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.     

Changing Microspatial Patterns of Sulfate-Reducing Microorganisms (SRM) during Cycling of Marine Stromatolite Mats

Microspatial arrangements of sulfate-reducing microorganisms (SRM) in surface microbial mats (~1.5 mm) forming open marine stromatolites were investigated. Previous research revealed three different mat types associated with these stromatolites, each with a unique petrographic signature. Here we focused on comparing “non-lithifying” (Type-1) and “lithifying” (Type-2) mats. Our results revealed three major trends: (1) Molecular typing using the dsrA probe revealed a shift in the SRM community composition between Type-1 and Type-2 mats. Fluorescence in-situ hybridization (FISH) coupled to confocal scanning-laser microscopy (CSLM)-based image analyses, and ³⁵SO₄ ²⁻-silver foil patterns showed that SRM were present in surfaces of both mat types, but in significantly (p < 0.05) higher abundances in Type-2 mats. Over 85% of SRM cells in the top 0.5 mm of Type-2 mats were contained in a dense 130 μm thick horizontal layer comprised of clusters of varying sizes; (2) Microspatial mapping revealed that locations of SRM and CaCO₃ precipitation were significantly correlated (p < 0.05); (3) Extracts from Type-2 mats contained acylhomoserine-lactones (C4-, C6-, oxo-C6 C7-, C8-, C10-, C12-, C14-AHLs) involved in cell-cell communication. Similar AHLs were produced by SRM mat-isolates. These trends suggest that development of a microspatially-organized SRM community is closely-associated with the hallmark transition of stromatolite surface mats from a non-lithifying to a lithifying state.     

液氮冷却对碳纤维复合材料钻削表面完整性的影响

目的 研究液氮冷却与钻削工艺对碳纤维复合材料钻削质量的影响。方法 采用YG10X硬质合金钻头开展碳纤维平纹织物/环氧树脂层压复合材料（T300）的液氮低温钻削与常温干式钻削的对比试验研究。分析液氮低温作用下不同钻削参数时的声发射信号有效电压值（Root-Mean-Square of Acoustic Emission Signals,AE-RMS）,并结合孔的加工质量与声发射信号进行有效的识别。结果 与常温干式钻削相比,液氮低温钻削的AE-RMS在钻削阶段平均值增大,且信号相对平稳,在钻出阶段末尾处减小,且无明显突变,孔出口分层因子和出口毛刺减小。在vf=30 mm/min时,孔出口分层因子降低了9.2%,孔壁表面质量提高。结论 与常温干式钻削相比,液氮低温钻削在钻削阶段中,AE-RMS增大,但其波动幅度减小,孔出口毛刺、撕裂等缺陷减少。通过SEM观察,液氮低温钻削下的纤维断口明显减少,树脂涂覆表面整洁平滑,横向纤维与树脂界面有较好的结合性,没有大面积纤维树脂剥离,孔壁表面质量提高。     

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     

超声信号的改进EMD阈值方法降噪研究

在进行工业超声无损检测的过程中,由于环境、仪器等原因产生噪声,对后续缺陷分析等工作形成一定干扰,不利于完成后期数据分析。因此为了使信号的信噪比有所提高,提出了一种改进的经验模态分解阈值降噪算法。同时对比小波软阈值降噪法与经验模态分解清除重复间隔阈值的方法,在MATLAB仿真软件中建立超声回波数学模型并进行算法验证。实验结果表明,经验模态分解降噪方法优于小波阈值降噪,改进后的经验模态分解阈值降噪方法在信噪比、均方误差、光滑度3个方面均有所提高,达到了较好的降噪效果。     

m序列伪随机动态测试信号建模与压缩检测方法

针对智能电网中动态负荷对电能计量的影响问题,建立了m序列伪随机动态测试信号的参数模型,并分析了该测试信号的统计特性;证明了该动态测试信号的频域稀疏性,采用压缩感知理论建立了伪随机动态测试信号的压缩感知检测系统模型,采用稳态优化方法构建了压缩感知测量矩阵;在此基础上,针对m序列伪随机动态测试信号,提出了电能量值的压缩感知测量方法;仿真分析了长度为255位、511位、1023位单周期和多周期m序列动态测试信号的相对误差,误差均小于10~(-12),可忽略不计,表明所提压缩感知测量方法能够准确测量伪随机动态测试信号的电能量值。     

基于振动信号的齿轮可靠性评估

为了保障产品设备能够安全可靠地运行,提出了基于设备振动信号的运行可靠性评估方法。该方法可以把反映设备运行状态的特征指标与可靠性指标之间建立联系,将提取并优选出的敏感特征指标与比例故障率模型相结合,建立适用于齿轮箱设备的可靠性评估模型,从而实现设备运行可靠性的有效评估。将该方法应用于减速齿轮箱的可靠性分析中,并在试验中随机抽取60个数据文件进行识别验证,对齿轮性能退化状态识别率达86.67%,表明此方法的合理性和有效性。