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In the context of the tadpole graph R$$ \mathcal{R} $$, we examine the damped Schrödinger semigroup e−itd2dx2$$ {e}^{- it\frac{d^2}{d{x}^2}} $$. The first step in our analysis involves a meticulous examination of the spectrum and a suitable decomposition of the resolvent's kernel. By doing so, we establish that the generalized eigenfunctions constitute a Riesz basis of a specific subspace of L2(R)$$ {L}^2\left(\mathcal{R}\right) $$. As a result, we demonstrate that the energy corresponding to the system decays exponentially. [ABSTRACT FROM AUTHOR]

In this paper, we study the Cauchy problem of a two-phase flow system consisting of the compressible isothermal Euler equations and the incompressible Navier-Stokes equations coupled through the drag force, which can be formally derived from the Vlasov-Fokker-Planck/incompressible Navier-Stokes equations. When the initial data is a small perturbation around an equilibrium state, we prove the global well-posedness of the classical solutions to this system and show the solutions tends to the equilibrium state as time goes to infinity. In order to resolve the main difficulty arising from the pressure term of the incompressible Navier-Stokes equations, we properly use the Hodge decomposition, spectral analysis, and energy method to obtain the L 2 time decay rates of the solution when the initial perturbation belongs to L 1 space. Furthermore, we show that the above time decay rates are optimal. [ABSTRACT FROM AUTHOR]

This article presents a method for automatically recognizing spoken digits in the Adi language using the highly effective open-source voice recognition toolkit, “Kaldi”. The study also includes an analysis of the formant frequencies and spectral characteristics of Adi digits. Adi is a zero-resource indigenous tribal language of Arunachal Pradesh with its roots in Tibeto-Burman. UNESCO's 2009 Atlas of the World's Languages in Danger classifies Adi as an endangered language in India. The research utilizes a modest digit corpus from 42 native Adi speakers, employing Mel Frequency Cepstral Coefficients (MFCC) and Perceptual Linear Prediction (PLP) features from continuous Adi speech utterances. The study explores both Monophone and Triphone models for digit recognition, with notable improvements in accuracy from 79.14% in the Monophone model to 84.29%, 88.43%, and 90.86% in the Triphone models (Tri1, Tri2, and Tri3). This proposed model holds promise for the development of Adi language speech recognition applications. [ABSTRACT FROM AUTHOR]

The geoid and quasi-geoid serve as the reference surfaces of the orthometric and normal height systems, respectively. In order to improve the accuracy of the (quasi-) geoid determined by the Stokes integral with use of the Remove-Compute-Restore (RCR) technique, various modification methods for the spherical Stokes’ kernels, including the spheroidal, cosine-, power-, and Molodensky-modified kernels, are studied in this paper. In addition to the traditional Molodensky-modified Stokes’ kernel, a more effective Molodensky-modified Stokes’ kernel is put forward. A general formula for spectral decomposition of the Stokes integral in the RCR mode is derived, followed by the spectral analysis to reveal the transfer principles of gravity data when using different Stokes’ kernels. The spheroidal and modified Stokes integrals can cause spectral leakage phenomenon, and a method to eliminate spectral leakage is presented based on spectral analysis. The research indicates the low truncation degree of the spheroidal Stokes’ kernel and the low modification degrees of the modified Stokes’ kernel affect the accuracy of the (quasi-) geoid significantly. Quantitative methods for estimating the empirical values of the parameters of the low-degree spheroidal and modified Stokes’ kernels are proposed and the effectiveness of the methods is validated through numerical tests. [ABSTRACT FROM AUTHOR]

We study the estimation problem of the spectral density function for harmonizable non‐stationary processes. More precisely, we consider spectrally correlated processes whose spectral measure has the support contained in the union of unknown lines with possibly non‐unit slopes. We propose the frequency‐smoothed periodogram along the estimated support line as an estimator of the spectral density function. We show the mean‐square consistency of the proposed estimator. Additionally, we discuss the estimation of the support line in a specific model with its applications in locating a moving source. Finally, we present simulations confirming the proven results. [ABSTRACT FROM AUTHOR]

Conical diffusers are widely used in technical devices (gasifiers, turbines, combustion chambers) and technological processes (ejectors, mixers, renewable energy). The perfection of flow gas dynamics in a conical diffuser affects the intensity of heat and mass transfer processes, the quality of mixing/separation of working media and the flow characteristics of technical devices. These parameters largely determine the efficiency and productivity of the final product. This article presents an analysis of experimental data on the gas-dynamic characteristics of stationary air flows in a vertical, conical, flat diffuser under different initial boundary conditions. An experimental setup was created, measuring instruments were selected, and an automated data collection system was developed. Basic data on the gas dynamics of air flows were obtained using the thermal anemometry method. Experimental data on instantaneous values of air flow velocity in a diffuser for initial velocities from 0.4 m/s to 2.22 m/s are presented. These data were the basis for calculating and obtaining velocity fields and turbulence intensity fields of the air flow in a vertical diffuser. It is shown that the value of the initial flow velocity at the diffuser inlet has a significant effect on the gas-dynamic characteristics. In addition, a spectral analysis of the change in air flow velocity both by height and along the diffuser axis was performed. The obtained data may be useful for refining engineering calculations, verifying mathematical models, searching for technical solutions and deepening knowledge about the features of gas dynamics of air flows in vertical diffusers. [ABSTRACT FROM AUTHOR]

