Matched Stochastic Resonance Enhanced Underwater Passive Sonar Detection under Non-Gaussian Impulsive Background Noise.

Remote passive sonar detection with low-frequency band spectral lines has attracted much attention, while complex low-frequency non-Gaussian impulsive noisy environments would strongly affect the detection performance. This is a challenging problem in weak signal detection, especially for the high false alarm rate caused by heavy-tailed impulsive noise. In this paper, a novel matched stochastic resonance (MSR)-based weak signal detection model is established, and two MSR-based detectors named MSR-PED and MSR-PSNR are proposed based on a theoretical analysis of the MSR output response. Comprehensive detection performance analyses in both Gasussian and non-Gaussian impulsive noise conditions are presented, which revealed the superior performance of our proposed detector under non-Gasussian impulsive noise. Numerical analysis and application verification have revealed the superior detection performance with the proposed MSR-PSNR detector compared with energy-based detection methods, which can break through the high false alarm rate problem caused by heavy-tailed impulsive noise. For a typical non-Gasussian impulsive noise assumption with α=1.5, the proposed MSR-PED and MSR-PSNR can achieve approximately 16 dB and 22 dB improvements, respectively, in the detection performance compared to the classical PED method. For stronger, non-Gaussian impulsive noise conditions corresponding to α=1, the improvement in detection performance can be more significant. Our proposed MSR-PSNR methods can overcome the challenging problem of a high false alarm rate caused by heavy-tailed impulsive noise. This work can lay a solid foundation for breaking through the challenges of underwater passive sonar detection under non-Gaussian impulsive background noise, and can provide important guidance for future research work.

Adaptive Intrawell Matched Stochastic Resonance with a Potential Constraint Aided Line Enhancer for Passive Sonars.

Remote passive sonar detection and classification are challenging problems that require the user to extract signatures under low signal-to-noise (SNR) ratio conditions. Adaptive line enhancers (ALEs) have been widely utilized in passive sonars for enhancing narrowband discrete components, but the performance is limited. In this paper, we propose an adaptive intrawell matched stochastic resonance (AIMSR) method, aiming to break through the limitation of the conventional ALE by nonlinear filtering effects. To make it practically applicable, we addressed two problems: (1) the parameterized implementation of stochastic resonance (SR) under the low sampling rate condition and (2) the feasibility of realization in an embedded system with low computational complexity. For the first problem, the framework of intrawell matched stochastic resonance with potential constraint is implemented with three distinct merits: (a) it can ease the insufficient time-scale matching constraint so as to weaken the uncertain affect on potential parameter tuning; (b) the inaccurate noise intensity estimation can be eased; (c) it can release the limitation on system response which allows a higher input frequency in breaking through the large sampling rate limitation. For the second problem, we assumed a particular case to ease the potential parameter a o p t = 1 . As a result, the computation complexity is greatly reduced, and the extremely large parameter limitation is relaxed simultaneously. Simulation analyses are conducted with a discrete line signature and harmonic related line signature that reflect the superior filtering performance with limited sampling rate conditions; without loss of generality of detection, we considered two circumstances corresponding to H 1 (periodic signal with noise) and H 0 (pure noise) hypotheses, respectively, which indicates the detection performance fairly well. Application verification was experimentally conducted in a reservoir with an autonomous underwater vehicle (AUV) to validate the feasibility and efficiency of the proposed method. The results indicate that the proposed method surpasses the conventional ALE method in lower frequency contexts, where there is about 10 dB improvement for the fundamental frequency in the sense of power spectrum density (PSD).

Arc hopping dynamics induced by interfacial negative differential resistance.

