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At least 469 records · Page 26

HydraGNN 2.0

HydraGNN is an Oak Ridge National Laboratory (ORNL)-branded implementation of distributed multi-tasking graph neural networks that supports several scientific applications within the ORNL portfolio to support the US-DOE mission. New or improved capabilities included in v2.0.0 release are as follows: 1) Enhancement in message passing layers through class inheritance 2) Adding transformation to ensure translation and rotation invariance 3) Supporting various optimizers 4) Atomic descriptors 5) Integration with continuous CI test 6) Distributed printouts and timers 7) Profiling 8) Support of ADIOS2 for scalable data loading 9) Large-scale system support, including Summit (ORNL) and Perlmutter (NERSC)

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗

pnnl-predictive-phenomics/csc052-gem

Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Bacillus These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity.

Torres, Victor E.↗

pnnl-predictive-phenomics/csc031-gem

Genome-Scale Metabolic Model of CarbStor Community member Microbacterium (csc031) Continuous Validation with Memote These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity

McNaughton, Andrew [@PNNL]↗

pnnl-predictive-phenomics/csc009-gem

Genome-Scale Metabolic Model of CarbStore Community member Curtobacterium (csc009) Continuous Validation with Memote These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity

Lin, Tesia↗

pnnl-predictive-phenomics/csc040-gem

Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Rhodococcus These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity.

McNaughton, Andrew [@PNNL]↗

pnnl-predictive-phenomics/csc043-gem

Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Paenibacillus These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity.

Zucker, Jeremy [Pacific Northwest National Laborat↗

kynema-fmb [SWR-23-07]

Kynema-FMB (FKA: Kynema) is an open-source performance portable flexible multibody (FMB) dynamics solver designed for time-domain simulations. While originally tailored for wind turbine structural dynamics, the formulation and implementation are those of a general flexible-multidbody dynamics solver that can readily be applied to a wide range of systems. Kynema was designed with a narrow focus, namely to provide a lightweight, fast, accurate FMD solver for coupling to computational-fluid-dynamics (CFD) codes, especially the CFD codes in the Kynema suite, for fluid-structure-interaction (FSI) simulations. Kynema-FMB is equipped to model systems that can be represented as a collection of beams and rigid bodies that are connected through constraints. Degrees of freedom are defined in the inertial/global frame of reference and include displacements and rotations (formally as rotation matrices, but stored as quaternions). The underlying formulation is built on a Lie-group time integrator designed for index-3 differential-algebraic equations, which is second-order accurate in time (Bruls et al., 2012). Beam models are based on geometrically exact beam theory and are discretized as high-order spectral finite elements similar to those in BeamDyn (Wang et al., 2017). The governing equations for a FMD system like a wind turbine constitute a highly nonlinear system of constrained partial-differential equations. Kynema-FMB uses analytical Jacobians in the nonlinear-system solves in each time step. Linear systems use sparse storage and several third-party sparse-linear-system solvers are enabled. Ill conditioning of linear systems is mitigated with preconditioning described in Bottasso et al, 2008. Kynema-FMB is integrated with a simple open-source controller (ROSCO). There is an application programming interface (API) for coupling to geometry-resolved CFD (like that in Sharma et al., 2023) and actuator-force CFD (like that in Kuhn et al., 2025). In the latter, for actuator-line models, Kynema-FMB includes an internal blade-element solver that depends on user-provided lookup tables for coefficients of lift and drag, i.e., aerodynamic polars. Kynema-FMB is written in C++ and leverages Kokkos and Kokkos-Kernels (KokkosEcosystem) as its performance portability layer enabling simulations on both CPU and GPU systems. The repository is equipped with extensive automated testing at the unit and regression/system levels. The following describes the high-level development objectives conceived for Kynema: *Kynema will follow modern software development best practices, including test-driven development (TDD), version control, hierarchical automated testing, and continuous integration (CI) for a robust development environment. *The core data structures are memory efficient and enable vectorization and parallelization at multiple levels. *Data structures are data-oriented to exploit methods for accelerated computing including high utilization of chip resources (e.g., single instruction multiple data (SIMD) instruction sets) and parallelization using GP-GPUs. *The computational algorithms incorporate robust open-source libraries for mathematical operations, resource allocation, and data management. *The API design considers multiple stakeholder needs and ensure integration with existing and future ecosystems for data science, machine learning, and AI. *Kynema-FMB is written in modern C++ and leverages Kokkos as its performance-portability library with inspiration from the kynema stack.

