Spectral Ratio Research Articles

Optimizing alteration mineral detection: A fusion of multispectral and hyperspectral remote sensing techniques in the Sar-e-Chah-e Shur, Iran

The Sar-e-Châh-e-Shur region in the Lut Block of eastern Iran has significant potential for diverse ore mineral deposits, particularly copper and iron mineralization. This study used multispectral remote sensing data, including ASTER, Sentinel 2, and Landsat 8 for detecting alteration zones associated with ore mineralization in the study area. Spectral ratios associated with porphyry copper-iron alterations and advanced argillic-iron alterations were utilized to establish training data, supplemented by hyperspectral data processing derived from Hyperion (spaceborne) and HyMap (airborne) sensors. Several classification algorithms were implemented, and evaluation metrics such as the Kappa coefficient and overall accuracy were calculated using a confusion matrix to assess classification performance. Field validation was conducted through thin mineral section analysis and geochemical stream sediment data, yielding a Normalized Score (NS) for conformity estimation. Notably, the Landsat 8, ASTER, and Sentinel 2 - classes category 2 -artificial neural networks-thresholds 2 (LAS-2-ANN2) class (representing advanced argillic alterations) was achieved a high score of 3.5, corresponding to an 87.5% match to the geological evidence. In addition, hyperspectral data processing using artificial neural network algorithms was yielded an overall score of 2.43, indicating a 61% match. In conclusion, this investigation highlighted the efficacy of fusing multispectral and hyperspectral data for accurate mineral alteration mapping in high potential regions, offering valuable insights for future exploration campaigns.

3D shear wave velocity imaging of the subsurface structure of granite rocks in the arid climate of Pan de Azúcar, Chile, revealed by Bayesian inversion of HVSR curves

Abstract. Seismic methods are emerging as efficient tools for imaging the subsurface to investigate the weathering zone. The structure of the weathering zone can be identified by differing shear wave velocities as various weathering processes will alter the properties of rocks. Currently, 3D subsurface modelling of the weathering zone is gaining increasing importance as results allow the identification of the weathering imprint in the subsurface not only from top to bottom but also in three dimensions. We investigated the 3D weathering structure of monzogranite bedrock near the Pan de Azúcar National Park (Atacama Desert, northern Chile), where the weathering is weak due to the arid climate conditions. We set up an array measurement that records seismic ambient noise, which we used to extract the horizontal-to-vertical spectral ratio (HVSR) curves. The curves were then used to invert for 1D shear wave velocity (Vs) models, which we then used to compile a pseudo-3D model of the subsurface structure in our study area. To invert the 1D Vs model, we applied a transdimensional hierarchical Bayesian inversion scheme, allowing us to invert the HVSR curve with minimal prior information. The resulting 3D model allowed us to image the granite gradient from the surface down to ca. 50 m depth and confirmed the presence of dikes of mafic composition intruding the granite. We identified three main zones of fractured granite, altered granite, and the granite bedrock in addition to the mafic dikes with relatively higher Vs. The fractured granite layer was identified with Vs of 1.4 km s−1 at 30–40 m depth, while the granite bedrock was delineated with Vs of 2.5 km s−1 and a depth range between 10 and 50 m depth. We compared the resulting subsurface structure to other sites in the Chilean coastal cordillera located in various climatic conditions and found that the weathering depth and structure at a given location depend on a complex interaction between surface processes such as precipitation rate, tectonic uplift and fracturing, and erosion. Moreover, these local geological features such as the intrusion of mafic dikes can create significant spatial variations to the weathering structure and therefore emphasize the importance of 3D imaging of the weathering structure. The imaged structure of the subsurface in Pan de Azúcar provides the unique opportunity to image the heterogeneities of a rock preconditioned for weathering but one that has never experienced extensive weathering given the absence of precipitation.

Validity of Acoustic Measures Obtained Using Various Recording Methods Including Smartphones With and Without Headset Microphones.

