Component Bands Research Articles

Utilization of ASTER data in lithological and lineament mapping of the southern flank of the Central High Atlas in Morocco

Geological mapping undoubtedly plays an important role in several studies and remote sensing data are of great significance in geological mapping, particularly in poorly mapped areas situated in inaccessible regions. In the present study, Principal Component Analysis (PCA), Band Rationing (BR) and Minimum Noise Fraction (MNF) algorithms are applied to map lithological units and extract lineaments in the Amezri-Amassine area, by using multispectral ASTER image and global digital elevation model (GDEM) data for the first time. Following preprocessing of ASTER images, advanced image algorithms such as PCA, BR and MNF analyses are applied to the 9ASTER bands. Validation of the resultant maps has relied on matching lithological boundaries and faults in the study area and on the basis of pre-existing geological maps. In addition to the PCA image, a new band-ratio image, 4/6–5/8–4/5, as adopted in the present work, provides high accuracy in discriminating lithological units. The MNF transformation reveals improvement over previous enhancement techniques, in detailing most rock units in the area. Hence, results derived from the enhancement techniques show a good correlation with the existing litho-structural map of the study area. In addition, the present results have allowed to update this map by identifying new lithological units and structural lineaments. Consequently, the methodology followed here has provided satisfactory results and has demonstrated the high potential of multispectral ASTER data for improving lithological discrimination and lineament extraction.

High-G MEMS Accelerometer Calibration Denoising Method Based on EMD and Time-Frequency Peak Filtering.

In order to remove noise generated during the accelerometer calibration process, an accelerometer denoising method based on empirical mode decomposition (EMD) and time-frequency peak filtering (TFPF) is proposed in this paper. Firstly, a new design of the accelerometer structure is introduced and analyzed by finite element analysis software. Then, an algorithm combining EMD and TFPF is proposed for the first time to deal with the noise of the accelerometer calibration process. Specific steps taken are to remove the intrinsic mode function (IMF) component of the high frequency band after the EMD decomposition, and then to use the TFPF algorithm to process the IMF component of the medium frequency band; meanwhile, the IMF component of the low frequency band is reserved, and finally the signal is reconstructed. The reconstruction results show that the algorithm can effectively suppress the random noise generated during the calibration process. The results of spectrum analysis show that EMD + TFPF can effectively protect the characteristics of the original signal and that the error can be controlled within 0.5%. Finally, Allan variance is used to analyze the results of the three methods to verify the filtering effect. The results show that the filtering effect of EMD + TFPF is the most obvious, being 97.4% higher than the original data.

Raman spectral analysis of microbial pigment compositions in vegetative cells and heterocysts of multicellular cyanobacterium

The one-dimensional multicellular cyanobacterium, Anabaena sp. PCC 7120, exhibits a simple topology consisting of two types of cells under the nitrogen-depleted conditions. Although the differentiated (heterocyst) and undifferentiated cells (vegetative cells) were distinguished by their cellular shapes, we found that their internal states, that is, microbial pigment compositions, were distinguished by using a Raman microscope. Almost of Raman bands of the cellular components were assigned to vibrations of the pigments; chlorophyll a, β-carotene, phycocyanin, and allophycocyanin. We found that the Raman spectral measurement can detect the decomposition of both phycocyanin and allophycocyanin, which are components of the light-harvesting phycobilisome complex in the photosystem II. We observed that the Raman bands of phycocyanin and allophycocyanin exhibited more remarkable decrease in the heterocysts when compared to those of chlorophyll a and β-carotene. This result indicated the prior decomposition of phycobilisome in the heterocysts. We show that the Raman measurement is useful to detect the change of pigment composition in the cell differentiation.

