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At least 91 records · Page 5

Spatial and temporal overlap between hatchery- and natural-origin steelhead and Chinook Salmon during spawning in the Klickitat River, Washington, USA

Abstract Objective A goal of many segregated salmonid hatchery programs is to minimize potential interbreeding between hatchery- and natural-origin fish. Our objective was to assess this on the Klickitat River, Washington, USA. Methods We used radiotelemetry to evaluate spatiotemporal spawning overlap between hatchery- and natural-origin steelhead Oncorhynchus mykiss and spring Chinook Salmon O. tshawytscha. We estimated percentages of tagged fish that spawned naturally in the Klickitat River subbasin, emigrated from the Klickitat River, or died before spawning. A kernel density analysis was used to estimate probability of spatiotemporal overlap between hatchery- and natural-origin spawners. Result For steelhead, 12% of hatchery-origin and 50% of natural-origin fish spawned naturally. For spring Chinook Salmon, 18% of hatchery-origin and 44% of natural-origin fish spawned naturally. Tag loss may result in underestimates in these percentages. Most hatchery-origin steelhead (90%) spawned downstream of river kilometer (rkm) 32, and 75% spawned from November to mid-March. The majority of natural-origin steelhead (64%) spawned upstream of rkm 32, and 75% spawned from mid-March to late May. Spawn timing of hatchery-origin Chinook Salmon (early August to mid-September) overlapped with that of natural-origin Chinook Salmon (late July to late September), and fish of both origins spawned in the same 30-km reach of the river. We estimated the percentage of hatchery-origin spawners (pHOS) on the natural spawning grounds to be 12% for steelhead and 40% for spring Chinook Salmon across all study years. For steelhead, we estimated the overlap probability to be 25% (95% CI = 22.5–28%). For spring Chinook Salmon, tight spatial clustering of hatchery-origin fish resulted in a lower overlap estimate of 21% (13–31%). Conclusion We suggest adjusting pHOS estimates using these overlap estimates or similar spatiotemporal data on actual spawner proximity and possible interactions, and that these types of analyses be used in conjunction with gene flow analysis to accurately evaluate effects of individual hatchery programs.

Zendt, Joseph S.↗

Quantifying soil organic matter stock distribution and origin following over a century of maize-based cropping in the former tallgrass prairie region of central USA

Tallgrass prairie conversion to maize-based agriculture in central North America has resulted in substantial loss of soil organic carbon (SOC) in less than two centuries. However, evaluations of how management practices may mitigate SOC losses are generally limited in soil depth and/or duration, missing long-term SOC stock outcomes that manifest over timescales of decades or longer. To address this, we sampled soils in year 145 of the Morrow Plots experiment to (i) evaluate effects of crop rotation and fertility management on SOC stocks and (ii) distinguish prairie- versus maize-derived SOC after continuous maize cropping since 1876 using stable carbon isotope ( 13 C) natural abundance. Soil organic carbon stock by equivalent soil mass (ESM) was + 30.7 Mg C ha −1 (+31.7 %) higher under maize-oat-alfalfa than continuous maize, but similar between maize-soybean and continuous maize. NPK fertilization and manuring did not influence SOC stocks by ESM. Response of SOC stocks at 15 cm depth intervals to NPK fertilization varied by depth and crop rotation, with lower SOC stocks at 30–45 cm under continuous maize and maize-soybean. Maize-derived C ranged 19.5–59.6 % of SOC stock across depths, indicating the majority of SOC was still derived from tallgrass prairie even after 145 years of continuous maize cropping. Our results confirm the potential of diversified crop rotation for minimizing SOC losses relative to tallgrass prairie at the supracentennial scale, and highlight the importance of relic prairie soil organic matter for future crop production in central North America.

crop rotation↗

Establishing nationwide power system vulnerability index across US counties using interpretable machine learning

