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.

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.

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.

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

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.

Surface and Content Validity of the Mentoring Function Scale for Novice Nurses

This study aimed to examine the surface and content validity of the Mentoring Function Scale for Novice Nurses, used to assess the mentoring of entry-level nurses, and to refine the scale items. In Study 1, six nurse education researchers, selected using convenience sampling, with five or more years of nursing experience and experience teaching novice nurses, were invited to an expert meeting in July 2015. A group interview was conducted that lasted approximately 120 minutes. Study 2 examined the content validity index. Between September and November 2015, we distributed a self-administered questionnaire survey to 11 participants selected by convenience sampling. The participants included five nurse education researchers with a minimum of five years of nursing experience and experience teaching novice nurses, as well as six clinical nurses with a master’s degree or higher. Finally, 81 questionnaire items were retained from the initial 125 items. The 81-item Mentoring Function Scale for Novice Nurses had higher content validity than the original scale. To further increase the scale’s applicability, future studies should assess its reliability, construct validity, and criterion-related validity.

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.

欧盟数字政策的内容框架、创新路径及启示——以数字经济和社会指数为锚点

[研究目的]欧盟以数字经济和社会指数作为数字政策的锚点,对欧盟及成员国的数字政策进行统筹规划。基于数字政策内容框架,欧盟系统地对欧盟范围内的数据等数字资源进行协调、组织与控制。探讨欧盟相关数字政策内容与实践路径可为欧盟后续数字政策预测,以及我国数字政策设计提供借鉴。[研究方法]面向数字经济和社会指数,结合网络调研、实地调研与内容分析,基于制度文本分析框架,从目标理念、基本制度两个层面,从数字技能、数字基础设施、业务数字化与数字公共服务四个维度,探究欧盟数字政策的内容框架与创新路径。[研究结果/结论]借鉴欧盟数字政策的内容框架及创新路径,我国可考虑构建与完善中国特色的数字发展指标体系,面向国内国际“双循环”需求设计数字理念,基于区域发展不平衡现状精准实施数字政策,聚焦数智技术前沿应用落地实践数字政策。

国外索引研究进展:以The Indexer为例

运用文献计量方法和内容分析方法,对2000-2008年间The Indexer刊登的论文进行统计分析,并对其研究类别进行了划分和汇总,通过对该刊文献的分析了解国外索引研究的进展。笔者在统计数据和文献内容分析的基础上,总结了国外索引研究的主要特点,并对国外索引研究趋势进行了梳理和阐述。

生成式人工智能赋能图书内容索引编制研究

生成式人工智能技术的快速发展为图书内容索引编制带来了革命性的变革。文章介绍了生成式人工智能的基本原理和技术,系统分析了传统图书内容索引编制方法的局限性以及未来发展面临的挑战,在进一步探析生成式人工智能技术在图书内容分析应用的基础上,深入论述了生成式人工智能技术赋能图书内容索引编制的具体表现,包括提高索引编制的准确性和效率、增强索引编制的个性化和智能性、实现多语种和多格式的兼容性和互通性。最后,为了能更好地利用该技术为图书生成高质量的内容索引,文章给出了利用生成式人工智能技术编制图书内容索引的具体过程,并从确保高质量训练数据、坚持多样化输入、选择合适模型并进行调优、进行必要人工干预与验证、注重安全与隐私保护等方面提出了具体保障策略,这将为生成式人工智能技术在图书内容索引编制中的应用提供重要参考和指导。

含砂量和细度模数双指标在广东某回填用海砂矿区圈矿和资源量估算中的应用

海砂圈矿指标是海砂资源储量估算的核心内容,对海砂资源的勘查、出让、开采和监管等工作均有十分重要的意义。本文在总结大量海砂勘查工作实践经验的基础上,提出了在海砂勘查工作中采用含砂量和细度模数双指标进行圈矿,并以广东某海域回填用海砂矿区为例,对比了单指标(含砂量≥50%)与双指标(含砂量≥50%,细度模数≥0.7)圈矿的实际应用效果。结果表明,仅采用单指标(含砂量≥50%)圈矿,容易造成估算的资源量偏大;采用双指标(含砂量≥50%,细度模数≥0.7)圈矿,不仅要求含砂量达标,而且要求砂的粗度达标,可有效避免粒度极细的砂被大量圈矿,保证了所圈定的海砂矿体的开采价值,较单指标圈矿更加科学和具有现实意义。

木香显微特征指数与化学成分的相关性研究

【目的】分析木香横切面油室数量、韧皮部占比与木香烃内酯和去氢木香内酯含量的相关性,及粉末特征中菊糖数、导管数与多糖含量的相关性,探索木香“辨状论质”的科学依据。【方法】采用横切面永久制片法、水合氯醛装片法、计数分析法对木香油室、菊糖和导管的显微特征常数值进行测定,分别采用高效液相色谱法和苯酚-硫酸法对木香烃内酯和去氢木香内酯含量、多糖含量进行测定,将两组数据用统计方法进行相关性分析。【结果】木香横切面单位面积油室数、韧皮部单位面积油室数与木香烃内酯和去氢木香内酯含量之间有显著的正相关关系;木香粉末中菊糖数与木香多糖含量存在显著的正相关关系;导管数与多糖含量之间无相关关系。【结论】初步建立了一种基于木香显微特征常数测定的中药材质量评价新方法及新技术,可为木香的质量控制提供新的技术手段。

