scholarly journals Statistical analysis of Stromboli VLP tremor in the band [0.1–0.5] Hz: some consequences for vibrating structures

2006 ◽  
Vol 13 (4) ◽  
pp. 393-400 ◽  
Author(s):  
E. De Lauro ◽  
S. De Martino ◽  
M. Falanga ◽  
M. Palo
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Noise Source ◽  
Volcanic Tremor ◽  
Large Data ◽  
Musical Instruments ◽  
Data Set ◽  
Long Period ◽  
Vibrating Structures ◽  
Analyze Time Series

Abstract. We analyze time series of Strombolian volcanic tremor, focusing our attention on the frequency band [0.1–0.5] Hz (very long period (VLP) tremor). Although this frequency band is largely affected by noise, we evidence two significant components by using Independent Component Analysis with the frequencies, respectively, of ~0.2 and ~0.4 Hz. We show that these components display wavefield features similar to those of the high frequency Strombolian signals (>0.5 Hz). In fact, they are radially polarised and located within the crater area. This characterization is lost when an enhancement of energy appears. In this case, the presence of microseismic noise becomes relevant. Investigating the entire large data set available, we determine how microseismic noise influences the signals. We ascribe the microseismic noise source to Scirocco wind. Moreover, our analysis allows one to evidence that the Strombolian conduit vibrates like the asymmetric cavity associated with musical instruments generating self-sustained tones.

A teleseism-specific detection algorithm for single short-period traces

1983 ◽  
Vol 73 (4) ◽  
pp. 1173-1186
Author(s):  
John R. Evans ◽  
Stephen S. Allen
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Vertical Component ◽  
Low Frequency ◽  
Field Studies ◽  
Detection Algorithm ◽  
P Waves ◽  
Data Set ◽  
Short Period ◽  
Worldwide Network

abstract An algorithm for microprocessor-controlled seismographic recorders is described which reliably detects major phases from earthquakes more than 3° from the sensor but rejects noise events and most earthquakes closer than 3°. Unusually large earthquakes within 3° also are detected. The algorithm is applicable to field studies using triggered seismographs to record teleseismic P waves, to worldwide network automation, and to scanning records for teleseisms. It uses two band-pass filtered data streams evolved from a single short-period vertical-component seismometer to differentiate (low-frequency) teleseisms from other signals; the low-frequency band (0.5 to 2.0 Hz) declares “triggers” while the high-frequency band (3.0 to 8.0 Hz) inhibits any of these triggers generated by broadband signals such as local earthquakes. Locally generated noise is usually high frequency and does not excite the low-frequency band. A 16-bit fixed-word-length implementation of this algorithm detected 82 per cent of good P phases (readable to ±0.25 sec) occurring more than 20° from the seismograph, and 50 per cent of earthquakes between 3° and 20°, in a test data set comprising 23 hr of data in 93 segments. The same implementation of the algorithm rejected most noise and 91 per cent of earthquakes within 3° of the seismograph.

scholarly journals Period-luminosity diagram of long period variables in the Magellanic Clouds

2019 ◽  
Vol 631 ◽  
pp. A24 ◽  
Author(s):  
T. Lebzelter ◽  
M. Trabucchi ◽  
N. Mowlavi ◽  
P. R. Wood ◽  
P. Marigo ◽  
...  
Keyword(s):  
Large Data ◽  
Magellanic Clouds ◽  
Asymptotic Giant Branch ◽  
High Mass ◽  
Red Giants ◽  
Agb Stars ◽  
Intermediate Mass ◽  
Data Set ◽  
Long Period ◽  
Long Period Variables

Context. The period-luminosity diagram (PLD) has proven to be a powerful tool for studying populations of pulsating red giants. Gaia Data Release 2 (DR2) provides a large data set including many long-period variables (LPVs) on which this tool can be applied. Aims. We investigate the location of LPVs from the Large and Small Magellanic Clouds in the PLD using various optical and infrared luminosity indicators from Gaia and 2MASS, respectively. We thereby distinguish between stars of different masses and surface chemistry. Methods. The data set taken from the Gaia DR2 catalogue of LPVs allows for a homogeneous study from low- to high-mass LPVs. These sources are divided into sub-populations of asymptotic giant branch (AGB) stars according to their mass and their O- or C-rich nature using the Gaia-2MASS diagram developed by our group. This diagram uses a Wesenheit index WBP, RP based on Wesenheit functions in the Gaia and 2MASS photometric bands. Four different luminosity indicators are used to study the period-luminosity (P–L) relations. Results. We provide the first observational evidence of a P–L relation offset for both fundamental and 1O pulsators between low- and intermediate-mass O-rich stars, in agreement with published pulsation predictions. Among the luminosity indicators explored, sequence C′ is the narrowest in the P–WBP, RP diagram, and is thus to be preferred over the other PLDs for the determination of distances using LPVs. The majority of massive AGB stars and red supergiants form a smooth extension of sequence C of low- and intermediate-mass AGB stars in the P–WBP, RP diagram, suggesting that they pulsate in the fundamental mode. All results are similar in the two Magellanic Clouds.