Power outages have become increasingly frequent, intense, and prolonged in the US due to climate change, aging electrical grids, and rising energy demand. However, largely due to the absence of granular spatiotemporal outage data, we lack data-driven evidence and analytics-based metrics to quantify power system vulnerability. This limitation has hindered the ability to effectively evaluate and address vulnerability to power outages in US communities. Here, in this work, we collected ∼179 million power outage records at 15-min intervals across 3022 US contiguous counties (96.15 % of the area) from 2014 to 2023. We developed a power system vulnerability assessment framework based on three dimensions (intensity, frequency, and duration) and applied interpretable machine learning models (XGBoost and SHAP) to compute Power System Vulnerability Index (PSVI) at the county level. Our analysis reveals a consistent increase in power system vulnerability across the US counties over the past decade. We identified 318 counties across 45 states as hotspots for high power system vulnerability, particularly in the West Coast (California and Washington), the East Coast (Florida and the Northeast area), the Great Lakes megalopolis (Chicago-Detroit metropolitan areas), and the Gulf of Mexico (Texas). Our heterogeneity analysis indicates that urban counties and those located along regional transmission boundaries tend to exhibit significantly higher vulnerability. Our results highlight the significance of the proposed PSVI for evaluating the vulnerability of communities to power outages. The findings underscore the widespread and pervasive impact of power outages across the country and offer crucial insights to support infrastructure operators, policymakers, and emergency managers in formulating policies and programs aimed at enhancing the resilience of the US power infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Simultaneous inhibition of ATM, ATR, and DNA-PK causes synergistic lethality

Here, in this paper, we report that simultaneous inhibition of the three primary DNA damage recognition PI3 kinase-like kinases (PIKKs) —ATM, ATR, and DNA-PK— induces severe combinatorial synthetic lethality in mammalian cells. Utilizing Chinese hamster cell lines CHO and V79 and their respective PIKK mutants, we evaluated effects of inhibiting these three kinases on cell viability, DNA damage response, and chromosomal integrity. Our results demonstrate that while single or dual kinase inhibition increased cytotoxicity, inhibition of all three PIKKs results in significantly higher synergistic lethality, chromosomal aberrations, and DNA double-strand break (DSB) induction as calculated by their synergy scores. These findings suggest that the overlapping redundancy of ATM, ATR, and DNA-PK functions is critical for cell survival, and their combined inhibition greatly disrupts DNA damage signaling and repair processes, leading to cell death. This study provides insights into the potential of multi-targeted DDR kinase inhibition as an effective anticancer strategy, necessitating further research to elucidate underlying mechanisms and therapeutic applications.

59 BASIC BIOLOGICAL SCIENCES↗

Revisiting a minimally destructive analytic approach for determining electrochemical kinetic parameters: Measuring aluminum corrosion across a wide pH range based on the Butler-Volmer equation

Here, this study revisits the three-point sampling of the simplified Butler-Volmer equation to address the limitations of strong potentiodynamic polarization, which can introduce irreversible damage and uncertainty in corrosion analysis. The method extracts electrochemical kinetic parameters while minimizing polarization effects, evaluates noise sensitivity relative to overpotential, and accounts for errors from signal noise, OCP drift, ohmic resistance, and mass-transfer constraints. Verified against the Tafel extrapolation method for aluminum corrosion across a wide pH range, this low-polarization approach enables accurate evaluations with specific error estimates, offering a robust alternative to linear polarization resistance methods that assume constant Tafel slopes.

36 MATERIALS SCIENCE↗

Economic dispatch of offshore renewable energy resources for islanded communities with optimal storage sizing

Coastal or isolated microgrids depend on diesel generators and could benefit from renewable energy resources, especially offshore wind and wave energy. Integrating these resources into microgrids is complicated by their high intermittency, which requires optimal economic dispatch to effectively evaluate. This study considers three coastal or islanded sites, and uses mid-fidelity models of wind and wave energy technologies, and local demand data to solve the optimal economic dispatch problem. An optimal storage sizing method is developed that finds the smallest capacity of energy storage required to meet the microgrid load during each season. The storage capacity decreases by a factor of two at most when adding wave energy converters to a system. Adding wave energy converters to a farm decreases cost by about 30%. Furthermore, the required storage size varies by two to three times from summer to winter. Compared with the state-of-the-art approaches that often overlook realistic offshore renewable energy technology in microgrid economic dispatch and optimal storage sizing, the proposed solution introduced in this study allows for better site selection, microgrid design, converter selection, and storage sizing considerations for isolated microgrids.

