Conditions for swappability of records in a microdata set when some marginals are fixed

We consider swapping of two records in a microdata set for the purpose of disclosure control. We give some necessary and sufficient conditions that some observations can be swapped between two records under the restriction that a given set of marginals are fixed. We also give an algorithm to find another record for swapping if one wants to swap out some observations from a particular record.     

Domain decomposition preconditioners of Neumann-Neumann type for hp-approximations on boundary layer meshes in three dimensions

We develop and analyse Neumann–Neumann methods for hpfinite-element approximations of scalar elliptic problems ongeometrically refined boundary layer meshes in three dimensions.These are meshes that are highly anisotropic where the aspectratio typically grows exponentially with the polynomial degree.The condition number of our preconditioners is shown to be independentof the aspect ratio of the mesh and of potentially large jumpsof the coefficients. In addition, it only grows polylogarithmicallywith the polynomial degree, as in the case of p approximationson shape-regular meshes. This work generalizes our previousone on two-dimensional problems in Toselli & Vasseur (2003a,submitted to Numerische Mathematik, 2003c to appear in Comput.Methods Appl. Mech. Engng.) and the estimates derived here canbe employed to prove condition number bounds for certain typesof FETI methods.     

A Quasilinear Hierarchical Size-Structured Model: Well-Posedness and Approximation

A finite difference approximation to a hierarchical size-structured model with nonlinear growth, mortality and reproduction rates is developed. Existence-uniqueness of the weak solution to the model is established and convergence of the finite-difference approximation is proved. Simulations indicate that the monotonicity assumption on the growth rate is crucial for the global existence of weak solutions. Numerical results testing the efficiency of this method in approximating the long-time behavior of the model are presented.     

CBS constants for multilevel splitting of graph-Laplacian and application to preconditioning of discontinuous Galerkin systems

The goal of this work is to derive and justify a multilevel preconditioner of optimal arithmetic complexity for symmetric interior penalty discontinuous Galerkin finite element approximations of second order elliptic problems. Our approach is based on the following simple idea given in [R.D. Lazarov, P.S. Vassilevski, L.T. Zikatanov, Multilevel preconditioning of second order elliptic discontinuous Galerkin problems, Preprint, 2005]. The finite element space of piece-wise polynomials, discontinuous on the partition , is projected onto the space of piece-wise constant functions on the same partition that constitutes the largest space in the multilevel method. The discontinuous Galerkin finite element system on this space is associated to the so-called “graph-Laplacian”. In 2-D this is a sparse M-matrix with -1 as off diagonal entries and nonnegative row sums. Under the assumption that the finest partition is a result of multilevel refinement of a given coarse mesh, we develop the concept of hierarchical splitting of the unknowns. Then using local analysis we derive estimates for the constants in the strengthened Cauchy–Bunyakowski–Schwarz (CBS) inequality, which are uniform with respect to the levels. This measure of the angle between the spaces of the splitting was used by Axelsson and Vassilevski in [Algebraic multilevel preconditioning methods II, SIAM J. Numer. Anal. 27 (1990) 1569–1590] to construct an algebraic multilevel iteration (AMLI) for finite element systems. The main contribution in this paper is a construction of a splitting that produces new estimates for the CBS constant for graph-Laplacian. As a result we have a preconditioner for the system of the discontinuous Galerkin finite element method of optimal arithmetic complexity.     

Preconditioned tensor format conjugate gradient squared and biconjugate gradient stabilized methods for solving stein tensor equations

This article is concerned with solving the high order Stein tensor equation arising in control theory. The conjugate gradient squared (CGS) method and the biconjugate gradient stabilized (BiCGSTAB) method are attractive methods for solving linear systems. Compared with the large-scale matrix equation, the equivalent tensor equation needs less storage space and computational costs. Therefore, we present the tensor formats of CGS and BiCGSTAB methods for solving high order Stein tensor equations. Moreover, a nearest Kronecker product preconditioner is given and the preconditioned tensor format methods are studied. Finally, the feasibility and effectiveness of the new methods are verified by some numerical examples.     

