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At least 109 records · Page 6

A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (n rs495828 = 53 and n rs505922 = 59); strongest association with venous embolism, odds ratio (OR rs495828 1.33 (p = 1.32 x 10 –199 ), and thrombosis OR rs505922 1.33, p = 2.2 x10 -265 . Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10 –191 ; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10 –12 . The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10 -23 , lupus OR 0.84, p = 3.97 x 10 –06 . PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10 –13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.

59 BASIC BIOLOGICAL SCIENCES↗

Unusual zwitterionic catalytic site of SARS–CoV-2 main protease revealed by neutron crystallography

The main protease (3CL M pro ) from SARS–CoV-2, the etiological agent of COVID-19, is an essential enzyme for viral replication. 3CL M pro possesses an unusual catalytic dyad composed of Cys 145 and His 41 residues. A critical question in the field has been what the protonation states of the ionizable residues in the substrate-binding active-site cavity are; resolving this point would help understand the catalytic details of the enzyme and inform rational drug development against this pernicious virus. Here, we present the room-temperature neutron structure of 3CL M pro , which allowed direct determination of hydrogen atom positions and, hence, protonation states in the protease. We observe that the catalytic site natively adopts a zwitterionic reactive form in which Cys 145 is in the negatively charged thiolate state and His 41 is doubly protonated and positively charged, instead of the neutral unreactive state usually envisaged. The neutron structure also identified the protonation states, and thus electrical charges, of all other amino acid residues and revealed intricate hydrogen-bonding networks in the active-site cavity and at the dimer interface. The fine atomic details present in this structure were made possible by the unique scattering properties of the neutron, which is an ideal probe for locating hydrogen positions and experimentally determining protonation states at near-physiological temperature. Our observations provide critical information for structure-assisted and computational drug design, allowing precise tailoring of inhibitors to the enzyme's electrostatic environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Bayesian model for multivariate discrete data using spatial and expert information with application to inferring building attributes

When modeling sparsely observed multivariate data, strong prior information elicited from experts can be used to bolster predictive accuracy and counteract sampling bias. Similarly, modeling autocorrelation in space can help make use of co-occurrence patterns present in many types of spatial data. To make use of both expert prior information and spatial structure, we propose a novel graphical model for a spatial Bayesian network developed specifically to address challenges in inferring the attributes of buildings from geographically sparse observational data. This model is implemented as the sum of a spatial multivariate Gaussian random field and a tabular conditional probability function in real-valued space prior to projection onto the probability simplex. This modeling form is especially suitable for the usage of prior information in the form of sets of atomic rules obtained from experts. To perform inference with missing data, we implement a Markov chain Monte Carlo scheme composed of alternating steps of Gibbs sampling of missing entries and Hamiltonian Monte Carlo for model parameters. A case study in building attribution is presented to highlight the advantages and limitations of this approach.

97 MATHEMATICS AND COMPUTING↗

Black hole cannibalism

Here, we consider a version of the Hayden–Preskill thought experiment in which the message thrown into the black hole is itself a smaller black hole. We then discuss the implications of the existence of a recovery channel for this black hole message at asymptotic infinity, resulting in a sharpening of the black hole information paradox for observers who never need to approach a horizon. We suggest decoherence mechanisms as a way of resolving this sharpened paradox.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Temporal Explosion Source Processes of Declared Nuclear Tests in the Democratic People’s Republic of Korea

In this work we highlight a preliminary temporal source analysis of the six declared Democratic People's Republic of Korea (DPRK) nuclear tests. We use regional seismic data to estimate relative source time functions (RSTFs) via iterative time-domain deconvolution (Ammon, 2006; Pippin, 2022) of vertical-component ground motions recorded within 2000 km of the source region. Since RSTFs are ideally independent of site and propagation effects, their amplitude spectrum is equivalent to the source spectral ratio, but they also retain phase information. We compare observed RSTFs (in the time and frequency domains) with synthetic RSTFs derived from the Mueller & Murphy (1971) explosion source model. The resolution of these time functions varies, however, we generally obtain high-quality results within the limitations of the recording broadband instrumentation. The results indicate that this method effectively preserves source time-history information that can be used for temporal analysis of remote nuclear explosions. This preliminary analysis is intended to assess the viability of using time-domain deconvolution methods for extracting temporal source information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

An iterative method to deblend AGN-Host contributions for Integral Field spectroscopic observations

