Spectral Content Research Articles

F-UNet++: Remote Sensing Image Fusion Based on Multipurpose Adaptive Shuffle Attention and Composite Multi-Input Reconstruction Network

The fusion of multispectral (MS) and panchromatic (PAN) images is of great significance for the construction of high-resolution remote sensing images. Because of differences in sensors, no single MS or PAN image can express the complete information of a scene. Therefore, it is a key issue to fuse MS images containing rich spectral content and PAN images with spatial information to construct a high-resolution MS image. In this work, an adaptive shuffle attention (ASA) module and an optimized UNet++ are combined in a fusion-UNet++ (F-UNet++) framework for the problem of MS and PAN image fusion. This ASA module can focus on important information in the mixed domain and adjust the dimensions of tensors. F-UNet++ includes a multiscale feature extraction module, multiscale feature fusion module, and image reconstruction module. The multiscale feature extraction module obtains spectral and spatial information, the multiscale feature fusion module fuses spectral and spatial information, and a composite multi-input image reconstruction module (CMI-UNet++) reconstructs the final image. By combining the ASA attention module, the loss of feature information can be reduced to enhance the fidelity of the spectral and spatial information of the fused image. Experiments show that F-UNet++ is qualitatively and quantitatively superior to current image fusion methods. (The code is available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/Josephing/F-UNet</uri> ).

Improving Spectral Responsivity Measurements by Correcting for Filter Bandwidth

Spectral responsivity (SR) measurements are key in characterizing photovoltaic (PV) devices and calculating spectral mismatch correction factors (MMF). SR is measured using different wavelengths of monochromatic light. In practical measurement systems, this light has a finite bandwidth, meaning that it is only quasi-monochromatic. The data analysis, however, typically assumes perfectly monochromatic light. The accuracy of the calculated SR then depends not only on the actual bandwidth of the monochromatic light used during the measurement but also on the intensity distribution inside the bandwidth. In our SR measurement system, we use quasi-monochromatic light obtained from a solar simulator and a range of bandpass filters. First, we measured and analyzed the spectral content of light transmitted for each filter. Then, we developed an iterative correction scheme for the measured SR. This numerical approach assumes no previous knowledge about the SR of the device under test (DUT). Applying this scheme for bandwidth correction to a range of PV cells with varying SR curves, we found that the corrections for most wavelengths are of minor importance. However, for those wavelengths where the shape of the SR curve of the reference device and DUT differ notably, the corrections are significant up to 20% and higher. We investigated the change in the spectral MMF, which was found to be negligible in most cases but not always. Therefore, the bandwidth correction is mainly important not only for improving SR measurements of PV devices but also relevant for the determination of spectral mismatch factors.

Characterization of shock-induced panel flutter with simultaneous use of DIC and PIV

In this experimental study, panel flutter induced by an impinging oblique shockwave is investigated at a freestream Mach number of 2, using the combination of planar particle image velocimetry (PIV) and stereographic digital image correlation (DIC) to obtain simultaneous full-field structural displacement and flow velocity measurements. High-speed cameras are employed to obtain a time-resolved description of the panel motion and the shockwave-boundary layer interaction (SWBLI). In order to prevent interference between the PIV and DIC systems, an optical isolation is implemented using fluorescent paint, dedicated light sources, and camera lens filters. The effect of the panel motion on the SWBLI behavior is assessed, by comparing it with the SWBLI on a rigid wall. The results show that panel oscillations occur with a maximum amplitude of ten times the panel thickness. The dominant frequencies observed in the panel oscillation (424 Hz and 1354 Hz) match the main spectral content of the reflected shockwave position. A further POD analysis of the panel displacement spatial distribution shows that these two frequency contributions are well captured by the first two POD modes, which correspond, respectively, to a first and a third bending mode shape and account for 92% of the total oscillation energy. The fluid-structure coupling is studied by identifying, in the flow, the regions of maximum correlation between the panel displacement and the flow velocity fluctuations. The results obtained prove that the inviscid flow region upstream of the SWBLI is perfectly in phase with the panel oscillation, while the downstream region has a delay of one quarter of the flutter cycle.

Effect of pre-analytical variables on Raman and FTIR spectral content of lymphocytes.

