Conventional Spectral Analysis Research Articles

Snapshot transient absorption spectroscopy: toward in vivo investigations of nonphotochemical quenching mechanisms

Although the importance of nonphotochemical quenching (NPQ) on photosynthetic biomass production and crop yields is well established, the in vivo operation of the individual mechanisms contributing to overall NPQ is still a matter of controversy. In order to investigate the timescale and activation dynamics of specific quenching mechanisms, we have developed a technique called snapshot transient absorption (TA) spectroscopy, which can monitor molecular species involved in the quenching response with a time resolution of 30s. Using intact thylakoid membrane samples, we show how conventional TA kinetic and spectral analyses enable the determination of the appropriate wavelength and time delay for snapshot TA experiments. As an example, we show how the chlorophyll-carotenoid charge transfer and excitation energy transfer mechanisms can be monitored based on signals corresponding to the carotenoid (Car) radical cation and Car S1 excited state absorption, respectively. The use of snapshot TA spectroscopy together with the previously reported fluorescence lifetime snapshot technique (Sylak-Glassman et al. in Photosynth Res 127:69-76, 2016) provides valuable information such as the concurrent appearance of specific quenching species and overall quenching of excited Chl. Furthermore, we show that the snapshot TA technique can be successfully applied to completely intact photosynthetic organisms such as live cells of Nannochloropsis. This demonstrates that the snapshot TA technique is a valuable method for tracking the dynamics of intact samples that evolve over time, such as the photosynthetic system in response to high-light exposure.

Vibration-based breathing crack identification using non-linear intermodulation components under noisy environment

Structural damages can result in non-linear dynamical signatures such as lower and higher order harmonics and signal modulation that can significantly enhance their detection. The conventional spectral analysis is used in most existing vibration-based damage diagnostic techniques to extract these damage-sensitive non-linear features. However, the major limitation of using spectral analysis is that the amplitudes of non-linear harmonics are highly sensitive to measurement noise and may mislead the damage diagnostic process. Keeping this in view, we present a new reference-free damage diagnostic technique for fatigue-breathing crack detection, localization and characterization using the cyclic spectral analysis-based technique. A new damage index based on spectral correlation exploiting the non-linear intermodulation in the response is proposed. The proposed cyclic spectral analysis-based diagnostics are highly immune to the measurement noise. Numerical and experimental simulation studies have been carried out by considering a beam with single and multiple breathing cracks, to test and verify the robustness and effectiveness of the proposed technique.

Linear viscoelastic characterisation of bituminous mixtures using random stress excitations

The three-dimensional linear viscoelastic characterisation of bituminous mixtures can be performed with the concurrent measurement of the complex Young's modulus and the complex Poisson's ratio. This normally requires the application of sinusoidal excitations leading to small strain amplitudes. Since in the linear domain the effects of sinusoidal excitations are independent of each other, the material behaviour can also be obtained using a broad-band multi-frequency excitation. In this study, the complex Young's modulus and Poisson's ratio of a bituminous mixture was obtained by applying a random wave axial stress to cylindrical specimens and measuring their strain response in the axial and transverse direction. The frequency response functions representing the Young's modulus and Poisson's ratio were calculated using a conventional spectral analysis approach. Sinusoidal tests at different strain levels were also carried out as a reference. Applying random waves at 10, 20 and 30°C provided results with a high signal-to-noise ratio at frequencies between 0.1 Hz and 40 Hz for the Young's modulus and between 1 and 90 Hz for Poisson's ratio. For both functions the results validate the time-temperature superposition principle. The direct comparison with the results of sinusoidal testing confirms the accuracy of the frequency response functions measured with the random wave approach and shows their potential for estimating the viscoelastic response of bituminous mixtures at infinitesimal strain level.

The structure of turbulent flow through submerged flexible vegetation

The hydrodynamics of turbulent flow through submerged flexible vegetation is investigated in a flume using acoustic Doppler velocimetery (ADV) measurements. The flow characteristics such as the energetics and momentum transfer derived from conventional spectral and quadrant analyses are considered as the flow encounters a finite vegetation patch. Consistent with numerous canopy flow experiments, a shear layer and coherent vortex structures near the canopy top emerge caused by Kelvin–Helmholtz instabilities after the flow equilibrates with the vegetated layer. These instabilities are commonly attributed to velocity differences between non-vegetated and vegetated canopy layers in agreement with numerous experiments and simulations conducted on dense rigid canopies. The power-spectral density function for vertical velocity turbulent fluctuations at different downstream positions starting from the edge of the vegetation layer are also computed. For a preset water depth, the dominant dimensionless frequency is found to be surprisingly invariant around 0.027 despite large differences in vegetation densities. The ejection and sweep events significantly contribute to the Reynolds stresses near the top of the vegetation. The momentum flux carried by ejections is larger than its counterpart carried by the sweeps above the canopy top. However, the momentum flux carried by sweeps is larger below the top of the canopy.

