基于扩频通信的无线抄表系统设计与实现

针对基于Zigbee技术的无线抄表系统成本高、抗干扰能力弱、通信距离受限的缺点,提出了一种扩频通信与GSM技术相结合的远程无线抄表系统设计。结合低功耗的射频收发芯片sx1278,设计了汇总节点、中继节点以及水表采集节点硬件电路,确定了通信的数据帧结构,制定了相应的组网算法。在抄表区域中采用抗干扰能力强的扩频通信技术进行无线抄表,在远距离通信中采用GSM技术将汇总的水表数据传送到控制中心,整个抄表系统具有低功耗、抗干扰能力强、自组网特点,能够实现远程控制无线自组织组网抄表。测试结果表明,设计的系统能够实现稳定的自组网,具有较高的抄表成功率、较好的性能和广泛的应用前景。     

隔离式协议转换器在压变并行温补系统上的研发与应用

文章提出隔离式协议转换器在压力变送器并行温压补偿系统上的研发与应用,其目的是替换现存以HART总线[1]为基础的并行温压补偿系统的补偿电路,进而简化了补偿电路,提高了主站与工位采集板之间的通讯速率,使系统的维护和维修简单,以及令PCI总线驱动控制PIO数字I/O电路[2]完全的独立出来,只用于温压补偿中气路的切换选择控制;隔离式协议转换器是一款自主研发、自拟协议的独立模块,经压力变送器生产企业的应用与验证,该研发成果能够较好地解决现在温压补偿系统存在的问题,同时易移植于其它温压补偿系统上,并满足压力变送器生产客户的需求。     

基于STM32的汽车涂装线监控系统研究与实现

针对现有汽车电泳涂装线监控系统普遍存在信息采集不全面、分析处理时间长、共享程度低等问题,研究开发了基于STM32的涂装线设备状态监控系统。该系统采用高性能的STM32处理器,结合通用性好易开发的VC 6.0平台自主开发系统上位机软件,完成对设备数据的采集、处理分析及在线显示。首先,构建基于数据采集、中央处理、设备控制及通信的下位机硬件系统;然后,通过RS485总线技术实现各采集模块与中央处理模块的通讯,并通过串口及时将设备参数上传到上位机,实现涂装线设备的实时监控。     

中性束注入器离子源测试台可编程逻辑控制系统

 为实现对离子源测试台系统现场设备的实时监控,设计了一套基于现场总线（Profibus）通讯协议的可编程逻辑控制器（PLC）系统。根据综合测试台测控要求确定PLC系统硬件配置,组建单主站Profibus-DP网络实现高速分布式I/O系统。该系统实时监测现场设备状态并与中性束注入总控实时交换数据,协调控制现场设备按序稳定运行。全图形化的人机操作界面实现了系统运行的可视化操作,数据的实时存储和显示为物理操作人员提供了实验分析依据。整个系统控制稳定可靠,重复性好,兼容性及扩展能力强。     

虚拟MODBUS协议在电气试验车中的应用

针对当前电气试验车集控系统中电力检测设备通信协议不统一的现状,在电气试验车研发中采用了全新的虚拟现场总线Modbus协议技术,将软件组态和硬件组态理念紧密结合,克服了不同厂家不同类型设备与试验车监控主机之间的通讯协议匹配问题。通过虚拟Modbus协议服务器软件提供标准化访问接口,使电气试验车测控软件可以用统一的方式控制各个检测设备,提高了电气试验车的系统集成度和设备兼容性。该方法的成功运用,也为高压电气试验设备通讯功能的标准化起到一定推动作用。     

机载远程智能接口数据集中器研究与实现

文章研究目的是研究新一代飞机机载计算机中具有通用化、标准化的远程智能接口数据集中器,以满足新一代飞机综合化航空电子系统要求;文章首先描述了远程智能接口数据集中器功能原理,然后重点介绍了AFDX网络通信、高速模拟信号采集、小信号处理、大功率控制、接口控制软件设计等远程智能接口关键技术,最后给出远程智能接口数据集中器具体实现;机载远程智能接口数据集中器已经在新一代飞机综合航电系统通过系统验证,试验结果证明远程智能接口数据集中器实现了各种传感器信息就近采集、及时进行数据转换和驱动输出控制的功能要求。     

