Spatial Spectral Analysis Research Articles

Method for Recognizing the Characteristic Elements of Protein Secondary Structure From the Llm of Its Amino Acid Sequence

The spatial structure of a protein determines its biochemical properties and, consequently, its function. The same applies to elements of secondary structure, which adopt shapes of helices, coiled coils, strands, sheets and other formations in three-dimensional space. Automatic detection of such formations based on their corresponding amino acid sequences in the protein will enable the cataloging of these sequence fragments, examining and systematizing their correspondence to spatial protein formations. This, in turn, should simplify the task of searching for complementary and functional similarities among different proteins. For this purpose, a method based on covariance, autocorrelation, and spatial-spectral analysis of embeddings of their amino acid sequences has been developed and tested.

Discovery of Radial Spectral Hardening in the Hot Bubble of Planetary Nebula BD+30°3639 with Median Energy Imaging

We apply an imaging analysis technique to study the spatial distribution of the X-ray spectral hardness across the hot bubble of planetary nebula BD+30°3639. Hot bubble emission is typically photon starved, thus limiting the methods for spatial–spectral analysis; however, this technique uses the statistics of photon energies across the nebula to identify spatial variations in the X-ray spectral hardness. Using the median energy value of the X-ray photons, we identified a rise in median energy values toward the projected edge of the nebula, which we refer to as radial spectral hardening. We explored the origin of this radial spectral hardening with an X-ray spectral analysis of distinct regions of high and low median energy values. Given the results of the X-ray spectral fits and the fact that the hot bubble is embedded within a young, dense, planetary nebula, we conclude that the radial spectral hardening is due to an increased column density at the projected nebular edge.

The Sun’s Magnetic Power Spectra over Two Solar Cycles. I. Calibration between SDO/HMI and SOHO/MDI Magnetograms

The Sun’s magnetic field is strongly structured over a broad range of scales. Magnetic spatial power spectral analysis provides a powerful tool for understanding the various scales of magnetic fields and their interactions with plasma motions. We aim to investigate the power spectra using spherical harmonic decomposition of high-resolution Solar and Heliospheric Observatory (SOHO)/Michelson Doppler Imager (MDI) and Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) synoptic magnetograms covering three consecutive solar cycle minima, in a series of papers. As the first of the series, we calibrate and analyze the power spectra based on cotemporal SDO/HMI and SOHO/MDI data in this paper. For the first time, we find that the calibration factor r between SOHO/MDI and SDO/HMI varies with the spatial scale l of the magnetic field, where l is the degree of the spherical harmonic. The calibration factor satisfies . With the calibration function, most contemporaneous SOHO/MDI and SDO/HMI magnetograms show consistent power spectra from about 8 Mm to the global scales over about three orders of magnitude. Moreover, magnetic power spectra from SOHO/MDI and SDO/HMI maps show peaks/knees at l ≈ 120, corresponding to the typical supergranular scale (about 35 Mm) constrained from direct velocimetric measurements. This study paves the way for investigating the solar cycle dependence of supergranulation and magnetic power spectra in subsequent studies.

Swash flows generated by a train of solitary waves on a planar slope

Six consecutive solitary waves with identical wave height and separation time are generated to study the flow structures during the uprush–downwash interactions in the swash zone. Using particle image velocimetry, the cross-shore velocity fields are captured. Two different wave conditions are examined with different wave-height-to-water-depth ratios, i.e.$H_o/h=0.11$and 0.22. The uprush–downwash interaction reaches quasi-steady state from the third solitary wave for both cases. For the former case, a weak non-stationary hydraulic jump appears during the downwash flow for all the six consecutive waves. The weak hydraulic jump evolves into a momentarily ‘stationary’ broken bore when the next wave arrives. For the latter case, the larger wave height generates stronger wave breaking. No non-stationary hydraulic jump is observed as the duration of downwash flow is relatively short. The flow reverses to the onshore direction before the downwash Froude number reaches the hydraulic jump condition. The temporal and spatial evolution of turbulence structure at the quasi-steady state is quantified using the spatial spectral analysis, the integral length scale and turbulence eddy viscosity. The results suggest that the large-scale energy generated during the uprush–downwash interaction modified the slope of the turbulence energy spatial spectrum in the inertial subrange from$-$5/3 to$-$1 in the larger length scale region, indicating the energy cascade depends not only on the dissipation rate, but also on the turbulent kinetic energy from the large-scale turbulence structure because of the large-scale energy injection in the inertial subrange.

