两条相互独立的非对称Cauchy过程轨道的乘积集的分形性质

设Ｘ１,Ｘ２是Ｒ＾ｄ上两条相互独立的非对称Ｃａｕｃｈｙ过程,我们求出了,两条轨道的乘积集的确切Ｈａｕｓｄｏｒｆｆ测度函数ψ（ｈ）＝ｈ＾２／ｌｏｇ＾ｈ,同时ψ（ｈ）,同时ψ（ｈ）也是图集的乘积集的确切Ｈａｕｓｄｏｒｆｆ测度函数,另外,我们还求出了乘积集的Ｈａｕｓｄｏｒｆｆ维数和Ｐａｃｋｉｎｇ维数均为２,从而证明了乘 集仍然是分形集。     

STABILITY OF DISPLACEMENT TO THE SECOND FUNDAMENTAL PROBLEM IN PLANE ELASTICITY

In this article, by using the stability of Cauchy type integral when the smooth perturbation for integral curve and the Sobolev type perturbation for kernel density happen, we discuss the stability of the second fundamental problem in plane elasticity when the smooth perturbation for the boundary of the elastic domain （unit disk） and the Sobolev type perturbation for the displacement happen. And the error estimate of the displacement between the second fundamental problem and its perturbed problem is obtained.     

Hochschild Cohomology and the Derived Class of m-Cluster Tilted Algebras of Type \mathbb{A}

In this paper, we characterize all the finite dimensional algebras that are derived equivalent to an m?cluster tilted algebra of type $\mathbb{A}$ . These algebras are gentle, and we show that the derived class of such an algebra is completely determined by the rank of its Grothendieck group and the dimension of its first Hochschild cohomology group.     

The Cauchy Problem for the Kadomtsev-Petviashvili (KPII) Equation in Three Space Dimensions

We prove the existence and uniqueness of local solutions in time for the Kadomtsev-Petviashvili equation (KPII) in ?³ for initial data in a suitable anisotropic Sobolev space of functions which have essentially 1⁺ derivative in the variable x and 0⁺ derivatives in the variables y and z.     

Scaling up the Greedy Equivalence Search algorithm by constraining the search space of equivalence classes

Greedy Equivalence Search (GES) is nowadays the state of the art algorithm for learning Bayesian networks (BNs) from complete data. However, from a practical point of view, this algorithm may not be efficient enough to deal with data from high dimensionality and/or complex domains. This paper proposes some modifications to GES aimed at increasing its efficiency. Under the faithfulness assumption, the modified algorithms preserve the same theoretical properties of the original one, that is, they recover a perfect map of the target distribution in the large sample limit. Moreover, experimental results confirm that, although the proposed methods carry out a significantly smaller number of computations, the quality of the BNs learned can be compared with those obtained with GES.     

Time-dependent coating flows in a strip, Part I: The linearized problem

This work is concerned with time-dependent coating flow in a strip . The Navier-Stokes equations are satisfied in the fluid region, the bottom substrate is moving with fixed velocity , and fluid is entering the strip through the upper boundary . The free boundary has the form for , where is the moving contact point. Our objective is to prove that if the initial data are close to those of a stationary solution (the existence of such a solution was established by the authors in an earlier paper) then the time-dependent problem has a unique solution with smooth free boundary, at least for a small time interval. In this Part I we study the linearized problem, about the stationary solution, and obtain sharp estimates for the solution and its derivatives. These estimates will be used in Part II to establish existence and uniqueness for the full nonlinear problem.

     

Differentiable Functionals and Smoothed Bootstrap

The differentiability properties of statistical functionals have several interesting applications. We are concerned with two of them. First, we prove a result on asymptotic validity for the so-called smoothed bootstrap (where the artificial samples are drawn from a density estimator instead of being resampled from the original data). Our result can be considered as a smoothed analog of that obtained by Parr (1985, Stat. Probab. Lett., 3, 97-100) for the standard, unsmoothed bootstrap. Second, we establish a result on asymptotic normality for estimators of type generated by a density functional being a density estimator. As an application, a quick and easy proof of the asymptotic normality of , (the plug-in estimator of the integrated squared density ) is given.