang Instrument Co.,LTD,Beijing,China).Two Chinese Coal Certified Reference Materials(GBW11115 and GBW11117) were tested using this method,and the recoveries of As were 99.7%～100.3% and the relative standard deviation(RSD) for As and Se were 5.6%～6.0% and 11.1%～13.5%,respectively.The limits of detection(LOD) of the method for Se and As determination were 0.01 and 0.05 μg·L-1,respectively.These results indicated that this new method was suitable for Se and As determination in coal,and it had the advantages of simple operation,high accuracy and reproducibility compared with the Chinese National Standard method.

Temperature drift will be brought to Micro-Spectrometer used for demodulating the Varied Line-Space(VLS) grating position sensor on aircraft due to high-low temperature shock.We successfully made a Micro-Spectrometer,for the VLS grating position sensor on aircraft,which still have stable output under temperature shock enviro nment.In order to present a real time temperature compensation scheme,the effects temperature change has on Micro-Spectrometer are analyzed and the traditional cross Czerny-Turner(C-T)optical structure is optimized.Both optical structures are analyzed by optics design software ZEMAX and proved that comparedwithtraditional cross C-T optical structure,the newone can accomplish not only smaller spectrum drift but also spectrum drift with better linearity.Based on the new optical structure.The scheme of using reference wavelength to accomplish real time temperature compensation was proposed and a Micro-fiber Spectrometer was successfully manufactured,whith is with Volume of 80 mm×70 mm×70 mm,integration time of 8～1 000 ms and FullWidthHalfMaximum(FWHM) of 2 nm.Experiments show that the new spectrometer meets the design requirement.Under high temperature in the range of nearly 60 ℃,the standard error of wavelength of this new spectrometer is smaller than 0.1 nm,and the maximum error of wavelength is 0.14 nm,which is much smaller than required 0.3 nm.Innovations of this paper are the schemeof real time temperature compensation,the new cross C-T optical structure and a Micro-fiber Spectrometer based on it.

In the reflection-based imaging spectrometer,multiple reflection(diffraction) produces stray light and it is difficult to assemble.To address that,a high performance transmission spectral imaging system based on general optical components was developed.On the basis of simple structure,the system is easy to assemble.And it has wide application and low cost compared to traditional imaging spectrometers.All components in the design can be replaced according to different application situations,having high degree of freedom.In order to reduce the influence of stray light,a method based on transmission was introduced.Two sets of optical systems with different objective lenses were simulated;the parameters such as distortion,MTF and aberration were analyzed and optimized in the ZEMAX software.By comparing the performance of system with different objective len 25 and 50 mm,it can be concluded that the replacement of telescope lens has little effect on imaging quality of whole system.An imaging spectrometer is developed successfully according design parameters.The telescope lens uses double Gauss structures,which is beneficial to reduce field curvature and distortion.As the craftsmanship of transmission-type plane diffraction grating is mature,it can be used without modification and it is easy to assemble,so it is used as beam-split component of the imaging spectrometer.In addition,the real imaging spectrometer was tested for spectral resolution and distortion.The result demonstrates that the system has good ability in distortion control,and spectral resolution is 2 nm.These data satisfy the design requirement,and obtained spectrum of deuterium lamp through calibrated system are ideal results.

Fiber-coupling surface Plasmon resonance sensor has attractive advantages of information transmission such as small volume,anti-electric magnetic field interference,and online real-time remote detection.In order to improve the performance of the sensor,the effect of the residual fiber thickness and the silver film thickness to the sensitivity of the sensor and the depth of the resonance peaks and full width ar half maximum(FWHM) are analyzed respectively.The results show that the increasing fiber residual thickness weakens the SPR phenomenon,and that the increasing silver film thickness widens the resonance peak,while the sensitivity of the sensor does not change monotonously.Through the integration of refractive index sensing sensitivity and full width at half maximum,figure of merit is presented and regarded as the optimized objective.The optimal design is achieved in the case of the fiber residual thickness for 66.5 μm,and the silver film thickness for 50 nm.The optimized design with the figure of merit of 98.67 is expected to be applied in the bio-chemical sensing and analysis.