Sprague, MichaelA.↗

Open Source Software Prevalence Ingest Tool

The OSSP Ingest Tool accepts user-input organizational information, ingests IT/OT asset lists in Excel format, and ingests the associated CycloneDX SBOM's. It then performs analytics demonstrating the ability to answer the follow research questions: o RQ1. Ability to identify all OSS services running on, and all OSS components present within, an OT device o RQ1a: Ability to differentiate multiple versions of the same OSS component within each OT device. o RQ1b: Ability to differentiate running from not-running OSS components. o RQ1c: Ability to differentiate based on the originator of the component, because a supplier may have modified it after retrieval from the upstream software source. o RQ2. Ability to correlate the identity of a single OSS component across multiple OT devices, mitigating common name variations such as differences in capitalization, '-' vs '_', and so on. o RQ3. Ability to perform subset analysis of OSS components across multiple OT devices o RQ3a: Ability to perform subset analysis across OSS libraries, generating density & distribution graphs to identify commonly-used libraries and outliers. o RQ3b: Ability to perform subset analysis of a single OSS library, generating density & distribution by CI sector, by device type, by device make/model, and/or by firmware version. o RQ3c: Ability to perform subset analysis by grouping OSS libraries according to programming language, then overlay with RQ4b. o RQ3d: Ability to perform subset analysis by OSS upstream source, providing insight into degree of modifications performed by suppliers. o RQ4. Ability to identify dependencies (transitive and direct) of each differentiated OSS library within each OT device, and enable RQ1,2,3 iteratively for dependencies. o RQ1. Ability to identify all OSS services running on, and all OSS components present within, an OT device o RQ1a: Ability to differentiate multiple versions of the same OSS component within each OT device. o RQ1b: Ability Page

Kapadia, Shayna [Lawrence Livermore National Labor↗

kessel

Kessel is a tool to create and drive continuous integration (CI) and developer workflows through a unified interface across multiple code projects and environments. It serves as a driver and integration layer for build systems and package managers, providing a flexible library of reusable components to build and execute complex workflows consistently.

Berger, Richard [@lanl]↗

Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality, however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from Chronic Renal Insufficiency Cohort (CRIC), Singapore Study of Macro-Angiopathy and Reactivity in Type 2 Diabetes (SMART2D), and the Pima Indian Study determined if urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in CRIC (HR 1.57, 1.18, 2.10) and SMART2D (HR 1.77, 1.00, 3.12). ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in CRIC (HR 2.36, 1.26, 4.39), SMART2D (HR 2.39, 1.08, 5.29), and Pima Indian study (HR 4.57, CI 1.37-13.34). Empagliflozin lowered UAdCR in non-macroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology and transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mammalian target of rapamycin (mTOR). Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

60 APPLIED LIFE SCIENCES↗

Radiosonde Observations of Environments Supporting Deep Moist Convection Initiation during RELAMPAGO-CACTI

The Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) and Cloud, Aerosol, and Complex Terrain Interactions (CACTI) projects deployed a high-spatiotemporal-resolution radiosonde network to examine environments supporting deep convection in the complex terrain of central Argentina. This study aims to characterize atmospheric profiles most representative of the near-cloud environment (in time and space) to identify the mesoscale ingredients affecting storm initiation and growth. Spatiotemporal autocorrelation analysis of the soundings reveals that there is considerable environmental heterogeneity, with boundary layer thermodynamic and kinematic fields becoming statistically uncorrelated on scales of 1–2 h and 30 km. Using this as guidance, we examine a variety of environmental parameters derived from soundings collected within close proximity (30 km in space and 30 min in time) of 44 events over 9 days where the atmosphere either: 1) supported the initiation of sustained precipitating convection, 2) yielded weak and short-lived precipitating convection, or 3) produced no precipitating convection in disagreement with numerical forecasts from convection-allowing models (i.e., Null events). There are large statistical differences between the Null event environments and those supporting any convective precipitation. Null event profiles contained larger convective available potential energy, but had low free-tropospheric relative humidity, higher freezing levels, and evidence of limited horizontal convergence near the terrain at low levels that likely suppressed deep convective growth. Here, we also present evidence from the radiosonde and satellite measurements that flow–terrain interactions may yield gravity wave activity that affects CI outcome.

