The geodetic detrending(GD)methodology was introduced in the past decade and has opened the door to the global monitoring of ionospheric scintillation using global navigation satellite system(GNSS)receivers.The perfor...The geodetic detrending(GD)methodology was introduced in the past decade and has opened the door to the global monitoring of ionospheric scintillation using global navigation satellite system(GNSS)receivers.The performance of GD has been demonstrated in geodetic receivers.However,extending scintillation monitoring to low-cost commercial receivers remains a challenge.Low-cost devices could serve as valuable complements to specialised and much more expensive scintillation monitoring receivers.In this paper,first,a feasibility study was conducted using the GD technique,demonstrating that the scintillation indices derived from the observations of two lowcost receivers(Septentrio Mosaic X5 and UBLOX ZED-F9P)have a resolution similar to that achieved by geodetic receiver models,whose price is one order of magnitude higher.Second,measurements of GNSS signals at different frequencies from the Galileo and global positioning system(GPS)satellites were analysed in a specific experiment over six days of null scintillation.Next,the noise level in the scintillation parameters derived from the experiment was evaluated,which shows that for low-cost receivers,the minimum scintillation detection threshold increases only negligibly compared to geodetic-grade receivers.Moreover,the geometry-free(GF)combination of L1 with a second signal of different frequency was investigated as an alternative to detrending GNSS signals.Finally,for determining the ionospheric fluctuations produced by scintillation,the limitations of using the GF combination versus the uncombined measurements were highlighted.It is concluded that the minimum resolution of scintillation indices derived from low-cost receiver measurements makes it possible to distinguish values associated with periods of scintillation activity from those produced by residual noise from mismodeling.For both geodetic and low-cost receivers,the scintillation detection threshold obtained with uncombined carrier-phase measurements is smaller than that achieved with the classic GF combination.展开更多
The China Seismo-Electromagnetic Satellite(CSES) was successfully launched in February 2018. The high precision magnetometer(HPM) on board the CSES has captured high-quality magnetic data that have been used to derive...The China Seismo-Electromagnetic Satellite(CSES) was successfully launched in February 2018. The high precision magnetometer(HPM) on board the CSES has captured high-quality magnetic data that have been used to derive a global lithospheric magnetic field model. While preparing the datasets for this lithospheric magnetic field model, researchers found that they still contained prominent residual trends within the magnetic anomaly even once signals from other sources had been eliminated. However, no processing was undertaken to deal with the residual trends during modeling to avoid subjective processing and represent the realistic nature of the data. In this work, we analyze the influence of these residual trends on the lithospheric magnetic field modeling.Polynomials of orders 0–3 were used to fit the trend of each track and remove it for detrending. We then derived four models through detrending-based processing, and compared their power spectra and grid maps with those of the CSES original model and CHAOS-7model. The misfit between the model and the dataset decreased after detrending the data, and the convergence of the inverted spherical harmonic coefficients improved. However, detrending reduced the signal strength and the power spectrum, while detrending based on high-order polynomials introduced prominent distortions in details of the magnetic anomaly. Based on this analysis, we recommend along-track detrending by using a zero-order polynomial(removing a constant value) on the CSES magnetic anomaly data to drag its mean value to zero. This would lead to only a slight reduction in the signal strength while significantly improving the stability of the inverted coefficients and details of the anomaly.展开更多
Slow trends in the RR interval(RRI) series should be removed in the preprocessing step to get a reliable result of heart rate variability(HRV) analysis. Re-sampling is required to convert the unevenly sampled RRI seri...Slow trends in the RR interval(RRI) series should be removed in the preprocessing step to get a reliable result of heart rate variability(HRV) analysis. Re-sampling is required to convert the unevenly sampled RRI series into evenly sampled time series when using the widely accepted smoothness priors approach(SPA). Noise is introduced in this process and the information quality is thus compromised. Empirical mode decomposition(EMD) and its variants, were introduced to directly process the unevenly sampled RRI series. Besides, a RR interval model was proposed to fascinate the introduction of standard metrics for the evaluation of the detrending performance. Based on standard metrics including signal-to-noise-ratio in d B(ISNR), mean square error(EMS), and percent root square difference(DPRS), the effectiveness of detrending methods in RR interval analysis were determined. Results demonstrate that complementary ensemble EMD(CEEMD, a variant of EMD) based method has a higher ISNR, a lower EMS and a lower DPRS as well as a better RRI series detrending performance compared with the SPA method, which would in turn lead to a more accurate HRV analysis.展开更多
As an important component of secondary aerosols,sulfate plays a crucial role in regulating atmospheric radiative balance and influencing the secondary formation of ozone(O_(3)).In real atmosphere,atmospheric oxidants ...As an important component of secondary aerosols,sulfate plays a crucial role in regulating atmospheric radiative balance and influencing the secondary formation of ozone(O_(3)).In real atmosphere,atmospheric oxidants NO_(2)and O_(3)can promote the oxidation of SO_(2)to form sulfate(SO_(4)^(2−))through multiphase chemistry that occur at different time scales.Due to the combined impact of meteorology,pollution sources,atmospheric chemistry,etc.,time-scale dependence of SO_(2)-SO_(4)^(2−)conversion makes the impact of NO_(2)/O_(3)on it more complex.In this study,based on long-term time series(2013-2020)of air pollution variables from seven stations in Hong Kong,the Multifractal Detrended Cross-Correlation Analysis(MFDCCA)method has been employed to quantify the cross-correlations between SO_(2)and SO_(4)^(2−)in real atmosphere at different time scales,for examining the time-scale dependence of SO_(2)-SO_(4)^(2−)conversion efficiency.Furthermore,the Pearson correlation analysis has been used to study the influence of NO_(2)/O_(3)on SO_(2)-SO_(4)^(2−)conversion,and the regional and seasonal differences have been analyzed by considering factors such as meteorology,pollution sources,and regional transport.Changes in the main components of secondary aerosols are closely linked with the co-control of regional PM_(2.5)and O_(3).Therefore,the exploration of the impact of co-existing NO_(2)/O_(3)gases on the secondary formation of sulfates in real atmosphere is significant.展开更多
