Ile-1781-Leu and Asp-2078-Gly Mutations in ACCase Gene,Endow Cross-resistance to APP,CHD, and PPZ in Phalaris minor from Mexico

Herbicides that inhibit acetyl coenzyme A carboxylase (ACCase) are commonly used in Mexico to control weedy grasses such as little seed canarygrass (Phalaris minor). These herbicides are classified into three major families (ariloxyphenoxypropionates (APP), cyclohexanodiones (CHD), and, recently, phenylpyrazolines (PPZ)). In this work, the resistance to ACCase (APP, CHD, and PPZ) inhibiting herbicides was studied in a biotype of Phalaris minor (P. minor) from Mexico, by carrying out bioassays at the whole-plant level and investigating the mechanism behind this resistance. Dose-response and ACCase in vitro activity assays showed cross-resistance to all ACCase herbicides used. There was no difference in the absorption, translocation, and metabolism of the ¹⁴C-diclofop-methyl between the R and S biotypes. The PCR generated CT domain fragments of ACCase from the R biotype and an S reference were sequenced and compared. The Ile-1781-Leu and Asp-2078-Gly point mutations were identified. These mutations could explain the loss of affinity for ACCase by the ACCase-inhibing herbicides. This is the first report showing that this substitution confers resistance to APP, CHD, and PPZ herbicides in P. minor from Mexico. The mutations have been described previously only in a few cases; however, this is the first study reporting on a pattern of cross-resistance with these mutations in P. minor. The findings could be useful for better management of resistant biotypes carrying similar mutations.     

一种无线网络优化中挖掘LTE小区场景突变的方法研究

研究了一种检测无线网络优化中挖掘LTE小区场景突变的方法，通过筛选过滤出场景突变的LTE小区数据集，分析确认是否由于某些性能指标或者参数原因而导致的小区场景突变，最终挖掘得到发生场景突变的LTE小区。     

Fermatean fuzzy linguistic set and its application in multicriteria decision making

In this paper, we propose the concept of Fermatean fuzzy linguistic term sets based on linguistic term sets and Fermatean fuzzy sets. The basic operational laws, the score function, and the accuracy function of Fermatean fuzzy linguistic numbers are provided. Then we propose the Fermatean fuzzy linguistic weighted aggregation operator, the Fermatean fuzzy linguistic weighted geometric operator, and the Fermatean fuzzy linguistic distance measures. Furthermore, we extend the TOPSIS method to the proposed distance measures, and the ranking of alternatives is obtained under a Fermatean fuzzy linguistic environment. An example is provided to illustrate the feasibility and effectiveness of the proposed method, and a comparison with the existing method is also analyzed. Finally, the sensitivity analysis of the parameter in the proposed distance measure is also discussed.     

Exponential ergodicity of some Markov dynamical systems with application to a Poisson-driven stochastic differential equation

We are concerned with the asymptotics of the Markov chain given by the post-jump locations of a certain piecewise-deterministic Markov process with a state-dependent jump intensity. We provide sufficient conditions for such a model to possess a unique invariant distribution, which is exponentially attracting in the dual-bounded Lipschitz distance. Having established this, we generalize a result of J. Kazak on the jump process defined by a Poisson-driven stochastic differential equation with a solution-dependent intensity of perturbations.     

An interval-valued exceedance method in MCDM with uncertain satisfactions

Multicriteria decision-making problems have been applied to many applications for its practicality. Nevertheless, when the evaluated satisfactions are more complex, such as interval-valued distributions, how to reasonably obtain the aggregation results of alternatives is still an open issue. In this paper, an interval-valued exceedance method is proposed to solve such a question based on the Golden Rule representative value and probabilistic exceedance method. Due to good performance of expressing uncertain information, the Golden Rule representative value method is used to order interval-valued satisfactions after an effective normalization process. In addition, a quantifier-based ordered weighted averaging operator is also introduced to consider the preferences of decision makers. A realistic application of supplier selection is shown to illustrate the practicality of the proposed method.     