54 ENVIRONMENTAL SCIENCES↗

Differential patterns of reproductive and lifestyle risk factors for breast cancer according to birth cohorts among women in China, Japan and Korea

Background: The birth cohort effect has been suggested to influence the rate of breast cancer incidence and the trends of associated reproductive and lifestyle factors. We conducted a cohort study to determine whether a differential pattern of associations exists between certain factors and breast cancer risk based on birth cohorts. Methods: This was a cohort study using pooled data from 12 cohort studies. We analysed associations between reproductive (menarche age, menopause age, parity and age at first delivery) and lifestyle (smoking and alcohol consumption) factors and breast cancer risk. We obtained hazard ratios (HRs) with 95% confidence intervals (CIs) using the Cox proportional hazard regression analysis on the 1920s, 1930s, 1940s and 1950s birth cohorts. Results: Parity was found to lower the risk of breast cancer in the older but not in the younger birth cohort, whereas lifestyle factors showed associations with breast cancer risk only among the participants born in the 1950s. In the younger birth cohort group, the effect size was lower for parous women compared to the other cohort groups (HR [95% CI] 0.86 [0.66–1.13] compared to 0.60 [0.49–0.73], 0.46 [0.38–0.56] and 0.62 [0.51–0.77]). Meanwhile, a higher effect size was found for smoking (1.45 [1.14–1.84] compared to 1.25 [0.99–1.58], 1.06 [0.85–1.32] and 0.86 [0.69–1.08]) and alcohol consumption (1.22 [1.01–1.48] compared to 1.10 [0.90–1.33], 1.15 [0.96–1.38], and 1.07 [0.91–1.26]). Conclusion: We observed different associations of parity, smoking and alcohol consumption with breast cancer risk across various birth cohorts.

60 APPLIED LIFE SCIENCES↗

The Cross-sectional and Longitudinal Association Between Thyroid Function and Depression: A Population-Based Study

Abstract Context An association of thyroid function with mood disorders has been widely suggested, but very few studies have examined this association longitudinally. Objective We assessed the cross-sectional and longitudinal association between thyroid function and depression in a population-based cohort. Methods A total of 9471 individuals were included in cross-sectional analyses, of whom 8366 had longitudinal data. At baseline, we assessed thyroid function using serum samples (thyrotropin [TSH], free thyroxine (FT4), and thyroid peroxidase antibodies) and depressive symptoms using the Centre for Epidemiologic Studies Depression (CES-D) scale. Incident depressive events (n = 1366) were continuously followed up with the CES-D and clinical interviews. We analyzed the cross-sectional association of thyroid function and thyroid disease with depressive symptoms using linear and logistic regression, and the longitudinal association with Cox proportional hazard models for depressive events. Results Lower TSH levels and lower and higher FT4 levels were cross-sectionally associated with more depressive symptoms with a B value of −0.07 per 1 unit increase of natural log-transformed TSH (95% CI −0.11; −0.04). Furthermore, hypothyroidism was cross-sectionally associated with less depressive symptoms and hyperthyroidism with more depressive symptoms. Longitudinally, there was a U-shaped association between FT4 and incident depressive events but only in euthyroid participants. Conclusion We show a cross-sectional association between thyroid (dys)function with depressive symptoms, and a U-shaped association between FT4 and incident depressive events in euthyroid individuals. Our findings suggest an association of thyroid function with the risk of developing depression, albeit small. Reverse causation and additional underlying factors may also contribute to the association.

