Why Phenolic Acids Are Unlikely Primary Allelochemicals in Rice

Allelopathy in rice (Oryza sativa, L.) effective against weeds has been found in about 3.5% of tested rice germplasm in both laboratory and field experimentation. However, the allelochemicals responsible for growth inhibition of rice-associated weeds have not yet been identified. In the literature, phenolic acids are often mentioned as putative allelochemicals. If phenolic acids commonly reach growth inhibitory concentrations in rice ecosystems, it must be expected that the degree of tolerance to phenolic acids will vary among traditional rice cultivars or plant species adapted to rice environments having inherently different phenolic acid concentrations. Phenolic acids concentrations are normally greater in submerged than in aerobic soils. A dose–response study, however, showed that seedlings of rice cultivars adapted to submerged anaerobic soils did not have higher level of tolerance against p-hydroxybenzoic acid than did seedlings of varieties adapted to aerobic upland soils. Moreover, traditional rice cultivars had no greater tolerance than did improved cultivars that were recently bred for traits other than tolerance of phenolic acids. Similarly, there were no differences in tolerance of p-hydroxybenzoic acid between two Echinochloa weed species adapted to either anaerobic or aerobic growth conditions. Thus, neither the rice cultivars nor weed species had evolved different tolerance levels against the phenolic acid. However, all rice cultivars had significantly greater tolerance of p-hydroxybenzoic acid than did either weed species. In a second experiment, the rates at which rice plants released phenolic acids into solution cultures were measured for at least one month, the time period of greatest allelopathic activity following planting under field conditions. The maximum release rate of phenolic acids during the first month of growth was approximately 10 g/plant/day. At a conventional plant density, the release rate of phenolic acids would be approximately 1 mg/m²day. This order of release rate cannot provide concentrations remotely close to phytotoxic levels determined for these rice cultivars and weed species. The results presented in this paper do not preclude the possibility that phenolic acids might be one component in a mixture of chemicals that, when present simultaneously, are allelopathic.     

On adaptive sliding mode control without switching gain overestimation

This paper presents some further results on adaptive sliding mode control (ASMC) for a class of nonlinear systems with bounded uncertain parameters. Given a large initial tracking error, current ASMC design generally produces an unnecessarily large switching gain, consequently leading to a serious chattering problem or a large‐amplitude control jump for the continuous counterpart. To solve such an overadaptation problem, the switching gain adaptation mechanism is first analyzed in this paper, and the adaptation induced by the initial tracking error is suggested to be removed. Then, by exploiting the global sliding mode feature of time‐varying sliding mode control and integral sliding mode control, we present two effective methodologies for ASMC design. The proposed ASMC algorithms ensure that there is no overestimation of the switching gain and the system response is not slowed down when a small switching gain is generated. The validity of the proposed methods is verified by both theoretical analysis and simulation results. Copyright © 2012 John Wiley & Sons, Ltd.     

Methane absorption and application of mixed organic aggregate prepared from Span80 and alkaline salt

The water-based materials for mine gas absorption and explosion suppression were prepared, in which the mixed organic aggregate of Span80 and alkaline salt can be used as methane absorbent. Methane was used as a model of mine gas, and the absorptions of methane with different complex materials were studied using head space gas chromatography. Then the state of aqueous material was characterized with laser light scattering instrument and the effects of different complex materials on explosion suppression were preliminarily studied in explosion chamber which can simulate mine gas explosion. The research results showed that complex material could absorb methane and there was some correlation between the mean diameter of organic aggregate in aqueous material and the absorption effect. Additionally, the aqueous material could suppress the methane explosion to some degree. The material can absorb mine gas in atomization condition, therefore, degrease mine gas concentration and influence the distribution of mine gas in the space, and then suppress the mine gas explosion to some extent.     

ZYBG型矿用瓦斯输送管道自动抑爆装置研制

为了保障瓦斯输送管道的安全性,采用主动抑爆技术研制了ZYBG型矿用瓦斯输送管道自动抑爆装置。该装置利用火焰探测器探测瓦斯爆炸信号,并将信号通过光电转换传输给控制器,控制器对信号进行判定和分析,在爆炸接近防护区间的瞬间快速打开高压抑爆器,释放抑爆介质,熄灭火焰,阻断爆炸的进一步传播。抑爆性能试验结果表明,该抑爆装置能够在5ms内快速捕捉火焰信息,并在35ms内迅速喷洒抑爆介质。     

