Data Processing of a Local Seismological Network for West Texas Seismicity Characterization

2020 ◽  
Vol 91 (6) ◽  
pp. 3469-3482 ◽  
Author(s):  
Dmitrii Merzlikin ◽  
Alexandros Savvaidis ◽  
Stefanie Whittaker ◽  
Ibinabo Bestmann
Keyword(s):  
Template Matching ◽  
Velocity Model ◽  
Seismic Network ◽  
Detection Sensitivity ◽  
Local Network ◽  
Short Term ◽  
West Texas ◽  
Network Sensitivity ◽  
Seismological Network

Abstract We propose a template-matching workflow capable of improving detection sensitivity of a seismic network and demonstrate its performance on the local seismic network comprising Texas Seismological Network installations in West Texas. We use three earthquakes from three clusters as our templates. Template matching is applied to each station independently. Then, SeisComP3 scanloc associator groups the obtained picks into seismic events following moveouts between stations consistent with a velocity model. In comparison to short-term over long-term average detection workflow, the number of “new,” previously undetected events more than doubles. The events detected by the template-matching workflow are registered on a set of stations, thus allowing for their absolute location. Template matching improves local network sensitivity. Among network parameters, station noise conditions appear to have the highest influence on the effectiveness of the workflow.

Persistent, “Mysterious” Seismoacoustic Signals Reported in Oklahoma State during 2019

2021 ◽  
Author(s):  
Joshua D. Carmichael ◽  
Andrew D. Thiel ◽  
Phillip S. Blom ◽  
Jacob I. Walter ◽  
Fransiska K. Dannemann Dugick ◽  
...  
Keyword(s):  
Media Coverage ◽  
Seismic Network ◽  
Acoustic Energy ◽  
Short Term ◽  
Noise Abatement ◽  
National Media ◽  
The Subject ◽  
Seismic Networks ◽  
Dynamic Formation

ABSTRACT We report on the source of seismoacoustic pulses that were observed across the state of Oklahoma (OK) during summer of 2019, and the subject of national media coverage and speculation. Seismic network data collected across four U.S. states and interviews with witnesses to the pulse’s effect on residential structures demonstrate that they were triggered by routine ammunition disposal operations conducted by McAlester Army Ammunition Plant (McAAP). During these operations, conventional explosives destroy obsolete munitions stored in pits through a controlled sequence of electronically timed shots that occur over tens of minutes. Despite noise-abatement efforts that reduce coupling of acoustic energy with air, some lower frequency, subaudible (infrasonic) sound radiates from these shots as discrete pulses. We use nine months of blast log documents, seismic network records, analyst picks, and physical modeling to demonstrate that seismic stations as far as 640 km from McAAP sample these pulses, which record seasonal patterns in stratospheric and tropospheric winds, as well as the dynamic formation of waveguides and shadow zones. Digital short-term average to long-term average detectors that we augment with dynamic thresholds and time-binning operations identify these pulses with a fair probability, when compared with visual observations. Our analyses thereby provide estimates of observation rates for both partial and full sequences of these pulses, as well as single shots. We suggest that disposal operations can exploit existing, composite seismic networks to predict where residents are likely to witness blasting. Crucially, our data also show that dense seismic networks can record multiscale atmospheric processes in the absence of infrasound arrays.

An Earthquake Detection and Location Architecture for Continuous Seismograms: Phase Picking, Association, Location, and Matched Filter (PALM)

2021 ◽  
Author(s):  
Yijian Zhou ◽  
Han Yue ◽  
Lihua Fang ◽  
Shiyong Zhou ◽  
Li Zhao ◽  
...  
Keyword(s):  
Visual Inspection ◽  
Southern California ◽  
Matched Filter ◽  
Seismic Network ◽  
Phase Detection ◽  
Short Term ◽  
Arrival Times ◽  
Earthquake Detection