Phase matching is one of the key techniques in temperature measuring by coherent anti-Stokes Raman scattering(CARS).In order to overcome the disadvantages of large background radiation,inconvenient adjusting and low-usage of Stokes laser energy in traditional unstable-resonator spatially enhanced detection(USED) phase matching,new implementation technique of USED CARS phase matching is researched.A piece of oblique reflector,which is as big as the Stokes spot and with an angle of 45 degrees,was used to replace the annular reflector in traditional USED to reflect the Stokes fully.Then,pump laser shines from the back of the oblique reflector to satisfy USED phase matching with reflected Stokes.In the new USED CARS phase matching,background radiation caused by reflecting was weakened for the area of oblique reflector is smaller than that of annular reflector;Furthermore,oblique reflector can be used as an adjusting component in experiments which can make beam path adjusting more easier;Finally,Stokes laser was in high-usage for it was fully reflected by the oblique reflector.Temperature measuring results on laminar flame suggest that new USED CARS phase matching has lower standard deviation and it is a more effective phase matching method.

The Sloan Digital Sky Survey(SDSS) has released the latest data(DR10) which covers the first APOGEE spectra.The massive spectra can be used for large sample research including the structure and evolution of the Galaxy and multi-waveband identi cation.In addition,the spectra are also ideal for searching for rare and special objects like white dwarf main-sequence star(WDMS).WDMS consist of a white dwarf primary and a low-mass main-sequence(MS) companion which has positive significance to the study of evolution and parameter of close binaries.WDMS is generally discovered by repeated imaging of the same area of sky,measuring light curves for objects or through photometric selection with follow-up observations.These methods require significant manual processing time with low accuracy and the real-time processing requirements can not be satisfied.In this paper,an automatic and efficient method for searching for WDMS candidates is presented.The method Genetic Algorithm(GA) is applied in the newly released SDSS-DR10 spectra.A total number of 4 140 WDMS candidates are selected by the method and 24 of them are new discoveries which prove that our approach of finding special celestial bodies in massive spectra data is feasible.In addition,this method is also applicable to mining other special celestial objects in sky survey telescope data.We report the identfication of 24 new WDMS with spectra.A compendium of positions,mjd,plate and fiberid of these new discoveries is presented which enrich the spectral library and will be useful to the research of binary evolution models.

The radiation spectrum from the plasmas contains a large amount of information of plasmas.Thus,one of the most effective methods to detecting the plasma parameters is measure the plasma radiation spectrum.Until now,since the restriction of the Toshiba mechanically ruled aberration-corrected concave gratings,the measurable wavelength range of the incidence flat-field grazing spectrometer in the soft X-ray range are only from 5 to 40 nm.In order to extend the wavelength rang of grazing incidence flat-field spectrometer,first,a grazing incidence concave reflection grating ray-trace code is written using optical path equation.Second,under the same conditions with reference 6,we compare our numerical results with Harada’s results.The results show that our results agree very well with the results of Harada.The results of comparison show that our ray-trace code is believable.Finally,the variety of the flat-field curves are detailedly investigated using the ray-trace code with the different grazing incidence conditions.The results show that the measurable wavelength range of the incidence flat-field grazing spectrometer are extended to 5~80 nm from the soft X-ray wavelength range of 5~40 nm.This result theoretically demonstrates the possibility of expanded the traditional band flat-field grazing incidence spectrometer from soft X-ray band to the extreme ultraviolet(XUV),and also bring a new design ideas for improving the use of grazing incidence flat field concave grating.