The goal of this study was to assess various recording methods, including combinations of high- versus low-cost microphones, recording interfaces, and smartphones in terms of their ability to produce commonly used time- and spectral-based voice measurements. Twenty-four vowel samples representing a diversity of voice quality deviations and severities from a wide age range of male and female speakers were played via a head-and-thorax model and recorded using a high-cost, research standard GRAS 40AF (GRAS Sound & Vibration) microphone and amplification system. Additional recordings were made using various combinations of headset microphones (AKG C555 L [AKG Acoustics GmbH], Shure SM35-XLR [Shure Incorporated], AVID AE-36 [AVID Products, Inc.]) and audio interfaces (Focusrite Scarlett 2i2 [Focusrite Audio Engineering Ltd.] and PC, Focusrite and smartphone, smartphone via a TRRS adapter), as well as smartphones direct (Apple iPhone 13 Pro, Google Pixel 6) using their built-in microphones. The effect of background noise from four different room conditions was also evaluated. Vowel samples were analyzed for measures of fundamental frequency, perturbation, cepstral peak prominence, and spectral tilt (low vs. high spectral ratio). Results show that a wide variety of recording methods, including smartphones with and without a low-cost headset microphone, can effectively track the wide range of acoustic characteristics in a diverse set of typical and disordered voice samples. Although significant differences in acoustic measures of voice may be observed, the presence of extremely strong correlations (rs > .90) with the recording standard implies a strong linear relationship between the results of different methods that may be used to predict and adjust any observed differences in measurement results. Because handheld smartphone distance and positioning may be highly variable when used in actual clinical recording situations, smartphone + a low-cost headset microphone is recommended as an affordable recording method that controls mouth-to-microphone distance and positioning and allows both hands to be available for manipulation of the smartphone device.

Site Response in the Walnut Creek–Concord Region of San Francisco Bay, California: Ground-Motion Amplification in a Fault-Bounded Basin

ABSTRACT 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.

Maximization of cytochrome C oxidase enzyme activity by optimizing color conversion from red organic light-emitting diodes

Photobiomodulation (PBM) therapy using red and near-infrared (NIR) light can effectively activate cytochrome C oxidase (CCO) enzyme to promote wound healing in living organisms. To maximize this therapeutic effect, the use of a light source with a spectrum absorbed by the CCO enzyme is necessary. A red/NIR light source optimized for CCO enzyme was obtained by partially color-converting a red organic light-emitting diode with copper indium sulfide/zinc sulfide quantum dots (QDs). To increase color conversion efficiency, the dispersion of QDs was improved by using a fibrous color conversion layer (FCCL). By optimizing the QD content in the FCCL, a red/NIR light source similar to the absorption spectrum of CCO enzyme was obtained with a spectral matching ratio of 81.7 %. When this light source was used in PBM therapy, it was experimentally verified that it showed a much faster wound closure effect compared to general red light, and it was proven that this was due to increased activity of the CCO enzyme. This study is a method of obtaining a red/NIR light source for PBM suitable for a specific enzyme performing a specific function, and is particularly useful due to its excellent form factor of being large, thin, and flexible.

Identification of Ground Vulnerability Based on Kg, PGA, and GSS Assessment by Single Station Microtremor in Bendosari Hamlet, Kalasan Village, Yogyakarta

Bendosari Hamlet, Kalasan, Yogyakarta is a research area that is one of the areas affected by the earthquake that occurred on May 27, 2006. The earthquake with a magnitude of 6.4 caused quite severe damage to buildings around the research area. Based on the phenomenon of earthquakes that have occurred, there needs to be further study related to vulnerable areas in the event of another earthquake. Research data is primary data taken using a single statiun microtremor tool with an overall acquisition point of 50 measurement points. This study aims to find out the value of seismic vulnerability index (Kg), Peak Ground Acceleration (PGA), and Ground Shear Strain (GSS). Using the Horizontal to Vertical Spectral Ratio (HVSR) method, the dominant frequency result (f0) and amplification factor value (A0) from data that has been recorded through the microtremor tool. Based on research that has been done, the results are obtained in the f0rm of seismic vulnerability index values that are in the range of 0.49 - 30.18, the value of the acceleration of ground movement is in the range of 0.21 - 0.61 Gal, and the ground shear strain value is in the range of 4 x 10-6 to 38 x 10-5. Point K26 which is the original documentation of buildings affected by the earthquake, analyzed that the value of Vs of 858.112 m / s on the vs ground profile indicates that there is hard soil at a depth after 27.2 m. This shows that the thickness of subsurface sedimentary rocks at point K26 is quite thick. Keywords: Bendosari Hamlet; Mikrotremor; GSS; HVSR; PGA; Seismic Vulnerability

On-Site Earthquake Early Warning Model for Selected Records in the NGA-West2 Dataset Using S- and P-Wave Spectral Ratios

ABSTRACT 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 R3P 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 RFP 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.

Inferring the Focal Depths of Small Earthquakes in Southern California Using Physics-Based Waveform Features

ABSTRACT 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, Φ≡log10(M0)+3log10(fc), 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.

