Teleseismic body waves extracted from ambient noise cross correlation between F-net and Chin Array phase Ⅱ

The vertical-vertical noise cross-correlation functions(NCFs)between two seismic arrays,the Japan F-net and Chin Array phase Ⅱ,are calculated using continuous recordings during 2013-2016.After array interferometry to obtain bin stacked NCFs,clear body waves are retrieved at different period bands.Teleseismic direct P waves for distance 15-40 degrees are observed between short period 3-10 s while core reflected PcP/ScS waves are more obvious for longer period 30-60 s.The signal-to-noise-ratio(SNR)of the short period P waves reaches its highest point with bin widths around 20 km while SNRs of PcP and ScS increase slowly with bin width.All those body waves demonstrate clear directivity with strong signals traveling from the east.The time-lapse SNR variations for the PcP and ScS show correlation with the occurrence of major earthquakes,while the P-wave SNR demonstrates seasonal variations with additional contribution from major earthquakes.The present results suggest teleseismic body waves can be retrieved through bin stacking,though further processing is still necessary to obtain finer waveforms such as P wave triplications.

Cross correlation mediated by distant Majorana zero modes with no overlap

Existing studies via shot noise calculation conclude that the cross correlation between the currents in the two leads connected by a pair of Majorana zero modes(MZMs)vanishes when their coupling energy𝜖∈_(M)→0.Motivated by the intrinsic nature of nonlocality of the MZMs,we revisit this important problem and propose an experimental scheme to demonstrate the nonvanishing cross correlation even at the limit𝜖∈_(M)→0.The proposed scheme employs the Andreevprocess-associated branch circuit currents,which are theoretically obtained by applying a decomposition analysis for the total currents while are accessible directly in practical measurement.For different bias voltage setup,we find intriguing results of both negative and positive correlations and carry out simple physical understanding using a quantum jump technique.Importantly,combining together with the evidence of the zero-bias-peak of conductance,the nonlocal cross correlation predicted in this work can help to confirm the existence of the nonlocal MZMs.

Composition of high frequency ambient noise from cross-correlation:A case study using a small aperture array

Long-time cross correlation of ambient noise has been proved as a powerful tool to extract Green＇s function between two receivers. The study of composition of ambient noise is important for a better understanding of this method. Previous studies confirm that ambient noise in the long period （3 s and longer） mostly consists of surface wave, and 0.25-2.5 s noise consists more of body waves. In this paper, we perform cross correlation processing at much higher frequency （30-70 Hz） using ambient noise recorded by a small aperture array. No surface waves emerge from noise correlation function （NCF）, but weak P waves emerge. The absence of surface wave in NCF is not due to high attenuation since surface waves are strong from active source, therefore probably the high ambient noise mostly consists of body wave and lacks surface wave. Origin of such high frequency body waves in ambient noise remains to be studied.

Efficient normalized cross correlation calculation method for stereo vision based robot navigation

Stereo vision systems are widely used for autonomous robot navigation. Most of them apply local window based methods for real-time purposes. Normalized cross correlation （NCC） is notorious for its high computational cost, though it is robust to different illumination conditions between two cameras. It is rarely used in real-time stereo vision systems. This paper proposes an efficient normalized cross correlation calculation method based on the integral image technique. Its computational complexity has no relationship to the size of the matching window. Experimental results show that our algorithm can generate the same results as traditional normalized cross correlation with a much lower computational cost. Our algorithm is suitable for planet rover navigation.

A Practical Approach for Missing Wireless Sensor Networks Data Recovery

In wireless sensor networks(WSNs),the performance of related applications is highly dependent on the quality of data collected.Unfortunately,missing data is almost inevitable in the process of data acquisition and transmission.Existing methods often rely on prior information such as low-rank characteristics or spatiotemporal correlation when recovering missing WSNs data.However,in realistic application scenarios,it is very difficult to obtain these prior information from incomplete data sets.Therefore,we aim to recover the missing WSNs data effectively while getting rid of the perplexity of prior information.By designing the corresponding measurement matrix that can capture the position of missing data and sparse representation matrix,a compressive sensing(CS)based missing data recovery model is established.Then,we design a comparison standard to select the best sparse representation basis and introduce average cross-correlation to examine the rationality of the established model.Furthermore,an improved fast matching pursuit algorithm is proposed to solve the model.Simulation results show that the proposed method can effectively recover the missing WSNs data.