ABSTRACT We present a new iterative deblending method to separate the host galaxy (HG) and their Active Galactic Nuclei (AGNs) emission with the use of Integral Field spectroscopic (IFS) data. The method decomposes the resolved HG emission from the unresolved AGN emission by modelling the two-dimensional surface brightness (SB) profile of the point-spread function (PSF) and the two-dimensional SB HG continuum simultaneously per each monochromatic slide. Our method does not require any prior information about the observed SB profile or a detailed fitting of the PSF, making it ideal for the automatic analysis of large galaxy samples. In this work, we test the quality of our method, its advantages, and its disadvantages. We test our method by using a set of IFS mock data cubes to quantify the reliability of our deblending process and further compare our method with the qdblend3d analysis tool. Furthermore, we applied our method to three data cubes selected from the MaNGA survey according to the dominance of either its HG or its AGN. We show that our deblending method is capable of disengaging the bright, non-resolved AGN emission from the HG continuum and its narrow emission lines. However, the decoupling depends on how well the IFS spatially resolves the PSF, and on the relative flux intensity of the HG-AGN. Therefore, the method is ideal for disentangling the bright-flux contribution from AGN-dominated spectra.

Ibarra-Medel, H. (ORCID:0000000297906313)↗

Discovering Elusive Dynamics Across Frontiers (Final Technical Report)

Profound puzzles, such as the nature of dark matter, the origins of the electroweak scale, the mechanism behind the small neutrino mass, and the strong CP problem, suggested new physics beyond the Standard Model and drove the particle physics program in search of the associated new particles. Despite extensive searches, conventional realizations of new physics have not yet provided conclusive evidence. This raised the serious possibility that new dynamics might be more elusive, perhaps due to a richer gauge and matter structure than previously considered. Notably, the existence of dark matter and advancements in understanding the naturalness problem urged exploration into sectors with complex gauge and matter structures. Through experiments like the LHC, DUNE, and small-scale experiments, the robust US HEP program played a critical role in pursuing these well-motivated but under-explored scenarios for new physics. I explored these physics opportunities in depth, focusing on novel searches and significant improvements in parameter space coverage. The elusive dynamics revealed rich information about the underlying theory and were essential in identifying observable opportunities. Understanding the observable consequences required a deep comprehension of the theory, which I also developed. The proposal included essential components aimed at coherently increasing our knowledge in well-motivated elusive dynamics models. Through research on high-quality axions, composite neutrinos, the Higgs boson as a portal to hidden strong dynamics, and new scalar potentials to generate alternative electroweak phase transitions, I focused on identifying new signatures and parameter regions in plausible elusive dynamics models. The exploration emphasized generic possibilities motivated by broad classes of elusive dynamics models. These signatures were not effectively probed previously due to various challenges such as triggering, background suppression, or experimental design. My research involved close interaction with experimental colleagues to overcome these difficulties, leveraging new theoretical and experimental possibilities. These efforts included identifying new observables such as timing information and substructure in calorimetries, new multiple-hit techniques, new scattering events, and new resonance searches in liquid argon detectors. This work created a positive feedback loop: theory and experimental work inspired each other, revealing new exciting opportunities that supported both programs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High-Precision Characterization of Seismicity from the 2022 Hunga Tonga-Hunga Ha'apai Volcanic Eruption

The earthquake swarm accompanying the January 2022 Hunga Tonga-Hunga Ha'apai (HTHH) volcanic eruption includes a large number of posteruptive moderate-magnitude seismic events and presents a unique opportunity to use remote monitoring methods to characterize and compare seismic activity with other historical caldera-forming eruptions. We compute improved epicentroid locations, magnitudes, and regional moment tensors of seismic events from this earthquake swarm using regional to teleseismic surface-wave cross correlation and waveform modeling. Precise relative locations of 91 seismic events derived from 59,047 intermediate-period Rayleigh- and Love-wave cross-correlation measurements collapse into a small area surrounding the volcano and exhibit a southeastern time-dependent migration. Regional moment tensors and observed waveforms indicate that these events have a similar mechanism and exhibit a strong positive compensated linear vector dipole component. Precise relative magnitudes agree with regional moment tensor moment magnitude ($M_w$) estimates while also showing that event sizes and frequency increase during the days after the eruption followed by a period of several weeks of less frequent seismicity of a similar size. The combined information from visual observation and early geologic models indicate that the observed seismicity may be the result of a complex series of events that occurred after the explosive eruption on 15 January, possibly involving rapid resupply of the magma chamber shortly after the eruption and additional faulting and instability in the following weeks. In addition, we identify and characterize an $M_w$ 4.5 event five days before the paroxysmal explosion on 15 January, indicating that additional seismic events preceding the main eruption could have been identified with improved local monitoring. As a result, our analysis of the HTHH eruption sequence demonstrates the value of potentially utilizing teleseismic surface-wave cross correlation and waveform modeling methods to assist in the detailed analysis of remote volcanic eruption sequences.