scholarly journals Observations of volcanic earthquakes and tremor at Deception Island - Antarctica

1999 ◽  
Vol 42 (3) ◽  
Author(s):  
G. Alguacil ◽  
J. C. Almendros ◽  
E. Del Pezzo ◽  
A. Garcia ◽  
J. M. Ibañez ◽  
...  
Keyword(s):  
Volcanic Activity ◽  
High Frequency ◽  
Low Frequency ◽  
Volcanic Tremor ◽  
Shallow Aquifer ◽  
Seismic Events ◽  
Deception Island ◽  
Rapid Phase ◽  
Long Period ◽  
Frequency Phase

Deception Island - South Shetlands, Antarctica is site of active volcanism. Since 1988 field surveys have been carried out with the aim of seismic monitoring, and in 1994 a seismic array was set up near the site of the Spanish summer base in order to better constrain the source location and spectral properties of the seismic events related to the volcanic activity. The array was maintained during the Antarctic summer of 1995 and the last field survey was carried out in 1996. Data show the existence of three different groups (or families) of seismic events: 1) long period events, with a quasi-monochromatic spectral content (1-3 Hz peak frequency) and a duration of more than 50 s, often occurring in small swarms lasting from several minutes to some day; 2) volcanic tremor, with a spectral shape similar to the long period events but with a duration of several minutes (2-10); 3) hybrid events, with a waveform characterised by the presence of a high frequency initial phase, followed by a low frequency phase with characteristics similar to those of the long period events. The high frequency phase of the hybrid events was analysed using polarisation techniques, showing the presence of P waves. This phase is presumably located at short epicentral distances and shallow source depth. All the analysed seismic events show back-azimuths between 120 and 330 degrees from north (corresponding to zones of volcanic activity) showing no seismic activity in the middle of the caldera. Particle motion, Fourier spectral and spectrogram analysis show that the low frequency part of the three groups of the seismic signals have similar patterns. Moreover careful observations show that the high frequency phase which characterises the hybrid events is present in the long period and in the tremor events, even with lower signal to noise ratios. This evidence suggests that long period events are events in which the high frequency part is simply difficult to observe, due to a very shallow source and/or hypocentral distance higher than that of hybrids, while the tremor is composed of rapidly occurring hybrid events. We propose a possible interpretation for the three groups of seismic events. These may be generated by multiple pressure-steps due to the rapid phase change from liquid to vapour in a shallow aquifer which comes in contact with hot materials. The pressure change can put a crack in resonance or excite the generation of multiple surface waves modes in the shallow layered structure.

Some statistical and CI models to predict chaotic high-frequency financial data

2020 ◽  
Vol 39 (5) ◽  
pp. 6419-6430
Author(s):  
Dusan Marcek
Keyword(s):  
Time Series Data ◽  
Moving Average ◽  
Methodological Approach ◽  
Back Propagation ◽  
Large Data ◽  
Series Data ◽  
Data Set ◽  
Training Time ◽  
Optimal Population ◽  
Forecast Time

To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers.

In silico Prediction of Inhibitory Constant of Thrombin Inhibitors Using Machine Learning

2019 ◽  
Vol 21 (9) ◽  
pp. 662-669 ◽  
Author(s):  
Junnan Zhao ◽  
Lu Zhu ◽  
Weineng Zhou ◽  
Lingfeng Yin ◽  
Yuchen Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Regression Tree ◽  
Large Data ◽  
Thrombin Inhibitors ◽  
Coagulation Cascade ◽  
Gradient Boosting ◽  
Support Vector ◽  
Data Set ◽  
Descriptor Selection

Background: Thrombin is the central protease of the vertebrate blood coagulation cascade, which is closely related to cardiovascular diseases. The inhibitory constant Ki is the most significant property of thrombin inhibitors. Method: This study was carried out to predict Ki values of thrombin inhibitors based on a large data set by using machine learning methods. Taking advantage of finding non-intuitive regularities on high-dimensional datasets, machine learning can be used to build effective predictive models. A total of 6554 descriptors for each compound were collected and an efficient descriptor selection method was chosen to find the appropriate descriptors. Four different methods including multiple linear regression (MLR), K Nearest Neighbors (KNN), Gradient Boosting Regression Tree (GBRT) and Support Vector Machine (SVM) were implemented to build prediction models with these selected descriptors. Results: The SVM model was the best one among these methods with R2=0.84, MSE=0.55 for the training set and R2=0.83, MSE=0.56 for the test set. Several validation methods such as yrandomization test and applicability domain evaluation, were adopted to assess the robustness and generalization ability of the model. The final model shows excellent stability and predictive ability and can be employed for rapid estimation of the inhibitory constant, which is full of help for designing novel thrombin inhibitors.