The complex dense-phase pneumatic conveying of pulverized coal process was studied using an electrical capacitance tomography(ECT) signal that represented the motion characteristics of gas-solid two-phase flow. The fl...The complex dense-phase pneumatic conveying of pulverized coal process was studied using an electrical capacitance tomography(ECT) signal that represented the motion characteristics of gas-solid two-phase flow. The fluctuation characteristics of conveying process signals are inseparable from the flow pattern. The denoised ECT signal and noise signal were obtained by db2 wavelet analysis. It was found that all noise signals were white Gaussian noise. Based on the assumption of the equal probability distribution of pulverized coal concentration, this paper proved that the time series distribution of pulverized coal concentration in the pipeline should obey the normal distribution. Furthermore, through the analysis of the distribution characteristics of the power spectral density function of denoised ECT signals of four flow patterns, they were α-dimensional fractal Brownian motion(fBm) signals, and the parameter α was estimated by the detrended fluctuation analysis. Based on the fBm characteristics of denoised ECT signals and white Gaussian noise, this paper proposed a method for calculating the pulverized coal concentration in the dense-phase pneumatic conveying. In addition to the method of concentration estimation with the significance of engineering guidance, this research can help people to further understand essential characteristics of ECT signals in the dense-phase pneumatic conveying.展开更多
Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspondence analyses （DCCAs） and a two-way indicator species analysis （TWINSPAN）. The distributi...Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspondence analyses （DCCAs） and a two-way indicator species analysis （TWINSPAN）. The distribution pattern and influential factors of the plant communities were also analyzed by testing elevation, slope, soil characteristics, longitude and latitude of 134 vegetation samples collected by representative plot sampling methods. Results showed that all the 134 vegetation samples could be divided into seven vegetation groups, separately dominated by Robinia pseucdoacacia, Imperata cylindrical, Miscanthus saccharifleus, Suaeda salsa, Aeluropus sinensis, Phragmites australis and Tamarix chinensis. The vegetation distribution pattern was mainly related to elevation, ground water depth and soil characteristics such as salinity and soluble potassium. Among the factors affecting distribution pattern of the plant communities, the species matrix explained by non-spatial environmental variation accounts for 45.2% of total variation. Spatial variation and spatial-structured environmental variation explain 11.8%, and 2.2%, respectively. Remained 40.8% of undetermined variation is attributed to biological and stochastic factors.展开更多
The relationships of 42 species of ground moss with six environmental factors in 41 sites on Changbai Mountain Biosphere Reserve were analyzed. Four site groups and four groups of ground moss ecological species were i...The relationships of 42 species of ground moss with six environmental factors in 41 sites on Changbai Mountain Biosphere Reserve were analyzed. Four site groups and four groups of ground moss ecological species were identified using the method of Two-way Indicator Species Analysis (TWINSPAN). The results of Detrended Canonical. Correspondence Analysis (DCCA) showed that altitude, soil sand content, soil acidity, forest canopy coverage and soil water content are the five major environmental factors influencing the distributional patterns of the moss species. The four groups of ecological species, which correspond well with the four site groups, are projected on the species-environment biplot of DCCA. Group 1 dominated in the bogs of Larix olgensis forest, group 2 in the alpine tundra, group 3 in the dense conifer forest, and group 4 mainly in the Betula ermanii community and the Betula ermanii-Larix olgensis forest in sub-alpine respectively.展开更多
Long tree-ring chronologies can be developed by overlapping data from living trees with data from fossil trees through cross-dating.However,low-frequency climate signals are lost when standardizing tree-ring series du...Long tree-ring chronologies can be developed by overlapping data from living trees with data from fossil trees through cross-dating.However,low-frequency climate signals are lost when standardizing tree-ring series due to the"segment length curse".To alleviate the segment length curse and thus improve the standardization method for developing long tree-ring chronologies,here we first calculated a mean value for all the tree ring series by overlapping all of the tree ring series.The growth trend of the mean tree ring width(i.e.,cumulated average growth trend of all the series)was determined using ensemble empirical mode decomposition.Then the chronology was developed by dividing the mean value by the growth trend of the mean value.Our improved method alleviated the problem of trend distortion.Long-term signals were better preserved using the improved method than in previous detrending methods.The chronologies developed using the improved method were better correlated with climate than those developed using conservative methods.The improved standardization method alleviates trend distortion and retains more of the low-frequency climate signals.展开更多
Seismic attributes have been widely used in oil and gas exploration and development. However, owing to the complexity of seismic wave propagation in subsurface media, the limitations of the seismic data acquisition sy...Seismic attributes have been widely used in oil and gas exploration and development. However, owing to the complexity of seismic wave propagation in subsurface media, the limitations of the seismic data acquisition system, and noise interference, seismic attributes for seismic data interpretation have uncertainties. Especially, the antinoise ability of seismic attributes directly affects the reliability of seismic interpretations. Gray system theory is used in time series to minimize data randomness and increase data regularity. Detrended fluctuation analysis （DFA） can effectively reduce extrinsic data tendencies. In this study, by combining gray system theory and DFA, we propose a new method called gray detrended fluctuation analysis （GDFA） for calculating the fractal scaling exponent. We consider nonlinear time series generated by the Weierstrass function and add random noise to actual seismic data. Moreover, we discuss the antinoise ability of the fractal scaling exponent based on GDFA. The results suggest that the fractal scaling exponent calculated using the proposed method has good antinoise ability. We apply the proposed method to 3D poststack migration seismic data from southern China and compare fractal scaling exponents calculated using DFA and GDFA. The results suggest that the use of the GDFA-calculated fractal scaling exponent as a seismic attribute can match the known distribution of sedimentary facies.展开更多