Abstract We developed an earthquake detection and location architecture for continuous seismograms that incorporates phase picking, phase association, location, and matched-filter techniques (PALM). The PALM architecture incorporates two modules: (1) PAL, the initial detection following picking, association, and location processes, and (2) match, expand, shift, and stack (MESS), a matched-filter detector that augments the template catalog. The effectiveness of PALM is demonstrated in building an early aftershock catalog for the 2019 Ridgecrest, California, earthquake. By comparing with Southern California Seismic Network arrival times, we show that the PAL picker combines the strengths of short-term average/long-term average and the kurtosis picker, realizing robust phase detection and precise picking. Our final MESS catalog is compared with two other matched-filter catalogs by Ross, Idini, et al. (2019) and Shelly (2020). We find that PALM directly recovers unbiased and detailed features in seismicity from continuous seismograms, which can be efficiently implemented to scan continuous waveforms without the need for visual inspection.

Simultaneous Earthquake Detection on Multiple Stations via a Convolutional Neural Network

2020 ◽  
Vol 92 (1) ◽  
pp. 246-260
Author(s):  
Shaobo Yang ◽  
Jing Hu ◽  
Haijiang Zhang ◽  
Guiquan Liu
Keyword(s):  
Event Detection ◽  
Seismic Data ◽  
Template Matching ◽  
Learning Tools ◽  
Data Sampling ◽  
Short Term ◽  
Gas Field ◽  
Earthquake Detection ◽  
Spurious Signals

Abstract In recent years, as the amount of seismic data has grown rapidly, it is very important to develop a fast and reliable event detection and association algorithm. Generally, event detection is first performed on individual stations followed by event association through linking phase arrivals to a common event generating them. This study considers earthquake detection as the problem of image classification and convolutional neural networks (CNNs), as some of the widely used deep-learning tools in image processing, can be well used to solve this problem. In contrast to existing studies training the network using seismic data from individual stations, in this study, we train a CNN model jointly using records of multiple stations. Because the CNN automatically synthesizes information among multiple stations, the detector can more reliably detect seismic events and is less affected by spurious signals. The CNN is trained using aftershock data of the 2013 Mw 6.6 Lushan earthquake. We have applied it on two very different datasets of Gofar transform fault, East Pacific Rise and Changning shale gas field in southern Sichuan basin, China. The tests show that the trained CNN has strong generalization ability and is flexible with the number of available stations, different instrument types, and different data sampling rates. It can detect many more events than the conventional short-term average/long-term average detector and is more efficient than template-matching methods.

Conceptual short-term memory (CSTM) supports core claims of Christiansen and Chater

2016 ◽  
Vol 39 ◽  
Author(s):  
Mary C. Potter
Keyword(s):  
Working Memory ◽  
Rapid Serial Visual Presentation ◽  
Language Comprehension ◽  
Short Term Memory ◽  
Visual Presentation ◽  
Long Term Memory ◽  
Short Term ◽  
Term Memory ◽  
Use Of Knowledge

AbstractRapid serial visual presentation (RSVP) of words or pictured scenes provides evidence for a large-capacity conceptual short-term memory (CSTM) that momentarily provides rich associated material from long-term memory, permitting rapid chunking (Potter 1993; 2009; 2012). In perception of scenes as well as language comprehension, we make use of knowledge that briefly exceeds the supposed limits of working memory.

Ultrastructural investigations of MDL 19,660-induced effects on the canine platelet and megakaryocyte

1990 ◽  
Vol 48 (3) ◽  
pp. 374-375
Author(s):  
D.E. Loudy ◽  
J. Sprinkle-Cavallo ◽  
J.T. Yarrington ◽  
F.Y. Thompson ◽  
J.P. Gibson
Keyword(s):  
Antidepressant Drug ◽  
Beagle Dogs ◽  
Long Term Effects ◽  
Short Term ◽  
Platelet Counts ◽  
Toxicological Studies ◽  
Induced Aggregation ◽  
Internal Architecture

