Humans have been using Cannabis and its extracts for a few thousand years as a medicinal and recreational drug. How- ever, the chemical component in Cannabis sativa, △9-tet- rahydrocannabinol （△9-THC）, an exogenou...Humans have been using Cannabis and its extracts for a few thousand years as a medicinal and recreational drug. How- ever, the chemical component in Cannabis sativa, △9-tet- rahydrocannabinol （△9-THC）, an exogenous cannabinoid, remained unknown until it was isolated and identified as the main psychoactive ingredient （Gaoni and Mechoulam, 1964）.展开更多
In mining, reservoir impoundment and hydraulic fracturing exploitation, the induced microseismic clusters may present complex waveforms at receivers since the individual events generally arrive very close. And the rou...In mining, reservoir impoundment and hydraulic fracturing exploitation, the induced microseismic clusters may present complex waveforms at receivers since the individual events generally arrive very close. And the routine methods for arrival picking are insufficiently efficient due to these strong influences. Here, we modified the empirical green function method and applied it to extract the green functions and the radiation coefficients of microseismic events with the largest energy in clusters.Multiple-channel records were used to estimate an "average" source spectrum and then the "average" source wavelet was removed from the records by deconvolution. We applied this method to the real data,and the result indicated clear improvement in extracting the dominant event of the clusters.展开更多
BACKGROUND Colorectal cancer(CRC)is one of the most common malignancies worldwide.AIM To explore the expression of microRNA miR-19a-3p and Forkhead box F2(FOXF2)in patients with CRC and the relevant mechanisms.METHODS...BACKGROUND Colorectal cancer(CRC)is one of the most common malignancies worldwide.AIM To explore the expression of microRNA miR-19a-3p and Forkhead box F2(FOXF2)in patients with CRC and the relevant mechanisms.METHODS Sixty-two CRC patients admitted to the hospital were enrolled into the study group,and sixty healthy people from the same period were assigned to the control group.Elbow venous blood was sampled from the patients and healthy individuals,and blood serum was saved for later analysis.MiR-19a-3p mimics,miR-19a-3p inhibitor,miR-negative control,small interfering-FOXF2,and short hairpin-FOXF2 were transfected into HT29 and HCT116 cells.Then quantitative polymerase chain reaction was performed to quantify the expression of miR-19a-3p and FOXF2 in HT29 and HCT116 cells,and western blot(WB)analysis was conducted to evaluate the levels of FOXF2,glycogen synthase kinase 3 beta(GSK-3β),phosphorylated GSK-3β(p-GSK-3β),β-catenin,p-β-catenin,α-catenin,Ncadherin,E-cadherin,and vimentin.The MTT,Transwell,and wound healing assays were applied to analyze cell proliferation,invasion,and migration,respectively,and the dual luciferase reporter assay was used to determine the correlation of miR-19a-3p with FOXF2.RESULTS The patients showed high serum levels of miR-19a-3p and low levels of FOXF2,and the area under the curves of miR-19a-3p and FOXF2 were larger than 0.8.MiR-19a-3p and FOXF2 were related to sex,tumor size,age,tumor-nodemetastasis staging,lymph node metastasis,and differentiation of CRC patients.Silencing of miR-19a-3p and overexpression of FOXF2 suppressed the epithelialmesenchymal transition,invasion,migration,and proliferation of cells.WB analysis revealed that silencing of miR-19a-3p and FOXF2 overexpression significantly suppressed the expression of p-GSK-3β,β-catenin,N-cadherin,and vimentin;and increased the levels of GSK-3β,p-β-catenin,α-catenin,and Ecadherin.The dual luciferase reporter assay confirmed that there was a targeted correlation of miR-19a-3p with FOXF2.In addition,a rescue experiment revealed that there were no differences in cell proliferation,invasion,and migration in HT29 and HCT116 cells co-transfected with miR-19a-3p-mimics+sh-FOXF2 and miR-19a-3p-inhibitor+si-FOXF2 compared to the miR-negative control group.CONCLUSION Inhibiting miR-19a-3p expression can upregulate the FOXF2-mediated Wnt/β-catenin signaling pathway,thereby affecting the epithelial-mesenchymal transition,proliferation,invasion,and migration of cells.Thus,miR-19a-3p is likely to be a therapeutic target in CRC.展开更多
The uniform mathematical model of distortion signals in power grid has been setup with the theory of Wiener-G Functional. Firstly,the Matlab simulation models were established. Secondly,the Wiener kernel of power load...The uniform mathematical model of distortion signals in power grid has been setup with the theory of Wiener-G Functional. Firstly,the Matlab simulation models were established. Secondly,the Wiener kernel of power load was found based on the Gaussian white noise as input. And then the uniform mathematical model of the power grid signal was established according to the homogeneous of the same order of Wiener functional series. Finally,taking three typical distortion sources which are semiconductor rectifier,electric locomotive and electric arc furnace in power grid as examples,we have validated the model through the Matlab simulation and analyzed the simulation errors. The results show that the uniform mathematical model of distortion signals in power grid can approximation the actual model by growing the items of the series under the condition of the enough storage space and computing speed.展开更多
