Objective To demonstrate changes in different frequencies of cerebral electrical activity or electroencephalogram （EEG） following exposure to high environmental heat in three different age groups of freely moving ra...Objective To demonstrate changes in different frequencies of cerebral electrical activity or electroencephalogram （EEG） following exposure to high environmental heat in three different age groups of freely moving rats. Methods Rats were divided into three groups （i） acute heat stress - subjected to a single exposure for four hours at 38 ℃; （ii） chronic heat stress exposed for 21 days daily for one hour at 38 ℃, and （iii） handling control groups. The digital polygraphic sleep-EEG recordings were performed just after the heat exposure from acute stressed rats and on 22nd day from chronic stressed rats by simultaneous recording of cortical EEG, EOG （electrooculogram）, and EMG （electromyogram）. Further, power spectrum analyses were performed to analyze the effects of heat stress. Results The frequency analysis of EEG signals following exposure to high environmental heat revealed that in all three age groups of rats, changes in higher frequency components （β2） were significant in all sleep-wake states following both acute and chronic heat stress conditions. After exposure to acute heat, significant changes in EEG frequencies with respect to their control groups were observed, which were reversed partly or fully in four hours of EEG recording. On the other hand, due to repetitive chronic exposure to hot environment, adaptive and long-term changes in EEG frequency patterns were observed. Conclusion The present study has exhibited that the cortical EEG is sensitive to environmental heat and alterations in EEG frequencies in different sleep-wake states due to heat stress can be differentiated efficiently by EEG power spectrum analysis.展开更多
Magnetic Barkhausen noise （ MBN） is a phenomenon of electromagnetic energy due to the movement of magnetic domain walls inside ferromagnetic materials when they are locally magnetized by an alternating magnetic fiel...Magnetic Barkhausen noise （ MBN） is a phenomenon of electromagnetic energy due to the movement of magnetic domain walls inside ferromagnetic materials when they are locally magnetized by an alternating magnetic fields. According to Faraday＇s law of electromagnetic induction, the noise can be received by the coil attached to the surface of the material being magnetized and the noise carries the message of the characteristics of the material such as stresses, hardness, phase content, etc. Based on the characteristic of the noise, researching about the relationship between the residual stress in the welding assembly and the noise are carried out. Furthermore, data process is performed by RMS （Root Mean Square） equation and Power Spectrum analysis.展开更多
To quantify the characteristics of the power spectrum of plant electrical signals, we defined the following concepts:spectral edge frequency (SEF), spectral center frequency (SCF), power index (PI) and power spectral ...To quantify the characteristics of the power spectrum of plant electrical signals, we defined the following concepts:spectral edge frequency (SEF), spectral center frequency (SCF), power index (PI) and power spectral entropy (PSE). These parameters were used to examine and quantify changes in the power spectrum of electrical signals in maize leaves under osmotic stress. In the absence of osmotic stress, the SEF of the electrical signal in maize leaves was approx. 0.2 Hz and the SCF was approx. 0.1 Hz. The electrical signal in maize leaves was mainly a slow wave signal with a frequency of 0-0.1 Hz. After 2 h osmotic stress, the SEF and SCF of the electrical signal increased to higher frequencies. The proportion of the fast wave frequency also increased to 0.1-0.2 Hz, resulting in a dramatic increase in PSE. We also found that the changes in PSE and SCF were significantly correlated during osmotic stress. We propose that the changes in the PSE and SCF in maize leaves can be used as a sensitive signal indicating water deficit in leaf cells under osmotic stress. Thus, measurement of SCF or PSE of electrical signals in maize leaves could be used to develop early warning and rapid diagnosis techniques for the water demands of plants.展开更多