Roa Dueñas, Oscar Hernando (ORCID:0000000207522261↗

Graphene SHDMC Data

The data used to produce all of the figures and tables in the manuscript titled "Highly Accurate Many-Body Theory Reaches 2D Materials" can be found here. This data set includes: -SHDMC results for graphene -selected CI with and without re-normalized second-order perturbation (rPT2) theory corrections for graphene -data demonstrating that SHDMC displays an exponential rate of convergence -data used for sCI + rPT2 complete basis set extrapolation -data used to extrapolate SHDMC energies to the infinite basis limit -data used to demonstrate compactness of SHDMC wavefunction

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗

Investigating effects of soil chemicals on density of small mammal bioindicators using spatial capture-recapture models

Monitoring the ecological impacts of environmental pollution and the effectiveness of remediation efforts requires identifying relationships between contaminants and the disruption of biological processes in populations, communities, or ecosystems. Wildlife are useful bioindicators, but traditional comparative experimental approaches rely on a staunch and typically unverifiable assumption that, in the absence of contaminants, reference and contaminated sites would support the same densities of bioindicators, thereby inferring direct causation from indirect data. We demonstrate the utility of spatial capture-recapture (SCR) models for overcoming these issues, testing if community density of common small mammal bioindicators was directly influenced by soil chemical concentrations. By modeling density as an inhomogeneous Poisson point process, we found evidence for an inverse spatial relationship between Peromyscus density and soil mercury concentrations, but not other chemicals, such as polychlorinated biphenyls, at a site formerly occupied by a nuclear reactor. Although the coefficient point estimate supported Peromyscus density being lower where mercury concentrations were higher (β = –0.44), the 95% confidence interval overlapped zero, suggesting no effect was also compatible with our data. Estimated density from the most parsimonious model (2.88 mice/ha; 95% CI = 1.63–5.08), which did not support a density-chemical relationship, was within the range of reported densities for Peromyscus that did not inhabit contaminated sites elsewhere. Environmental pollution remains a global threat to biodiversity and ecosystem and human health, and our study provides an illustrative example of the utility of SCR models for investigating the effects that chemicals may have on wildlife bioindicator populations and communities.

36 MATERIALS SCIENCE↗

Leaf gas exchange, leaf water potential and spectral reflectance, BIONTE, Brazil, 2023

Leaf traits measured at the top of the canopy on 30 tree species in the BIONTE experimental forest, near Manaus, Brazil, at three time points during August to November, 2023. The aim of this study was to test the relationship between leaf water use efficiency and wood density. Leaf gas exchange was measured on top-of-canopy leaves accessed by an articulated boom lift. Response curves (A-Ci and A-Q), and dark adapted respiration were measured on cut branches. Survey gas exchange measurements were performed on attached leaves at various times during the day. Following gas exchange, leaves were harvested, and measured for leaf water potential and spectral reflectance. Data in this data package is presented in csv files, with metadata in csv and descriptive experimental protocols as pdf. Gas exchange data and metadata meets the requirements of the ESS-DIVE reporting format for leaf-level gas exchange data and metadata.

54 ENVIRONMENTAL SCIENCES↗

PARETO 0.3.0 Release

PARETO 0.3.0 Release. Highlights: - Fixing Warning in get_data - Clean up of old main function which has been replaced by the run files - Adding plot_scatter() function - Support node capacity - Add Gurobi troubleshooting files to gitignore by @melody-shellman - Set slacks to zero - Water treatment case study - Fix defaultvalue treatement - Fix bug for incorrect number of input arguments in water quality - Pipeline configs documentation - Enable rendering Unicode characters in ReadTheDocs PDF builds - Adding support for units - Add discrete water quality to the model - Updating documentation for strategic model, and corresponding fixes to strategic model - Rework getting started docs build section and more - Enable Codecov reports in CI builds - Correct error in CompletionsPadSupplyBalanceRule

PARETO,PSE,Process Systems Engineering,Produced wa↗