The use of Fourier transform infrared (FTIR) and Raman spectroscopy (RS) for the analysis of lymphocytes in clinical applications is increasing in the field of biomedicine. The pre-analytical phase, which is the most vulnerable stage of the testing process, is where most errors and sample variance occur; however, it is unclear how pre-analytical variables affect the FTIR and Raman spectra of lymphocytes. In this study, we evaluated how pre-analytical procedures undertaken before spectroscopic analysis influence the spectral integrity of lymphocytes purified from the peripheral blood of male volunteers (n = 3). Pre-analytical variables investigated were associated with (i) sample preparation, (blood collection systems, anticoagulant, needle gauges), (ii) sample storage (fresh or frozen), and (iii) sample processing (inter-operator variability, time to lymphocyte isolation). Although many of these procedural pre-analytical variables did not alter the spectral signature of the lymphocytes, evidence of spectral effects due to the freeze-thaw cycle, in vitro culture inter-operator variability and the time to lymphocyte isolation was observed. Although FTIR and RS possess clinical potential, their translation into a clinical environment is impeded by a lack of standardisation and harmonisation of protocols related to the preparation, storage, and processing of samples, which hinders uniform, accurate, and reproducible analysis. Therefore, further development of protocols is required to successfully integrate these techniques into current clinical workflows.

Cerebrovascular Impedance as a Function of Cerebral Perfusion Pressure.

Goal: Cerebrovascular impedance is modulated by a vasoactive autoregulative mechanism in response to changes in cerebral perfusion pressure. Characterization of impedance and the limits of autoregulation are important biomarkers of cerebral health. We developed a method to quantify impedance based on the spectral content of cerebral blood flow and volume at the cardiac frequency, measured with diffuse optical methods. Methods: In three non-human primates, we modulated cerebral perfusion pressure beyond the limits of autoregulation. Cerebral blood flow and volume were measured with diffuse correlation spectroscopy and near-infrared spectroscopy, respectively. Results: We show that impedance can be used to identify the lower and upper limits of autoregulation. Conclusions: This impedance method may be an alternative method to measure autoregulation and a way of assessing cerebral health non-invasively at the clinical bedside.

Stimulus Design for Visual Evoked Potential Based Brain-Computer Interfaces.

Visual stimuli design plays an important role in brain-computer interfaces (BCIs) based on visual evoked potentials (VEPs). Variations in stimulus parameters have been shown to affect both decoding accuracy and subjective perception experience, implying the need for a trade-off in design. In this study, we comprehensively and systematically compared various combinations of amplitude contrast and spectral content parameters in the stimulus design to quantify their impact on decoding performance and subject comfort. Specifically, three parameters were investigated: 1) contrast level, 2) temporal pattern (periodic steady-state or pseudo-random code-modulated), and 3) frequency range. We collected electroencephalogram (EEG) data and subjective perception ratings from ten subjects and evaluated the decoding accuracy and subject comfort rating for different combinations of the stimulus parameters. Our results indicate that while high-frequency steady-state VEP (SSVEP) stimuli were rated the most comfortable, they also had the lowest decoding accuracy. Conversely, low-frequency SSVEP stimuli were rated the least comfortable but had the highest decoding accuracy. Standard and high-frequency M-sequence code-modulated VEPs (c-VEPs) produced intermediates between the two. We observed a consistent trade-off relationship between decoding accuracy and subjective comfort level across all parameters. Based on our findings, we offer c-VEP as a preferable stimulus for achieving reliable decoding accuracy while maintaining a reasonable level of comfortability.

Evaluation of Bone Conduction and Active-Noise-Cancellation Headsets Based on Listening Tests in a Virtual Environment

Alternative design headsets incorporating activenoise-cancellation or bone conduction were evaluated in listening tests in a virtual reality environment. Virtual sound sources in the horizontal plane had to be identified using stereo panning in the frontal hemisphere. In addition, transfer characteristics and damping effects were measured with a dummy-head. Results indicate that up to five source locations can be used in real applications with high accuracy in virtual scenarios, independent of the spectral content of the excitation signals. Furthermore, the use of noise cancellation in presence of 80 dB background noise does not improve performance. Commercially available bone conduction headsets can provide the same detection accuracy even if the subjective sound quality is lower.