Climate affects Picea crassifolia growth and climate change will lead to changes in the climate–growth relationship(i.e., the "divergence" phenomenon). However, standardization methods can also change the u...Climate affects Picea crassifolia growth and climate change will lead to changes in the climate–growth relationship(i.e., the "divergence" phenomenon). However, standardization methods can also change the understanding of such a relationship. We tested the stability of this relationship by considering several variables: 1) two periods(1952–1980 and 1981–2009), 2) three elevations(2700, 3000, and 3300 m), and 3) chronologies detrended using cubic splines with two different flexibilities. With increasing elevation, the climatic factor limiting the radial growth of Picea crassifolia shifted from precipitation to temperature. At the elevation of 2700 m, the relationship between radial growth and mean temperature of the previous December changed so that the more flexible spline had a greater precipitation signal. At the elevation of 3000 m, positive correlation of radial growth with mean temperature and precipitation in September of the previous year became more significant. At the elevation of 3300 m, positive correlation between radial growth and precipitation of the currentsummer and the previous spring and autumn was no longer significant, whereas the positive correlation between radial growth and temperature of the current spring and summer strengthened. The detrending with the most flexible spline enhanced the precipitation signal at 2700 m, while that with the least flexible spline enhanced the temperature signal at 3300 m. All results indicated that the divergence phenomenon was affected by the climatic signals in the chronologies and that it was most dependent on the detrending method. This suggests it is necessary to select a suitable spline bootstrap for studies of growth divergence phenomena.展开更多
To detect the occurrence of ionospheric scintillation in the equatorial region,a coherent/non-coherent integration method is adopted on the accumulation of intermediate frequency(IF)signal and local code,in the proces...To detect the occurrence of ionospheric scintillation in the equatorial region,a coherent/non-coherent integration method is adopted on the accumulation of intermediate frequency(IF)signal and local code,in the process of signal acquisition based on software receiver.The processes of polynomial fitting and sixth-order Butterworth filtering are introduced to detrend the tracking results.Combining with ionospheric scintillation detection algorithm and preset thresholds,signal acquisition and tracking,scintillation detection,positioning solution are realized under the influence of strong ionospheric scintillation.Under the condition that the preset threshold of amplitude and carrier phase scintillation indices are set to 0.5 and 0.15,and the percentage of scin-tillation occurrence is 50%,respectively,PRN 12 and 31 affected by strong amplitude scintillation are detected effectively.Results show that the positioning errors in the horizontal direction are below 5m approximately.The software receiver holds performances of accurate acquisition,tracking and positioning on the strong ionospheric scintillation conditions,which can provide important basis and helpful guidance for relevant research on ionospheric scintillation,space weather and receiver design with high performance.展开更多
Quantitative precipitation estimation （QPE） plays an important role in meteorological and hydrological applications.Ground-based telemetered rain gauges are widely used to collect precipitation measurements.Spatial ...Quantitative precipitation estimation （QPE） plays an important role in meteorological and hydrological applications.Ground-based telemetered rain gauges are widely used to collect precipitation measurements.Spatial interpolation methods are commonly employed to estimate precipitation fields covering non-observed locations.Kriging is a simple and popular geostatistical interpolation method,but it has two known problems：uncertainty underestimation and violation of assumptions.This paper tackles these problems and seeks an optimal spatial interpolation for QPE in order to enhance spatial interpolation through appropriately assessing prediction uncertainty and fulfilling the required assumptions.To this end,several methods are tested：transformation,detrending,multiple spatial correlation functions,and Bayesian kriging.In particular,we focus on a short-term and time-specific rather than a long-term and event-specific analysis.This paper analyzes a stratiform rain event with an embedded convection linked to the passing monsoon front on the 23 August 2012.Data from a total of 100 automatic weather stations are used,and the rainfall intensities are calculated from the difference of 15 minute accumulated rainfall observed every 1 minute.The one-hour average rainfall intensity is then calculated to minimize the measurement random error.Cross-validation is carried out for evaluating the interpolation methods at regional and local levels.As a result,transformation is found to play an important role in improving spatial interpolation and uncertainty assessment,and Bayesian methods generally outperform traditional ones in terms of the criteria.展开更多
When exploring the temporal and spatial change law of ocean environment, the most common method used is using smaller-scale observed data to derive the change law for a larger-scale system. For instance, using 30-year...When exploring the temporal and spatial change law of ocean environment, the most common method used is using smaller-scale observed data to derive the change law for a larger-scale system. For instance, using 30-year observation data to derive 100-year return period design wave height. Therefore, the study of inherent self-similarity in ocean hydrological elements becomes increasingly important to the study of multi-year return period design wave height derivation. In this paper, we introduced multifractal to analyze the statistical characteristics of wave height series data observed from oceanic hydrological station. An improvement is made to address the existing problems of the multifractal detrended fluctuation analysis (MF-DFA) method, where trend function showed a discontinuity between intervals. The improved MFDFA method is based on signal mode decomposition, replacing piecewise polynomial fitting used in the original method. We applied the proposed method to the wave height data collected at Chaolian Island, Shandong, China, from 1963 to 1989 and was able to conclude the wave height sequence presented weak multi-fractality. This result provided strong support to the past research on the derivation of multi-year return period design wave height with observed data. Moreover, the new method proposed in this paper also provides a new perspective to explore the intrinsic characteristic of data.展开更多
In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads o...In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject＇s brain function is healthy or not.展开更多
Massive seamounts have been surveyed and documented in the last decades.However,the morphologies of seamounts are usually described in qualitative manners,yet few quantitative detections have been carried out.Here,bas...Massive seamounts have been surveyed and documented in the last decades.However,the morphologies of seamounts are usually described in qualitative manners,yet few quantitative detections have been carried out.Here,based on the high-re solution multi-beam bathymetric data,we report a recentlysurveyed guy ot on the Caroline Ridge in the West Pacific,and the large-scale volcanic structures and smallscale erosive-depositional landforms in the guyot area have been identified.The multifractal features of the guyot are characterized for the first time by applying multifractal detrended fluctuation analysis on the surveyed bathymetric data.The results indicate that the multifractal spectrum parameters of the seafloor have strong spatial dependency on the fluctuations of local landforms.Both small-and large-scale components contribute to the degree of asymmetry of the multifractal spectrum(B),while the fluctuations of B are mostly attributed to the changes in small-scale roughness.The maximum singularity strength(α0)correlates well with the roughness of large-scale landforms and likely reflects the large-scale topographic irregularity.Comparing to traditional roughness parameters or monofractal exponents,multifractal spectra are able to depict not only the multiscale characteristics of submarine landforms,but also the spatial variations of scaling behaviors.Although more comparative works are required for various seamounts,we hope this study,as a case of quantifying geomorphological characters and multiscale behaviors of seamounts,can encourage further studies on seamounts concerning geomorphological processes,ocean bottom circulations,and seamount ecosystems.展开更多