双路热动力试验台集散控制系统设计与实现

自行设计了基于串行总线结构的双路热动力试验台集散控制系统 ,采用RS -4 2 2协议进行管理站与现场控制台的分布式智能仪表的远距离通讯和控制。管理站还设计了一套独立的高精度的数据采集系统 ,它由IEEE -4 88接口与管理站计算机通讯 ,管理站计算机以此为标准修正智能仪表及协调现场控制台控制。实现了对温度、压力、流量等的集散控制。     

基于CC-Link总线的沥青搅拌站控制系统设计

针对目前沥青搅拌站控制系统的不足、结构复杂、现场设备分散、接线繁杂及系统实时性差等问题,根据产品生产工艺流程,系统硬件设计采用三菱 Q00UCPU、CC-Link 主站模块 QJ61BT11N 等设备,辅以变频调速,高精度的传感器,可靠的数据通讯设备,多种信号通过分布式 I/O 组件和 CC-Link 传送至 PLC 进行处理;软件上设计了搅拌站的监控系统和现场设备的通讯接口,使用人机界面实现设备的远程控制,操作方便,工作稳定,降低了成本,提高了生产效率;该系统经过实际现场生产,总线通讯正常,累计生产超过8 000吨料,超过40 h无故障。     

ITER PF电源现场层监控系统网络拓扑延时分析

为保障ITER极向场(PF)电源系统的高实时性控制需求,根据其设备体积大、分布分散等特点,选取了支持多种设备连接拓扑的实时工业以太网现场总线EtherCAT作为ITER PF电源现场层监控系统的数据通讯协议.为研究ITER极向场电源现场层监控系统的实时性,分析了数据帧在几种适合ITER PF整流器单元现场层信号采集与控...     

基于TCP/IP协议的测控系统的开发

为实现复杂工业现场下的设备测试,本文介绍了一种基于TCP/IP协议的测控系统,该系统采用客户机/服务器模型。测控系统的中央控制计算机与子测控系统的下位机间为“一对多”通讯,中央控制计算机作为服务器,子测控系统的下位机作为客户机;子测控系统的上位机与下位机之间采用“一对一”网络通讯,子测控系统的下位机作为服务器,上位机作为客户机。中央控制计算机采用LabView开发,子测控系统的上位机与下位机采用Visual C+ 6.0开发。最终实现了测控系统的TCP/IP通讯,完成了复杂工业现场下的测试工作。     

Some mathematical aspects of Anderson localization: boundary effect,multimodality, and bifurcation

Anderson localization is a famous wave phenomenon that describes the absence of diffusion of waves in a disordered medium. Here we generalize the landscape theory of Anderson localization to general elliptic operators and complex boundary conditions using a probabilistic approach, and further investigate some mathematical aspects of Anderson localization that are rarely discussed before. First, we observe that under the Neumann boundary condition, the low energy quantum states are localized on the boundary of the domain with high probability. We provide a detailed explanation of this phenomenon using the concept of extended subregions and obtain an analytical expression of this probability in the one-dimensional case. Second, we find that the quantum states may be localized in multiple different subregions with high probability in the one-dimensional case and we derive an explicit expression of this probability for various boundary conditions. Finally, we examine a bifurcation phenomenon of the localization subregion as the strength of disorder varies. The critical threshold of bifurcation is analytically computed based on a toy model and the dependence of the critical threshold on model parameters is analyzed.     