58 GEOSCIENCES↗

Contrasting Stratospheric Smoke Mass and Lifetime From 2017 Canadian and 2019/2020 Australian Megafires: Global Simulations and Satellite Observations

Stratospheric injections of carbonaceous aerosols and combustion gases by extreme wildfires have become increasingly common. Recent “megafires,” particularly large and intense fires, delivered particulate burdens to the lower stratosphere comparable to those of moderate volcanic eruptions. The 2017 Canadian megafire generated four large Pyrocumulonimbi (pyroCbs), injecting up to ≈0.3 Tg of smoke in the lower stratosphere. Even more extreme, the 2019/2020 Australian event produced a pyroCb activity resulting in stratospheric smoke intrusions of ≈1 Tg. To understand their contrasting behavior, we present global climate simulations of the atmospheric response to these events, applying smoke burdens informed by remote observations. Model outcomes, compared to satellite data of smoke transport, reproduce reasonably well the initial plume rise, at 0.2–0.3 km/day, attaining heights of ≈20 km in Canada and above 30 km in Australia. Global dispersal of the plume occurs within about 3 weeks in both cases, consistent with observations. Smoke removal timescales, ≈5 months for the Canadian megafire, agree with remote measurements. During the Australian megafire, observations indicate stratospheric injections three times as large, and models predict comparatively longer smoke lifetimes, ≈16 months. After the latter event, atmospheric optical depths and radiative cooling achieved values close to those measured following the Pinatubo eruption. Sensitivity tests of model assumptions indicate, in accord with prior studies, that smoke burden, injection heights, and black carbon content can determine plume evolution and possible climate impacts. An empirical relation between peak heights of stratospheric plumes and lifetimes is derived that can help assess megafire impacts on the stratosphere, climate and the Earth system

54 ENVIRONMENTAL SCIENCES↗

Inference of Multichannel r -process Element Enrichment in the Milky Way Using Binary Neutron Star Merger Observations

Observations of GW170817 strongly suggest that binary neutron star (BNS) mergers produce rapid neutron-capture nucleosynthesis ( r -process) elements. However, it remains an open question whether these mergers can account for all the r -process element enrichment in the Milky Way’s history. Here, we constrain the contributions of the BNS channel using astrophysical neutron star observations. The rate and mass distributions are constrained by LIGO/Virgo/Kagra through the latest catalog GWTC-3, the neutron star equation of state by gravitational-wave, radio, and X-ray observations, and the delay time distribution by short gamma-ray burst (GRB) host galaxy associations. We present a Bayesian framework to consistently combine these observations with abundance information to quantify the contribution and uncertainties of single and multiple astrophysical enrichment sources, and obtain a distribution of per-event BNS r -process element yields consistent with geophysical and astrophysical abundance constraints. We then adopt a Galactic chemical evolution model assuming an instantaneous and fixed amount of Fe enrichment from core-collapse supernovae, and show that BNS-only enrichment scenarios remain inconsistent with the observed r-process abundance trend of disk stars in the Galaxy even with the uncertainties in BNS merger observations. Using stellar abundance observations instead of the short GRB constraints, we can infer a shorter BNS delay time distribution with power-law index α ≤ −2.0 and minimum delay time ${t}_{{\rm{\min }}}\leqslant 40$ Myr at 90% confidence, consistent with detailed Galactic chemical evolution models. Such delay times are in tension with those predicted by standard BNS formation models. Alternatively, we confirm that a two-channel scenario, in which the second channel tracks the star formation history without significant delay, can account for both Galactic stellar and short GRB observations. We estimate that 45%–90% of the r -process abundance in the Milky Way today would have been produced by this star formation-tracking channel, rather than BNS mergers with significant delay times.