Jade is a highly valuable and diverse gemstone, and its spectral characteristics can be used to identify its quality and type. We propose a jade ultraviolet (UV) spectrum recognition model based on deep learning, called SpectraViT, aiming to improve the accuracy and efficiency of jade identification. The algorithm combines residual modules to extract local features and transformers to capture global dependencies of jade's UV spectrum, and finally classifying jade using fully connected layers. Experiments were conducted on a UV spectrum dataset containing four types of jade (natural diamond, cultivated diamond (CVD/HPHT), and moissanite). The results show that the algorithm can effectively identify different types of jade, achieving an accuracy of 99.24%, surpassing traditional algorithms based on Support Vector Machines (SVM) and Partial Least Squares Discriminant Analysis (PLS_DA), as well as other deep learning methods. This paper also provides a reference solution for other spectral analysis problems. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Inorganic Analytical Chemistry / Zhongguo Wuji Fenxi Huaxue is the property of Beijing Research Institute of Mining & Metallurgy Technology Group and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Iron nanoparticles (FeNPs) speak to promising specialists for ecological remediation. We synthesized iron nanoparticles by using Terminalia bellirica (TB) fruit extract to degrade malachite green (MG), an organic dye. We observed the surface plasmon resonance (SPR) with a UV–visible spectrophotometer and found FeNPs to be nonplasmonic. The Terminalia bellirica fruit extract includes -OH groups in the nanoparticle synthesis response, as demonstrated by FTIR spectroscopy. We used high-resolution transmission electron microscopy (HRTEM) to confirm the spherical shape of iron nanoparticles, measuring approximately 25–60 nm. XRD results give an amorphous nature (α-Fe) to nanoparticles. An increase in temperature led to the growth of Fe2O3 NPs in the synthesized FeNPs. Zeta potential was used to characterize the soundness of synthesized FeNPs. It breaks down the most at a pH of 6.0 and a temperature of 80 °C, with Fe3+ and TB fruit extract adding up to 92% and 91.6%, respectively. The dye concentration for this process is 50 mg/L. [ABSTRACT FROM AUTHOR]

Dissolved organic matter (DOM) is easy to combine with residual pesticides and affect their morphology and environmental behavior. Given that the binding mechanism between DOM and the typical herbicide glyphosate in soil is not yet clear, this study used adsorption experiments, multispectral techniques, density functional theory, and pot experiments to reveal the interaction mechanism between DOM and glyphosate on Mollisol in farmland and their impact on the environment. The results show that the adsorption of glyphosate by Mollisol is a multilayer heterogeneous chemical adsorption process. After adding DOM, due to the early formation of DOM and glyphosate complex, the adsorption process gradually became dominated by single-layer chemical adsorption, and the adsorption capacity increased by 1.06 times. Glyphosate can quench the endogenous fluorescence of humic substances through a static quenching process dominated by hydrogen bonds and van der Waals forces, and instead enhance the fluorescence intensity of protein substances by affecting the molecular environment of protein molecules. The binding of glyphosate to protein is earlier, of which affinity stronger than that of humic acid. In this process, two main functional groups (C–O in aromatic groups and C–O in alcohols, ethers and esters) exist at the binding sites of glyphosate and DOM. Moreover, the complexation of DOM and glyphosate can effectively alleviate the negative impact of glyphosate on the soil. This study has certain theoretical guidance significance for understanding the environmental behavior of glyphosate and improving the sustainable utilization of Mollisol. [ABSTRACT FROM AUTHOR]

Recent studies have demonstrated changes in athletes brain imaging across a competitive season due to repeated head impacts during collision sports. However, there is no data reporting cortical activity in elite female rugby sevens players. There is scant literature on the effects of high-definition (HD)-transcranial direct current stimulation (tDCS) on cortical activity responses at different time points (TP) across the competitive season on the responsiveness of spectral band frequencies for HD-tDCS stimulation. This study examined the cortical activity of elite female rugby sevens players prior to pre-season (TP1) and following five months of training and competition (TP2), and the acute effects of HD-tDCS on cortical activity parameters. For each TP, the squad was randomly allocated to the HD-tDCS sham or the HD-tDCS anodal (active) stimulation groups. The Stroop task was performed for approximately 15 min prior to HD-tDCS (Stroop task-PRE). Following completion of the Stroop task-PRE, participants received 20-minutes of HD-tDCS stimulation and then performed the Stroop task (Stroop task-POST). A diminished responsiveness of cortical activity to the perturbation (HD-tDCS) for TP2 (vs. TP1) was observed, with cortical rhythms exhibiting a relative decline in faster bands (alpha, beta, and gamma), while slower bands (delta and theta) increased its proportional contribution to cortical activity. This discovery implies a potential alteration in the neural substrate's responsiveness to neuromodulation, likely influenced by the cumulative effects of repeated head impacts. The diminished responsiveness to HD-tDCS prompts significant considerations for the application of neuromodulation techniques in athletes participating in contact/collision sports. [ABSTRACT FROM AUTHOR]

Cotton is an important strategic material and one of our important economic crops. It plays an important role in our agricultural production, people's livelihood and secondary and tertiary industries. Cotton aphid is one of the major pests in the process of cotton growth and development. The lag and inaccuracy of aphid information will lead to the excessive application of pesticides, which will accelerate the destruction of cotton habitat and the pollution of cotton field environment. Therefore, it is of great practical significance to obtain the temporal and spatial distribution, hazard level and occurrence area of aphids in cotton fields in real time and accurately for the prevention and control of cotton aphid, cotton field management and farmland environmental protection. Remote sensing technology and machine vision technology speed up the acquisition of real-time and dynamic information and classification of aphids in cotton fields. This paper focused on "cotton aphid situation information monitoring", carried out literature review and combing at home and abroad, and described the research status and progress of traditional methods, remote sensing technology and image recognition on cotton aphid situation information. The problems in the monitoring of cotton aphid were discussed, and the research focus and development trend of the monitoring and diagnosis of cotton aphid damage information in the future were prospected. [ABSTRACT FROM AUTHOR]

On-chip spectrometers are increasingly becoming tools that might help in everyday life needs. The possibility offered by several available integration technologies and materials to be used to miniaturize spectrometers has led to a plethora of very different devices, that in principle can be compared according to their metrics. Having access to a reference database can help in selecting the best-performing on-chip spectrometers and being up to date in terms of standards and developments. In this paper, an overview of the most relevant publications available in the literature on miniaturized spectrometers is reported and a database is provided as an open-source project to which researchers can have access and participate in order to improve the share of knowledge in the interested scientific community. [ABSTRACT FROM AUTHOR]

The article presents the results of the development and research regarding the application of modal analysis to the evaluation of a multi-point projection welding process. The quality control system is based on the information provided by modal analysis for the entire welding station after the previously completed welding process. The research is carried out due to the lack of an effective method for assessing the course of the multi-spot projection welding process in the case of a single current circuit passing through many points at the same time. A study of the applicability of modal analysis in investigating the quality of a multipoint joint was conducted for four DIN 928 nuts welded to a steel profile. The aim of the study was to determine the influence of weld defects on the displacement of resonant frequencies. To realize the objective, the dynamic properties of the entire welding station, including the sample in the frequency domain, were investigated. In the first stage of the study, a finite element method was used to perform modal analysis and examine the form of vibrations for the individual natural frequencies of the welding fixture including the sample. Then, quality verification using the dynamic resistance method was performed, which was compared later with the modal approach. The last stage of the study was to conduct modal analysis in the frequency domain to verify the numerical studies. [ABSTRACT FROM AUTHOR]