Toll-like receptor （TLR）-mediated inflammatory response could negatively affect bone metabolism. In this study, we determined how osteogenesis is regulated during inflammatory responses that are downstream of TLR si...Toll-like receptor （TLR）-mediated inflammatory response could negatively affect bone metabolism. In this study, we determined how osteogenesis is regulated during inflammatory responses that are downstream of TLR signaling. Human primary osteoblasts were cultured in collagen gels. Pam3CSK4 （P3C） and Escherichia coli lipopolysaccharide （EcLPS） were used as TLR2 and TLR4 ligand respectively. Porphyromonas gingivalis LPS having TLR2 activity with either TLR4 agonism （Pg1690） or TLR4 antagonism （Pg1449） and mutant E. coli LPS （LPxE/LPxF/WSK） were used. IL-lp, SH2-containing inositol phosphatase-1 （SHIP1） that has regulatory roles in osteogenesis, alkaline phosphatase and mineralization were analyzed. 3α-Aminocholestane （3AC） was used to inhibit SHIP1. Our results suggest that osteoblasts stimulated by P3C, poorly induced IL-1β but strongly upregulated SHIP1 and enhanced osteogenic mediators. On the contrary, EcLPS significantly induced IL-1β and osteogenic mediators were not induced. While Pg1690 downmodulated osteogenic mediators, Pg1449 enhanced osteogenic responses, suggesting that TLR4 signaling annuls osteogenesis even with TLR2 activity. Interestingly, mutant E. coli LPS that induces weak inflammation upregulated osteogenesis, but SHIP1 was not induced. Moreover, inhibiting SHIP1 significantly upregulated TLR2-mediated inflammatory response and downmodulated osteogenesis. In conclusion, these results suggest that induction of weak inflammatory response through TLR2 （with SHIP1 activity） and mutant TLR4 ligands could enhance osteogenesis.展开更多
In this report the combined method of correlation radar signal(RS)processing based on the theory of atomic functions(AF)is examined.Examples of using of new Kravchenko probability weight functions(WF)designs are prese...In this report the combined method of correlation radar signal(RS)processing based on the theory of atomic functions(AF)is examined.Examples of using of new Kravchenko probability weight functions(WF)designs are presented.Quality functional to estimate accuracy and efficiency of RS processing for concrete physical models is constructed.It is shown that the proposed approach significantly improves the quality of the coherent analysis of RS.展开更多
As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery...As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn＇t require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor＇s own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.展开更多
Blind separation of source signals usually relies either on the condition of statistically independence or involving their higher-order cumulants. The model of two channels signal separation is considered. A criterion...Blind separation of source signals usually relies either on the condition of statistically independence or involving their higher-order cumulants. The model of two channels signal separation is considered. A criterion based on correlation functions is proposed. It is proved that the signals can be separated, using only the condition of noncorrelation. An algorithm is derived, which only involves the solution to quadric nonlinear equations.展开更多
According to the features of the wideband underwater acoustic signals,an algorithm for the wideband ambiguity function is put forward based on Mellin transform.The wideband acoustic signal processing using the fast Me...According to the features of the wideband underwater acoustic signals,an algorithm for the wideband ambiguity function is put forward based on Mellin transform.The wideband acoustic signal processing using the fast Mellin transform is also explored.The theoretical analysis and simulation results show that the algorithm has not only high computation efficiency but also good concentration in wideband ambiguity domain.It suits for the wideband underwater acoustic signal processing.展开更多
Denervation often results in skeletal muscle atrophy.Different mechanisms seem to be involved in the determination between denervated slow and fast skeletal muscle atrophy.At the epigenetic level,mi RNAs are thought t...Denervation often results in skeletal muscle atrophy.Different mechanisms seem to be involved in the determination between denervated slow and fast skeletal muscle atrophy.At the epigenetic level,mi RNAs are thought to be highly involved in the pathophysiological progress of denervated muscles.We used mi RNA microarrays to determine mi RNA expression profiles from a typical slow muscle（soleus muscle） and a typical fast muscle（tibialis anterior muscle） at an early denervation stage in a rat model.Results showed that mi R-206,mi R-195,mi R-23 a,and mi R-30 e might be key factors in the transformation process from slow to fast muscle in denervated slow muscles.Additionally,certain mi RNA molecules（mi R-214,mi R-221,mi R-222,mi R-152,mi R-320,and Let-7e） could be key regulatory factors in the denervated atrophy process involved in fast muscle.Analysis of signaling pathway networks revealed the mi RNA molecules that were responsible for regulating certain signaling pathways,which were the final targets（e.g.,p38 MAPK pathway; Pax3/Pax7 regulates Utrophin and follistatin by HDAC4; IGF1/PI3K/Akt/m TOR pathway regulates atrogin-1 and Mu RF1 expression via Fox O phosphorylation）.Our results provide a better understanding of the mechanisms of denervated skeletal muscle pathophysiology.展开更多
Ambiguity function （AF） is proposed to represent ultrasonic signal to resolve the preprocessing problem of different center frequencies and different arriving times among ultrasonic signals for feature extraction, a...Ambiguity function （AF） is proposed to represent ultrasonic signal to resolve the preprocessing problem of different center frequencies and different arriving times among ultrasonic signals for feature extraction, as well as offer time-frequency features for signal classification. Moreover, Karhunen-Loeve （K-L） transform is considered to extract signal features from ambiguity plane, and then the features are presented to probabilistic neural network （PNN） for signal classification. Experimental results show that ambiguity function eliminates the difference of center frequency and arriving time existing in ultrasonic signals, and ambiguity plane features extracted by K-L transform describe the signal of different classes effectively in a reduced dimensional space. Classification result suggests that the ambiguity plane features obtain better performance than the features extracted by wavelet transform （WT）.展开更多