Lipid hydroperoxides in nutrition,health, and diseases

Research on lipid peroxidation in food degradation, oil and fat nutrition, and age-related diseases has gained significant international attention for the view of improvement of societal health and longevity. In order to promote basic studies on these topics, a chemiluminescence detection-high performance liquid chromatography instrument using a high-sensitivity single photon counter as a detector was developed. This instrument enabled us to selectively detect and quantify lipid hydroperoxides, a primary product of lipid peroxidation reactions, as hydroperoxide groups at the lipid class level. Furthermore, an analytical method using liquid chromatography–tandem mass spectrometry has been established to discriminate the position and stereoisomerization of hydroperoxide groups in lipid hydroperoxides. Using these two methods, the reaction mechanisms of lipid peroxidation in food and in the body have been confirmed.     

Geometries,stabilities, and electronic properties analysis in In_nNi~((0,±1)) clusters: Molecular modeling and DFT calculations

Density functional theory(DFT) with the B3 LYP method and the SDD basis set is selected to investigate In_nNi,In_nNi~-, and In_nNi~+ (n = 1–14) clusters. For neutral and charged systems, several isomers and different multiplicities are studied with the aim to confirm the most stable structures. The structural evolution of neutral, cationic, and anionic In_nNi clusters, which favors the three-dimensional structures for n = 3–14. The main configurations of the In_nNi isomers are not affected by adding or removing an electron, the order of their stabilities is also nearly not affected. The obtained binding energy exhibits that the Ni-doped In_(13) cluster is the most stable species of all different sized clusters. The calculated fragmentation energy and the second-order energy difference as a function of the cluster size exhibit a pronounced even–odd alternation phenomenon. The electronic properties including energy gap(E_g), adiabatic electron affinity(AEA), vertical electron detachment energy(VDE), adiabatic ionization potential energy(AIP), and vertical ionization potential energy(VIP) are studied. The total magnetic moments show that the different magnetic moments depend on the number of the In atoms for charged In_nNi. Additionally, the natural population analysis of In_nNi~((0,±1)clusters is also discussed.     

Entropy Optimization,Maxwell–Boltzmann,and Rayleigh Distributions

In physics, communication theory, engineering, statistics, and other areas, one of the methods of deriving distributions is the optimization of an appropriate measure of entropy under relevant constraints. In this paper, it is shown that by optimizing a measure of entropy introduced by the second author, one can derive densities of univariate, multivariate, and matrix-variate distributions in the real, as well as complex, domain. Several such scalar, multivariate, and matrix-variate distributions are derived. These include multivariate and matrix-variate Maxwell–Boltzmann and Rayleigh densities in the real and complex domains, multivariate Student-t, Cauchy, matrix-variate type-1 beta, type-2 beta, and gamma densities and their generalizations.     

微波消解-ICP-AES测定香烟接装纸中的汞、砷、铅、铬、镉和硒

采用HNO3-HCl-HF-H2O2消解体系对香烟接装纸进行湿法消解和微波消解,去除有机成分,保留待测元素。结果表明:不同种类的接装纸中各元素含量也不尽相同,但是大量吸烟对身体的有害程度还是显而易见的。采用微波消解-电感耦合等离子体-原子发射光谱法测定香烟接装纸中的As、Cd、Cr、Hg、Pb、Se等的含量。重金属元素加标回收率为96.7%—104.8%,检出限在0.000075—0.1288μg/mL范围内。     

Correlations,Information Backflow,and Objectivity in a Class of Pure Dephasing Models

We critically examine the role that correlations established between a system and fragments of its environment play in characterising the ensuing dynamics. We employ a dephasing model with different initial conditions, where the state of the initial environment represents a tunable degree of freedom that qualitatively and quantitatively affects the correlation profiles, but nevertheless results in the same reduced dynamics for the system. We apply recently developed tools for the characterisation of non-Markovianity to carefully assess the role that correlations, as quantified by the (quantum) Jensen–Shannon divergence and relative entropy, as well as changes in the environmental state, play in whether the conditions for classical objectivity within the quantum Darwinism paradigm are met. We demonstrate that for precisely the same non-Markovian reduced dynamics of the system arising from different microscopic models, some exhibit quantum Darwinistic features, while others show that no meaningful notion of classical objectivity is present. Furthermore, our results highlight that the non-Markovian nature of an environment does not a priori prevent a system from redundantly proliferating relevant information, but rather it is the system’s ability to establish the requisite correlations that is the crucial factor in the manifestation of classical objectivity.     