采用支持向量回归抑制噪声的经验模态分解方法

在实际信号分解中,经验模态分解（ EMD）是对噪声敏感的,往往会分离出一些虚假的本征模函数,对信号的分析产生一定影响。为了提高EMD分解的正确率,减少其出现虚假本征模函数的情况,文中提出了一种基于支持向量回归（ SVR）的去噪方法。先对一次EMD分解结果进行SVR逐层滤波并且对信号进行重组,然后利用EMD方法对重组信号进行二次分解。实验表明,二次分解结果已经非常接近于理想的分解结果,不会出现虚假IMF。这种分解方法对噪声不敏感,能有效提高EMD方法对噪声的容忍度。     

偏磁式消弧线圈在安钢220kV变电站的应用

分析偏磁式消弧线圈补偿装置的作用及工作原理,介绍偏磁式消弧线圈补偿装置在安钢某220kV变电站10kV系统的具体应用.     

改进R-FCN模型的小尺度行人检测

目的 为了有效解决传统行人检测算法在分辨率低、行人尺寸较小等情境下检测精度低的问题,将基于区域全卷积网络（region-based fully convolutional networks,R-FCN）的目标检测算法引入到行人检测中,提出一种改进R-FCN模型的小尺度行人检测算法。方法 为了使特征提取更加准确,在ResNet-101的conv5阶段中嵌入可变形卷积层,扩大特征图的感受野;为提高小尺寸行人检测精度,在ResNet-101中增加另一条检测路径,对不同尺寸大小的特征图进行感兴趣区域池化;为解决小尺寸行人检测中的误检问题,利用自举策略的非极大值抑制算法代替传统的非极大值抑制算法。结果 在基准数据集Caltech上进行评估,实验表明,改进的R-FCN算法与具有代表性的单阶段检测器（single shot multiBox detector,SSD）算法和两阶段检测器中的Faster R-CNN（region convolutional neural network）算法相比,检测精度分别提高了3.29%和2.78%;在相同ResNet-101基础网络下,检测精度比原始R-FCN算法提高了12.10%。结论 本文提出的改进R-FCN模型,使小尺寸行人检测精度更加准确。相比原始模型,改进的R-FCN模型对行人检测的精确率和召回率有更好的平衡能力,在保证精确率的同时,具有更大的召回率。     

A pair of parallel differential magnetic‐field probes with high measurement accuracy and high electric‐field suppression ratio

Magnetic‐field probes can be used for electromagnetic interference measurement of high‐speed circuits. The main magnetic probe performance includes sensitivity, spatial resolution, electric‐field suppression ratio (EFSR), and measurement accuracy. In this article, a pair of differential magnetic‐field probes is proposed to improve measurement accuracy without reducing sensitivity. The proposed differential probes consist of two asymmetric loop probes, which are designed in the same plane and separated by a row of periodic vias. The proposed differential probes are fabricated under PCB process. High accuracy can be achieved by measuring difference between outputs of the two probes. In addition, EFSR can be improved by size optimization of the differential magnetic‐field probes. Simulation and measurement results show the operating bandwidth is from 100 MHz to 12 GHz, the measurement error is 3.4% and the EFSR is about 40 dB. The proposed probes have higher measurement accuracy and higher EFSR than the conventional single probe, and larger operation bandwidth than the stacked differential probes.     

Radio frequency interference suppression algorithm in the spatial domian for high-frequency radars

Radio frequency interference suppression is a very important issue in applications of high-frequency surface wave radar. This paper proposes a new interference suppression algorithm which makes use of RF interference azimuth information on the basis of learning common RF interference suppression algorithms and spatial spectrum estimation. First, we apply the MUSIC algorithm to estimate the interference azimuth and obtains the interference's signal space after the first Fourier transform; next, we use space decomposition to decompose the radar echo and obtain interference components; last, we subtract radio frequency interference components from the original signals. This algorithm can do great amount of RF interference suppression in actual data and get good results.     

Research on adaptive notch filter cascading neural network anti-jamming algorithm

Satellite navigation suffers from performance degradation in the presence of narrowband interference. We present a Global Positioning System(GPS) receiver anti-jamming algorithm based on the neural network. The method combines the adaptive notch filter with the Back Propagation(BP) neural network. We first use the two order lattice infinite impulse response adaptive notch filter to eliminate-out-of-band jamming, then use the BP neural network predictor to estimate and cancel jamming. We analyze three aspects of algorithm performance which include acquired satellite numbers,signal-to-noise improvements and iteration numbers. Simulation results show that the method can effectively suppress narrowband interference and has a better anti-jamming capacity and a faster convergence speed.