Iterative histogram equalization using discrete wavelet transform in low-dynamic range

A progressive histogram equalization (HE) and contrast enhancement method is proposed in the frequency domain. This method has an iterative structure based on the 6-sigma rule in the low-dynamic range using discrete wavelet transform. The proposed method determines an automatic threshold for attenuating the high-frequency amplitude of a signal in the discrete wavelet domain, based on the standard deviation of the absolute power of the high-frequency components in the signal band generated from the probability density function (PDF). Then an iterative quantization procedure is used where the PDF values in the frequency domain are randomly quantized. Besides, the maximum Bhattacharyya coefficient, which matches the original input image’s PDF, is used as a cost function to optimize the histogram smoothing output. For the random number generation, a 32-bit pseudorandom generator is employed to produce the same result for the output image at each runtime. The quantization factor parameter enables a controlled contrast enhancement rate to receive balanced equalization results in images. In the experimental studies, the proposed iterative HE method is compared with the well-known global, local, and brightness preserving algorithms. Experimental studies quantitatively and qualitatively display promising and encouraging results in terms of various state-of-the-art quality assessment metrics such as mean squared error, peak signal-to-noise ratio, structural similarity index measurement, contrast improvement index, absolute mean brightness error, and quality-aware relative contrast measure.

Speech Enhancement for Laser Doppler Vibrometer Dealing with Unknown Irradiated Objects

The acquisition of distant sound has always been a hot research topic. Since sound is caused by vibration, one of the best methods for measuring distant sound is to use a laser Doppler vibrometer (LDV). This laser has high directivity, that enables it to acquire sound from far away, which is of great practical use for disaster relief and other situations. However, due to the vibration characteristics of the irradiated object itself and the reflectivity of its surface (or other reasons), the acquired sound is often lacking frequency components in certain frequency bands and is mixed with obvious noise. Therefore, when using LDV to acquire distant speech, if we want to recognize the actual content of the speech, it is necessary to enhance the acquired speech signal in some way. Conventional speech enhancement methods are not generally applicable due to the various types of degradation in observed speech. Moreover, while several speech enhancement methods for LDV have been proposed, they are only effective when the irradiated object is known. In this paper, we present a speech enhancement method for LDV that can deal with unknown irradiated objects. The proposed method is composed of noise reduction, pitch detection, power spectrum envelope estimation, power spectrum reconstruction, and phase estimation. Experimental results demonstrate the effectiveness of our method for enhancing the acquired speech with unknown irradiated objects.

Exploring the impact of structure-sensitive factors on luminescence and absorption of trivalent rare earth embedded in disordered crystal structures of Gd3Ga5O12–Gd3Al5O12 and Lu2SiO5–Gd2SiO5 solid solution crystals

High resolution spectra of optical absorption and luminescence were recorded at temperatures below 6 K for Pr3+, Sm3+, Er3+, and Yb3+ ions embedded in Gd3Ga5O12–Gd3Al5O12 and Lu2SiO5–Gd2SiO5 solid solution crystals fabricated by the Czochralski method. Detailed analysis of acquired spectral bands related to transitions between the lowest energy components (0–0) lines of initial and terminal multiplets provided quantitative information regarding bandwidths, peak transition energies and number of band components. Combination of these data with structural peculiarities of the hosts made it possible to propose the interpretation of optical interaction in systems under study.

Mapping and analysis of structural lineaments using SRTM radar data and Landsat-8 OLI image: an example from the Telouet–Tighza area, Marrakech High Atlas, Morocco

This study provides the first evaluation of the potential of both the Landsat-8 Operational Land Imager (OLI) sensor images and the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) data for automated lineament extraction in the south side of the Marrakech High Atlas (Telouet–Tighza area). After image corrections, enhancement methods such as principal component analysis, band composite (BC), and directional filtering were adopted to create new images that provided high visibility of linear structures. The new Landsat BC image used in this study was selected based on the calculation of the optimum index factor and correlation index. In addition to the Landsat image, the SRTM DEM was used to detect structural lineaments in the area by generating shaded relief images. Multisource data, such as band ratio image, geological maps, and fieldwork, were used to eliminate the nongeological lineaments extracted. The results indicate that an automated method was applied successfully for lineament mapping in this area, by detailing the main tectonic faults. Moreover, new lineaments are identified and are validated by fieldwork. Structural lineaments extracted show compatibility in their direction, length, distribution, and density with the tectonic evolution of the study area. A total of 2945 lineaments were extracted with major ENE–WSW and predominant E–W directions. The new structural map shows more structural information compared with the geological map of this area and exemplifies the performance of Landsat-8 OLI bands and SRTM data in this kind of study.

