原位漫反射红外光谱研究NO和NH3在MnOx/TiO2催化材料上的吸附行为及反应机理

MnO_x/TiO₂催化材料在选择性催化还原过程中表现出了较好的低温催化活性,为了深入了解其作用机理,进一步改善催化活性,本工作采用原位漫反射红外光谱法系统地分析了NO和NH₃在MnO_x/TiO₂催化材料上的单吸附和共吸附行为。分析认为,该催化材料表面发生的选择性催化还原过程符合Eley-Ridal机理,催化反应发生在吸附态的NH₃和气态NO之间,而吸附态的NO及后续生成的硝酸盐、亚硝酸盐等物质会占据催化材料的活性位点,影响其对NH₃的吸附,进而导致脱硝活性下降。     

TiO2纳米带/石墨烯纳米复合材料一锅煮溶剂热法合成及其近红外肾癌热疗应用研究

采用一锅煮溶剂热法成功合成二氧化钛纳米带/石墨烯复合材料(TiO2/GR),该过程可以同步实现石墨烯的还原及TiO2/GR的原位生成。利用透射电镜(TEM)、扫描电镜(SEM)、选区电子衍射(SAED)等分别对TiO2/GR的形貌、结构和尺寸进行了详细表征。体外实验结果显示,在近红外光照射下,以TiO2/GR为新型光热试剂,对照组肾癌细胞仍保持较高活性,而实验组的肾癌细胞活力则降低为4.72%,揭示了该纳米复合材料在肾癌热疗方面的潜力。     

A Method for Calculating Thermal Radiation Properties of Multilayer Films from Optical Constants

A calculation method for the incident angle dependence of the solar absorptance _S and the temperature dependence of the total hemispherical emittance _H of multilayer films is proposed. The method is based on calculation of _S and _H from optical constants in the wavelength region from 0.25 to 100 m for thin polymer films and deposited metal. In this paper we provide values of _S in the incident angle region from 0 to 90° and _H in the temperature range from 173.15 to 373.15 K for two-layer samples of aluminum-deposited polyimide film. The results obtained for _S and _H by the present method are compared with experimental results measured by both spectroscopic and calorimetric methods. The calculated results of _S and _H agree well with the experimental results.     

Retrieval of Total Suspended Matter in the Lower of Minjiang River based on PSO-RBF

Total suspended matter (TSM) is one of the important parameters of water environment.As the spectral characteristics of the Case-II water are complicated,so it is not suitable to represent the relationship between spectral characteristics andTSM by simple linear models.In this paper,the test data,which is acquired by water quality sampling and spectral measurement of 40 points from July 12 -13,2017,together with GF-1 WFV1 bands reflectance data are used to analysis the correlation between remote sensing factors and TSM.Taking advantage of high correlation coefficients between bands,such as b3,b3/b2 and b3/b1,we construct PSO-RBF and RBF neural network model to inverse TSM.At the same time,a empirical b3/b2 ratio model is also proposed.The result shows that PSO-RBF neural network model’s performance is better than traditional RBF neural network and the empirical model,whose R²=0.890,RMSE=3.01 mg/L.On this basis,the GF-1 WFV1 remote sensing image is used to inverse TSM of Minjiang River,which is calculated by the well-trained PSO-RBF model.Furthermore,the spatial distribution characteristics of TSM is also studied.The result of TSM inversion comes to RMSE=3.65 mg·L^-1,MRE=14.11% respectively,and remote sensing image retrieval results accuracy was significantly higher than that of Kriging interpolation results,and there is     

Reproducing Spectral Reflectances From Tristimulus Colours

Physically based rendering systems often support spectral rendering to simulate light transport in the real world. Material representations in such simulations need to be defined as spectral distributions. Since commonly available material data are in tristimulus colours, we ideally would like to obtain spectral distributions from tristimulus colours as an input to spectral rendering systems. Reproduction of spectral distributions given tristimulus colours, however, has been considered an ill‐posed problem since single tristimulus colour corresponds to a set of different spectra due to metamerism. We show how to resolve this problem using a data‐driven approach based on measured spectra and propose a practical algorithm that can faithfully reproduce a corresponding spectrum only from the given tristimulus colour. The key observation in colour science is that a natural measured spectrum is usually well approximated by a weighted sum of a few basis functions. We show how to reformulate conversion of tristimulus colours to spectra via principal component analysis. To improve accuracy of conversion, we propose a greedy clustering algorithm which minimizes reconstruction error. Using pre‐computation, the runtime computation is just a single matrix multiplication with an input tristimulus colour. Numerical experiments show that our method well reproduces the reference measured spectra using only the tristimulus colours as input.     