Iid2022: a workshop on statistical methods for event data in astronomy

We review the iid2022 workshop on statistical methods for X-ray and γ-ray astronomy and high–energy astrophysics event data in astronomy, held in Guntersville, AL, on Nov. 15–18 2022. New methods for faint source detection, spatial point processes, variability and spectral analysis, and machine learning are discussed. Ideas for future developments of advanced methodology are shared.

Active Flow Control in Compressor Cascades with Steady and Pulsed Jets

This paper describes a detailed experimental investigation into the impact of steady and pulsed blowing on endwall secondary structures and losses in a compressor cascade. Owing to their high configuration flexibility, injection holes are integrated in the cascade sidewalls to manage the secondary flows. Loss reductions of 3.2 and 5.72% relative to the uncontrolled case are achieved by steady blowing with straight and optimized inclined holes, respectively. Superior loss reduction of 7.85% is obtained by pulsed blowing through inclined holes. To identify the secondary flow structures near the endwall and suction surfaces, a self-developed oil visualization method and spatial-spectral analysis are performed. Experimental results show that two concentrated shedding vortices exist in the cascade corner region. Loss reduction is achieved as the blowing suppresses the dominant vortex. Pulsed blowing intensifies the acceleration effect on the boundary layer, resulting in better performance with the same injection velocity. The impact of the pulse frequency on loss generation is investigated, and it is found that the optimal frequency is close to the shedding frequency of the dominant vortex in the cascade corner region.

Spatial-Spectral Analysis of Hyperspectral Images Reveals Early Detection of Downy Mildew on Grapevine Leaves.

Downy mildew is a highly destructive disease of grapevine. Currently, monitoring for its symptoms is time-consuming and requires specialist staff. Therefore, an automated non-destructive method to detect the pathogen before the visible symptoms appear would be beneficial for early targeted treatments. The aim of this study was to detect the disease early in a controlled environment, and to monitor the disease severity evolution in time and space. We used a hyperspectral image database following the development from 0 to 9 days post inoculation (dpi) of three strains of Plasmopara viticola inoculated on grapevine leaves and developed an automatic detection tool based on a Support Vector Machine (SVM) classifier. The SVM obtained promising validation average accuracy scores of 0.96, a test accuracy score of 0.99, and it did not output false positives on the control leaves and detected downy mildew at 2 dpi, 2 days before the clear onset of visual symptoms at 4 dpi. Moreover, the disease area detected over time was higher than that when visually assessed, providing a better evaluation of disease severity. To our knowledge, this is the first study using hyperspectral imaging to automatically detect and show the spatial distribution of downy mildew on grapevine leaves early over time.

Improving the accuracy and performance speed of the digital spectral-correlation method for measuring delay in radio signals and direction finding