Dynamics of cavity structures and wall-pressure fluctuations associated with shedding mechanism in unsteady sheet/cloud cavitating flows

The physics and mechanism of sheet/cloud cavitation in a convergent–divergent channel are investigated using synchronized dynamic surface pressure measurement and high-speed imaging in a water tunnel to probe the cavity shedding mechanism. Experiments are conducted at a fixed Reynolds number ofRe = 7.8 × 105for different values of the cavitation numberσbetween 1.20 and 0.65, ranging from intermittent inception cavitation, sheet cavitation to quasi-periodic cloud cavitation. Two distinct cloud cavitation regimes, i.e. the re-entrant jet and shockwave shedding mechanism, are observed, accompanied by complex flow phenomenon and dynamics, and are examined in detail. An increase in pressure fluctuation intensity at the numbers 3 and 4 transducer locations are captured during the transition from re-entrant jet to shockwave shedding mechanism. The spectral content analysis shows that, in cloud cavitation, several frequency peaks are identified with the dominant frequency caused by the large-scale cavity shedding process and the secondary frequency related to re-entrant jet/shockwave dynamics. Statistical analysis based on defined grey level profiles reveals that, in cloud cavitation, the double-peak behaviours of the probability density functions with negative skewness values are found to be owing to the interactions of the re-entrant jet/shockwave with cavities in the region of 0.25 ~ 0.65 mean cavity length (Lc). In addition, multi-scale proper orthogonal decomposition analysis with an emphasis on the flow structures in the region of 0.25 ~ 0.65Lcreveals that, under the shockwave shedding mechanism, both the re-entrant jet and shockwave are captured and their interactions are responsible for the dynamics and statistics of cloud shedding process.

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer’s Disease continuum?

Alzheimer’s disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by mild cognitive impairment (MCI), the initial stage of clinical cognitive decline. However, the neural correlates of these prodromic stages are not completely clear yet. Recent studies suggest that EEG analysis tools characterizing the cortical activity as a whole, such as microstates and cortical regions connectivity, might support a characterization of SCD and MCI conditions. Here we test this approach by performing a broad set of analyses to identify the prominent EEG markers differentiating SCD (n = 57), MCI (n = 46) and healthy control subjects (HC, n = 19). We found that the salient differences were in the temporal structure of the microstates patterns, with MCI being associated with less complex sequences due to the altered transition probability, frequency and duration of canonic microstate C. Spectral content of EEG, network connectivity, and spatial arrangement of microstates were instead largely similar in the three groups. Interestingly, comparing properties of EEG microstates in different cerebrospinal fluid (CSF) biomarkers profiles, we found that canonic microstate C displayed significant differences in topography in AD-like profile. These results show that the progression of dementia might be associated with a degradation of the cortical organization captured by microstates analysis, and that this leads to altered transitions between cortical states. Overall, our approach paves the way for the use of non-invasive EEG recordings in the identification of possible biomarkers of progression to AD from its prodromal states.

Solar Panel Automated Cleaning Using Water Re-Capture and Re-Circulation System

Abstract: Sun photovoltaic (SPV) module energy output is closely correlated with solar accessible irradiance, spectral content, and other factors including environmental and climatic factors. It is normal for dust from the outside environment to collect on solar photovoltaic (PV) system panels. Physical factors like rain, dirt, dust, snow, etc. can lower a solar panel's overall efficiency. So maintaining a clean solar panel is crucial. The performance of solar panels can be negatively impacted by collected dust, according to research, however, the results were not measured. This study's goal was to investigate how dust build-up affects the efficiency of solar PV panels. To test the electrical output and efficiency of solar panels, experiments were carried out utilizing dust particles on solar panels with a constant-power light source. The efficiency and resultant electrical power generated revealed it. According to the study, the effectiveness of a photovoltaic solar panel might be reduced by up to 30% by dust build-up on its surface. Therefore, it is crucial to clean the solar panel of any dust. We may clean the solar panels and improve their effectiveness by using the wiper on the water pump's base.

Unsteady RANS-based DMD analysis of airfoil NACA0015 with Gurney flap

The present investigation summarizes the numerical prediction and DMD analysis of the flow in the vicinity of a Gurney flap set on an airfoil NACA0015 at Re = 10,300 tested in a water tunnel with time-resolved Particle Image Velocimetry. A series of two-dimensional U-RANS simulations has been accomplished using an incompressible, time-accurate solver of OpenFOAM. A purely data-based DMD analysis has followed to extract the spatio-temporal coherent structures from the time-evolving flowfields, to mimic the experiments. It is stressed that this work focuses on the analysis of this kind of flap by applying DMD to datasets generated with numerical simulations, which has not been previously investigated, but using experimental datasets. Under this approach, the comparison of the numerics with the experimental counterpart shows a remarkable agreement for both the structures and major frequencies, which stresses the suitability of the incompresible U-RANS approach in this class of studies. Special attention has been focused on the modelling of the experimental facility, and a quantification of the prediction accuracy is provided by assessing the deviation of the spectral content. The simulations clearly show the key role of having a good characterization of the water tunnel to be successful at capturing the spectrum and flow unsteadiness. Furthermore, they reveal quite promising for those industrial oriented simulations, which deal with lift-enhancement devices and lift-to-drag ratio optimization of airfoils since they permit an accurate prediction.

