Relational Database for Horizontal-to-Vertical Spectral Ratios

Frequency-dependent horizontal-to-vertical spectral ratios (HVSRs) of Fourier amplitudes from three-component recordings can provide useful information for site response modeling. However, such information is not incorporated into most ground-motion models, including those from Next-Generation Attenuation projects, which instead use the time-averaged shear-wave velocity (VS) in the upper 30 m of the site and sediment depth terms. To facilitate utilization of HVSR, we developed a publicly accessible relational database. This database is adapted from a similar repository for VS data and provides microtremor-based HVSR data (mHVSR) and supporting metadata, but not parameters derived from the data. Users can interact with the data directly within a web portal that contains a graphical user interface (GUI) or through external tools that perform cloud-based computations. Within the database GUI, the median horizontal-component mHVSR can be plotted against frequency, with the mean and mean ± one standard deviation (representing variability across time windows) provided. Using external interactive tools (provided as a Jupyter Notebook and an R script), users can replot mHVSR (as in the database) or create polar plots. These tools can also derive parameters of potential interest for modeling purposes, including a binary variable indicating whether an mHVSR plot contains peaks, as well as the fitted properties of those peaks (frequencies, amplitudes, and widths). Metadata are also accessible, which includes site location, details about the instruments used to make the measurements, and data processing information related to windowing, antitrigger routines, and filtering.

On the Utility of Horizontal-to-Vertical Spectral Ratios of Ambient Noise in Joint Inversion with Rayleigh Wave Dispersion Curves for the Large-N Maupasacq Experiment

Horizontal-to-Vertical Spectral Ratios (HVSR) and Rayleigh group velocity dispersion curves (DC) can be used to estimate the shallow S-wave velocity (VS) structure. Knowing the VS structure is important for geophysical data interpretation either in order to better constrain data inversions for P-wave velocity (VP) structures such as travel time tomography or full waveform inversions or to directly study the VS structure for geo-engineering purposes (e.g., ground motion prediction). The joint inversion of HVSR and dispersion data for 1D VS structure allows characterising the uppermost crust and near surface, where the HVSR data (0.03 to 10s) are most sensitive while the dispersion data (1 to 30s) constrain the deeper model which would, otherwise, add complexity to the HVSR data inversion and adversely affect its convergence. During a large-scale experiment, 197 three-component short-period stations, 41 broad band instruments and 190 geophones were continuously operated for 6 months (April to October 2017) covering an area of approximately 1500km2 with a site spacing of approximately 1 to 3km. Joint inversion of HVSR and DC allowed estimating VS and, to some extent density, down to depths of around 1000m. Broadband and short period instruments performed statistically better than geophone nodes due to the latter’s gap in sensitivity between HVSR and DC. It may be possible to use HVSR data in a joint inversion with DC, increasing resolution for the shallower layers and/or alleviating the absence of short period DC data, which may be harder to obtain. By including HVSR to DC inversions, confidence improvements of two to three times for layers above 300m were achieved. Furthermore, HVSR/DC joint inversion may be useful to generate initial models for 3D tomographic inversions in large scale deployments. Lastly, the joint inversion of HVSR and DC data can be sensitive to density but this sensitivity is situational and depends strongly on the other inversion parameters, namely VS and VP. Density estimates from a HVSR/DC joint inversion should be treated with care, while some subsurface structures may be sensitive, others are clearly not. Inclusion of gravity inversion to HVSR/DC joint inversion may be possible and prove useful.

Effect Of The Horizontal Component Of Earthquake On The Buckling Of Concrete Spherical Shells

The buckling failure of reinforced concrete spherical shell structures under the effect of the horizontal component of earthquake is investigated using a finite element method over a wide range of shell configurations. For this effect, two different loading case scenarios are considered; first, the shell is analyzed under the effects of the vertical seismic component alone. Then, the model is reanalyzed under the same loading conditions plus the horizontal earthquake component, taking into account two different horizontal-to-vertical earthquake spectral ratios. It is concluded that including the horizontal component of earthquake can result in a reduction in the buckling capacity of this type of structure; the impact of which is highly influenced by the horizontal-to-vertical earthquake spectral ratio and the shell geometry. It is also observed that the formulation adopted by ACI slightly overestimates the buckling capacity of spherical shells especially when horizontal seismic effects are included.

