Intelligent resource allocation for transmission security on IRS-assisted spectrum sharing systems with OFDM

In this paper, intelligent reflecting surface (IRS) technology is employed to enhance physical layer security (PLS) for spectrum sharing communication systems with orthogonal frequency division multiplexing (OFDM). Aiming to improve the secondary users’ secrecy rates, a design problem for jointly optimizing the transmission beamforming of secondary base station (SBS), the IRS’s reflecting coefficient and the channel allocation is formulated under the constraints of the requirements of minimum data rates of primary users and the interference between users. As the scenario is highly complex, it is quite challenging to address the non-convexity of the optimization problem. Thus, a deep reinforcement learning (DRL) based approach is taken into consideration. Specifically, we use dueling double deep Q networks (D3QN) and soft Actor–Critic (SAC) to solve the discrete and continuous action space optimization problems, respectively, taking full advantage of the maximum entropy RL algorithm to explore all possible optimal paths. Finally, simulation results show that our proposed approach has a great improvement in security transmission rate compared with the scheme without IRS and OFDM, and our proposed D3QN-SAC approach is more effective than other approaches in terms of maximum security transmission rate.     

多孔介质中流动参数的三维显示

本文利用当今三维图形工作站提供的最新视觉化技术，动态显示多孔介质中流动的原理和方法，主要探讨三个问题：（１）改进参数场图像化的质量。力求以逼真的，生活化的三维图形显示参数场的分布；（２）尽可能加快动态显示速度，力求以更强的动感显示出流动过程中参数场的变化规律；（３）尽可能丰富图形编辑功能，提高人机联作交互性。     

液相色谱-串联质谱法快速测定蔬菜中19种农药残留

建立了蔬菜中19种农药残留的快速测定方法。蔬菜样品用乙腈-甲酸均质提取,经三氯甲烷液-液萃取,溶剂转换后加入甲苯作为保护剂;经N-丙基乙二胺(PSA)、石墨化碳黑(GCB)净化,液相色谱-串联质谱(LC-MS/MS)正离子源(ESI+)、多反应监测模式(MRM)测定,基质匹配标准工作曲线定量。蔬菜样品基质在50~1 000ng/mL浓度范围内线性关系良好(r20.99)。在0.01、0.02、0.04mg/kg添加浓度水平下,各农药回收率在65.4%~120.0%之间,相对标准偏差(RSD)在3.35%~17.46%之间。实验发现QuEChERS各吸附剂对极性和化学结构不同农药的吸附作用有所不同,进一步通过正交试验设计的优化,得到了一组极性有差异和化学结构不同的农药净化用吸附剂和保护剂的组合方式。     

Regularized Principal Component Analysis for Spatial Data

In many atmospheric and earth sciences, it is of interest to identify dominant spatial patterns of variation based on data observed at p locations and n time points with the possibility that p > n. While principal component analysis (PCA) is commonly applied to find the dominant patterns, the eigenimages produced from PCA may exhibit patterns that are too noisy to be physically meaningful when p is large relative to n. To obtain more precise estimates of eigenimages, we propose a regularization approach incorporating smoothness and sparseness of eigenimages, while accounting for their orthogonality. Our method allows data taken at irregularly spaced or sparse locations. In addition, the resulting optimization problem can be solved using the alternating direction method of multipliers, which is easy to implement, and applicable to a large spatial dataset. Furthermore, the estimated eigenfunctions provide a natural basis for representing the underlying spatial process in a spatial random-effects model, from which spatial covariance function estimation and spatial prediction can be efficiently performed using a regularized fixed-rank kriging method. Finally, the effectiveness of the proposed method is demonstrated by several numerical examples.     

Statistical and Geometrical Way of Model Selection for a Family of Subdivision Schemes

The objective of this article is to introduce a generalized algorithm to produce the m-point n-ary approximating subdivision schemes(for any integer m, n ≥ 2). The proposed algorithm has been derived from uniform B-spline blending functions. In particular, we study statistical and geometrical/traditional methods for the model selection and assessment for selecting a subdivision curve from the proposed family of schemes to model noisy and noisy free data. Moreover, we also discuss the deviation of subdivision curves generated by proposed family of schemes from convex polygonal curve. Furthermore, visual performances of the schemes have been presented to compare numerically the Gibbs oscillations with the existing family of schemes.     

Flow of a mixture of a viscous fluid and a granular solid in an orthogonal rheometer

In this paper, we study the flow of a linearly viscous fluid and a granular solid, consisting of many particles, situated between two parallel plates rotating about different axes. Flow in orthogonal rheometers has been studied for many viscoelastic fluids so that their rheological properties can be measured. The mixture is modeled using the theory of interacting continua, and constitutive relations for the fluid phase, the granular phase, and the interaction forces are provided. For a very special case, an analytical solution to the equations of motion is also provided.     

Second-order differential equations in the Laguerre–Hahn class

Laguerre–Hahn families on the real line are characterized in terms of second-order differential equations with matrix coefficients for vectors involving the orthogonal polynomials and their associated polynomials, as well as in terms of second-order differential equation for the functions of the second kind. Some characterizations of the classical families are derived.