To enhance the capacity of the radar-reconnaissance interception receiver recognizing linear frequency modulated (LFM) at a low signal-noise ratio, this paper presents WignerHough transform (WHT) of the LFM signal and...To enhance the capacity of the radar-reconnaissance interception receiver recognizing linear frequency modulated (LFM) at a low signal-noise ratio, this paper presents WignerHough transform (WHT) of the LFM signal and its corresponding characteristics, derives the probability density functions of the LFM signal and Gaussian white noise within WHT based on entropy (WHTE), dimension under different assumptions and puts forward a WHT algorithm based on entropy of slice to improve the capacity of detecting the LFM signal. Entropy of the WHT domain slice is adopted to assess the information size of polar radius or angle slice, which is converted into the weight factor to weight every slice. Double-deck weight is used to weaken the influences of noise and disturbance terms and WHTE treatment and signal detection procedure are also summarized. The rationality of the algorithm is demonstrated through theoretical analysis and formula derivation, the efficiency of the algorithm is verified by simulation comparison between WHT, fractional Fourier transform and periodic WHT, and it is highlighted that the WHTE algorithm has better detection accuracy and range of application against strong noise background.展开更多
Recently, various control methods represented by proportional-integral-derivative （PID） control are used for robotic control. To cope with the requirements for high response and precision, advanced feedforward contr...Recently, various control methods represented by proportional-integral-derivative （PID） control are used for robotic control. To cope with the requirements for high response and precision, advanced feedforward controllers such as gravity compensator, Coriolis/centrifugal force compensator and friction compensators have been built in the controller. Generally, it causes heavy computational load when calculating the compensating value within a short sampling period. In this paper, integrated recurrent neural networks are applied as a feedforward controller for PUMA560 manipulator. The feedforward controller works instead of gravity and Coriolis/centrifugal force compensators. In the learning process of the neural network by using back propagation algorithm, the learning coefficient and gain of sigmoid function are tuned intuitively and empirically according to teaching signals. The tuning is complicated because it is being conducted by trial and error. Especially, when the scale of teaching signal is large, the problem becomes crucial. To cope with the problem which concerns the learning performance, a simple and adaptive learning technique for large scale teaching signals is proposed. The learning techniques and control effectiveness are evaluated through simulations using the dynamic model of PUMA560 manipulator.展开更多
A heavy rainfall event that occurred over the middle and lower reaches of the Yangtze River Basin （YRB） during July 11-13 2000 is explored in this study. The potential/stream function is used to analyze the upstream...A heavy rainfall event that occurred over the middle and lower reaches of the Yangtze River Basin （YRB） during July 11-13 2000 is explored in this study. The potential/stream function is used to analyze the upstream ＂strong signals＂ of the water vapor transport in the Tibetan Plateau （TP）. The studied time period covers from 2000 LST 5 July to 2000 LST 15 July （temporal resolution： 6 hours）. By analyzing the three-dimensional structure of the water vapor flux, vorticity and divergence prior to and during the heavy rainfall event, the upstream ＂strong signals＂ related to this heavy rainfall event are revealed. A strong correlation exists between the heavy rainfall event in the YRB and the convective clouds over the TE The ＂convergence zone＂ of the water vapor transport is also identified, based on correlation analysis of the water vapor flux two days and one day prior to, and on the day of, the heavy rainfall. And this ＂convergence zone＂ coincides with the migration of the maximum rainfall over the YRB. This specific coupled structure actually plays a key role in generating heavy rainfall over the YRB. The eastward movement of the coupled system with a divergence]convergence center of the potential function at the upper/lower level resembles the spatiotemporal evolution of the heavy rainfall event over the YRB. These upstream ＂strong signals＂ are clearly traced in this study through analyzing the three-dimensional structure of the potential/stream function of upstream water vapor transport.展开更多
The electrical characteristics of tissue yield valuable information for the early diagnosis of pathological changes. Magneto-acoustic tomography( MAT) is a novel functional imaging approach for imaging electrical cond...The electrical characteristics of tissue yield valuable information for the early diagnosis of pathological changes. Magneto-acoustic tomography( MAT) is a novel functional imaging approach for imaging electrical conductivity. It combines the advantages of high spatial resolution of ultrasonic imaging and high contrast ratio of electrical impedance tomography. It has potential application value in the early tumor diagnosis and bioelectricity monitoring. The analysis and detection of the magneto acoustic signal have a key role in improving the contrast resolution,imaging resolution and reconstruction accuracy of the electrical conductivity image. In this paper,the amplitude,the waveform characteristics and the frequency characteristics of the magnetic sound signal are review ed by the theoretical research,simulation and testing experiments of the weak magneto-acoustic signal.展开更多