High-resolution spatial elastic wave velocity variation detected using multiple-linear-array microtremor measurements

We propose a method for capturing the near-surface elastic wave velocity variation using microtremors. The proposed method does not directly estimate the velocity of the medium; instead, it measures the spatial velocity change. We apply the stretching method, which is often used to detect the time variation of shear wave velocity based on the monitoring of seismic ambient noise, to microtremor recordings. Because spatially dense ambient noise records are unavailable, we performed microtremor measurements using multiple linear arrays with multiple sensors along the survey line to collect as many recordings as possible. The synchronised microtremor recordings of each array were used to compute the horizontal-to-vertical spectral ratio (H/V), cross-correlation (CC), autocorrelation (AC), and single-station cross-correlation (SC). The H/V ratio and the waveforms of these correlation functions showed significant spatial variation. The velocity variation was measured quantitatively using the stretching method, which correlates a compressed and stretched reference function with each function on the line. The velocity variation of the vertical and radial components of CC compares well with the variation of the H/V peak, indicating that the radial components of CC retrieved the Rayleigh-wave Green’s function. The waveforms of AC and SC also showed spatial variation but the measured value of velocity change was smaller than that for CC. Further investigation is awaited to conclude if this is due to low-quality data or inappropriate measurement conditions. The reliability of the velocity change was confirmed by comparing the results to dispersion curves obtained using the conventional array method.

Application of microtremor H/V spectral ratio method in determining characteristic parameters of typical laterite sites

Microtremor signals contain rich geophysical information, and the application of microtremor measurements in determining site characteristic parameters is increasingly valued because of their advantages of simple operation, environmental friendliness, and low cost. In this study, systematic microtremor measurements were conducted at a typical laterite site. The microtremor measurement data were processed with different combinations of horizontal components using the H/V spectral ratio method(H: Horizontal frequency domain signal of the microtremor; V: Vertical frequency domain signal of the microtremor). to take the HVSR curve. The period corresponding to the peak of the HVSR curve was considered to be the predominant period of the site, the site classifications were determined, and geotechnical types were divided. This study indicates that the microtremor H/V spectral ratio method is highly consistent with the results of borehole exploration for determining site classifications and dividing geotechnical types. Moreover, using the combination of vectors sum of East-West direction and North-South direction as horizontal components in the microtremor H/V spectral ratio method can more easily and accurately determine the site-predominant period.

Analysis of submarine seismic ambient noise data in Bohai Sea and Yellow Sea and its application

Submarine seismic ambient noise imaging combines current marine and on-land seismic detection technologies. Based on data from several broadband shallow-sea type ocean bottom seismometers (SOBSs) deployed in the Bohai Sea and north Yellow Sea, this paper analyzes the characteristics of the submarine seismic ambient noise and explores the theory, technology, method and application of the submarine seismic ambient noise imaging by using the single point horizontal and vertical spectral ratio method (HVSR). The observations yield the following results: 1) Submarine seismic ambient noise has consistent and constant energy, making it an appropriate passive seismic source for submarine high frequency surface wave investigation. 2) Using the HVSR approach, a single three-component OBS could differentiate between the basement and sediments. Array seismic observation could be utilized to extract the frequency dispersion curve and invert it to obtain the velocity structure for more accurate stratification. 3) The SOBS we use is suitable for submarine surface wave exploration. 4) Tomography results with greater resolution and deeper penetration could be obtained by combining the use of active and passive sources in a simultaneous inversion of the HVSR and frequency dispersion curve. Seamless land-to-ocean seismic research can be accomplished with submarine seismic ambient noise imaging technologies.

Assessment of Site Effects and Numerical Modeling of Seismic Ground Motion to Support Seismic Microzonation of Dushanbe City, Tajikistan

In the territory of Dushanbe city, the capital of Tajikistan, detailed geological and geophysical data were collected during geophysical surveys in 2019–2020. The data comprise 5 microtremor array measurements, 9 seismic refraction tomography profiles, seismological data from 5 temporary seismic stations for standard spectral ratio calculations, 60 borehole datasets, and 175 ambient noise measurements. The complete dataset for Dushanbe was used to build a consistent 3D geologic model of the city with a size of 12 × 12 km2. The results of the seismological and geophysical surveys were compared and calibrated with borehole data to define the boundaries of each layer in the study area. The Leapfrog Works software was utilized to create a 3D geomodel. From the 3D geomodel, we extracted six 12 km long 2D geological cross-sections. These 2D geological cross-sections were used for 2D dynamic numerical modeling with the Universal Distinct Element Code software to calculate the local seismic response. Finally, the dynamic numerical modeling results were compared with the amplification functions obtained from the seismological and ambient noise data analysis. The 2D dynamic numerical modeling results allowed a better assessment of the site effects in the study area to support seismic microzonation and the determination of local peak ground acceleration changes in combination with regional seismic hazard maps. In addition, our results confirm the strong seismic amplification effects noted in some previous studies, which are attributed to the influence of local topographic and subsurface characteristics on seismic ground motions.

