Spatial Spectrum Analysis Research Articles

Особливості розпаду щільної плазми високовольтних імпульсних розрядів у воді, ініційованих електричним вибухом залізного провідника

The article presents the results of investigations of the decay coefficients of dense plasma in impulse discharges in water initiated by an electric explosion of an iron conductor. An analysis of time-resolved and spatial emission spectra of the discharges was performed, along with the study of absorption spectra dynamics with a 5 μs interval. The electron concentration of the dense plasma was determined at different time points, allowing the determination of its decay coefficients at electron concentrations ranging from 1020 to 1021 cm-3. It was found that under equal electron concentrations in the plasma, the decay coefficients of plasma with iron impurities are consistent with the decay coefficients of plasma with tungsten impurities.

Investigation of clear cell renal cell carcinoma grades using diffusion-relaxation correlation spectroscopic imaging with optimized spatial-spectrum analysis.

To differentiate high-grade from low-grade clear cell renal cell carcinoma (ccRCC) using diffusion-relaxation correlation spectroscopic imaging (DR-CSI) spectra in an equal separating analysis. Eighty patients with 86 pathologically confirmed ccRCCs who underwent DR-CSI were enrolled. Two radiologists delineated the region of interest. The spectrum was derived based on DR-CSI and was further segmented into multiple equal subregions from 2*2 to 9*9. The agreement between the 2 radiologists was assessed by the intraclass correlation coefficient (ICC). Logistic regression was used to establish the regression model for differentiation, and 5-fold cross-validation was used to evaluate its accuracy. McNemar's test was used to compare the diagnostic performance between equipartition models and the traditional parameters, including the apparent diffusion coefficient (ADC) and T2 value. The inter-reader agreement decreased as the divisions in the equipartition model increased (overall ICC ranged from 0.859 to 0.920). The accuracy increased from the 2*2 to 9*9 equipartition model (0.68 for 2*2, 0.69 for 3*3 and 4*4, 0.70 for 5*5, 0.71 for 6*6, 0.78 for 7*7, and 0.75 for 8*8 and 9*9). The equipartition models with divisions >7*7 were significantly better than ADC and T2 (vs ADC: P = .002-.008; vs T2: P = .001-.004). The equipartition method has the potential to analyse the DR-CSI spectrum and discriminate between low-grade and high-grade ccRCC. The evaluation of DR-CSI relies on prior knowledge, and how to assess the spectrum derived from DR-CSI without prior knowledge has not been well studied.

Salt resistance study and molecular dynamics simulation of hydrophobic-association polymer with internal salt structure

The salt resistance of hydrophobically relating polymer fracturing fluid is one of the main indicators to meet the fracturing operation. Thus, a chain transfer agent was created in this study. Hydrophobically related polymer PDMA2 was synthesized in an aqueous solution through the RAFT approach. The salt resistance mechanism of the polymer was elucidated using molecular simulation software. The experimental results demonstrated that the salt resistance of the polymer can be enhanced by introducing long hydrophobic chain monomers via RAFT polymerization. Inorganic salt ions can improve the polymer skeleton and facilitate polymer chain bonding. The rotation radius of the hydrophobic polymer PDMA2 lowers as the salt concentration rises, allowing polymer molecule interaction. Combined with spatial conformation and fluorescence spectrum analysis, PDMA2 containing hydrophobic monomer was discovered to improve the association effect of polymer and produce more hydrophobic microregions. The radial distribution function results show that increasing the salt content compresses the polymer's main chain. On the polymer backbone, the radial distribution function between N-N atoms grows. This study demonstrates that the hydrophobic-association polymer can meet the service conditions of oilfield mineralized strata and lower the consumption of freshwater resources.