Codeword position index based sparse code multiple access (CPI‐SCMA) is an effective scheme that expands codeword positions in the time domain and carries extra information by their index. This paper proposes a dual‐mode CPI‐SCMA (DCPI‐SCMA) scheme to improve the error propagation caused by the mismatch between SCMA codewords and information bits. Furthermore, a DCPI‐SCMA with transmit diversity scheme is proposed where index bits are repeatedly transmitted to obtain a transmit diversity gain; hence, a higher reliability can be achieved with a slight loss of spectral efficiency. An optimal approach for the codebook index pattern is derived where the decision of index bits is involved in the demodulation of SCMA. It can be seen from simulation results and system analysis that the proposed schemes achieve better bit error rate performance with a decrease in complexity and obtain better robustness and flexibility compared with the existing CPI‐based SCMA schemes under the same spectral efficiency. [ABSTRACT FROM AUTHOR]

This brief proposes a calibration method for offset, gain, and timing‐skew mismatches in time‐interleaved analog‐to‐digital converters. The calibration method includes the estimation method and the correction method. The estimation method is based on the difference between the spectral distribution of the error harmonics and the input signal. The correction method adopts sequential correction. Simulation results demonstrate that the proposed method calibrated all three mismatches simultaneously and eased the limit for input signals compared with the traditional method. [ABSTRACT FROM AUTHOR]

Fluid resonance in the narrow gap formed by a two-box system under irregular wave actions is investigated by employing a viscous numerical wave flume based on the OpenFOAM package. The accuracy of the numerical model is validated by comparing it with previous experimental data and numerical results in the literature. It can be observed that the viscous fluid flow model can work well in predicting the free surface amplitudes around the resonant frequency, while the potential flow model overpredicts the resonant amplitude. Numerical simulations suggested that the periods of wave responses in the narrow gap are always around the resonant period with small standard deviations. This can be explained by the spectral analysis that the wave energy in the narrow gap is concentrated at the resonant frequency. The normalized wave amplitudes calculated from the samplings of the large free surface amplitudes are always smaller than the samplings of the small free surface amplitudes. With the increase of the peak enhancement factor, the normalized significant wave heights under irregular wave actions increase and decrease around resonant and nonresonant frequencies, respectively. Compared to the results under regular wave actions, smaller and larger wave amplitudes appeared in the results of irregular wave actions around the resonant and nonresonant frequency ranges, respectively. The decreased normalized wave amplitudes with the increase of incident irregular wave amplitudes can be observed at all the frequency ranges. [ABSTRACT FROM AUTHOR]

Thirty-seven portable accelerometers were deployed in the eastern San Francisco Bay communities of Walnut Creek and Concord to study site response in a fault-bounded, urban, sedimentary basin. Local earthquakes were recorded for a period of two years from 2017 to 2019 resulting in 101 well-recorded events. Site response is estimated by two methods: the reference site spectral ratio method and a source-site spectral inversion method. The reference site spectral ratio method allows investigation of the variability of site amplification with source azimuth and frequency. The source-site spectral inversion method yields the best least-squares fit to site response for a database of ground-motion records. Both methods show substantial amplification in the Walnut Creek-Concord basin below 2 Hz indicating strong surface-wave development. Greater amplification is seen for sources aligned along the long axis of the basin. Inversion using close-in sources at short distances yields lower amplification at longer periods than the entire data set due to reduced surface-wave generation for steeper angles of incidence. Inversion of site response spectra for shallow shear-wave velocity using a global search algorithm yields VS30 values consistent with generalized mapping results based on geology and topography but with greater variability due to local site variations. 3D finite-element modeling shows greater amplification in the Walnut Creek-Concord basin with a basin-edge effect likely contributing to higher ground motions. Topography is also seen to lead to increased scattering and shadowing effects. [ABSTRACT FROM AUTHOR]

Ground-motion models (GMMs) are fundamental for the estimation of ground shaking for probabilistic seismic hazard assessment. Because of the paucity of ground motion recordings in regions of low seismicity, stochastic approaches are often employed to generate synthetic data. In this study, we developed a GMM using a stochastic simulation approach for southwest Iberia--a zone for which seismic hazard is usually assessed using models developed for other regions. We collected geological, tectonic, and ground-motion data for offshore and inland Iberia, and calibrated several parameters for a stochastic simulation. The resulting synthetic response spectra were used to train a machine learning algorithm (artificial neural network) capable of predicting peak ground acceleration, peak ground velocity, and spectral acceleration on rock (VS30 = 760 M/S), along with the associated between-event and within-event terms. The resulting model was compared against other existing models for stable continental regions and ground-motion recordings for Portugal and Spain. The results indicate a good agreement with observations and the model can be used directly in probabilistic seismic hazard analysis for southwest Iberia. [ABSTRACT FROM AUTHOR]

On-site earthquake early warning (EEW) requires the best estimates of earthquake magnitude and distance parameters within a few seconds after the P-wave arrival for estimating the subsequent S-wave parameters. The errors in the estimates of the earthquake P-wave parameters will propagate into the estimates of the S-wave parameters. To solve this problem, we used the methodology by Zhao and Zhao (2019), which uses the spectral ratio between the response spectral values of the first 3 s of the S wave and that of the first 3 s of the P wave, referred to as the R3P model. The modeling presented here was based on strong-motion records from the Next Generation Attenuation (NGA)-West2 dataset. We also used the spectral ratio between the response spectral values from the full records from the S-wave arrival time to the end of the record and that of the first 3 s P wave to develop a second EEW model (the RFP model). An advantage of these two models is that the magnitude and hypocentral distance are not required in considerable magnitude and distance ranges. This means that the errors in the estimated source and path parameters from the first 3 s of the P wave will not affect the model predictions. A theoretical justification for these results is that the magnitude and the distance scaling rates for the first 3 s of the P wave are similar to those of the first 3 s of the S wave. This may also apply to the full S-wave window within useful EEW magnitude and distance ranges. We also found that when the estimated magnitude and distance for a record are necessary, the effect of the corresponding errors would be smaller than using a ground-motion prediction equation (GMPE), because the magnitude and distance scaling rates from this study are smaller than those of many GMPEs. [ABSTRACT FROM AUTHOR]

