Multiple re-configurable intelligent surfaces based physical layer eavesdropper detection for V2I communications

Inspired by the promising potential of re-configurable intelligent surface (RIS)-aided transmission in achieving the vision of 6th Generation (6G) network, we analyze the security model for a vehicular-to-infrastructure (V2I) network by considering multiple RISs (M-RIS) on buildings to act as passive relays at fixed distances from a source. In addition, multiple eavesdroppers are presented in the vicinity of the intended destination. Our aim is to enhance the secrecy capacity (SC) and to minimize secrecy outage probability (SOP) in presence of multiple eavesdroppers with the help of M-RIS in V2I communications. We propose a key-less physical layer security using beam-forming by exploiting M-RIS. The proposed approach assumes the concept of detecting eavesdroppers before the information can be transmitted via beam-forming by utilizing M-RIS. The results reveal that with consideration of M-RIS and beam-forming, the achievable SC and SOP performance is significantly improved while imposing minimum power consumption and fewer RIS reflectors.     

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.     

Secrecy energy efficiency optimization for multiuser massive MIMO wiretap systems with transmit antenna selection

Massive multiple-input-multiple-output (Massive MIMO) significantly improves the capacity of wireless communication systems. However, large-scale antennas bring high hardware costs, and security is a vital issue in Massive MIMO networks. To deal with the above problems, antenna selection (AS) and artificial noise (AN) are introduced to reduce energy consumption and improve system security performance, respectively. In this paper, we optimize secrecy energy efficiency (SEE) in a downlink multi-user multi-antenna scenario, where a multi-antenna eavesdropper attempts to eavesdrop the information from the base station (BS) to the multi-antenna legitimate receivers. An optimization problem is formulated to maximize the SEE by jointly optimizing the transmit beamforming vectors, the artificial noise vector and the antenna selection matrix at the BS. The formulated problem is a nonconvex mixed integer fractional programming problem. To solve the problem, a successive convex approximation (SCA)-based joint antenna selection and artificial noise (JASAN) algorithm is proposed. After a series of relaxation and equivalent transformations, the nonconvex problem is approximated to a convex problem, and the solution is obtained after several iterations. Simulation results show that the proposed algorithm has good convergence behavior, and the joint optimization of antenna selection and artificial noise can effectively improve the SEE while ensuring the achievable secrecy rate.     

公共安全视域下精神药物光谱学无损分类

该文对苯二氮类和吩噻嗪类镇静安眠药样品的红外光谱数据进行采集,构建了不同数据分类模型并对比了不同波段光谱数据集对其分析准确率的影响.结果表明,借助贝叶斯判别分析的基于全波段数据集的二阶导数模型分类效果优于其他单一模型,对于苯二氮类和吩噻嗪类两个不同类型精神药物的总体分类准确率达92.7％.借助贝叶斯判别分析的基于全波段和指纹区融合数据集的二阶导数融合模型分类效果最佳,对苯二氮类和吩噻嗪类两个不同类型精神药物的总体分类准确率达到100％;对苯二氮类和吩噻嗪类中不同种类精神药物的总体分类准确率则分别达到96.7％和100％.该研究实现了不同类型及同一类型不同种类镇静安眠药的快速准确定性分析,为此类管制类药物走私案件的准确定性提供了一定的技术支持.     

接枝改性PVDF基含氟聚合物

聚偏氟乙烯(PVDF基)含氟聚合物由于其独特的性能受到了广泛的关注。将功能化链段引入PVDF基含氟聚合物可以进一步提升其性能并拓展其应用领域。相较于物理共混法和直接共聚改性法,通过接枝改性法将功能化单体引入含氟聚合物的侧链具有更显著的优势,可便捷、高效地得到组成精确,结构可控的接枝共聚物。本文综述了通过活性自由基聚合(包括ATRP、SET-LRP、有机催化原子转移自由基聚合(O-ATRP)、光诱导Cu(Ⅱ)介导RDRP)和高能射线辐射(γ射线,紫外,电子束)等对PVDF基含氟聚合物功能化接枝改性的方法,并对其发展趋势以及改性聚合物的应用前景进行了展望。     