基于变异算子和邻域值自适应的MOEA/D算法

基于分解的多目标进化算法（MOEA/D）在解决多目标问题时，具有简单有效的特点。但多数MOEA/D采用固定的控制参数，导致全局搜索能力差，难以平衡收敛性和多样性。针对以上问题提出一种基于变异算子和邻域值自适应的多目标优化算法。该算法根据种群中个体适应度值的分散或集中程度进行判断，并据此对变异算子进行自适应的调节，从而增强算法的全局搜索能力；根据进化所处的阶段以及个体适应度值的集中程度，自适应地调节邻域值大小，保证每个个体在不同的进化代数都有一个邻域值大小；在子问题邻域中，统计子问题对应个体的被支配数，通过判断被支配数是否超过设定的上限，来决定是否将Pareto支配关系也作为邻域内判断个体好坏的准则之一。将提出的算法与传统的MOEA/D在标准测试问题上进行对比。实验结果表明，提出的算法求得的解集具有更好的收敛性和多样性，在求解性能上具有一定的优势。     

A RBF based finite difference method for option pricing under regime-switching jump-diffusion model

Abstract

In this article, we presented a method for option pricing problem under regime-switching jump-diffusion models. We have proposed a numerical method for solving a partial integro-differential equation (PIDE) for pricing European option and for solving linear complementarity problem (LCP), to evaluate the price of American options. We use implicit explicit method for time semi discretization, followed by radial basis function based finite difference (RBF-FD) method for spatial discretization to solve PIDE. The proposed method is further extended to solve the LCP by coupling it with operator splitting method. Numerical simulation is done for European and American option to demonstrate efficiency and accuracy of the proposed method.     

迭代最近点算法的改进策略

迭代最近点（Iterative Closest Point, ICP）算法是一种最为常见的点云配准方法，虽然配准精度高，但收敛速度慢，对含噪声、覆盖率较低点云的配准效果不佳。鉴于此，本文提出3种ICP算法的改进方法。针对含噪声的点云，采用概率ICP算法来抑制噪声点对配准结果的影响，提高配准精度；为了提高点云配准速度，采用坐标ICP算法实现点云的快速配准；针对低覆盖率点云，采用盒子ICP算法实现配准，可以大大提高配准精度和速度。通过兔子点云配准实验表明，3种改进的ICP算法在点云配准精度和速度方面都有很大程度的提高，均为有效的点云配准方法。     

泛逻辑学理论——机制主义人工智能理论的逻辑基础

当前，世界各主要大国都把人工智能作为它们的国家战略。人工智能的发展正在快速改变着人类的生活方式和思想观念。在中国，有一小批研究者20多年来一直在基于辩证唯物主义潜心研究具有普适性的人工智能基础理论，包括智能的形成机制、逻辑基础、数学基础、协调机理、矛盾转化等。终于，他们各自建立了机制主义人工智能理论、泛逻辑学理论、因素空间理论、协调学、可拓学、集对分析等。其中，机制主义人工智能理论是基于智能形成机制的通用理论，它能把现有的结构主义、功能主义和行为主义三大流派有机地统一起来，使意识、情感、理智成为三位一体的关系；因素空间理论是机制主义人工智能理论的数学基础；泛逻辑学理论是机制主义人工智能理论的逻辑基础。本文介绍了泛逻辑学理论的基本思想、理论基础和应用方法，阐明它的理论意义和应用价值。特别需要指出的是，在广义概率论基础上建立的命题泛逻辑（包括刚性逻辑和柔性逻辑），可看成一个完整的命题级智能信息处理算子库，库中完整地包含了全部18种柔性信息处理模式（包括16种布尔信息处理模式），可用类型编码<a,b,e>来严格区分，用它可寻找到适合自己的信息处理算子完整簇来使用。在每一个信息处理模式中，各种不确定性的组合状态由不确定性程度属性编码<k,h,β,e>来严格区分，用它可在本信息处理模式的算子完整簇中精确选择具体的算子来使用。这表明柔性信息处理本质上是一把密码锁，它需要专门的密码<a,b,e>+<k,h,β,e>才能正常打开，不能乱点鸳鸯谱。通过只有18种模式，每种模式可以从最大算子连续变化到最小算子，已经证明了没有一个命题算子被遗漏。