A promising direction for the development of passive radar monitoring stations is to improve their efficiency by increasing their speed of performance. For the digital spectral-correlation method for determining the delay of radio signals and direction finding, analytical expressions have been derived for a variance of the estimation of the delay in receiving a signal by radio channels and directions to the source of radio emission. A feature of the method reported in this study is the use of two-stage temporal and spatial spectral analysis of the mutual spectrum, a single-iteration correlation analysis. The duration of estimating the direction finding has been evaluated through the total number of multiplication operations with accumulation. The proposed method, while providing for a gain of 27 times in terms of performance speed, demonstrated a slight decrease in accuracy compared to the optimal one due to energy signal loss. The result of the simulation has established the dependences of the standard deviation in the direction finding and delay estimates on the signal-to-noise ratio, the type of spectral analysis window, and the size of the antenna base. The standard deviation of the direction-finding estimate depends on the signal-to-noise ratio and varies over the range of values [0.08; 0.034]° with a change in the signal/noise ratio [−10; 40] dB. As the signal/noise ratio increases, the error decreases in line with a hyperbolic dependence. The standard deviation of the delay estimate depends on the signal-to-noise ratio and varies similarly to the error of the directional estimate, and is in the range of values [18.176; 1.56] ns, which corresponds to an error of [0.637; 0.055] %. The error of direction-finding estimation, depending on the size of the antenna base, decreases in the exponent within [1.6; 0.03]° with an increase in the antenna base in the range from 200 to 7,500 m. The results reported here could be used for the parametric optimization of spectral-correlation radio direction finders at passive radar monitoring stations.

Bayesian Subpixel Mapping of Hyperspectral Imagery via Discrete Endmember Variability Mixture Model and Markov Random Field

Although Bayesian methods have been very effective for spatial-spectral analysis of hyperspectral imagery (HSI), they had not been fully explored for enhanced sub-pixel mapping (SPM) by simultaneously considering several key issues i.e., endmember variability, the discrete nature of subpixel class labels and the spatial information in HSI. Therefore, we propose a new Bayesian SPM method based on discrete endmember variability mixture model (DEMM) and Markov random field (MRF), which has three main characteristics. First, DEMM allows the advanced SPM by completely accounting for the endmember-abundance patterns of each pixel to accommodate the endmember variability, the discrete hidden class label field of subpixels while taking into account the noise heterogeneity effect. Second, the discrete class label field modeled by MRF together with the DEMM, which can be integrated into a novel Bayesian model to better exploit the spatial contextual and spectral information. Third, the resulting Bayesian model can be efficiently solved by a designed expectation-maximization (EM) iteration, where E-step estimates the subpixel class label field using a simulated annealing (SA) algorithm and M-step estimates the endmembers for each pixel in HSI using alternating nonnegative least squares (ANLS) approach. The experimental results on three HSI datasets demonstrate that the proposed approach outperforms previously available SPM techniques.

Performance of the Adriatic early warning system during the multi-meteotsunami event of 11–19 May 2020: an assessment using energy banners

Abstract. This study quantifies the performance of the Croatian meteotsunami early warning system (CMeEWS) composed of a network of air pressure and sea level observations, a high-resolution atmosphere–ocean modelling suite, and a stochastic surrogate model. The CMeEWS, which is not operational due to a lack of numerical resources, is used retroactively to reproduce the multiple events observed in the eastern Adriatic between 11 and 19 May 2020. The performances of the CMeEWS deterministic models are then assessed with an innovative method using energy banners based on temporal and spatial spectral analysis of the high-pass-filtered air pressure and sea level fields. It is found that deterministic simulations largely fail to forecast these extreme events at endangered locations along the Croatian coast, mostly due to a systematic northwestward shift of the atmospheric disturbances. Additionally, the use of combined ocean and atmospheric model results, instead of atmospheric model results only, is not found to improve the selection of the transects used to extract the atmospheric parameters feeding the stochastic meteotsunami surrogate model. Finally, in operational mode, the stochastic surrogate model would have triggered the warnings for most of the observed events but also set off some false alarms. Due to the uncertainties associated with operational modelling of meteotsunamigenic disturbances, the stochastic approach has thus proven to overcome the failures of the deterministic forecasts and should be further developed.