Coulomb-assisted nonlocal electron transport between two pairs of Majorana bound states in a superconducting island

We investigate the nonlocal transport modulated by Coulomb interactions in devices comprising two interacting Majorana wires,where both nanowires are in proximity to a mesoscopic superconducting(SC)island.Each Majorana bound state(MBS)is coupled to one lead via a quantum dot with resonant levels.In this device,the nonlocal correlations can be induced in the absence of Majorana energy splitting.We find that the negative differential conductance and giant current noise cross correlation could be induced,due to the interplay between nonlocality of MBSs and dynamical Coulomb blockade effect.This feature may provide a signature for the existence of the MBSs.

THE CORRELATED CROSS SECTION OF THE MANY-BODY SCATTERING

In this paper the tensor probability current and continuity equation is obtained, with this the correlated cross section of many particle scattering can be evaluation.

Ambient noise spectral properties in the north area of Xisha

Ambient noise is very important in the prediction system of a sonar performance, because it determines the detection ranges always in a passive sonar and usually in an active sonar. In the uncertainty issue for the so-nar performance, it is necessary to know this factor＇s statistical characteristics that are only obtained by data processing from the underwater ambient noise measurements. Broad-band ambient noise signals from 16 hydrophones were amplified and recorded for 2 min every 1 h. The results show that the ambient noise is essentially depth independent. The cross correlation of the ambient noise levels （1, 6 and 12 h average） with a wind speed is presented. It was found that the correlation is excellent on the upper frequency band and the noise levels correlate better with high wind speed than with low wind speed.

Theoretical analysis of stack gas emission velocity measurement by optical scintillation

Theoretical analysis for an online measurement of the stack gas flow velocity based on the optical scintillation method with a structure of two parallel optical paths is performed. The causes of optical scintillation in a stack are first introduced. Then, the principle of flow velocity measurement and its mathematical expression based on cross correlation of the optical scintillation are presented. The field test results show that the flow velocity measured by the proposed technique in this article is consistent with the value tested by the Pitot tube. It verifies the effectiveness of this method. Finally, by use of the structure function of logarithmic light intensity fluctuations, the theoretical explanation of optical scintillation spec- tral characteristic in low frequency is given. The analysis of the optical scintillation spectrum provides the basis for the measurement of the stack gas flow velocity and particle concentration simultaneously.

Analysis of the relationship between water level fluctuation and seismicity in the Three Gorges Reservoir(China)

The Three Gorges Reservoir is a good site for the further researches on reservoir induced seismicity due to decades＇ seismic monitoring. After the first water impounding in 2003, seismic activity becomes more frequent than that before water impoundment. In order to quantitatively study, the relationship between the water level fluctuation and earthquakes in TGR, we introduced statistical methods to attain the goal. First of all, we relocated the earthquakes in TGR region with double difference method and divided the earthquakes into 5 clusters with clustering analysis method. Secondly, to examine the impacts of water level fluctuation in different water filling stages on the seismic activity in the 5 clusters, a series of statistical analyses are applied. Pearson correlation results show that only the 175 m water level fluc- tuation has significantly positive impacts on the seismic activity in clusters I, II, III and V with correlation coefficients of 0.44, 0.38, 0.66 and 0.63. Cross-correlation analysis demonstrates that 0, ], 0 and 0 month time delay separately for the clusters I, II, III and V exists. It illustrated the influences of the water loading and pore pressure diffusion on induced earthquakes. Cointegration tests and impulse response analysis denoted that the 175 m water level only had long term and significant effects just on the seismic events in the intersection region of the Fairy Mount Fault and Nine-brook Fault. One standard deviation shock to 175 m water level increased the seismic activity in cluster V for the first 3 months, and then the negative influence was shown. After 7 months, the negative impulse response becomes stable. The long-term effect of the 175 m water impoundment also proved the important role of pore pressure diffusion in RIS with time.

Automatic onset phase picking for portable seismic array observation

Automatic phase picking is a critical procedure for seismic data processing, especially for a huge amount of seismic data recorded by a large-scale portable seismic array. In this study is presented a new method used for automatic accurate onset phase picking based on the proporty of dense seismic array observations. In our method, the Akaike＇s information criterion （AIC） for the single channel observation and the least-squares cross-correlation for the multi-channel observation are combined together. The tests by the seismic array observation data after triggering with the short-term average/long-term average （STA/LTA） technique show that the phase picking error is less than 0.3 s for local events by using the single channel AIC algorithm. In terms of multi-channel least-squares cross-correlation technique, the clear teleseismic P onset can be detected reliably. Even for the teleseismic records with high noise level, our algorithm is also able to effectually avoid manual misdetections.