Seismic characterisation of the subsoil under a historic building: Cathedral Church of Saint Mary in Murcia case study

This research focuses on the Cathedral Church of Saint Mary in Murcia, Spain, which is located in a moderate-to-high seismic risk zone in the Spanish context. The study uses geophysical techniques and geotechnical investigation to characterise seismic ground models at the building's scale, aiming to understand the real amplification of the ground under seismic effect in historic buildings. Three soil layers (silt, sand with gravel, and gravel) were identified through core borings. Multichannel Analysis of Surface Waves (MASW) profiles and Mini-array profiles revealed Vs values of 305 ± 32 m/s, 296 ± 62 m/s, and 440 ± 38.5 m/s, respectively, for these materials. Seismic Refraction Tomography (SRT) showed Vp values of 586 ± 73 m/s, 700 m/s, and 1466 ± 489 m/s for the corresponding layers. The horizontal-to-vertical spectral ratio (HVSR) approach identified a ground predominant period ranging from 0.37 to 0.38 s. Another significant peak at 2.3 s is observed, probably associated to the Triassic basement. Three seismic events with magnitudes Mw between 4.9 and 5.1 were used as inputs to determine the amplification factor (AF). The results indicate a PGA amplification factor between 1.7 and 2.1. These results contribute to the conservation and mitigation of seismic risk of this cultural heritage generating input data that enables precise computation of the soil-structure interaction.

Enhancement of the NORAD-Atomic-Data Database in Plasma

We report recent enhancements to the online atomic database at the Ohio State University, NORAD-Atomic-Data, that provide various parameters for radiative and collisional atomic processes dominant in astrophysical plasma. NORAD stands for Nahar Osu RADiative. The database belongs to the data sources, especially for the latest works, of the international collaborations of the Opacity Project and the Iron Project. The contents of the database are calculated values for energies, oscillator strengths, radiative decay rates, lifetimes, cross-sections for photoionization, electron-ion recombination cross-sections, and recombination rate coefficients. We have recently expanded NORAD-Atomic-Data with several enhancements over those reported earlier. They are as follows: (i) We continue to add energy levels, transition parameters, cross-sections, and recombination rates for atoms and ions with their publications. (ii) Recently added radiative atomic data contain a significant amount of transition data for photo-absorption spectral features corresponding to the X-ray resonance fluorescence effect, showing prominent wavelength regions of bio-signature elements, such as phosphorus ions, and emission bumps of heavy elements, such as of lanthanides, which may be created in a kilonova event. We are including (iii) collisional data for electron-impact-excitation, (iv) experimental data for energies and oscillator strengths for line formation, (v) experimental cross-sections for photoionization that can be applied for benchmarking and other applications, and (vi) the introduction of a web-based interactive feature to calculate spectral line ratios at various plasma temperature and density diagnostics, starting with our recently published data for P II. We presented a summary description of theoretical backgrounds for the computed data in the earlier paper. With the introduction of experimental results in the new version of NORAD, we present a summary description of measurement of high-resolution photoionization cross-sections at an Advanced Light Source of LBNL synchrotron set-up and briefly discuss other set-ups. These additions should make NORAD-Atomic-Data more versatile for various applications. For brevity, we provide information on the extensions and avoid repetition of data description of the original paper.