We analyze the correlation properties of the Erd6s-Rdnyi random graph （RG） and the Barabdsi-Albert scale-free network （SF） under the attack and repair strategy with detrended fluctuation analysis （DFA）. The maxi...We analyze the correlation properties of the Erd6s-Rdnyi random graph （RG） and the Barabdsi-Albert scale-free network （SF） under the attack and repair strategy with detrended fluctuation analysis （DFA）. The maximum degree kmax, representing the local property of the system, shows similar scaling behaviors for random graphs and scale-free networks. The fluctuations are quite random at short time scales but display strong anticorrelation at longer time scales under the same system size N and different repair probability pre. The average degree 〈k〉, revealing the statistical property of the system, exhibits completely different scaling behaviors for random graphs and scale-free networks. Random graphs display long-range power-law correlations. Scale-free networks are uncorrelated at short time scales; while anticorrelated at longer time scales and the anticorrelation becoming stronger with the increase of pre.展开更多
Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspon-dence analyses(DCCAs) and a two-way indicator species analysis(TWINSPAN).The distribution pat...Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspon-dence analyses(DCCAs) and a two-way indicator species analysis(TWINSPAN).The distribution pattern and influential factors of the plant communities were also analyzed by testing elevation, slope, soil characteristics, longitude and latitude of 134 vegetation samples collected by representative plot sampling methods.Results showed that all the 134 vegetation samples could be divided into seven vegetation groups, separately dominated by Robinia pseucdoacacia, Imperata cylindrical, Miscanthus saccharifleus, Suaeda salsa, Aeluropus sinensis, Phragmites australis and Tamarix chinensis.The vegetation distribution pattern was mainly related to elevation, ground water depth and soil characteristics such as salinity and soluble potassium.Among the factors affecting distribution pattern of the plant communities, the species matrix explained by non-spatial environmental variation accounts for 45.2% of total variation.Spatial variation and spatial-structured environmental variation explain 11.8%, and 2.2%, respectively.Remained 40.8% of undetermined variation is attributed to biological and stochastic factors.展开更多
We study the dynamical properties of heart rate variability （HRV） in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulate...We study the dynamical properties of heart rate variability （HRV） in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulated by the interaction of two branches of the autonomic nervous system： the parasympathetic and sympathetic nervous systems. By investigating the multifractal properties of light, deep, rapid-eye-movement （REM） sleep and wake stages, we firstly find an increasing multifractal behaviour during REM sleep which may be caused by augmented sympathetic activities relative to non-REM sleep. In addition, the investigation of long-range correlations of HRV in sleep with second order detrended fluctuation analysis presents irregular phenomena. These findings may be helpful to understand the underlying regulating mechanism of heart rate by autonomic nervous system during wake-sleep transitions.展开更多
Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time se...Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.展开更多
A method for gearbox fault diagnosis consists of feature extraction andfault identification. Many methods for feature extraction have beendevised for exposing nature of vibration data of a defective gearbox. Inadditio...A method for gearbox fault diagnosis consists of feature extraction andfault identification. Many methods for feature extraction have beendevised for exposing nature of vibration data of a defective gearbox. Inaddition, features extracted from gearbox vibration data are identifiedby various classifiers. However, existing literatures leave much to bedesired in assessing performance of different combinatorial methods forgearbox fault diagnosis. To this end, this paper evaluated performance ofseveral typical combinatorial methods for gearbox fault diagnosis byassociating each of multifractal detrended fluctuation analysis (MFDFA),empirical mode decomposition (EMD) and wavelet transform (WT) witheach of neural network (NN), Mahalanobis distance decision rules(MDDR) and support vector machine (SVM). Following this,performance of different combinatorial methods was compared using agroup of gearbox vibration data containing slightly different faultpatterns. The results indicate that MFDFA performs better in featureextraction of gearbox vibration data and SVM does the same in faultidentification. Naturally, the method associating MFDFA with SVMshows huge potential for fault diagnosis of gearboxes. As a result, thispaper can provide some useful information on construction of a methodfor gearbox fault diagnosis.展开更多
基金funding from European Union(MCIN/AEI/10.13039/501100011033/FEDER)(Nos.PID2022-138485OB-I00 and CNS2022-135383)European Space Agency(RT-WMIS)(No.4000137762/22/NL/GLC/ov)funding support from the China Scholarship Council(No.202006020025)。
文摘The geodetic detrending(GD)methodology was introduced in the past decade and has opened the door to the global monitoring of ionospheric scintillation using global navigation satellite system(GNSS)receivers.The performance of GD has been demonstrated in geodetic receivers.However,extending scintillation monitoring to low-cost commercial receivers remains a challenge.Low-cost devices could serve as valuable complements to specialised and much more expensive scintillation monitoring receivers.In this paper,first,a feasibility study was conducted using the GD technique,demonstrating that the scintillation indices derived from the observations of two lowcost receivers(Septentrio Mosaic X5 and UBLOX ZED-F9P)have a resolution similar to that achieved by geodetic receiver models,whose price is one order of magnitude higher.Second,measurements of GNSS signals at different frequencies from the Galileo and global positioning system(GPS)satellites were analysed in a specific experiment over six days of null scintillation.Next,the noise level in the scintillation parameters derived from the experiment was evaluated,which shows that for low-cost receivers,the minimum scintillation detection threshold increases only negligibly compared to geodetic-grade receivers.Moreover,the geometry-free(GF)combination of L1 with a second signal of different frequency was investigated as an alternative to detrending GNSS signals.Finally,for determining the ionospheric fluctuations produced by scintillation,the limitations of using the GF combination versus the uncombined measurements were highlighted.It is concluded that the minimum resolution of scintillation indices derived from low-cost receiver measurements makes it possible to distinguish values associated with periods of scintillation activity from those produced by residual noise from mismodeling.For both geodetic and low-cost receivers,the scintillation detection threshold obtained with uncombined carrier-phase measurements is smaller than that achieved with the classic GF combination.