Superpixel-guided preprocessing algorithm for accelerating hyperspectral endmember extraction based on spatial–spectral analysis

Preprocessing is a major area of interest in the field of hyperspectral endmember extraction, for it can provide a few high-quality candidates for fast endmember extraction without sacrificing endmember accuracy. We propose a superpixel-guided preprocessing (SGPP) algorithm to accelerate endmember extraction based on spatial compactness and spectral purity analysis. The proposed SGPP first transforms a hyperspectral image into low-dimension data using principal component analysis. SGPP then utilizes the superpixel method, which normally has linear complexity, to segment the first three components into a set of superpixels. Next, SGPP transforms low-dimension superpixels into noise-reduced superpixels and calculates their spatial compactness and spectral purity based on Tukey’s test and data convexity. SGPP finally retains a few high-quality pixels from each superpixel with high spatial compactness and spectral purity indices for subsequent endmember identification. Based on the spectral angle distance, root-mean-square error, and speedup, experiments are conducted on synthetic and real hyperspectral datasets, and they indicate that SGPP is superior to current state-of-the-art preprocessing techniques.

Load balancing transmission technology of network communication based on phase spectrum compensation

In order to improve the load balance scheduling transmission ability of multi-frequency network communication in high-order nonlinear system, load balance design is needed. A load balance transmission method of multi-frequency network communication in high-order nonlinear system based on phase spectrum compensation is proposed. The time domain model of high-order nonlinear system multi-frequency network communication load is constructed by multi-frequency modulation phase spectrum compensation method. The feature detection of high-order nonlinear system multi-frequency network communication load is realized by high-order statistical feature connection identification and communication load balancing method. The autocorrelation constraint parameters of high-order nonlinear system multi-frequency network communication load are analyzed. The multi-dimensional array networking structure model of high-order nonlinear system multi-frequency network communication load is constructed by spatial spectral density analysis method. Combined with phase spectrum compensation and signal detection methods, the extracted high-order nonlinear system multi-frequency network communication load spectrum features are adaptively scheduled and filtered. In the wireless communication networking environment, load balance transmission of communication load in multi-frequency network of high-order nonlinear system is realized. The simulation results show that this method has better balance and lower error rate in multi-frequency network communication load balancing transmission, which improves the accuracy of multi-frequency network communication load balancing scheduling in high-order nonlinear systems.

Understanding the radio relic emission in the galaxy cluster MACS J0717.5+3745: Spectral analysis

Radio relics are diffuse, extended synchrotron sources that originate from shock fronts generated during cluster mergers. The massive merging galaxy cluster MACS J0717.5+3745 hosts one of the more complex relics known to date. We present upgraded Giant Metrewave Radio Telescope band 3 (300−500 MHz) and band 4 (550−850 MHz) observations. These new observations, combined with published VLA and the new LOFAR HBA data, allow us to carry out a detailed, high spatial resolution spectral analysis of the relic over a broad range of frequencies. The integrated spectrum of the relic closely follows a power law between 144 MHz and 5.5 GHz with a mean spectral slope α = −1.16 ± 0.03. Despite the complex morphology of this relic, its subregions and the other isolated filaments also follow power-law behaviors, and show similar spectral slopes. Assuming diffusive shock acceleration, we estimated a dominant Mach number of ∼3.7 for the shocks that make up the relic. A comparison with recent numerical simulations suggests that in the case of radio relics, the slopes of the integrated radio spectra are determined by the Mach number of the accelerating shock, with α nearly constant, namely between −1.13 and −1.17, for Mach numbers 3.5 − 4.0. The spectral shapes inferred from spatially resolved regions show curvature, we speculate that the relic is inclined along the line of sight. The locus of points in the simulated color-color plots changes significantly with the relic viewing angle. We conclude that projection effects and inhomogeneities in the shock Mach number dominate the observed spectral properties of the relic in this complex system. Based on the new observations we raise the possibility that the relic and a narrow-angle-tailed radio galaxy are two different structures projected along the same line of sight.

Finger Pad Topography beyond Fingerprints: Understanding the Heterogeneity Effect of Finger Topography for Human-Machine Interface Modeling.

