Goodness-of-Fit Test for Non-Stationary and Strongly Dependent Samples

In this article we improve a goodness-of-fit test, of the Kolmogorov-Smirnov type, for equally distributed- but not stationary-strongly dependent data. The test is based on the asymptotic behavior of the empirical process, which is much more complex than in the classical case. Applications to simulated data and discussion of the obtained results are provided. This is, to the best of our knowledge, the first result providing a general goodness of fit test for non-weakly dependent data.

Asymptotic Extremal Distribution for Non-Stationary, Strongly-Dependent Data

Fisher-Tippet-Gnedenko classical theory shows that the normalized maximum of n iid random variables with distribution F belonging to a very wide class of functions, converges in law to an extremal distribution H, that is determined by the tail of F. Extensions of this theory from the iid case to stationary and weak dependent sequences are well known from the work of Leadbetter, Lindgreen and Rootzén. In this paper, we present a very simple class of random processes that runs from iid sequences to non-stationary and strongly dependent processes, and we study the asymptotic behavior of its normalized maximum. More interesting, we show that when the process is strongly dependent, the asymptotic distribution is no longer an extremal one, but a mixture of extremal distributions. We present very simple theoretical and simulated examples of this result. This provides a simple framework to asymptotic approximations of extremes values not covered by classical extremal theory and its well-known extensions.

Fluctuations and pseudo long range dependence in network flows: A non-stationary Poisson process model

In the study of complex networks （systems）, the scaling phenomenon of flow fluctuations refers to a certain powerlaw between the mean flux （activity） （Fi） of the i-th node and its variance σi as σi α （Fi）α Such scaling laws are found to be prevalent both in natural and man-made network systems, but the understanding of their origins still remains limited. This paper proposes a non-stationary Poisson process model to give an analytical explanation of the non-universal scaling phenomenon： the exponent α varies between 1/2 and 1 depending on the size of sampling time window and the relative strength of the external/internal driven forces of the systems. The crossover behaviour and the relation of fluctuation scaling with pseudo long range dependence are also accounted for by the model. Numerical experiments show that the proposed model can recover the multi-scaiing phenomenon.

Non-stationary Buffeting Response Analysis of Long Span Suspension Bridge Under Strong Wind Loading

The non-stationary buffeting response of long span suspension bridge in time domain under strong wind loading is computed. Modeling method for generating non-stationary fluctuating winds with probabilistic model for non-stationary strong wind fields is first presented. Non-stationary wind forces induced by strong winds on bridge deck and tower are then given a brief introduction. Finally,Non-stationary buffeting response of Pulite Bridge in China,a long span suspension bridge,is computed by using ANSYS software under four working conditions with different combination of time-varying mean wind and time-varying variance. The case study further confirms that it is necessity of considering non-stationary buffeting response for long span suspension bridge under strong wind loading,rather than only stationary buffeting response.

The maxima and sums of multivariate non-stationary Gaussian sequences

Let {Xkl,…, Xkp, k≥ 1} be a p-dimensional standard （zero-means, unit-variances）non-stationary Gaussian vector sequence. In this work, the joint limit distribution of the maximaof {Xkl,…, Xkp, k 〉 1}, the incomplete maxima of those sequences subject to random failureand the partial sums of those sequences are obtained.

On the strong convergence properties for weighted sums of negatively orthant dependent random variables

In the paper, the strong convergence properties for two different weighted sums of negatively orthant dependent(NOD) random variables are investigated. Let {X, n ≥ 1}be a sequence of NOD random variables. The results obtained in the paper generalize the corresponding ones for i.i.d. random variables and identically distributed NA random variables to the case of NOD random variables, which are stochastically dominated by a random variable X. As a byproduct, the Marcinkiewicz-Zygmund type strong law of large numbers for NOD random variables is also obtained.

Estimating the Components of a Mixture of Extremal Distributions under Strong Dependence

In this paper, we provide a method based on quantiles to estimate the parameters of a finite mixture of Fréchet distributions, for a large sample of strongly dependent data. This is a situation that appears when dealing with environmental data and there was a real need of such method. We validate our approach by means of estimation and goodness-of-fit testing over simulated data, showing an accurate performance.