一种用于活细胞中检测Zn2+的萘酚席夫碱类荧光探针

设计合成了1种基于C=N异构化和螯合荧光增强机理（CHEF）的Zn²⁺荧光探针BMO和NBMO,其结构经¹H NMR,¹³C NMR,¹H-¹H COSY,HSQC,IR和HRMS进行了表征。光谱分析实验结果显示,探针对Zn²⁺均具有较好的选择性和灵敏度,检出限分别为30和21 nmol·L^-1。在0~20 μmol·L^-1浓度的范围内,BMO和NBMO的荧光强度与Zn²⁺浓度可呈良好的线性关系。NBMO-Zn²⁺配合物单晶结构和Job曲线证实该探针与Zn²⁺以1：1配位。NBMO被成功应用于活细胞中Zn²⁺的检测。     

A UV‐Cleavable Bottlebrush Polymer with o‐Nitrobenzyl‐Linked Side Chains

An ultraviolet (UV)‐cleavable bottlebrush polymer is synthesized using the “grafting‐onto” strategy by combining living radical polymerization and copper‐catalyzed azide‐alkyne cycloaddition (CuAAC). In this approach, reversible addition‐fragmentation chain transfer polymerization is used to prepare a poly(methylacrylate) backbone with azide side groups, while atom transfer radical polymerization is employed to prepare polystyrene (PS) side chains end‐functionalized with o‐nitrobenzyl (UV‐cleavable) propargyl groups. CuAAC is then used to graft PS side chains onto the polymer backbone, producing the corresponding bottlebrush polymers with UV‐cleavable PS side chains. The formation of the bottlebrush polymer is characterized by ¹H nuclear magnetic resonance spectroscopy, gel permeation chromatography (GPC), and Fourier transform infrared spectroscopy. The cleavage behavior of the bottlebrush polymer is monitored in tetrahydrofuran solution under UV irradiation by GPC and viscosity measurements.

     

Phenanthroline-fluorescein molecular hybrid as a ratiometric and selective fluorescent chemosensor for Cu2+ via FRET strategy: synthesis,computational studies and in vitro applications

A FRET-based chemosensor L containing donor phenanthroline and acceptor fluorescein moiety was designed, synthesised and characterised for the ratiometric fluorescent detection of Cu²⁺ in organo-aqueous solution. Probe L showed high selectivity and excellent sensitivity towards Cu²⁺ ions by exhibiting both colorimetric and fluorometric changes due to opening of the spirolactum ring of fluorescein upon complexation with Cu²⁺. In presence of Cu²⁺ ions, probe L formed L-Cu²⁺ complex in 1:1 stoichiometric fashion which is established on the basis of Job’s plot and mass spectroscopy. We also performed DFT computational studies to know the binding nature and coordination feature of the complex. Furthermore, fluorescence imaging studies revealed that probe L was cell permeable and could be used to detect intracellular Cu²⁺ in living cells.     

Maximizing H‐Colorings of Connected Graphs with Fixed Minimum Degree

For graphs G and H , an H‐coloring of G is a map from the vertices of G to the vertices of H that preserves edge adjacency. We consider the following extremal enumerative question: for a given H , which connected n‐vertex graph with minimum degree δ maximizes the number of H‐colorings? We show that for nonregular H and sufficiently large n , the complete bipartite graph is the unique maximizer. As a corollary, for nonregular H and sufficiently large n the graph is the unique k‐connected graph that maximizes the number of H‐colorings among all k‐connected graphs. Finally, we show that this conclusion does not hold for all regular H by exhibiting a connected n‐vertex graph with minimum degree δ that has more ‐colorings (for sufficiently large q and n ) than .     

稀土安全评价:集成算法改进与实证

稀土作为我国战略性矿产资源,其安全问题一直是政府和学术界关注与研究的重要课题.建立了稀土安全的概念框架与评价体系,针对传统AHP中九标度法的不足,基于熵值法、加速遗传算法及扩充标度值的层次分析法,提出了一种改进的层次分析法(EV-AGA-EAHP),通过集成模糊C-均值聚类算法和模糊综合评价法,研究提出了一种模糊综合集成评价方法(EV-AGA-EAHP-FCM-FIJ),给出了集成算法及步骤,对2001-2013年我国稀土安全水平进行了评价,提出了保障我国稀土安全的建议.