With the rapid development of haptic devices, there is an increasing demand to understand finger pad topography under different conditions, especially for investigation of the human-machine interface in surface haptic devices. An accurate description of finger pad topography across scales is essential for the study of the interfaces and could be used to predict the real area of contact and friction force, both of which correlate closely with human tactile perception. However, there has been limited work reporting the heterogeneous topography of finger pads across scales. In this work, we propose a detailed heterogeneous finger topography model based on the surface roughness power spectrum. The analysis showed a significant difference between the topography on ridges and valleys of the fingerprint and that the real contact area estimation could be different by a factor of 3. In addition, a spatial-spectral analysis method is developed to effectively compare topography response to different condition changes. This paper provides insights into finger topography for advanced human-machine interaction interfaces.

A Multiwavelength Study of the γ-Ray Binary Candidate HESS J1832–093

Abstract We investigate the nature of the unidentified very-high-energy γ-ray object, HESS J1832–093, in a multiwavelength context. Based on X-ray variability and spectral index ( ), and its broadband spectrum, which was remarkably similar to that of HESS J0632+057—a confirmed γ-ray binary—HESS J1832–093 has been considered a strong γ-ray binary candidate in previous works. In this work, we provide further evidence for this scenario. We obtained a spectrum of its IR counterpart using Gemini/Flamingo, finding absorption lines that are usually seen in massive stars, in particular O stars. We also obtained a rather steep ATCA spectrum ( ), which is consistent with a γ-ray binary. Based on spatial-spectral analysis and variability search, we found that 4FGL J1832.9-0913 is possibly associated with SNR G22.7-0.2 rather than with HESS J1832–093 only.

Effects of Topographic Perturbation on the Precipitation Distribution in Sichuan

Terrain characteristics can be accurately represented in spectrum space. Terrain spectra can quantitatively reflect effects of topographic dynamic forcing on the atmosphere. The one-dimensional weighted-average spatial spectral analysis method is used to explore topographic forcing on precipitation distribution in Sichuan. Results indicate that spectral distributions of terrain and winter precipitation in zonal direction present a typical resonance coupling pattern, while that of terrain and precipitation in other seasons drifts toward the smaller scale. In meridional direction, spectral distributions of terrain and precipitation in each season present the large-scale drift pattern. Different patterns are probably relevant to the change of circulations. In winter, due to strong zonal circulation and weak meridional circulation, atmospheric fluctuations caused by zonal topographic forcing show the most significant impact on precipitation. After that season, the zonal circulation weakens gradually in agreement with the decrease of zonal topographic forcing while the meridional flow enhances, leading to the increase of the damping of the zonal wind disturbance caused by terrain, and the pattern transforms from resonance to drift. Summer rainfall is produced by interaction among different scale systems, and terrain is one of the most important factors. The maximum topographic spectral energy in zonal direction is about an order of magnitude larger than that in meridional direction, implying that effects of topographic dynamic forcing are zonally stronger than that in meridional direction. Values of meridional and zonal topographic characteristic scales are 296.8 km and 475.8 km, respectively, which reflects the characteristic of the mesoscale topographic forcing coincident with the frequent mesoscale systems in Sichuan. The peak of the precipitation spectral energy in summer is about two orders of magnitude larger than that in winter and one order of magnitude larger than that in spring or autumn, and the characteristic scale in summer is about 150 km smaller than that in winter. It illustrates that the intensity of the zonal topographic dynamic forcing in summer is significantly increased when the scale of precipitation systems decreases, which explains the high frequency of mesoscale convective precipitation, and implies the significant impact of topographic dynamic forcing on atmosphere as well. The strongest summer precipitation in Sichuan is located at Ya'an, where larger-scale topographic perturbation is more significant than other region in Sichuan. The terrain spectra and summer precipitation spectra in meridional direction are phase-locked in identical wavelength (37.1 km), implying the critical role of terrain on the occurrence of heavy rainfall, and the effect of topographic dynamic forcing in meridional direction is dominant.