This paper proposes a desirable method to detect different kinds of low probability of intercept (LPI) radar signals, targeted at the main intra-pulse modulation method of LPI radar signals including the signals of li...This paper proposes a desirable method to detect different kinds of low probability of intercept (LPI) radar signals, targeted at the main intra-pulse modulation method of LPI radar signals including the signals of linear frequency modulation, phase code, and frequency code. Firstly, it improves the coherent integration of LPI radar signals by adding the periodicity of the ambiguity function. Then, it develops a frequency domain detection method based on fast Fourier transform (FFT) and segmented autocorrelation function to detect signals without features of linear frequency modulation by virtue of the distribution characteristics of noise signals in the frequency domain. Finally, this paper gives a verification of the performance of the method for different signal-to-noise ratios by conducting simulation experiments, and compares the method with existing ones. Additionally, this method is characterized by the straightforward calculation and high real-time performance, which is conducive to better detecting all kinds of LPI radar signals.展开更多
The present study used a microelectronic neural bridge comprised of electrode arrays for neural signal detection, functional electrical stimulation, and a microelectronic circuit including signal amplifying, processin...The present study used a microelectronic neural bridge comprised of electrode arrays for neural signal detection, functional electrical stimulation, and a microelectronic circuit including signal amplifying, processing, and functional electrical stimulation to bridge two separate nerves, and to restore the lost function of one nerve. The left leg of one spinal toad was subjected to external mechanical stimulation and functional electrical stimulation driving. The function of the left leg of one spinal toad was regenerated to the corresponding leg of another spinal toad using a microelectronic neural bridge. Oscilloscope tracings showed that the electromyographic signals from controlled spinal toads were generated by neural signals that controlled the spinal toad, and there was a delay between signals. This study demonstrates that microelectronic neural bridging can be used to restore neural function between different injured nerves.展开更多
The main symptom of patients with Alzheimer’s disease is cognitive dysfunction. Alzheimer’s disease is mainly diagnosed based on changes in brain structure. Functional connectivity reflects the synchrony of function...The main symptom of patients with Alzheimer’s disease is cognitive dysfunction. Alzheimer’s disease is mainly diagnosed based on changes in brain structure. Functional connectivity reflects the synchrony of functional activities between non-adjacent brain regions, and changes in functional connectivity appear earlier than those in brain structure. In this study, we detected resting-state functional connectivity changes in patients with Alzheimer’s disease to provide reference evidence for disease prediction. Functional magnetic resonance imaging data from patients with Alzheimer’s disease were used to show whether particular white and gray matter areas had certain functional connectivity patterns and if these patterns changed with disease severity. In nine white and corresponding gray matter regions, correlations of normal cognition, early mild cognitive impairment, and late mild cognitive impairment with blood oxygen level-dependent signal time series were detected. Average correlation coefficient analysis indicated functional connectivity patterns between white and gray matter in the resting state of patients with Alzheimer’s disease. Functional connectivity pattern variation correlated with disease severity, with some regions having relatively strong or weak correlations. We found that the correlation coefficients of five regions were 0.3–0.5 in patients with normal cognition and 0–0.2 in those developing Alzheimer’s disease. Moreover, in the other four regions, the range increased to 0.45–0.7 with increasing cognitive impairment. In some white and gray matter areas, there were specific connectivity patterns. Changes in regional white and gray matter connectivity patterns may be used to predict Alzheimer’s disease;however, detailed information on specific connectivity patterns is needed. All study data were obtained from the Alzheimer’s Disease Neuroimaging Initiative Library of the Image and Data Archive Database.展开更多
The ship hydraulic pressure signal is one of the important characters for the target detection and recognition. At present, most of the researches on the detection focus on the ways in the time domain. The ways are us...The ship hydraulic pressure signal is one of the important characters for the target detection and recognition. At present, most of the researches on the detection focus on the ways in the time domain. The ways are usually invalid in the large wind wave background. In order to solve the problem efficiently, we present an effectual way to detect the ship using the ship hydraulic pressure signal. Firstly, the signature in the proposed method is decomposed by wavelet-transform technique and reconstructed at the low-frequency region. Then,a predictive model is set up by using the radial basis function(RBF) neural network. Finally, the signature predictive error is regarded as the testing signal which can be used to judge whether the target exists or does not.The practical result shows that the method can improve the signal to noise ratio(SNR) obviously.展开更多
基金supported by National Institutes of Health grants NS076815
文摘Humans have been using Cannabis and its extracts for a few thousand years as a medicinal and recreational drug. How- ever, the chemical component in Cannabis sativa, △9-tet- rahydrocannabinol （△9-THC）, an exogenous cannabinoid, remained unknown until it was isolated and identified as the main psychoactive ingredient （Gaoni and Mechoulam, 1964）.