Previous short term toxicological studies of one to two weeks duration have demonstrated that MDL 19,660 (5-(4-chlorophenyl)-2,4-dihydro-2,4-dimethyl-3Hl, 2,4-triazole-3-thione), an antidepressant drug, causes a dose-related thrombocytopenia in dogs. Platelet counts started to decline after two days of dosing with 30 mg/kg/day and continued to decrease to their lowest levels by 5-7 days. The loss in platelets was primarily of the small discoid subpopulation. In vitro studies have also indicated that MDL 19,660: does not spontaneously aggregate canine platelets and has moderate antiaggregating properties by inhibiting ADP-induced aggregation. The objectives of the present investigation of MDL 19,660 were to evaluate ultrastructurally long term effects on platelet internal architecture and changes in subpopulations of platelets and megakaryocytes.Nine male and nine female beagle dogs were divided equally into three groups and were administered orally 0, 15, or 30 mg/kg/day of MDL 19,660 for three months. Compared to a control platelet range of 353,000- 452,000/μl, a doserelated thrombocytopenia reached a maximum severity of an average of 135,000/μl for the 15 mg/kg/day dogs after two weeks and 81,000/μl for the 30 mg/kg/day dogs after one week.

Comparison of Auditory, Language, Memory, and Attention Abilities in Children With and Without Listening Difficulties

2020 ◽  
Vol 29 (4) ◽  
pp. 710-727
Author(s):  
Beula M. Magimairaj ◽  
Naveen K. Nagaraj ◽  
Alexander V. Sergeev ◽  
Natalie J. Benafield
Keyword(s):  
Auditory Processing ◽  
Short Term Memory ◽  
Group Differences ◽  
Long Term Memory ◽  
Short Term ◽  
Significant Group ◽  
Term Memory ◽  
Memory And Attention ◽  
Speed And Accuracy

Objectives School-age children with and without parent-reported listening difficulties (LiD) were compared on auditory processing, language, memory, and attention abilities. The objective was to extend what is known so far in the literature about children with LiD by using multiple measures and selective novel measures across the above areas. Design Twenty-six children who were reported by their parents as having LiD and 26 age-matched typically developing children completed clinical tests of auditory processing and multiple measures of language, attention, and memory. All children had normal-range pure-tone hearing thresholds bilaterally. Group differences were examined. Results In addition to significantly poorer speech-perception-in-noise scores, children with LiD had reduced speed and accuracy of word retrieval from long-term memory, poorer short-term memory, sentence recall, and inferencing ability. Statistically significant group differences were of moderate effect size; however, standard test scores of children with LiD were not clinically poor. No statistically significant group differences were observed in attention, working memory capacity, vocabulary, and nonverbal IQ. Conclusions Mild signal-to-noise ratio loss, as reflected by the group mean of children with LiD, supported the children's functional listening problems. In addition, children's relative weakness in select areas of language performance, short-term memory, and long-term memory lexical retrieval speed and accuracy added to previous research on evidence-based areas that need to be evaluated in children with LiD who almost always have heterogenous profiles. Importantly, the functional difficulties faced by children with LiD in relation to their test results indicated, to some extent, that commonly used assessments may not be adequately capturing the children's listening challenges. Supplemental Material https://doi.org/10.23641/asha.12808607

Abstract #283 Diabetes Increases Short-Term but not Long-Term Risk of Fracture: A Community-Based Study

2019 ◽  
Vol 25 ◽  
pp. 114
Author(s):  
Alyssa Dufour ◽  
Setareh Williams ◽  
Richard Weiss ◽  
Elizabeth Samelson
Keyword(s):  
Short Term ◽  
Community Based ◽  
Risk Of Fracture

Abstract #238: Improved Short Term and Long Term Outcomes of Early Insulin Initiation in Type 2 Diabetes Over 10 Years

2017 ◽  
Vol 23 ◽  
pp. 50
Author(s):  
Jothydev Kesavadev ◽  
Shashank Joshi ◽  
Banshi Saboo ◽  
Hemant Thacker ◽  
Arun Shankar ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Insulin Initiation ◽  
Long Term Outcomes ◽  
Short Term
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