A Scalable Systolic Accelerator for Estimation of the Spectral Correlation Density Function and Its FPGA Implementation

The spectral correlation density (SCD) function is the time-averaged correlation of two spectral components used for analyzing periodic signals with time-varying spectral content. Although the analysis is extremely powerful, it has not been widely adopted in real-time applications due to its high computational complexity. In this article, we present an efficient FPGA implementation of the FFT accumulation method (FAM) for estimating the SCD function and its alpha profile. The implementation uses a linear systolic array with a bi-directional datapath consisting of DSP-based processing elements (PEs) with a dedicated instruction schedule, achieving a PE utilization of 88.2%. The 128-PE implementation achieves a clock frequency in excess of 530 MHz and consumes 151K LUTs, 151K FFs, 264 BRAMs, 4 URAMs, and 1,054 DSPs, which is less than 36% of the logic fabric on a Zynq UltraScale+ XCZU28DR-2FFVG1517E RFSoC device. It has a modest 12.5W power consumption and an energy efficiency of 4,832 MOPS/W, which is 20.6× better than the published state-of-the-art GPU implementation. In terms of throughput, it achieves 15,340 windows/s (15,340 windows/s × 2,048 samples/window = 31.4 MS/s), which is a 4.65× improvement compared to the above-mentioned GPU implementation and 807× compared to an existing hybrid FPGA-GPU implementation.

Optimization of Dominant Frequency and Bandwidth Analysis in Multi-Frequency 3D GPR Signals to Identify Contaminated Areas.

Ground-penetrating radar (GPR) has been widely used in investigations of contaminated areas because of its sensitivity to variations associated with the nature of pore fluids. However, most of the studies were usually based on the visual interpretation of radargrams or on a time domain amplitude analysis. In this work, we propose a methodology that consists of analyzing the spectral content of the signal recorded in multi-frequency 3D GPR profiles. A remarkable advantage of this type of antenna is its step-frequency system, which provides a much wider emission spectrum than the one corresponding to conventional single-frequency antennas. From the data in the frequency domain, the dominant frequency and bandwidth were calculated as parameters whose variation could be related to the presence of light non-aqueous phase liquid (LNAPL) in the subsurface. By analyzing the variations of these two parameters simultaneously, we were able to delimit the contaminated zones in a case study, associating them with a significant shift of the frequency spectrum with respect to the average of the study area. Finally, as a validation method of the proposed methodology, the results of the frequency analysis were compared with resistivity data obtained with an electromagnetic conductivity meter, showing a very good correlation between the results.

Tuning defect-related optical bands by channeling implants in semiconductors

Ion implantation is an excellent method to introduce defects into semiconductors, extending their functionalities in a controllable way. Herein, we investigated an option to use crystallographically aligned implants as an additional route to control the balance between optically active defects, selecting ZnO as a test material. The optical data were correlated with the structural analysis confirming the formation of different dominating crystalline defects in samples implanted along and off [0001] direction. Specifically, we demonstrated that different proportions in the contents of the extended and point defects in the initial as-implanted states of these samples, lead to prominent variations in the defect-related luminescence upon annealing. As such, we conclude that channeling implants may have an added value in the functionalization of defects in semiconductors, e.g. to tune specific spectral contents in the defect-related emission bands.

Dynamic Sensitivities to Fractal Machine Noises in a Mechanical Face Seal

Abstract Mechanical face seals are wide spread in many applications of powered equipment and turbomachinery. Often machine vibration and noise are unavoidable because of changing conditions which can be persistent and forceful. In critical applications when seals fail, they may have significant or even catastrophic consequences. To ensure the safety of such machinery and its associated mechanical components, machine vibration and noise must be diagnosed and quantified to keep the system’s response within certain limits. This work focuses on the dynamics of a flexibly mounted stator mechanical face seal that is subjected to combinations of broad-band noisy vibrations of the shaft and the housing. In all previous work, the positions of the housing and the shaft have been considered fixed. The current work relaxes that condition, augmenting the equations of motion to incorporate equipment’s noisy vibrations. Noises are expediently produced by the Weierstrass–Mandelbrot (WM) fractal function. A numerical simulation ensues, and the time-domain responses are subject to spectral analyses. Results show that under some design conditions, the seal is largely insensitive to machine vibrations. However, under other conditions, the seal response to exterior machine noise exhibits a rich spectral content that stems from various transient phenomena that include intensified half-frequency whirl, near synchronous response at steady-state, and super-synchronous higher harmonic oscillations caused by face contact.