Applications of Fractional Lower Order Frequency Spectrum Technologies to Bearing Fault Analysis

The traditional spectral analysis method is used to study the characteristics of bearing fault signals in frequency domain, which is reasonable and effective in general cases. However, it is proved that the fault signals have heavy tails in this paper, which are α stable distribution, and 1 < α < 2, and even the noises belong to α stable distribution. Then the conventional spectral analysis methods degenerate and even fail under α stable distribution environment. Several improved frequency spectral analysis methods are proposed employing fractional lower order covariation or fractional lower order covariance in this paper, including fractional lower order Blackman‐Tukey covariation spectrum (FLOBTCS), fractional lower order periodogram covariation spectrum (FLOPCS), and fractional lower order welch covariation spectrum (FLOWCS). In order to suppress side lobe and improve resolution, we present novel fractional lower order autoregression (FLO‐AR) and fractional lower order autoregressive moving average (FLO‐ARMA) parameter model frequency spectrum methods, and the calculation steps are summarized. The proposed spectrum methods are compared with the existing methods based on second‐order statistics under Gaussian and SαS distribution environments, and the results show that the new algorithms have better performance than the traditional methods. Finally, the improved methods are applied to estimate frequency spectrums of the normal and outer race fault signals, and it is demonstrated that they are effective for fault diagnosis.

Extraction of High-Precision Urban Impervious Surfaces from Sentinel-2 Multispectral Imagery via Modified Linear Spectral Mixture Analysis.

This study explores the performance of Sentinel-2A Multispectral Instrument (MSI) imagery for extracting urban impervious surface using a modified linear spectral mixture analysis (MLSMA) method. Sentinel-2A MSI provided 10 m red, green, blue, and near-infrared spectral bands, and 20 m shortwave infrared spectral bands, which were used to extract impervious surfaces. We aimed to extract urban impervious surfaces at a spatial resolution of 10 m in the main urban area of Guangzhou, China. In MLSMA, a built-up image was first extracted from the normalized difference built-up index (NDBI) using the Otsu’s method; the high-albedo, low-albedo, vegetation, and soil fractions were then estimated using conventional linear spectral mixture analysis (LSMA). The LSMA results were post-processed to extract high-precision impervious surface, vegetation, and soil fractions by integrating the built-up image and the normalized difference vegetation index (NDVI). The performance of MLSMA was evaluated using Landsat 8 Operational Land Imager (OLI) imagery. Experimental results revealed that MLSMA can extract the high-precision impervious surface fraction at 10 m with Sentinel-2A imagery. The 10 m impervious surface map of Sentinel-2A is capable of recovering more detail than the 30 m map of Landsat 8. In the Sentinel-2A impervious surface map, continuous roads and the boundaries of buildings in urban environments were clearly identified.

Cell type discrimination based on image features of molecular component distribution

Machine learning-based cell classifiers use cell images to automate cell-type discrimination, which is increasingly becoming beneficial in biological studies and biomedical applications. Brightfield or fluorescence images are generally employed as the classifier input variables. We propose to use Raman spectral images and a method to extract features from these spatial patterns and explore the value of this information for cell discrimination. Raman images provide information regarding distribution of chemical compounds of the considered biological entity. Since each spectral wavelength can be used to reconstruct the distribution of a given compound, spectral images provide multiple channels of information, each representing a different pattern, in contrast to brightfield and fluorescence images. Using a dataset of single living cells, we demonstrate that the spatial information can be ranked by a Fisher discriminant score, and that the top-ranked features can accurately classify cell types. This method is compared with the conventional Raman spectral analysis. We also propose to combine the information from whole spectral analyses and selected spatial features and show that this yields higher classification accuracy. This method provides the basis for a novel and systematic analysis of cell-type investigation using Raman spectral imaging, which may benefit several studies and biomedical applications.

A coumarin with an unusual structure from Cuphea ignea, its cytotoxicity and antioxidant activities.