基金supported by the National Natural Science Foundation of China(Grant:41404038)the Natural Science Foundation of Jiangsu Province(Grant:BK20130570)the National Key R&D Program of China(2016YFC0600302)
文摘In mining, reservoir impoundment and hydraulic fracturing exploitation, the induced microseismic clusters may present complex waveforms at receivers since the individual events generally arrive very close. And the routine methods for arrival picking are insufficiently efficient due to these strong influences. Here, we modified the empirical green function method and applied it to extract the green functions and the radiation coefficients of microseismic events with the largest energy in clusters.Multiple-channel records were used to estimate an "average" source spectrum and then the "average" source wavelet was removed from the records by deconvolution. We applied this method to the real data,and the result indicated clear improvement in extracting the dominant event of the clusters.
文摘BACKGROUND Colorectal cancer(CRC)is one of the most common malignancies worldwide.AIM To explore the expression of microRNA miR-19a-3p and Forkhead box F2(FOXF2)in patients with CRC and the relevant mechanisms.METHODS Sixty-two CRC patients admitted to the hospital were enrolled into the study group,and sixty healthy people from the same period were assigned to the control group.Elbow venous blood was sampled from the patients and healthy individuals,and blood serum was saved for later analysis.MiR-19a-3p mimics,miR-19a-3p inhibitor,miR-negative control,small interfering-FOXF2,and short hairpin-FOXF2 were transfected into HT29 and HCT116 cells.Then quantitative polymerase chain reaction was performed to quantify the expression of miR-19a-3p and FOXF2 in HT29 and HCT116 cells,and western blot(WB)analysis was conducted to evaluate the levels of FOXF2,glycogen synthase kinase 3 beta(GSK-3β),phosphorylated GSK-3β(p-GSK-3β),β-catenin,p-β-catenin,α-catenin,Ncadherin,E-cadherin,and vimentin.The MTT,Transwell,and wound healing assays were applied to analyze cell proliferation,invasion,and migration,respectively,and the dual luciferase reporter assay was used to determine the correlation of miR-19a-3p with FOXF2.RESULTS The patients showed high serum levels of miR-19a-3p and low levels of FOXF2,and the area under the curves of miR-19a-3p and FOXF2 were larger than 0.8.MiR-19a-3p and FOXF2 were related to sex,tumor size,age,tumor-nodemetastasis staging,lymph node metastasis,and differentiation of CRC patients.Silencing of miR-19a-3p and overexpression of FOXF2 suppressed the epithelialmesenchymal transition,invasion,migration,and proliferation of cells.WB analysis revealed that silencing of miR-19a-3p and FOXF2 overexpression significantly suppressed the expression of p-GSK-3β,β-catenin,N-cadherin,and vimentin;and increased the levels of GSK-3β,p-β-catenin,α-catenin,and Ecadherin.The dual luciferase reporter assay confirmed that there was a targeted correlation of miR-19a-3p with FOXF2.In addition,a rescue experiment revealed that there were no differences in cell proliferation,invasion,and migration in HT29 and HCT116 cells co-transfected with miR-19a-3p-mimics+sh-FOXF2 and miR-19a-3p-inhibitor+si-FOXF2 compared to the miR-negative control group.CONCLUSION Inhibiting miR-19a-3p expression can upregulate the FOXF2-mediated Wnt/β-catenin signaling pathway,thereby affecting the epithelial-mesenchymal transition,proliferation,invasion,and migration of cells.Thus,miR-19a-3p is likely to be a therapeutic target in CRC.
基金Sponsored by the National Natural Science Foundation of China(Grant No.51277043)
文摘The uniform mathematical model of distortion signals in power grid has been setup with the theory of Wiener-G Functional. Firstly,the Matlab simulation models were established. Secondly,the Wiener kernel of power load was found based on the Gaussian white noise as input. And then the uniform mathematical model of the power grid signal was established according to the homogeneous of the same order of Wiener functional series. Finally,taking three typical distortion sources which are semiconductor rectifier,electric locomotive and electric arc furnace in power grid as examples,we have validated the model through the Matlab simulation and analyzed the simulation errors. The results show that the uniform mathematical model of distortion signals in power grid can approximation the actual model by growing the items of the series under the condition of the enough storage space and computing speed.