To estimate predicted ground motion from a teleseismic slip model, we use a low- and high-frequency hybrid method to simulate the regional, strong ground motions observed following the 18 April 2014 moment magnitude (MW) 7.3 Papanoa, Mexico, earthquake. To generate the regional ground motion at low frequencies (<1 Hz), a teleseismically derived, finite-fault, kinematic model is used to define the earthquake source, taking into account slip-model variations identified with a parameter sampling approach that considers possible errors in the fault geometry, the hypocenter depth, and the rupture velocity. A 3D crustal model is used to calculate the low-frequency ground motions using a finite-element calculation that includes topography and considers variations in the source model to estimate the uncertainty in the calculations. High frequencies (>1 Hz) are added using a 1D full-wave propagation code that estimates uncertainties by considering multiple random distributions of slip with different spatial correlation lengths. The synthetic, broadband (0.05-10.0 Hz) ground motions are obtained by combining the low- and high-frequency portions match filtered at 1 Hz. These synthetic ground motions are compared with the regional observations using velocity records, peak ground acceleration, and medians of the orientation-independent response spectra of the horizontal components (RotD50) calculated at periods of 0.2, 0.3, 0.5, 1.0, 2.0, 3.0, 5.0, 7.5, and 10.0 s. The results indicate that ground motions estimated at these periods using our hybrid approach based primarily on a teleseismically derived source model are comparable to the values observed for the 2014 Papanoa earthquake at regional distances. The approach could be used to estimate strong-motion spectral levels expected for regions with limited local and regional recordings and could also fill in magnitude or distance gaps in ground-motion prediction relations utilized in the assessment of seismic hazard. [ABSTRACT FROM AUTHOR]

Determining the depths of small crustal earthquakes is challenging in many regions of the world, because most seismic networks are too sparse to resolve trade-offs between depth and origin time with conventional arrival-time methods. Precise and accurate depth estimation is important, because it can help seismologists discriminate between earthquakes and explosions, which is relevant to monitoring nuclear test ban treaties and producing earthquake catalogs that are uncontaminated by mining blasts. Here, we examine the depth sensitivity of several physics-based waveform features for ~8000 earthquakes in southern California that have well-resolved depths from arrival-time inversion. We focus on small earthquakes (2 < ML < 4) recorded at local distances (<150 km), for which depth estimation is especially challenging. We find that differential magnitudes (MW/ML-MC) are positively correlated with focal depth, implying that coda wave excitation decreases with focal depth. We analyze a simple proxy for relative frequency content, ɸ ≊ log10(M0) + 3log10(fc)ɸ, and find that source spectra are preferentially enriched in high frequencies, or "blue-shifted," as focal depth increases. We also find that two spectral amplitude ratios Rg 0.5-2 Hz/Sg 0.5-8 Hz and Pg/Sg at 3-8 Hz decrease as focal depth increases. Using multilinear regression with these features as predictor variables, we develop models that can explain 11%-59% of the variance in depths within 10 subregions and 25% of the depth variance across southern California as a whole. We suggest that incorporating these features into a machine learning workflow could help resolve focal depths in regions that are poorly instrumented and lack large databases of well-located events. Some of the waveform features we evaluate in this study have previously been used as source discriminants, and our results imply that their effectiveness in discrimination is partially because explosions generally occur at shallower depths than earthquakes. [ABSTRACT FROM AUTHOR]

Estimating the corner frequency (fc) of an earthquake is of fundamental importance to improving our knowledge of the physics of the rupture that gives rise to a seismic event, while also having important implications by providing information on the high-frequency radiation for seismic hazard studies. However, the estimation of fc through spectral-fitting methods suffers from trade-offs with the estimation of seismic wave attenuation, making the obtained values precise but not necessarily accurate. For this reason, after a review of the source model proposed by Brune (1970), a new method of estimating fc, based on the phase fitting of Fourier spectra of the Brune's seismic pulse related to S-waves, called Fourier phase spectra fitting (FPS), is proposed and evaluated in this study. The method can be applied in cases in which Brune's model may be appropriate, while also considering the effects of propagation on impulse deformation, for which the synthetic tests have been conducted. The results, obtained first using synthetic seismograms generated under controlled conditions and then on a data set of recordings of real seismic events collected at the Groningen gas field in the Netherlands, showed the method to be promising (being accurate and precise) and at the same time pointed out its limitations, with its applicability being restricted to short hypocentral distances of <20 km. [ABSTRACT FROM AUTHOR]

The main purpose of this study is the subsurface investigation of two complex geological environments focusing on the improvement of data acquisition and processing parameters regarding electric and seismic tomographic techniques. Two different study areas, in central–east Peloponnese and SE Attica, were selected, where detailed geological mapping and surface geophysical survey were carried out. The applied geophysical survey included the application of electrical resistivity tomography (ERT), seismic refraction tomography (SRT) and ground penetrating radar (GPR). The geoelectrical measurements were acquired with different arrays and electrode configurations. Moreover, various types of seismic sources were used at seventeen shot locations along the seismic arrays. For the processing of geoelectrical data, clustered datasets were created, increasing the depth of investigation and discriminatory capability. The seismic data processing included the following: (a) the creation of synthetic models and seismic records to determine the effectiveness and capabilities of the technique, (b) spectral analysis of the seismic records to determine the optimal seismic source type and (c) inversion of the field data to create representative subsurface velocity models. The results of the two techniques successfully delineated the complex subsurface structure that characterizes these two geological environments. The application of the ERT combined with the SRT are the two dominant, high-resolution techniques for the elucidation of complex subsurface structures. [ABSTRACT FROM AUTHOR]

The Azadirachta indica, normally known as the Neem tree, is a remarkable plant with a rich history of medicinal and healing properties. This evergreen tree, native to the Indian subcontinent, is renowned globally for its adaptability and ability to address various health issues. This bio-analytical study aims to identify and structurally elucidate the major phytoconstituents present in the hydroalcoholic extract of the Neem plant. In this phyto-analysis, the phytoconstituents from the Neem plant were isolated using column chromatography and their structural elucidation was accomplished using spectral analysis. Two major isolate, Nimoid and Nimbine were identified and structurally elucidated from A. indica by spectral analysis (I.R., NMR and mass spectroscopy). Neem plant traditionally use for skin conditions, infected burns, and septic sores. These medicinal properties are outcome of major phytoconstituents Nimoid and Nimbine. [ABSTRACT FROM AUTHOR]

