参数方程所确定的函数的高阶导数的一种逐次求导法

求由参数方程所确定的函数的高阶导数，本文提出了一种较为直观、简便的逐次求导法。     

基于非负矩阵分解的隐含语义图像检索

提出了一种基于非负矩阵分解(Non-negative Matrix Factorization,NMF)的隐含语义索引(Latent Semantic Indexing,LSI)模型用于图像检索.应用NMF训练算法构造了一个语义空间,将查询图像和原型图像都投影到该空间以获得语义特征,在此空间中进行相似性的度量并将距离最近的图像返回给用户.与已有两种检索模型的实验结果对比表明,所提出模型是有效的.     

层合圆板轴对称自由振动问题的精确解

本文从三维弹性力学基本方程出发,抛弃任何有关位移模式和应力分布的假设,建立了横观各向同性层合圆板轴对称自由振动问题的状态方程。给出了本问题的精确解式。此解满足弹性力学全部方程,并计及了所有独立的弹性常数。无论层数多少,最后都归结为解二元一次联立代数方程。数值结果和Reissner理论、Mindlin理论以及有关文献作了对比,结果令人满意。     

硬脂酸/插层高岭石复合相变材料的制备和热性能研究

高岭石(K)是一种常见的黏土矿物,具有低成本、阻燃、多层结构等固有优点。本文采用真空浸渍法将硬脂酸(SA)吸附到插层高岭石(IKL)和二甲基亚砜(DMSO)复合物的孔隙中来制备用于储热的复合相变材料。通过X射线衍射(XRD)、红外光谱(FT-IR)、热重分析(TG)、差示扫描量热法(DSC)、扫描电子显微镜(SEM)和比表面积分析仪(BET)表征了复合材料的热性能、结构和主要组分。由于插层复合物形成后高岭石层间距增大,对SA的吸附率达到32.3%,熔化和凝固潜热值分别为43.36 J/g和43.16 J/g,熔化和凝固温度分别为51.9℃和51.7℃。此外,该复合相变材料具有较好的热稳定性。由于SA/IKL复合相变材料具有高吸附量、高潜热、良好的热稳定和低成本等优点,因此,其在实际的应用中具有潜在的价值。     

磷光碳点粉末的合成及其在抗背景干扰的潜指纹成像中的应用

以乙二胺、磷酸和硼酸为反应物,采用水热法制备了荧光碳点(CDs)溶液,进一步加热水热反应溶液,获得了磷光CDs粉末。利用X射线衍射(XRD)、透射电子显微镜(TEM)、X射线光电子能谱(XPS)、紫外可见(UV-Vis)吸收光谱和光致发光光谱等对CDs的结构、形貌和尺寸、表面基团与化学组成以及光学特性进行了表征。结果表明,合成的CDs粉末为无定型碳,形貌为单分散的近球形,尺寸分布在3.78~7.64 nm范围之内,其表面存在大量的N、P和B杂原子基团。CDs粉末在365 nm紫外光照射下呈现明亮的蓝色荧光,关闭激发光后,呈现长达10 s的绿色室温磷光。该CDs粉末可作为指纹试剂应用于具有复杂背景图案且有强荧光发射基质表面的潜指纹(LFPs)显现。显现后的LFPs在激发光关闭后均呈现明亮完整的磷光指纹图谱,指纹细节特征清晰可辨,有效消除了背景图案与背景荧光干扰。同时,制备的CDs粉末对不同干扰背景客体表面老化7 d的LFPs也能够显现出清晰可识别的磷光指纹图谱。     

Energy consumption for creep fracture of metallic materials

The energy conservation law is applied to formulate the ductile and brittle creep fracture criterion for metallic materials. The criterion contains a summary of heat and latent energies. Assuming that the heat energy is given out so it has no effect on the fracture process, the ductile creep fracture criterion is simplified. To take into account the evaluation of the damage state of materials the compressibility condition is introduced and the brittle creep fracture law is formulated.     

中国投资者多角度舆情分析及其在股市预测中的作用

股市中存在与投资者舆情有关的非理性现象，舆情与股市关系的量化研究对发掘股市规律和辅助投资预测具有重要意义.本文基于论坛中的投资者发言，创新性地建立CNN-TLDA混合模型对舆情进行多角度量化分析，从积极度和关注主题两方面探究投资者舆情和股市的相互影响关系，并基于长短时记忆(LSTM)网络对舆情在股市预测中的作用进行探讨.研究表明:中国股市投资者普遍悲观，投资者乐观度和关注主题都与股市高度相关.多角度舆情分析使预测误差下降至41%.研究成果能够辅助投资者的投资决策，也能为股市中个体投资者舆情的分析与利用提供科学参考.     

基于密度Canopy的评论文本主题识别方法

融合Sentence-BERT和LDA的评论文本主题识别（SBERT-LDA）方法，将LDA的主题数作为K-means算法中的k值，导致算法可解释性较差、主题一致性较低。为了解决上述问题，提出基于密度Canopy的SBERT-LDA优化方法（SBERT-LDA-DC），利用密度Canopy改进K-means算法。实验结果表明，提出的方法在一致性指标上要优于使用K-means以及K-means++对特征向量聚类的同类方法；与SBERT-LDA方法相比，在1 852条戏剧评论数据集上，一致性指标值提高了22.9%。因此，所提出的SBERT-LDA-DC方法是有效的，对产品或服务提供者更好地了解用户意见、完善自身产品或提升服务水平提供了新方法，具有较强的实际应用价值。     

Model selection for partial least squares calibration and implications for analysis of atmospheric organic aerosol samples with mid‐infrared spectroscopy

In developing partial least squares calibration models, selecting the number of latent variables used for their construction to minimize both model bias and model variance remains a challenge. Several metrics exist for incorporating these trade‐offs, but the cost of model parsimony and the potential for underfitting on achievable prediction errors are difficult to anticipate. We propose a metric that penalizes growing model variance against decreasing bias as additional latent variables are added. The magnitude of the penalty is scaled by a user‐defined parameter that is formulated to provide a constraint on the fractional increase in root mean square error of cross‐validation (RMSECV) when selecting a parsimonious model over the conventional minimum RMSECV solution. We evaluate this approach for quantification of four organic functional groups using 238 laboratory standards and 750 complex atmospheric organic aerosol mixtures with mid‐infrared spectroscopy. Parametric variation of this penalty demonstrates that increase in prediction errors due to underfitting is bounded by the magnitude of the penalty for samples similar to laboratory standards used for model training and validation. Imposing an ensemble of penalties corresponding to a 0–30% allowable increase in RMSECV through sum of ranking differences leads to the selection of a model that increases the actual RMSECV up to 20% for laboratory standards but achieves an 85% reduction in the mean error in predicted concentrations for environmental mixtures. Partial least squares models developed with laboratory mixtures can provide useful predictions in complex environmental samples, but may benefit from protection against overfitting. © 2015 The Authors. Journal of Chemometrics published by John Wiley & Sons Ltd.     

Soluble polymeric ligands for metal complexation and catalyst recovery

Soluble polymers that bind metals and that in turn can be separated from other components of a reaction mixture are described. The polymers used include derivatives of acrylamides, acrylates, polystyrene and other polymers. Both sequestration of trace metals and recovery of homogeneous catalysts is discussed. Separation methods using liquid/liquid mixtures that are monophasic during a reaction but biphasic during a separation are emphasized.