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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Illuminating the North Korean nuclear explosion test in 2017 using remote infrasound observations

North Korea conducted its sixth underground nuclear explosion test (mb 6.3) on 2017 September 3. The underground explosion produced substantial low-frequency atmospheric waves, which were detected by infrasound arrays located up to a distance of 566 km. These infrasound waves are formed by the conversion of seismic energy to acoustic energy across the lithosphere–atmosphere interface. While infrasound records at regional distances produce estimates of ground motion amplitude over spatially extended regions covering about 26 500 km 2 , 3-D full seismo-acoustic simulations within the lithosphere and atmosphere provide quantitative information about seismo-acoustic energy partitioning. Our results demonstrate the capability of remote infrasound observations combined with 3-D propagation modelling to further develop discrimination methods for underground sources. These results contribute to enhance the confidence of source identification and characterization in nuclear test monitoring research, which is essential for the enforcement of the Comprehensive Nuclear-Test-Ban Treaty.

58 GEOSCIENCES↗
DOE OSTI2022

Evaluating the location capabilities of a regional infrasonic network in Utah, US, using both ray tracing-derived and empirical-derived celerity-range and backazimuth models

SUMMARY More realistic models for infrasound signal propagation across a region can be used to improve the precision and accuracy of spatial and temporal source localization estimates. Motivated by incomplete infrasound event bulletins in the Western US, the location capabilities of a regional infrasonic network of stations located between 84–458 km from the Utah Test and Training Range, Utah, USA, is assessed using a series of near-surface explosive events with complementary ground truth (GT) information. Signal arrival times and backazimuth estimates are determined with an automatic F-statistic based signal detector and manually refined by an analyst. This study represents the first application of three distinct celerity-range and backazimuth models to an extensive suite of realistic signal detections for event location purposes. A singular celerity and backazimuth deviation model was previously constructed using ray tracing analysis based on an extensive archive of historical atmospheric specifications and is applied within this study to test location capabilities. Similarly, a set of multivariate, season and location specific models for celerity and backazimuth are compared to an empirical model that depends on the observations across the infrasound network and the GT events, which accounts for atmospheric propagation variations from source to receiver. Discrepancies between observed and predicted signal celerities result in locations with poor accuracy. Application of the empirical model improves both spatial localization precision and accuracy; all but one location estimates retain the true GT location within the 90 per cent confidence bounds. Average mislocation of the events is 15.49 km and average 90 per cent error ellipse areas are 4141 km2. The empirical model additionally reduces origin time residuals; origin time residuals from the other location models are in excess of 160 s while residuals produced with the empirical model are within 30 s of the true origin time. We demonstrate that event location accuracy is driven by a combination of signal propagation model and the azimuthal gap of detecting stations. A direct relationship between mislocation, error ellipse area and increased station azimuthal gaps indicate that for sparse networks, detection backazimuths may drive location biases over traveltime estimates.

58 GEOSCIENCES↗
DOE OSTI2022

Probabilistic inversion of circular phase spectra: application to two-station phase-velocity dispersion estimation in western Canada

SUMMARY Periodic directional and temporal measurements are common in seismology, and necessitate specific statistical analyses that are appropriate for circular quantities. In this work, we explore the use of a von Mises distribution as a representation of errors on circular seismological observations. Specifically, we automate the estimation of surface-wave phase-velocity dispersion for the teleseismic two-station method, which generally suffers from a 2π phase ambiguity. The use of Bayesian inverse techniques, which aim to rigorously quantify model parameter uncertainty, have become widespread throughout seismology over the last decade. Here, we apply Bayesian inversion to measurements of surface-wave phase spectra in order to estimate 1-D, path-averaged Earth structure between station pairs. The dispersion curve and associated uncertainties are additional results of the inversion, which can then be used as input for subsequent analyses (e.g. tomography). We demonstrate this technique through application to surface-wave recordings from long-running seismic stations throughout western Canada. Our results for over 10 000 station pairs reveal first-order tectonic features consistent with previous studies, which provides confidence in our approach as well as an initial step towards resolving a full 3-D seismic velocity model for the region. This work also presents a foundation for the inversion of surface-wave phase spectra to estimate 3-D Earth structure directly. Finally, the ideas presented in this work are not limited to the inversion of surface-wave phase spectra, but can also be considered for Bayesian geophysical inversion of any circular quantities.