Introduction: The coverage of a makeup foundation is a perceived attribute which is not captured by opacity or any other single optical property. As previous instrumental measurements do not allow us to consistently compare one product to another, we have begun exploring new parameters and analysis methods made available by hyperspectral imaging. Presumably, the coverage of makeup comes from the change in color, homogeneity, and evenness over the face after application, and the ability of the product to hide spots and other blemishes. Methods: As a starting point to unravelling this complex topic, we define a homogeneity factor αHF which measures the change in the homogeneity of the spectra using the distribution of spectral angles in the face. We likewise define a spectral shift factor βSF which indicates the degree of spectral change after product application. To test these new parameters and the overall analysis method, we applied them to the HSI validation dataset which contains data for three makeup foundation products of different coverage levels applied to 9 models. Results: We find that αHF correlates with the sensory ranking of coverage. Similarly, the parameter βSF correlates with the visible color change induced by the product, and we can map the three products into distinct categories based on their effect on αHF and βSF. Discussion: Nevertheless, the homogeneity factor αHF does not fully describe coverage, and in the variability in the product effect from model to model we find evidence that we must also account for the relative color difference between the model's skin tone and the product shade among other factors. [ABSTRACT FROM AUTHOR]

Exploring the molecular packing and interaction between chiral molecules, no matter single enantiomer or racemates, is important for recognition and resolution of chiral drugs. However, sensitive and non‐destructive analysis methods are lacking. Herein, an intermolecular‐charge transfer (ICT) based spectroscopy is reported to reveal the differences in interaction between the achiral acceptor 1,2,4,5‐tetracyanobenzene (TCNB) and the chiral donors, including S, R, and racemic naproxen (S/R/rac‐NAP). In this process, S‐NAP+TCNB and R‐NAP+TCNB display a narrower band gap attributed to the newly formed ICT state. In contrast, the mixed rac‐NAP and TCNB exhibit almost no significant change due to the strong affinity between the stereoisomers according to the Wallach's rule. Thus, S/R‐NAP can be easily distinguished from rac‐NAP based on significantly different optical behavior. The single crystal analysis, infrared spectroscopy, fluorescence spectroscopy, and theoretical calculation of naproxen confirm the importance of carboxyl for this differentiation in molecular packing and interaction. In addition, the esterification derivatization of naproxen achieves the manipulation of the intermolecular interaction model of racemates from the absolute Wallach's rule to a coexisting form of Wallach's rule and ICT. Further, visualized chiral purification of naproxen by the simple cocrystallization method is achieved through the collaboration of ICT and Wallach's rule. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Abamectin (ABA) is considered a powerful insecticidal and anthelmintic agent. It is an intracellular product of Streptomyces avermitilis; is synthesized through complicated pathways and can then be extracted from mycelial by methanol extraction. ABA serves as a biological control substance against the root-knot nematode Meloidogyne incognita. This investigation is intended to reach a new strain of S. avermitilis capable of producing ABA effectively. Results: Among the sixty actinobacterial isolates, Streptomyces St.53 isolate was chosen for its superior nematicidal effectiveness. The mycelial-methanol extract of isolate St.53 exhibited a maximum in vitro mortality of 100% in one day. In the greenhouse experiment, the mycelial-methanol extract demonstrated, for the second-stage juveniles (J2s), 75.69% nematode reduction and 0.84 reproduction rate (Rr) while for the second-stage juveniles (J2s), the culture suspension demonstrated 75.38% nematode reduction and 0.80 reproduction rate (Rr). Molecular identification for St.53 was performed using 16 S rRNA gene analysis and recorded in NCBI Genbank as S. avermitilis MICNEMA2022 with accession number (OP108264.1). LC-MS was utilized to detect and identify abamectin in extracts while HPLC analysis was carried out for quantitative determination. Both abamectin B1a and abamectin B1b were produced and detected at retention times of 4.572 and 3.890 min respectively. Conclusion: Streptomyces avermitilis MICNEMA2022 proved to be an effective source for producing abamectin as a biorational agent for integrated nematode management. [ABSTRACT FROM AUTHOR]

The successful growth of 2-Methylbenzimidazolium 4-nitrobenzoate 4-nitrobenzoic acid (MINB) from a solution of ethyl and methyl alcohol using the solvent evaporation solution technique (SEST). The MINB crystal belongs to the triclinic crystal system and possesses a centrosymmetric P-1 space group, maintained by N–H...O and O–H...O interactions. Proton configuration confirmation was achieved through 1H-NMR analysis, while FTIR and Raman studies identified functional groups and vibrational frequencies. Optical transmission analysis revealed exceptional transparency (> 90%), along with a cut-off wavelength at 400 nm and Eg = 2.91 eV. The crystal's thermal behaviour was studied using thermogravimetric and differential thermal analysis, etching studies assessed crystal perfection, Vicker's microhardness test determined load-dependent hardness, and dielectric properties (ε′, δ) were measured at 313 K with the frequency range of 50 Hz to 5 MHz. Nonlinear optical characteristics were explored using Q-switched Nd:YAG laser with a wavelength of 532 nm, exhibits Reverse saturable absorption (RSA) has been triggered by Two-Photon Absorption (2PA). The nonlinear absorption coefficient (β) of MINB crystal increased with concentration of solution, while the optical limiting threshold decreased with higher MINB concentrations, showcasing its intriguing properties and potential applications. We exploited First-principles density functional theory and ab-initio molecular dynamics simulations to investigate the electrical and optical characteristics of the MINB material. We establish that this material exhibits semiconductor properties, characterized by an energy band gap of 2.86 eV and notable absorption in the Ultraviolet (UV) light spectrum. [ABSTRACT FROM AUTHOR]

