62 research outputs found
Global multiple-frequency seismic tomography using teleseismic and core-diffracted body waves
Seismic tomography is the pre-eminent tool for imaging the Earth's interior. Since the advent of this method in the 1980's, the internal structure of Earth has been vastly sampled and imaged at a variety of scales, and the resulting models have served as the primary means to investigate the processes driving our planet. Significant recent advances in seismic data acquisition and computing power have drastically progressed tomographic methods. Broad-band seismic waveforms can now be simulated up to the highest naturally occurring frequencies and consequently, measurement techniques can exploit seismic waves in their entire usable spectrum and in multiple frequencies.
This dissertation revolves around aspects of global multiple-frequency seismic tomography, from retrieving and processing of large seismological data sets to explore the multi-scale structure of the earth. The centrepiece of this work is an efficient processing strategy to assemble the largest possible data sets for waveform-based tomographic inversions. Motivated by the complex but loosely-constrained structure of the lowermost mantle, we aim to increase the spatial resolution and coverage of the mantle in all depths by extracting a maximum of information from observed seismograms.
We first present a method that routinely measures finite-frequency traveltimes of Pdiff waves by cross-correlating observed waveforms with synthetic seismograms across the broad-band frequency range. Large volumes of waveform data of ~ 2000 earthquakes are retrieved and pre-processed using fully automatic software built for this purpose. Synthetic seismograms for these earthquakes are calculated by semi-analytical wave propagation through a spherically symmetric earth model, to 1 Hz dominant frequency. This way, we construct one of the largest core-diffracted P wave traveltime collections so far with a total of 479,559 traveltimes in frequency passbands ranging from 30.0 to 2.7 s dominant period. Projected onto their core-grazing ray segments, the Pdiff observations recover major structural, lower-mantle heterogeneities known from existing global mantle models.
An inversion framework with adaptive parameterisation and locally-adjusted regularisation is developed to accurately map the information of this data set onto the desired model parameters. This broad-band waveform inversion seamlessly incorporates the Pdiff measurements alongside a very large data set of conventional teleseismic P and PP measurements. We obtain structural heterogeneities of considerable detail in all mantle depths. The mapped features confirm several previously imaged structures. At the same time, sharper outlines for several subduction systems (e.g., Tethyan, Aegean and Farallon slabs) and uprising mantle plumes (e.g., Iceland, Afar and Tristan da Cunha) appear in our model. We trace some of these features throughout the mantle to investigate their morphological characteristics in a large (whole-mantle) context. Moreover, we report the structural findings revealed by our model. This ranges from geometries of slab complexes and subdivisions of Large Low Shear Velocity Provinces at the root of the mantle to tomographic evidence to support the existence of deep-mantle plumes beneath Iceland and Tristan da Cunha
ObspyDMT: a Python toolbox for retrieving and processing large seismological data sets
We present obspyDMT, a free, open-source software toolbox for the query, retrieval, processing and management of seismological data sets, including very large, heterogeneous and/or dynamically growing ones. ObspyDMT simplifies and speeds up user interaction with data centers, in more versatile ways than existing tools. The user is shielded from the complexities of interacting with different data centers and data exchange protocols and is provided with powerful diagnostic and plotting tools to check the retrieved data and metadata. While primarily a productivity tool for research seismologists and observatories, easy-to-use syntax and plotting functionality also make obspyDMT an effective teaching aid. Written in the Python programming language, it can be used as a stand-alone command-line tool (requiring no knowledge of Python) or can be integrated as a module with other Python codes. It facilitates data archiving, preprocessing, instrument correction and quality control-routine but nontrivial tasks that can consume much user time. We describe obspyDMT's functionality, design and technical implementation, accompanied by an overview of its use cases. As an example of a typical problem encountered in seismogram preprocessing, we show how to check for inconsistencies in response files of two example stations. We also demonstrate the fully automated request, remote computation and retrieval of synthetic seismograms from the Synthetics Engine (Syngine) web service of the Data Management Center (DMC) at the Incorporated Research Institutions for Seismology (IRIS)
Subducted lithosphere under South America from multifrequency p wave tomography
We analyze mantle structure under South America in the DETOX-P1 seismic tomography model, a global-scale, multifrequency inversion of teleseismic P waves. DETOX-P1 inverts the most extensive data set of broadband, waveform-based traveltime measurements to date, complemented by analyst-picked traveltimes from the ISC-EHB catalog. The mantle under South America is sampled by ∼665,000 cross-correlation traveltimes measured on 529 South American broadband stations and on 5,389 stations elsewhere. By their locations, depths, and geometries, we distinguish four high-velocity provinces under South America, interpreted as subducted lithosphere (“slabs”). The deepest (∼1,800–1,200 km depth) and shallowest (<600 km) slab provinces are observed beneath the Andean Cordillera near the continent’s northwest coast. At intermediate depths (1,200–900 km, 900–600 km), two slab provinces are observed farther east, under Brazil, Bolivia and Venezuela, with links to the Caribbean. We interpret the slabs relative to South America’s paleo-position over time, exploring the hypothesis that slabs sank essentially vertically after widening by viscous deformation in the mantle transition zone. The shallowest slab province carries the geometric imprint of the continental margin and represents ocean-beneath-continent subduction during Cenozoic times. The deepest, farthest west slab complex formed under intra-oceanic trenches during late Jurassic and Cretaceous times, far west of South America’s paleo-position adjoined to Africa. The two intermediate slab complexes record the Cretaceous transition from westward intra-oceanic subduction to eastward subduction beneath South America. This geophysical inference matches geologic records of the transition from Jura-Cretaceous, extensional “intra-arc” basins to basin inversion and onset of the modern Andean arc ∼85 Ma
A Deep Learning Approach to Geographical Candidate Selection through Toponym Matching
Recognizing toponyms and resolving them to their real-world referents is required to provide advanced semantic access to textual data. This process is often hindered by the high degree of variation in toponyms. Candidate selection is the task of identifying the potential entities that can be referred to by a previously recognized toponym. While it has traditionally received little attention, candidate selection has a significant impact on downstream tasks (i.e. entity resolution), especially in noisy or non-standard text. In this paper, we introduce a deep learning method for candidate selection through toponym matching, using state-of-the-art neural network architectures. We perform an intrinsic toponym matching evaluation based on several datasets, which cover various challenging scenarios (cross-lingual and regional variations, as well as OCR errors) and assess its performance in the context of geographical candidate selection in English and Spanish. </p
Isolated Intraconal Meningioma
Purpose: To report a rare case of isolated intraconal meningioma.