Measuring Acoustic Wave Transit Time in Furnace Based on Active Acoustic Source Signal

Accurate measurement of transit time for acoustic wave between two sensors installed on two sides of a furnace is a key to implementing the temperature field measurement technique based on acoustical method. A new method for measuring transit time of acoustic wave based on active acoustic source signal is proposed in this paper, which includes the followings： the time when the acoustic source signal arrives at the two sensors is measured first; then, the difference of two arriving time arguments is computed, thereby we get the transit time of the acoustic wave between two sensors installed on the two sides of the furnace. Avoiding the restriction on acoustic source signal and background noise, the new method can get the transit time of acoustic wave with higher precision and stronger ability of resisting noise interference.

Dissimilarity Measures for Time Series and Trend Analysis: Application to COVID-19 Cases Series

In this paper we propose some dissimilarity measure functions for trends of nonstationary time series.If time series are stationary,the cross correlation function can be applied as a similarity measure.However,the validity of the cross correlation function is lost for nonstationary time series.Moreover,the cross correlation function cannot be calculated if one of trends is constant.The proposed functions can be applied even if trends are constant and their values are determined through the minimization.The clustering is considered as an application of the dissimilarity measure.Furthermore the problem of the common trend within multiple time series is considered and the estimation algorithm is proposed.Usability of the proposed method is demonstrated by applying to series of COVID-19 cases in Japan.

Stability of PAC(Psy-2A-Crt I) gene and agronomic traits in the F_(2:3) of IR36/PAC transgenic plants

This study was carried out to evaluate the expression of yellow endosperm color in the progeny of Psy-2A-Crt I（β-carotene gene, PAC） transgenic plants crossed with IR36. The selected 25 lines of F2 progeny exhibited stable expression of yellow endosperm color and high agronomic characteristics. IR36 and PAC transgenic plant of the grain length, width and ratio showed the same tendency of normal distribution. For progeny selection, colorimeters were as employed to distinguish differing visible colors. Correlation analysis was conducted to investigate the relationship between b＊ value and the expression of specific genes. b＊ value was associated with the relative expression of the PAC-Rev and MAR product by real-time PCR and t-test revealed significant difference. Based on this study, correlation between colorimetric values and real-time PCR was effective to detect gene expression. Yellow endosperm progenies represent a new genetic pool that might be useful to increase the genetic diversity of yellow endosperm rice.

Correlations between Shortening Rate,Uplift Rate,and Inversion Rate in Central Inversion Zone of Xihu Depression,East China Sea Basin

Late Miocene shortening rate, uplift rate, and inversion rate in the central inversion zone of the Xihu （西湖） depression, East China Sea basin, were independently determined from a large number of 2D reflection seismic data and methods. Shortening rate was estimated from the 2DMOVE balanced cross-section technology, uplift rate was calculated after absolute erosions were determined from seismic data during the uplifting time, and inversion rate was measured using the improved calculation method by Song （1997）. The cross correlations among shortening rate, uplift rate, and inversion rate show a good positive relationship, with some differences existing in local areas. This article analyzes the cross correlation between these structural rates and discusses the dynamics of mechanisms for basin inversion and their influence on hydrocarbon accumulation.

THE FLOW PATTERNS OF BUBBLE PLUME IN AN MBBR

The flow patterns of the gas-liquid two-phase flow in a Moving-Bed Biofilm Reactor （MBBR） have a critical effect upon the mass transfer by the convection. Bubble plumes promote unsteadily fluctuating two-phase flows during the aeration. This article studies the unsteady structure of bubble plumes through experiments. The time-serial bubble plume images in various cases of the tank are analyzed. The Recursive Cross Correlation-Particle Image Velocimetry （RCC-PIV） is used to calculate the velocities in those cases, and then the time-serial vortex, the total turbulence intensity, the time-serial streamline are obtained. It is shown that the aspect ratio and the void fraction are the dominant factors influencing the unsteady structure of bubble plumes. When the aspect ratio is unity and the void fraction is high, the bubble plumes see a symmetrical vortex structure with a long residence time, which is beneficial for optimizing the aeration system and enhancing the applied range of bubble plumes.