Clustering analysis of high spatial resolution spectra of asteroid (162173) Ryugu from Hayabusa2/NIRS3

Asteroids, and more globally small bodies, are keys to unravel the origin and the evolution of our Solar system. Remnants of the material which formed planets early on, they captured the composition and the conditions of formation of the latter at that time, since they did not undergo too harsh internal alteration during their lifetimes. The Hayabusa2 spacecraft explored the Cb-type asteroid (162173) Ryugu between June 2018 and November 2019, notably collecting data with its Near-InfraRed Spectrometer (NIRS3) in the 1.8–3.2 ​μm range. We selected five NIRS3 datasets among the ones having the highest spatial resolution on which we applied the G-mode multivariate statistical analysis, in order to spot small heterogeneities at the surface of Ryugu. Both global scale and local scale cases were investigated. With a confidence level of 3σ, we obtained two classes at global and local scales, while decreasing to 2σ results in the identification of more classes (five at global scale, four at local scale). Overall, our results are consistent among them and with previous studies. In particular, terrains spectrally redder as well as terrains spectrally bluer than the average surface are newly identified by our analysis. The floors of all main craters at the surface of Ryugu appear redder than their surroundings, and are associated with a probable smaller grain size material. A large depression of the Northern hemisphere may contain bluer heterogeneities likely due to a more packed or/and fresher, subsequently deposited material. Finally, a comparison with data from the Hayabusa2 optical camera ONC-T shows no evident correlation between the spectral properties in the near-infrared and in the visible.

First Sidelobe Analysis of Spatial Spectrum for Distributed Dual mmWave Radars

This letter considers a distributed cascade of two millimeter-wave (mmWave) radars to achieve a large virtual aperture for high-resolution angle measurement. In order to explore the high sidelobe problem caused by distributed radars, we derive the general Bartlett spatial spectrum expression of the virtual array. Furthermore, we introduce four cases to describe the relationship between the radar spacing, the number of transmitters/receivers, and the sidelobe position of the spatial spectrum. Finally, numerical simulation and experiment examples are provided to verify the effectiveness of the analysis.

Electrochemical Polishing of Tungsten: An Investigation of Critical Spatial Frequency and Ultimate Roughness

Electrochemical polishing (ECP) offers incomparable advantages and great potential in metal polishing by surface errors correction. This paper systematically investigates the ultimate roughness and surface errors correction ability of ECP over different spatial frequency ranges. This paper further explores the law of ECP influencing errors at different frequency ranges, proposes and clarifies the concept of critical spatial frequency, and studies the law of polishing parameters affecting critical spatial frequency by using spatial frequency spectrum analysis. The surface roughness evolution and ultimate roughness of ECP were investigated using the surface error filtering method based on the critical spatial frequency. The ultimate roughness of ECP was determined by two different strategies, (i) stepwise polishing and (ii) one-step polishing. In addition, the stepwise polishing was also investigated for any possible inconsistency with one-step polishing on the final surface roughness. As ECP progressed, the optimization speed of surface roughness gradually decreased, and the surface roughness eventually reached a stable limiting value. Further analysis revealed that crystal corrosion is mainly responsible for inhibiting surface roughness optimization.

Spatial Power Spectral Analysis of the Suzaku X-Ray Background

Power spectra of spatial fluctuations of X-ray emission may impose constraints on the origins of the emission independent of that from the energy spectra. We generated spatial power spectrum densities (PSDs) of blank X-ray skies observed with the Suzaku X-ray observatory utilizing the modified Δ-variance method. Using the total measured count rate as the diagnostic tool, we found that a model consisting of the sum of two components, one for the unresolved faint point sources and one for the uniform flat-field emission, can represent well the observed PSD in three different energy bands (0.2–0.5, 0.5–2, and 2–10 keV); only an upper limit is obtained for the latter component in 2–10 keV. X-ray counting rates corresponding to the best-fit PSD model functions and diffuse emission fractions were estimated, and we confirmed that the sum of the counting rates of two model components is consistent with those actually observed with the detector for all energy bands. The ratio of the flat-field counting rate to the total in 0.5–2 keV, however, is significantly larger than the diffuse emission fraction estimated from the model fits of energy spectra. We discussed that this discrepancy can be reconciled by systematic effects in the PSD and energy spectrum analyses. The present study demonstrates that the spatial power spectrum analysis is powerful in constraining the origins of the X-ray emission.

