Effects of Phenyl Content and Molecular Structure on the Refractive Index of Organic Silicon Polymer

The effects of phenyl content and group distribution on the refractive index of phenyl silicone oil were investigated by synthesis and characterization of silicone oils of different molecular structures.A group contribution function model was established to predict the refractive index. The results showed that refractive index of phenyl silicone oil increased as its phenyl content increased. A linear equation had been established to describe the quantitative relationship between the refractive index and phenyl content.Refractive index values from the group contribution function model showed good consistency with experimental results.

Assessment of Soil Water Content in Field with Antecedent Precipitation Index and Groundwater Depth in the Yangtze River Estuary

To better understand soil moisture dynamics in the Yangtze River Estuary （YRE） and predict its variation in a simple way, a field monitoring experiment was carried out along the north branch of the Yangtze River, where seawater intrusion was strong and salt-water variation is one of the limiting factors of local agriculture. In present paper, relation between antecedent precipitation index （API） and soil water content is studied, and effects of groundwater depth on soil water content was analyzed. A relatively accurate prediction result of soil water content was reached using a neural network model. The impact analysis result showed that the variation of the API was consistent with soil water content and it displayed significant correlations with soil water content in both 20 and 50 cm soil layer, and higher correlation was observed in the layer of 20 cm. Groundwater impact analysis suggested that soil moisture was affected by the depth of groundwater, and was affected more greatly by groundwater at depth of 50 cm than that at 20 cm layer. By introducing API, groundwater depth and temperature together, a BP artificial network model was established to predict soil water content and an acceptable agreement was achieved. The model can be used for supplementing monitoring data of soil water content and predicting soil water content in shallow groundwater areas, and can provide favorable support for the research of water and salt transport in estuary area.

Research on the Contents and Indexes of Reservoir Operational Security

Reservoirs play an important role in the development of economy and society, as well as the maintenance of ecological balance. The reservoir operational security can make every function of reservoirs fully played. This paper makes a systematic analysis on the meaning of reservoir operational security and builds up a framework system of it from the perspective of organization and system. On this3 basis, the paper researches the contents and indexes of reservoir operational security from the microscopic, intermediate and macroscopic aspects. The results of this paper provide a foundation for further research on reservoir operational security management.

Effects of Moisture Content and Plasticity Index on Duncan-Chang Model Parameters of Hydraulic Fill Soft Soil

In order to explore the effects of moisture content and plasticity index on Duncan-Chang model parameters?K,n,?C?and?Rf,?we selected 8 groups of soft soil with water content of 69.1%?-?94.3% and plasticity index of 32.2?-?54.1 for triaxial unconsolidated undrained shear test. The results show that?Cuu,?K?and?n?values all showed a downward trend, and?Rf?variation was not obvious with the increase of moisture content. The variation rule of each parameter is not obvious with the increase of plasticity index. When moisture content is constant,?Cuu?and?n?values do not change much,?K?increases with the increase of plasticity index within the range of 70%?-?80% moisture content, and does not change much with the increase of plasticity index when moisture content is greater than 80%,?Rf?has no obvious rule.?When the plasticity index is constant,?Cuu,?Kand?n?decrease with the increase of moisture content,?Rf?has no obvious rule. The maximum value of?Cuu?is 20.18?kPa, the minimum is 3.72?kPa, and the maximum to minimum ratio is 5.42. The maximum value of?K?is 0.517, the minimum is 0.022, and the maximum to minimum ratio is 23.5. The maximum value of?n?is 1.198, the minimum is 0.150, and the maximum to minimum ratio is 7.99. The maximum value of?Rf?is 0.872, the minimum is 0.679, and the maximum to minimum ratio is 1.28.

Contents Index to Volume 4

Research Papers Generating a multilingual taxonomy based on multilingual terminology clustering Chengzhi ZHANG 2011,4(2):27Construction of an evaluation system for information openness of local governments Fang WANG&Qun GU 2011,4(1):28Real-time virtual reference service based on applicable artificial intelligence technologies:The debut of the robot Xiaotu at Tsinghua University Library

Hyperspectral Inversion of Potassium Content in Apple Leaves Based on Vegetation Index