gravitational wave astronomy↗

Differentially Private Synthesis and Sharing of Network Data Via Bayesian Exponential Random Graph Models

Abstract Network data often contain sensitive relational information. One approach to protecting sensitive information while offering flexibility for network analysis is to share synthesized networks based on the information in originally observed networks. We employ differential privacy (DP) and exponential random graph models (ERGMs) and propose the DP-ERGM method to synthesize network data. We apply DP-ERGM to two real-world networks. We then compare the utility of synthesized networks generated by DP-ERGM, the DyadWise Randomized Response (DWRR) approach, and the Synthesis through Conditional distribution of Edge given nodal Attribute (SCEA) approach. In general, the results suggest that DP-ERGM preserves the original information significantly better than two other approaches in network structural statistics and inference for ERGMs and latent space models. Furthermore, DP-ERGM satisfies node DP through modeling the global network structure with ERGM, a stronger notion of privacy than the edge DP under which DWRR and SCEA operate.

graph synthesis↗

Spatial Distribution of Ultraviolet Emission from Cometary Activity at 67P/Churyumov-Gerasimenko

The Alice ultraviolet spectrograph on board the Rosetta orbiter provided the first near-nucleus ultraviolet observations of a cometary coma from arrival at comet 67P/Churyumov-Gerasimenko in 2014 August through 2016 September. The characterization of atomic and molecular emissions in the coma revealed the unexpected contribution of dissociative electron impact emission at large heliocentric distances and during some outbursts. This mechanism also proved useful for compositional analysis, and Alice observed many cases that suggested elevated levels of the supervolatile O{sub 2}, identifiable in part to their emissions resulting from dissociative electron impact. In this paper, we present the first two-dimensional UV maps constructed from Alice observations of atomic emission from 67P during an increase in cometary activity on 2015 November 7–8. Comparisons to observations of the background coma and an earlier collimated jet are used to describe possible changes to the near-nucleus coma and plasma. To verify the mapping method and place the Alice observations in context, comparisons to images derived from the MIRO and VIRTIS-H instruments are made. The spectra and maps we present show an increase in dissociative electron impact emission and an O{sub 2}/H{sub 2}O ratio of ~0.3 for the activity; these characteristics have been previously identified with cometary outbursts seen in Alice data. Further, UV maps following the increases in activity show the spatial extent and emission variation experienced by the near-nucleus coma, informing future UV observations of comets that lack the same spatial resolution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Capturing Historic Reliability Performance Through Graph Databases: A Model Based System Engineering Approach

With the goal of improving the performance and reliability of high dependable technological systems such as nuclear power plants, advanced monitoring and health management systems are employed to inform system engineers on observed degradation processes and anomalous behaviors of assets and components. This information is captured in the form of large amount of data which can be heterogenous in nature (e.g., numeric, textual). Such large data availability poses challenges when system engineers are required to parse and analyze them in order to track historic reliability performance of assets and components. This paper tackles directly this challenge by providing means to organize data in the form of a graph: a knowledge graph. The presented approach distinguish itself from current knowledge graph-based methods by the fact that model-based system engineering (MBSE) models are used to “put data into context”. In particular, MBSE models are used as skeleton of a knowledge graph; numeric and textual data elements, once processed, are associated to MBSE model elements. Thus, a knowledge graph captures both system architecture (though MBSE models) and health/performance data. Such feature opens the door to new data analytics methods designed to identify causal relations between observed phenomena.

97 - MATHEMATICS AND COMPUTING↗

Investigation of the 244 Pu ⁢( 48 Ca,𝑥⁢𝑛) 292−𝑥 Fl reaction with the LBNL SHREC detector: Investigation of decay chains of isotopes of flerovium (𝑍=114)