Source depth estimation using angle-range interference pattern in deep ocean bottom bounce area

Passive sonar limits the ability to sample vertical scale spatiotemporally, and the received signal is indistinct by noise, resulting in the performance degradation or even failure of the source depth estimation method in deep ocean bottom bounce area. When vertical line array is arranged near the sea surface to locate the source by matched-field processing in bottom bounce area, there is great ambiguity in depth dimension. In this work, the problem of source depth estimation in bottom bounce area is addressed. The peak stripe of angle-range interference pattern is modeled and analyzed based on the ray theory, and a source depth estimation method is proposed, which comprises two parts: estimating sound source depth by utilizing peak stripe fluctuation characteristic combined with spatial spectrum analysis, and reconstructing interference pattern using principal component analysis. The flowchart of the method is listed as follows. Firstly, the spatial spectrum corresponding to each range is spliced to obtain the original angle-range interference pattern. Secondly, the original interference pattern is denoised by principal component analysis to obtain the reconstructed interference structure. Finally, the fluctuation period of peak fringes is extracted from the reconstructed interference pattern to calculate the source depth. Under the low signal-to-noise ratio (SNR) condition, the peak stripe destroyed by noise will reappear in the reconstructed interference pattern and the estimation result of sound source depth will be more accurate, making the source depth estimation method suitable for bottom bounce area. The method combines the space-time cumulative gain of the array and the low-rank characteristic of the interference pattern. The simulation results obtained by Bellhop indicate that the fluctuation period of peak stripe depends on the depth and frequency of the source, which is consistent with the modeling result, and the source depth can be estimated precisely by spatial Fourier transform. The simulation results also show that the rank of the interference pattern is very low and the peak stripe can be composed of a few principal components. Monte Carlo experimental results indicate that the estimated results of the source depth by using reconstructed interference pattern are more accurate than those without using principal component analysis at low SNR condition. The proposed method can achieve more than 80% accuracy at –3 dB SNR.

GASKAP-HI pilot survey science I: ASKAP zoom observations of Hi emission in the Small Magellanic Cloud

Abstract We present the most sensitive and detailed view of the neutral hydrogen ( ${\rm H\small I}$ ) emission associated with the Small Magellanic Cloud (SMC), through the combination of data from the Australian Square Kilometre Array Pathfinder (ASKAP) and Parkes (Murriyang), as part of the Galactic Australian Square Kilometre Array Pathfinder (GASKAP) pilot survey. These GASKAP-HI pilot observations, for the first time, reveal ${\rm H\small I}$ in the SMC on similar physical scales as other important tracers of the interstellar medium, such as molecular gas and dust. The resultant image cube possesses an rms noise level of 1.1 K ( $1.6\,\mathrm{mJy\ beam}^{-1}$ ) $\mathrm{per}\ 0.98\,\mathrm{km\ s}^{-1}$ spectral channel with an angular resolution of $30^{\prime\prime}$ ( ${\sim}10\,\mathrm{pc}$ ). We discuss the calibration scheme and the custom imaging pipeline that utilises a joint deconvolution approach, efficiently distributed across a computing cluster, to accurately recover the emission extending across the entire ${\sim}25\,\mathrm{deg}^2$ field-of-view. We provide an overview of the data products and characterise several aspects including the noise properties as a function of angular resolution and the represented spatial scales by deriving the global transfer function over the full spectral range. A preliminary spatial power spectrum analysis on individual spectral channels reveals that the power law nature of the density distribution extends down to scales of 10 pc. We highlight the scientific potential of these data by comparing the properties of an outflowing high-velocity cloud with previous ASKAP+Parkes ${\rm H\small I}$ test observations.

Real-time monitoring of silica ceramic composites grinding surface roughness based on signal spectrum analysis

Aiming at the difficulty of real-time ceramic surface roughness monitoring in the automatic grinding process, a time–spatial domain spectrum analysis method was proposed based on the monitored grinding force signal and grinding surface texture curve. Discrete Fourier Transform (DFT) was employed to acquire spectral responses of grinding force and surface texture. The mean and maximum values of grinding force signal and surface texture in their amplitude-frequency curve were found to be positively correlated. The chi-square distribution model was then developed to predict the amplitude-frequency response of surface texture by monitoring force signal. Subsequently, the Inverse Discrete Fourier Transform (IDFT) was performed to obtain the surface texture curve. The mathematical function of the surface texture curve was modelled by the grinding force signal, finally. The surface roughness (Ra) could be calculated from the surface texture curve. In this work, taking the surface grinding of silica ceramic composites as an example, 75 stochastic groups of grinding experiments were designed. The results show that the real-time monitoring of silica ceramic composites grinding surface roughness could be accurately predicted by the chi-square model. The correlation coefficient between the predicted Ra and the actual one has reached 0.9821. The proposed prediction model could be valuable for the online measurement of grinding quality towards intelligent manufacturing.

