Basis Sets Dependency in Constructing Spectroscopy-Accuracy Ab Initio Global Electric Dipole Moment Functions

Recently, more attention have been paid on the construction of dipole moment functions (DMF) using theoretical methods. However, the computational methods to construct DMFs are not validated as much as those for potential energy surfaces do. In this letter, using Ar...He as an example, we tested how spectroscopyaccuracy DMFs can be constructed using ab initio methods. We especially focused on the basis set dependency in this scenario, i.e., the convergence of DMF with the sizes of basis sets, basis set superposition error, and mid-bond functions. We also tested the explicitly correlated method, which converges with smaller basis sets than the conventional methods do. This work can serve as a pictorial sample of all these computational technologies behaving in the context of constructing DMFs.     

Amorphous Carbon Film with Self-modified Carbon Nanoparticles Synthesized by Low Temperature Carbonization of Phenolic Resin for Simultaneous Sensing of Dopamine and Uric Acid

A self-modified film electrode consisting of homogeneous snowflake-shaped nanoparticles on the amorphous carbon substrate (HNAC) was prepared by low temperature carbonization of phenolic resin. Such a unique structure was beneficial to enhance the electroanalysis signal responds. Simultaneous detection of DA and UA was performed on the HNAC using differential pulse voltammetry (DPV) at pH 8 phosphate buffer. The well-defined oxidation peak potential separation reached 260 mV between DA and UA. Meanwhile, the detection limit of HNAC were 0.401 μM (DA) and 2.800 μM (UA).     

A new characterization of the Berger sphere in complex projective space

We give a complete classification of Lagrangian immersions of homogeneous 3-manifolds (the Berger spheres, the Heisenberg group ${\text{Nil}}_3$, the universal covering of the Lie group $\text{PSL}(2,\mathbb{R})$ and the Lie group ${\text{Sol}}_3$) in 3-dimensional complex space forms. As a corollary, we get a new characterization of the Berger sphere in complex projective space.     

基于Demons算法改进的图像去噪模型研究

在Demons算法的基础上, 将扩散过程看作图像配准, 建立一种新的基于图像配准的Demons 去噪模型. 实验表明, 该模型去噪效果优于经典的Perona-Malik模型, 排除了模型的病态性. 考虑到新模型在图像去噪过程中仅靠梯度信息表示图像的局部特征还不完善, 故将水平集曲率作为控制图像结构的驱动力因素引入到此模型中, 提出了一种新的梯度和曲率双重驱动力的图像去噪模型. 分析和仿真结果表明, 两种新模型都可有效抑制噪声, 清晰度也有明显的提高, 其中双重驱动力的图像去噪模型去噪效果更具优越性.     

Possibilistic nested logic programs and strong equivalence

In this paper, the class of possibilistic nested logic programs is introduced. These possibilistic logic programs allow us to use nested expressions in the bodies and heads of their rules. By considering a possibilistic nested logic program as a possibilistic theory, a construction of a possibilistic logic programing semantics based on answer sets for nested logic programs and the proof theory of possibilistic logic is defined. In order to define a general method for computing the possibilistic answer sets of a possibilistic nested program, the idea of equivalence between possibilistic nested programs is explored. By considering properties of equivalence between possibilistic programs, a process of transforming a possibilistic nested logic program into a possibilistic disjunctive logic program is defined. Given that our approach is an extension of answer set programming, we also explore the concept of strong equivalence between possibilistic nested logic programs. To this end, we introduce the concept of poss SE-models. Therefore, we show that two possibilistic nested logic programs are strong equivalents whenever they have the same poss SE-models.The expressiveness of the possibilistic nested logic programs is illustrated by a scenario from the medical domain. In particular, we exemplify how possibilistic nested logic programs are expressive enough for capturing medical guidelines which are pervaded by vagueness and qualitative information.     

Joint distributions of random sets and their relation to copulas

Random sets are set-valued random variables. They have been applied in various fields like stochastic geometry, statistics, economics, engineering or computer science, and are often used for modeling uncertainty. In an earlier paper the author has defined joint capacity and joint containment functionals which are multivariate set functions describing the joint distribution of random sets. This paper is concerned with the question how copulas can be used to describe or model the dependence of random sets. It is demonstrated that a joint containment functional can be related to its margins by a family of copulas. Furthermore, the paper provides a first insight how copulas can be used to define joint containment functionals.     

On independent sets in random graphs

The independence number of a sparse random graph G(n,m) of average degree d = 2m/n is well‐known to be with high probability, with in the limit of large d. Moreover, a trivial greedy algorithm w.h.p. finds an independent set of size , i.e., about half the maximum size. Yet in spite of 30 years of extensive research no efficient algorithm has emerged to produce an independent set with size for any fixed (independent of both d and n). In this paper we prove that the combinatorial structure of the independent set problem in random graphs undergoes a phase transition as the size k of the independent sets passes the point . Roughly speaking, we prove that independent sets of size form an intricately rugged landscape, in which local search algorithms seem to get stuck. We illustrate this phenomenon by providing an exponential lower bound for the Metropolis process, a Markov chain for sampling independent sets. © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 47, 436–486, 2015     

Asymptotically optimal neighbour sum distinguishing colourings of graphs

Consider a simple graph G = (V,E) and its proper edge colouring c with the elements of the set {1,2,…,k}. The colouring c is said to be neighbour sum distinguishing if for every pair of vertices u, v adjacent in G, the sum of colours of the edges incident with u is distinct from the corresponding sum for v. The smallest integer k for which such colouring exists is known as the neighbour sum distinguishing index of a graph and denoted by . The definition of this parameter, which makes sense for graphs containing no isolated edges, immediately implies that , where Δ is the maximum degree of G. On the other hand, it was conjectured by Flandrin et al. that for all those graphs, except for C₅. We prove this bound to be asymptotically correct by showing that . The main idea of our argument relays on a random assignment of the colours, where the choice for every edge is biased by so called attractors, randomly assigned to the vertices. © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 47, 776–791, 2015     

不同结构Cu_2O多晶的合成及其对高氯酸铵热分解的催化作用

利用均相反应器,在没有添加剂的条件下合成了具有多孔结构的Cu2O微球.考察了合成时间以及反应器旋转速度对Cu2O微球结构的影响.通过增加聚乙烯吡咯烷酮(PVP)的用量,使得Cu2O从多孔微球转变为立方体孪晶,最终形成十四面体孪晶结构.同时,将不同结构的Cu2O多晶应用于催化高氯酸铵(AP)的热分解,结果表明:多孔Cu2O微球较其它结构的Cu2O对AP的热分解具有更高的催化活性,使得AP的低温分解温度降低了37.4°C,而AP在低温阶段的分解量也由8.7%增加至49.0%.