Insect-corn kernel interaction: Chemical signaling of the grain and host recognition by Sitophilus zeamais

In living organisms, the cuticle has structural functions and is involved through chemical signaling in biological interactions such as plant-insect and provides protection against biotic and abiotic factors, thereby avoiding desiccation or the attack of predators. The objective of this study was to investigate the participation of the epicuticle in the maize kernel-Sitophilus zeamais interaction. The GC-MS analysis of the epicuticle extract demonstrated the presence of aliphatic hydrocarbons, alcohols, ethers, fatty acids, sterols and their derivatives. The results of bioassays show that the epicuticle of maize has a primordial role in its interaction with S. zeamais, and participates in the recognition and attraction to the food source, as well as regulating its reproduction. In addition the compounds present in the epicuticle extract may act as signal molecules and development regulators. This study reveals the effect of the maize kernel cuticle on Sitophilus behavior and contributes to the understanding of the interaction.     

Proposed network structures and combined adaptive algorithms for electrocardiogram signal denoising

An electrocardiogram (ECG) signal is a record of the electrical activities of heart muscle and is used clinically to diagnose heart diseases. An ECG signal should be presented as clear as possible to support accurate decisions made by doctors. This article proposes different combinations of combined adaptive algorithms to derive different noise-cancelling structures to remove (denoise) different kinds of noise from ECG signals. The algorithms are applied to the following types of noise: power line interference, baseline wander, electrode motion artifact, and muscle artifacts. Moreover, the results of the suggested models and algorithms are compared with those of conventional denoising tools such as the discrete wavelet transform, an adaptive filter, and a multilayer neural network (NN) to ensure the superiority of the proposed combined structures and algorithms. Furthermore, the hybrid concept is based on dual, triple, and quadruple combinations of well-known algorithms that derive adaptive filters, such as the least mean squares, normalized least mean squares and recursive least squares algorithms. The combinations are formulated based on partial update, variable step-size (VSS), and second iterative VSS algorithms, which are considered in different combinations. In addition, biased NN and unbiased linear neural network (ULNN) structures are considered. The performance of the different structures and related algorithms are evaluated by measuring the post-signal-to-noise ratio, mean square error, and percentage root mean square difference.     

Observer‐based fuzzy adaptive quantized control for uncertain nonlinear multiagent systems

This paper focuses on consensus quantized control design problem for uncertain nonlinear multiagent systems with unmeasured states. Every follower can be denoted through a system with unmeasurable states, hysteretic quantized input, and unknown nonlinearities. Fuzzy state observer and Fuzzy logic systems are employed to estimate unmeasured states and approximate unknown nonlinear functions, respectively. The hysteretic quantized input can be split into two bounded nonlinear functions to avoid chattering problem. By combining adaptive backstepping and first‐order filter signals, an observer‐based fuzzy adaptive quantized control scheme is designed for each follower. All signals exist in closed‐loop systems are semiglobally uniformly ultimately bounded, and all followers can accomplish a desired consensus results. Finally, a numerical example is employed to elaborate the effectiveness of proposed control strategy.     

Fractional observer to estimate periodical forces

In the present work we propose a fractional state observer with constant gain to estimate the periodical force exerted on a mechanical system by measuring only its displacement. The state observer is designed from both the Fourier series that approximates the periodical force and the equations of the damped harmonic oscillator that represents the behavior of the system. Specifically, the reconstruction of the force is carried out from the estimates of the series coefficients, which in fact are part of the dynamical system that composes the observer. Adams-Bashforth-Moulton method is used to compute the fractional derivatives of the observer in the Liouville-Caputo sense. Experiments based on real data are presented to show the advantages of using a fractional observer in the reconstruction of forces.     

非圆车削干扰分析与补偿

数控机床采用直线电机作为刀具的伺服进给机构,可以解决非圆零件的加工问题。但是非圆车削加工的加工精度会受到各种干扰的影响,其中主要的是切削力和控制系统及传感器所受到的干扰,介绍了采用切削力前馈补偿和卡尔曼滤波器2种实用的补偿方法,最后利用Simu-link软件进行了仿真证明。     

提高新集一矿提升系统可靠性实践

针对新集一矿摩擦轮绞车存在由于同步开关误报、井口到位不准确及箕斗被二次装煤而造成超载等不足之处,提出了一些切实可行的方法,解决提升系统有关问题,供提升系统改造和新建矿井设计所用。     

舰船综合业务传输设备的EMC设计

阐述了舰船综合业务传输设备的EMC设计思想,提出了具体解决方案.实践证明该方法可以有效地屏蔽各种电磁信号的干扰,保证设备正常工作.     

岩石超声波信号的小波时频分析

岩石超声波信号是一种非平稳信号.由于传统的短时Fourier变换(STFT)使用的窗函数固定,分辨率单一,其分析结果只能大致反映信号能量随时间的变化.小波变换(WT)以小波基为变换基础,具有多分辨率特点,其分析结果较详细地反映了质点震动强度随时间的衰减起伏变化.分析认为小波变换是一种更优越的处理岩石声学信号的时频方法.     

胛⑾讣际踅逃恐氐闶笛槭?上海交通大学

200030,上海200030磁悬浮;;微陀螺;;电容检测为了实现磁悬浮转子微陀螺的电容检测,使用数值积分方法计算了新型磁悬浮转子微陀螺的电容值与转子倾斜角度的关系。计算确定了电容极板尺寸,电容的连接采用了差动电容的连接方式。通过电容检测电路,检测到了小角度输入范围内的陀螺输出信号。检测结果表明:该电容结构对于静态角度输入具有较好的线性响应,该微陀螺原形的电容结构能够检测到的转子倾斜角度可达到0.1°,对应的电容变化约为1 000 aF,满足了微陀螺对电容检测的要求。Design of capacitance structure of micro gyroscope with electromagnetically levitated rotorHUANG Xiao-gang,LIU Wu,SHAO Shi-yi,CHEN Wen-yuan,ZHANG Wei