Generation of buckling and wrinkling in elastic films: The effect of initial imperfection.

The symmetry breaking that is induced by initial imperfection (e.g., geometry or material inhomogeneity and out-of-plane disturbance) is a necessary condition for film buckling. However, the effect of initial imperfection on the buckling behavior is still not clear cut. Herein, given an elastic substrate-free circular film subjected to in-plane compressive stress and arbitrary initial imperfection, evolution of the deflection morphology is numerically studied and theoretically analyzed. Specifically, a two-dimensional spatial spectrum analysis is adopted to acquire the deflection morphology's dominant wavelength, which is combined with the maximum absolute deflection to characterize the deflection patterns. Before the so-called critical instability, the film under compression is found to go through a transition stage. Overall, the deflection increment in this stage is negligible except approaching the critical state. However, the dominant wavelength is found to be continuously growing (or decreasing) rather than suddenly appears upon reaching the so-called critical state, and, interestingly, such growth is found to be independent of the intensity and pattern of the initial imperfection if the same initial dominant wavelength is guaranteed. In the discussion, for both the transition and buckling stages, evolution laws of the deflection amplitude and wavelength are established analytically and found to agree well with the numerical results. This research clearly presents the actual evolution process of wrinkling morphology from linear in-plane deformation with small stable deflection to out-of-plane instability with large deflection, which deepens the cognition of instability behavior of films and provides a basis for related applications such as high-precision mechanical characterization.

Imaging and Controlling Photonic Modes in Perovskite Microcavities.

Perovskite microcavities have excellent photophysical properties for integrated optoelectronic devices, such as nanolasers. Imaging and controlling the photonic modes within the cavity are fundamentally important to understand and develop applications. Here, photoemission electron microscopy (PEEM) is used to image the photonic modes within optical microcavities with a nanometer-scale spatial resolution. From a CsPbBr3 microcavity, hybrid mode patterns are observed. Spatial frequency spectrum analysis on the patterns uncovers the characteristic cavity modes, which are modeled with transverse magnetic (TM) and transverse electric (TE) waves, and assigned to exciton-polariton modes. Based on this understanding, the light focus in a designed microcavity is imaged in real space and controlled by the light field polarization. The study confirms that the cavity modes in perovskites can be effectively observed by the PEEM technique under resonant excitation, which, in turn, promotes the design of optoelectronic devices based on perovskite microcavities.

Ground moving target indication and parameter estimation algorithm using deramp space-time adaptive processing

Deramp space-time adaptive processing (Deramp-STAP) algorithm has been validated in its effectiveness in reducing the required channels to enable ground moving target indication (GMTI) for multi-channel synthetic aperture radar (SAR) systems. However, the parameter estimation for the moving target, including the critical radial velocity, is not accurate enough, and the radial velocity is always approximated by the equivalent velocity obtained by the Deramp operation. For the indication and imaging of ground moving targets, the accurate estimation of the radial velocity is of importance to improve the signal-clutter-noise-ratio of STAP and estimate the initial azimuth position of the moving target. A method for GMTI and the corresponding parameter estimation using Deramp-STAP is proposed. Compared with the traditional Deramp-STAP algorithms, the proposed algorithm utilizes the equivalent velocity estimated by Radon transform to remove the linear range migration before STAP and figure out where the moving target is located in the azimuth frequency domain. To estimate the radial velocity more accurately, the fast Fourier transform along the spatial direction is performed on the pixel where the moving target is located in the azimuth frequency domain after the Deramp operation, and then the radial velocity can be obtained through the spatial spectrum analysis. Finally, the estimated radial velocity is applied to construct the azimuth compression function for the moving target imaging, and then the initial azimuth position can be estimated. Several simulation experiments have been implemented to validate the effectiveness of the proposed algorithm.

Space division multiplexing technology based on transverse wavenumber of Lommel–Gaussian beam

We propose a novel orbital angular momentum (OAM) space division multiplexing system based on Lommel–Gaussian (LMG) beam, which utilizes different transverse wavenumbers under the same topological charge. Using the random phase screen method and diffraction theory, the evolution of light field and mode crosstalk are effectively analyzed during transmission. Owing to the non-diffracting feature, LMG beams are more robust than traditional Laguerre–Gaussian (LG) beams through spatial spectrum analysis under the same intensity. More importantly, the results show that the shape of demultiplexed spot is related to the symmetry of original OAM-carrying beam and LMG beams with smaller scaling factor are better for detection. This work is anticipated to open up new perspectives for future high-capacity communication missions.