Gosselin, Jeremy M. (ORCID:0000000203754102)↗
DOE OSTI2024

A Pn magnitude scale m b ( Pn ) for earthquakes along the equatorial Mid-Atlantic Ridge

We developed a short-period Pn magnitude scale m b (Pn) for earthquakes along the equatorial Mid-Atlantic Ridge. Due to low signal-to-noise ratios, teleseismic body wave magnitude and long-period surface wave magnitude cannot be confidently determined for small earthquakes of m b < 4. Local magnitude scales are also not useful for these events because the oceanic environment does not allow the propagation of crustal phases. However, regional high-frequency Pn waves from these small- to moderate-size (m b 3–6) earthquakes are well recorded in the equatorial Atlantic region and can be used to assign magnitudes. We measured over 2041 Pn peak amplitudes on vertical records from about 21 stations in northeastern Brazil and 11 stations in western Africa in the distance range of 700–3700 km. We analysed data from 189 events from the global centroid moment tensor catalogue to tie our m b (Pn) scale to M w so that seismic moments can be readily estimated. Pn arrivals show apparent group velocity between 7.9 km s –1 at short ranges (~1000 km) and up to 9.1 km s –1 at 3500 km. The measured peak amplitudes have a frequency between 0.8 and 3 Hz at 1000–1800 km, but at greater distances, 1800–3700 km, they show a remarkably consistent frequency of about 0.8 Hz. The peak amplitude attenuates at a higher rate at short distances (~0.65 magnitude units between 700 and 2000 km) but attenuates at a lower rate at long distances (~0.35 magnitude units between 2000 and 3700 km). The low rate of amplitude decay with distance and nearly constant frequency content of the peak amplitudes suggest that Pn waves propagate efficiently in the lower part of the upper mantle in the equatorial Atlantic Ocean basins. Furthermore, these are important attributes of oceanic Pn waves that can be used to assign magnitude for small- to moderate-size earthquakes in the equatorial mid-Atlantic region. The estimated station corrections correlate well with upper mantle low-velocity anomalies, especially in Brazil.

58 GEOSCIENCES↗
DOE OSTI2024

Localization of infrasonic sources via Bayesian back projection

SUMMARY A Bayesian framework is investigated for event-specific localization of infrasonic sources using back projection ray tracing. Direction-of-arrival information from array-based detection analysis is used to initialize a back projection ray path originating from the detecting array location and quantifying propagation characteristics from hypothetical source locations. The Fisher statistic, computed from the array’s beam coherence, is mapped into uncertainty in the launch angles of the ray path. Auxiliary parameters previously introduced for solving the Transport equation to compute geometric spreading along ray paths are used to map uncertainty in the ray launch angles into spatial and temporal uncertainties in the ray path. An atmospheric ensemble approach is applied to account for atmospheric uncertainty, and the relation between uncertainties in the atmospheric state and confidence in estimated localization are evaluated using several ensembles with specified variances. The method is evaluated using a synthetic event in the western United States constructed via forward propagation simulations as well as a single-station, multi-arrival detection from a surface explosion in the western United States. Localization results using this event-specific approach are more accurate and exhibit improved precision than existing Bayesian localization methods that leverage generalized, pre-computed propagation statistics.

58 GEOSCIENCES↗
DOE OSTI2025

Divide and conquer: separating the two probabilities in seismic phase picking

There are two fundamental probabilities in the seismic phase picking process—the probability of the existence of a seismic phase (detection probability) and the probability associated with the phase arrival time estimation (timing probability). The nearly ubiquitous approach in developing deep learning phase picking models is to use a kernel, such as a truncated Gaussian, to mask the labelled phase arrival time and train a segmentation model. Once a model is trained, the times of the peaks in the output are taken as phase arrival times (picks), and the height of the peaks are taken as ‘probability’ of the picks. Here, we show that this ‘probability’ represents neither the detection nor the timing probability because this approach forces the output to follow the shape of the kernel. We introduce an approach using two models to estimate these two distinct probabilities. We use a binary classifier with a calibrated confidence to address the detection probability and a multiclass classifier to obtain a probability mass function to address the timing probability. This new approach can make the deep learning-based phase picking process more interpretable and provide options to logically control seismic monitoring workflows.