Difference mode decomposition for adaptive signal decomposition

Adaptive extraction of concerned components (CC) from mixed frequency components remains to be a challenging topic in various research domains. Most existing adaptive mode decomposition algorithms for extracting CC, such as wavelet transform, wavelet packet transform, singular value decomposition, empirical mode decomposition, empirical wavelet transform, and variational mode decomposition, are intrinsically adaptive band-pass filter banks and they face the following two tough problems. The first problem is that they cannot separate CC from interferential components in same frequency bands. The second problem is that it is not fully effective in automatically selecting CC distributed in different frequency bands by using some designed criteria. In this paper, a new decomposition approach called difference mode decomposition (DMD) is proposed to adaptively decompose a mixed signal into CC, reference components, and noise, and enrich the domain of adaptive mode decomposition. The proposed DMD relies on convex optimization and Fourier transform, and its decomposition is mathematically justified and composes physical interpretations. Analyses of simulated and real-world bearing and gear vibration signals are used to verify the effectiveness and superiority of the proposed DMD over existing adaptive mode decomposition algorithms. It is demonstrated that the proposed DMD can effectively extract CC such as repetitive transients caused by bearing and gear faults. Moreover, since the proposed DMD is based on Fourier transform expanded by trigonometric basis functions, the proposed DMD can be easily extended to other domains by expanding basis functions besides the frequency domain.

Effects of Temperature on Visible and Infrared Spectra of Mercury Minerals Analogues

Mercury’s peculiar orbit around the Sun (3:2 spin–orbit resonance) and lack of atmosphere result in one the widest temperature ranges experienced at the surface of a planetary body in the solar system. Temperature variations affect the physical and, therefore, spectral properties of minerals to varying degrees; thus, it is crucial to study them in the context of the upcoming arrival of the BepiColombo spacecraft in Mercury orbit in the fall of 2025. In this work, we heated and cooled analog materials (plagioclase and volcanic glasses) at temperatures representative of the hermean surface. With our experimental setup, we could measure near-infrared (1.0–3.5 μm) and thermal infrared (2.0–14.3 μm) reflectance spectra of our analogs at various temperatures during a heating (25–400 ∘C) or cooling cycle (−125–25 ∘C), allowing us to follow the evolution of the spectral properties of minerals. We also collected reflectance spectra in the visible domain (0.47–14.3 μm) before and after heating. In the visible spectra, we identified irreversible changes in the spectral slope (reddening) and the reflectance (darkening or brightening) that are possibly associated with oxidation, whereas the temperature had reversible effects (e.g., band shifts of from ten to a hundred nanometers towards greater wavelengths) on the infrared spectral features of our samples. These reversible changes are likely caused by the crystal lattice dilatation during heating. Finally, we took advantage of the water and ice present on/in our samples to study the different components of the absorption band at 3.0 μm when varying temperatures, which may be useful as a complement to future observations of the north pole of Mercury. The wavelength ranges covered by our measurements are of interest for the SIMBIO-SYS and MERTIS instruments, which will map the mineralogy of Mercury’s surface from spring 2026, and for which we selected useful spectral parameters that are proxies of surface temperature variations.

GRB 200829A: External-shock Origin of the Very Early Prompt Emission?

Long-duration GRB 200829A was detected by Fermi-GBM and Swift-BAT/XRT, and then rapidly observed by other ground-based telescopes. It has a weak γ-ray emission in the very early phase and is followed by a bright spiky γ-ray emission pulse. The radiation spectrum of the very early emission is best fitted by a power-law function with index ∼−1.7. However, the bright spiky γ-ray pulse, especially the time around the peak, exhibits a distinct two-component radiation spectrum, i.e., Band function combined with a blackbody radiation spectrum. We infer the photospheric properties and reveal a medium magnetization at a photospheric position by adopting the initial size of the outflow as r 0 = 109 cm. It implies that the Band component in this pulse may be formed during the dissipation of the magnetic field. The power-law radiation spectra found in the very early prompt emission may imply the external-shock origination of this phase. Then, we perform the Markov Chain Monte Carlo method fitting on the light curves of this burst, where the jet corresponding to the γ-ray pulse at around 20 s is used to refresh the external shock. It is shown that the light curves of the very early phase and X-ray afterglow after 40 s, involving the X-ray bump at around 100 s, can be well modeled in the external-shock scenario. For the obtained initial outflow, we estimate the minimum magnetization factor of the jet based on the fact that the photospheric emission of this jet is missed in the very early phase.