基金supported by Elam M. and Georgina E.Hack Memorial Research Funds,Department of Periodontics,University of Washington,Seattle,WA,USAsupported by WVCTSI funds,West Virginia University,Morgantown,WV,USA
文摘Toll-like receptor （TLR）-mediated inflammatory response could negatively affect bone metabolism. In this study, we determined how osteogenesis is regulated during inflammatory responses that are downstream of TLR signaling. Human primary osteoblasts were cultured in collagen gels. Pam3CSK4 （P3C） and Escherichia coli lipopolysaccharide （EcLPS） were used as TLR2 and TLR4 ligand respectively. Porphyromonas gingivalis LPS having TLR2 activity with either TLR4 agonism （Pg1690） or TLR4 antagonism （Pg1449） and mutant E. coli LPS （LPxE/LPxF/WSK） were used. IL-lp, SH2-containing inositol phosphatase-1 （SHIP1） that has regulatory roles in osteogenesis, alkaline phosphatase and mineralization were analyzed. 3α-Aminocholestane （3AC） was used to inhibit SHIP1. Our results suggest that osteoblasts stimulated by P3C, poorly induced IL-1β but strongly upregulated SHIP1 and enhanced osteogenic mediators. On the contrary, EcLPS significantly induced IL-1β and osteogenic mediators were not induced. While Pg1690 downmodulated osteogenic mediators, Pg1449 enhanced osteogenic responses, suggesting that TLR4 signaling annuls osteogenesis even with TLR2 activity. Interestingly, mutant E. coli LPS that induces weak inflammation upregulated osteogenesis, but SHIP1 was not induced. Moreover, inhibiting SHIP1 significantly upregulated TLR2-mediated inflammatory response and downmodulated osteogenesis. In conclusion, these results suggest that induction of weak inflammatory response through TLR2 （with SHIP1 activity） and mutant TLR4 ligands could enhance osteogenesis.
基金Russian Foundation for Basic Research(No.12-02-90425)
文摘In this report the combined method of correlation radar signal(RS)processing based on the theory of atomic functions(AF)is examined.Examples of using of new Kravchenko probability weight functions(WF)designs are presented.Quality functional to estimate accuracy and efficiency of RS processing for concrete physical models is constructed.It is shown that the proposed approach significantly improves the quality of the coherent analysis of RS.
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2007AA04Z433)Hunan Provincial Natural Science Foundation of China (Grant No. 09JJ8005)Scientific Research Foundation of Graduate School of Beijing University of Chemical and Technology,China (Grant No. 10Me002)
文摘As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn＇t require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor＇s own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.
文摘Blind separation of source signals usually relies either on the condition of statistically independence or involving their higher-order cumulants. The model of two channels signal separation is considered. A criterion based on correlation functions is proposed. It is proved that the signals can be separated, using only the condition of noncorrelation. An algorithm is derived, which only involves the solution to quadric nonlinear equations.
基金Sponsored by National Nature Science Foundation of China(10474079)
文摘According to the features of the wideband underwater acoustic signals,an algorithm for the wideband ambiguity function is put forward based on Mellin transform.The wideband acoustic signal processing using the fast Mellin transform is also explored.The theoretical analysis and simulation results show that the algorithm has not only high computation efficiency but also good concentration in wideband ambiguity domain.It suits for the wideband underwater acoustic signal processing.
基金supported by the National Natural Science Foundation of China,No.81101365,81171722 and 81000805
文摘Denervation often results in skeletal muscle atrophy.Different mechanisms seem to be involved in the determination between denervated slow and fast skeletal muscle atrophy.At the epigenetic level,mi RNAs are thought to be highly involved in the pathophysiological progress of denervated muscles.We used mi RNA microarrays to determine mi RNA expression profiles from a typical slow muscle（soleus muscle） and a typical fast muscle（tibialis anterior muscle） at an early denervation stage in a rat model.Results showed that mi R-206,mi R-195,mi R-23 a,and mi R-30 e might be key factors in the transformation process from slow to fast muscle in denervated slow muscles.Additionally,certain mi RNA molecules（mi R-214,mi R-221,mi R-222,mi R-152,mi R-320,and Let-7e） could be key regulatory factors in the denervated atrophy process involved in fast muscle.Analysis of signaling pathway networks revealed the mi RNA molecules that were responsible for regulating certain signaling pathways,which were the final targets（e.g.,p38 MAPK pathway; Pax3/Pax7 regulates Utrophin and follistatin by HDAC4; IGF1/PI3K/Akt/m TOR pathway regulates atrogin-1 and Mu RF1 expression via Fox O phosphorylation）.Our results provide a better understanding of the mechanisms of denervated skeletal muscle pathophysiology.