58 GEOSCIENCES↗
DOE OSTI2020

The effect of school intervention programs on the body mass index of adolescents: a systematic review with meta-analysis

Abstract Effective obesity interventions in adolescent populations have been identified as an immediate priority action to stem the increasing prevalence of adult obesity. The purpose of this meta-analysis was to make a quantitative analysis of the impact of school-based interventions on body mass index during adolescence. Studies were retrieved from PubMed, Scopus, Science Direct and Web of Science databases. Results were pooled using a random-effects model with 95% confidence interval considered statistically significant. Of the 18 798 possible relevant articles identified, 12 articles were included in this meta-analysis. The global result showed a low magnitude effect, though it was statistically significant (N = 14 428), global e.s. = −0.055, P = 0.004 (95% CI = −0.092, −0.017). Heterogeneity was low among the studies (I2 = 9.017%). The funnel plot showed no evidence of publication bias. The rank-correlation test of Begg (P = 0.45641) and Egger’s regression (P = 0.19459) confirmed the absence of bias. This meta-analysis reported a significant effect favoring the interventions; however, future research are needed since the reported the evidence was of low magnitude, with the studies following a substantial range of approaches and mostly had a modest methodological quality.

Saavedra Dias, R.↗
DOE OSTI2021

Reduction in total and major cause-specific mortality from tobacco smoking cessation: a pooled analysis of 16 population-based cohort studies in Asia

Little is known about the time course of mortality reduction following smoking cessation in Asians who have smoking behaviours distinct from their Western counterparts. We evaluated the level of reduction in all-cause, cardiovascular disease (CVD) and lung cancer mortality by years since quitting smoking, in Asia. Using Cox regression, we analysed individual participant data (n = 709 151) from 16 prospective cohorts conducted in China, Japan, Korea/Singapore, and India/Bangladesh, separately by cohorts. Cohort-specific hazard ratios (HRs) were combined using a random-effects meta-analysis. During a mean follow-up of 12.0 years, 108 287 deaths were ascertained—35 658 from CVD and 7546 from lung cancer. Among Asian men, a dose-response relationship of risk reduction in deaths from all causes, CVD and lung cancer was observed with an increase in years after smoking cessation. Compared with never smokers, however, all-cause and CVD mortality among former smokers remained elevated 10–14 years after quitting [multivariable-adjusted HR (95% confidence interval (CI) = 1.25 (1.13–1.37) and 1.20 (1.02–1.41), respectively]. Lung cancer mortality stayed almost 2-fold higher than among never smokers 15–19 years after smoking cessation [1.97 (1.41–2.73)], particularly among former heavy smokers [2.62 (1.71–4.00)]. Women who quitted for ≥5 years retained a significantly elevated mortality from all causes, CVD and lung cancer. Overall patterns of the cessation-mortality associations were similar across countries. Our findings suggest that adverse effects of tobacco smoking persist for an extended time period, even for more than two decades, which is beyond the time windows defined in current clinical guidelines for risk assessment of lung cancer and CVD.

Public, Environmental & Occupational Health↗
DOE OSTI2021

Excess deaths reveal the true spatial, temporal and demographic impact of COVID-19 on mortality in Ecuador