Pressure broadening in Raman spectra of CH4–N2, CH4–CO2, and CH4–C2H6 gas mixtures

Different molecular environments change the spectrum of a given gas sample involved in a mixture compared to the spectrum of a pure gas. It is necessary to account for this effect to improve the accuracy of the analysis of the natural gas composition by Raman spectroscopy. First, the change in the main components of natural gas (methane, nitrogen, carbon dioxide, and ethane) must be considered. This work is devoted to the mutual influence of CH4–N2, CH4–CO2, and CH4–C2H6 on their characteristic Raman bands in the range of 300–2500 cm−1. The half-width and asymmetry of the Q branches of N2, CO2, and C2H6 as a function of methane concentration were obtained in the range of 1–50 bar. The averaged broadening coefficients of the rotational-vibrational lines of the ν2 band of CH4 perturbed by N2, CO2, and C2H6 are measured. A high-sensitivity spectrometer with a resolution of 0.5 cm−1 based on spontaneous Raman scattering was used to obtain reliable results. The algorithm and all the necessary parameters for simulating the effect of various molecular environments on the Raman bands of the main components of natural gas are presented.

Monitoring Method of Non-Gaussian Process Based on Fractal Analysis With Kernel Independent Component Regression

Process monitoring is very important for the safety of industrial production processes. The traditional monitoring method based on independent component analysis has the disadvantages as follows. (1) The importance ordering problem of independent components has not been solved; (2) The dynamic problem is not considered. To address these issues, a fractal dimension-based dynamic kernel independent components regression (FD-KICR) method is proposed. The contributions of the proposed method are as follows: (1) The intrinsic dimension of the data is calculated through the improved fractal dimension, and then the number of selected nonlinear ICs (nICs) is determined; (2) The time lags are computed with fractal dimension to effectively describe the dynamic structure of data; (3) By correlating temperature with independent components selection and indirectly monitoring temperature changes through bands of independent components, this method can effectively monitor the safety of the production process. This proposed method is applied to the electrical fused magnesia furnace (EFMF). The experience results show the effectiveness of this method.

Characterization of freeze-dried oxidized human red blood cells for pre-transfusion testing by synchrotron FTIR microspectroscopy live-cell analysis.

Oxidative treatment of human red blood cells (RBCs) prior to freeze-drying appears to stabilize the RBCs to withstand dried storage at room temperature. To better understand the effects of oxidation and freeze-drying/rehydration on RBC lipids and proteins, single-cell measurements were performed by synchrotron-based Fourier transform infrared (FTIR) microspectroscopy 'live-cell' (unfixed) analysis. Lipid and protein spectral data of tert-butyl hydroperoxide (TBHP)-oxidized RBCs (oxRBCs), FDoxRBCs and control (untreated) RBCs were compared using principal component analysis (PCA) and band integration ratios. The oxRBCs and FDoxRBCs samples had similar spectral profiles that were clearly different to control RBCs. Spectral changes in the CH stretching region of oxRBCs and FDoxRBCs indicated the presence of increased saturated and shorter-chain lipids, consistent with lipid peroxidation and stiffening of the RBC membrane compared to control RBCs. The PCA loadings plot for the fingerprint region of control RBCs corresponding to the α-helical structure of hemoglobin, shows that oxRBCs and FDoxRBCs have conformational changes in the protein secondary structure to β-pleated sheets and β-turns. Finally, the freeze-drying process did not appear to compound or induce additional changes. In this context, FDoxRBCs could become a stable source of reagent RBCs for pre-transfusion blood serology testing. The synchrotron FTIR microspectroscopic live-cell protocol provides a powerful analytical tool to characterize and contrast the effects of different treatments on RBC chemical composition at the single cell level.