The electroencephalogram (EEG) is a cornerstone tool for the diagnosis, management, and prognosis of selected patient populations. EEGs offer significant advantages such as high temporal resolution, real-time cortical function assessment, and bedside usability. The quantitative EEG (qEEG) added the possibility of long recordings being processed in a compressive manner, making EEG revision more efficient for experienced users, and more friendly for new ones. Recent advancements in commercially available software, such as Persyst, have significantly expanded and facilitated the use of qEEGs, marking the beginning of a new era in its application. As a result, there has been a notable increase in the practical, real-world utilization of qEEGs in recent years. This paper aims to provide an overview of the current applications of qEEGs in daily neurological emergencies and ICU practice, and some elementary principles of qEEGs using Persyst software in clinical settings. This article illustrates basic qEEG patterns encountered in critical care and adopts the new terminology proposed for spectrogram reporting. [ABSTRACT FROM AUTHOR]

Hypnotic phenomena exhibit significant inter-individual variability, with some individuals consistently demonstrating efficient responses to hypnotic suggestions, while others show limited susceptibility. Recent neurophysiological studies have added to a growing body of research that shows variability in hypnotic susceptibility is linked to distinct neural characteristics. Building on this foundation, our previous work identified that individuals with high and low hypnotic susceptibility can be differentiated based on the arrhythmic activity observed in resting-state electrophysiology (rs-EEG) outside of hypnosis. However, because previous work has largely focused on mean spectral characteristics, our understanding of the variability over time of these features, and how they relate to hypnotic susceptibility, is still limited. Here we address this gap using a time-resolved assessment of rhythmic alpha peaks and arrhythmic components of the EEG spectrum both prior to and following hypnotic induction. Using multivariate pattern classification, we investigated whether these neural features differ between individuals with high and low susceptibility to hypnosis. Specifically, we used multivariate pattern classification to investigate whether these non-stationary neural features could distinguish between individuals with high and low susceptibility to hypnosis before and after a hypnotic induction. Our analytical approach focused on time-resolved spectral decomposition to capture the intricate dynamics of neural oscillations and their non-oscillatory counterpart, as well as Lempel–Ziv complexity. Our results show that variations in the alpha center frequency are indicative of hypnotic susceptibility, but this discrimination is only evident during hypnosis. Highly hypnotic-susceptible individuals exhibit higher variability in alpha peak center frequency. These findings underscore how dynamic changes in neural states related to alpha peak frequency represent a central neurophysiological feature of hypnosis and hypnotic susceptibility. [ABSTRACT FROM AUTHOR]

The adsorption and fluorescence spectra of the grown Nd∶GdYAG were measured. The spectral parameters, such as oscillator strength, line strength, intensity parameter Ωt, transition probability between 4 F3/2→4 IJ levels, radiation lifetime, and fluorescence branching ratio, were calculated with Judd-Ofelt theory. The calculated Ωt are Ω2 = (0.813 ±0.200) ×10-20 cm2, Ω4 = (3. 381 ±0. 187) × 10 -20 cm2, Ω6 = (5. 135 ± 0. 278) × 10 -20 cm2, respectively. Compared with Nd-doped YAG, LuAG, YVO4, and other crystals, Nd∶GdYAG crystal has a larger Ω2, showing that the addition of Gd3 + increases the disorder of the host. The absorption cross-section and refractive index in the range of 300 ~1 200 nm were calculated and fitted. The absorption cross-section at 808 nm is 5. 0 ×10 -20 cm2. The refractive index at 1 064 nm is 1. 80. The measured fluorescence lifetime of 4 F3/2 level is 228 μs, which is close to the calculated radiation lifetime of 240 μs. The emission cross-section at 1 064 nm is 1. 23 × 10 -19 cm2, which is close to that of Nd∶ YAG crystal. Addition, at room temperature, the thermal conductivity of Nd∶GdYAG crystal is 5. 992 W/(m·K), which is slightly smaller than that of Nd∶YAG and Nd∶GGG, but larger than that of Nd∶YVO4 crystal. The results show that Nd∶GdYAG is a promising new laser crystal material. [ABSTRACT FROM AUTHOR]

Due to rapid economic development and urbanization, water pollution has posed a significant threat to public health and social stability. Therefore, accurate and rapid monitoring of water quality becomes particularly important and significant. As an environmentally friendly, nondestructive and efficient detection technology, spectral analysis technology provides an effective tool for qualitative analysis and quantitative detection of pollutants in water environment. In this paper, the principle of UV-Vis spectroscopy and near-infrared (NIR) spectroscopy and their application in water quality detection are studied. UV-Vis and NIR spectroscopy techniques for the detection of many kinds of water quality parameters are discussed according to the classification of chemical oxygen demand, organic matter, microbial pollutants, heavy metals and emerging pollutants. The information of light source in spectroscopy measurement and the algorithms used in spectral data processing are summarized. Finally, the application tendency of spectrum technology in water pollution detection is prospected. [ABSTRACT FROM AUTHOR]

The idea that mental events unfold over time with an intrinsically paced regularity has a long history within experimental psychology, and it has gained traction from the actual measurement of brain rhythms evident in EEG signals recorded from the human brain and from direct recordings of action potentials and local field potentials within the nervous systems of nonhumans. The weak link in this idea, however, is the challenge of extracting signatures of this temporal structure from behavioral measures. Because there is nothing in the seamless stream of conscious awareness that belies rhythmic modulations in sensitivity or mental acuity, one must deploy inferential strategies for extracting evidence for the existence of temporal regularities in neural activity. We have devised a parametric procedure for analysis of temporal structure embedded in behaviorally measured data comprising durations. We confirm that this procedure, dubbed PATS, achieves comparable results to those obtained using spectral analysis, and that it outperforms conventional spectral analysis when analyzing human response time data containing just a few hundred data points per condition. PATS offers an efficient, sensitive means for bridging the gap between oscillations identified neurophysiologically and estimates of rhythmicity embedded within durations measured behaviorally. [ABSTRACT FROM AUTHOR]

The density (ρ) and dynamic viscosity (η) values of the binary mixed solution (ethylene glycol propyl ether (2-PE) and dimethyl sulfoxide (DMSO)) with different concentrations were measured by Ubbelohde viscometer (0.8–0.9 mm in diameter) and 25 mL pycnometer at atmospheric pressure and 293.15–318.15 K of the temperature. According to the ρ and η values, the viscosity deviation (), excess molar volume (), partial molar volume ( , ), apparent molar volume ( , ), excess Gibbs energy of activation for viscous flow (), and thermal expansion coefficient () of the mixed solution were obtained by the calculation method. In addition, the intermolecular forces between 2-PE and DMSO were analyzed by infrared spectra (FTIR), ultraviolet spectra (UV–Vis) and fluorescence spectra. The results showed that hydrogen bond is formed between the hydrogen atom on hydroxyl of 2-PE and oxygen atom of DMSO, and the hydrogen bond affects the physical properties of the binary system. Based on the analysis above, the result was interpreted as (CH3)2S=O···HOCH2CH2OCH2CH2CH3. [ABSTRACT FROM AUTHOR]