Correction of refractive index mismatch-induced aberrations under radially polarized illumination by deep learning.

Radially polarized field under strong focusing has emerged as a powerful manner for fluorescence microscopy. However, the refractive index (RI) mismatch-induced aberrations seriously degrade imaging performance, especially under high numerical aperture (NA). Traditional adaptive optics (AO) method is limited by its tedious procedure. Here, we present a computational strategy that uses artificial neural networks to correct the aberrations induced by RI mismatch. There are no requirements for expensive hardware and complicated wavefront sensing in our framework when the deep network training is completed. The structural similarity index (SSIM) criteria and spatial frequency spectrum analysis demonstrate that our deep-learning-based method has a better performance compared to the widely used Richardson-Lucy (RL) deconvolution method at different imaging depth on simulation data. Additionally, the generalization of our trained network model is tested on new types of samples that are not present in the training procedure to further evaluate the utility of the network, and the performance is also superior to RL deconvolution.

Relative vibration identification of cutter and workpiece based on improved bidimensional empirical mode decomposition

In the process of cutting, the relative vibration between the cutter and the workpiece has an important effect on the surface topography. In this study, the bidimensional empirical mode decomposition (BEMD) method is used to identify such effect. According to Riesz transform theory, a type of isotropic monogenic signal is proposed. The boundary data is extended on the basis of a similarity principle that deals with serious boundary effect problem. The decomposition examples show that the improved BEMD can effectively solve the problem of boundary effect and decompose the original machined surface topography at multiple scales. The characteristic surface topography representing the relative vibration between the cutter and the workpiece through feature identification is selected. In addition, the spatial spectrum analysis of the extracted profile is carried out. The decimal part of the frequency ratio that has an important effect on the shape of the contour can be accurately identified through contour extraction and spatial spectrum analysis. The decomposition results of simulation and experimental surface morphology demonstrate the validity of the improved BEMD algorithm in realizing the relative vibration identification between the cutter and the workpiece.

Experimental study of bubble sources localization in a water tank for oil spill detection

Since the Deepwater Horizon oil spill in 2010, there have been increasing demand for a real-time monitoring system that can detect, locate, and assess oil leakages. To this goal, we launched a three-year research project to develop a passive acoustic technique in 2017. The leaked crude oil creates underwater sound through bubble oscillations in an oil spill event. This paper focuses on studying the localization of the source of bubble-induced sounds in an experimental environment. Hydrophone arrays were deployed randomly and used to receive the acoustic signals in a 2 m × 2 m × 2 m water tank. We used spatial spectrum analysis algorithms such as Multiple Signal Classification (MUSIC) and Estimation of Signal Parameters by Rotational Invariance Techniques (ESPRIT) to determine the direction of arrival (DOA) by a hydrophone Uniform Linear Array (ULA), and utilized the multiple 2-D angles to localize the bubbles in 3-D space. We will also investigate the sensitivity of the localization algorithm with respect to the variations of physical features such as the cluster of frequency components and noise level. Experiment results will be presented and discussed.Since the Deepwater Horizon oil spill in 2010, there have been increasing demand for a real-time monitoring system that can detect, locate, and assess oil leakages. To this goal, we launched a three-year research project to develop a passive acoustic technique in 2017. The leaked crude oil creates underwater sound through bubble oscillations in an oil spill event. This paper focuses on studying the localization of the source of bubble-induced sounds in an experimental environment. Hydrophone arrays were deployed randomly and used to receive the acoustic signals in a 2 m × 2 m × 2 m water tank. We used spatial spectrum analysis algorithms such as Multiple Signal Classification (MUSIC) and Estimation of Signal Parameters by Rotational Invariance Techniques (ESPRIT) to determine the direction of arrival (DOA) by a hydrophone Uniform Linear Array (ULA), and utilized the multiple 2-D angles to localize the bubbles in 3-D space. We will also investigate the sensitivity of the localization algorithm with respect...