应用K o lm ogorov熵评价准则,进行砂岩全应力应变曲线阶段特征的非线性动力学研究,定量描述了峰前、峰后和全程三个层次的分段特征。通过与功率谱分析结论的比较研究,得出砂岩全应力应变曲线阶段特征的K o lm ogorov熵分析具有高度的...应用K o lm ogorov熵评价准则,进行砂岩全应力应变曲线阶段特征的非线性动力学研究,定量描述了峰前、峰后和全程三个层次的分段特征。通过与功率谱分析结论的比较研究,得出砂岩全应力应变曲线阶段特征的K o lm ogorov熵分析具有高度的可靠性,是对功率谱分析方法的科学验证与有益补充,开辟了岩石全应力应变曲线分段特征定量研究的新途径,具有一定的理论意义。展开更多
文摘Objective To demonstrate changes in different frequencies of cerebral electrical activity or electroencephalogram （EEG） following exposure to high environmental heat in three different age groups of freely moving rats. Methods Rats were divided into three groups （i） acute heat stress - subjected to a single exposure for four hours at 38 ℃; （ii） chronic heat stress exposed for 21 days daily for one hour at 38 ℃, and （iii） handling control groups. The digital polygraphic sleep-EEG recordings were performed just after the heat exposure from acute stressed rats and on 22nd day from chronic stressed rats by simultaneous recording of cortical EEG, EOG （electrooculogram）, and EMG （electromyogram）. Further, power spectrum analyses were performed to analyze the effects of heat stress. Results The frequency analysis of EEG signals following exposure to high environmental heat revealed that in all three age groups of rats, changes in higher frequency components （β2） were significant in all sleep-wake states following both acute and chronic heat stress conditions. After exposure to acute heat, significant changes in EEG frequencies with respect to their control groups were observed, which were reversed partly or fully in four hours of EEG recording. On the other hand, due to repetitive chronic exposure to hot environment, adaptive and long-term changes in EEG frequency patterns were observed. Conclusion The present study has exhibited that the cortical EEG is sensitive to environmental heat and alterations in EEG frequencies in different sleep-wake states due to heat stress can be differentiated efficiently by EEG power spectrum analysis.
文摘Magnetic Barkhausen noise （ MBN） is a phenomenon of electromagnetic energy due to the movement of magnetic domain walls inside ferromagnetic materials when they are locally magnetized by an alternating magnetic fields. According to Faraday＇s law of electromagnetic induction, the noise can be received by the coil attached to the surface of the material being magnetized and the noise carries the message of the characteristics of the material such as stresses, hardness, phase content, etc. Based on the characteristic of the noise, researching about the relationship between the residual stress in the welding assembly and the noise are carried out. Furthermore, data process is performed by RMS （Root Mean Square） equation and Power Spectrum analysis.
基金supported by the National Natural Science Foundation of China(50977079)the Scientific Research Plan Project of Shaanxi Education Department(09JK667)
文摘To quantify the characteristics of the power spectrum of plant electrical signals, we defined the following concepts:spectral edge frequency (SEF), spectral center frequency (SCF), power index (PI) and power spectral entropy (PSE). These parameters were used to examine and quantify changes in the power spectrum of electrical signals in maize leaves under osmotic stress. In the absence of osmotic stress, the SEF of the electrical signal in maize leaves was approx. 0.2 Hz and the SCF was approx. 0.1 Hz. The electrical signal in maize leaves was mainly a slow wave signal with a frequency of 0-0.1 Hz. After 2 h osmotic stress, the SEF and SCF of the electrical signal increased to higher frequencies. The proportion of the fast wave frequency also increased to 0.1-0.2 Hz, resulting in a dramatic increase in PSE. We also found that the changes in PSE and SCF were significantly correlated during osmotic stress. We propose that the changes in the PSE and SCF in maize leaves can be used as a sensitive signal indicating water deficit in leaf cells under osmotic stress. Thus, measurement of SCF or PSE of electrical signals in maize leaves could be used to develop early warning and rapid diagnosis techniques for the water demands of plants.
文摘应用K o lm ogorov熵评价准则,进行砂岩全应力应变曲线阶段特征的非线性动力学研究,定量描述了峰前、峰后和全程三个层次的分段特征。通过与功率谱分析结论的比较研究,得出砂岩全应力应变曲线阶段特征的K o lm ogorov熵分析具有高度的可靠性,是对功率谱分析方法的科学验证与有益补充,开辟了岩石全应力应变曲线分段特征定量研究的新途径,具有一定的理论意义。