Measuring atmospheric winds over longer ranges using VHF-MST radar is extremely useful for studying stratosphere-troposphere exchange. The present study uses an adaptive block technique (ABlockJS), a mixed model of a parametric technique, and a few non-parametric techniques to address this aspect. The signal estimates are substantiated with five moments and six quality-related parameters while deriving three wind components along with horizontal wind speed and direction. The parametric part of the technique improves the signal, while the non-parametric part lowers noise variance. This technique is established using NARL MST Radar experimental data. The computed wind components derived from this technique are verified with the independent wind components acquired from the concurrent GPS radiosonde in-situ observations. It is observed that this analytical technique can deliver wind components more precisely and consistently, covering longer ranges of 25.20 km. It enhances the benchmark range coverage of 21.45 km attained using Fourier-based estimators on the MST dataset. The complete procedure is developed in C# from scratch without using any standard routine from available packages, thus, it fits acquisition-time application needs fine. It benefits various atmospheric research which demands higher range coverage using VHF radar. [ABSTRACT FROM AUTHOR]

In a study conducted in a metro tunnel, acceleration and displacement sensors were strategically placed along steel rails, track beds, and tunnel walls to capture real-time dynamic responses during train operations. Data were analyzed in the time and frequency domains, focusing on vibration levels and one-third octave bands. The results indicated that peak vibration acceleration significantly decreases from steel rails to tunnel walls, with different vibration frequencies observed at various locations: steel rails (200 Hz–1400 Hz), track beds, and tunnel walls (70 Hz–400 Hz). Cracks notably increase peak acceleration, vibration levels, peak frequency, and steel rail displacement but do not alter the overall vibration trends. Tunnel wall responses show the highest sensitivity to cracks, with a 300% increase in peak frequency, followed by track beds (100%) and steel rails (70%). Vibration levels under one-third octave band processing increased by 12.4% for tunnel walls, 8.8% for track beds, and 2.2% for steel rails. Cracks also caused steel rails' vertical and lateral displacement to rise by 112% and 53%, respectively. These findings provide valuable insights for vibration reduction and crack repair in long-term subway operations. [ABSTRACT FROM AUTHOR]

Irrigated agricultural lands in arid and semi-arid regions are prone to soil degradation. Remote sensing technology has proven useful for mapping and monitoring the extent of this issue. To accurately discern soil salinity, it is essential to choose appropriate spectral wavelengths. This study evaluated the potential of the land degradation index (LDI) using the visible and near infrared (VNIR) and the short wavelength infrared (SWIR) spectral bands compared to that of soil salinity indices by integrating only the VNIR wavelengths. Landsat-OLI and Sentinel-MSI data, acquired 2 weeks apart, were rigorously preprocessed and used. This research was conducted over irrigated agricultural land in Morocco, which is well known for its semi-arid climate and moderately saline soil. Furthermore, a field soil survey was conducted and 42 samples with variable electrical conductivity (EC) were collected for index calibration and validation of the results. The results showed that the visual analysis of the derived maps based on the examined indices exhibited a clear spatial pattern of gradual soil salinity changes extending from the elevated upstream plateau to the downstream of the plain, which limits agricultural activities in the southwestern sector of the study area. The results of this study show that LDI is effective in identifying soil salinity, as indicated by a coefficient of determination (R2) of 0.75 when using Sentinel-MSI and 0.72 with Landsat-OLI. The R2 value of 0.89 and root mean square error (RMSE) of 0.87 dS/m for soil salinity maps generated from LDI with Sentinel-MSI demonstrate high accuracy. In contrast, the R2 value of 0.83 and RMSE of 1.24 dS/m for maps produced from Landsat-OLI indicate lower accuracy. These findings indicate that high-resolution Sentinel-MSI data significantly improved the prediction of salinity-affected soils. Furthermore, this study highlights the benefits of using VNIR and SWIR bands for precise soil salinity mapping. [ABSTRACT FROM AUTHOR]

Transcutaneous spinal cord stimulation (tSCS) is a promising noninvasive alternative to epidural stimulation. However, further studies are needed to clarify how tSCS affects postural control. The aim of this study was to investigate the effect of transcutaneous cervical spinal cord stimulation on postural stability in healthy participants via computerized stabilization. The center of pressure and the frequency spectrum of the statokinesiogram were assessed in 14 healthy volunteers under tSCS conditions with frequencies of 5 Hz or 30 Hz, subthreshold or suprathreshold stimulus strength, open or closed eyes, and hard or soft surfaces in various combinations. The results revealed that not all the changes in the center of the pressure oscillations reached statistical significance when the tSCS was used. However, tSCS at a frequency of 30 Hz with a suprathreshold stimulus strength improved postural stability. The use of subthreshold or suprathreshold tSCS at 5 Hz led to a shift of 60% of the signal power to the low-frequency range, indicating activation of the vestibular system. With tSCS at 30 Hz, the vestibular component remained dominant, but a decrease in the proportion of high-frequency oscillations was observed, which is associated with muscle proprioception. Thus, transcutaneous electrical stimulation of the cervical spinal cord may be an effective method for activating spinal cord neural networks capable of modulating postural control. [ABSTRACT FROM AUTHOR]

Abstract Codeword position index based sparse code multiple access (CPI‐SCMA) is an effective scheme that expands codeword positions in the time domain and carries extra information by their index. This paper proposes a dual‐mode CPI‐SCMA (DCPI‐SCMA) scheme to improve the error propagation caused by the mismatch between SCMA codewords and information bits. Furthermore, a DCPI‐SCMA with transmit diversity scheme is proposed where index bits are repeatedly transmitted to obtain a transmit diversity gain; hence, a higher reliability can be achieved with a slight loss of spectral efficiency. An optimal approach for the codebook index pattern is derived where the decision of index bits is involved in the demodulation of SCMA. It can be seen from simulation results and system analysis that the proposed schemes achieve better bit error rate performance with a decrease in complexity and obtain better robustness and flexibility compared with the existing CPI‐based SCMA schemes under the same spectral efficiency.