scholarly journals Correlation between the structure and skin permeability of compounds

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ruolan Zeng ◽  
Jiyong Deng ◽  
Limin Dang ◽  
Xinliang Yu
Keyword(s):  
Large Data ◽  
Qsar Model ◽  
Coefficient Of Determination ◽  
Support Vector ◽  
Skin Permeability ◽  
Data Set ◽  
Test Set ◽  
Svm Algorithm ◽  
Svm Model ◽  
Toxicity Relationship

AbstractA three-descriptor quantitative structure–activity/toxicity relationship (QSAR/QSTR) model was developed for the skin permeability of a sufficiently large data set consisting of 274 compounds, by applying support vector machine (SVM) together with genetic algorithm. The optimal SVM model possesses the coefficient of determination R2 of 0.946 and root mean square (rms) error of 0.253 for the training set of 139 compounds; and a R2 of 0.872 and rms of 0.302 for the test set of 135 compounds. Compared with other models reported in the literature, our SVM model shows better statistical performance in a model that deals with more samples in the test set. Therefore, applying a SVM algorithm to develop a nonlinear QSAR model for skin permeability was achieved.

scholarly journals Galaxy spin direction distribution in HST and SDSS show similar large-scale asymmetry

2020 ◽  
Vol 37 ◽  
Author(s):  
Lior Shamir
Keyword(s):  
Large Scale ◽  
Spiral Galaxies ◽  
Hubble Space Telescope ◽  
Gravitational Interaction ◽  
Large Data ◽  
Sloan Digital Sky Survey ◽  
Data Sets ◽  
Dipole Axis ◽  
Data Set ◽  
The Asymmetry

Abstract Several recent observations using large data sets of galaxies showed non-random distribution of the spin directions of spiral galaxies, even when the galaxies are too far from each other to have gravitational interaction. Here, a data set of $\sim8.7\cdot10^3$ spiral galaxies imaged by Hubble Space Telescope (HST) is used to test and profile a possible asymmetry between galaxy spin directions. The asymmetry between galaxies with opposite spin directions is compared to the asymmetry of galaxies from the Sloan Digital Sky Survey. The two data sets contain different galaxies at different redshift ranges, and each data set was annotated using a different annotation method. The results show that both data sets show a similar asymmetry in the COSMOS field, which is covered by both telescopes. Fitting the asymmetry of the galaxies to cosine dependence shows a dipole axis with probabilities of $\sim2.8\sigma$ and $\sim7.38\sigma$ in HST and SDSS, respectively. The most likely dipole axis identified in the HST galaxies is at $(\alpha=78^{\rm o},\delta=47^{\rm o})$ and is well within the $1\sigma$ error range compared to the location of the most likely dipole axis in the SDSS galaxies with $z>0.15$ , identified at $(\alpha=71^{\rm o},\delta=61^{\rm o})$ .

scholarly journals The Complete DNA Sequence of the Mitochondrial Genome of a “Living Fossil,” the Coelacanth (Latimeria chalumnae)

Genetics ◽  
1997 ◽  
Vol 146 (3) ◽  
pp. 995-1010 ◽  
Author(s):  
Rafael Zardoya ◽  
Axel Meyer
Keyword(s):  
Mitochondrial Genome ◽  
Tandem Repeats ◽  
Phylogenetic Analyses ◽  
Large Data ◽  
Molecular Data ◽  
Phylogenetic Position ◽  
Data Set ◽  
Living Fossil ◽  
Latimeria Chalumnae ◽  
Relationship Of

The complete nucleotide sequence of the 16,407-bp mitochondrial genome of the coelacanth (Latimeria chalumnae) was determined. The coelacanth mitochondrial genome order is identical to the consensus vertebrate gene order which is also found in all ray-finned fishes, the lungfish, and most tetrapods. Base composition and codon usage also conform to typical vertebrate patterns. The entire mitochondrial genome was PCR-amplified with 24 sets of primers that are expected to amplify homologous regions in other related vertebrate species. Analyses of the control region of the coelacanth mitochondrial genome revealed the existence of four 22-bp tandem repeats close to its 3′ end. The phylogenetic analyses of a large data set combining genes coding for rRNAs, tRNA, and proteins (16,140 characters) confirmed the phylogenetic position of the coelacanth as a lobe-finned fish; it is more closely related to tetrapods than to ray-finned fishes. However, different phylogenetic methods applied to this largest available molecular data set were unable to resolve unambiguously the relationship of the coelacanth to the two other groups of extant lobe-finned fishes, the lungfishes and the tetrapods. Maximum parsimony favored a lungfish/coelacanth or a lungfish/tetrapod sistergroup relationship depending on which transversion:transition weighting is assumed. Neighbor-joining and maximum likelihood supported a lungfish/tetrapod sistergroup relationship.

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