基于Copula函数的华南台风灾情重现期研究

利用1981-2014年华南台风灾情数据，选取受灾人口、农作物受灾面积和直接经济损失，应用Copula函数理论，计算灾情重现期，分析台风灾害的灾情.首先，借助Clayton Copula函数构造三变量的联合分布，计算单变量重现期、联合重现期及同现重现期，并求出该重现期下的设计值.计算结果表明联合重现期的设计值要优于单变量重现期和同现重现期的设计值．因此，选取联合重现期的设计值作为防灾标准的最优参考，并将联合重现期记为灾情重现期．然后，计算2015-2017年登陆华南台风灾害的灾情重现期，并对台风灾害的灾情进行分析．发现台风灾情重现期越长的台风造成的灾情越严重．最后，利用灾情重现期与致灾重现期对台风灾害的发生频率作综合性分析，可以为台风灾害的风险评估提供一种新思路．     

一类零膨胀广义线性模型极大似然估计的相合性与渐近正态性

讨论了响应变量为单参数指数族且在零点处膨胀的广义线性模型的大样本性质，对其参数进行了极大似然估计，给出了一些正则条件.基于所提出的正则条件，证明了模型参数极大似然估计的相合性与渐近正态性.     

Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study

Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.     

On the effect of fractional statistics on quantum ion acoustic waves

In this paper, I study the effect of a small deviation from the Fermi–Dirac statistics on the quantum ion acoustic waves. For this purpose, a quantum hydrodynamic model is developed based on the Polychronakos statistics, which allows for a smooth interpolation between the Fermi and Bose limits, passing through the case of classical particles. The model includes the effect of pressure as well as quantum diffraction effects through the Bohm potential. The equation of state for electrons obeying fractional statistics is obtained and the effect of fractional statistics on the kinetic energy and the coupling parameter is analyzed. Through the model, the effect of fractional statistics on the quantum ion acoustic waves is highlighted, exploring both linear and weakly nonlinear regimes. It is found that fractional statistics enhance the amplitude and diminish the width of the quantum ion acoustic waves. Furthermore, it is shown that a small deviation from the Fermi–Dirac statistics can modify the type structures, from bright to dark soliton. All known results of fully degenerate and non-degenerate cases are reproduced in the proper limits.     

Definition and detection of data-based uniqueness in evaluating bilinear (two-way) chemical measurements

Multivariate curve resolution methods, frequently used in analyzing bilinear data sets, result in ambiguous decomposition in general. Implementing the adequate constraints may lead to reduce the so-called rotational ambiguity drastically, and in the most favorable cases to the unique solution. However, in some special cases, non-negativity constraint as minimal information of the system is a sufficient condition to resolve profiles uniquely. Although, several studies on exploring the uniqueness of the bilinear non-negatively constrained multivariate curve resolution methods have been made in the literature, it has still remained a mysterious question. In 1995, Manne published his profile-based theorems giving the necessary and sufficient conditions of the unique resolution. In this study, a new term, i.e., data-based uniqueness is defined and investigated in details, and a general procedure is suggested for detection of uniquely recovered profile(s) on the basis of data set structure in the abstract space. Close inspection of Borgen plots of these data sets leads to realize the comprehensive information of local rank, and these argumentations furnish a basis for data-based uniqueness theorem. The reported phenomenon and its exploration is a new stage (it can be said fundament) in understanding and describing the bilinear (matrix-type) chemical data in general.     