Pattern formation in plasma-solid interaction represents a great research challenge in many applications from plasma etching to surface treatment, whereby plasma attachments on electrodes (arc roots) are constricted to self-organized spots. Gliding arc discharge in a Jacob's Ladder, exhibiting hopping dynamics, provides a unique window to probe the nature of pattern formation in plasma-surface interactions. In this work, we find that the existence of negative differential resistance (NDR) across the sheath is responsible for the observed hopping pattern. Due to NDR, the current density and potential drop behave as activator and inhibitor, the dynamic interactions of which govern the surface current density re-distribution and the formation of structured spots. In gliding arc discharges, new arc roots can form separately in front of the existing root(s), which happens periodically to constitute the stepwise hopping. From the instability phase-diagram analysis, the phenomenon that arc attachments tend to constrict itself spontaneously in the NDR regime is well explained. Furthermore, we demonstrate via a comprehensive magnetohydrodynamics (MHD) computation that the existence of a sheath NDR can successfully reproduce the arc hopping as observed in experiments. Therefore, this work uncovers the essential role of sheath NDR in the plasma-solid surface pattern formation and opens up a hitherto unexplored area of research for manipulating the plasma-solid interactions.

Correlation Analysis of Rubella Incidence and Meteorological Variables Based on Chinese Medicine Theory of Yunqi.

OBJECTIVE: To analyze the correlations between the incidence of rubella and meteorological factors over the same period and previous periods including 1, 2, 3 and 4 year ago (defined according to Chinese medicine Yunqi theory of "pestilence occurring after 3 years") and establish the rubella-meteorological forecast models for Beijing area, China. METHODS: Data regarding the incidence of rubella between 1990 and 2004 from Beijing Center for Disease Control and Prevention, and the meteorological variables including daily average temperatures, daily average wind speeds, average precipitations, average relative humidity, average vapor pressures and average low cloud covers between 1986 and 2004 were collected from the Beijing Meteorological Observatory. Descriptive statistics and back-propagation artificial neural network for forecast model's establishment were adopted for data analysis. RESULTS: The average temperature and relative humidity have a great contribution (100%) to the rubella morbidity. But the combination of other meteorological factors contributed to improve the accuracy of rubella-meteorological forecast models. The forecast accuracy could be improved by 76% through utilizing a combination of meteorological variables spanning from 3 years ago to the present rather than utilizing data from a single year or dating back to more earlier time than 3 years. CONCLUSIONS: There is a close relationship between the incidence of rubella and meteorological variables in current year and previous 3 years. This finding suggests that rubella prediction would benefit from consideration to previous climate changes.

[Influence of repeated seizures and large dosage anti-epileptic drug on phosphorylated cAMP response element binding protein in rat's hippocampus and effect of Caoguo Zhimu Decoction].

OBJECTIVE: To study the influence of repeated seizures and anti-epileptic drug on phosphorylated cAMP response element binding protein (pCREB) in rat model of cognitive impairment, and the effect of Caoguo Zhimu Decoction (CZD) on it. METHODS: On the basis of epileptic model induced by pentylenetetrazol (PTZ), cognitive impairment model was induced by kindling epilepsy with PTZ everyday, which were then di-vided into the model-1 group, the CZD-1 group, the nimodipine-1 group, and those by injecting large dosage phenytoin sodium were divided into the model-2 group, the CZD-2 group and the nimodipine-2 group. Changes of pCREB protein in rat's hippocampus were detected using immunohistochemistry and Western blotting assay. RESULTS: The expression of pCREB was higher in the CZD-1 and nimodipine-1 group than in the model group, while it was significantly different in the CZD-2 and nimodipine-2 groups than in the model-2 group. CONCLUSION: CZD could relieve the cognitive dysfunction in the epileptic model rats induced by everyday PTZ kindling or by dilantin through increasing the pCREB expression.

Incidence of allergic rhinitis and meteorological variables: Non-linear correlation and non-linear regression analysis based on Yunqi theory of chinese medicine.

OBJECTIVE: To analyze the correlations between the incidence of allergic rhinitis (AR) and meteorological variables of previous periods, so as to establish non-linear prediction equations of AR in Beijing area. METHODS: AR patients (10,478 cases) collected from Beijing Tongren Hospital during 2007-2010 and meteorological data (including daily average temperature, daily maximum temperature, daily minimum temperature, daily relative humidity, daily average vapor pressure, daily dew point temperature, daily precipitation, daily average wind speed, sea level pressure, and degree of comfort) collected from Beijing Municipal Meteorological Observatory in the same periods were used for the analysis. Non-linear correlation and regression were adopted to analyze the relationship between AR incidence and meteorological variables of former six-qi stage which was defined according to Yunqi theory of Chinese medicine. Comprehensive meteorological parameter was introduced to establish the predictive model. RESULTS: The high incidence of AR appeared in the 4th qi stage (from the Beginning of Autumn to Autumn Equinox), while the changes of meteorological variables appeared in the 3rd qi stage (from Grain in Beard to Greater Heat), which advanced one phase. The incidence of AR was closely associated with vapor pressure. The correlation coeffifi cients of two predictive models were between 0.8931-0.9176 and all of them have passed signififi cant statistical tests, which showed a satisfactory fifi tting effect. CONCLUSION: Comprehensive meteorological parameters can be used to forecast AR incidence, which is benefifi cial to AR prevention.