后处理工艺制备多级孔Ti-BEA沸石及其环氧化催化性能

基于脱铝多级孔BEA沸石与二氯二茂钛的固相反应,开展了钛掺杂量可调的多级孔Ti-beta后处理工艺制备研究.对制备的多级孔Ti-beta样品的理化性质进行了表征,包括X射线衍射、氮气吸附脱附测试、扫描电镜、透射电镜、紫外可见吸收光谱和紫外拉曼光谱等.结果表明,多级孔BEA沸石具有较好的化学稳定性,脱铝-钛化的后处理过程未对样品多级孔结构产生明显影响. 以环己烯和十二烯的烯烃环氧化为探针反应表征了合成多级孔Ti-beta与纯相微孔Ti-beta沸石的催化性能.结果表明,在小分子环己烯的环氧化反应中,多级孔Ti-beta沸石的催化活性(转化率59.4%)与微孔Ti-beta相当(转化率57.9%);但是在较大分子十二烯的催化反应中,多级孔结构Ti-beta材料的催化性能(转化率11.1%)明显优于纯相微孔材料(转化率6.8%),且产物中环氧化物选择性更高(分别为60.3%和37.8%).     

Hydrothermal synthesis of peony-like CuO micro/nanostructures for high-performance lithium-ion battery anodes

The peony-like CuO micro/nanostructures were fabricated by a facile hydrothermal approach. The peonylike CuO micro/nanostructures about 3-5 μm in diameter were assembled by CuO nanoplates. These CuO nanoplates, as the building block, were self-assembled into multilayer structures under the action of ethidene diamine, and then grew into uniform peony-like CuO architecture. The novel peony-like CuO micro/nanostructures exhibit a high cycling stability and improved rate capability. The peony-like CuO micro/nanostructures electrodes show a high reversible capacity of 456 mAh/g after 200 cycles, much higher than that of the commercial CuO nanocrystals at a current 0.1 C. The excellent electrochemical performance of peony-like CuO micro/nanostructures might be ascribed to the unique assembly structure, which not only provide large electrode/electrolyte contact area to accelerate the lithiation reaction, but also the interval between the multilayer structures of CuO nanoplates electrode could provide enough interior space to accommodate the volume change during Li~+ insertion and de-insertion process.     

Programming With Models: Writing Statistical Algorithms for General Model Structures With NIMBLE

We describe NIMBLE, a system for programming statistical algorithms for general model structures within R. NIMBLE is designed to meet three challenges: flexible model specification, a language for programming algorithms that can use different models, and a balance between high-level programmability and execution efficiency. For model specification, NIMBLE extends the BUGS language and creates model objects, which can manipulate variables, calculate log probability values, generate simulations, and query the relationships among variables. For algorithm programming, NIMBLE provides functions that operate with model objects using two stages of evaluation. The first stage allows specialization of a function to a particular model and/or nodes, such as creating a Metropolis-Hastings sampler for a particular block of nodes. The second stage allows repeated execution of computations using the results of the first stage. To achieve efficient second-stage computation, NIMBLE compiles models and functions via C++, using the Eigen library for linear algebra, and provides the user with an interface to compiled objects. The NIMBLE language represents a compilable domain-specific language (DSL) embedded within R. This article provides an overview of the design and rationale for NIMBLE along with illustrative examples including importance sampling, Markov chain Monte Carlo (MCMC) and Monte Carlo expectation maximization (MCEM). Supplementary materials for this article are available online.     

Novel Bi2MoO6 Nanosheets/Vertical TiO2 Nanorods Arrays Heterojunction with Enhanced Photoelectrochemical Performance under Visible Light Irradiation

Novel Bi₂MoO₆/TiO₂ heterojunction was fabricated by growing Bi₂MoO₆ nanosheets arrays on the vertically aligned TiO₂ nanorods arrays via a two-step solvothermal method. The obtained Bi₂MoO₆/TiO₂ hierarchical heterojunction showed excellent visible light photoelectrochemical performance. Compared with the pure TiO₂ and Bi₂MoO₆, the photocurrent density of the heterojunction was increased 57 and 29 times, respectively. Furthermore, the hydrogen generation rate of the Bi₂MoO₆/TiO₂ for photoelectrocatalytic water-splitting was about 6 times higher than that of the pure Bi₂MoO₆. The improved performance can be attributed to the synergistic effects of enhanced absorption of visible light, increase of migration rate and separation efficiency of photo-induced carriers.     

Hierarchical Archimedean copulas through multivariate compound distributions

In this paper, we propose a new hierarchical Archimedean copula construction based on multivariate compound distributions. This new imbrication technique is derived via the construction of a multivariate exponential mixture distribution through compounding. The absence of nesting and marginal conditions, contrarily to the nested Archimedean copulas approach, leads to major advantages, such as a flexible range of possible combinations in the choice of distributions, the existence of explicit formulas for the distribution of the sum, and computational ease in high dimensions. A balance between flexibility and parsimony is targeted. After presenting the construction technique, properties of the proposed copulas are investigated and illustrative examples are given. A detailed comparison with other construction methodologies of hierarchical Archimedean copulas is provided. Risk aggregation under this newly proposed dependence structure is also examined.