基金a project funded by the China National Space Administration (CNSA) and the Ministry of Emergency Management of Chinasupported by the Civil Aerospace Technology Pilot Research Project (D040203)+1 种基金the National Natural Science Foundation of China (42004051, 42274214)the APSCO Earthquake Research Project Phase Ⅱ and Dragon 6 cooperation 2025-2029 (95437)。
文摘The China Seismo-Electromagnetic Satellite(CSES) was successfully launched in February 2018. The high precision magnetometer(HPM) on board the CSES has captured high-quality magnetic data that have been used to derive a global lithospheric magnetic field model. While preparing the datasets for this lithospheric magnetic field model, researchers found that they still contained prominent residual trends within the magnetic anomaly even once signals from other sources had been eliminated. However, no processing was undertaken to deal with the residual trends during modeling to avoid subjective processing and represent the realistic nature of the data. In this work, we analyze the influence of these residual trends on the lithospheric magnetic field modeling.Polynomials of orders 0–3 were used to fit the trend of each track and remove it for detrending. We then derived four models through detrending-based processing, and compared their power spectra and grid maps with those of the CSES original model and CHAOS-7model. The misfit between the model and the dataset decreased after detrending the data, and the convergence of the inverted spherical harmonic coefficients improved. However, detrending reduced the signal strength and the power spectrum, while detrending based on high-order polynomials introduced prominent distortions in details of the magnetic anomaly. Based on this analysis, we recommend along-track detrending by using a zero-order polynomial(removing a constant value) on the CSES magnetic anomaly data to drag its mean value to zero. This would lead to only a slight reduction in the signal strength while significantly improving the stability of the inverted coefficients and details of the anomaly.
基金Project(41227803)supported by the National Natural Science Foundation of ChinaProject(KF11011)supported by the State Key Laboratory of Automotive Safety and Energy(Tsinghua University),ChinaProject(DTNH22-08-C-00082)supported by the National Highway Traffic Safety Administration,USA
文摘Slow trends in the RR interval(RRI) series should be removed in the preprocessing step to get a reliable result of heart rate variability(HRV) analysis. Re-sampling is required to convert the unevenly sampled RRI series into evenly sampled time series when using the widely accepted smoothness priors approach(SPA). Noise is introduced in this process and the information quality is thus compromised. Empirical mode decomposition(EMD) and its variants, were introduced to directly process the unevenly sampled RRI series. Besides, a RR interval model was proposed to fascinate the introduction of standard metrics for the evaluation of the detrending performance. Based on standard metrics including signal-to-noise-ratio in d B(ISNR), mean square error(EMS), and percent root square difference(DPRS), the effectiveness of detrending methods in RR interval analysis were determined. Results demonstrate that complementary ensemble EMD(CEEMD, a variant of EMD) based method has a higher ISNR, a lower EMS and a lower DPRS as well as a better RRI series detrending performance compared with the SPA method, which would in turn lead to a more accurate HRV analysis.
基金supported by the National Natural Science Foundation of China(No.52160024)the Natural Science Foundation of Hunan Province,China(No.2022JJ30475)+2 种基金the Innovation Team Funds of China West Normal University(No.KCXTD2023-4)the Natural Science Foundation of Sichuan,China(No.24NSFSC0537)the Fundamental Research Funds of China West Normal University(Nos.22kE015 and 22kE016).
文摘As an important component of secondary aerosols,sulfate plays a crucial role in regulating atmospheric radiative balance and influencing the secondary formation of ozone(O_(3)).In real atmosphere,atmospheric oxidants NO_(2)and O_(3)can promote the oxidation of SO_(2)to form sulfate(SO_(4)^(2−))through multiphase chemistry that occur at different time scales.Due to the combined impact of meteorology,pollution sources,atmospheric chemistry,etc.,time-scale dependence of SO_(2)-SO_(4)^(2−)conversion makes the impact of NO_(2)/O_(3)on it more complex.In this study,based on long-term time series(2013-2020)of air pollution variables from seven stations in Hong Kong,the Multifractal Detrended Cross-Correlation Analysis(MFDCCA)method has been employed to quantify the cross-correlations between SO_(2)and SO_(4)^(2−)in real atmosphere at different time scales,for examining the time-scale dependence of SO_(2)-SO_(4)^(2−)conversion efficiency.Furthermore,the Pearson correlation analysis has been used to study the influence of NO_(2)/O_(3)on SO_(2)-SO_(4)^(2−)conversion,and the regional and seasonal differences have been analyzed by considering factors such as meteorology,pollution sources,and regional transport.Changes in the main components of secondary aerosols are closely linked with the co-control of regional PM_(2.5)and O_(3).Therefore,the exploration of the impact of co-existing NO_(2)/O_(3)gases on the secondary formation of sulfates in real atmosphere is significant.