Paper] Study on Single Frequency Downlink with Coupling Loop Interference Canceller for Professional SC-FDE Wireless Camera using Millimeter-wave Band

Professional wireless cameras using the millimeter-wave band can transmit more information than those in the UHF band, making this band especially useful for transmitting high-quality video and audio with low latency. Although such devices have been put into practical use, there is a need to downsize the equipment on the camera side to reduce expensive millimeter-wave band components and improve operability. In this study, we configure the downlink of a professional wireless camera for UHDTV as a single frequency network (SFN) and study the expansion of coverage provided by a booster. A coupling loop interference canceller and multi-path equalizer are installed in the booster. A computer simulation shows that the booster works well. SFN interference, in which the master and booster waves multiply propagate, can be equalized through frequency domain equalization (FDE) of the single-carrier (SC) system at the receiver side.

Disentangling the Frequency Content in Optoacoustics.

Signals acquired by optoacoustic tomography systems have broadband frequency content that encodes information about structures on different physical scales. Concurrent processing and rendering of such broadband signals may result in images with poor contrast and fidelity due to a bias towards low frequency contributions from larger structures. This problem cannot be addressed by filtering different frequency bands and reconstructing them individually, as this procedure leads to artefacts due to its incompatibility with the entangled frequency content of signals generated by structures of different sizes. Here we introduce frequency-band model-based (fbMB) reconstruction to separate frequency-band-specific optoacoustic image components during image formation, thereby enabling structures of all sizes to be rendered with high fidelity. In order to disentangle the overlapping frequency content of image components, fbMB uses soft priors to achieve an optimal trade-off between localization of the components in frequency bands and their structural integrity. We demonstrate that fbMB produces optoacoustic images with improved contrast and fidelity, which reveal anatomical structures in in vivo images of mice in unprecedented detail. These enhancements further improve the accuracy of spectral unmixing in small vasculature. By offering a precise treatment of the frequency components of optoacoustic signals, fbMB improves the quality, accuracy, and quantification of optoacoustic images and provides a method of choice for optoacoustic reconstructions.

Influence of Hot Band Annealing on Cold-Rolled Microstructure and Recrystallization in AA 6016

The influence of an intermediate heat treatment at the end of hot rolling and before cold rolling on Cube texture formation during the final solution annealing of AA 6016 is investigated. Three hot bands with different initial grain sizes and textures are considered: the first one without annealing before cold rolling, while the other two hot bands are heat treated at 540 °C for 1 hour in air before being cold rolled. One of the heat-treated hot bands was left to cool down in air and the other inside the furnace. Electron-backscatter diffraction (EBSD) maps of the cold-rolled specimens and crystal plasticity simulations show no difference in the amount of Cube remaining in the microstructure at the end of cold rolling for all three specimens. The initial grain size of the hot band has no influence on the Cube texture fraction left in the microstructure at the end of cold rolling for thickness reductions higher than 65 pct. Nevertheless, the grain size of the hot band affects the shape and distribution of the Cube grains left in the microstructure and the kernel average misorientation in the cold-rolled specimens. Moreover, the heat treatment decreases the intensity of the beta fiber components (Brass, Copper, and S) in the hot band and promotes the formation of a cold-rolled microstructure with a low kernel average misorientation. Both these factors lower the probability of preferential Cube nucleation during solution annealing and keep the Cube volume fraction after recrystallization below 10 pct, while it reaches 25 pct without intermediate annealing.

A reliable method of wind power fluctuation smoothing strategy based on multidimensional non‐linear exponential smoothing short‐term forecasting

This paper investigates the multi-dimensional non-linear exponential smoothing prediction method under different weight coefficients, so as to realize the short-term prediction of the original wind power output. Based on the current research on wind power fluctuation prediction, this paper firstly proposes a new multi-dimensional nonlinear exponential smoothing prediction method. Based on different weight coefficients, the corresponding short-term forecast volatility is obtained. Then, the wavelet packet decomposition method is used to further realize the secondary smoothing of the prediction wind power fluctuations. Hybrid energy storage system (HESS) plays an important role in wind power fluctuation suppression from different frequency bands. However, the traditional fixed frequency power allocation method significantly degrades the performance of the accuracy of the algorithm. Therefore, this paper proposes a frequency conversion entropy strategy, which combines energy value with wavelet packet decomposition. By calculating the energy components of different frequency bands, the fluctuation can be divided effectively. Finally, simulation and experiment discussions show that the proposed algorithm in this paper can realize the power allocation effectively compared to the traditional one. And it further verifies the feasibility and reliability of the strategy proposed in this work.