Effect Of The Horizontal Component Of Earthquake On The Buckling Of Concrete Spherical Shells

The buckling failure of reinforced concrete spherical shell structures under the effect of the horizontal component of earthquake is investigated using a finite element method over a wide range of shell configurations. For this effect, two different loading case scenarios are considered; first, the shell is analyzed under the effects of the vertical seismic component alone. Then, the model is reanalyzed under the same loading conditions plus the horizontal earthquake component, taking into account two different horizontal-to-vertical earthquake spectral ratios. It is concluded that including the horizontal component of earthquake can result in a reduction in the buckling capacity of this type of structure; the impact of which is highly influenced by the horizontal-to-vertical earthquake spectral ratio and the shell geometry. It is also observed that the formulation adopted by ACI slightly overestimates the buckling capacity of spherical shells especially when horizontal seismic effects are included.

Fluid activity detection in geothermal areas using a single seismic station by monitoring horizontal-to-vertical spectral ratios

Subsurface structure survey based on horizontal-to-vertical (H/V) spectral ratios is widely conducted. The major merit of this survey is its convenience to obtain a stable result using a single station. Spatial variations of H/V spectral ratios are well-known phenomena, and it has been used to estimate the spatial fluctuation in subsurface structures. It is reasonable to anticipate temporal variations in H/V spectral ratios, especially in areas like geothermal fields, carbon capture and storage fields, etc., where rich fluid flows are expected, although there are few reports about the temporal changes. In Okuaizu Geothermal Field (OGF), Japan, dense seismic monitoring was deployed in 2015, and continuous monitoring has been consistent. We observed the H/V spectral ratios in OGF and found their repeated temporary drops. These drops seemed to be derived from local fluid activities according to a numerical calculation. Based on this finding, we examined a coherency between the H/V spectral ratios and fluid activities in OGF and found a significance. In conclusion, monitoring H/V spectral ratios can enable us to grasp fluid activities that sometimes could lead to a relatively large seismic event.

Determination of clemastine by the HPLC method in the blood

Topicality. Сlemastine fumarate (tavegil)-1-methyl-2 [2-α-methyl-p-chlorobenzhydryloxy)-ethyl]-pyrrolidine fumarate is the first generation H1-histamine receptor blocker. Сlemastine fumarate selectively inhibits histamine H1 receptors and reduces capillary permeability. The drug has a pronounced anti-allergic and antipruritic effect. Clemastine prevents the development of vasodilation and the smooth muscle contraction induced by histamine. Сlemastine fumarate has an isignificant anticholinergic activity, causes sedation. The drug is used to treat pruritus in psoriasis, multiple sclerosis and optic neuritis. Clemastine is characterized by the following side effects: increased fatigue, drowsiness, sedation, weakness, lethargy, impaired coordination of movements; nausea, vomiting, decreased blood pressure, palpitations, hemolytic anemia, skin rash, anaphylactic shock. In case of an overdose, the drug has a neurotoxic effect, which manifests itself in impaired consciousness with the development of generalized anticholinergic convulsive syndrome. The urgent task for monitoring the treatment effectiveness of the population with сlemastine fumarate and diagnosis of drug intoxication is the choice of highly sensitive and selective research methods of its analysis in pharmaceuticals and biological matrices during the treatment. Aim. To develop an algorithm for directed analysis of clemastine in biological extracts from the blood using a unified method of the HPLC research. Materials and methods. The extraction of clemastine was performed with chloroform at Ph 9.0. The extracts were purified from impurities by a combination of TLC and extraction with hexane. The TLC purification and identification of clemastine were carried out under optimal conditions: the system of organic solvents – methanol – 25 % solution of ammonium hydroxide (100 : 1.5) and chromatographic plates – Sorbfil PTLC-AF-A, Rf сlemastine = 0.60 ± 0.03. To detect clemastine, the most sensitive location reagents were used –UV light (λ = 254 nm) and Dragendorff’s reagent modified by Mounier. The chromatographic analysis was performed on a “Milichrome A-02” microcolumn liquid chromatograph (EkoNova, Closed Joint-Stock Company, Russia) under standardized HPLC conditions: the reversed-phase variant using a metal column with a non-polar absorbent Prontosil 120-5C 18 AQ, 5 μm; the mobile phase in the linear gradient mode – from eluent А (5 % acetonitrile and 95 % buffer solution – 0.2 М solution of lithium perchlorate in 0.005 М solution of perchloric acid) to eluent B (100 % acetonitrile) for 40 min. Regeneration of the column was conducted for 2 min with the mixture of solvents; the flow rate of the mobile phase was 100 μl/min, the injection volume – 4 μl. The multichannel detection of the substance was performed using a two-beam multi-wave UV spectrophotometer at 8 wavelengths of 210, 220, 230, 240, 250, 260, 280, and 300 nm; the optimal value of the column temperature – 37-40 °С and the pump pressure – 2.8-3.2 MPa. Results and discussion. Isolation of clemastine from the blood was performed according to the method developed, including the extraction with chloroform at pH 9.0; the extraction purification of extracts with hexane from impurities; the TLC purification and identification of clemastine. Using the unified HPLC method clemastine was identified by retention parameters and spectral ratios. For the quantitative determination, a calibration graph or the straight line equation corresponding to this graph were used. The results obtained indicated the reliability and reproducibility of the method. It was found that the relative uncertainty of the average result in the analysis of clemastine in the blood was ε = ± 4.63 %, the relative standard deviation of the average result was RSDx = 1.67 %. Conclusions. Clemastine was extracted with chloroform at pH 9.0 from the blood. Purification of extracts from co-extractive compounds was performed by combining TLC and extraction with hexane. It has been found that when isolating сlemastine from the blood according to the methods developed it is possible to determine 36.05-39.55 % of the substance (ε = ± 4.63 %, RSDx = 1.67 %). The method of TLC purification and identification of сlemastine in biogenic extracts was tested under the optimal conditions: the system of organic solvents – methanol – 25 % solution of ammonium hydroxide (100 : 1.5), the use of reagents – UV light, Dragendorff’s reagent modified by Mounier, Rf сlemastine = 0.60 ± 0.03 (Sorbfil PTLC-AF-A). The unified HPLC method for identification and quantification of сlemastine was tested in biogenic extracts from the blood according to the algorithm of the directed analysis developed. It has been found that сlemastine can be identified by the retention time – 25.997-26.011 min; the retention volume – 2599.7-2601.1 μl; spectral ratios – 0.741; 0.536; 0.096; 0.023; 0.027; 0.005; 0.003. The сlemastine content was determined by the equation S = 0.15 · 10-3 С + 0.14 · 10-3; the correlation coefficient was equal to 0.9998. Chromatographic methods can be recommended for implementation in practice of the Bureau of Forensic Medical Examination, poison control centers, clinical laboratories regarding the study of medicinal substances in biological objects.