基金funding from Shanghai Sailing Program (22YF1417600)Guangxi Science and Technology Major Program (AA23062019)
文摘The complex dense-phase pneumatic conveying of pulverized coal process was studied using an electrical capacitance tomography(ECT) signal that represented the motion characteristics of gas-solid two-phase flow. The fluctuation characteristics of conveying process signals are inseparable from the flow pattern. The denoised ECT signal and noise signal were obtained by db2 wavelet analysis. It was found that all noise signals were white Gaussian noise. Based on the assumption of the equal probability distribution of pulverized coal concentration, this paper proved that the time series distribution of pulverized coal concentration in the pipeline should obey the normal distribution. Furthermore, through the analysis of the distribution characteristics of the power spectral density function of denoised ECT signals of four flow patterns, they were α-dimensional fractal Brownian motion(fBm) signals, and the parameter α was estimated by the detrended fluctuation analysis. Based on the fBm characteristics of denoised ECT signals and white Gaussian noise, this paper proposed a method for calculating the pulverized coal concentration in the dense-phase pneumatic conveying. In addition to the method of concentration estimation with the significance of engineering guidance, this research can help people to further understand essential characteristics of ECT signals in the dense-phase pneumatic conveying.
基金Foundation project： This study was financially supported by the Na- tional Natural Science Foundation of China （No. 40771172） and the orientation project of the Chinese Academy of Sciences （No. kzcx2-yw-308）
文摘Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspondence analyses （DCCAs） and a two-way indicator species analysis （TWINSPAN）. The distribution pattern and influential factors of the plant communities were also analyzed by testing elevation, slope, soil characteristics, longitude and latitude of 134 vegetation samples collected by representative plot sampling methods. Results showed that all the 134 vegetation samples could be divided into seven vegetation groups, separately dominated by Robinia pseucdoacacia, Imperata cylindrical, Miscanthus saccharifleus, Suaeda salsa, Aeluropus sinensis, Phragmites australis and Tamarix chinensis. The vegetation distribution pattern was mainly related to elevation, ground water depth and soil characteristics such as salinity and soluble potassium. Among the factors affecting distribution pattern of the plant communities, the species matrix explained by non-spatial environmental variation accounts for 45.2% of total variation. Spatial variation and spatial-structured environmental variation explain 11.8%, and 2.2%, respectively. Remained 40.8% of undetermined variation is attributed to biological and stochastic factors.
文摘The relationships of 42 species of ground moss with six environmental factors in 41 sites on Changbai Mountain Biosphere Reserve were analyzed. Four site groups and four groups of ground moss ecological species were identified using the method of Two-way Indicator Species Analysis (TWINSPAN). The results of Detrended Canonical. Correspondence Analysis (DCCA) showed that altitude, soil sand content, soil acidity, forest canopy coverage and soil water content are the five major environmental factors influencing the distributional patterns of the moss species. The four groups of ecological species, which correspond well with the four site groups, are projected on the species-environment biplot of DCCA. Group 1 dominated in the bogs of Larix olgensis forest, group 2 in the alpine tundra, group 3 in the dense conifer forest, and group 4 mainly in the Betula ermanii community and the Betula ermanii-Larix olgensis forest in sub-alpine respectively.
文摘Long tree-ring chronologies can be developed by overlapping data from living trees with data from fossil trees through cross-dating.However,low-frequency climate signals are lost when standardizing tree-ring series due to the"segment length curse".To alleviate the segment length curse and thus improve the standardization method for developing long tree-ring chronologies,here we first calculated a mean value for all the tree ring series by overlapping all of the tree ring series.The growth trend of the mean tree ring width(i.e.,cumulated average growth trend of all the series)was determined using ensemble empirical mode decomposition.Then the chronology was developed by dividing the mean value by the growth trend of the mean value.Our improved method alleviated the problem of trend distortion.Long-term signals were better preserved using the improved method than in previous detrending methods.The chronologies developed using the improved method were better correlated with climate than those developed using conservative methods.The improved standardization method alleviates trend distortion and retains more of the low-frequency climate signals.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.2012QNA62)the Natural Science Foundation of Jiangsu Province(Grant No.BK20130201)+1 种基金the Chinese Postdoctoral Science Foundation(Grant No.2014M551703)the National Natural Science Foundation of China(Grant No.41374140)
文摘Seismic attributes have been widely used in oil and gas exploration and development. However, owing to the complexity of seismic wave propagation in subsurface media, the limitations of the seismic data acquisition system, and noise interference, seismic attributes for seismic data interpretation have uncertainties. Especially, the antinoise ability of seismic attributes directly affects the reliability of seismic interpretations. Gray system theory is used in time series to minimize data randomness and increase data regularity. Detrended fluctuation analysis （DFA） can effectively reduce extrinsic data tendencies. In this study, by combining gray system theory and DFA, we propose a new method called gray detrended fluctuation analysis （GDFA） for calculating the fractal scaling exponent. We consider nonlinear time series generated by the Weierstrass function and add random noise to actual seismic data. Moreover, we discuss the antinoise ability of the fractal scaling exponent based on GDFA. The results suggest that the fractal scaling exponent calculated using the proposed method has good antinoise ability. We apply the proposed method to 3D poststack migration seismic data from southern China and compare fractal scaling exponents calculated using DFA and GDFA. The results suggest that the use of the GDFA-calculated fractal scaling exponent as a seismic attribute can match the known distribution of sedimentary facies.