纸页受力微损伤演化过程的声发射及多元统计特征

纸页受载后的损伤断裂行为涉及其使用性能,对其损伤断裂过程的研究不仅有助于揭示纸页破坏行为的物理本质,而且有助于对纸页质量及其生产、加工工艺作出更加科学合理的评定。本文基于声发射(Acoustic Emission,AE)实验研究纸页内部微损伤演化过程,给出了评估纸页宏观损伤断裂性能的定量描述方法。首先,根据AE信号与微损伤事件之间存在本质上的关联性,通过采集和观测纸页试样受载过程中的AE信号来研究纸页损伤断裂的基本特征;其次,针对所采集AE信号的数据量大、蕴含信息丰富导致数据分析和处理困难的特点,本文采用多元随机变量的分析方法。利用概率熵和Andrews曲线法等统计分析手段对AE数据展开研究分析,并最终利用一条损伤状态轨迹曲线实现了对纸页微损伤演化过程的完整宏观描述。结果表明,纸页微损伤演化过程呈现明显阶段性变化特征;Andrews曲线的聚类结果有效地区分了不同损伤阶段的相似性和差异性,同时,不同损伤阶段中纸样的微观形貌观测提供了实验性的证据。本文以一种典型的牛皮箱板纸为试件,验证了上述方法的有效性。     

基于深圳市出租车轨迹数据的高效益寻客策略研究

出租车作为城市公共交通的重要补充形式,在居民日常出行中发挥着重要作用.然而,客源时空分布不均衡导致了出租车空载率高、寻客难度大等问题,降低了出租车的运营效率.随着ITS(intelligent transport system)技术的发展,越来越多的学者将出租车寻客模式作为其研究点,目前尚缺乏对基于寻客效益指标的寻客策略方法的研究.为了提高出租车寻客效益,提出了基于寻客效益指标模型的时空分析方法,将出租车载客态单位时间收入E及相邻空载态寻客时间T相结合作为寻客效益评价指标,并采用数理统计与地理统计相结合的方法,对高效益客源的时空分布特征进行研究.采用深圳市2011年4月18—24日一周内13 798辆出租车的GPS轨迹数据,分析了深圳市出租车的运营特点及人们出行需求的时空分布特征.结果表明:该方法能够较好地反映高效益客源的时空分布特征,为出租车高效益寻客提供辅助决策支持,也为出租车高效运营提供了新的视角.     

Nanogram/mL detection of nortriptyline: Preparation of a molecularly imprinted polymer for spectrophotometric determination of nortriptyline based on multivariate optimization methods

In this work, the molecularly imprinted polymer was used as a selective sorbent in solid‐phase extraction method for the spectrophotometric determination of nortriptyline at 239 nm. Molecularly imprinted polymer was synthesized by pyrrole as a functional monomer in the presence of nortriptyline as a template. Several factors, consist of the concentration of the monomer to template ratio, amount of initiator, stirring rate, reaction time, the pH of the buffer solution, amount of sorbent, loading time, shaking rate of loading, extraction time, and shaking rate of extraction were evaluated due to their effectiveness in the preparation and extraction capability of molecularly imprinted polymer. Multivariate optimization methods, such as Plackett‐Burman and central composite designs, were employed to find and optimize the significant factors. Under the selected optimal conditions, molecularly imprinted polymer showed a linear range from 0.1 to 100 µmol/L (0.026 to 26 µg/mL) nortriptyline, a detection limit of 10.3 nmol/L (2.7 ng/mL), a highly repeatable (relative standard deviation of 3.7%) and reproducible response (relative standard deviation of 4.6%), and a good selectivity in the presence of structurally related molecules. Furthermore, molecularly imprinted polymer showed high extraction efficiency and was successfully used for the determination of nortriptyline in real samples.     

An interview with Sam C. Saunders

Sam C. Saunders, the son of Elizabeth Cundiff and Winston E. Saunders, was born in Richland, OR, on February 24, 1931. The family moved to La Grande, OR, in 1944, where Sam completed high school and two years at Eastern Oregon College. He then received the BSc degree in Mathematics from the University of Oregon, Eugene, OR, in 1952, and he attended the University of Washington, Seattle, WA, receiving a PhD degree under Z. W. Birnbaum. After graduating, he accepted employment at the Boeing Company in its Mathematical Services Unit and, in 1972, a position as a Full Professor at Washington State University, Pullman, WA, from which he retired in 1996.