16 TIDAL AND WAVE POWER↗

Microstructural and nanomechanical studies of PVD Cr coatings on SiC for LWR fuel cladding applications

The microstructure and nanomechanical properties of pure Cr coatings deposited on SiC with various physical vapor deposition (PVD) methods have been investigated for the mitigation of hydrothermal corrosion of SiC-SiC f (SiC fiber-reinforced SiC matrix) composite fuel cladding in light water reactors (LWR). Cr coatings (4–7 μm thick) were deposited on unbiased SiC substrates using six variants of magnetron sputtering processes: (i) standard (S-DCMS), (ii) pulsed (P-DCMS), (iii) ion-assisted (I-DCMS), and (iv) pulsed ion-assisted direct current magnetron sputtering (PI-DCMS), (v) high-power impulse magnetron sputtering (HiPIMS), and (vi) bipolar HiPIMS (B-HiPIMS). Microstructural characterization and nanoindentation testing were used to evaluate effects of deposition technique on coating microstructure and nanomechanical properties. The application of positive reverse pulses to the sputter target induced coarsening of the columnar grain structure, while ion bombardment of substrates during deposition promoted densification of the coating microstructure. Both effects are exemplified in B-HiPIMS deposition, resulting in a high-density microstructure with compressive residual stress. Material pile-up around nano-indents and plastic work during nanoindentation were analyzed to understand deformation behavior of the coatings. Finally, the results suggest the B-HiPIMS process to be among the promising methods for the deposition of Cr coatings on SiC-SiC f for LWR cladding application.

36 MATERIALS SCIENCE↗

Proteomic Characterization of Damaged Single Hairs Recovered after an Explosion for Protein-Based Human Identification

Evidence recovery is challenging where an explosion has occurred. Though hair evidence may be sufficiently robust to be recovered at the site, forensic analysis underutilizes the matrix by relying on morphological analysis. Where DNA is compromised, particularly in hair, protein-based human identification presents a promising alternative. Detection of amino acid polymorphisms in hair proteins as genetically variant peptides (GVPs) permits the inference of individualizing single nucleotide polymorphisms for identification. However, an explosive blast may damage hair proteins and compromise GVP identification. This work evaluates effects of an explosive blast on the hair proteome and GVP identification, investigates microscopy as a predictor of proteome profiling success in recovered hairs to improve analysis throughput, and quantifies discriminative power in damaged hairs. The proteomics dataset has been deposited into the ProteomeXchange Consortium (PXD017427). With the exception of degradation in keratins K75, K80, K40, and keratin-associated protein KAP10-11 as markers of hair cuticular damage, corroborated by scanning electron microscopic analysis, minimal hair proteome degradation following explosion allowed successful proteome profiling of single hairs regardless of morphological damage. Finally, GVP identification remained independent of explosion conditions, permitting similar discriminative power between exploded and undamaged hairs. These findings lend greater confidence to GVP analysis in one-inch hairs for forensic identification and provide information about hair protein localization.

59 BASIC BIOLOGICAL SCIENCES↗

Design improvements for a recirculating reactor: Enhanced temperature measurement and sample-isolated reactivity in steady-state kinetic studies

Building upon a previous recirculating reactor design [S.A. Tenney, K. Xie, J.R. Monnier, A. Rodriguez, R.P. Galhenage, S. Audrey, D.A. Chen, Rev. Sci. Instrum. 84, 104101 (2013)], we present significant improvements that address key limitations in steady-state kinetic measurements for heterogeneous catalysis. The enhanced reactor design features direct sample heating with a focused IR lamp and temperature measurement in direct contact with the sample, enabling more accurate temperature control and improved kinetic analysis. A critical advancement is the isolation of sample reactivity from reactor wall contributions, ensuring that only the sample contributes to measured reaction rates. This was a limitation in earlier designs where the entire reactor contributed to the observed reactivity. The system incorporates a bypass flow cell for direct comparison with powder catalysts under identical conditions using a standard plug-flow reactor configuration. We demonstrate these capabilities through CO oxidation experiments on Pt(111) single crystals and graphene-passivated Pt(111), highlighting the system's ability to differentiate catalytic activity in model systems and directly compare them with high surface area powder catalysts. This reactor is particularly suited for thin films and low surface area catalysts that are not effectively evaluated in traditional flow reactors, especially for samples with low numbers of active sites or slow reaction rates.