Renal calculus composition analysis using dual-energy CT: a prospective observational study

BackgroundTo analyze preoperatively the composition of renal calculi using dual-energy computed tomography (DECT) and compare it with reference standard biochemical stone analysis.MethodsEighty-one participants who were diagnosed with renal calculi underwent DECT at 80 kVp and 140 kVp. Spectral analysis was performed, and the energy map generated was used to classify the calculus based on available preset data. Average Hounsfield units (HU) were calculated for the two energy levels, and ratio of HU was derived (DE ratio) and calculus was categorized into different stone compositions. Hounsfield units of each calculus was measured at 120 kVp standard dose CT, and Hounsfield density (HU/largest transverse diameter) was derived. Comparison of results of spectral analysis and DE ratio was done and correlated with the biochemical laboratory analysis as reference standard wherever available.ResultsSpectral analysis and CT prediction of stone were performed for all 81 patients. CT prediction of stone based on DE ratio into “uric acid,” “struvite,” “calcium oxalate” and “calcium carbonate apatite” was performed. Assessment of stone composition by biochemical analysis was done for 65 patients who eventually underwent PCNL for stone extraction.Both DE ratio and spectral analysis were able to differentiate calculus into various types based on composition with statistically significant p values. However, spectral analysis proved to be marginally better in renal stone characterization particularly for mixed stones. The DE ratio for uric acid stones was derived as 0.9–1.1, 0.9–2.3 for mixed stones and 1.0–2.4 for calcium stones.ConclusionsSpectral analysis promises a practical approach to predicting calculus composition preoperatively, thereby avoiding unnecessary surgical intervention.

Lunar Surface Resource Exploration: Tracing Lithium, 7 Li and Black Ice Using Spectral Libraries and Apollo Mission Samples

This is an exercise to explore the concentration of lithium, lithium-7 isotope and the possible presence of black dirty ice on the lunar surface using spectral data obtained from the Clementine mission. The main interest in tracing the lithium and presence of dark ice on the lunar surface is closely related to future human settlement missions on the moon. We investigate the distribution of lithium and 7 Li isotope on the lunar surface by employing spectral data from the Clementine images. We utilized visible (VIS–NIR) imagery at wavelengths of 450, 750, 900, 950 and 1000 nm, along with near-infrared (NIR–SWIR) at 1100, 1250, 1500, 2000, 2600 and 2780 nm, encompassing 11 bands in total. This dataset offers a comprehensive coverage of about 80% of the lunar surface, with resolutions ranging from 100 to 500 m, spanning latitudes from 80°S to 80°N. In order to extract quantitative abundance of lithium, ground-truth sites were used to calibrate the Clementine images. Samples (specifically, 12045, 15058, 15475, 15555, 62255, 70035, 74220 and 75075) returned from Apollo missions 12, 15, 16 and 17 have been correlated to the Clementine VIS–NIR bands and five spectral ratios. The five spectral ratios calculated synthesize the main spectral features of sample spectra that were grouped by their lithium and 7 Li content using Principal Component Analysis. The ratios spectrally characterize substrates of anorthosite, silica-rich basalts, olivine-rich basalts, high-Ti mare basalts and Orange and Glasses soils. Our findings reveal a strong linear correlation between the spectral parameters and the lithium content in the eight Apollo samples. With the values of the 11 Clementine bands and the 5 spectral ratios, we performed linear regression models to estimate the concentration of lithium and 7 Li. Also, we calculated Digital Terrain Models (Altitude, Slope, Aspect, DirectInsolation and WindExposition) from LOLA-DTM to discover relations between relief and spatial distribution of the extended models of lithium and 7 Li. The analysis was conducted in a mask polygon around the Apollo 15 landing site. This analysis seeks to uncover potential 7 Li enrichment through spallation processes, influenced by varying exposure to solar wind. To explore the possibility of finding ice mixed with regolith (often referred to as `black ice’), we extended results to the entire Clementine coverage spectral indices, calculated with a library (350–2500 nm) of ice samples contaminated with various concentrations of volcanic particles.

Seismic Discrimination Between Nuclear Explosions and Natural Earthquakes using Multi-Machine Learning Techniques

AbstractIn the field of seismic signal analysis, it is of utmost importance to accurately differentiate between earthquakes and underground nuclear explosions. As a contribution for the verification regime of the Comprehensive Nuclear Test Ban Treaty (CTBT), Various methods have been employed for this purpose, including Complexity, Spectral ratio, mb—Ms (body wave and surface wave magnitudes), and corner frequency of P and S waves. These discrimination techniques have been examined to manually identify natural seismic events from nuclear explosions across different regions worldwide, such as China, India, Pakistan, North Korea, and the United States. To gather the necessary data, a comprehensive dataset comprising nuclear explosions and earthquakes of the same magnitude range (4 ≤ mb ≤ 6.5) of 35 seismic events from 1945 to 2017 has been compiled from the International Research Institute for Seismology (IRIS) using broadband and long period seismic stations. The objective of this study is to employ a range of linear and nonlinear Machine Learning (ML) models with the aim of automatically distinguishing between underground nuclear explosions and large earthquakes to enhance the accuracy of manual feature extraction. For this purpose, time domain waveforms and different classifier techniques focused on feature extraction have been used. The ML models employed include logistic regression, K-nearest neighbours classifier, decision tree classifier, random forest classifier, voting classifier, and Naive Bayes. The outcomes of the ROC and AUC analyses were employed to validate the validity of our proposed discrimination algorithm. The results show that the Random Forest Classifier is the most effective model, obtaining 100% accuracy in the case of feature extraction, while the best model for the time domain waveform classifier that achieved 75.5% accuracy is the voting classifier.