This study was undertaken in order to evaluate the effects of different processing techniques, namely, enzyme-assisted cold-pressing, Soxhlet extraction and aqueous enzymatic extraction on the basic physicochemical properties, antioxidant activity, fatty acid composition, spectral characteristics and volatile flavor substances of corn germ oil. The results showed that the acid value and peroxide value of corn germ oil obtained by enzyme-assisted cold pressing were higher than those obtained by the other methods. The hydroxyl radical scavenging ability of the oil obtained by enzyme-assisted cold pressing was the highest, and there was no significant difference in the contents of linoleic acid, linolenic acid or unsaturated fatty acids oil among the three oil samples. The full spectrum analysis showed that the highest content of linolenic acid (conjugated trienoic acid) was found in the oil obtained by aqueous enzymatic extraction. The composition and relative content of volatile compounds in corn germ oil varied significantly with the different production processes. In summary, the processing methods can affect the physicochemical properties, antioxidant properties and flavor substances of corn germ oil, which provides a theoretical reference for the utilization of corn processing by-products and the moderate processing of corn germ oil.

Abstract Background Abamectin (ABA) is considered a powerful insecticidal and anthelmintic agent. It is an intracellular product of Streptomyces avermitilis; is synthesized through complicated pathways and can then be extracted from mycelial by methanol extraction. ABA serves as a biological control substance against the root-knot nematode Meloidogyne incognita. This investigation is intended to reach a new strain of S. avermitilis capable of producing ABA effectively. Results Among the sixty actinobacterial isolates, Streptomyces St.53 isolate was chosen for its superior nematicidal effectiveness. The mycelial-methanol extract of isolate St.53 exhibited a maximum in vitro mortality of 100% in one day. In the greenhouse experiment, the mycelial-methanol extract demonstrated, for the second-stage juveniles (J2s), 75.69% nematode reduction and 0.84 reproduction rate (Rr) while for the second-stage juveniles (J2s), the culture suspension demonstrated 75.38% nematode reduction and 0.80 reproduction rate (Rr). Molecular identification for St.53 was performed using 16 S rRNA gene analysis and recorded in NCBI Genbank as S. avermitilis MICNEMA2022 with accession number (OP108264.1). LC-MS was utilized to detect and identify abamectin in extracts while HPLC analysis was carried out for quantitative determination. Both abamectin B1a and abamectin B1b were produced and detected at retention times of 4.572 and 3.890 min respectively. Conclusion Streptomyces avermitilis MICNEMA2022 proved to be an effective source for producing abamectin as a biorational agent for integrated nematode management.

Spectral gamma-ray logging stands out as an efficacious methodology in the exploration of uranium(U). In order to address the challenges associated with low statistical efficacy in spectral analysis and mitigate the impact of spectral drift, machine learning algorithms such as Back Propagation (BP) neural network, Generalized Regression Neural Network (GRNN), and Support Vector Machine (SVM) have been employed for the quantitative interpretation of uranium. A method rooted in machine learning algorithms for energy spectral analysis has been proposed, catering to the analysis of high-speed spectra logging and gamma-ray spectra characterized by spectral drift. Examinations conducted on standard model wells containing uranium revealed that the BP neural network exhibited commendable accuracy in uranium interpretation, achieving quantification accuracy rates of 86.986 % and 93.478 % for low-grade and medium-high-grade uranium ores in the Testing Set, respectively. Notably, marginal variations in the model's quantification errors were observed under diverse logging speeds and spectral drift conditions, underscoring the capacity of gamma-ray spectral quantitative interpretation through machine learning algorithms to effectively surmount the impacts of logging speed and spectral drift. This machine learning-based approach to energy spectral analysis proved instrumental in enhancing traditional logging speeds to 6 m/min, presenting a novel perspective for the quantitative interpretation of uranium spectral gamma-ray logging at heightened logging speeds.

Background/Introduction: The rapid advancement of computer technologies, along with the significant role of emotions in daily life, has driven interest in intelligent emotion recognition systems. Electroencephalography (EEG) serves as a prominent objective tool in affective computing. However, effectively integrating multichannel EEG spatial and temporal information remains a critical challenge. This study introduces a novel emotion recognition model grounded in cognitive and biological principles, emphasizing the importance of spatiotemporal dynamics in emotional processing. Methods: In this research, brain frequency bands were extracted through wavelet analysis, and the signals within predefined time windows were quantified. These features were then concatenated across distinct brain channels to create a comprehensive matrix representing spatiotemporal brain information. The matrix was characterized using both the summation of matrix cells and the highest singular value to optimize computational costs during classification. The resulting attributes were input into a classification module for emotion detection. Results: Experimental results on the Database for Emotion Analysis using Physiological Signals (DEAP) achieved a maximum accuracy of 89.55%. Conclusions: This work introduces a novel approach to analyzing and classifying EEG signals elicited by various emotional stimuli, demonstrating that the proposed model is competitive with the state-of-the-art classification schemes, thereby paving the way for future development of a robust spatiotemporal-based EEG emotion recognition system. [ABSTRACT FROM AUTHOR]

Developmental coordination disorder is a neurodevelopmental disorder characterized by a marked deterioration in the development of motor and coordination skills that significantly impairs with daily activity and academic performance. Accurate diagnosis of the disease requires extensive testing and long-term observations. These tests and observations can be time-consuming, expensive, incomplete, inaccurate, and subjective. EEG is a strong candidate to overcome these limitations. In this study, an EEG-based deep learning model is presented to support experts in detecting developmental coordination disorder in children from EEG signals. The dataset consists of EEG signals recorded from 16 children without developmental coordination disorder and 16 children with developmental coordination disorder. By calculating the power spectral density values of frequencies between 1-49 hertz of EEG signals using periodogram, welch, and multitaper methods, 49 feature vectors were extracted for each of the spectral analysis methods. Then, the performances of support vector machine (SVM), random forest (RF), k-nearest neighbors (kNN) and longshort-term memory (LSTM) algorithms were compared. After the experiments, the model integrating welch and LSTM algorithm showed the highest performance. The proposed deep learning model achieved promising performance with 0.984 sensitivity, 0.959 specificity, 0.962 precision, 0.973 f1-score, 0.944 Matthews correlation coefficient, and 97.20% accuracy. [ABSTRACT FROM AUTHOR]