The aim of this study is to establish the estimation model of potassium content in apple leaves by using vegetation index. A total of 96 fresh apple leaves were collected from 24 orchards in Qixia County, Shandong Province. The spectral reflectance of the leaves was measured by ASD FieldSpec4. The difference vegetation index (DVI), ratio vegetation index (RVI) and normalized vegetation index (NDVI) were used to make the contour map through Matlab platform, and the combination of high correlation wavelength was selected to establish the random forest (RF) regression model of potassium content. The hyperspectral reflectance increased with the increase of leaf potassium content. The correlation between DVI and the content of potassium is higher than NDVI and RVI. The optimal vegetation index was DVI (364,740), the correlation coefficient was 0.5355. The random forest regression model established with DVI selected vegetation index was the best. R2 was 0.8995, RMSE and RE% were 0.0791 and 0.0617 respectively. Using DVI to establish the random forest regression model to reverse the potassium content of apple leaves has achieved good results. It is important to determine the growth status of apple in hyperspectral and to determine the potash fertilizer of apple trees.

Indexing of Content-Based Image Retrieval System with Image Understanding Approach

This paper presents a novel efficient semantic image classification algorithm for high-level feature indexing of high-dimension image database. Experiments show that the algorithm performs well. The size of the train set and the test set is 7 537 and 5 000 respectively. Based on this theory, another ground is built with 12,000 images, which are divided into three classes: city, landscape and person, the total result of the classifications is 88.92%, meanwhile, some preliminary results are presented for image understanding based on semantic image classification and low level features. The groundtruth for the experiments is built with the images from Corel database, photos and some famous face databases.

开采保护层与预抽煤层瓦斯防突效果分析

为比较开采保护层与预抽煤层瓦斯防突效果,以1124(3)运顺开采保护层段和预抽煤层瓦斯段煤巷掘进为试验对象,统计了试验地点煤巷掘进期间残余瓦斯含量、钻屑瓦斯解吸指标K1、钻屑量等防突指标,采用假设检验方法推断了各防突指标是否有差别,分析了开采保护层段和预抽煤层瓦斯段各防突指标产生差别的原因,验证了开采保护层区域防突措施比预抽煤层瓦斯区域防突措施更加安全可靠。

基于超分辨率重建与机器学习的油菜苗情监测方法

为优化养分管理和确保植株正常生长,以无人机遥感技术高效且非破坏采集田间作物苗情信息,监测油菜苗期的叶面积指数(LAI)与叶绿素相对含量(SPAD)。针对无人机因飞行高度与图像分辨率相互制约,监测效率与监测精度难以兼顾的问题,采用超分辨率重建方法,融合较低飞行高度拍摄高分辨率影像,重建较高飞行高度拍摄影像,建模完成后可通过拍摄飞行影像监测LAI和SPAD。试验设置3个氮肥梯度、3个播期、3个种植密度处理,在苗期利用无人机分别采集20m及40m 2个飞行高度的油菜苗影像,采用SRRestnet方法,对40m影像进行超分辨率重建。基于20m、40m及40m重建影像中提取的3种特征组合,利用偏最小二乘回归(PLSR)、随机森林(RF)、支持向量回归(SVR)3种机器学习方法对LAI和SPAD进行监测。结果表明,超分辨率重建后的图像在表型苗情监测中表现出良好效果,PLSR监测LAI、RF监测SPAD的监测精度最高,且40m重建图像的作业效率相比于20m图像提高48.6%。

不同低温循环水暂养时间对克氏原螯虾肌肉品质和健康状况的影响

为探讨低温(5~6℃)循环水暂养时间对克氏原螯虾肌肉品质、健康状况的影响,各处理组随机选取20尾初始体重为(25.28±1.56) g的克氏原螯虾进行低温暂养,对试验起始阶段(对照)与低温暂养15 d、30 d的克氏原螯虾的肌肉营养成分、肌肉氨基酸组成和含量、肌肉离心损失率和蒸煮损失率、肌肉质构特性及肝胰腺抗氧化指标进行分析。结果显示,与试验起始阶段相比,随着低温暂养时间延长至30 d,克氏原螯虾肌肉脂肪含量显著下降(P<0.05);随着暂养时间延长至15 d、30 d,克氏原螯虾肌肉的蛋白质含量显著下降(P<0.05)。与试验起始阶段相比,低温暂养15 d、30 d的克氏原螯虾肌肉中甲硫氨酸含量、精氨酸含量、谷氨酸含量、天冬氨酸含量、丙氨酸含量、甘氨酸含量、酪氨酸含量均无显著变化,而组氨酸含量呈下降趋势,其余氨基酸含量从低温暂养15 d或30 d开始显著上升(P<0.05);必需氨基酸含量、鲜味氨基酸含量和总氨基酸含量整体较为稳定(P>0.05)。与试验起始阶段相比,低温暂养15 d、30 d的克氏原螯虾肌肉的离心损失率、蒸煮损失率的变化不显著(P>0.05),肌肉的硬度从低温暂养15 d开始显著下降,肌肉的恢复性在低温暂养30 d时显著下降(P<0.05),肌肉的咀嚼性、弹性无显著变化(P>0.05)。与试验起始阶段相比,低温暂养15 d、30 d的克氏原螯虾肝胰腺中谷胱甘肽过氧化物酶活性呈显著下降趋势(P<0.05),并在低温暂养30 d时降至最低值,显著低于试验初始阶段。研究结果显示,在低温下暂养30 d不会显著影响克氏原螯虾的肌肉品质和健康状况,后期可调整暂养参数以完善养殖技术。