Phenolic metabolite profiling using two dimensional paper chromatographic analysis (2 DPC) was used for assaying the complex mixture of phenolics of an aqueous ethanol aerial part extract of Cuphea ignea (Lytheraceae). A coumarin with a rare structure, namely, 7-hydroxy 3-methoxy coumarin 5-O-β-glucopyranoside was isolated from the investigated extract. The structure was elucidated by conventional methods and spectral analysis, including one and two dimensional NMR (1D and 2D NMR), as well as by interpretation of the spectra obtained by high resolution electrospray ionization mass technique (HRESIMS). The rare coumarin significantly inhibited reactive oxygen species production with an ED50 value of 6.31±1.64 μg/ml and 5.78±0.66 μg/ml as determined by the the free radical 2,2-diphenyl-1-picrylhydrazyl (DPPH) and the oxygen radical absorption capacity (ORAC) assay respectively. The isolated coumarin presented a cytotoxic activity assessed by using the neutral red assay (NRU) against lung cancer cell line (H23) with IC50 of 40.38±2.75 μg/ml.

Laser Frequency Analysis Aided by Electronic Frequency Dividers

Conventional laser spectral analysis relies on direct measurement of power spectral density (PSD), which is not able to distinguish certain types of phase and frequency modulations without ambiguity. In this paper, we propose and demonstrate a modified scheme aimed at improving the specificity in laser frequency analysis. Our method is based on PSD measurement of the downshifted laser spectrum in the radio-frequency range but introduces an electronic frequency divider (EFD) prior to the spectrum analyzer. By monitoring the spectral changes caused by the EFD, we show, both theoretically and experimentally, that common scenarios of phase and frequency modulations, such as wideband frequency modulation (FM) and broadband phase modulation, can be differentiated without ambiguity. Moreover, the new method allows for quantitative assessment of wideband FM parameters such as modulation frequency, modulation index, and frequency deviation, which is not possible with any conventional spectral analysis methods. This technique may find potential applications in laser frequency metrology, microwave photonics, optical sensing, and radar/lidar technologies.

Sleep architecture and EEG power spectra in recently detoxified alcohol dependent patients.

Persistent sleep abnormalities during abstinence are a harbinger for relapse in patients with chronic alcohol dependence. The present study aimed to compare polysomnography (PSG) data between 'recently detoxified' patients with chronic alcohol dependence and healthy controls. Both conventional sleep architectural and power spectral analyses were conducted. Twenty subjects in each of the groups were enrolled. A 2 nights' sleep (first-habituation and second-experimental) PSG data was collected. Computer assisted scoring supplemented by manual method using the Rechtschaffen and Kales criteria were used for sleep staging. Twenty eight channels were used for the EEG recording. Spectral power across early NREM (Non-rapid-eye-movement), Slow Wave Sleep and REM was computed using the Welch's averaged periodogram method. Results on conventional sleep staging showed that patients had significantly lesser total sleep time, sleep efficiency and stage shifts and longer sleep onset latency; while duration of each NREM stages were significantly lower, and latency of stage 2 NREM was significantly longer in patients. After controlling for multiple comparisons, spectral power analysis revealed significant differences only during REM sleep and specifically in high frequency (beta and gamma) bands. Stating the mutually complementary role of conventional and spectral analyses of polysomnography EEG data, we conclude that sleep abnormalities are fairly evident in recently detoxified alcohol dependent patients.

Polarimetric Thomson scattering for high Te fusion plasmas

Polarimetric Thomson scattering (TS) is a technique for the analysis of TS spectra in which the electron temperature Te is determined from the depolarization of the scattered radiation, a relativistic effect noticeable only in very hot (Te ⩾ 10 keV) fusion plasmas. It has been proposed as a complementary technique to supplement the conventional spectral analysis in the ITER CPTS (Core Plasma Thomson Scattering) system for measurements in high Te, low ne plasma conditions. In this paper we review the characteristics of the depolarized TS radiation with special emphasis to the conditions of the ITER CPTS system and we describe a possible implementation of this diagnostic method suitable to significantly improve the performances of the conventional TS spectral analysis in the high Te range.