Nondestructive testing method based on lamb waves for localization and extent of damage

Based on Lamb wave analysis of propagation in plate-like structures, a damage detection method is proposed that not only locates the position of the damage accurately but also estimates its size. Similar damage detection methods focus only on localization giving no quantitative estimation of extent. To improve detection, we propose two predictive circle methods for size estimation. Numerical simulations and experiments were performed for an aluminum plate with a hole. Two PZT configurations of different sizes were designed to excite and detect Lamb waves. From cross-correlation analysis, the damage location and extent can be determined. Results show that the proposed method enables a better quantitative resolution in detection, the size of the inspection area influences the accuracy of damage identification, and the closer is the inspected area to the damage, the more accurate are the results. The method proposed can be developed into a multiple-step detection method for multi-scale analysis with prospective accuracy.

Binocular Vision Object Positioning Method for Robots Based on Coarse-fine Stereo Matching

In order to improve the low positioning accuracy and execution efficiency of the robot binocular vision,a binocular vision positioning method based on coarse-fine stereo matching is proposed to achieve object positioning.The random fern is used in the coarse matching to identify objects in the left and right images,and the pixel coordinates of the object center points in the two images are calculated to complete the center matching.In the fine matching,the right center point is viewed as an estimated value to set the search range of the right image,in which the region matching is implemented to find the best matched point of the left center point.Then,the similar triangle principle of the binocular vision model is used to calculate the 3D coordinates of the center point,achieving fast and accurate object positioning.Finally,the proposed method is applied to the object scene images and the robotic arm grasping platform.The experimental results show that the average absolute positioning error and average relative positioning error of the proposed method are 8.22 mm and 1.96%respectively when the object's depth distance is within 600 mm,the time consumption is less than 1.029s.The method can meet the needs of the robot grasping system,and has better accuracy and robustness.

Identifying key bird species and geographical hotspots of avian influenza A(H7N9)virus in China

Background:In China since the first human infection of avian influenza A(H7N9)virus was identified in 2013,it has caused serious public health concerns due to its wide spread and high mortality rate.Evidence shows that bird migration plays an essential role in global spread of avian influenza viruses.Accordingly,in this paper,we aim to identify key bird species and geographical hotspots that are relevant to the transmission of avian influenza A(H7N9)virus in China.Methods:We first conducted phylogenetic analysis on 626 viral sequences of avian influenza A(H7N9)virus isolated in chicken,which were collected from the Global Initiative on Sharing All Influenza Data(GISAID),to reveal geographical spread and molecular evolution of the virus in China.Then,we adopted the cross correlation function(CCF)to explore the relationship between the identified influenza A(H7N9)cases and the spatiotemporal distribution of migratory birds.Here,the spatiotemporal distribution of bird species was generated based on bird observation data collected from China Bird Reports,which consists of 157272 observation records about 1145 bird species.Finally,we employed a kernel density estimator to identify geographical hotspots of bird habitat/stopover that are relevant to the influenza A(H7N9)infections.Results:Phylogenetic analysis reveals the evolutionary and geographical patterns of influenza A(H7N9)infections,where cases in the same or nearby municipality/provinces are clustered together with small evolutionary differences.Moreover,three epidemic waves in chicken along the East Asian-Australasian flyway in China are distinguished from the phylogenetic tree.The CCF analysis identifies possible migratory bird species that are relevant to the influenza A(H7N9)infections in Shanghai,Jiangsu,Zhejiang,Fujian,Jiangxi,and Guangdong in China,where the six municipality/provinces account for 91.2%of the total number of isolated H7N9 cases in chicken in GISAID.Based on the spatial distribution of identified bird species,geographical hotspots are further estimated and illustrated within these typical municipality/provinces.Conclusions:In this paper,we have identified key bird species and geographical hotspots that are relevant to the spread of influenza A(H7N9)virus.The results and findings could provide sentinel signal and evidence for active surveillance,as well as strategic control of influenza A(H7N9)transmission in China.

Experimental Analysis of Pressure Fluctuations behind a Bottom Aerator

Experimental observations show that the random process of two phase flow behind an aerator is an ergodic process and its amplitude distribution is similar to a normal distribution. The maximum pressure fluctuation is at the re attachment point where the jet trajectory flow over the aerator re attaches to bottom of the channel, and its amplitude is 2 3 times larger than when there is no aerator. There is a dominant frequency of 1 24 Hz in the model, but the coherence in the frequency domain is not obvious for other frequencies beside the dominant frequency. There is a large vortex at the re attachment point behind the aerator but correlation among the measurement points is not obvious in the time domain.