In order to improve the accuracy and stability of the rebuilt spectrums,it is necessary that stability analysis and nicety measuring of the maximum optical path difference of interferograms in the photo-elastic modulator Fourier transform spectrometers(PEM-FTS).The maximum optical difference of interferograms is uncertain parameter,and it is relate to the resonant state,characteristic of frequency-thermal drift and driving voltage of PEM.Therefore,based on the principle of photo-elastic modulator Fourier transform interferometer,the model of the freguency-thermal drift is built,and the variety of the maximum optical path difference is analyzed;A measuring method of the maximum optical path difference is put forward,which is zero-crossing counting of laser’s interference signal when the driving signal of PEM is as the standard.In the method the dual channel high-speed comparator and FPGA are used to transform sine wave to square wave,to realize zero-crossing trigger counting and errors compensation.On the condition that the 670.8 nm laser is as the power source to produce the reference interferograms by the PEM interferometer,the 77.471 μm maximum optical path difference could be measured by the zero-crossing counting.the measuring errors is less than 0.167 nm,the rebuilt spectral peak wavelength errors of the infrared blackbody is less than 2 nm.the result is content with PEM-FTS.

To be able to quickly and efficiently identify Enemy camouflaged maneuvering targets in the wild environment,target recognition system was designed based on spectral detection technology and video target recognition method.System was composed of the visible light image acquisition module and static interferometer module.The system used image recognition technology to obtain two dimensional video images of measurement region,and through spectrum detection technology to identify targets.Ultimately,measured target was rebuilt on the corresponding position in the image,so the visual target recognition was realized.After the theoretical derivation,identifiable target function formula of the system was obtained,and based on the functional relationship to complete the quantitative experiments for target recognition.In the experiments,maneuvering target in the battlefield environment was simulated by a car.At different distances,the background was respectively selected to detect a flat wasteland,bushes and abandoned buildings.Obvious target,coated camouflage target and covered disguises target was respectively spectrum detection.Experimental results show that spectrum detection technology can overcome the shortcomings of unrecognized the camouflaged target by traditional image target recognition method.Testing background had some influence on spectrum detection results,and the continuity of the background was conducive to target recognition.Covered disguises target was the hardest to identify in various camouflage mode.As the distance between the target and the system increases,signal to noise ratio of the system was reduced.In summary,the system can achieve effective recognition of camouflaged targets to meet the design requirements.

In order to smooth the spectra automatically and reliably,a spectral smoothing algorithm with adaptive multiscale window average(AWMA) is demonstrated.In this method,different positions of the spectra are smoothed by windows of different width,and the width of the windows will directly affect smoothing.The window with inappropriate width may cause excessive denoising(peak distortion or loss) or inadequate denoising(the flat region of the spectra still contains a lot of noise).So,how to get the right width of the window is the key of spectral smoothing.The algorithm optimized the width of windows by an iterative method,and verified whether the width is the best according to statistical Z-test.In order to increase the reliability of the algorithm,a comprehensive comparison of the thresholds of hypothesis according to simulation data of different SNR was performed.When the threshold is set to 1.1,the denoising effect can be the best.In this work,the AMWA algorithm was tested by simulated spectra and real spectra,and it can automatically adapt to different spectral shape and different noise intensity.A comprehensive comparison of AMWA smoothing,Savitzky-Golay smoothing and moving average smoothing was performed in this paper,and the AMWA algorithm is better than the other two algorithms.Results show that the AMWA algorithm not only has better denoising effect,but also has higher accuracy and fidelity.This method has achieved great effect not only to simulated spectra but also to real spectra.

In the present paper,a new model-based method was proposed for temperature prediction and correction.First,a temperature prediction model was obtained from training samples;then,the temperature of test samples were predicted;and finally,the correction model was used to reduce the nonlinear effects of spectra from temperature variations.Two experiments were used to verify the proposed method,including a water-ethanol mixture experiment and a ternary mixture experiment.The results show that,compared with classic method such as continuous piecewise direct standardization(CPDS),our method is efficient for temperature correction.Furthermore,the temperatures of test samples are not necessary in the proposed method,making it easier to use in real applications.