Strong Law of Large Numbers for a 2-Dimensional Array of Pairwise Negatively Dependent Random Variables

In this paper, we obtain the strong law of large numbers for a 2-dimensional array of pairwise negatively dependent random variables which are not required to be identically distributed. We found the sufficient conditions of strong law of large numbers for the difference of random variables which independent and identically distributed conditions are regarded. In this study, we consider the limit as which is stronger than the limit as m× n→?∞ when m, n →?∞?are natural numbers.

Spin-Unrestricted Multi-Configuration Time-Dependent Hartree Fock Theory

Based on spin-unrestricted hartree fock theory, we present the spin unrestricted multi- configuration time dependent hartree lock theory （UMCTDHF） to describe the electron correlation dynamics of systems interacting with laser field. The positive spin orbitals and the negative spin orbitals are propagated in their own subspace respectively. The spin orbital in the spin-down subspace acts with that in the spin-up subspace by the reduced density matrix and mean field operator. The ground energy is acquired by propagating the trial wave function in the imaginary time by using spin-restricted MCTDHF （RMCTDHF） and UMCTDHF respectively. Then the ionization probabilities and the electrons energies are calculated by using RMCTDHF and UMCTDHF when the laser field is present. The ionization probability calculated with UMCTDHF agrees with the previous theoretical reports very well. The UMCTDHF method is accurate and applicable for open shell system beyond the capability of the RMCTDHF method.

FREE BOUNDARY VALUE PROBLEM FOR THE CYLINDRICALLY SYMMETRIC COMPRESSIBLE NAVIER-STOKES EQUATIONS WITH DENSITY-DEPENDENT VISCOSITY

In this paper, we investigate the free boundary value problem （FBVP） for the cylindrically symmetric isentropic compressible Navier-Stokes equations （CNS） with density- dependent viscosity coefficients in the case that across the free surface stress tensor is balanced by a constant exterior pressure. Under certain assumptions imposed on the initial data, we prove that there exists a unique global strong solution which tends pointwise to a non-vacuum equilibrium state at an exponential time-rate as the time tends to infinity.

基于h-BN的方向依赖高次谐波产生(特邀)

利用紧束缚电子能带结构并结合求解两能带半导体Bloch方程的方法,研究了单层h-BN的高次谐波产生过程。结果显示平行于驱动光偏振方向的谐波分量在截止区表现出异常的晶格取向依赖关系,当光子能量超过7.31 eV时,奇次谐波的取向依赖相对于较低级次的奇次谐波取向依赖表现出明显的30°角度偏移。确定了能够发生偏移的那些谐波光子能量与布里渊区M点处的载流子动力学相关。进一步的时频分析表明,当驱动光偏振沿zigzag方向时,截止区谐波仅在特定极性的激光半周期内产生,这导致了zigzag方向谐波的急剧减弱,从而造成了截止区晶格取向分布的偏移。这一现象对利用高次谐波光谱重建电子能带结构具有重要意义。

基于微服务分布式链路的服务质量优化策略

微服务架构作为一种敏捷而弹性的软件设计范式,已经在当今的软件开发领域中取得了广泛的应用.然而,随着微服务数量的不断增加,系统复杂度随之升高,系统的服务质量随之下降,如何提升微服务架构下的线上业务服务质量是一个重要命题,而服务链路的优化是其中的关键挑战.本文通过对微服务架构下服务链路的深入研究,提出了链路抽样、链路拓扑生成、强弱依赖判定、循环调用识别、重复无效调用识别等链路分析方法,并在此基础之上,实践了一系列包括强弱演练、循环调用分拆、重复调用减支合并、故障自愈、链路溯源等在内的一系列有效的优化策略,有效提升了微服务架构下的生产运行系统服务质量.

宽象限相依样本下频率插值密度估计的收敛性质

频率多边形插值估计是一种非常重要的概率密度估计方法,该估计不仅在相同计算量下比直方图估计收敛速度快,而且在计算二元数据集合比核密度估计更简单、便捷,所以对其进一步探究是有理论研究价值的。设{Xn,n≥1}为宽象限相依的随机序列,具有未知的密度函数f(x),利用宽象限相依序列的Rosenthal-型不等式和截尾的技术,在适当的条件情况下,获得了频率插值密度估计的强相合性和r阶矩相合性。

On Complete Convergence for Arrays of Rowwise Strong Mixing Random Variables

In this paper, we present a general method to prove the complete conver- gence for arrays of rowwise strong mixing random variables, and give some results on complete convergence under some suitable conditions. Some Marcinkiewicz-Zygmund type strong laws of large numbers are also obtained.