Viscosity,heat conductivity,and Prandtl number effects in the Rayleigh–Taylor Instability

The two-dimensional Rayleigh–Taylor instability problem is simulated with a multiple-relaxation-time discrete Boltzmann model with a gravity term. Viscosity, heat conductivity, and Prandtl number effects are probed from macroscopic and nonequilibrium viewpoints. In the macro sense, both viscosity and heat conduction show a significant inhibitory effect in the reacceleration stage, which is mainly achieved by inhibiting the development of the Kelvin–Helmholtz instability. Before this, the Prandtl number effect is not sensitive. Viscosity, heat conductivity, and Prandtl number effects on nonequilibrium manifestations and the degree of correlation between the nonuniformity and the nonequilibrium strength in the complex flow are systematically investigated.     

RET receptor signaling: Function in development,metabolic disease,and cancer

The RET proto-oncogene encodes a receptor tyrosine kinase whose alterations are responsible for various human cancers and developmental disorders, including thyroid cancer, non-small cell lung cancer, multiple endocrine neoplasia type 2, and Hirschsprung’s disease. RET receptors are physiologically activated by glial cell line-derived neurotrophic factor (GDNF) family ligands that bind to the coreceptor GDNF family receptor α (GFRα). Signaling via the GDNF/GFRα1/RET ternary complex plays crucial roles in the development of the enteric nervous system, kidneys, and urinary tract, as well as in the self-renewal of spermatogonial stem cells. In addition, another ligand, growth differentiation factor-15 (GDF15), has been shown to bind to GFRα-like and activate RET, regulating body weight. GDF15 is a stress response cytokine, and its elevated serum levels affect metabolism and anorexia-cachexia syndrome. Moreover, recent development of RET-specific kinase inhibitors contributed significantly to progress in the treatment of patients with RET-altered cancer. This review focuses on the broad roles of RET in development, metabolic diseases, and cancer.     

Analytical Solutions,Moments, and Their Asymptotic Behaviors for the Time-Space Fractional Cable Equation

Following the fractional cable equation established in the letter [B.I. Henry, T.A.M. Langlands, and S.L. Wearne, Phys. Rev. Lett. 100 (2008) 128103], we present the time-space fractional cable equation which describes the anomalous transport of electrodiffusion in nerve cells. The derivation is based on the generalized fractional Ohm's law; and the temporal memory effects and spatial-nonlocality are involved in the time-space fractional model. With the help of integral transform method we derive the analytical solutions expressed by the Green's function; the corresponding fractional moments are calculated; and their asymptotic behaviors are discussed. In addition, the explicit solutions of the considered model with two different external current injections are also presented.     

Regularization,Bayesian Inference,and Machine Learning Methods for Inverse Problems

Classical methods for inverse problems are mainly based on regularization theory, in particular those, that are based on optimization of a criterion with two parts: a data-model matching and a regularization term. Different choices for these two terms and a great number of optimization algorithms have been proposed. When these two terms are distance or divergence measures, they can have a Bayesian Maximum A Posteriori (MAP) interpretation where these two terms correspond to the likelihood and prior-probability models, respectively. The Bayesian approach gives more flexibility in choosing these terms and, in particular, the prior term via hierarchical models and hidden variables. However, the Bayesian computations can become very heavy computationally. The machine learning (ML) methods such as classification, clustering, segmentation, and regression, based on neural networks (NN) and particularly convolutional NN, deep NN, physics-informed neural networks, etc. can become helpful to obtain approximate practical solutions to inverse problems. In this tutorial article, particular examples of image denoising, image restoration, and computed-tomography (CT) image reconstruction will illustrate this cooperation between ML and inversion.