基金supported by the "the Fundamental Research Funds for the Central Nonprofit Research Institution of CAF",Forest degradation and restoration mechanisms of the alpine mountains from the western China (contract: CAFYBB2014ZD001)
文摘Climate affects Picea crassifolia growth and climate change will lead to changes in the climate–growth relationship(i.e., the "divergence" phenomenon). However, standardization methods can also change the understanding of such a relationship. We tested the stability of this relationship by considering several variables: 1) two periods(1952–1980 and 1981–2009), 2) three elevations(2700, 3000, and 3300 m), and 3) chronologies detrended using cubic splines with two different flexibilities. With increasing elevation, the climatic factor limiting the radial growth of Picea crassifolia shifted from precipitation to temperature. At the elevation of 2700 m, the relationship between radial growth and mean temperature of the previous December changed so that the more flexible spline had a greater precipitation signal. At the elevation of 3000 m, positive correlation of radial growth with mean temperature and precipitation in September of the previous year became more significant. At the elevation of 3300 m, positive correlation between radial growth and precipitation of the currentsummer and the previous spring and autumn was no longer significant, whereas the positive correlation between radial growth and temperature of the current spring and summer strengthened. The detrending with the most flexible spline enhanced the precipitation signal at 2700 m, while that with the least flexible spline enhanced the temperature signal at 3300 m. All results indicated that the divergence phenomenon was affected by the climatic signals in the chronologies and that it was most dependent on the detrending method. This suggests it is necessary to select a suitable spline bootstrap for studies of growth divergence phenomena.
文摘To detect the occurrence of ionospheric scintillation in the equatorial region,a coherent/non-coherent integration method is adopted on the accumulation of intermediate frequency(IF)signal and local code,in the process of signal acquisition based on software receiver.The processes of polynomial fitting and sixth-order Butterworth filtering are introduced to detrend the tracking results.Combining with ionospheric scintillation detection algorithm and preset thresholds,signal acquisition and tracking,scintillation detection,positioning solution are realized under the influence of strong ionospheric scintillation.Under the condition that the preset threshold of amplitude and carrier phase scintillation indices are set to 0.5 and 0.15,and the percentage of scin-tillation occurrence is 50%,respectively,PRN 12 and 31 affected by strong amplitude scintillation are detected effectively.Results show that the positioning errors in the horizontal direction are below 5m approximately.The software receiver holds performances of accurate acquisition,tracking and positioning on the strong ionospheric scintillation conditions,which can provide important basis and helpful guidance for relevant research on ionospheric scintillation,space weather and receiver design with high performance.
基金funded by the Korea Meteorological Administration Research and Development Program (Grant No. CATER 2013-2040)supported by the Brain Pool program of the Korean Federation of Science and Technology Societies (KOFST) (Grant No. 122S-1-3-0422)
文摘Quantitative precipitation estimation （QPE） plays an important role in meteorological and hydrological applications.Ground-based telemetered rain gauges are widely used to collect precipitation measurements.Spatial interpolation methods are commonly employed to estimate precipitation fields covering non-observed locations.Kriging is a simple and popular geostatistical interpolation method,but it has two known problems：uncertainty underestimation and violation of assumptions.This paper tackles these problems and seeks an optimal spatial interpolation for QPE in order to enhance spatial interpolation through appropriately assessing prediction uncertainty and fulfilling the required assumptions.To this end,several methods are tested：transformation,detrending,multiple spatial correlation functions,and Bayesian kriging.In particular,we focus on a short-term and time-specific rather than a long-term and event-specific analysis.This paper analyzes a stratiform rain event with an embedded convection linked to the passing monsoon front on the 23 August 2012.Data from a total of 100 automatic weather stations are used,and the rainfall intensities are calculated from the difference of 15 minute accumulated rainfall observed every 1 minute.The one-hour average rainfall intensity is then calculated to minimize the measurement random error.Cross-validation is carried out for evaluating the interpolation methods at regional and local levels.As a result,transformation is found to play an important role in improving spatial interpolation and uncertainty assessment,and Bayesian methods generally outperform traditional ones in terms of the criteria.
基金Supported by the NSFC-Shandong Joint Fund “Study on the DisasterCausing Mechanism and Disaster Prevention Countermeasures of MultiSource Storm Surges”(No.U1706226)the National Natural Science Foundation of China “Coastal Engineering and Risk Assessment Based on a Four-Layer Nested Multi-Objective Probability Model”(No.51379195)+1 种基金the Natural Science Foundation of Shandong Province “Three-Layer Nested Multi-Objective Probability Prediction and Risk Assessment in Coastal Engineering”(No.ZR2013EEM034)the Program of Promotion Plan for Postgraduates’ Educational Quality “Paying More Attention to the Study on the Cultivation Mode of Mathematical Modeling for Engineering Postgraduates”(No.861801232417)
文摘When exploring the temporal and spatial change law of ocean environment, the most common method used is using smaller-scale observed data to derive the change law for a larger-scale system. For instance, using 30-year observation data to derive 100-year return period design wave height. Therefore, the study of inherent self-similarity in ocean hydrological elements becomes increasingly important to the study of multi-year return period design wave height derivation. In this paper, we introduced multifractal to analyze the statistical characteristics of wave height series data observed from oceanic hydrological station. An improvement is made to address the existing problems of the multifractal detrended fluctuation analysis (MF-DFA) method, where trend function showed a discontinuity between intervals. The improved MFDFA method is based on signal mode decomposition, replacing piecewise polynomial fitting used in the original method. We applied the proposed method to the wave height data collected at Chaolian Island, Shandong, China, from 1963 to 1989 and was able to conclude the wave height sequence presented weak multi-fractality. This result provided strong support to the past research on the derivation of multi-year return period design wave height with observed data. Moreover, the new method proposed in this paper also provides a new perspective to explore the intrinsic characteristic of data.
基金supported by the Science Foundation of Jiangsu Province of China (Grant No.BK2011759)
文摘In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject＇s brain function is healthy or not.