36 MATERIALS SCIENCE↗

Digital holography for real-time non-invasive monitoring of larval fish at power plant intakes

Effective evaluation of technological and operational approaches to reduce entrainment of marine organisms at cooling water intake structures (CWIS) requires accurate organism-sensing systems. Current detection methods lead to large temporal data gaps, require tedious manual analysis, and are fatal to organisms. In this report we describe integrating deep learning with a non-lethal, non-intrusive imaging method—digital holography—to rapidly detect fish larvae. Laboratory experiments demonstrated that the instrument could successfully image fish larvae at flow rates exceeding ranges seen in CWIS. Holograms of two fish larvae species, in the presence of bubbles and detritus, were collected to build a large database for training a lightweight convolutional neural network. The model achieves 97% extraction accuracy in quantifying larvae, and distinguishing them from other particles, including detritus and bubbles, when applied to a dataset of manually classified images, exceeding previous metrics for non-lethal, accurate, and real-time detection. These results demonstrate the potential of in situ holographic imaging for monitoring endangered larval fish species at power plant intake structures, and for high-fidelity, real-time applications in monitoring aquatic ichthyoplankton.

endangered species↗

Urbanization-induced land and aerosol impacts on storm propagation and hail characteristics

Changes in land surface and aerosol characteristics from urbanization can affect dynamic and microphysical properties of severe storms, thus affecting hazardous weather events resulting from such storms such as hail and tornado. We examine the joint and individual effects of urban land and anthropogenic aerosols of Kansas City on a severe convective storm observed during the 2015 Plains Elevated Convection At Night (PECAN) field campaign, focusing on storm evolution, convective intensity, and hail characteristics. The simulations are carried out at the cloud-resolving scale (1 km) using a version of WRF-Chem in which the spectral-bin microphysics (SBM) is coupled with the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC). It is found that the urban land effect of Kansas City initiated a much stronger convective cell and the storm got further intensified when interacting with stronger turbulence induced by the urban land. The urban land effect also changed the storm path by diverting the storm toward the city mainly resulting from enhanced urban land-induced convergence in the urban area and around the urban-rural boundaries. The joint effect of urban land and anthropogenic aerosols enhances occurrences of both severe hail and significant severe hail by ~ 20% by enhancing hail formation and growth from riming. Overall the urban land effect on convective intensity and hail is relatively larger than the anthropogenic aerosol effect, but the joint effect is much notable than either of the individual effects, emphasizing the importance to consider both effects in evaluating urbanization effects.

Lin, Yun↗

Performance Assessments of Demand Flexibility from Grid-Interactive Efficient Buildings: Issues and Considerations

This SEE Action Network report explains basic concepts and fundamental considerations for assessing the actual demand flexibility performance of buildings participating in demand flexibility programs and responding to time-varying retail rates. Demand flexibility is the capability of distributed energy resources (DERs) to adjust a building’s load profile across different timescales. Assessments determine the timing, location, quantity, and quality of grid services provided. The results can be used for financial settlements and to improve performance of demand flexibility, support its consideration in resource potential studies and electricity system planning, and contribute to cost-effectiveness evaluations. While practitioners and regulators regularly find opportunities to improve performance assessments of demand-related services, to a large degree current best practices are sufficient for basic service offerings as demand flexibility is implemented today. However, advances in assessment practices will be required in a future with grid-interactive efficient buildings (GEBs) that provide continuous demand flexibility by integrating multiple DERs and flexibility modes (load shed, load shift, modulate, and generate). Example practices include using new baseline constructs—including whether baselines are even required for certain building flexibility modes or configurations, deploying more advanced metering and analytics, further developing cybersecurity standards, improving communication standards for increased interoperability, and establishing performance metrics and assessment procedures for load modulation as it is more fully defined and implemented. This report provides information on prioritizing and designing performance assessment elements for demand flexibility programs and time-varying retail rates, assessment protocols, and research and development needs. Additional research sponsored by DOE’s Building Technologies Office offers more detailed technical information on assessing performance of demand flexibility, including definition of performance metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SAVY-4000 Finite-Element Drop Test Analysis