文摘Ambiguity function （AF） is proposed to represent ultrasonic signal to resolve the preprocessing problem of different center frequencies and different arriving times among ultrasonic signals for feature extraction, as well as offer time-frequency features for signal classification. Moreover, Karhunen-Loeve （K-L） transform is considered to extract signal features from ambiguity plane, and then the features are presented to probabilistic neural network （PNN） for signal classification. Experimental results show that ambiguity function eliminates the difference of center frequency and arriving time existing in ultrasonic signals, and ambiguity plane features extracted by K-L transform describe the signal of different classes effectively in a reduced dimensional space. Classification result suggests that the ambiguity plane features obtain better performance than the features extracted by wavelet transform （WT）.
基金supported by the Aeronautical Science Fund of China(201455960252015209619)
文摘To enhance the capacity of the radar-reconnaissance interception receiver recognizing linear frequency modulated (LFM) at a low signal-noise ratio, this paper presents WignerHough transform (WHT) of the LFM signal and its corresponding characteristics, derives the probability density functions of the LFM signal and Gaussian white noise within WHT based on entropy (WHTE), dimension under different assumptions and puts forward a WHT algorithm based on entropy of slice to improve the capacity of detecting the LFM signal. Entropy of the WHT domain slice is adopted to assess the information size of polar radius or angle slice, which is converted into the weight factor to weight every slice. Double-deck weight is used to weaken the influences of noise and disturbance terms and WHTE treatment and signal detection procedure are also summarized. The rationality of the algorithm is demonstrated through theoretical analysis and formula derivation, the efficiency of the algorithm is verified by simulation comparison between WHT, fractional Fourier transform and periodic WHT, and it is highlighted that the WHTE algorithm has better detection accuracy and range of application against strong noise background.
基金supported by Grant-in-Aid for Scientific Research(C) (No. 20560248) of Japan
文摘Recently, various control methods represented by proportional-integral-derivative （PID） control are used for robotic control. To cope with the requirements for high response and precision, advanced feedforward controllers such as gravity compensator, Coriolis/centrifugal force compensator and friction compensators have been built in the controller. Generally, it causes heavy computational load when calculating the compensating value within a short sampling period. In this paper, integrated recurrent neural networks are applied as a feedforward controller for PUMA560 manipulator. The feedforward controller works instead of gravity and Coriolis/centrifugal force compensators. In the learning process of the neural network by using back propagation algorithm, the learning coefficient and gain of sigmoid function are tuned intuitively and empirically according to teaching signals. The tuning is complicated because it is being conducted by trial and error. Especially, when the scale of teaching signal is large, the problem becomes crucial. To cope with the problem which concerns the learning performance, a simple and adaptive learning technique for large scale teaching signals is proposed. The learning techniques and control effectiveness are evaluated through simulations using the dynamic model of PUMA560 manipulator.
文摘A heavy rainfall event that occurred over the middle and lower reaches of the Yangtze River Basin （YRB） during July 11-13 2000 is explored in this study. The potential/stream function is used to analyze the upstream ＂strong signals＂ of the water vapor transport in the Tibetan Plateau （TP）. The studied time period covers from 2000 LST 5 July to 2000 LST 15 July （temporal resolution： 6 hours）. By analyzing the three-dimensional structure of the water vapor flux, vorticity and divergence prior to and during the heavy rainfall event, the upstream ＂strong signals＂ related to this heavy rainfall event are revealed. A strong correlation exists between the heavy rainfall event in the YRB and the convective clouds over the TE The ＂convergence zone＂ of the water vapor transport is also identified, based on correlation analysis of the water vapor flux two days and one day prior to, and on the day of, the heavy rainfall. And this ＂convergence zone＂ coincides with the migration of the maximum rainfall over the YRB. This specific coupled structure actually plays a key role in generating heavy rainfall over the YRB. The eastward movement of the coupled system with a divergence]convergence center of the potential function at the upper/lower level resembles the spatiotemporal evolution of the heavy rainfall event over the YRB. These upstream ＂strong signals＂ are clearly traced in this study through analyzing the three-dimensional structure of the potential/stream function of upstream water vapor transport.
基金supported by the Project of the National Natural Foundation of China (Grant Nos.61501523,81171424)
文摘The electrical characteristics of tissue yield valuable information for the early diagnosis of pathological changes. Magneto-acoustic tomography( MAT) is a novel functional imaging approach for imaging electrical conductivity. It combines the advantages of high spatial resolution of ultrasonic imaging and high contrast ratio of electrical impedance tomography. It has potential application value in the early tumor diagnosis and bioelectricity monitoring. The analysis and detection of the magneto acoustic signal have a key role in improving the contrast resolution,imaging resolution and reconstruction accuracy of the electrical conductivity image. In this paper,the amplitude,the waveform characteristics and the frequency characteristics of the magnetic sound signal are review ed by the theoretical research,simulation and testing experiments of the weak magneto-acoustic signal.