基金the Senior User Project of R/V Kexue(No.KEXUE2018G11)the Science and Technology Basic Resources Investigation Program ofChina(No.2017FY100801)the Open Fund of the Key Laboratoryof Marine Geology and Environment,Chinese Academy of Sciences(No.MGE2018KG02)。
文摘Massive seamounts have been surveyed and documented in the last decades.However,the morphologies of seamounts are usually described in qualitative manners,yet few quantitative detections have been carried out.Here,based on the high-re solution multi-beam bathymetric data,we report a recentlysurveyed guy ot on the Caroline Ridge in the West Pacific,and the large-scale volcanic structures and smallscale erosive-depositional landforms in the guyot area have been identified.The multifractal features of the guyot are characterized for the first time by applying multifractal detrended fluctuation analysis on the surveyed bathymetric data.The results indicate that the multifractal spectrum parameters of the seafloor have strong spatial dependency on the fluctuations of local landforms.Both small-and large-scale components contribute to the degree of asymmetry of the multifractal spectrum(B),while the fluctuations of B are mostly attributed to the changes in small-scale roughness.The maximum singularity strength(α0)correlates well with the roughness of large-scale landforms and likely reflects the large-scale topographic irregularity.Comparing to traditional roughness parameters or monofractal exponents,multifractal spectra are able to depict not only the multiscale characteristics of submarine landforms,but also the spatial variations of scaling behaviors.Although more comparative works are required for various seamounts,we hope this study,as a case of quantifying geomorphological characters and multiscale behaviors of seamounts,can encourage further studies on seamounts concerning geomorphological processes,ocean bottom circulations,and seamount ecosystems.
基金The project supported by National Natural Science Foundation of China under Grant Nos. 70271067 and 70401020 and the Science Foundation of the Ministry of Education of China under Grant No. 03113
文摘We analyze the correlation properties of the Erd6s-Rdnyi random graph （RG） and the Barabdsi-Albert scale-free network （SF） under the attack and repair strategy with detrended fluctuation analysis （DFA）. The maximum degree kmax, representing the local property of the system, shows similar scaling behaviors for random graphs and scale-free networks. The fluctuations are quite random at short time scales but display strong anticorrelation at longer time scales under the same system size N and different repair probability pre. The average degree 〈k〉, revealing the statistical property of the system, exhibits completely different scaling behaviors for random graphs and scale-free networks. Random graphs display long-range power-law correlations. Scale-free networks are uncorrelated at short time scales; while anticorrelated at longer time scales and the anticorrelation becoming stronger with the increase of pre.
基金supported by the Na-tional Natural Science Foundation of China (No. 40771172)the orientation project of the Chinese Academy of Sciences (No. kzcx2-yw-308)
文摘Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspon-dence analyses(DCCAs) and a two-way indicator species analysis(TWINSPAN).The distribution pattern and influential factors of the plant communities were also analyzed by testing elevation, slope, soil characteristics, longitude and latitude of 134 vegetation samples collected by representative plot sampling methods.Results showed that all the 134 vegetation samples could be divided into seven vegetation groups, separately dominated by Robinia pseucdoacacia, Imperata cylindrical, Miscanthus saccharifleus, Suaeda salsa, Aeluropus sinensis, Phragmites australis and Tamarix chinensis.The vegetation distribution pattern was mainly related to elevation, ground water depth and soil characteristics such as salinity and soluble potassium.Among the factors affecting distribution pattern of the plant communities, the species matrix explained by non-spatial environmental variation accounts for 45.2% of total variation.Spatial variation and spatial-structured environmental variation explain 11.8%, and 2.2%, respectively.Remained 40.8% of undetermined variation is attributed to biological and stochastic factors.
基金Supported by the National Science Foundation of China under Grant Nos 60471057 and 70571075, and the Foundation for Graduate Student of USTC under Grant No KD2006046.
文摘We study the dynamical properties of heart rate variability （HRV） in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulated by the interaction of two branches of the autonomic nervous system： the parasympathetic and sympathetic nervous systems. By investigating the multifractal properties of light, deep, rapid-eye-movement （REM） sleep and wake stages, we firstly find an increasing multifractal behaviour during REM sleep which may be caused by augmented sympathetic activities relative to non-REM sleep. In addition, the investigation of long-range correlations of HRV in sleep with second order detrended fluctuation analysis presents irregular phenomena. These findings may be helpful to understand the underlying regulating mechanism of heart rate by autonomic nervous system during wake-sleep transitions.
基金Projects(61271321,61573253,61401303)supported by the National Natural Science Foundation of ChinaProject(14ZCZDSF00025)supported by Tianjin Key Technology Research and Development Program,China+1 种基金Project(13JCYBJC17500)supported by Tianjin Natural Science Foundation,ChinaProject(20120032110068)supported by Doctoral Fund of Ministry of Education of China
文摘Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.
基金supported by Shandong ProvincialNatural Science Foundation China (ZR2012EEL07).
文摘A method for gearbox fault diagnosis consists of feature extraction andfault identification. Many methods for feature extraction have beendevised for exposing nature of vibration data of a defective gearbox. Inaddition, features extracted from gearbox vibration data are identifiedby various classifiers. However, existing literatures leave much to bedesired in assessing performance of different combinatorial methods forgearbox fault diagnosis. To this end, this paper evaluated performance ofseveral typical combinatorial methods for gearbox fault diagnosis byassociating each of multifractal detrended fluctuation analysis (MFDFA),empirical mode decomposition (EMD) and wavelet transform (WT) witheach of neural network (NN), Mahalanobis distance decision rules(MDDR) and support vector machine (SVM). Following this,performance of different combinatorial methods was compared using agroup of gearbox vibration data containing slightly different faultpatterns. The results indicate that MFDFA performs better in featureextraction of gearbox vibration data and SVM does the same in faultidentification. Naturally, the method associating MFDFA with SVMshows huge potential for fault diagnosis of gearboxes. As a result, thispaper can provide some useful information on construction of a methodfor gearbox fault diagnosis.