PFE Auxiliary Systems conducted drop testing on SAVY-4000 containers to evaluate structural response under 12-foot drop conditions. In support of that effort, a finite-element modeling capability was developed to simulate drop response across multiple container sizes and impact orientations. The purpose of this work was to provide a consistent analysis framework that could support interpretation of testing, compare response trends across multiple configurations, and generate quantities of interest for later comparison with experimental data. More broadly, the analysis and testing were intended to assess whether the containers continued to perform their primary function after a 12-foot drop, namely maintaining structural integrity and containment of the contents. The modeling approach combined an implicit preload analysis with an explicit drop simulation so that each drop event began from a mechanically realistic assembled condition, including compression of the silicone O-ring. Separate models were developed for 2-quart, 5-quart, 12-quart, and 10-gallon containers. The results were evaluated in terms of strain-gauge response, collar-lid gap behavior, and accumulated plastic strain. In addition, parametric studies were performed on the 2-quart container to assess sensitivity to O-ring stiffness, friction, canister thickness, geometry tolerance, and mesh density. The simulations showed that predicted drop responses depended strongly on both container size and drop orientation. Gap metrics identified cases in which the predicted collar-lid opening exceeded the nominal O-ring cross-section threshold, while plastic strain metrics identified localized regions of elevated permanent deformation. Parametric studies showed that the predicted response was especially sensitive to the assumed O-ring stiffness and contact friction, while the geometry tolerance study produced smaller changes in the cases examined. The main value of this work was that it established a repeatable modeling and simulation workflow to support drop-test implementation, evaluate effects of future configuration changes, and understand modeling assumptions that most influenced predicted response. At the current stage, the results were viewed as preliminary model predictions rather than validated predictions. The next step would be to compare drop-test data to the model so that predictive values of the workflow could be refined and used with greater confidence to assess whether the containers maintained structural integrity and containment of the contents after a 12-foot drop.

42 ENGINEERING↗

Spatial–Temporal Patterns of Historical, Near-Term, and Projected Drought in the Conterminous United States

Major droughts in the United States have heavily impacted the hydrologic system, negatively effecting energy and food production. Improved understanding of historical drought is critical for accurate forecasts. Data from global climate models (GCMs), commonly used to assess drought, cannot effectively evaluate local patterns because of their low spatial scale. This research leverages downscaled (~4 km grid spacing) temperature and precipitation estimates from nine GCMs’ data under the business-as-usual scenario (Representative Concentration Pathway 8.5) to examine drought patterns. Drought severity is estimated using the Palmer Drought Severity Index (PDSI) with the Thornthwaite evapotranspiration method. The specific objectives were (1) To reproduce historical (1966–2005) drought and calculate near-term to future (2011–2050) drought patterns over the conterminous USA. (2) To uncover the local variability of spatial drought patterns in California between 2012 and 2018 using a network-based approach. Our estimates of land proportions affected by drought agree with the known historical drought events of the mid-1960s, late 1970s to early 1980s, early 2000s, and between 2012 and 2015. Network analysis showed heterogeneity in spatial drought patterns in California, indicating local variability of drought occurrence. The high spatial scale at which the analysis was performed allowed us to uncover significant local differences in drought patterns. This is critical for highlighting possible weak systems that could inform adaptation strategies such as in the energy and agricultural sectors.

