PSO-LSSVM对LIBS定量分析精度的提高

针对土壤定量分析受基体效应影响大，LIBS定量分析精度不佳等问题，采用粒子群算法对LSSVM进行优化，提高模型的精确度。选取Pb Ⅰ 405.78 nm和Cr Ⅰ 425.44 nm作为分析谱线进行分析。采集十二个不同浓度样品的特征光谱，每个浓度样品在不同点采集20组数据，将其中17组数据设为训练集，3组数据设为预测集，用LSSVM和PSO-LSSVM两种方法建立定标模型。对比两种模型的拟合相关系数（R2）、训练集均方根误差（RMSEC）和预测集均方根误差(RMSEP)。由于自吸收效应的影响，随着浓度的增加，预测值逐渐低于实际值，LSSVM定标模型的拟合程度较低，无法达到实验要求，模型性能有待提高。利用粒子群算法对LSSVM的模型参数惩罚系数和核函数参数进行优化，得到最佳的参数组合，Pb元素为(8 096.8, 138.865 7)，Cr元素为(4 908.6, 393.563 5)，用最佳的参数组合构建LSSVM的定标模型。相比于LSSVM，PSO-LSSVM定标模型的精确度更高，Pb和Cr元素的R2提高到了0.982 8和0.985 0，拟合效果明显提升。Pb和Cr元素的训练集均方根误差由0.026 0 Wt%和0.027 2 Wt%下降到0.022 4 Wt%和0.019 1 Wt%，预测集均方根误差由0.101 8 Wt%和0.078 8 Wt% 下降到0.045 8 Wt%和0.042 0 Wt%，模型的稳定性进一步提高。说明PSO-LSSVM算法能够更好地降低土壤基体效应和自吸收效应带来的影响，提高分析结果的精确度与稳定性。     

对称向量拟均衡问题有效解的存在性

利用标量化方法建立对称向量拟均衡问题有效解的存在性定理。作为标量化方法的应用，利用这一方法得到向量变分不等式和拟向量变分不等式有效解的存在性定理。     

Semi-concurrent vector fields in Finsler geometry

In the present paper, we give an answer to a question which is closely related to doubly warped product of Finsler metrics: ‘‘For each n, is there an n-dimensional Finsler manifold $(M,F)$, admitting a non-constant smooth function f on M such that $\frac{\partial f}{\partial x^i}\frac{\partial g^{ij}}{\partial y^k}=0$?”. We relate the preceding mentioned condition to different concepts appeared and studied in Finsler geometry. We introduce and investigate the notion of a semi concurrent vector field on a Finsler manifold. We show that some special Finsler manifolds admitting such vector fields turn out to be Riemannian. We prove that Tachibana's characterization of Finsler manifolds admitting a concurrent vector field leads to Riemannian metrics. Various examples for conic Finsler spaces that admit semi-concurrent vector field are presented.     

Free boundary problem for a fully nonlinear and degenerate parabolic equation in an angular domain

This paper concerns with the problem of how to running an insurance company to maximize his total discounted expected dividends. In our model, the dividend rate is limited in $[0,M]$ and the company is allowed to transfer any proportion of risk by reinsuring. So there are two strategies which we call dividend strategy and reinsurance strategy. The objective function and the corresponding optimal two strategies are the solution and the two free boundaries of the following Barenblatt parabolic equation

$v_t?\underset{0\le a\le 1}{\max }?(\frac{1}{2}{a}^2{\sigma }^2{v}_{xx}+a\mu v_x)+cv?\underset{0\le l\le M}{\max }?[(1?v_x)l]=0$

under certain boundary conditions on an angular domain

$Q_T=\{(x,t)|0<x<Mt,0<t\le T\}.$

The main effort is to analyze the properties of the solution and the free boundaries to show the optimal decision for the insurance company.     

Convergence of solutions for the fractional Cahn–Hilliard system

This paper deals with the Cauchy–Dirichlet problem for the fractional Cahn–Hilliard equation. The main results consist of global (in time) existence of weak solutions, characterization of parabolic smoothing effects (implying under proper condition eventual boundedness of trajectories), and convergence of each solution to a (single) equilibrium. In particular, to prove the convergence result, a variant of the so-called ?ojasiewicz–Simon inequality is provided for the fractional Dirichlet Laplacian and (possibly) non-analytic (but $C^1$) nonlinearities.     

Dose‐dependent exposure profile and metabolic characterization of notoginsenoside R1 in rat plasma by ultra‐fast liquid chromatography–electrospray ionization–tandem mass spectrometry

Notoginsenoside R₁ (NGR₁), a diagnostic protopanaxatriol‐type (ppt‐type) saponin in Panax notoginseng, possesses potent biological activities including antithrombotic, anti‐inflammatory, neuron protection and improvement of microcirculation, yet its pharmacokinetics and metabolic characterization as an individual compound remain unclear. The aim of this study was to investigate the exposure profile of NGR₁ in rats after oral and intravenous administration and to explore the metabolic characterization of NGR₁. A simple and sensitive ultra‐fast liquid chromatographic–tandem mass spectrometric method was developed and validated for the quantitative determination of NGR₁ and its major metabolites, and for characterization of its metabolic profile in rat plasma. The blood samples were precipitated with methanol, quantified in a negative multiple reaction monitoring mode and analyzed within 6.0 min. Validation parameters (linearity, precision and accuracy, recovery and matrix effect, stability) were within acceptable ranges. After oral administration, NGR₁ exhibited dose‐independent exposure behaviors with t_1/2 over 8.0 h and oral bioavailability of 0.25–0.29%. A total of seven metabolites were characterized, including two pairs of epimers, 20(R)‐notoginsenoside R₂/20(S)‐notoginsenoside R₂ and 20(R)‐ginsenoside Rh₁/20(S)‐ginsenoside Rh₁, with the 20(R) form of saponins identified for the first time in rat plasma. Five deglycometabolites were quantitatively determined, among which 20(S)‐notoginsenoside R₂, ginsenoside Rg₁, ginsenoside F₁ and protopanaxatriol displayed relatively high exploration, which may partly explain the pharmacodynamic diversity of ginsenosides after oral dose.     

基于计算机视觉技术的茶叶品质随机森林感官评价方法研究

为弥补茶叶品质感官审评存在的缺陷，利用计算机视觉技术对茶叶品质进行快速无损评价研究。以碧螺春绿茶为对象，依据专家感官审评结果，将茶样分成4个等级；采用中值滤波及拉普拉斯算子对茶样图像进行预处理，并提取预处理后的茶样图像的颜色特征和纹理特征以表征茶叶图像的外形特征，利用随机森林算法对茶叶外形特征属性进行重要性排序；筛选出重要性较大的特征及随机森林算法中最优的决策树棵数建立感官评价模型，并与建立的支持向量机(SVM)模型性能相比较。结果表明：色调均值、色调标准差、绿体均值、平均灰度级、饱和度均值、红体均值、饱和度标准差、亮度均值、一致性等9个特征属性的重要性较大，且与感官审评特征描述结果相一致；当采用优选出的9个重要性较大的特征及决策数棵数为500时，建立的模型性能最优，模型总体判别率为95.75%，Kappa系数为0.933，OOB误差为5%，较SVM模型分别提高了3.5%，0.066，优选的9个重要性较大的图像特征与感官审评特征描述相一致。研究表明：利用随机森林方法筛选出对茶叶外形特征属性贡献最大的少数几个特征建立模型，模型性能就能达到很好的识别效果，模型得到简化，同时模型精度和稳定性都高于其他方法。