Accepted Background In early 2020, Ecuador reported one of the highest surges of per capita deaths across the globe. Methods We collected a comprehensive dataset containing individual death records between 2015 and 2020, from the Ecuadorian National Institute of Statistics and Census and the Ecuadorian Ministry of Government. We computed the number of excess deaths across time, geographical locations and demographic groups using Poisson regression methods. Results Between 1 January and 23 September 2020, the number of excess deaths in Ecuador was 36 402 [95% confidence interval (CI): 35 762–36 827] or 208 per 100 000 people, which is 171% of the expected deaths in that period in a typical year. Only 20% of the excess deaths are attributable to confirmed COVID-19 deaths. Strikingly, in provinces that were most affected by COVID-19 such as Guayas and Santa Elena, the all-cause deaths are more than double the expected number of deaths that would have occurred in a normal year. The extent of excess deaths in men is higher than in women, and the number of excess deaths increases with age. Indigenous populations had the highest level of excess deaths among all ethnic groups. Conclusions Overall, the exceptionally high level of excess deaths in Ecuador highlights the enormous burden and heterogeneous impact of COVID-19 on mortality, especially in older age groups and Indigenous populations in Ecuador, which was not fully revealed by COVID-19 death counts. Together with the limited testing in Ecuador, our results suggest that the majority of the excess deaths were likely to be undocumented COVID-19 deaths.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Identification of 2 Novel Subtypes of Hepatitis C Virus Genotype 8 and a Potential New Genotype Successfully Treated With Direct Acting Antivirals

Abstract Background Hepatitis C virus (HCV) has high genetic diversity and is classified into 8 genotypes and >90 subtypes, with some endemic to specific world regions. This could compromise direct-acting antiviral efficacy and global HCV elimination. Methods We characterized HCV subtypes “rare” in the United Kingdom (non-1a/1b/2b/3a/4d) by means of whole-genome sequencing via a national surveillance program. Genetic analyses to determine the genotype of samples with unresolved genotypes were undertaken by comparison with International Committee on Taxonomy of Viruses HCV reference sequences. Results Two HCV variants were characterized as being closely related to the recently identified genotype (GT) 8, with >85% pairwise genetic distance similarity to GT8 sequences and within the typical intersubtype genetic distance range. The individuals infected by the variants were UK residents originally from Pakistan and India. In contrast, a third variant was only confidently identified to be more similar to GT6 compared with other genotypes across 6% of the genome and was isolated from a UK resident originally from Guyana. All 3 were cured with pangenotypic direct-acting antivirals (sofosbuvir-velpatasvir or glecaprevir-pibrentasvir) despite the presence of resistance polymorphisms in NS3 (80K/168E), NS5A (28V/30S/62L/92S/93S) and NS5B (159F). Conclusions This study expands our knowledge of HCV diversity by identifying 2 new GT8 subtypes and potentially a new genotype.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

In with the old, in with the new: machine learning for time to event biomedical research

The predictive modeling literature for biomedical applications is dominated by biostatistical methods for survival analysis, and more recently some out of the box machine learning approaches. In this article, we show a presentation of a machine learning method appropriate for time-to-event modeling in the area of prostate cancer long-term disease progression. Using XGBoost adapted to long-term disease progression, we developed a predictive model for 118 788 patients with localized prostate cancer at diagnosis from the Department of Veterans Affairs (VA). Our model accounted for patient censoring. Harrell’s c-index for our model using only features available at the time of diagnosis was 0.757 95% confidence interval [0.756, 0.757]. Our results show that machine learning methods like XGBoost can be adapted to use accelerated failure time (AFT) with censoring to model long-term risk of disease progression. Furthermore, the long median survival justifies and requires censoring. Overall, we show that an existing machine learning approach can be used for AFT outcome modeling in prostate cancer, and more generally for other chronic diseases with long observation times.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

Using ensembles and distillation to optimize the deployment of deep learning models for the classification of electronic cancer pathology reports

One of the goals of the Surveillance, Epidemiology, and End Results (SEER) program is to estimate incidence, prevalence, and mortality of all cancers. To that end, cancer registries across the country maintain a massive database of cancer pathology reports which contain rich information to understand cancer trends. However, these reports are stored in the form of unstructured text, and human annotators are required to read and extract relevant information. In this article, we show that existing deep learning models for automating information extraction from cancer pathology reports can be significantly improved by using ensemble model distillation. We found that by training multiple predictive models and transferring their knowledge to a single, low-resource model, we can reduce the number of highly confident wrong predictions. Our results show that our implemented methods could save 1000s of manual annotation hours.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Estimating Bat Fatality at a Texas Wind Energy Facility: Implications Transcending the United States-Mexico Border