H/V spectral ratios at the InSight landing site using ambient noise and Marsquake records

<p>The InSight mission landed on Mars on November 26th, 2018 and its seismometer, the Seismic Experiment for Interior Structure (SEIS), has recorded continuous Martian seismic data since February 2019, consisting of mainly ambient seismic noise but also hundreds of seismic events.</p><p>We used the SEIS data to study the horizontal-to-vertical spectral ratios from both the ambient seismic noise (nHV) and the seismic events (eHV), for frequencies above 0.6 Hz, in order to get further constraints on the first tens of meters at the Insight landing site. The nHV curve was obtained by using data segments of 50 s over more than 400 Sols. The preferred nHV curve is observed during the northern spring and summer at low wind levels and it is a mostly flat curve with a prominent trough around ~2.4 Hz. Outside of these time periods, the nHV curve is contaminated with artificial peaks likely related to lander modes. On the other hand, the eHV curve was created using 336 seismic events with quality either A, B or C, as defined by the Marsquake Service. For each seismic event, we computed the signal-to-noise ratio (SNR) at each frequency and only frequencies with SNR>3 were used to obtain the final eHV curve. In addition to the 2.4 Hz trough, the final eHV curve shows a strong peak around 8 Hz, which is not observed from the ambient noise data possibly due to a lack of seismic energy in this frequency band able to excite it.</p><p>A preliminary inversion of the eHV curve, considering the fundamental mode of the Rayleigh wave only, shows that the 2.4 Hz trough and the 8 Hz peak can be explained by a shear-wave velocity model increasing from the surface to a depth of 5-8 m (likely the boundary between the regolith and coarse ejecta), in good agreement with previous analysis based on compliance observations, hammering measurements and satellite images. At this depth, a discontinuity leading to a higher velocity layer is observed, which is followed by a deeper low-velocity layer about 20 m thick. The modeling assuming body waves only or a full diffuse seismic wavefield is currently under investigation.</p>