基于反射光谱的PCA及BP神经网络法预测甘蔗叶片叶绿素含量

叶绿素是植物进行光合作用的重要色素,叶绿素含量可以作为评价植物生长状况的重要参数。本研究基于甘蔗叶片的反射光谱,利用PCA及BP神经网络算法,建立了甘蔗叶片的叶绿素含量预测模型。PCA算法可以在尽可能少地丢失有用光谱信息的前提下,降低输入光谱矩阵的维数,最大限度地减少冗余信息。BP神经网络算法因其良好的非线性逼近能力可大大提高该模型的预测精度。研究发现：基于PCA和BP算法建立的叶绿素含量预测模型,其预测值与实测值之间的R2达0.8929,表明该模型具有较高的预测能力。     

Study on the Inversion of Chlorophyll Content of Spartina Alterniflora Leaf in the Yangtze River Estuary Wetland based on Spectral Analysis#br#

Spartina alterniflora is one of the most important invasive species in the coastal wetlands in China,which have a profound impact on the local ecological system.The information of chlorophyll content is an important basic data for quantitative research on key ecological function of wetland ecosystem.The Yangtze River in Chongming Dongtan wetland is the study area.Based on the measured leaf spectral reflectance and total chlorophyll content of Spartina alterniflora,in the range of 400~1 000 nm,the ratio of the original form of the spectral reflectance and first derivative spectral reflectance(RVI)and normalized difference vegetation index(NDVI)in the form of combination are established for the correlation with the content of chlorophyll and the construction of the estimation model.The results show that RVI and NDVI vegetation index form model based on the original spectra have the highest accuracy,whose root mean square error(RMSE)are up to respectively 0.24 and 0.25;Because of the nosie in the first derivative spectral reflectance,the estimation model of chlorophyll has poor results;Based on the band selected from the model,the red edge band is particularly important in the estimation of chlorophyll content of Spartina alterniflora.     

不同来路海洛因近红外光谱的支持向量机模式识别

应用支持向量分类方法,将云南省9个地区缴获的1148个海洛因样品,用近红外漫反射光谱在4 000 cm-1～10 000 cm-1范围内吸收系数数据集合,构建判别毒品来路的分类器.光谱数据选取了指纹波数区段5 990 cm-1～7 500 cm-1,以及最大和较大吸收系数的41个波数的光谱数据.针对一对一算法的五分类问题,采用两种分类法C.SVC和v-SVC,4种核函数,分别以默认参数和优化参数,得训练集模型有效率和检验集的预报总精度.比较各种模型后,确定了152个指纹区波数,线性核函数的L-152 C-SVC作为分类器模型.该模型对已知分类的5个地区随机选取的训练集样本,在10-交叉检验下的有效率是90.74%,对不包含洲练集的其余全部已知样品,其预报总精度是88.71%.5地庆分类统计计算的敏感性、特异性、相关系数的评价都较好.最后,又试用该分类器于未知地毒品的来路辨认.与报道的模式识别比较,工作没有止于训练集给出模型,检验集判断预报效果的已知样品,又走出了重要一步,即识别训练集和检验集之外的未知样品.     

利用采样球体提取真实感纹理

提出了一种从真实物体中提取纹理的方法.利用具有复杂纹理的参考球体作为被采样物体,计算其组成材质的BRDF(bidirectional reflectance distribution function)模型参数以及各点由不同材质构成的比例,形成一幅材质权重图.该图作为纹理映射到3D物体上后,配合BRDF模型参数进行渲染,形成一种适用于重光照(relighting)的纹理.被渲染物体可根据自身方位以及光源亮度/方位呈现出自然的光影变化,达到较为逼真的外观效果.     

Mapping leaf chlorophyll and leaf area index using inverse and forward canopy reflectance modeling and SPOT reflectance data

Reflectance data in the green, red and near-infrared wavelength region were acquired by the SPOT high resolution visible and geometric imaging instruments for an agricultural area in Denmark (56°N, 9°E) for the purpose of estimating leaf chlorophyll content (C_ab) and green leaf area index (LAI). SPOT reflectance observations were atmospherically corrected using aerosol data from MODIS and profiles of air temperature, humidity and ozone from the Atmospheric Infrared Sounder (AIRS), and used as input for the inversion of a canopy reflectance model. Computationally efficient inversion schemes were developed for the retrieval of soil and land cover-specific parameters which were used to build multiple species and site dependent formulations relating the two biophysical properties of interest to vegetation indices or single spectral band reflectances. Subsequently, the family of model generated relationships, each a function of soil background and canopy characteristics, was employed for a fast pixel-wise mapping of C_ab and LAI.The biophysical parameter retrieval scheme is completely automated and image-based and solves for the soil background reflectance signal, leaf mesophyll structure, specific dry matter content, Markov clumping characteristics, C_ab and LAI without utilizing calibration measurements.Despite the high vulnerability of near-infrared reflectances (ρ_nir) to variations in background properties, an efficient correction for background influences and a strong sensitivity of ρ_nir to LAI, caused LAI-ρ_nir relationships to be very useful and preferable over LAI-NDVI relationships for LAI prediction when LAI > 2. Reflectances in the green waveband (ρ_green) were chosen for producing maps of C_ab.The application of LAI-NDVI, LAI-ρ_nir and C_ab-ρ_green relationships provided reliable quantitative estimates of C_ab and LAI for agricultural crops characterized by contrasting architectures and leaf biochemical constituents with overall root mean square deviations between estimates and in-situ measurements of 0.74 for LAI and 5.0 μg cm^− 2 for C_ab.The results of this study illustrate the non-uniqueness of spectral reflectance relationships and the potential of physically-based inverse and forward canopy reflectance modeling techniques for a reasonably fast and accurate retrieval of key biophysical parameters at regional scales.