Wind energy development causes bat fatalities. Despite emphasis on understanding and reducing these impacts, few data are available for the southwest region of the United States and northern Mexico. We monitored bat fatalities for a full year (March 2017–March 2018) at a wind energy facility in south Texas near the United States–Mexico border. We established search plots of 100-m radius at eight randomly selected turbines (of 255) and searched the roads and pads at an additional 92 turbines. We conducted weekly searches from spring through fall and bimonthly during winter. We used GenEst (Generalized Mortality Estimator) to estimate bat fatalities corrected for searcher efficiency, carcass removal, and density-weighted proportion of area searched. We found 205 bats during standardized searches, the majority of which were Brazilian free-tailed bats (Tadarida brasiliensis, 76%). The corrected fatality estimates were 16 bats/megawatt/year (95% confidence interval [CI]: 12 – 30 bats/megawatt/year) across all species. Species composition at our site is similar to that of northern Mexico, an area of expanding wind energy development with no published studies.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2023

Human papillomavirus–associated anal squamous cell carcinoma: sociodemographic, geographic, and county-level economic trends in incidence rates—United States, 2001-2019

Abstract Background Incidence of anal squamous cell carcinoma is increasing, but vaccination against human papillomavirus (HPV) and removal of precancerous anal lesions could prevent new cases. The overall HPV-associated cancer incidence is reported to be higher in rural populations and in counties with lower economic status. We assessed these differences specifically for HPV-associated anal squamous cell carcinoma and described the geographic, county-level economic, and sociodemographic variations in incidence rates and trends. Methods We analyzed data from the US Cancer Statistics to assess age-standardized incidence rates of HPV-associated squamous cell carcinomas among adults aged 18 years and older from 2001 to 2019. We calculated rate ratios and 95% confidence intervals to examine differences in incidence rates. We also quantified changes in incidence rates over time using joinpoint regression. Results From 2001 to 2019, 72 421 new cases of HPV-associated anal squamous cell carcinoma were diagnosed among women (2.8 per 100 000) and 37 147 among men (1.7 per 100 000). Age-standardized incidence rates were higher in the South compared with other census regions and in counties ranked in the bottom 25% and 25%-75% economically than in the top 25%. The overall incidence rate increased in women but remained stable in men during 2009-2019. Incidence rates increased in adults aged 50 years and older but decreased among those aged 40-44 years from 2001 to 2019 in women and from 2007 to 2019 in men. Conclusions There were inequities in HPV-associated anal squamous cell carcinoma incidence by geographic and county-level economic characteristics. Failure to improve vaccine and treatment equity may widen existing disparities.

Oncology↗
DOE OSTI2020

Epidemiological Studies of Low-Dose Ionizing Radiation and Cancer: Rationale and Framework for the Monograph and Overview of Eligible Studies

Abstract Whether low-dose ionizing radiation can cause cancer is a critical and long-debated question in radiation protection. Since the Biological Effects of Ionizing Radiation report by the National Academies in 2006, new publications from large, well-powered epidemiological studies of low doses have reported positive dose-response relationships. It has been suggested, however, that biases could explain these findings. We conducted a systematic review of epidemiological studies with mean doses less than 100 mGy published 2006–2017. We required individualized doses and dose-response estimates with confidence intervals. We identified 26 eligible studies (eight environmental, four medical, and 14 occupational), including 91 000 solid cancers and 13 000 leukemias. Mean doses ranged from 0.1 to 82 mGy. The excess relative risk at 100 mGy was positive for 16 of 22 solid cancer studies and 17 of 20 leukemia studies. The aim of this monograph was to systematically review the potential biases in these studies (including dose uncertainty, confounding, and outcome misclassification) and to assess whether the subset of minimally biased studies provides evidence for cancer risks from low-dose radiation. Here, we describe the framework for the systematic bias review and provide an overview of the eligible studies.