Correlation analysis for the attack of bacillary dysentery and meteorological factors based on the Chinese medicine theory of Yunqi and the medical-meteorological forecast model.

OBJECTIVE: To explore the impact of meteorological factors on the outbreak of bacillary dysentery, so as to provide suggestions for disease prevention. METHODS: Based on the Chinese medicine theory of Yunqi, the descriptive statistics, single-factor correlation analysis and back-propagation artificial neural net-work were conducted using data on five basic meteorological factors and data on incidence of bacillary dysentery in Beijing, China, for the period 1970-2004. RESULTS: The incidence of bacillary dysentery showed significant positive correlation relationship with the precipitation, relative humidity, vapor pressure, and temperature, respectively. The incidence of bacillary dysentery showed a negatively correlated relationship with the wind speed and the change trend of average wind speed. The results of medical-meteorological forecast model showed a relatively high accuracy rate. CONCLUSIONS: There is a close relationship between the meteorological factors and the incidence of bacillary dysentery, but the contributions of which to the onset of bacillary dysentery are different to each other.

Clinical trial on the characteristics of zheng classification of pulmonary diseases based on infrared thermal imaging technology.

Zheng classification study based on infrared thermal imaging technology has not been reported before. To detect the relative temperature of viscera and bowels of different syndromes patients with pulmonary disease and to summarize the characteristics of different Zheng classifications, the infrared thermal imaging technology was used in the clinical trial. The results showed that the infrared thermal images characteristics of different Zheng classifications of pulmonary disease were distinctly different. The influence on viscera and bowels was deeper in phlegm-heat obstructing lung syndrome group than in cold-phlegm obstructing lung syndrome group. It is helpful to diagnose Zheng classification and to improve the diagnosis rate by analyzing the infrared thermal images of patients. The application of infrared thermal imaging technology provided objective measures for medical diagnosis and treatment in the field of Zheng studies and provided a new methodology for Zheng classification.

Correlation analysis for the attack of respiratory diseases and meteorological factors.

OBJECTIVE: To investigate the relationship between respiratory diseases onset and the meteorological factors in the same period and in a specific environment. METHODS METHODS: By using the data of daily incidence of respiratory diseases obtained from Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine from January 1, 1998 to December 31, 2007, and the data of 16 items of meteorological factors (such as the average, maximum, and minimum temperatures, etc., including meteorological factors derived) obtained from the Beijing Municipal Meteorological Observatory, mathematical statistical methods were applied to achieve the non-linear correlation analysis, or the correlation test, between the incidence of respiratory diseases and the time-related meteorological factors. RESULTS: The simple correlation coefficients of the relationship between the incidence of respiratory diseases and 9 meteorological elements, including the average values of temperature, maximum temperature, minimum temperature, degree of comfort, precipitation, vapor pressure, low cloud cover, change of vapor pressure, and change of wind speed, were all greater than 0.8286, in which one of the relationship between the incidence of respiratory diseases and the maximum temperature is as high as 0.9670. Statistical tests showed R>Rα=0.05 and F>Fα=0.05. CONCLUSIONS: The incidence of respiratory diseases was closely correlated to meteorological factors, such as air temperature, vapor pressure, precipitation, wind speed, etc. To a certain extent, this conclusion confirmed the scientificity and objectivity of the theory of five evolutive phases and six climatic factors (Wu Yun Liu Qi ) in Huang Di Nei Jing (The Yellow Emperor's Canon of Internal Medicine).