基于关联规则和拓扑序列的分类器链方法

在分类器链方法中,如何确定标签学习次序至关重要,为此,提出一种基于关联规则和拓扑序列的分类器链方法 (TSECC).首先结合频繁模式设计了一种基于强关联规则的标签依赖度量策略;接下来通过标签间依赖关系构建有向无环图,对图中所有顶点进行拓扑排序;最后将得到的拓扑序列作为分类器链方法中标签的学习次序,对每个标签的分类器依次迭代更新.特别地,为减少无标签依赖或标签依赖度较低的“孤独”标签对其余标签预测性能的影响,将“孤独”标签排在拓扑序列之外,利用二元关联模型训练.在多种公共多标签数据集上的实验结果表明, TSECC能够有效提升分类性能.

STRONG LAW OF LARGE NUMBERS AND GROWTH RATE FOR NOD SEQUENCES

In the paper,we get the precise results of Hájek-Rényi type inequalities for the partial sums of negatively orthant dependent sequences,which improve the results of Theorem 3.1and Corollary 3.2 in Kim(2006)and the strong law of large numbers and strong growth rate for negatively orthant dependent sequences.

基于“壮火食气,少火生气”论激素依赖型哮喘的中西医诊治

糖皮质激素(GC)是治疗哮喘等呼吸系统疾病的首选药物,具有较强的抗炎、抗过敏、解痉平喘等作用,然而对糖皮质激素GC治疗不敏感的患者,需长期依赖口服大剂量激素才能实现对症状的控制,易发展为激素依赖型哮喘(SDA)。过量使用激素药物引发严重的不良反应与并发症,严重限制了其长期使用,成为临床亟待解决的难题。从中医学角度看,激素与肾脏同源,皆是“水中之火”,兼具正、邪两种属性,传统的“壮火食气,少火生气”观点认为运用药物调节机体,将病理之火(壮火)转化为生理之火(少火),可有效改善体内的生理功能失和。基于“壮火食气,少火生气”理论,论述了SDA的中西医诊疗机制,分别对SDA发病机制、西医治疗手段及其不良反应进行分析,从理论和实践应用两方面分析了中医诊治的出发点和功效,为SDA的中医治疗提供了理论基础。

A CENTRAL LIMIT THEOREM FOR STRONG NEAR-EPOCH DEPENDENT RANDOM VARIABLES

In this paper, a central limit theorem for strong near-epoch dependent sequences of random variables introduced in [9] is showed. Under the same moments condition,the authors essentially weaken the "size" requirement mentioned in other papers about near epoch dependence.

Global Strong Solutions of the Cauchy Problem for 1D Compressible Navier-Stokes Equations with Density-dependent Viscosity

We consider the Cauchy problem for one-dimensional compressible isentropic Navier-Stokes equations with density-dependent viscosity μ（ρ） = Aρα, where α〉 0 and A 〉0. The global existence of strong solutions is obtained, which improves the previous results by enlarging the interval of α. Moreover, our result shows that no vacuum is developed in a finite time provided the initial data does not contain vacuum.

On the Strong Limit Theorems for Double Arrays of Blockwise M-dependent Random Variables

For a double array of blockwise M-dependent random variables {Xmn,m ≥ 1,n ≥ 1}, ∑i^m=1 ∑^nj=1 strong laws of large numbers are established for double sums ∑m i=1 ∑j^n=1 ij, m≥ 1, n 〉 1. The main results are obtained for （i） random variables {Xmn, m≥ 1, n ≥ 1} being non-identically distributed but satisfy a condition on the summability condition for the moments and （ii） random variables {Xmn, m ≥ 1, n ≥ 1} being stochastically dominated. The result in Case （i） generalizes the main result of M6ricz et al. [J. Theoret. Probab., 21, 660-671 （2008）] from dyadic to arbitrary blocks, whereas the result in Case （ii） extends a result of Gut [Ann. Probab., 6, 469-482 （1978）] to the bockwise M-dependent setting. The sharpness of the results is illustrated by some examples.