Reduced-order analysis of buffet flow of space launchers

A reduced-order analysis based on optimized dynamic mode decomposition (DMD) is performed on the turbulent wake of a generic axisymmetric space launcher configuration computed via a zonal large-eddy simulation at the free stream Mach number $Ma_{\infty }=0.8$ and the Reynolds number based on the main body diameter $Re_{D}=6\times 10^{5}$ to investigate the buffet phenomenon. The transonic wake is characterized by an unsteady recirculation region occurring around the nozzle due to the separation of the turbulent boundary layer at the main body shoulder and subsequent dynamic interaction of the unstable free-shear layer with the nozzle surface. This results in strongly periodic and antisymmetric wall pressure fluctuations, for which three distinct frequency ranges are identified using conventional spectral analysis, i.e. $Sr_{D}\approx 0.1$, $Sr_{D}\approx 0.2$ and $Sr_{D}\approx 0.35$. For the spatially integrated side (buffet) loads on the nozzle, the second range is found to be energetically most dominant. To clarify the origin of the detected wake dynamics, the underlying spatio-temporal coherent modes are extracted using DMD. Subsequent analysis of the reduced-order modelled flow field based on the identified DMD modes reveals that at $Sr_{D}\approx 0.1$ a longitudinal cross-pumping motion of the separation bubble takes place, caused by a harmonic antisymmetric oscillation of the main recirculation vortex in the streamwise direction. At $Sr_{D}\approx 0.2$, a cross-flapping motion of the shear layer is determined, triggered by antisymmetric vortex shedding which is in phase with the cross-pumping motion such that it occurs at twice the frequency value. The last range of $Sr_{D}\approx 0.35$ is attributed to a swinging motion of the shear layer caused by a higher harmonic of the vortex shedding mode. Conclusively, the controversial aspect of the true three-dimensional shape of the antisymmetric mode at $Sr_{D}\approx 0.2$ that dominates the buffet phenomenon is scrutinized. Inclined elongated closed-loop vortices are identified that are shed in alternating sequence from azimuthally opposite positions in a longitudinal plane of symmetry that changes its momentary orientation irregularly, maintaining an axisymmetric time-averaged field and spatially isotropic buffet loads.

Spectral method for processing signals of a high-accuracy laser radar

A spectral method is proposed to determine the signal frequency and readings of a laser radar with a frequency modulation of the reference channel based on signal preprocessing with a Gaussian window and calculation of its spectral centroid. Numerical simulation and experiments with a frequency modulation band 5–20 MHz wide have shown that this method provides an order of magnitude better accuracy than the conventional spectral analysis methods.

Lqregularization-based unobserved baselines’ data estimation method for tomographic synthetic aperture radar inversion

The elevation image quality of tomographic synthetic aperture radar (TomoSAR) data depends mainly on the elevation aperture size, number of baselines, and baseline distribution. In TomoSAR, due to the restricted number of baselines with irregular distributions, the elevation imaging quality is always unacceptable using the conventional spectral analysis approach. Therefore, for a given limited number of irregular baselines, the completion of data for the unobserved virtual uniform baseline distribution should be addressed to improve the spectral analysis-based TomoSAR reconstruction quality. We propose an Lq(0<q≤1) regularization-based unobserved baselines’ data estimation method for TomoSAR, which uses the geometric imaging relationship between the observed and unobserved baseline distributions. In the proposed method, we first estimate the transformation matrix between the acquisitions and the data of virtual uniform baseline distribution by solving an optimization problem, before calculating the data for virtual baseline distribution based on the acquisitions and the transformation matrix. Finally, the elevation reflectivity function is recovered using the spectral analysis method based on the estimated data. Compared with the reconstructed results only based on the limited irregular acquisitions, the image recovered using the dataset with a virtual uniform baseline distribution can improve the elevation image quality in an efficient manner.

Remote picometer fiber Bragg grating demodulation using a dual-wavelength source.

We report on the self-referenced, intensity-based, remote and passive interrogation of a fiber Bragg grating (FBG) for point sensing, by use of a reconfigurable dual-wavelength source composed of a tunable wavelength and subsequent suppressed-carrier, electro-optic amplitude modulation. The demodulation procedure is based on the measurement of the reflected power at two different wavelengths within the FBG spectral response. The grating was interrogated by use of conventional spectral analysis, and also after 32.9 km of single-mode fiber using a dispersive incoherent optical Fourier-domain reflectometry technique. Both procedures provide picometer resolution in the determination of Bragg wavelength shifts at a comparatively similar scan time (∼1 s) and received power (-16 dBm). The main limitations in each interrogation scheme have been identified. These results show the feasibility of interrogation systems incorporating relatively simple frequency combs at a calibrated, and eventually reconfigurable, wavelength grid with an, at least, similar performance to that of commercial FBG interrogators.