机器学习结合高光谱植被指数与SPAD值估算冬小麦氮含量

冬小麦叶片氮含量与叶片光合作用和营养状况密切相关,直接影响植株生长发育,而茎秆中的氮含量与茎秆中纤维素、半纤维素和木质素的比例和含量密切相关,直接影响茎秆质量及植株的抗倒伏能力。然而,有关对冬小麦茎秆氮含量估算研究较为有限,限制了从氮含量角度判断茎秆质量及对倒伏的预测能力。为精准估算冬小麦不同器官(叶片、茎秆)氮含量,该研究通过2年田间试验,获取冬小麦4个关键生育期(拔节期、抽穗期、开花期、灌浆期)和3种施氮水平条件下(N1、N2和N3)的冠层光谱反射率、叶片、茎秆氮含量及叶片SPAD(soil and plant analyzer development,SPAD)值。分析了不同生育期和施氮水平条件下高光谱植被指数对叶片和茎秆氮含量的敏感性,并结合5种常用的机器学习算法:随机森林回归(random forest regression,RFR)、支持向量回归(support vector regression,SVR)、偏最小二乘回归(partial least squares regression,PLSR)、高斯过程回归(gaussian process regression,GPR)、深度神经网络回归(deep neural networks,DNN)构建冬小麦叶片和茎秆氮含量估算模型。结果表明:高光谱植被指数对叶片和茎秆氮含量的敏感性受到生育期和施氮水平的影响。在灌浆期,最佳植被指数双峰冠层植被指数DCNI(double-peak canopy nitrogen index)对叶片氮含量的敏感性最高,R^(2)为0.866。对茎秆氮含量,在抽穗期的敏感性最高,最佳植被指数归一化叶绿素比值指数NPQI(normalized phaeophytinization index)与氮含量决定系数R^(2)=0.677。施氮水平的提升增加了光谱植被指数对茎秆氮含量的敏感性。结合SPAD值的机器学习算法提升了氮含量的估算精度,对叶片氮含量,在不同生育期和施氮水平条件下估算精度提升了1%~7%,其中在全生育期的归一化均方根误差NRMSE从0.254降低到0.214,抽穗期的NRMSE提升最大,从0.201降低到0.128。对茎秆氮含量,全生育期的NRMSE从0.443降低到0.400,抽穗期的NRMSE变化最大,从0.323降低到0.268。在全生育期,结合SPAD值的DNN模型对叶片(R^(2)=0.782、NRMSE=0.214)和茎秆(R^(2)=0.802、NRMSE=0.400)氮含量的估算精度最佳。研究说明,SPAD值与光谱植被指数结合有利于提升冬小麦不同生育期和施氮水平条件下叶片和茎秆氮含量的估算精度。

基于TDM-PMC指数模型的省级“十四五”中医药文化政策文本分析

基于省级“十四五”中医药发展规划中的文化政策,在政策文本数据挖掘的基础上,建立中医药文化政策TDM-PMC指数模型,对我国多个省份“十四五”中医药文化政策进行内容分析与量化评价,总结探讨我国中医药文化政策的不足之处并提出优化策略,为推动中医药文化建设提供参考。研究发现,我国中医药文化政策省域发展失调,政策内部结构均衡性不足;中医药文化发展的经济支撑有待加强,人才培育有待完善;中医药文化发展目标清晰度不高,政策干预强度不足。需要提高各省份中医药文化政策水平,补齐中医药文化政策短板;加大中医药文化发展的经济支撑力度,完善中医药文化科普人才培育;提升中医药文化政策内容清晰度,细化中医药文化发展目标。