Power spectrum modelling of galaxy and radio intensity maps including observational effects

ABSTRACT Fluctuations in the large-scale structure of the Universe contain significant information about cosmological physics, but are modulated in survey data sets by various observational effects. Building on existing literature, we provide a general treatment of how fluctuation power spectra are modified by a position-dependent selection function, noise, weighting, smoothing, pixelization, and discretization. Our work has relevance for the spatial power spectrum analysis of galaxy surveys with spectroscopic or accurate photometric redshifts, and radio intensity-mapping surveys of the sky brightness temperature including generic noise, telescope beams, and pixelization. We consider the autopower spectrum of a field, the cross-power spectrum between two fields and the multipoles of these power spectra with respect to a curved sky, deriving the corresponding power spectrum models, estimators, errors, and optimal weights. We note that ‘FKP weights’ for individual tracers do not in general provide the optimal weights when measuring the cross-power spectrum. We validate our models using mock data sets drawn fromN-body simulations.1 Our treatment should be useful for modelling and studying cosmological fluctuation fields in observed and simulated data sets.

Astrocytic Atrophy Following Status Epilepticus Parallels Reduced Ca2+ Activity and Impaired Synaptic Plasticity in the Rat Hippocampus.

Epilepsy is a group of neurological disorders commonly associated with the neuronal malfunction leading to generation of seizures. Recent reports point to a possible contribution of astrocytes into this pathology. We used the lithium-pilocarpine model of status epilepticus (SE) in rats to monitor changes in astrocytes. Experiments were performed in acute hippocampal slices 2–4 weeks after SE induction. Nissl staining revealed significant neurodegeneration in the pyramidal cell layers of hippocampal CA1, CA3 areas, and the hilus, but not in the granular cell layer of the dentate gyrus. A significant increase in the density of astrocytes stained with an astrocyte-specific marker, sulforhodamine 101, was observed in CA1 stratum (str.) radiatum. Astrocytes in this area were also whole-cell loaded with a morphological tracer, Alexa Fluor 594, for two-photon excitation imaging. Sholl analyses showed no changes in the size of the astrocytic domain or in the number of primary astrocytic branches, but a significant reduction in the number of distal branches that are resolved with diffraction-limited light microscopy (and are thought to contain Ca2+ stores, such as mitochondria and endoplasmic reticulum). The atrophy of astrocytic branches correlated with the reduced size, but not overall frequency of Ca2+ events. The volume tissue fraction of nanoscopic (beyond the diffraction limit) astrocytic leaflets showed no difference between control and SE animals. The results of spatial entropy-complexity spectrum analysis were also consistent with changes in ratio of astrocytic branches vs. leaflets. In addition, we observed uncoupling of astrocytes through the gap-junctions, which was suggested as a mechanism for reduced K+ buffering. However, no significant difference in time-course of synaptically induced K+ currents in patch-clamped astrocytes argued against possible alterations in K+ clearance by astrocytes. The magnitude of long-term-potentiation (LTP) was reduced after SE. Exogenous D-serine, a co-agonist of NMDA receptors, has rescued the initial phase of LTP. This suggests that the reduced Ca2+-dependent release of D-serine by astrocytes impairs initiation of synaptic plasticity. However, it does not explain the failure of LTP maintenance which may be responsible for cognitive decline associated with epilepsy.

Digital Speckle Photography of Subpixel Displacements of Speckle Structures Based on Analysis of Their Spatial Spectra

We have investigated the capabilities of the method of digital speckle interferometry for determining subpixel displacements of a speckle structure formed by a displaceable or deformable object with a scattering surface. An analysis of spatial spectra of speckle structures makes it possible to perform measurements with a subpixel accuracy and to extend the lower boundary of the range of measurements of displacements of speckle structures to the range of subpixel values. The method is realized on the basis of digital recording of the images of undisplaced and displaced speckle structures, their spatial frequency analysis using numerically specified constant phase shifts, and correlation analysis of spatial spectra of speckle structures. Transformation into the frequency range makes it possible to obtain quantities to be measured with a subpixel accuracy from the shift of the interference-pattern minimum in the diffraction halo by introducing an additional phase shift into the complex spatial spectrum of the speckle structure or from the slope of the linear plot of the function of accumulated phase difference in the field of the complex spatial spectrum of the displaced speckle structure. The capabilities of the method have been investigated in natural experiment.