Sensitivity of the Fe Kα Compton shoulder to the geometry and variability of the X-ray illumination of cosmic objects

In an X-ray reflection spectrum, a tail-like spectral feature generated via Compton down-scattering, known as a Compton shoulder (CS), appears at the low-energy side of the iron K$\alpha$ line. Despite its great diagnostic potential, its use as a spectral probe of the reflector has been seriously limited due to observational difficulties and modelling complexities. We revisit the basic nature of the CS by systematic investigation into its dependence on spatial and temporal parameters. The calculations are performed by Monte-Carlo simulations for sphere and slab geometries. The dependence is obtained in a two-dimensional space of column density and metal abundance, demonstrating that the CS solves parameter degeneration between them which was seen in conventional spectral analysis using photoelectric absorption and fluorescence lines. Unlike the iron line, the CS does not suffer from any observational dependence on the spectral hardness. The CS profile is highly dependent on the inclination angle of the slab geometry unless the slab is Compton-thick, and the time evolution of the CS is shown to be useful to constrain temporal information on the source if the intrinsic radiation is variable. We also discuss how atomic binding of the scattering electrons in cold matter blurs the CS profile, finding that the effect is practically similar to thermal broadening in a plasma with a moderate temperature of $\sim$5 eV. Spectral diagnostics using the CS is demonstrated with grating data of X-ray binary GX 301$-$2, and will be available in future with high-resolution spectra of active galactic nuclei obtained by microcalorimeters.

Influence of inverse spin Hall effect in spin-torque ferromagnetic resonance measurements

We have performed spectral analyses of spin-torque ferromagnetic resonance (ST-FMR) signals in both Ni80Fe20/Ta and Co40Fe40B20/Ta bilayers and compared the spin Hall angles of these signals. We found that the contribution of the inverse spin Hall effect to the total signal in ST-FMR measurements is marked particularly in the case of Co40Fe40B20/Ta bilayers, because the anisotropic magnetoresistance effect in Co40Fe40B20, i.e., the origin of the ST-FMR signal, is much smaller than that in Ni80Fe20. When we take into account the contribution of the inverse spin Hall effect, the spin Hall angle of Co40Fe40B20/Ta decreases to less than half of that estimated by conventional ST-FMR spectral analysis.

Time-Frequency Enhancement Technique for Bevel Gear Fault Diagnosis

Gear failure is one of the most common causes of breakdown in rotating machineries. It is well known that vibration signals from machineries can be effectively used to detect certain gear faults. Yet it is still not an easy task to find a symptom that reflects a particular fault from vibration signals. This paper presents an advanced time-frequency signal processing technique for extracting important gear fault information from the vibration signal that is heavily corrupted by measurement noise. Experiments were performed on a bevel gearbox test rig using vibration measurements. The Time Synchronous Average (TSA) was initially utilized to eliminate all asynchronous component of vibration signal obtained from the gear. The Continuous Wavelet Transform (CWT) method was then used to capture the non-stationary behaviour of the impulse signal generated from the broken bevel gear tooth. It was shown that the diagnosis method using the Continuous Wavelet Transform combined with Time Synchronous Averaging outperformed the conventional spectral analysis, capable of identifying the angular location of broken teeth in the gear.

The relationship between spectral and wavelet techniques for noise analysis

Despite over 40 years of research, the optimum methods for the analysis of electrochemical noise data remain uncertain. One class of methods examine the frequency content of the noise signal. The first such method to be used was conventional spectral analysis, initially using the Fourier Transform, and subsequently the Maximum Entropy Method. Apart from questions over the relative merits of the two methods, the estimation of the power spectrum suffers from the formal requirement that the signal being analysed is stationary, since corrosion processes are frequently non-stationary. This has lead to the use of alternative analysis methods that do not require the signal to be stationary, including wavelet analysis and, more recently, the Hilbert-Huang transform. It is not always appreciated that the wavelet method was developed as an extension of the Fourier transform and that there is a close relationship between the two methods. This paper will explore this relationship and implications for the analysis of electrochemical noise.

Matrix-Completion-Based Airborne Tomographic SAR Inversion Under Missing Data

Tomographic synthetic aperture radar imaging (TomoSAR) is a new SAR imaging modality that extends the synthetic aperture principle into the elevation direction. In TomoSAR, the elevation resolution depends on the length of elevation aperture and the baseline distribution. When the length of elevation aperture is fixed, the number of baselines is important for the elevation reconstruction. Therefore, improving the elevation imaging quality with the finite amount of baselines is worth researching. This letter proposes a novel missing data compensation approach in TomoSAR via matrix completion (MC), which is a technique of the low-rank matrix recovery from a subset of the matrix elements. In the proposed method, we first exploit MC to estimate the 2-D focused image data of unknown baselines, which are located on the uniform data grid without changing the length of elevation aperture. Based on the recovered data, we then recover the elevation reflectivity function by the spectral analysis (SA) method. Compared with the conventional SA technique, the proposed approach can achieve much higher elevation image quality, due to more available data offered by MC. The effectiveness of the proposed method is validated with the experimental results based on simulated and real airborne data.