基金supported by the National Natural Science Foundation of China(61571462)Weapons and Equipment Exploration Research Project(7131464)
文摘This paper proposes a desirable method to detect different kinds of low probability of intercept (LPI) radar signals, targeted at the main intra-pulse modulation method of LPI radar signals including the signals of linear frequency modulation, phase code, and frequency code. Firstly, it improves the coherent integration of LPI radar signals by adding the periodicity of the ambiguity function. Then, it develops a frequency domain detection method based on fast Fourier transform (FFT) and segmented autocorrelation function to detect signals without features of linear frequency modulation by virtue of the distribution characteristics of noise signals in the frequency domain. Finally, this paper gives a verification of the performance of the method for different signal-to-noise ratios by conducting simulation experiments, and compares the method with existing ones. Additionally, this method is characterized by the straightforward calculation and high real-time performance, which is conducive to better detecting all kinds of LPI radar signals.
基金supported by the National Natural Science Foundation of China,No,90707005,61001046 and 61204018the Natural Science Foundation of Education Department of Jiangsu Province,No.11KJB510023the Special Foundation and Open Foundation of State Key Laboratory of Bioelectronics of Southeast University,No.2011E05
文摘The present study used a microelectronic neural bridge comprised of electrode arrays for neural signal detection, functional electrical stimulation, and a microelectronic circuit including signal amplifying, processing, and functional electrical stimulation to bridge two separate nerves, and to restore the lost function of one nerve. The left leg of one spinal toad was subjected to external mechanical stimulation and functional electrical stimulation driving. The function of the left leg of one spinal toad was regenerated to the corresponding leg of another spinal toad using a microelectronic neural bridge. Oscilloscope tracings showed that the electromyographic signals from controlled spinal toads were generated by neural signals that controlled the spinal toad, and there was a delay between signals. This study demonstrates that microelectronic neural bridging can be used to restore neural function between different injured nerves.
基金supported by the National Natural Science Foundation of China,No.61401308,61572063(both to XHW)the Natural Science Foundation of Beijing of China,No.L172055(to XHW)+3 种基金the Beijing Municipal Science&Technology Commission Research Fund of China,No.Z171100000417004(to XHW)the China Postdoctoral Fund,No.2018M631755(to XHW)the Special Fund for Improving Comprehensive Strength of Hebei University in the Midwest of China,No.801260201011(to XHW)the High-Level Talent Funding Project—Selective Post-doctoral Research Project Fund of Hebei Province of China,No.B2018003002(to XHW)
文摘The main symptom of patients with Alzheimer’s disease is cognitive dysfunction. Alzheimer’s disease is mainly diagnosed based on changes in brain structure. Functional connectivity reflects the synchrony of functional activities between non-adjacent brain regions, and changes in functional connectivity appear earlier than those in brain structure. In this study, we detected resting-state functional connectivity changes in patients with Alzheimer’s disease to provide reference evidence for disease prediction. Functional magnetic resonance imaging data from patients with Alzheimer’s disease were used to show whether particular white and gray matter areas had certain functional connectivity patterns and if these patterns changed with disease severity. In nine white and corresponding gray matter regions, correlations of normal cognition, early mild cognitive impairment, and late mild cognitive impairment with blood oxygen level-dependent signal time series were detected. Average correlation coefficient analysis indicated functional connectivity patterns between white and gray matter in the resting state of patients with Alzheimer’s disease. Functional connectivity pattern variation correlated with disease severity, with some regions having relatively strong or weak correlations. We found that the correlation coefficients of five regions were 0.3–0.5 in patients with normal cognition and 0–0.2 in those developing Alzheimer’s disease. Moreover, in the other four regions, the range increased to 0.45–0.7 with increasing cognitive impairment. In some white and gray matter areas, there were specific connectivity patterns. Changes in regional white and gray matter connectivity patterns may be used to predict Alzheimer’s disease;however, detailed information on specific connectivity patterns is needed. All study data were obtained from the Alzheimer’s Disease Neuroimaging Initiative Library of the Image and Data Archive Database.
文摘The ship hydraulic pressure signal is one of the important characters for the target detection and recognition. At present, most of the researches on the detection focus on the ways in the time domain. The ways are usually invalid in the large wind wave background. In order to solve the problem efficiently, we present an effectual way to detect the ship using the ship hydraulic pressure signal. Firstly, the signature in the proposed method is decomposed by wavelet-transform technique and reconstructed at the low-frequency region. Then,a predictive model is set up by using the radial basis function(RBF) neural network. Finally, the signature predictive error is regarded as the testing signal which can be used to judge whether the target exists or does not.The practical result shows that the method can improve the signal to noise ratio(SNR) obviously.