Case Report: A 24-year-old woman presented with painless proptosis in her left eye which started and progressed during her pregnancy about 10 months ago. Hertel exophthalomometry revealed anterior displacement of the globe with 4 mm of proptosis which was remarkable. Magnetic resonance imaging (MRI) demonstrated an intraconal circumscribed oval-shaped mass with hypointense signals on T1- weighted images and hyperintense signals on T2-weighted images, mimicking cavernous hemangioma. This mass, however, was free of any connections to optic nerve or bones. Due to the imaging characteristics, more prevalent diagnoses like cavernous hemangioma were placed on the top of the differential diagnoses list. However, during the surgical excision, the tumor’s consistency and gross features were not compatible with cavernous hemangioma. The pathologic findings instead determined meningotheliomatous meningioma, a very rare condition, which was far from our expectations prior to the surgery.
Conclusion: Ectopic orbital meningiomas are rare tumors that are not easily diagnosed without postoperative histopathology. Despite its low prevalence, they should be considered in the differential diagnosis list of intraconal masses with hypointense signals on T1-weighted images and hyperintense signals on T2- weighted images
Living Machines: A study of atypical animacy
This paper proposes a new approach to animacy detection, the task of determining whether an entity is represented as animate in a text. In particular, this work is focused on atypical animacy and examines the scenario in which typically inanimate objects, specifically machines, are given animate attributes. To address it, we have created the first dataset for atypical animacy detection, based on nineteenth-century sentences in English, with machines represented as either animate or inanimate. Our method builds on recent innovations in language modeling, specifically BERT contextualized word embeddings, to better capture fine-grained contextual properties of words. We present a fully unsupervised pipeline, which can be easily adapted to different contexts, and report its performance on an established animacy dataset and our newly introduced resource. We show that our method provides a substantially more accurate characterization of atypical animacy, especially when applied to highly complex forms of language use
AxiSEM3D: broad-band seismic wavefields in 3-D global earth models with undulating discontinuities
We present a novel numerical method to simulate global seismic wave propagation in realisticaspherical 3-D earth models across the observable frequency band of global seismic data. Ourmethod, named AxiSEM3D, is a hybrid of spectral element method (SEM) and pseudospectralmethod. It describes the azimuthal dimension of global wavefields with a substantially reducednumber of degrees of freedom via a global Fourier series parametrization, of which the numberof terms can be locally adapted to the inherent azimuthal complexity of the wavefields.AxiSEM3D allows for material heterogeneities, such as velocity, density, anisotropy andattenuation, as well as for finite undulations on radial discontinuities, both solid–solid andsolid–fluid, and thereby a variety of aspherical Earth features such as ellipticity, surfacetopography, variable crustal thickness, undulating transition zone and core–mantle boundarytopography. Undulating discontinuities are honoured by means of the ‘particle relabellingtransformation’, so that the spectral element mesh can be kept spherical. The implementation ofthe particle relabelling transformation is verified by benchmark solutions against a discretized3-D SEM, considering ellipticity, topography and bathymetry (with the ocean approximatedas a hydrodynamic load) and a tomographic mantle model with an undulating transition zone.For the state-of-the-art global tomographic models with aspherical geometry but without a 3-Dcrust, efficiency comparisons suggest that AxiSEM3D can be two to three orders of magnitudefaster than a discretized 3-D method for a seismic period at 5 s or below, with the speed-upincreasing with frequency and decreasing with model complexity. We also verify AxiSEM3Dfor localized small-scale heterogeneities with strong perturbation strength. With reasonablecomputing resources, we have achieved a corner frequency of up to 1 Hz for 3-D mantlemodels
Exclusive Seismoacoustic Detection and Characterization of an Unseen and Unheard Fireball Over the North Atlantic
Small meteoroids that enter Earth's atmosphere often go unnoticed because their detection and characterization rely on human observations, introducing observational biases in space and time. Acoustic shockwaves from meteoroid ablation convert to infrasound and seismic energy, enabling fireball detection using seismoacoustic methods. We analyzed an unreported fireball in 2022 near the Azores, recorded by 26 seismometers and two infrasound arrays. Through polarization analyses, array methods, and 3‐D ray‐tracing, we determined that the terminal blast occurred at 40 km altitude, ∼60 km NE of São Miguel Island. This location matches an unidentified flash captured by a lightning detector aboard the GOES‐16 satellite. The estimated kinetic energy is ∼10−3 kT TNT equivalent, suggesting a 10−1 m object diameter, thousands of which enter the atmosphere annually. Our results demonstrate how geophysical methods, in tandem with satellite data, can significantly improve the observational completeness of meteoroids, advancing our understanding of their sources and entry processes
Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019
BACKGROUND: The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. METHODS: We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. FINDINGS: In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. INTERPRETATION: The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rheumatoid arthritis and upsurging new cases of other five IMIDs, respectively. FUNDING: The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation. The project funded by Scientific Research Fund of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (2022QN38)
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