54 ENVIRONMENTAL SCIENCES↗

A Modeling-Based Flammable Risk Treatment of Refrigerant Leakage from a Commercial R-290 Refrigeration Machine

Because of serious concerns about global warming, manufacturers have started phasing out high global warming potential (GWP) refrigerants in commercial refrigeration equipment (e.g., R-134a). As a potential replacement, propane (R-290) is an environmentally friendly refrigerant for commercial refrigeration equipment because its GWP is only three. However, propane is flammable and is therefore classified as a Class A3 refrigerant per ASHRAE Standards, so safety is a very important consideration when propane-based equipment is designed and deployed in buildings. In the event of a refrigerant leak, flammability of the refrigerant depends on the refrigerant’s local concentration, which is highly affected by the indoor air environment, including temperature and air flow. In this study, a ventilation system attached to a commercial R-290 refrigeration device was designed to eliminate the flammability risk. Moreover, a computational fluid dynamics (CFD) model was developed to investigate the refrigerant leak, thereby evaluating effects of the ventilation system. The CFD model can visualize the flammable zones owing to the leak.

42 ENGINEERING↗

NLR Core Modeling & Decision Support Capabilities: FASTSim, RouteE, T3CO & OpenPATH

This project is part of the program area to develop and improve core capabilities for the Energy-Efficient Mobility Systems (EEMS) program that enable research, development and deployment of advanced mobility solutions and enhance the EEMS Program's ability to address system-level transportation challenges. Advancements to the Future Automotive Systems Technology Simulator (FASTSim), Route Energy Prediction Model (RouteE), Transportation Technology Total Cost of Ownership (T3CO) and Open Platform for Agile Trip Heuristics (OpenPATH) core capabilities under this project supports the overall EEMS Program goals to effectively evaluate energy and mobility impacts of future transportation technologies and services, and to identify the most promising pathways to reduce transportation costs and environmental harms, and to improve mobility access. This presentation was prepared for the 2026 Annual Merit Review of this project.

33 ADVANCED PROPULSION SYSTEMS↗

Targeted alpha therapy in a systemic mouse model of prostate cancer - a feasibility study

225 Ac-PSMA-617 targeted-therapy has demonstrated efficacy in 75-85% of patients; however, responses are not durable. We aimed to establish translatable mouse models of disseminated prostate cancer (PCa) to evaluate effectiveness of 225 Ac-PSMA-617 at various disease stages. Methods: C4-2, C4-2B, or 22Rv1 cells were injected into the left ventricle of male NSG mice. Disease progression was monitored using bioluminescence imaging (BLI). For treatment, mice were injected with 40 kBq 225 Ac-PSMA-617 at one (early treatment cohort) or three weeks (late treatment cohort) post-inoculation. Treatment efficacy was monitored by BLI of whole-body tumor burden. Mice were sacrificed based on body conditioning score. Results: C4-2 cells yielded metastases in liver, lungs, spleen, stomach, bones, and brain - achieving a clinically relevant model of widespread metastatic disease. The disease burden in the early treatment cohort was stable over 27 weeks in 5/9 mice and progressive in 4/9 mice. These mice were sacrificed due to brain metastases. Median survival of the late treatment cohort was superior to controls (13 vs. 7 weeks; p<0.0001) but inferior to that in the early treatment cohort (13 vs. 27 weeks; p<0.001). Late cohort mice succumbed to extensive liver involvement. The 22Rv1 and C4-2B systemic models were not used for treatment due to high kidney metastatic burden or low take rate, respectively. Conclusion: C4-2 cells reproduced metastatic cancer spread most relevantly. Early treatment with 225 Ac-PSMA-617 prevented liver metastases and led to significant survival benefit. Late treatment improved survival without reducing tumor burden in the liver, the main site of metastasis. The current findings suggest that early 225 Ac-PSMA-617 intervention is more efficacious in the setting of widespread metastatic PCa.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Solar Farm’s Microclimates Effects: Predicting Abundance and Visiting Frequency of Pollinators

The solar farm is garnering attention for its contribution to ecosystem services, particularly in supporting pollinators. Although numerous studies have focused on the distinct microclimates of solar farms, there has been limited effort to validate and model the impact of these conditions on insects [1]. To effectively evaluate and leverage the ecosystem services from solar farms in policymaking, understanding how insects react to microclimate variations in diverse designs and management methods is essential. This study aims to validate and model the impact of temperature and shade at solar farms on pollinator populations and their frequency of pollination as well as compare the potential for increased pollination under different types of panels within a solar grazing setup.

Chung, Hyun Yong↗