The 244 Pu ⁢( 48 Ca,𝑥⁢𝑛)⁢ 292−𝑥 Fl reaction was investigated at Lawrence Berkeley National Laboratory’s 88 Inch Cyclotron using the Berkeley Gas-filled Separator (BGS), the newly installed Superheavy Recoil detector, along with an upgraded digital electronics and data acquisition system. Seven decay chains were observed starting with an evaporation residue, followed by a single 𝛼 decay and a spontaneous fission. The decay characteristics of these seven decay chains led to an assignment to 288 Fl , the product of the 4⁢𝑛 reaction channel. Two additional chains were (tentatively) assigned to the decay of the 3⁢𝑛 exit channel, 289 Fl . Cross sections for the 4⁢𝑛 and 3⁢𝑛 exit channels were 𝜎 prod =6.7⁢($^{36}_{25}$) pb and 𝜎 prod =1.6⁢($^{22}_{11}$) pb, respectively. Another decay chain, tentatively assigned to the 5⁢𝑛 exit channel through the 48 Ca + 244 Pu reaction or the 3⁢𝑛 exit channel of the 48 Ca + 242 Pu reaction, was also detected. Detailed information regarding the observed decay chains and their nuclear structure aspects is discussed, along with the performance of the BGS and the new detection system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Grid Topology Discovery Algorithm Evaluation of Suitability for Utility Deployment (CRADA 606 Final Report)

This work presents the results of a field-informed demonstration aimed at evaluating the practical suitability of a topology discovery algorithm for utility environments. We demonstrated an algorithm that uses a graph-theory-informed state estimation approach for model selection. In collaboration with Survalent and Peninsula Light Co., the algorithm was applied to real feeder models and field measurements from supervisory control and data acquisition (SCADA) and advanced metering infrastructure (AMI) systems to identify the operational topology of a power distribution system. The demonstration assessed the algorithm’s performance under realistic data conditions, including sparse and noisy measurements, and examined its ability to identify the most likely network configurations. The results confirmed that the approach can effectively narrow down feasible topologies, providing operators with improved situational awareness of network status. Key lessons learned emphasize the need for systematic data validation and strategic sensor placement to enhance observability. These insights inform future deployment strategies and guide refinements for broader adoption in utility operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Strong Lensing by Galaxies

Strong gravitational lensing at the galaxy scale is a valuable tool for various applications in astrophysics and cosmology. Some of the primary uses of galaxy-scale lensing are to study elliptical galaxies’ mass structure and evolution, constrain the stellar initial mass function, and measure cosmological parameters. Since the discovery of the first galaxy-scale lens in the 1980s, this field has made significant advancements in data quality and modeling techniques. In this review, we describe the most common methods for modeling lensing observables, especially imaging data, as they are the most accessible and informative source of lensing observables. We then summarize the primary findings from the literature on the astrophysical and cosmological applications of galaxy-scale lenses. We also discuss the current limitations of the data and methodologies and provide an outlook on the expected improvements in both areas in the near future.

79 ASTRONOMY AND ASTROPHYSICS↗

An integrated integral projection model ( IPM 2 ) to disentangle size‐structured harvest and natural mortality

Abstract Body size is one of the most important traits governing individual‐level demographic rates and modulating population‐level processes. Multiple size‐dependent demographic rates can simultaneously change population structure, so distinguishing their individual contributions to overall population dynamics remains a challenge. Disentangling size‐dependent harvest rates from other demographic rates is critical for assessing the impact of removal on populations of invasive species. Inference about invasive populations can be difficult, however, as observations are often collected opportunistically as part of removal programs, rather than experimentally designed. Yet accurate inference is essential for understanding the feasibility of population suppression and optimising management decisions. We develop an integrated integral projection model (IPM 2 ) that leverages the strengths of the integrated population model and integral projection model to enable inference about complex, size‐structured demographic rates from imperfect observations. We apply the IPM 2 in the context of invasive European green crab ( Carcinus maenas ), a species for which individual body size strongly regulates both the observation‐generating process and latent, population dynamics. The IPM 2 facilitates the distinct estimation of green crab size‐structured harvest and natural mortality rates, parameters for which no explicit data is collected and that are unidentifiable in component datasets of the integrated population model. The model represents how the green crab population changes over time, providing the first estimates of size‐structured abundance of this high‐priority species. By forecasting the stable size distribution and equilibrium population size under varying removal efforts, we demonstrate that extremely high levels of removal effort can reduce the equilibrium green crab population size. Yet these high mortality rates also shift the stable size distribution and increase the equilibrium abundance of smaller crabs, since size‐selective removal alters intraspecific interactions. The ecological outcome of this shift in size structure will be variable, as green crab size modulates only some of its interactions with other species. These results highlight the value of the IPM 2 framework for inferring complex population dynamics with information needs that outpace information in individual observational datasets, providing a path forward for accurate assessment of conservation programs.

Keller, Abigail G. [Department of Environment Scie↗