Common spatial-spectral analysis of EMG signals for multiday and multiuser myoelectric interface

Practical implementation of myoelectric interfaces have been largely hindered by cumbersome training and retraining procedures required for use across multiple days or for multiple users. We thus present a common spatial-spectral analysis (CSSA) framework to eliminate the need for retraining over multiple days or for multiple users. The CSSA is implemented through spectral decomposition and common modes analysis, maximumly utilizing the common spatial-spectral electromyography (EMG) mode from multiple days or for multiple users. Experiments involving two scenarios were conducted to simulate the application of multiday or multiuser myoelectric interface. Eight healthy and three amputee subjects participated in the first experiment for ten consecutive days, and seven healthy subjects participated in the second experiment involving a multiuser interface. Experimental results demonstrated that the control performance without retraining the myoelectric interface with the CSSA was significantly improved, and the classifier model pre-trained by background data under CSSA enabled EMG signals from new days or users to be recognized without training or retraining. The results could serve as a foundation for practical implementation of myoelectric interfaces.

METHOD OF AUTOMATED EXTRACTING OF DISPERSION CURVES BASED ON TIME-FREQUENCY DISTRIBUTION OF SEISMIC DATAv

The paper discusses the method of multichannel analysis of surface waves. We propose an automated method of surface waves extraction, based on the time-frequency representation of seismograms and their subsequent spatial spectral analysis. This approach is robust for the extraction of smooth and realistic dispersion curves in automatic mode. This provides a more reliable assessment of high-velocity sections of shear waves by the method of multichannel analysis of surface waves. The article presents the results of testing of the developed approach with using noisy synthetic and real seismic data.

TomoSAR Imaging for the Study of Forested Areas: A Virtual Adaptive Beamforming Approach

Among the objectives of the upcoming space missions Tandem-L and BIOMASS, is the 3-D representation of the global forest structure via synthetic aperture radar (SAR) tomography (TomoSAR). To achieve such a goal, modern approaches suggest solving the TomoSAR inverse problems by exploiting polarimetric diversity and structural model properties of the different scattering mechanisms. This way, the related tomographic imaging problems are treated in descriptive regularization settings, applying modern non-parametric spatial spectral analysis (SSA) techniques. Nonetheless, the achievable resolution of the commonly performed SSA-based estimators highly depends on the span of the tomographic aperture; furthermore, irregular sampling and non-uniform constellations sacrifice the attainable resolution, introduce artifacts and increase ambiguity. Overcoming these drawbacks, in this paper, we address a new multi-stage iterative technique for feature-enhanced TomoSAR imaging that aggregates the virtual adaptive beamforming (VAB)-based SSA approach, with the wavelet domain thresholding (WDT) regularization framework, which we refer to as WAVAB (WDT-refined VAB). First, high resolution imagery is recovered applying the descriptive experiment design regularization (DEDR)-inspired reconstructive processing. Next, the additional resolution enhancement with suppression of artifacts is performed, via the WDT-based sparsity promoting refinement in the wavelet transform (WT) domain. Additionally, incorporation of the sum of Kronecker products (SKP) decomposition technique at the pre-processing stage, improves ground and canopy separation and allows for the utilization of different better adapted TomoSAR imaging techniques, on the ground and canopy structural components, separately. The feature enhancing capabilities of the novel robust WAVAB TomoSAR imaging technique are corroborated through the processing of airborne data of the German Aerospace Center (DLR), providing detailed volume height profiles reconstruction, as an alternative to the competing non-parametric SSA-based methods.

Passive Three-Dimensional Spatial-Spectral Analysis Based on k-Space Tomography

A 2D distributed-aperture imaging system paired with a newly developed imaging modality, k-space tomography, is presented for detection of radio waves’ frequency and angle of arrival in azimuthal and elevation directions through coherent optical processing. This technique uses fiber-length dispersion in conjunction with a distributed antenna array to provide unique spatio-temporally encoded charge-coupled device (CCD)-captured interferograms, from which a computational tomographic reconstruction of the RF signal environment at newly allocated 5G bands can be obtained.