Direct spectral measurements of midinfrared radiation from a laser wakefield accelerator

The formation of plasma waves during laser wakefield acceleration (LWFA) produces time-dependent frequency shifts in the driving laser pulse, extending its spectral content to the infrared. We present direct spectral measurements of multi-mJ infrared pulses from an LWFA. Experimental beam profile measurements and three-dimensional particle-in-cell simulations suggest high focusability of these pulses. Particle-in-cell simulations demonstrate that the measurement of side-scattered infrared radiation may serve as a diagnostic of plasma waves and the efficiency of spectral broadening during LWFA.

Investigations concerning the Flow Stabilization of Backward Curved Centrifugal Impellers at Low Flow Rate

For a backward curved centrifugal fan, reducing volume flow rate from design operating point towards part load yields an increase in noise emission together with a reduction of efficiency. The spectral content of the emerging noise emission can be characterized by a subharmonic hump with several harmonics. Based on narrow-band acoustic measurements and numerical Lattice-Boltzmann simulations, a deeper insight is sought after. Downstream unsteady flow patterns are identified to play a central role in this performance deterioration; and geometrical flow stabilization means are investigated.

The Observations of the 2022 Tonga-Hunga Tsunami Waves in the Sea of Japan

On 15 January 2022, the Tonga-Hunga submarine volcano erupted in the southwest Pacific Ocean and created strong tsunami waves that had a dual generation mechanism: “direct” (caused by the explosion) and “atmospheric” (induced by propagating atmospheric Lamb waves). Trans-oceanic waves spread across the ocean and were clearly recorded in marginal seas of the northwestern Pacific, including the Sea of Japan. The two distinct types of incoming waves produced a variety of effects in the sea as determined by the wave origin, propagation features and local topographic properties. Statistical and spectral properties of the tsunami waves recorded in the Sea of Japan and vicinity, including the adjacent part of the northwestern Pacific, are the main subject of the present study. The Sea of Japan is a semi-isolated basin connected to the Pacific Ocean through several straits. The features of these straits (widths, depths, and geometry) significantly affected the arriving waves, strongly modifying their statistical characteristics and spectral content. As discussed in detail in this paper, the two types of incoming tsunami waves are consequently transformed in substantially different ways.

Data reduction and restoration of spectropolarimetric microlensed hyperspectral imager data

Context. A microlensed hyperspectral imager (MiHI) is an integral field spectrograph based on a double-sided microlens array.Aims. To convert the raw data frames of such an instrument to hyperspectral cubes, and restore them to high-resolution science-ready Stokes data, a new kind of data reduction procedure is required.Methods. An optimized ad hoc transfer map of a MiHI prototype was used to convert the raw data into raw hyperspectral form. The transfer map was modified to match the position of the image on the detector, which was found to drift considerably during the course of an observing day. The determination of this position was used to move the recorded flat-field images to the position of the observation, which was found to be a critical step in the accurate gain correction of the raw data cubes. The converted data were found to be suitable for image restoration but still contained unwanted polarimetric structure that needed to be removed.Results. The extracted and restored data were found to be of a similar spatial resolution as the equivalent data from the context imager, while retaining a spectral resolution of approximately 300 000. The noise properties of the raw data were determined by the photon statistics and were found to be consistent with the estimated transparency of the instrument and the integration time of the image sensor. As for all image-restored data, the noise properties of the restored data were found to be dependent on the instrumental and atmospheric point spread function. An attempt to compare the data to other similar data suggested that the data had a spectral and spatial information content comparable to that of a Hinode spectro-polarimetric scan, but with a higher spatial resolution and a temporal cadence of approximately 10s.

Spectral Content of Acoustic Signals of Artificial Sandstone Samples under Uniaxial Loading

Spectral Content of Acoustic Signals of Artificial Sandstone Samples under Uniaxial Loading