Berrington de Gonzalez, Amy↗
DOE OSTI2020

A measurement of the Hubble constant from Type II supernovae

ABSTRACT Progressive increases in the precision of the Hubble-constant measurement via Cepheid-calibrated Type Ia supernovae (SNe Ia) have shown a discrepancy of ∼4.4σ with the current value inferred from Planck satellite measurements of the cosmic microwave background radiation and the standard $\Lambda $cold dark matter (ΛCDM) cosmological model. This disagreement does not appear to be due to known systematic errors and may therefore be hinting at new fundamental physics. Although all of the current techniques have their own merits, further improvement in constraining the Hubble constant requires the development of as many independent methods as possible. In this work, we use SNe II as standardisable candles to obtain an independent measurement of the Hubble constant. Using seven SNe II with host-galaxy distances measured from Cepheid variables or the tip of the red giant branch, we derive H$_0= 75.8^{+5.2}_{-4.9}$ km s−1 Mpc−1 (statistical errors only). Our value favours that obtained from the conventional distance ladder (Cepheids + SNe Ia) and exhibits a difference of 8.4 km s−1 Mpc−1 from the Planck + ΛCDM value. Adding an estimate of the systematic errors (2.8 km s−1 Mpc−1) changes the ∼1.7σ discrepancy with Planck +ΛCDM to ∼1.4σ. Including the systematic errors and performing a bootstrap simulation, we confirm that the local H0 value exceeds the value from the early Universe with a confidence level of 95 per cent. As in this work, we only exchange SNe II for SNe Ia to measure extragalactic distances, we demonstrate that there is no evidence that SNe Ia are the source of the H0 tension.

de Jaeger, T.↗
DOE OSTI2020

A study on the statistical significance of mutual information between morphology of a galaxy and its large-scale environment

ABSTRACT A non-zero mutual information between morphology of a galaxy and its large-scale environment is known to exist in Sloan Digital Sky Survey (SDSS) upto a few tens of Mpc. It is important to test the statistical significance of these mutual information if any. We propose three different methods to test the statistical significance of these non-zero mutual information and apply them to SDSS and Millennium run simulation. We randomize the morphological information of SDSS galaxies without affecting their spatial distribution and compare the mutual information in the original and randomized data sets. We also divide the galaxy distribution into smaller subcubes and randomly shuffle them many times keeping the morphological information of galaxies intact. We compare the mutual information in the original SDSS data and its shuffled realizations for different shuffling lengths. Using a t-test, we find that a small but statistically significant (at $99.9{{\ \rm per\ cent}}$ confidence level) mutual information between morphology and environment exists upto the entire length-scale probed. We also conduct another experiment using mock data sets from a semi-analytic galaxy catalogue where we assign morphology to galaxies in a controlled manner based on the density at their locations. The experiment clearly demonstrates that mutual information can effectively capture the physical correlations between morphology and environment. Our analysis suggests that physical association between morphology and environment may extend to much larger length-scales than currently believed, and the information theoretic framework presented here can serve as a sensitive and useful probe of the assembly bias and large-scale environmental dependence of galaxy properties.

Sarkar, Suman↗
DOE OSTI2020

Propagating sample variance uncertainties in redshift calibration: simulations, theory, and application to the COSMOS2015 data

ABSTRACT Cosmological analyses of galaxy surveys rely on knowledge of the redshift distribution of their galaxy sample. This is usually derived from a spectroscopic and/or many-band photometric calibrator survey of a small patch of sky. The uncertainties in the redshift distribution of the calibrator sample include a contribution from shot noise, or Poisson sampling errors, but, given the small volume they probe, they are dominated by sample variance introduced by large-scale structures. Redshift uncertainties have been shown to constitute one of the leading contributions to systematic uncertainties in cosmological inferences from weak lensing and galaxy clustering, and hence they must be propagated through the analyses. In this work, we study the effects of sample variance on small-area redshift surveys, from theory to simulations to the COSMOS2015 data set. We present a three-step Dirichlet method of resampling a given survey-based redshift calibration distribution to enable the propagation of both shot noise and sample variance uncertainties. The method can accommodate different levels of prior confidence on different redshift sources. This method can be applied to any calibration sample with known redshifts and phenotypes (i.e. cells in a self-organizing map, or some other way of discretizing photometric space), and provides a simple way of propagating prior redshift uncertainties into cosmological analyses. As a worked example, we apply the full scheme to the COSMOS2015 data set, for which we also present a new, principled SOM algorithm designed to handle noisy photometric data. We make available a catalogue of the resulting resamplings of the COSMOS2015 galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