基于植被指数特征优选的冬小麦叶片含水量估算

为进一步提升利用高光谱数据快速监测叶片含水量的能力,以关中地区冬小麦为研究对象,分别获取2022和2023年孕穗期、抽穗期及灌浆期冬小麦叶片含水量,并同步监测叶片高光谱信息。通过波段组合的形式构建植被指数,并利用相关性分析进行初步筛选,再以ReliefF算法优选得到输入特征变量,然后分别利用随机森林(random forest,RF)、长短期记忆(long short-term memory,LSTM)网络和基于粒子群(particle swarm optimization,PSO)优化的反向传播神经网络(back propagation neural network,BPNN)构建冬小麦叶片含水量估算模型,并进行精度评价。结果表明,通过相关性分析与ReliefF算法结合优选变量,能够较单独通过相关分析明显提升LSTM和PSO-BPNN模型的建模精度,但对RF模型则无法优化变量。相关性分析与ReliefF结合后PSO-BPNN模型在各生育时期均取得最佳预测结果,其中孕穗期、抽穗期和灌浆期验证集r2分别为0.816、0.736和0.806,RMSE分别为0.546%、0.899%和1.531%,NRMSE分别为0.681%、1.195%和2.185%。由此可见,在相关分析的基础上,通过ReliefF算法优选特征变量能够提升特定模型对冬小麦叶片含水量的估算精度,其中对PSO-BPNN模型的效果最好。

Influence of flux composition on microstructure and oxygen content of low carbon steel weldments in submerged arc welding

This study has been conducted to evaluate the influence of flux composition on the microstructure and oxygen content of the low carbon steel weldments using developed agglomerated fluxes.Ca_F2,FeMn and NiO were added to the CaO-SiO_2-Al_2O_3 base fluxes in the varying amount of 2%-8% to examine the various elements transferred to the weldments.The microstructure obtained was a mixture of pearlite and ferrite contents.This study reveals that CaF_2 and Fe Mn both are having significant effect on pearlite percentage while CaF_2 and NiO are significant for oxygen transfer in the welds.The interaction effects of CaF_2 and Fe Mn and CaF_2 and Ni O are also significant to the microstructure of the welds.The fluxes were designed using response surface methodology( RSM) and were developed by agglomeration technique.

Derivation of salt content in salinized soil from hyperspectral reflectance data: A case study at Minqin Oasis, Northwest China

Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced technologies are used to efficiently and accurately assess the status of salinization processes. Case studies to determine the relations between particular types of salinization and their spectral reflectances are essential because of the distinctive characteristics of the reflectance spectra of particular salts. During April 2015 we collected surface soil samples(0–10 cm depth) at 64 field sites in the downstream area of Minqin Oasis in Northwest China, an area that is undergoing serious salinization. We developed a linear model for determination of salt content in soil from hyperspectral data as follows. First, we undertook chemical analysis of the soil samples to determine their soluble salt contents. We then measured the reflectance spectra of the soil samples, which we post-processed using a continuum-removed reflectance algorithm to enhance the absorption features and better discriminate subtle differences in spectral features. We applied a normalized difference salinity index to the continuum-removed hyperspectral data to obtain all possible waveband pairs. Correlation of the indices obtained for all of the waveband pairs with the wavebands corresponding to measured soil salinities showed that two wavebands centred at wavelengths of 1358 and 2382 nm had the highest sensitivity to salinity. We then applied the linear regression modelling to the data from half of the soil samples to develop a soil salinity index for the relationships between wavebands and laboratory measured soluble salt content. We used the hyperspectral data from the remaining samples to validate the model. The salt content in soil from Minqin Oasis were well produced by the model. Our results indicate that wavelengths at 1358 and 2382 nm are the optimal wavebands for monitoring the concentrations of chlorine and sulphate compounds, the predominant salts at Minqin Oasis. Our modelling provides a reference for future case studies on the use of hyperspectral data for predictive quantitative estimation of salt content in soils in arid regions. Further research is warranted on the application of this method to remotely sensed hyperspectral data to investigate its potential use for large-scale mapping of the extent and severity of soil salinity.

Monitoring Soil Salt Content Using HJ-1A Hyperspectral Data: A Case Study of Coastal Areas in Rudong County, Eastern China

Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of mapping soil salt content. This study tested a new method for predicting soil salt content with improved precision by using Chinese hyperspectral data, Huan Jing-Hyper Spectral Imager(HJ-HSI), in the coastal area of Rudong County, Eastern China. The vegetation-covered area and coastal bare flat area were distinguished by using the normalized differential vegetation index at the band length of 705 nm(NDVI705). The soil salt content of each area was predicted by various algorithms. A Normal Soil Salt Content Response Index(NSSRI) was constructed from continuum-removed reflectance(CR-reflectance) at wavelengths of 908.95 nm and 687.41 nm to predict the soil salt content in the coastal bare flat area(NDVI705 < 0.2). The soil adjusted salinity index(SAVI) was applied to predict the soil salt content in the vegetation-covered area(NDVI705 ≥ 0.2). The results demonstrate that 1) the new method significantly improves the accuracy of soil salt content mapping(R2 = 0.6396, RMSE = 0.3591), and 2) HJ-HSI data can be used to map soil salt content precisely and are suitable for monitoring soil salt content on a large scale.