Damage detection of thin plates by fusing variational mode decomposition and spectral entropy

This paper presents a new approach for damage detection in thin plates by fusing variational mode decomposition and spectral entropy (VMD-SE). In this method, after the received signal is decomposed into some intrinsic mode functions (IMFs) by variational mode decomposition (VMD), the spectral entropy ratio of the first and last IMFs is calculated for optimizing the VMD’s parameters and improving its decomposition performance. Moreover, the cross-correlation coefficient between the decomposed IMFs and the reference signal is computed to separate the desired IMF, which contains more damage information. Finally, the spectral entropy of the obtained IMF is calculated as an indicator for assessing the damage’s severity. The comparative analysis of the simulated signal clearly shows that only the proposed method can successfully separate the damage-related and reference signals. To verify the VMD-SE method, damage detection of two different types of damage on aluminum and composite fiber-reinforced polymer (CFRP) plates is conducted by using this new approach. The experimental results demonstrate that the parameters of VMD affect greatly its decomposition performance, and the best parameters are selected. The results also indicate that the normalized spectral entropy monotonically increases when the diameter of the through-hole or the length of the scratch increases. In addition, the correlation coefficients of the fitting lines of the plates are larger than 0.998. The experimental results of aluminum specimens demonstrate that the damage’s location has an influence on the normalized spectral entropy. At last, based on the linear relationship, the severity of damage in the fourth specimen is identified. The identification results demonstrate that the relative error of the aluminum and CFRP plates is less than 7.34%, which indicates that this new algorithm by fusing VMD and spectral entropy can detect the damage size in thin plates accurately and efficiently.

Electron and ion temperature measurement with a new x-ray imaging crystal spectrometer on WEST.

A new x-ray imaging crystal spectrometer (XICS) has been installed, aligned, and used during experimental campaigns on the WEST tokamak. It has three interchangeable crystals for measuring the Ar XVII, Ar XVIII, and Fe XXV spectra, respectively. A patented rotating table holding the crystals is used to monitor the crystal facing the plasma remotely and without changing the position of the camera. Here, the focus is made on the Ar XVII spectrum, between 3.93 and 4.00 Å. The design of the diagnostic is presented, and a synthetic diagnostic, implemented with the Python library ToFu, is used to show the instrument's operational performance and limits. The instrument function exhibits the following two main features: a distortion for the Ar XVII spectrum, presumably due to the crystal manufacturing in two parts, and the measurement of three W spectral lines on the Ar XVI spectrum. Line of sight-integrated profiles of the electron and ion temperatures are thus extracted from the Ar XVII spectrum from two distinct spectral line ratios and from the Doppler broadening, respectively. The bremsstrahlung emission and the W line measurements are the two main limitations to compute the electron temperature. Tomographic inversions are also implemented with the library ToFu and used in order to obtain the local electron and ion temperature profiles, which are compared to other measurements from the WEST ECE (electron cyclotron emission) diagnostic. It is shown that both the XICS line-integrated and ECE Te measurements are in better agreement. Systematic differences are shown between the electron temperature profiles calculated from the two available line ratios.

Site effect evaluation for Culiacan, Sinaloa, Mexico

Using the spectral ratio technique (HVSR), we performed an analysis of 120 seismic noise records obtained at different points distributed throughout the city of Culiacán, Sinaloa, México. The results show a clear relationship of dominant periods between 0.2 to 0.7 for the alluvium zone in the central and western area of the city and minor periods for points near outcrops of igneous rocks south and southeast of the city. The higher relative amplitudes were found along the riverbed, in the transition zone of conglomerate deposits to alluvium. We performed a multichannel analysis (station arrays) at some points in which we also measured H/V. Afterward, we produced velocity profiles were obtained and transfer functions were calculated. Five of these values were compared with the HVSR technique. Three of them could be compared with the surficial startigraphy obtained in soil mechanics studies to which access was granted.