A potential absorber for PHz electronics using Sn/h-BN Van der Waals structure: A hybrid DFT and macroscopic investigations

The rapid rollout of the next-generation network has sparked discussion about an entirely new set of optical techniques. To prepare the path for future wireless network growth, we must investigate the PHz band’s potential for supporting infrastructures. Engineered materials might play a perceptible role in designing such critical PHz band components. This work demonstrates an efficient Stanene/hexagonal- Boron Nitride heterostructure-based metasurface absorber for the PHz regime. An ab-initio computational approach has been employed to estimate the optical and electronic behavior of Sn/h-BN heterostructure . A high absorption coefficient and excellent optical characteristics are obtained by the proposed metasurface absorber based on Sn/h-BN Van der Waals (vdW) structure. The absorption of PHz waves by a metasurface comprising a bi-periodic array of meta-atoms on top of a dielectric substrate backed by gold is simulated using CST Microwave Studio™. By utilizing the Finite Integral Techniques (FIT), a high absorptance (around 0.98) is achieved over a 0.45 PHz wide spectral regime for normal incidence, regardless of the polarization states. • A Sn/h-BN Van der Waals structure has been investigated for device application. • A hybrid DFT and macroscopic approach is used to design an optical absorber. • High absorption coefficient and anisotropic properties are exhibited by the investigated materials. • A high absorptance (around 98%), were achieved over a 0.45 PHz wide spectral regime for normal incidence.

A novel blood glucose time series prediction framework based on a novel signal decomposition method

Unstable blood glucose levels will bring about a series of complications, and even threaten our life in severe cases. Therefore, accurately predicting and controlling blood glucose has become an indispensable part of diabetes treatment. For the sake of boosting the accuracy of blood glucose prediction, a novel time-frequency signal analytical technology called improved ensemble empirical mode decomposition based on fractal dimension (FEEMD) is first proposed to decompose the nonlinear and non-stationary raw blood glucose series to obtain intrinsic mode functions (IMFs) and residual components (Rs) in different frequency bands. Then, in order to overcome the problem that the kernel extreme learning machine (KELM) is easy to fall into the local optimum, the sparrow search algorithm (SSA) is introduced to further enhance the robustness and stability of KELM model. Ultimately, the predictions of each optimized KELM are fused to achieve the final prognostic results. Through the experimental results of three patients, the following contributions can be summarized: (a) FEEMD exploits the box-counting dimension to remove abnormal signals in the original sequence, which guarantees the completeness of decomposition and obtains better decomposition results; (b) SSA is exploited to optimize the KELM, which can significantly boost the prediction effects; (c) When compared with the other seven benchmark models, the proposed framework in this paper is more suitable for predicting blood glucose and has higher prediction accuracy; (d) This paper also verifies that the proposed architecture can effectively reduce the false negative rate and increase the overall alarming accuracy in early warning of hypoglycemia.

Roll Eccentricity Signal Detection and Its Engineering Application Based on SFFT-IAA

The roll eccentricity signal is a weak and complex periodic signal that is difficult to be identified. To improve the detection accuracy of the roll eccentricity signal and to compensate effectively, this study proposed a roll eccentricity signal detection method by combining the sparse fast Fourier transform (SFFT) and the iterative adaptive approach (IAA). The proposed method can rapidly determine the frequency range of the roll eccentricity signal by using the SFFT. Then, it divides the frequency range into several small frequency bands. In each small frequency band, the frequency, amplitude, and phase angle of each harmonic component of the roll eccentricity signal were estimated by using IAA. The simulation results show that the proposed method can find all frequency components, and the frequency estimation accuracy is higher than 99.88%. Finally, the engineering application of this method and the eccentricity compensation control were investigated. In engineering applications, the proposed method can reduce the thickness fluctuation of the finished strip by 89.2%, and the product quality is improved significantly. The simulation results and engineering experiments show that the proposed method has an excellent effect on detecting and compensating roll eccentricity signals.